Search

Abstract Genetic studies have identified the voltage‐gated sodium channel 1.7 (Nav1.7) as pain target. Due to the ineffectiveness of small molecules and monoclonal antibodies as therapeutics for pain, single‐domain antibodies (VHHs) are developed against the human Nav1.7 (hNav1.7) using a novel antigen presentation strategy. A 70 amino‐acid peptide from the hNav1.7 protein is identified as a target antigen. A recombinant version of this peptide is grafted into the complementarity determining region 3 (CDR3) loop of an inert VHH in order to maintain the native 3D conformation of the peptide. This antigen is used to isolate one VHH able to i) bind hNav1.7, ii) slow the deactivation of hNav1.7, iii) reduce the ability of eliciting action potentials in nociceptors, and iv) reverse hyperalgesia in in vivo rat and mouse models. This VHH exhibits the potential to be developed as a therapeutic capable of suppressing pain. This novel antigen presentation strategy can be applied to develop biologics against other difficult targets such as ion channels, transporters and GPCRs.

Abstract Bacteria are becoming increasingly resistant to antibiotics, reducing our ability to treat infections and threatening to undermine modern health care. Optimising antibiotic use is a key element in tackling the problem. Traditional economic evaluation methods do not capture many of the benefits from improved antibiotic use and the potential impact on resistance. Not capturing these benefits is a major obstacle to optimising antibiotic use, as it fails to incentivise the development and use of interventions to optimise the use of antibiotics and preserve their effectiveness (stewardship interventions). Estimates of the benefits of improving antibiotic use involve considerable uncertainty as they depend on the evolution of resistance and associated health outcomes and costs. Here we discuss how economic evaluation methods might be adapted, in the face of such uncertainties. We propose a threshold-based approach that estimates the minimum resistance-related costs that would need to be averted by an intervention to make it cost-effective. If it is probable that without the intervention costs will exceed the threshold then the intervention should be deemed cost-effective.

Abstract Background Prior to September 2021, 55,000–90,000 hospital inpatients in England were identified as having a potentially nosocomial SARS-CoV-2 infection. This includes cases that were likely missed due to pauci- or asymptomatic infection. Further, high numbers of healthcare workers (HCWs) are thought to have been infected, and there is evidence that some of these cases may also have been nosocomially linked, with both HCW to HCW and patient to HCW transmission being reported. From the start of the SARS-CoV-2 pandemic interventions in hospitals such as testing patients on admission and universal mask wearing were introduced to stop spread within and between patient and HCW populations, the effectiveness of which are largely unknown. Materials/methods Using an individual-based model of within-hospital transmission, we estimated the contribution of individual interventions (together and in combination) to the effectiveness of the overall package of interventions implemented in English hospitals during the COVID-19 pandemic. A panel of experts in infection prevention and control informed intervention choice and helped ensure the model reflected implementation in practice. Model parameters and associated uncertainty were derived using national and local data, literature review and formal elicitation of expert opinion. We simulated scenarios to explore how many nosocomial infections might have been seen in patients and HCWs if interventions had not been implemented. We simulated the time period from March-2020 to July-2022 encompassing different strains and multiple doses of vaccination. Results Modelling results suggest that in a scenario without inpatient testing, infection prevention and control measures, and reductions in occupancy and visitors, the number of patients developing a nosocomial SARS-CoV-2 infection could have been twice as high over the course of the pandemic, and over 600,000 HCWs could have been infected in the first wave alone. Isolation of symptomatic HCWs and universal masking by HCWs were the most effective interventions for preventing infections in both patient and HCW populations. Model findings suggest that collectively the interventions introduced over the SARS-CoV-2 pandemic in England averted 400,000 (240,000 – 500,000) infections in inpatients and 410,000 (370,000 – 450,000) HCW infections. Conclusions Interventions to reduce the spread of nosocomial infections have varying impact, but the package of interventions implemented in England significantly reduced nosocomial transmission to both patients and HCWs over the SARS-CoV-2 pandemic.

Summary: Background: The Narrative Experiences Online (NEON) Intervention provides self-managed web-based access to mental health recovery narratives (n = 659). We evaluated effectiveness and cost-effectiveness in improving quality of life for adults resident in England with mental health problems and recent psychosis experience. Methods: Prospectively registered pragmatic parallel-group randomised trial controlling for usual care, recruiting from statutory mental health services and through community engagement activities, with a 52-week primary endpoint (ISRCTN11152837). All trial procedures and the NEON Intervention were delivered by an integrated web-application. Randomisation was through an independently generated list (no stratification). Allocation was masked for statistical staff and the Chief Investigator but not participants. Intervention arm participants received immediate NEON Intervention access. Control arm participants received access after completing primary endpoint questionnaires. The primary outcome was quality of life through the Manchester Short Assessment (MANSA). Serious Adverse Events (SAEs) were collected through web-based safety report forms and identified from health service usage data. The primary analysis was by a prospectively described Intention To Treat principle excluding participants who had registered multiple times, with multiple imputation for missing data. Findings: Between 9 March 2020 and 1 March 2021, 739 participants were randomised (intervention:370; control: 369), providing more than 90% power to detect a baseline-adjusted difference of 0.25 in the MANSA score. Mean age was 34.8 years (standard deviation (SD) 12.0), 561 (75.9%) were white British, 443 (59.9%) were female, 609 (82.4%) had accessed specialist care mental health services, and 698 (94.5%) had accessed primary care mental health services. Mean baseline MANSA score was 3.7 for control and intervention arms (SD 0.9 and 1.0). 565 (76.5%) participants provided primary endpoint MANSA data with a mean score of 4.1 (SD 1.0) for both arms. We found no significant difference in Quality of Life between the two arms at the primary endpoint (baseline-adjusted difference 0.07, 95% CI −0.07 to 0.21, p = 0.35). The incremental cost-effectiveness ratio (£110,501 per quality-adjusted life-year (QALY)) exceeded the prospectively defined cost-effectiveness threshold (£30,000 per QALY). 158 (42.8%) control arm and 194 (52.4%) intervention arm participants accessed narratives outside of the NEON Intervention. There were no related serious adverse events (SAEs). 116 unrelated SAEs were reported by control arm participants, and 107 by intervention arm participants. Interpretation: Our findings do not indicate NEON Intervention access for all people with psychosis experience. Future research should consider a) evaluation with current mental health services users; b) optimisation to enable users to find hope-promoting narratives. Funding: National Institute for Health and Care Research (NIHR).

Abstract Background Asymptomatic SARS-CoV-2 testing of hospitalised patients began in April-2020, with twice weekly healthcare worker (HCW) testing introduced in November-2020. Guidance recommending asymptomatic testing was withdrawn in August-2022. Assessing the impact of this decision from data alone is challenging due to concurrent changes in infection prevention and control practices, community transmission rates, and a reduction in ascertainment rate from reduced testing. Computational modelling is an effective tool for estimating the impact of this change. Methods Using a computational model of SARS-CoV-2 transmission in an English hospital we estimate the effectiveness of several asymptomatic testing strategies, namely; (1) Symptomatic testing of patients and HCWs, (2) testing of all patients on admission with/without repeat testing on days 3 and 5–7, and (3) symptomatic testing plus twice weekly asymptomatic HCW testing with 70% compliance. We estimate the number of patient and HCW infections, HCW absences, number of tests, and tests per case averted or absence avoided, with differing community prevalence rates over a 12-week period. Results Testing asymptomatic patients on admission reduces the rate of nosocomial SARS-CoV-2 infection by 8.1–21.5%. Additional testing at days 3 and 5–7 post admission does not significantly reduce infection rates. Twice weekly asymptomatic HCW testing can reduce the proportion of HCWs infected by 1.0-4.4% and monthly absences by 0.4–0.8%. Testing asymptomatic patients repeatedly requires up to 5.5 million patient tests over the period, and twice weekly asymptomatic HCW testing increases the total tests to almost 30 million. The most efficient patient testing strategy (in terms of tests required to prevent a single patient infection) was testing asymptomatic patients on admission across all prevalence levels. The least efficient was repeated testing of patients with twice weekly asymptomatic HCW testing in a low prevalence scenario, and in all other prevalence levels symptomatic patient testing with regular HCW testing was least efficient. Conclusions Testing patients on admission can reduce the rate of nosocomial SARS-CoV-2 infection but there is little benefit of additional post-admission testing. Asymptomatic HCW testing has little incremental benefit for reducing patient cases at low prevalence but has a potential role at higher prevalence or with low community transmission. A full health-economic evaluation is required to determine the cost-effectiveness of these strategies.

Abstract Background There is evidence that during the COVID pandemic, a number of patient and HCW infections were nosocomial. Various measures were put in place to try to reduce these infections including developing asymptomatic PCR (polymerase chain reaction) testing schemes for healthcare workers. Regularly testing all healthcare workers requires many tests while reducing this number by only testing some healthcare workers can result in undetected cases. An efficient way to test as many individuals as possible with a limited testing capacity is to consider pooling multiple samples to be analysed with a single test (known as pooled testing). Methods Two different pooled testing schemes for the asymptomatic testing are evaluated using an individual-based model representing the transmission of SARS-CoV-2 in a ‘typical’ English hospital. We adapt the modelling to reflect two scenarios: a) a retrospective look at earlier SARS-CoV-2 variants under lockdown or social restrictions, and b) transitioning back to ‘normal life’ without lockdown and with the omicron variant. The two pooled testing schemes analysed differ in the population that is eligible for testing. In the ‘ward’ testing scheme only healthcare workers who work on a single ward are eligible and in the ‘full’ testing scheme all healthcare workers are eligible including those that move across wards. Both pooled schemes are compared against the baseline scheme which tests only symptomatic healthcare workers. Results Including a pooled asymptomatic testing scheme is found to have a modest (albeit statistically significant) effect, reducing the total number of nosocomial healthcare worker infections by about 2 $$\%$$ % in both the lockdown and non-lockdown setting. However, this reduction must be balanced with the increase in cost and healthcare worker isolations. Both ward and full testing reduce HCW infections similarly but the cost for ward testing is much less. We also consider the use of lateral flow devices (LFDs) for follow-up testing. Considering LFDs reduces cost and time but LFDs have a different error profile to PCR tests. Conclusions Whether a PCR-only or PCR and LFD ward testing scheme is chosen depends on the metrics of most interest to policy makers, the virus prevalence and whether there is a lockdown.

Abstract Background Globally, detections of carbapenemase-producing Enterobacterales (CPE) colonisations and infections are increasing. The spread of these highly resistant bacteria poses a serious threat to public health. However, understanding of CPE transmission and evidence on effectiveness of control measures is severely lacking. This paper provides evidence to inform effective admission screening protocols, which could be important in controlling nosocomial CPE transmission. Methods CPE transmission within an English hospital setting was simulated with a data-driven individual-based mathematical model. This model was used to evaluate the ability of the 2016 England CPE screening recommendations, and of potential alternative protocols, to identify patients with CPE-colonisation on admission (including those colonised during previous stays or from elsewhere). The model included nosocomial transmission from colonised and infected patients, as well as environmental contamination. Model parameters were estimated using primary data where possible, including estimation of transmission using detailed epidemiological data within a Bayesian framework. Separate models were parameterised to represent hospitals in English areas with low and high CPE risk (based on prevalence). Results The proportion of truly colonised admissions which met the 2016 screening criteria was 43% in low-prevalence and 54% in high-prevalence areas respectively. Selection of CPE carriers for screening was improved in low-prevalence areas by adding readmission as a screening criterion, which doubled how many colonised admissions were selected. A minority of CPE carriers were confirmed as CPE positive during their hospital stay (10 and 14% in low- and high-prevalence areas); switching to a faster screening test pathway with a single-swab test (rather than three swab regimen) increased the overall positive predictive value with negligible reduction in negative predictive value. Conclusions Using a novel within-hospital CPE transmission model, this study assesses CPE admission screening protocols, across the range of CPE prevalence observed in England. It identifies protocol changes—adding readmissions to screening criteria and a single-swab test pathway—which could detect similar numbers of CPE carriers (or twice as many in low CPE prevalence areas), but faster, and hence with lower demand on pre-emptive infection-control resources. Study findings can inform interventions to control this emerging threat, although further work is required to understand within-hospital transmission sources.

Abstract Glycosylation is a key quality attribute that must be closely monitored for protein therapeutics. Established assays such as HILIC-Fld of released glycans and LC-MS of glycopeptides work well for glycoproteins with a few glycosylation sites but are less amenable for those with multiple glycosylation sites, resulting in complex datasets that are time consuming to generate and difficult to analyze. As part of efforts to improve preparedness for future pandemics, researchers are currently assessing where time can be saved in the vaccine development and production process. In this context, we evaluated if neutral and acidic monosaccharides analysis via HPAEC-PAD could be used as a rapid and robust alternative to LC-MS and HILIC-Fld for monitoring glycosylation between protein production batches. Using glycoengineered spike proteins we show that the HPAEC-PAD monosaccharide assays could quickly and reproducibly detect both major and minor glycosylation differences between batches. Moreover, the monosaccharide results aligned well with those obtained by HILIC-Fld and LC-MS.

Abstract Background As the COVID-19 pandemic continues to evolve, novel vaccines need to be developed that are readily manufacturable and provide clinical efficacy against emerging SARS-CoV-2 variants. Virus-like particles (VLPs) presenting the spike antigen at their surface offer remarkable benefits over other vaccine antigen formats; however, current SARS-CoV-2 VLP vaccines candidates in clinical development suffer from challenges including low volumetric productivity, poor spike antigen density, expression platform-driven divergent protein glycosylation and complex upstream/downstream processing requirements. Despite their extensive use for therapeutic protein manufacturing and proven ability to produce enveloped VLPs, Chinese Hamster Ovary (CHO) cells are rarely used for the commercial production of VLP-based vaccines. Methods Using CHO cells, we aimed to produce VLPs displaying the full-length SARS-CoV-2 spike. Affinity chromatography was used to capture VLPs released in the culture medium from engineered CHO cells expressing spike. The structure, protein content, and glycosylation of spikes in VLPs were characterized by several biochemical and biophysical methods. In vivo, the generation of neutralizing antibodies and protection against SARS-CoV-2 infection was tested in mouse and hamster models. Results We demonstrate that spike overexpression in CHO cells is sufficient by itself to generate high VLP titers. These VLPs are evocative of the native virus but with at least three-fold higher spike density. In vivo, purified VLPs elicit strong humoral and cellular immunity at nanogram dose levels which grant protection against SARS-CoV-2 infection. Conclusions Our results show that CHO cells are amenable to efficient manufacturing of high titers of a potently immunogenic spike protein-based VLP vaccine antigen.

Abstract Background Interstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive pulmonary disorders with a poor prognosis. Prompt and accurate diagnosis is important to enable patients to receive appropriate care at the earliest possible stage to delay disease progression and prolong survival. Artificial intelligence-assisted lung auscultation and ultrasound (LUS) could constitute an alternative to conventional, subjective, operator-related methods for the accurate and earlier diagnosis of these diseases. This protocol describes the standardised collection of digitally-acquired lung sounds and LUS images of adult outpatients with IPF, NSIP or COPD and a deep learning diagnostic and severity-stratification approach. Methods A total of 120 consecutive patients (≥ 18 years) meeting international criteria for IPF, NSIP or COPD and 40 age-matched controls will be recruited in a Swiss pulmonology outpatient clinic, starting from August 2022. At inclusion, demographic and clinical data will be collected. Lung auscultation will be recorded with a digital stethoscope at 10 thoracic sites in each patient and LUS images using a standard point-of-care device will be acquired at the same sites. A deep learning algorithm (DeepBreath) using convolutional neural networks, long short-term memory models, and transformer architectures will be trained on these audio recordings and LUS images to derive an automated diagnostic tool. The primary outcome is the diagnosis of ILD versus control subjects or COPD. Secondary outcomes are the clinical, functional and radiological characteristics of IPF, NSIP and COPD diagnosis. Quality of life will be measured with dedicated questionnaires. Based on previous work to distinguish normal and pathological lung sounds, we estimate to achieve convergence with an area under the receiver operating characteristic curve of > 80% using 40 patients in each category, yielding a sample size calculation of 80 ILD (40 IPF, 40 NSIP), 40 COPD, and 40 controls. Discussion This approach has a broad potential to better guide care management by exploring the synergistic value of several point-of-care-tests for the automated detection and differential diagnosis of ILD and COPD and to estimate severity. Trial registration Registration: August 8, 2022. ClinicalTrials.gov Identifier: NCT05318599.

A bright ( m _F150W,AB = 24 mag), z = 1.95 supernova (SN) candidate was discovered in JWST/NIRCam imaging acquired on 2023 November 17. The SN is quintuply imaged as a result of strong gravitational lensing by a foreground galaxy cluster, detected in three locations, and remarkably is the second lensed SN found in the same host galaxy. The previous lensed SN was called “Requiem,” and therefore the new SN is named “Encore.” This makes the MACS J0138.0−2155 cluster the first known system to produce more than one multiply imaged SN. Moreover, both SN Requiem and SN Encore are Type Ia SNe (SNe Ia), making this the most distant case of a galaxy hosting two SNe Ia. Using parametric host fitting, we determine the probability of detecting two SNe Ia in this host galaxy over a ∼10 yr window to be ≈3%. These observations have the potential to yield a Hubble constant ( H _0 ) measurement with ∼10% precision, only the third lensed SN capable of such a result, using the three visible images of the SN. Both SN Requiem and SN Encore have a fourth image that is expected to appear within a few years of ∼2030, providing an unprecedented baseline for time-delay cosmography.

James Webb Space Telescope NIRCam images have revealed 154 reliable globular cluster (GC) candidates around the z = 0.0513 elliptical galaxy VV 191a after subtracting 34 likely interlopers from background galaxies inside our search area. NIRCam broadband observations are made at 0.9–4.5 μ m using the F090W, F150W, F356W, and F444W filters. Using point-spread-function-matched photometry, the data are analyzed to present color–magnitude diagrams and color distributions that suggest a relatively uniform population of GCs, except for small fractions of reddest (5%–8%) and bluest (2%–4%) outliers. GC models in the F090W versus (F090W–F150W) diagram fit the NIRCam data well and show that the majority of GCs detected have a mass of ∼10 ^6.5 M _⊙ , with metallicities [Fe/H] spanning the typical range expected for GCs (−2.5 ≲ [Fe/H]≲ 0.5). However, the models predict ∼0.3–0.4 mag bluer (F356W–F444W) colors than the NIRCam data for a reasonable range of GC ages, metallicities, and reddening. Although our data do not quite reach the luminosity function turnover, the measured luminosity function is consistent with previous measurements, suggesting an estimated peak at m _AB ∼ −9.4 ± 0.2 mag in the F090W filter.

A wealth of observations have long suggested that the vast majority of isolated classical dwarf galaxies ( M _* = 10 ^7 –10 ^9 M _⊙ ) are currently star forming. However, recent observations of the large abundance of “ultra-diffuse galaxies” beyond the reach of previous large spectroscopic surveys suggest that our understanding of the dwarf galaxy population may be incomplete. Here we report the serendipitous discovery of an isolated quiescent dwarf galaxy in the nearby Universe, which was imaged as part of the JWST PEARLS Guaranteed Time Observation program. Remarkably, individual red-giant branch stars are visible in this near-IR imaging, suggesting a distance of 30 ± 4 Mpc, and a wealth of archival photometry point to an sSFR of 2 × 10 ^−11 yr ^−1 and star formation rate of 4 × 10 ^−4 M _⊙ yr ^−1 . Spectra obtained with the Lowell Discovery Telescope find a recessional velocity consistent with the Hubble Flow and >1500 km s ^−1 separated from the nearest massive galaxy in Sloan Digital Sky Survey suggesting that this galaxy was either quenched from internal mechanisms or had a very high-velocity (≳1000 km s ^−1 ) interaction with a nearby massive galaxy in the past. This analysis highlights the possibility that many nearby quiescent dwarf galaxies are waiting to be discovered and that JWST has the potential to resolve them.

IntroductionInformal carers of people with mental health problems often have unmet support needs. Mental health recovery narratives are increasingly accessible, but their relevance to and effect on informal carers have been minimally investigated. The Narrative Experiences Online (NEON) Intervention is a first-in-field intervention that provides informal carers with access to a diverse collection of recorded mental health recovery narratives. This trial aimed to examine the feasibility and acceptability of the NEON Intervention for informal carers.MethodsThis study involved a two-arm feasibility randomized controlled trial. Carers were randomly assigned to receiving versus not receiving the NEON Intervention. The feasibility aspects investigated included the acceptability of the intervention and of randomization, trial processes, engagement rates, recruitment procedures, attrition, sample size estimation, identification of candidate primary and secondary outcomes, and the feasibility of conducting a definitive trial. A qualitative process evaluation was conducted.FindingsA total of 121 carers were eligible, of whom 54 were randomized (intervention: 27, control: 27). Twelve-month follow-up data were available for 36 carers. Carers accessed a mean of 25 narratives over a 12-month period, and the intervention group, compared with the control group, reported a small effect on hope and a moderate effect on the presence of meaning in life. Five modifications were recommended to improve the user experience, applicability, and trial processes.DiscussionThe NEON Intervention is feasible and acceptable. Significant refinement of the NEON Intervention and trial processes is required to personalize and ensure applicability to carers. Further feasibility testing is recommended prior to a definitive trial.

ABSTRACTEffective processes for synthesizing antibody-drug conjugates (ADCs) require: 1) site-specific incorporation of the payload to avoid interference with binding to the target epitope, 2) optimal drug/antibody ratio to achieve sufficient potency while avoiding aggregation or solubility problems, and 3) a homogeneous product to facilitate approval by regulatory agencies. In conventional ADCs, the drug molecules are chemically attached randomly to antibody surface residues (typically Lys or Cys), which can interfere with epitope binding and targeting, and lead to overall product heterogeneity, long-term colloidal instability and unfavorable pharmacokinetics. Here, we present a more controlled process for generating ADCs where drug is specifically conjugated to only Fab N-linked glycans in a narrow ratio range through functionalized sialic acids. Using a bacterial sialytransferase, we incorporated N-azidoacetylneuraminic acid (Neu5NAz) into the Fab glycan of cetuximab. Since only about 20% of human IgG1 have a Fab glycan, we extended the application of this approach by using molecular modeling to introduce N-glycosylation sites in the Fab constant region of other therapeutic monoclonal antibodies. We used trastuzumab as a model for the incorporation of Neu5NAz in the novel Fab glycans that we designed. ADCs were generated by clicking the incorporated Neu5NAz with monomethyl auristatin E (MMAE) attached to a self-immolative linker terminated with dibenzocyclooctyne (DBCO). Through this process, we obtained cetuximab-MMAE and trastuzumab-MMAE with drug/antibody ratios in the range of 1.3 to 2.5. We confirmed that these ADCs still bind their targets efficiently and are as potent in cytotoxicity assays as control ADCs obtained by standard conjugation protocols. The site-directed conjugation to Fab glycans has the additional benefit of avoiding potential interference with effector functions that depend on Fc glycan structure.

IntroductionDuring the first wave of the COVID-19 pandemic 293,204 inpatients in England tested positive for SARS-CoV-2. It is estimated that 1% of these cases were hospital-associated using European centre for disease prevention and control (ECDC) and Public Health England (PHE) definitions. Guidelines for preventing the spread of SARS-CoV-2 in hospitals have developed over time but the effectiveness and efficiency of testing strategies for preventing nosocomial transmission has not been explored.MethodsUsing an individual-based model, parameterised using multiple datasets, we simulated the transmission of SARS-CoV-2 to patients and healthcare workers between March and August 2020 and evaluated the efficacy of different testing strategies. These strategies were: 0) Testing only symptomatic patients on admission; 1) Testing all patients on admission; 2) Testing all patients on admission and again between days 5 and 7, and 3) Testing all patients on admission, and again at days 3, and 5-7. In addition to admissions testing, patients that develop a symptomatic infection while in hospital were tested under all strategies. We evaluated the impact of testing strategy, test characteristics and hospital-related factors on the number of nosocomial patient infections.ResultsModelling suggests that 84.6% (95% CI: 84.3, 84.7) of community-acquired and 40.8% (40.3, 41.3) of hospital-associated SARS-CoV-2 infections are detectable before a patient is discharged from hospital. Testing all patients on admission and retesting after 3 or 5 days increases the proportion of nosocomial cases detected by 9.2%. Adding discharge testing increases detection by a further 1.5% (relative increase). Increasing occupancy rates, number of beds per bay, or the proportion of admissions wrongly suspected of having COVID-19 on admission and therefore incorrectly cohorted with COVID-19 patients, increases the rate of nosocomial transmission. Over 30,000 patients in England could have been discharged while incubating a non-detected SARS-CoV-2 infection during the first wave of the COVID-19 pandemic, of which 3.3% could have been identified by discharge screening. There was no significant difference in the rates of nosocomial transmission between testing strategies or when the turnaround time of the test was increased.DiscussionThis study provides insight into the efficacy of testing strategies in a period unbiased by vaccines and variants. The findings are relevant as testing programs for SARS-CoV-2 are scaled back, and possibly if a new vaccine escaping variant emerges.

Background Negative symptoms are typically observed in people with schizophrenia and indicate a loss or reduction of a normal function (e.g. reduced motivation and affect display). Despite obstructing people’s recovery, intervention development receives limited attention. Objectives This study evaluates, for the first time, the feasibility and acceptability of a novel Virtual Reality Supported Therapy for the Negative SympToms of Psychosis. Design This is a single (rater)-blind randomised study with two conditions (Virtual Reality Supported Therapy for the Negative SympToms of Psychosis plus treatment as usual vs. treatment as usual alone) recruiting people with schizophrenia experiencing debilitating negative symptoms. Assessments are at baseline and at 3-month postrandomisation. Setting Psychosis outpatient clinics. Main outcome measures The prespecified primary outcome is participants’ goal attainment, and secondary outcomes are negative symptoms and functioning. The study assesses feasibility and acceptability parameters including recruitment, eligibility, treatment adherence and retention. Acceptability is evaluated qualitatively using a post-therapy feedback interview and data analysed through thematic analysis. Therapy effect on outcomes is estimated using intention-to-treat principles. Results The study recruited its prespecified target of 30 participants (15 randomised to Virtual Reality Supported Therapy for the Negative SympToms of Psychosis). Two participants in each therapy arm were either ‘lost at follow-up’ or discontinued the trial. Therapy engagement for those randomised to Virtual Reality Supported Therapy for the Negative SympToms of Psychosis was appropriate and research procedures were considered feasible. Nine participants took part in the acceptability interview and described the therapy and virtual reality procedures as positive and useful. There were 2 serious adverse events for participants randomised to treatment as usual and 11 adverse events (7 in the Virtual Reality Supported Therapy for the Negative SympToms of Psychosis group and 4 in the treatment-as-usual group). Adverse events were not related to research and therapy procedures. Preliminary analysis suggested the therapy may have a large effect on participants’ goals and a possible effect on negative symptoms. Limitations The study was not able to evaluate the hypothesised mechanistic aspect of the therapy (i.e. reward learning) due to pandemic-imposed social distancing measures. The current study also did not have a follow-up assessment, and this limitation did not allow to assess possible change in intervention effect over time. Conclusion We showed that Virtual Reality Supported Therapy for the Negative SympToms of Psychosis is a feasible, acceptable and safe intervention. This therapy has the potential to support people with schizophrenia in achieving their recovery goals by reducing the burden of negative symptoms. The results of this study support further evaluation of Virtual Reality Supported Therapy for the Negative SympToms of Psychosis to assess its efficacy in an appropriately powered randomised controlled trial. Study registration The study protocol was pre-registered on ClinicalTrials.gov (identifier: NCT03995420). Funding This project was funded by the National Institute for Health and Care Research (NIHR) Efficacy and Mechanism Evaluation (EME) programme, an MRC and NIHR partnership (NIHR-EME: 17/59/13). This will be published in full in Efficacy and Mechanism Evaluation; Vol. 10, No. 6. See the NIHR Journals Library website for further project information. Plain language summary Background Schizophrenia is one of the most severe and debilitating mental health conditions. Full recovery rates are low, and the illness burden is huge for those affected. Research suggests that negative symptoms reduce people’s recovery prospect. Negative symptoms include poor motivation, social withdrawal, difficulty in enjoying daily activities and reduced communication. These symptoms influence patients’ day-to-day functioning, and reports of patient groups have highlighted this as a key area for new treatment development. Aims To: (1) develop a novel virtual reality supported therapy (called Virtual Reality Supported Therapy for the Negative SympToms of Psychosis) targeting the negative symptoms of schizophrenia with the overall aim of improving recovery; (2) evaluate Virtual Reality Supported Therapy for the Negative SympToms of Psychosis for ease of use, acceptability and safety and estimate its potential benefits. Development work The Virtual Reality Supported Therapy for the Negative SympToms of Psychosis software and procedures were initially developed by the research team. This process included several feedback phases from different stakeholders including service users, clinicians and technology experts. The resulting therapy is a 12-session virtual reality supported intervention delivered by a psychologist. Evaluation work We used a controlled study design where half of the participants were offered Virtual Reality Supported Therapy for the Negative SympToms of Psychosis in addition to their usual treatment and the other half received usual treatment alone. The study recruited to target (30 participants) but took longer than anticipated to complete because of COVID-19 pandemic restrictions. Prior to random assignment, participants were assessed with measures of goal attainment, negative symptoms and functioning. Four participants did not complete the study (two in Virtual Reality Supported Therapy for the Negative SympToms of Psychosis and two in usual treatment alone). More than 80% of the participants in the therapy group received an appropriate number of therapy sessions. Interviews suggested that the therapy was considered acceptable and useful. Preliminary analysis suggested that the intervention had a positive effect on therapy recovery goals and negative symptoms. The research procedures were considered feasible. Implications and next steps The results of this study are encouraging and support further evaluation of this therapy through a randomised controlled trial to formally assess its efficacy. Scientific summary Background Schizophrenia is one of the most severe and debilitating mental health conditions. Full recovery rates are low, and the illness burden is huge for those affected. Negative symptoms (NS) are typically observed in people with schizophrenia and indicate a loss or reduction in normal functioning. NS include poor motivation, social withdrawal, difficulty in enjoying activities and reduced communication. These symptoms influence patients’ day-to-day functioning, and reports of patient groups have highlighted this as a key area for new treatment development. Despite obstructing people’s recovery, intervention development has received limited attention. Main barriers that have hampered development are the lack of clear therapy targets and poor adherence to interventions because of lack of motivation. In recent years research showed that people with NS are more sensitive to negative feedback and less sensitive to positive feedback. This may be a mechanism maintaining NS. Further, the use of digital technology in therapy delivery has the potential to make therapies more engaging and improve adherence. Virtual reality (VR), a form of computer-simulated immersive reality, may offer opportunities to improve engagement and therapy experience and reduce therapy motivational needs. Objectives Develop a novel virtual reality supported therapy [called Virtual Reality Supported Therapy for the Negative SympToms of Psychosis (V-NeST)] targeting the NS of schizophrenia with the overall aim of improving recovery. Evaluate V-NeST for ease of use, acceptability and safety and estimate its potential benefits. Methods Design This is a two-arm randomised controlled trial comparing V-NeST plus treatment as usual (TAU) to TAU alone. Participants were assessed at baseline and at 12 weeks postrandomisation (i.e. end of therapy for those randomised to V-NeST). The primary outcome was participants’ progress on personal recovery goals measured by the Goal Attainment Scale (GAS) at 12 weeks postrandomisation. Secondary outcomes were NS and functioning. Apart from the participants, the therapists and the trial principal investigator, all other study staff including outcome assessors and the trial statistician were blind to trial arm allocation, until primary analysis completion. Ethical approval and protocol registration Study procedures were reviewed and approved by the London Camberwell and St. Giles NHS ethics committee (approval number 19/LO/0830). The study protocol was pre-registered on ClinicalTrials.gov (identifier: NCT03995420). Randomisation Consented participants were randomised using a web-based randomisation service at the UKCRC registered King’s Clinical Trials Unit. Randomisation used variable block size (i.e. 2, 4 and 6) with equal allocation. Participants Participants were recruited from community mental health teams, which are part of the South London and Maudsley NHS Foundation Trust. Inclusion criteria: (1) currently under the care of a community psychosis services; (2) older than 18 years; (3) in a stable clinical condition; (4) with a documented episode of psychosis (e.g. first-episode psychosis) and/or a diagnosis of schizophrenia; (5) no current episode or history of epilepsy (as it is a contraindication for VR); (6) experiencing disabling NS as identified by care staff. Exclusion criteria: (1) having a comorbid organic condition affecting their behaviour; (2) severe learning disability; (3) insufficient communication skills for consenting and undertaking the research assessment and therapy. Measures The primary outcome of this study was GAS, which is a structured measure of personal recovery goals. The following measures were secondary outcomes: The Clinical Assessment Interview for Negative Symptoms, which is an interviewer-based assessment of NS. The self-evaluation of negative symptoms, which provides an assessment of NS from the participant’s perspective. The Work and Social Adjustment Scale was used to assess functioning. The mechanistic elements of the intervention were assessed using the Effort Expenditure for Reward Task and the Wisconsin Card Sorting Task. The following measures were used to characterise the sample: The Psychotic Symptom Rating Scales to assess the positive symptoms of psychosis. The Hospital Anxiety and Depression Scale to assess anxiety and depression. The Rosenberg Self-Esteem Scale to assess self-esteem. The digit span to assess working memory and the Trail Making (A and B) to assess processing speed and executive function. Acceptability Participants randomised to V-NeST were invited to participate in a feedback semistructured interview assessing acceptability. The interview asked questions in relation to the therapy and assessment procedures, use of VR and asked suggestions for therapy and research procedures improvements. All interviews were recorded and transcribed. Service users involvement People experienced in using mental health services were consulted at different stages of this study, including the initial discussions on study procedures, to revise wording on the study information sheet and consent forms and for feedback on VR development. Service users were part of the trial management group and supported the interpretation and dissemination of the results and are also authors on this report. Sample size On the basis of previous research and recommendations from our lead statistician, we have considered a sample size of 30 participants to be adequate for obtaining reliable feasibility parameter estimates. And on the basis of previous similar studies conducted on our site, we have estimated for a dropout rate of 20% over the study period. Feasibility evaluation The feasibility of the trial procedures was examined using proportions and exact Clopper Pearson’s 95% confidence intervals (CIs) for assessments of feasibility and acceptability in terms of recruitment, consent and availability for screening, eligibility, availability for baseline assessment and randomisation, treatment retention and follow-up assessments, and availability and consent to be approached by a research therapist. Explorative treatment effect estimate These analyses followed the intention-to-treat principle, with data from all participants who took part in the study considered. Clinical outcomes were analysed using a linear regression model with data collected from all participants irrespective of whether they attended the intervention or not. Treatment differences with 95% CIs at follow-up are presented. In addition, standardised effect sizes (Cohen’s d calculated as the adjusted mean difference between treatment arms estimates divided by the within-groups pooled standard deviation) with 95% CIs will be presented. Our main aim was to estimate the likely range of intervention effects at post-treatment by assessing 95% CIs of the treatment effects. Acceptability evaluation Thematic analysis was used to analyse the post-therapy feedback interview transcripts. This explored participants’ experiences of receiving the therapy and taking part in this research study. Emergent themes were identified by one researcher and then the themes were reviewed and coded by four members of the team including service users with relevant lived experience. Results Recruitment and retention A total of 190 people were assessed for eligibility of which 160 were excluded: 39 people declined to participate, 44 were not contactable and the remaining 77 people did not meet inclusion criteria. Thus 30 participants were assessed at baseline and randomised into V-NeST plus TAU (N = 15; 50%) or TAU alone (N = 15; 50%). Out of these 30 participants, 29 received the allocated treatment (14 participants received V-NeST plus TAU and 15 participants received TAU alone). Four participants did not provide data at follow-up; they either were ‘lost at follow-up’ (V-NeST: N = 1 and TAU alone: N = 2) or discontinued the study (V-NeST: N = 1). All 30 participants were considered for the primary analyses. In the treatment arm, 14 out of 15 participants attended at least 1 therapy session with an average of 9.7 (standard deviation = 3.77, range 1–12) sessions. Two participants did not receive the minimum therapy dose of six sessions and completed one and four therapy sessions, respectively. Assessment completion All participants completed all clinical outcome measures (primary and secondary) at the baseline, while 76% of the participants completed the mechanistic outcomes. At follow-up, data completion for the primary and secondary outcome ranged between 86% and 100%. The completion rate for the mechanistic measure was 26%. Adverse events There were two serious adverse events (from two participants) and 11 adverse events (AEs) recorded in this study. AEs were not considered linked to the therapy or the research procedures. Acceptability evaluation Nine out of fifteen participants in the intervention arm of the trial were interviewed. Themes emerging from the interview were as follows: (1) therapy contributing to personal goals; (2) impact of pandemic-imposed restrictions on recovery; (3) debilitating nature of NS; (4) value of using virtual reality; (5) feedback on therapy procedures and suggestions for improvements. Treatment effect estimate The results of linear regression model analyses with the clinical outcome as the dependent variable, group as categorical independent variables and baseline value of outcome as a covariate showed that V-NeST had a large treatment effect on therapy goals [Cohen’s d = 1.48 (95% CI 0.61 to 2.35)]. The treatment effects of main secondary outcomes were smaller and all favouring V-NeST but with large CIs. Conclusions V-NeST demonstrated good acceptability and feasibility parameters particularly considering this study involved participants with severe and disabling levels of NS. The therapy procedures were considered acceptable, and the VR aspects were well tolerated and found to be engaging. Several therapy features were suggested for revision, including ways of interacting with the virtual environment (e.g. hands movements) and some therapy components (e.g. making psychoeducation more engaging). Only one participant had tried VR before, and most had limited digital technology skills. This was not a barrier to therapy use and the VR proved intuitive and easy to learn. The feasibility of the research procedure was also good with most research procedures being well tolerated by all participants. The study recruited to target (30 participants) but considered 190 referrals to meet its target. This means approximately one in six of the people referred was able to take part in the trial. While this study had comprehensive inclusion criteria, there is consensus that recruiting people with NS in research studies may be complex. However, we proved that it is possible and that once participants entered the trial, we retained more than 80% of those randomised to treatment. The explorative analysis on the prespecified primary outcome suggested that the intervention may be helpful in supporting people’s recovery goals. This outcome was chosen as this was what service users suggested to be the most valuable. This result is encouraging and taken together with the acceptability and feasibility findings supports further development and evaluation of this therapy. Future steps for developing V-NeST will include the modification of the VR software and therapy procedures in line with the feedback received from participants. A formal evaluation of efficacy will also require an appropriately powered trial. A future evaluation should also consider the cost-efficacy of this intervention and how it may be implemented in clinical settings (e.g. therapist training or access to VR). The development and evolution of digital therapies has enormous potential to reduce the impact of NS on recovery in people with schizophrenia. There is the promise of better and more engaging therapies coupled with the prospect of these being easier to deliver for services. Study registration The study protocol was pre-registered on ClinicalTrials.gov (identifier: NCT03995420). Funding This project was funded by the National Institute for Health and Care Research (NIHR) Efficacy and Mechanism Evaluation (EME) programme, an MRC and NIHR partnership (NIHR-EME: 17/59/13). This will be published in full in Efficacy and Mechanism Evaluation; Vol. 10, No. 6. See the NIHR Journals Library website for further project information.

Partnering with people most affected by mental health problems can transform mental health outcomes. Citizen science as a research approach enables partnering with the public at a substantial scale, but there is scarce guidance on its use in mental health research. To develop best practise guidelines for conducting and reporting research, we conducted a systematic review of studies reporting mental health citizen science research. Documents were identified from electronic databases (n = 10), grey literature, conference proceedings, hand searching of specific journals and citation tracking. Document content was organised in NVIVO using the ten European Citizen Science Association (ECSA) citizen science principles. Best practise guidelines were developed by (a) identifying approaches specific to mental health research or where citizen science and mental health practises differ, (b) identifying relevant published reporting guidelines and methodologies already used in mental health research, and (c) identifying specific elements to include in reporting studies. A total of 14,063 documents were screened. Nine studies were included, from Australia, Belgium, Canada, Denmark, Netherlands, Spain, the UK, and the United States. Citizen scientists with lived experience of mental health problems were involved in data collection, analysis, project design, leadership, and dissemination of results. Most studies reported against some ECSA principles but reporting against these principles was often unclear and unstated. Best practise guidelines were developed, which identified mental health-specific issues relevant to citizen science, and reporting recommendations. These included citizen science as a mechanism for empowering people affected by mental health problems, attending to safeguarding issues such as health-related advice being shared between contributors, the use of existing health research reporting guidelines, evaluating the benefits for contributors and impact on researchers, explicit reporting of participation at each research stage, naming the citizen science platform and data repository, and clear reporting of consent processes, data ownership, and data sharing arrangements. We conclude that citizen science is feasible in mental health and can be complementary to other participatory approaches. It can contribute to active involvement, engagement, and knowledge production with the public. The proposed guidelines will support the quality of citizen science reporting.

Abstract Background From March 2020 through August 2021, 97,762 hospital-onset SARS-CoV-2 infections were detected in English hospitals. Resulting excess length of stay (LoS) created a potentially substantial health and economic burden for patients and the NHS, but we are currently unaware of any published studies estimating this excess. Methods We implemented appropriate causal inference methods to determine the extent to which observed additional hospital stay is attributable to the infection rather than the characteristics of the patients. Hospital admissions records were linked to SARS-CoV-2 test data to establish the study population (7.5 million) of all non-COVID-19 admissions to English hospitals from 1st March 2020 to 31st August 2021 with a stay of at least two days. The excess LoS due to hospital-onset SARS-CoV-2 infection was estimated as the difference between the mean LoS observed and in the counterfactual where infections do not occur. We used inverse probability weighted Kaplan–Meier curves to estimate the mean survival time if all hospital-onset SARS-CoV-2 infections were to be prevented, the weights being based on the daily probability of acquiring an infection. The analysis was carried out for four time periods, reflecting phases of the pandemic differing with respect to overall case numbers, testing policies, vaccine rollout and prevalence of variants. Results The observed mean LoS of hospital-onset cases was higher than for non-COVID-19 hospital patients by 16, 20, 13 and 19 days over the four phases, respectively. However, when the causal inference approach was used to appropriately adjust for time to infection and confounding, the estimated mean excess LoS caused by hospital-onset SARS-CoV-2 was: 2.0 [95% confidence interval 1.8–2.2] days (Mar-Jun 2020), 1.4 [1.2–1.6] days (Sep–Dec 2020); 0.9 [0.7–1.1] days (Jan–Apr 2021); 1.5 [1.1–1.9] days (May–Aug 2021). Conclusions Hospital-onset SARS-CoV-2 is associated with a small but notable excess LoS, equivalent to 130,000 bed days. The comparatively high LoS observed for hospital-onset COVID-19 patients is mostly explained by the timing of their infections relative to admission. Failing to account for confounding and time to infection leads to overestimates of additional length of stay and therefore overestimates costs of infections, leading to inaccurate evaluations of control strategies.

New JWST/NIRCam wide-field slitless spectroscopy provides redshifts for four z > 8 galaxies located behind the lensing cluster MACS J0416.1−2403. Two of them, “Y1” and “JD,” have previously reported spectroscopic redshifts based on Atacama Large Millimeter/submillimeter Array measurements of [O iii ] 88 μ m and/or [C ii ] 157.7 μ m lines. Y1 is a merging system of three components, and the existing redshift z = 8.31 is confirmed. However, JD is at z = 8.34 instead of the previously claimed z = 9.28. JD’s close companion, “JD-N,” which was a previously discovered z > 8 candidate, is now identified at the same redshift as JD. JD and JD-N form an interacting pair. A new candidate at z > 8, “f090d_018,” is also confirmed and is at z = 8.49. These four objects are likely part of an overdensity that signposts a large structure extending ∼165 kpc in projected distance and ∼48.7 Mpc in radial distance. They are magnified by less than 1 mag and have an intrinsic M _UV ranging from −19.57 to −20.83 mag. Their spectral energy distributions show that the galaxies are all very young with ages ∼ 4–18 Myr and stellar masses of about 10 ^7–8 M _⊙ . These infant galaxies have very different star formation rates ranging from a few to over a hundred solar masses per year, but only two of them (JD and f090d_018) have blue rest-frame UV slopes β < −2.0 indicative of a high Lyman-continuum photon escape fraction that could contribute significantly to the cosmic hydrogen-reionizing background. Interestingly, these two galaxies are the least massive and least active ones among the four. The other two systems have much flatter UV slopes largely because of their high dust extinction ( A _V = 0.9–1.0 mag). Their much lower indicated escape fractions show that even very young, actively star-forming galaxies can have a negligible contribution to reionization when they quickly form dust throughout their bodies.

The first public 0.9–4.4 μ m NIRCam images of the North Ecliptic Pole Time Domain Field uncovered galaxies displaying point-source features in their cores as seen in the longer-wavelength filters. We visually identified a sample of 66 galaxies (∼1 galaxy arcmin ^–2 ) with pointlike cores and have modeled their two-dimensional light profiles with GalFit , identifying 16 galactic nuclei with measurable point-source components. GalFit suggests that the visual sample is a mix of both compact stellar bulge and point-source galaxy cores. This core classification is complemented by spectral energy distribution modeling to infer the sample’s active galactic nucleus (AGN) and host-galaxy parameters. For galaxies with measurable point-source components, the median fractional AGN contribution to their 0.1–30.0 μ m flux is 0.44, and 14/16 are color-classified AGN. We conclude that near-infrared point-source galaxy cores are signatures of AGN. In addition, we define an automated sample-selection criterion to identify these point-source features. This criterion can be used in other extant and future NIRCam images to streamline the search for galaxies with unresolved IR-luminous AGN. The James Webb Space Telescope’s superb angular resolution and sensitivity at infrared wavelengths are resurrecting the morphological identification of AGN.

We present a new parametric lens model for the G165.7+67.0 galaxy cluster, which was discovered with Planck through its bright submillimeter flux, originating from a pair of extraordinary dusty star-forming galaxies (DSFGs) at z ≈ 2.2. Using JWST and interferometric mm/radio observations, we characterize the intrinsic physical properties of the DSFGs, which are separated by only ∼1″ (8 kpc) and a velocity difference Δ V ≲ 600 km s ^−1 in the source plane, and thus are likely undergoing a major merger. Boasting intrinsic star formation rates SFR _IR = 320 ± 70 and 400 ± 80 M _⊙ yr ^−1 , stellar masses of $\mathrm{log}[{M}_{\star }/{M}_{\odot }]=10.2\pm 0.1$ and 10.3 ± 0.1, and dust attenuations of A _V = 1.5 ± 0.3 and 1.2 ± 0.3, they are remarkably similar objects. We perform spatially resolved pixel-by-pixel spectral energy distribution (SED) fitting using rest-frame near-UV to near-IR imaging from JWST/NIRCam for both galaxies, resolving some stellar structures down to 100 pc scales. Based on their resolved specific star formation rates (SFRs) and UVJ colors, both DSFGs are experiencing significant galaxy-scale star formation events. If they are indeed interacting gravitationally, this strong starburst could be the hallmark of gas that has been disrupted by an initial close passage. In contrast, the host galaxy of SN H0pe has a much lower SFR than the DSFGs, and we present evidence for the onset of inside-out quenching and large column densities of dust even in regions of low specific SFR. Based on the intrinsic SFRs of the DSFGs inferred from UV through far-infrared SED modeling, this pair of objects alone is predicted to yield an observable 1.1 ± 0.2 core-collapse supernovae per year, making this cluster field ripe for continued monitoring.

Supernova (SN) SN H0pe is a gravitationally lensed, triply imaged, Type Ia SN (SN Ia) discovered in James Webb Space Telescope imaging of the PLCK G165.7+67.0 cluster of galaxies. Well-observed multiply imaged SNe provide a rare opportunity to constrain the Hubble constant ( H _0 ), by measuring the relative time delay between the images and modeling the foreground mass distribution. SN H0pe is located at z = 1.783 and is the first SN Ia with sufficient light-curve sampling and long enough time delays for an H _0 inference. Here we present photometric time-delay measurements and SN properties of SN H0pe. Using JWST/NIRCam photometry, we measure time delays of Δ t _ab = $-{116.6}_{-9.3}^{+10.8}$ observer-frame days and Δ t _cb = $-{48.6}_{-4.0}^{+3.6}$ observer-frame days relative to the last image to arrive (image 2b; all uncertainties are 1 σ ), which corresponds to a ∼5.6% uncertainty contribution for H _0 assuming 70 km s ^−1 Mpc ^−1 . We also constrain the absolute magnification of each image to μ _a = ${4.3}_{-1.8}^{+1.6}$ , μ _b = ${7.6}_{-2.6}^{+3.6}$ , μ _c = ${6.4}_{-1.5}^{+1.6}$ by comparing the observed peak near-IR magnitude of SN H0pe to the nonlensed population of SNe Ia.

The James Webb Space Telescope (JWST) North Ecliptic Pole (NEP) Time-domain Field (TDF) is a >14′ diameter field optimized for multiwavelength time-domain science with JWST. It has been observed across the electromagnetic spectrum both from the ground and from space, including with the Hubble Space Telescope (HST). As part of HST observations over three cycles (the “TREASUREHUNT” program), deep images were obtained with the Wide Field Camera on the Advanced Camera for Surveys in F435W and F606W that cover almost the entire JWST NEP TDF. Many of the individual pointings of these programs partially overlap, allowing an initial assessment of the potential of this field for time-domain science with HST and JWST. The cumulative area of overlapping pointings is ∼88 arcmin ^2 , with time intervals between individual epochs that range between 1 day and 4+ yr. To a depth of m _AB ≃ 29.5 mag (F606W), we present the discovery of 12 transients and 190 variable candidates. For the variable candidates, we demonstrate that Gaussian statistics are applicable and estimate that ∼80 are false positives. The majority of the transients will be supernovae, although at least two are likely quasars. Most variable candidates are active galactic nuclei (AGNs), where we find 0.42% of the general z ≲ 6 field galaxy population to vary at the ∼3 σ level. Based on a 5 yr time frame, this translates into a random supernova areal density of up to ∼0.07 transients arcmin ^−2 (∼245 deg ^−2 ) per epoch and a variable AGN areal density of ∼1.25 variables arcmin ^−2 (∼4500 deg ^−2 ) to these depths.

We present an analysis of the ultraviolet luminosity function (UV LF) and star formation rate density of distant galaxies (7.5 < z < 13.5) in the “blank” fields of the Prime Extragalactic Areas for Reionization and Lensing Science (PEARLS) survey combined with Early Release Science data from the CEERS, GLASS, and NGDEEP surveys/fields and the first data release of JADES. We use strict quality cuts on EAZY photometric redshifts to obtain a reliable selection and characterization of high-redshift ( z > 6.5) galaxies from a consistently processed set of deep, near-infrared imaging. Within an area of 180 arcmin ^2 , we identify 1046 candidate galaxies at redshifts z > 6.5 and we use this sample to study the UV LF in four redshift bins between 7.5 < z < 13.5. The measured number density of galaxies at z = 8 and z = 9 matches those of past observations undertaken by the Hubble Space Telescope (HST). Our z = 10.5 measurements lie between early James Webb Space Telescope (JWST) results and past HST results, indicating cosmic variance may be the cause of previous high density measurements. However, the number densities of UV-luminous galaxies at z = 12.5 are high compared to predictions from simulations. When examining the star formation rate density of galaxies at this period, our observations are still largely consistent with a constant star formation efficiency, are slightly lower than previous early estimations using JWST, and support galaxy driven reionization at z ≤ 8.

A Type Ia supernova (SN) at z = 1.78 was discovered in James Webb Space Telescope Near Infrared Camera imaging of the galaxy cluster PLCK G165.7+67.0 (G165; z = 0.35). The SN is situated 1.5–2 kpc from the host-galaxy nucleus and appears in three different locations as a result of gravitational lensing by G165. These data can yield a value for Hubble’s constant using time delays from this multiply imaged SN Ia that we call “SN H0pe.” Over the cluster, we identified 21 image multiplicities, confirmed five of them using the Near-Infrared Spectrograph, and constructed a new lens model that gives a total mass within 600 kpc of (2.6 ± 0.3) × 10 ^14 M _⊙ . The photometry uncovered a galaxy overdensity coincident with the SN host galaxy. NIRSpec confirmed six member galaxies, four of which surround the SN host galaxy with relative velocity ≲900 km s ^−1 and projected physical extent ≲33 kpc. This compact galaxy group is dominated by the SN host galaxy, which has a stellar mass of (5.0 ± 0.1) × 10 ^11 M _⊙ . The group members have specific star formation rates of 2–260 Gyr ^−1 derived from the H α -line fluxes corrected for stellar absorption, dust extinction, and slit losses. Another group centered on a strongly lensed dusty star-forming galaxy is at z = 2.24. The total (unobscured and obscured) SFR of this second galaxy group is estimated to be (≳ 100 M _⊙ yr ^−1 ), which translates to a supernova rate of ∼1 SNe yr ^−1 , suggesting that regular monitoring of this cluster may yield additional SNe.

Abstract Background SARS-CoV-2 is known to transmit in hospital settings, but the contribution of infections acquired in hospitals to the epidemic at a national scale is unknown. Methods We used comprehensive national English datasets to determine the number of COVID-19 patients with identified hospital-acquired infections (with symptom onset > 7 days after admission and before discharge) in acute English hospitals up to August 2020. As patients may leave the hospital prior to detection of infection or have rapid symptom onset, we combined measures of the length of stay and the incubation period distribution to estimate how many hospital-acquired infections may have been missed. We used simulations to estimate the total number (identified and unidentified) of symptomatic hospital-acquired infections, as well as infections due to onward community transmission from missed hospital-acquired infections, to 31st July 2020. Results In our dataset of hospitalised COVID-19 patients in acute English hospitals with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired. We estimated that only 30% (range across weeks and 200 simulations: 20–41%) of symptomatic hospital-acquired infections would be identified, with up to 15% (mean, 95% range over 200 simulations: 14.1–15.8%) of cases currently classified as community-acquired COVID-19 potentially linked to hospital transmission. We estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200–16,400) or 20.1% (19.2–20.7%) of all identified hospitalised COVID-19 cases. Conclusions Transmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the “first wave” in England, but less than 1% of all infections in England. Using time to symptom onset from admission for inpatients as a detection method likely misses a substantial proportion (> 60%) of hospital-acquired infections.

“Epistemic injustice” refers to how people from marginalized groups are denied opportunities to create knowledge and derive meaning from their experiences. In the mental health field, epistemic injustice occurs in both research and service delivery systems and particularly impacts people from racialized communities. Lived experience involvement and leadership are often proposed as methods of combatting epistemic injustice, a tool for ensuring the views of people at the center of an issue are heard and can inform decision-making. However, this approach is not without challenges. In this paper, we draw on our work as intermediary organizations that center lived experience perspectives to challenge epistemic injustice. We highlight two problems we have identified in working in the mental health research field: “elite capture” and “epistemic exploitation”. We believe that these problems are barriers to the radical and structural change required for epistemic justice to occur. We propose a pragmatic approach to addressing these issues. Based on our work we suggest three considerations for researchers and our own organizations to consider when involving people with lived experience. These include reflecting on the purpose of creating knowledge, with a focus on impact. Embedding lived experience roles, with appropriate employment, support and remuneration, and acknowledging that it may be necessary to work alongside existing systems as a “critical friend” while developing new spaces and structures for alternative forms of knowledge. Finally, the mental health research system needs to change. We believe these three considerations will help us better move toward epistemic justice in mental health research.

The purpose of this quantitative study was to investigate nonprofit organizations’ satisfaction with volunteer retention during the COVID-19 pandemic. The participants were 74 nonprofit organizations’ leaders who participated in the online survey. The response rate was 10.6%. We found that the overall mean score for satisfaction with organizational retention of volunteers during the COVID-19 pandemic was 3.50 (SD = .98), and the importance of volunteer management practices was 3.52 (SD = .96). Most nonprofit organizations were proactive (38.8%) and reacted promptly (52.2%) while addressing the organizations’ response to the pandemic. Approximately 10.3% of the variation in satisfaction with organizational retention of volunteers during the COVID-19 pandemic could be explained by the importance of volunteer management practices and organizational response to the COVID-19 pandemic. However, within the final model, only one factor was a significant predictor of satisfaction with organizational retention of volunteers during the COVID-19 pandemic, namely, organizational response to the COVID-19 pandemic (β = -.304; p = .014). Recommendations for future research discussed. Implications for volunteer management and leadership studies faculty, University Extension educators, human resources practitioners, and local nonprofit organizations’ leaders are also presented.

Abstract Background There is a significant push to change the trajectory of youth mental ill-health and suicide globally. Ensuring that young people have access to services that meet their individual needs and are easily accessible is a priority. Genuine stakeholder engagement in mental health system design is critical to ensure that system strengthening is likely to be successful within these complex environments. There is limited literature describing engagement processes undertaken by research teams in mental health program implementation and planning. This protocol describes the methods that will be used to engage local communities using systems science methods to mobilize knowledge and action to strengthen youth mental health services. Methods Using participatory action research principles, the research team will actively engage with local communities to ensure genuine user-led participatory systems modelling processes and enhance knowledge mobilisation within research sites. Ensuring that culturally diverse and Aboriginal and Torres Strait Islander community voices are included will support this process. A rigorous site selection process will be undertaken to ensure that the community is committed and has capacity to actively engage in the research activities. Stakeholder engagement commences from the site selection process with the aim to build trust between researchers and key stakeholders. The research team will establish a variety of engagement resources and make opportunities available to each site depending on their local context, needs and audiences they wish to target during the process. Discussion This protocol describes the inclusive community engagement and knowledge mobilization process for the Right care, first time, where you live research Program. This Program will use an iterative and adaptive approach that considers the social, economic, and political context of each community and attempts to maximise research engagement. A theoretical framework for applying systems approaches to knowledge mobilization that is flexible will enable the implementation of a participatory action research approach. This protocol commits to a rigorous and genuine stakeholder engagement process that can be applied in mental health research implementation.

Abstract Background People with severe mental illnesses (SMI) such as schizophrenia die on average 15 to 20 years earlier than everyone else. Two thirds of these deaths are from preventable physical illnesses such as hypertension, cardiovascular disease, and diabetes, which are worsened by weight gain. Antipsychotics are associated with significant weight gain. In REalist Synthesis Of non-pharmacologicaL interVEntions (RESOLVE), a realist synthesis, combining primary and secondary data, will be used to understand and explain how, why, for whom, and in what contexts non-pharmacological interventions can help service users to manage antipsychotic-induced weight gain. Methods A five-step approach will be used to develop guidance: 1. Developing the initial programme theory An initial (candidate) programme theory, which sets out how and why outcomes occur within an intervention, will be developed. 2. Developing the search The initial programme theory will be refined using academic and grey literature. The proposed initial sampling frame are as follows: Context: people living with SMI, taking antipsychotics, different types of SMI. Intervention: non-pharmacological interventions. Mechanisms: triggered by the intervention. Outcomes e.g. weight, metabolic adverse events, quality of life, adherence, burden, economic. Searching for relevant documents will continue until sufficient data is found to conclude that the refined programme theory is coherent and plausible. Lived experience (service users) and stakeholder (practitioners) groups will provide feedback. 3. Selection, appraisal and data extraction Documents will be screened against inclusion and exclusion criteria. The text extracted from these documents will be coded as contexts, mechanisms and their relationships to outcomes. 4. Primary data collection Realist interviews with up to 30 service users and informal carers, and 20 practitioners will gather data to support, refute or refine the programme theory. 5. Data analysis A realist logic of analysis will be used to develop and refine the programme theory from secondary and primary data. The analysis will aim to identify practical intervention strategies to change contexts so that key mechanisms are triggered to produce desired outcomes. Guidance will be produced based on these strategies. Discussion This realist synthesis aims to develop guidance for service users and practitioners on the most appropriate interventional strategies to manage and limit antipsychotic weight gain. Systematic review registration PROSPERO: CRD42021268697

Background. Antimicrobial resistance (AMR) is a global public health threat. The wider implications of AMR, such as the impact of antibiotic resistance (ABR) on surgical procedures, are yet to be quantified. The objective of this study was to produce a conceptual modeling framework to provide a basis for estimating the current and potential future consequences of ABR for surgical procedures in England. Design. A framework was developed using literature-based evidence and structured expert elicitation. This was applied to populations undergoing emergency repair of the neck of the femur and elective colorectal resection surgery. Results. The framework captures the implications of increasing ABR by allowing for higher rates of surgical site infection (SSI) as the effectiveness of antibiotic prophylaxis wanes and worsened outcomes following SSIs to reflect reduced antibiotic treatment effectiveness. The expert elicitation highlights the uncertainty in quantifying the impact of ABR, reflected in the results. A hypothetical SSI rate increase of 14% in a person undergoing emergency repair of the femur could increase costs by 39% (−2% to 108% credible interval [CI]) and decrease quality-adjusted life-years by 11% (0.4% to 62% CI) over 15 y. Conclusions. The modeling framework is a starting point for addressing the implication of ABR on the outcomes and costs of surgeries. Due to clinical uncertainty highlighted in the expert elicitation process, the numerical outputs of the case studies should not be focused on but rather the framework itself, illustration of the evidence gaps, the benefit of expert elicitation in quantifying parameters with limited data, and the potential magnitude of the impact of ABR on surgical procedures. Implications. The framework can be used to support research surrounding the health and cost burden of ABR in England. Highlights The modeling framework is a starting point for assessing the health and cost impacts of antibiotic resistance on surgeries in England. Formulating a framework and synthesizing evidence to parameterize data gaps provides targets for future research. Once data gaps are addressed, this modeling framework can be used to feed into overall estimates of the health and cost burden of antibiotic resistance and evaluate control policies.

We consider the effect of including an active galactic nuclei (AGN) component when fitting spectral energy distributions of 109 spectroscopically confirmed z ≈ 3.5–12.5 galaxies with JWST. Remarkably, we find that the resulting cosmic star formation history is ≈0.4 dex lower at z ≳ 9.5 when an AGN component is included in the fitting. This alleviates previously reported excess star formation at z ≳ 9.5 compared to models based on typical baryon conversion efficiencies inside dark matter halos. We find that the individual stellar masses and star formation rates can be as much as ≈4 dex lower when fitting with an AGN component. These results highlight the importance of considering both stellar mass assembly and supermassive black hole growth when interpreting the light distributions of among the first galaxies to ever exist.

BackgroundAutomated virtual reality (VR) therapy has the potential to substantially increase access to evidence-based psychological treatments. The results of a multicenter randomized controlled trial showed that gameChange VR cognitive therapy reduces the agoraphobic avoidance of people diagnosed with psychosis, especially for those with severe avoidance. ObjectiveWe set out to use a peer research approach to explore participants’ experiences with gameChange VR therapy. This in-depth experiential exploration of user experience may inform the implementation in clinical services and future VR therapy development. MethodsPeer-led semistructured remote interviews were conducted with 20 people with a diagnosis of psychosis who had received gameChange as part of the clinical trial (ISRCTN17308399). Data were analyzed using interpretative phenomenological analysis and template analyses. A multiperspectival approach was taken to explore subgroups. Credibility checks were conducted with the study Lived Experience Advisory Panel. ResultsParticipants reported the substantial impact of anxious avoidance on their lives before the VR intervention, leaving some of them housebound and isolated. Those who were struggling the most with agoraphobic avoidance expressed the most appreciation for, and gains from, the gameChange therapy. The VR scenarios provided “a place to practise.” Immersion within the VR scenarios triggered anxiety, yet participants were able to observe this and respond in different ways than usual. The “security of knowing the VR scenarios are not real” created a safe place to learn about fears. The “balance of safety and anxiety” could be calibrated to the individual. The new learning made in VR was “taken into the real world” through practice and distilling key messages with support from the delivery staff member. ConclusionsAutomated VR can provide a therapeutic simulation that allows people diagnosed with psychosis to learn and embed new ways of responding to the situations that challenge them. An important process in anxiety reduction is enabling the presentation of stimuli that induce the original anxious fears yet allow for learning of safety. In gameChange, the interaction of anxiety and safety could be calibrated to provide a safe place to learn about fears and build confidence. This navigation of therapeutic learning can be successfully managed by patients themselves in an automated therapy, with staff support, that provides users with personalized control. The clinical improvements for people with severe anxious avoidance, the positive experience of VR, and the maintenance of a sense of control are likely to facilitate implementation.

We report the results of James Webb Space Telescope/NIRCam observations of 19 (sub)millimeter sources detected by the Atacama Large Millimeter Array (ALMA). The accurate ALMA positions allowed unambiguous identifications of their NIRCam counterparts. Taking gravitational lensing into account, these represent 16 distinct galaxies in three fields and constitute the largest sample of its kind to date. The counterparts’ spectral energy distributions cover from rest-frame ultraviolet to near-IR and provide photometric redshifts (1 < z < 4.5) and stellar masses ( M _* > 10 ^10.5 M _⊙ ), which are similar to submillimeter galaxies (SMGs) studied previously. However, our sample is fainter in (sub)millimeter than the classic SMG samples are, and our sources exhibit a wider range of properties. They have dust-embedded star formation rates as low as 10 M _⊙ yr ^−1 , and the sources populate both the star-forming main sequence and the quiescent categories. The deep NIRCam data allow us to study the rest-frame near-IR morphologies. Excluding two multiply imaged systems and one quasar, the majority of the remaining sources are disk-like and show either little or no disturbance. This suggests that secular growth is a potential route for the assembly of high-mass disk galaxies. While a few objects have large disks, the majority have small disks (median half-mass radius of 1.6 kpc). At this time, it is unclear whether this is due to the prevalence of small disks at these redshifts or some unknown selection effects of deep ALMA observations. A larger sample of ALMA sources with NIRCam observations will be able to address this question.

Antimicrobial resistance (AMR) may negatively impact surgery patients through reducing the efficacy of treatment of surgical site infections, also known as the “primary effects” of AMR. Previous estimates of the burden of AMR have largely ignored the potential “secondary effects,” such as changes in surgical care pathways due to AMR, such as different infection prevention procedures or reduced access to surgical procedures altogether, with literature providing limited quantifications of this potential burden. Former conceptual models and approaches for quantifying such impacts are available, though they are often high-level and difficult to utilize in practice. We therefore expand on this earlier work to incorporate heterogeneity in antimicrobial usage, AMR, and causative organisms, providing a detailed decision-tree-Markov-hybrid conceptual model to estimate the burden of AMR on surgery patients. We collate available data sources in England and describe how routinely collected data could be used to parameterise such a model, providing a useful repository of data systems for future health economic evaluations. The wealth of national-level data available for England provides a case study in describing how current surveillance and administrative data capture systems could be used in the estimation of transition probability and cost parameters. However, it is recommended that such data are utilized in combination with expert opinion (for scope and scenario definitions) to robustly estimate both the primary and secondary effects of AMR over time. Though we focus on England, this discussion is useful in other settings with established and/or developing infectious diseases surveillance systems that feed into AMR National Action Plans.

The Research Chapter (Chapter 8) of the English Surveillance Programme for Antimicrobial Utilisation and Resistance (ESPAUR) Report 2021–2022 showcases the research that has been undertaken and that is ongoing at the UK Health Security Agency (UKHSA) in the field of healthcare-associated infections (HCAIs) and antimicrobial resistance (AMR) from April 2021 to March 2022 [...]

Background The high prevalence of mental distress among university students is gaining academic, policy and public attention. As the volume of research into student mental health increases, it is important to involve students to ensure that the evidence produced can translate into meaningful improvements. Aims For the first time, we consult UK students about their research priorities on student mental health. Method This priority setting exercise involved current UK university students who were asked to submit three research questions relating to student mental health. Responses were aggregated into themes through content analysis and considered in the context of existing research. Students were involved throughout the project, including inception, design, recruitment, analysis and dissemination. Results UK university students (N = 385) submitted 991 questions, categorised into seven themes: epidemiology, causes and risk factors, academic factors and work–life balance, sense of belonging, intervention and services, mental health literacy and consequences. Across themes, respondents highlighted the importance of understanding the experience of minority groups. Conclusions Students are interested in understanding the causes and consequences of poor mental health at university, across academic and social domains. They would like to improve staff and students’ knowledge about mental health, and have access to evidence-based support. Future research should take a broad lens to evaluate interventions; considering how services are designed and delivered, and investigating institutional and behavioural barriers to accessibility, including how this varies across different groups within the student population.

Summary: Many infection prevention and control (IPC) interventions have been adopted by hospitals to limit nosocomial transmission of SARS-CoV-2. The aim of this systematic review is to identify evidence on the effectiveness of these interventions. We conducted a literature search of five databases (OVID MEDLINE, Embase, CENTRAL, COVID-19 Portfolio (pre-print), Web of Science). SWIFT ActiveScreener software was used to screen English titles and abstracts published between 1st January 2020 and 6th April 2021. Intervention studies, defined by Cochrane Effective Practice and Organisation of Care, that evaluated IPC interventions with an outcome of SARS-CoV-2 infection in either patients or healthcare workers were included. Personal protective equipment (PPE) was excluded as this intervention had been previously reviewed. Risks of bias were assessed using the Cochrane tool for randomised trials (RoB2) and non-randomized studies of interventions (ROBINS-I). From 23,156 screened articles, we identified seven articles that met the inclusion criteria, all of which evaluated interventions to prevent infections in healthcare workers and the majority of which were focused on effectiveness of prophylaxes. Due to heterogeneity in interventions, we did not conduct a meta-analysis. All agents used for prophylaxes have little to no evidence of effectiveness against SARS-CoV-2 infections. We did not find any studies evaluating the effectiveness of interventions including but not limited to screening, isolation and improved ventilation. There is limited evidence from interventional studies, excluding PPE, evaluating IPC measures for SARS-CoV-2. This review calls for urgent action to implement such studies to inform policies to protect our most vulnerable populations and healthcare workers.

Introducción. Que la actitud hacia el aprendizaje de los estudiantes presenta impacto sobre el aprendizaje y el rendimiento académico ha sido ampliamente demostrado. Determinar los factores que influyen sobre la actitud de los estudiantes hacia el aprendizaje resulta muy relevante para cambiar actitudes negativas o generar actitudes positivas, que favorezcan su disposición para aprender y rendimiento. El presente estudio tiene por objetivo determinar los factores que influyen en la actitud hacia el aprendizaje en asignaturas de matemáticas en primer año de la carrera de Ingeniería, en una universidad chilena. Método. El método utilizado contempló el desarrollo de un instrumento de medición de factores relevantes previamente reportados en la literatura, el cual se aplicó a 873 estudiantes de primer año de la Facultad de Ingeniería y Ciencias de la Universidad Diego Portales en Chile, que cursaron las asignaturas de Cálculo 1 y Álgebra y Geometría. Se formula un modelo conceptual que es analizado mediante las herramientas de Ecuaciones estructurales, bajo el método Mínimos Cuadrados Parciales (Partial Least Squares: PLS). Resultados. Los resultados obtenidos indican que los factores, según su grado de influencia: Motivación por aprender, Metodología de aprendizaje, Idoneidad del profesor y percepción de Utilidad de la asignatura, influyen positivamente en la Actitud hacia el aprendizaje, la que influye a su vez en el rendimiento académico, a través de un factor que captura el Aprendizaje autodeclarado del estudiante. Discusión. Se enfatiza en la importancia de conocer los factores que influyen sobre la actitud hacia el aprendizaje, para establecer acciones que influyan sobre estos factores que podrían favorecer el aprendizaje y un mejor rendimiento.

Abstract Background To reduce inappropriate antibiotic use, public health campaigns often provide fear-based information about antimicrobial resistance (AMR). Meta-analyses have found that fear-based campaigns in other contexts are likely to be ineffective unless respondents feel confident they can carry out the recommended behaviour (‘self-efficacy’). This study aimed to test the likely impact of fear-based messages, with and without empowering self-efficacy elements, on patient consultations/antibiotic requests for influenza-like illnesses, using a randomised design. Methods We hypothesised that fear-based messages containing empowering information about self-management without antibiotics would be more effective than fear alone, particularly in a pre-specified subgroup with low AMR awareness. Four thousand respondents from an online panel, representative of UK adults, were randomised to receive three different messages about antibiotic use and AMR, designed to induce fear about AMR to varying degrees. Two messages (one ‘strong-fear’, one ‘mild-fear’) also contained empowering information regarding influenza-like symptoms being easily self-managed without antibiotics. The main outcome measures were self-reported effect of information on likelihood of visiting a doctor and requesting antibiotics, for influenza-like illness, analysed separately according to whether or not the AMR information was ‘very/somewhat new’ to respondents, pre-specified based on a previous (non-randomised) survey. Results The ‘fear-only’ message was ‘very/somewhat new’ to 285/1000 (28.5%) respondents, ‘mild-fear-plus-empowerment’ to 336/1500 (22.4%), and ‘strong-fear-plus-empowerment’ to 388/1500 (25.9%) (p = 0.002). Of those for whom the respective information was ‘very/somewhat new’, only those given the ‘strong-fear-plus-empowerment’ message said they would be less likely to request antibiotics if they visited a doctor for an influenza-like illness (p

Abstract Background Antibiotic resistance (ABR) poses a major threat to health and economic wellbeing worldwide. Reducing ABR will require government interventions to incentivise antibiotic development, prudent antibiotic use, infection control and deployment of partial substitutes such as rapid diagnostics and vaccines. The scale of such interventions needs to be calibrated to accurate and comprehensive estimates of the economic cost of ABR. Methods A conceptual framework for estimating costs attributable to ABR was developed based on previous literature highlighting methodological shortcomings in the field and additional deductive epidemiological and economic reasoning. The framework was supplemented by a rapid methodological review. Results The review identified 110 articles quantifying ABR costs. Most were based in high-income countries only (91/110), set in hospitals (95/110), used a healthcare provider or payer perspective (97/110), and used matched cohort approaches to compare costs of patients with antibiotic-resistant infections and antibiotic-susceptible infections (or no infection) (87/110). Better use of methods to correct biases and confounding when making this comparison is needed. Findings also need to be extended beyond their limitations in (1) time (projecting present costs into the future), (2) perspective (from the healthcare sector to entire societies and economies), (3) scope (from individuals to communities and ecosystems), and (4) space (from single sites to countries and the world). Analyses of the impact of interventions need to be extended to examine the impact of the intervention on ABR, rather than considering ABR as an exogeneous factor. Conclusions Quantifying the economic cost of resistance will require greater rigour and innovation in the use of existing methods to design studies that accurately collect relevant outcomes and further research into new techniques for capturing broader economic outcomes.

Using the first epoch of four-band NIRCam observations obtained by the James Webb Space Telescope (JWST) Prime Extragalactic Areas for Reionization and Lensing Science Program in the Spitzer IRAC Dark Field, we search for F150W and F200W dropouts. In 14.2 arcmin ^2 , we have found eight F150W dropouts and eight F200W dropouts, all brighter than 27.5 mag (the brightest being ∼24 mag) in the band to the red side of the break. As they are detected in multiple bands, these must be real objects. Their nature, however, is unclear, and characterizing their properties is important for realizing the full potential of JWST. If the observed color decrements are due to the Lyman break, these objects should be at z ≳ 11.7 and z ≳ 15.4, respectively. The color diagnostics show that at least four F150W dropouts are far away from the usual contaminators encountered in dropout searches (red galaxies at much lower redshifts or brown dwarf stars). While the diagnostics of the F200W dropouts are less certain due to the limited number of passbands, at least one of them is likely not a known type of contaminant, and the rest are consistent with either high-redshift galaxies with evolved stellar populations or old galaxies at z ≈ 3–8. If a significant fraction of our dropouts are indeed at z ≳ 12, we have to face the severe problem of explaining their high luminosities and number densities. Spectroscopic identifications of such objects are urgently needed.

The Time Domain Field (TDF) near the North Ecliptic Pole in JWST’s continuous-viewing zone will become a premier “blank field” for extragalactic science. JWST/NIRCam data in a 16 arcmin ^2 portion of the TDF identify 4.4 μ m counterparts for 62 of 63 3 GHz sources with S (3 GHz) > 5 μ Jy. The one unidentified radio source may be a lobe of a nearby Seyfert galaxy, or it may be an infrared-faint radio source. The bulk properties of the radio-host galaxies are consistent with those found by previous work: redshifts range from 0.14–4.4 with a median redshift of 1.33. The radio emission arises primarily from star formation in ∼2/3 of the sample and from an active galactic nucleus (AGN) in ∼1/3, but just over half the sample shows evidence for an AGN either in the spectral energy distribution or by radio excess. All but three counterparts are brighter than magnitude 23 AB at 4.4 μ m, and the exquisite resolution of JWST identifies correct counterparts for sources for which observations with lower angular resolution would misidentify a nearby bright source as the counterpart when the correct one is faint and red. Up to 11% of counterparts might have been unidentified or misidentified absent NIRCam observations.

With its unprecedented sensitivity and spatial resolution, the James Webb Space Telescope (JWST) has opened a new window for time-domain discoveries in the infrared. Here we report observations in the only field that has received four epochs (spanning 126 days) of JWST NIRCam observations in Cycle 1. This field is toward MACS J0416.1−2403, which is a rich galaxy cluster at redshift z = 0.4 and is one of the Hubble Frontier Fields. We have discovered 14 transients from these data. Twelve of these transients happened in three galaxies (with z = 0.94, 1.01, and 2.091) crossing a lensing caustic of the cluster, and these transients are highly magnified by gravitational lensing. These 12 transients are likely of a similar nature to those previously reported based on the Hubble Space Telescope (HST) data in this field, i.e., individual stars in the highly magnified arcs. However, these 12 could not have been found by HST because they were too red and too faint. The other two transients are associated with background galaxies ( z = 2.205 and 0.7093) that are only moderately magnified, and they are likely supernovae. They indicate a demagnified supernova surface density, when monitored at a time cadence of a few months to a ∼3–4 μ m survey limit of AB ∼28.5 mag, of ∼0.5 arcmin ^−2 integrated to z ≈ 2. This survey depth is beyond the capability of HST but can be easily reached by JWST.

We identify 71 distant stars in James Webb Space Telescope/NIRCam early release observations (ERO) images of the field of galaxy cluster SMACS J0723.3-7327 (SMACS 0723). Given the relatively small (∼10°) angular separation between SMACS 0723 and the Large Magellanic Cloud (LMC), it is likely that these stars are associated with the LMC outskirts or the Leading Arm. This is further bolstered by a spectral energy distribution (SED) analysis, which suggests an excess of stars at a physical distance of 40–100 kpc, consistent with being associated with or located behind the Magellanic system. In particular, we find that the overall surface density of stars brighter than 27.0 mag in the field of SMACS 0723 is ∼2.3 times that of stars in a blank field with similar Galactic latitude (the North Ecliptic Pole Time Domain Field), and that the density of stars in the SMACS 0723 field with SED-derived distances consistent with the Magellanic system is ∼6.1 times larger than that of the blank field. The candidate stars at these distances are consistent with a stellar population at the same distance modulus with [Fe/H] = −1.0 and an age of ∼5.0 Gyr. On the assumption that all of the 71 stars are associated with the LMC, then the stellar density of the LMC at the location of the SMACS 0723 field is ∼740 stars kpc ^−3 , which helps trace the density of stars in the LMC outskirts.

We present a multiwavelength analysis using the Submillimeter Array (SMA), James Clerk Maxwell Telescope, NOEMA, JWST, the Hubble Space Telescope (HST), and the Spitzer Space Telescope of two dusty strongly star-forming galaxies, 850.1 and 850.2, seen through the massive cluster lens A 1489. These SMA-located sources both lie at z = 4.26 and have bright dust continuum emission, but 850.2 is a UV-detected Lyman-break galaxy, while 850.1 is undetected at ≲ 2 μ m, even with deep JWST/NIRCam observations. We investigate their stellar, interstellar medium, and dynamical properties, including a pixel-level spectral energy distribution analysis to derive subkiloparsec-resolution stellar-mass and A _V maps. We find that 850.1 is one of the most massive and highly obscured, A _V ∼ 5, galaxies known at z > 4 with M _* ∼10 ^11.8 M _⊙ (likely forming at z > 6), and 850.2 is one of the least massive and least obscured, A _V ∼ 1, members of the z > 4 dusty star-forming population. The diversity of these two dust-mass-selected galaxies illustrates the incompleteness of galaxy surveys at z ≳ 3–4 based on imaging at ≲ 2 μ m, the longest wavelengths feasible from HST or the ground. The resolved mass map of 850.1 shows a compact stellar-mass distribution, ${R}_{{\rm{e}}}^{\mathrm{mass}}$ ∼1 kpc, but its expected evolution means that it matches both the properties of massive, quiescent galaxies at z ∼ 1.5 and ultramassive early-type galaxies at z ∼ 0. We suggest that 850.1 is the central galaxy of a group in which 850.2 is a satellite that will likely merge in the near future. The stellar morphology of 850.1 shows arms and a linear bar feature that we link to the active dynamical environment it resides within.

Gradients in the mass-to-light ratio of distant galaxies impede our ability to characterize their size and compactness. The long-wavelength filters of JWST’s NIRCam offer a significant step forward. For galaxies at Cosmic Noon ( z ∼ 2), this regime corresponds to the rest-frame near-infrared, which is less biased toward young stars and captures emission from the bulk of a galaxy’s stellar population. We present an initial analysis of an extraordinary lensed dusty star-forming galaxy at z = 2.3 behind the El Gordo cluster ( z = 0.87), named El Anzuelo (“The Fishhook”) after its partial Einstein-ring morphology. The far-UV to near-IR spectral energy distribution suggests an intrinsic star formation rate of ${81}_{-2}^{+7}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}$ and dust attenuation A _V ≈ 1.6, in line with other DSFGs on the star-forming main sequence. We develop a parametric lens model to reconstruct the source-plane structure of dust imaged by the Atacama Large Millimeter/submillimeter Array, far-UV to optical light from Hubble, and near-IR imaging with 8 filters of JWST/NIRCam, as part of the Prime Extragalactic Areas for Reionization and Lensing Science program. The source-plane half-light radius is remarkably consistent from ∼1 to 4.5 μ m, despite a clear color gradient where the inferred galaxy center is redder than the outskirts. We interpret this to be the result of both a radially decreasing gradient in attenuation and substantial spatial offsets between UV- and IR-emitting components. A spatial decomposition of the SED reveals modestly suppressed star formation in the inner kiloparsec, which suggests that we are witnessing the early stages of inside-out quenching.

A full understanding of how unusually large ultradiffuse galaxies (UDGs) fit into our conventional theory of galaxy formation remains elusive, despite the large number of objects identified locally. A natural extension of UDG research is the study of similar galaxies at higher redshift to establish how their properties may evolve over time. However, this has been a challenging task given how severely systematic effects and cosmological surface brightness dimming inhibit our ability to analyze low surface brightness galaxies at high z . Here, we present a sample of low stellar surface density galaxies (LDGs) at moderate redshift, likely the progenitors of local UDGs, identified using deep near-IR observations of the El Gordo cluster at z = 0.87 with JWST. By stacking eight NIRCAM filters, we reach an apparent surface brightness sensitivity of 24.59 mag arcsec ^−2 , which is faint enough to be complete to the bright end of the LDG population. Our analysis identifies significant differences between this population and UDGs observed locally, such as their color and size distributions, which suggest that the UDG progenitors at high z are bluer and more extended than UDGs at z = 0. This suggests that multiple mechanisms are responsible for the UDG formation and that prolonged transformation of cluster dwarfs is not a primary UDG formation mechanism at high z . Furthermore, we find a slight overabundance of LDGs in El Gordo, and, in contrast to findings in local clusters, our analysis does not show a deficit of LDGs in the center of El Gordo, implying that tidal destruction of LDGs is significant between z = 0.87 and z = 0.