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BackgroundSMS text messages through mobile phones are a common means of interpersonal communication. SMS text message surveys are gaining traction in health care and research due to their feasibility and patient acceptability. However, challenges arise in implementing SMS text message surveys, especially when targeting marginalized populations, because of barriers to accessing phones and data as well as communication difficulties. In primary care, traditional surveys (paper-based and online) often face low response rates that are particularly pronounced among disadvantaged groups due to financial limitations, language barriers, and time constraints. ObjectiveThis study aimed to investigate the potential of SMS text message–based patient recruitment and surveys within general practices situated in lower socioeconomic areas. This study was nested within the Reducing Alcohol-Harm in General Practice project that aimed to reduce alcohol-related harm through screening in Australian general practice. MethodsThis study follows a 2-step SMS text message data collection process. An initial SMS text message with an online survey link was sent to patients, followed by subsequent surveys every 3 months for consenting participants. Interviews were conducted with the local primary health network organization staff, the participating practice staff, and the clinicians. The qualitative data were analyzed using constructs from the Consolidated Framework for Implementation Research. ResultsOut of 6 general practices, 4 were able to send SMS text messages to their patients. The initial SMS text message was sent to 8333 patients and 702 responses (8.2%) were received, most of which were not from a low-income group. This low initial response was in contrast to the improved response rate to the ongoing 3-month SMS text message surveys (55/107, 51.4% at 3 months; 29/67, 43.3% at 6 months; and 44/102, 43.1% at 9 months). We interviewed 4 general practitioners, 4 nurses, and 4 administrative staff from 5 of the different practices. Qualitative data uncovered barriers to engaging marginalized groups including limited smartphone access, limited financial capacity (telephone, internet, and Wi-Fi credit), language barriers, literacy issues, mental health conditions, and physical limitations such as manual dexterity and vision issues. Practice managers and clinicians suggested strategies to overcome these barriers, including using paper-based surveys in trusted spaces, offering assistance during survey completion, and offering honoraria to support participation. ConclusionsWhile SMS text message surveys for primary care research may be useful for the broader population, additional efforts are required to ensure the representation and involvement of marginalized groups. More intensive methods such as in-person data collection may be more appropriate to capture the voice of low-income groups in primary care research. International Registered Report Identifier (IRRID)RR2-10.3399/BJGPO.2021.0037

Background The COVID-19 pandemic disrupted cardiovascular disease management in primary care in England.Objective To describe the impact of the pandemic on blood pressure screening and hypertension management based on a national quality of care scheme (Quality and Outcomes Framework, QOF) across key demographic, regional and clinical subgroups.Methods With NHS England approval, a population-based cohort study was conducted using OpenSAFELY-TPP on 25.2 million NHS patients registered at general practices (March 2019 to March 2023). We examined monthly changes in recorded blood pressure screening in the preceding 5 years in patients aged ≥45 years and recorded the hypertension prevalence and the percentage of patients treated to target (≤140/90 mmHg for patients aged ≤79 years and ≤150/90 mmHg for patients aged ≥80 years) in the preceding 12 months.Results The percentage of patients aged ≥45 years who had blood pressure screening recorded in the preceding 5 years decreased from 90% (March 2019) to 85% (March 2023). Recorded hypertension prevalence was relatively stable at 15% throughout the study period. The percentage of patients with a record of hypertension treated to target in the preceding 12 months reduced from a maximum of 71% (March 2020) to a minimum of 47% (February 2021) in patients aged ≤79 years and from 85% (March 2020) to a minimum of 58% (February 2021) in patients aged ≥80 years before recovery. Blood pressure screening rates in the preceding 5 years remained stable in older people, patients with recorded learning disability or care home status.Conclusions The pandemic substantially disrupted hypertension management QOF indicators, which is likely attributable to general reductions of blood pressure measurement including screening. OpenSAFELY can be used to continuously monitor changes in national quality-of-care schemes to identify changes in key clinical subgroups early and support prioritisation of recovery from care disrupted by COVID-19.

Objective To investigate the effect of the covid-19 pandemic on the number of patients with group A streptococcal infections and related antibiotic prescriptions.Design Retrospective cohort study in England using OpenSAFELY-TPP.Setting Primary care practices in England that used TPP SystmOne software, 1 January 2018 to 31 March 2023, with the approval of NHS England.Participants Patients registered at a TPP practice at the start of each month of the study period. Patients with missing data for sex or age were excluded, resulting in a population of 23 816 470 in January 2018, increasing to 25 541 940 by March 2023.Main outcome measures Monthly counts and crude rates of patients with group A streptococcal infections (sore throat or tonsillitis, scarlet fever, and invasive group A streptococcal infections), and recommended firstline, alternative, and reserved antibiotic prescriptions linked with a group A streptococcal infection before (pre-April 2020), during, and after (post-April 2021) covid-19 restrictions. Maximum and minimum count and rate for each infectious season (time from September to August), as well as the rate ratio of the 2022-23 season compared with the last comparably high season (2017-18).Results The number of patients with group A streptococcal infections, and antibiotic prescriptions linked to an indication of group A streptococcal infection, peaked in December 2022, higher than the peak in 2017-18. The rate ratios for monthly sore throat or tonsillitis (possible group A streptococcal throat infection), scarlet fever, and invasive group A streptococcal infection in 2022-23 relative to 2017-18 were 1.39 (95% confidence interval (CI) 1.38 to 1.40), 2.68 (2.59 to 2.77), and 4.37 (2.94 to 6.48), respectively. The rate ratio for prescriptions of first line, alternative, and reserved antibiotics to patients with group A streptococcal infections in 2022-23 relative to 2017-18 were 1.37 (95% CI 1.35 to 1.38), 2.30 (2.26 to 2.34), and 2.42 (2.24 to 2.61), respectively. For individual antibiotic prescriptions in 2022-23, azithromycin showed the greatest relative increase versus 2017-18, with a rate ratio of 7.37 (6.22 to 8.74). This finding followed a marked decrease in the recording of patients with group A streptococcal infections and associated prescriptions during the period of covid-19 restrictions where the maximum count and rates were lower than any minimum rates before the covid-19 pandemic.Conclusions Recording of rates of scarlet fever, sore throat or tonsillitis, and invasive group A streptococcal infections, and associated antibiotic prescribing, peaked in December 2022. Primary care data can supplement existing infectious disease surveillance through linkages with relevant prescribing data and detailed analysis of clinical and demographic subgroups.

Summary: Male infertility is a recognized side effect of chemoradiotherapy. Extant spermatogonial stem cells (SSCs) may act as originators for any subsequent recovery. However, which type of SSCs, the mechanism by which they survive and resist toxicity, and how they act to restart spermatogenesis remain largely unknown. Here, we identify a small population of Set domain-containing protein 4 (Setd4)-expressing SSCs that occur in a relatively dormant state in the mouse seminiferous tubule. Extant beyond high-dose chemoradiotherapy, these cells then activate to recover spermatogenesis. Recovery fails when Setd4+ SSCs are deleted. Confirmed to be of fetal origin, these Setd4+ SSCs are shown to facilitate early testicular development and also contribute to steady-state spermatogenesis in adulthood. Upon activation, chromatin remodeling increases their genome-wide accessibility, enabling Notch1 and Aurora activation with corresponding silencing of p21 and p53. Here, Setd4+ SSCs are presented as the originators of both testicular development and spermatogenesis recovery in chemoradiotherapy-induced infertility.

Nucleolar morphology is a well-established indicator of ribosome biogenesis activity that has served as the foundation of many screens investigating ribosome production. Missing from this field of study is a broad-scale investigation of the regulation of ribosomal DNA morphology, despite the essential role of rRNA gene transcription in modulating ribosome output. We hypothesized that the morphology of rDNA arrays reflects ribosome biogenesis activity. We established GapR-GFP, a prokaryotic DNA-binding protein that recognizes transcriptionally-induced overtwisted DNA, as a live visual fluorescent marker for quantitative analysis of rDNA organization in Schizosaccharomyces pombe. We found that the morphology-which we refer to as spatial organization-of the rDNA arrays is dynamic throughout the cell cycle, under glucose starvation, RNA pol I inhibition, and TOR activation. Screening the haploid S. pombe Bioneer deletion collection for spatial organization phenotypes revealed large ribosomal protein (RPL) gene deletions that alter rDNA organization. Further work revealed RPL gene deletion mutants with altered rDNA organization also demonstrate resistance to the TOR inhibitor Torin1. A genetic analysis of signaling pathways essential for this resistance phenotype implicated many factors including a conserved MAPK, Pmk1, previously linked to extracellular stress responses. We propose RPL gene deletion triggers altered rDNA morphology due to compensatory changes in ribosome biogenesis via multiple signaling pathways, and we further suggest compensatory responses may contribute to human diseases such as ribosomopathies. Altogether, GapR-GFP is a powerful tool for live visual reporting on rDNA morphology under myriad conditions.

Summary: Background: Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe the incidence and differences in demographic and clinical characteristics in recorded long COVID in primary care records in England. Methods: With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. Using OpenSAFELY, we calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and adjusted (for age, sex, 9 NHS regions of England, and the dominant variant circulating) rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. Findings: We identified a total of 55,465 people recorded to have long COVID over the study period, which included 20,025 diagnoses codes and 35,440 codes for further assessment. The incidence of new long COVID records increased steadily over 2021, and declined over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5–179) and 100.5 in men (99.5–102). The majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 or more weeks before the long COVID record. Interpretation: In this descriptive study, EHR recorded long COVID was very low between 2020 and 2023, and incident records of long COVID declined over 2022. Using EHR diagnostic or referral codes unfortunately has major limitations in identifying and ascertaining true cases and timing of long COVID. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Summary: Background: Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. We aimed to evaluate and estimate the differences in health impacts of long COVID across sociodemographic categories and quantify this in Quality-Adjusted Life-Years (QALYs), widely used measures across health systems. Methods: With the approval of NHS England, we utilised OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. Findings: The total OpenPROMPT cohort consisted of 7575 individuals who consented to data collection, with which we used data from 6070 participants who completed a baseline research questionnaire where 24.6% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a higher likelihood or odds of reporting loss in quality-of-life (Odds Ratio (OR): 4.7, 95% CI: 3.72–5.93) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 17.7, 95% CI: 10.37–30.33) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. Interpretation: We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Background: The COVID-19 pandemic has had a significant impact on delivery of NHS care. We have developed the OpenSAFELY Service Restoration Observatory (SRO) to develop key measures of primary care activity and describe the trends in these measures throughout the COVID-19 pandemic. Methods: With the approval of NHS England, we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care electronic health record (EHR) data on 48 million adults. Results: We produced 11 measures reflective of clinical activity in general practice. A substantial drop in activity was observed in all measures at the outset of the COVID-19 pandemic. By April 2021, the median rate had recovered to within 15% of the median rate in April 2019 in six measures. The remaining measures showed a sustained drop, ranging from a 18.5% reduction in medication reviews to a 42.0% reduction in blood pressure monitoring. Three measures continued to show a sustained drop by December 2021. Conclusions: The COVID-19 pandemic was associated with a substantial change in primary care activity across the measures we developed, with recovery in most measures. We delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. We will continue to expand the set of key measures to be routinely monitored using our publicly available NHS OpenSAFELY SRO dashboards with near real-time data. Funding: This research used data assets made available as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20058).The OpenSAFELY Platform is supported by grants from the Wellcome Trust (222097/Z/20/Z); MRC (MR/V015757/1, MC_PC-20059, MR/W016729/1); NIHR (NIHR135559, COV-LT2-0073), and Health Data Research UK (HDRUK2021.000, 2021.0157).

Summary: Background: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. Methods: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. Findings: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. Interpretation: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. Funding: LSHTM COVID-19 Response Grant (DONAT15912).

[This corrects the article DOI: 10.1371/journal.pone.0259299.].

The built environment sector is responsible for almost one-third of the world's final energy consumption. Hence, seeking plausible solutions to minimise building energy demands and mitigate adverse environmental impacts is necessary. Artificial intelligence (AI) techniques such as machine and deep learning have been increasingly and successfully applied to develop solutions for the built environment. This review provided a critical summary of the existing literature on the machine and deep learning methods for the built environment over the past decade, with special reference to holistic approaches. Different AI-based techniques employed to resolve interconnected problems related to heating, ventilation and air conditioning (HVAC) systems and enhance building performances were reviewed, including energy forecasting and management, indoor air quality and occupancy comfort/satisfaction prediction, occupancy detection and recognition, and fault detection and diagnosis. The present study explored existing AI-based techniques focusing on the framework, methodology, and performance. The literature highlighted that selecting the most suitable machine learning and deep learning model for solving a problem could be challenging. The recent explosive growth experienced by the research area has led to hundreds of machine learning algorithms being applied to building performance-related studies. The literature showed that existing research studies considered a wide range of scope/scales (from an HVAC component to urban areas) and time scales (minute to year). This makes it difficult to find an optimal algorithm for a specific task or case. The studies also employed a wide range of evaluation metrics, adding to the challenge. Further developments and more specific guidelines are required for the built environment field to encourage best practices in evaluating and selecting models. The literature also showed that while machine and deep learning had been successfully applied in building energy efficiency research, most of the studies are still at the experimental or testing stage, and there are limited studies which implemented machine and deep learning strategies in actual buildings and conducted the post-occupancy evaluation.

Numerous genes required for sexual reproduction remain to be identified even in simple model species like Schizosaccharomyces pombe. To address this, we developed an assay in S. pombe that couples transposon mutagenesis with high-throughput sequencing (TN-seq) to quantitatively measure the fitness contribution of nonessential genes across the genome to sexual reproduction. This approach identified 532 genes that contribute to sex, including more than 200 that were not previously annotated to be involved in the process, of which more than 150 have orthologs in vertebrates. Among our verified hits was an uncharacterized gene, ifs1 (important for sex), that is required for spore viability. In two other hits, plb1 and alg9, we observed a novel mutant phenotype of poor spore health wherein viable spores are produced, but the spores exhibit low fitness and are rapidly outcompeted by wild type. Finally, we fortuitously discovered that a gene previously thought to be essential, sdg1 (social distancing gene), is instead required for growth at low cell densities and can be rescued by conditioned medium. Our assay will be valuable in further studies of sexual reproduction in S. pombe and identifies multiple candidate genes that could contribute to sexual reproduction in other eukaryotes, including humans.

The use of fixed or scheduled setpoints combined with varying occupancy patterns in buildings could lead to spaces being over or under-conditioned, which may lead to significant waste in energy consumption. The present study aims to develop a vision-based deep learning method for real-time occupancy activity detection and recognition. The method enables predicting and generating real-time heat gain data, which can inform building energy management systems and heating, ventilation, and air-conditioning (HVAC) controls. A faster region-based convolutional neural network was developed, trained and deployed to an artificial intelligence-powered camera. For the initial analysis, an experimental test was performed within a selected case study building's office space. Average detection accuracy of 92.2% was achieved for all activities. Using building energy simulation, the case study building was simulated with both ‘static’ and deep learning influenced profiles to assess the potential energy savings that can be achieved. The work has shown that the proposed approach can better estimate the occupancy internal heat gains for optimising the operations of building HVAC systems.

Here we present a machine-learning-based method for utilizing traditional ocean-viewing satellites to perform automated atmospheric correction of nanosatellite data. These sensor convolution techniques are required because nanosatellites do not usually possess the wavelength combinations required to atmospherically correct upwelling radiance data for oceanographic applications; however, nanosatellites do provide superior ground-viewing spatial resolution (~3 m). Coincident multispectral data from the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (Suomi NPP VIIRS; referred to herein as “VIIRS”) were used to remove atmospheric contamination at each of the nanosatellite’s visible wavelengths to yield an estimate of spectral water-leaving radiance [Lw(l)], which is the basis for surface ocean optical products. Machine learning (ML) algorithms (KNN, decision tree regressors) were applied to determine relationships between Lw and top-of-atmosphere (Lt)/Rayleigh (Lr) radiances within VIIRS training data, and then applied to test cases for (1) the Marine Optical Buoy (MOBY) in Hawaii and (2) the AErosol RObotic Network Ocean Color (AERONET-OC), Venice, Italy. For the test cases examined, ML-based methods appeared to improve statistical results when compared to alternative dark spectrum fitting (DSF) methods. The results suggest that ML-based sensor convolution techniques offer a viable path forward for the oceanographic application of nanosatellite data streams.

Image-based cell classification has become a common tool to identify phenotypic changes in cell populations. However, this methodology is limited to organisms possessing well-characterized species-specific reagents (e.g., antibodies) that allow cell identification, clustering, and convolutional neural network (CNN) training. In the absence of such reagents, the power of image-based classification has remained mostly off-limits to many research organisms. We have developed an image-based classification methodology we named Image3C (Image-Cytometry Cell Classification) that does not require species-specific reagents nor pre-existing knowledge about the sample. Image3C combines image-based flow cytometry with an unbiased, high-throughput cell clustering pipeline and CNN integration. Image3C exploits intrinsic cellular features and non-species-specific dyes to perform de novo cell composition analysis and detect changes between different conditions. Therefore, Image3C expands the use of image-based analyses of cell population composition to research organisms in which detailed cellular phenotypes are unknown or for which species-specific reagents are not available.

Accurate maps of species ranges are essential to inform conservation, but time-consuming to produce and update. Given the pace of change of knowledge about species distributions and shifts in ranges under climate change and land use, a need exists for timely mapping approaches that enable batch processing employing widely available data. We develop a systematic approach of batch-processing range maps and derived Area of Habitat maps for terrestrial bird species with published ranges below 125,000 km2 in Central and South America. (Area of Habitat is the habitat available to a species within its range.) We combine existing range maps with the rapidly expanding crowd-sourced eBird data of presences and absences from frequently surveyed locations, plus readily accessible, high resolution satellite data on forest cover and elevation to map the Area of Habitat available to each species. Users can interrogate the maps produced to see details of the observations that contributed to the ranges. Previous estimates of Areas of Habitat were constrained within the published ranges and thus were, by definition, smaller-typically about 30%. This reflects how little habitat within suitable elevation ranges exists within the published ranges. Our results show that on average, Areas of Habitat are 12% larger than published ranges, reflecting the often-considerable extent that eBird records expand the known distributions of species. Interestingly, there are substantial differences between threatened and non-threatened species. Some 40% of Critically Endangered, 43% of Endangered, and 55% of Vulnerable species have Areas of Habitat larger than their published ranges, compared with 31% for Near Threatened and Least Concern species. The important finding for conservation is that threatened species are generally more widespread than previously estimated.

A new concept of non-rapid eye movement (NREM) and rapid eye movement (REM) sleep is proposed, that of multi-component integrative states that define stable and unstable sleep, respectively, NREMS, NREMUS REMS, and REMUS. Three complementary data sets are used: obstructive sleep apnea (20), healthy subjects (11), and high loop gain sleep apnea (50). We use polysomnography (PSG) with beat-to-beat blood pressure monitoring, and electrocardiogram (ECG)-derived cardiopulmonary coupling (CPC) analysis to demonstrate a bimodal, rather than graded, characteristic of NREM sleep. Stable NREM (NREMS) is characterized by high probability of occurrence of the

Juxtaglomerular cell tumor (JGCT) is a rare tumor. It is a renin-secreting neoplasm that can cause secondary hypertension. It generally affects adolescents and young adults. Patients typically present with chief complaint of headache leading to a diagnosis of severe hypertension. Herein we report a case of JGCT in a 19-year-old Asian female who initially presented with neurological deficits, and was subsequently found to be hypertensive. She had elevated levels of renin and aldosterone with hypokalemia, and responded to renin inhibitors and an aldosterone antagonist. CT scan demonstrated a 2.2 cm left renal tumor. A partial nephrectomy was performed. Histology showed a well-circumscribed tumor consisting of sheets of polygonal to ovoid cells with eosinophilic cytoplasm and indistinct cell borders. The neoplastic cells are positive for CD34 and synaptophysin. CD117 and tryptase highlight the scattered mast cells within the tumor. After surgical removal of the tumor, the patient’s blood pressure is normal. We also reviewed the literature and discussed the differential diagnoses.

Meiotic drivers are parasitic loci that force their own transmission into greater than half of the offspring of a heterozygote. Many drivers have been identified, but their molecular mechanisms are largely unknown. The wtf4 gene is a meiotic driver in Schizosaccharomyces pombe that uses a poison-antidote mechanism to selectively kill meiotic products (spores) that do not inherit wtf4. Here, we show that the Wtf4 proteins can function outside of gametogenesis and in a distantly related species, Saccharomyces cerevisiae. The Wtf4poison protein forms dispersed, toxic aggregates. The Wtf4antidote can co-assemble with the Wtf4poison and promote its trafficking to vacuoles. We show that neutralization of the Wtf4poison requires both co-assembly with the Wtf4antidote and aggregate trafficking, as mutations that disrupt either of these processes result in cell death in the presence of the Wtf4 proteins. This work reveals that wtf parasites can exploit protein aggregate management pathways to selectively destroy spores.

NR4A is a nuclear receptor protein family whose members act as sensors of cellular environment and regulate multiple processes such as metabolism, proliferation, migration, apoptosis, and autophagy. Since the ligand binding domains of these receptors have no cavity for ligand interaction, their function is most likely regulated by protein abundance and post-translational modifications. In particular, NR4A1 is regulated by protein abundance, phosphorylation, and subcellular distribution (nuclear-cytoplasmic translocation), and acts both as a transcription factor and as a regulator of other interacting proteins. SUMOylation is a post-translational modification that can affect protein stability, transcriptional activity, alter protein-protein interactions and modify intracellular localization of target proteins. In the present study we evaluated the role of SUMOylation as a posttranslational modification that can regulate the activity of NR4A1 to induce autophagy-dependent cell death. We focused on a model potentially relevant for neuronal cell death and demonstrated that NR4A1 needs to be SUMOylated to induce autophagic cell death. We observed that a triple mutant in SUMOylation sites has reduced SUMOylation, increased transcriptional activity, altered intracellular distribution, and more importantly, its ability to induce autophagic cell death is impaired.

The satellite validation navy tool (SAVANT) was developed by the Naval Research Laboratory to help facilitate the assessment of the stability and accuracy of ocean color satellites, using numerous ground truth (in situ) platforms around the globe and support methods for match-up protocols. The effects of varying spatial constraints with permissive and strict protocols on match-up uncertainty are evaluated, in an attempt to establish an optimal satellite ocean color calibration and validation (cal/val) match-up protocol. This allows users to evaluate the accuracy of ocean color sensors compared to specific ground truth sites that provide continuous data. Various match-up constraints may be adjusted, allowing for varied evaluations of their effects on match-up data. The results include the following: (a) the difference between aerosol robotic network ocean color (AERONET-OC) and marine optical Buoy (MOBY) evaluations; (b) the differences across the visible spectrum for various water types; (c) spatial differences and the size of satellite area chosen for comparison; and (d) temporal differences in optically complex water. The match-up uncertainty analysis was performed using Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) SNPP data at the AERONET-OC sites and the MOBY site. It was found that the more permissive constraint sets allow for a higher number of match-ups and a more comprehensive representation of the conditions, while the restrictive constraints provide better statistical match-ups between in situ and satellite sensors.

Risk for renal cell carcinoma (RCC) is higher when there are first-degree family members with the disease. Here, Scelo and colleagues perform a genome-wide association meta-analysis and new genome-wide scan to identify seven new loci with significant RCC association.

A pulse pressurisation technique is developed and utilised for determining building leakage at low pressure, based on a “quasi-steady pulse” concept. The underlying principle of the technique is to subject the building envelope to a known volume change in a short period of time (typically 1.5 s). The resulting pressure pulse is recorded, from which the leakage characteristic at low pressure is determined. The technique minimizes the effects of wind and buoyancy forces and has proven to be repeatable. It can use a compact and portable test rig and does not need to penetrate the building envelope. Therefore, it can obtain the leakage of a building very quickly and efficiently. Throughout the various stages of research and development of the pulse technique, experimental investigations have been carried out under different configurations and scenarios in order to validate the changes that have been made for the purpose of system development and optimisation. This paper provides an overview of experimental investigations in the validation process by covering comparison between blower door and pulse unit, comparison between piston-based pulse unit and nozzle-based pulse unit, testing with multiple pulse units in a large building, testing with a known opening, and testing in different building types with a range of volumes and airtightness levels. It enables us to understand the strengths and the limits of the pulse technique, from the experimental and practical perspectives. A good repeatability level (within ±5%) has been maintained throughout the various developmental stages and the average value of Q50/Q4 reported herein was in close agreement (

In this essay we propose a reframing of the Bloomberg Terminal, an interface used to track financial trades and values, by using it as a creative, critical and curatorial device to explore the relationship between the art and finance. To contextualise this approach, we offer a history of the Bloomberg Terminal alongside an analysis of the power of interfaces to shape both the user and the represented information. We use the terminal as a way to critique the relationship between art acquisition and financial trading companies. We then describe some outcomes of a series of workshops themed around the idea of ‘building an alternative Bloomberg’. We conclude by offering some potential applications of a re-framed Bloomberg Terminal as an open and modular interface for engaging with issues around art and finance, both in terms of content and curation.

Miscanthus (Miscanthus sp. Family: Poaceae) was hot-water extracted (two h, at 160 °C) at three scales: laboratory (Parr reactor, 300 cm3), intermediate (M/K digester, 4000 cm3), and pilot (65 ft3-digester, 1.841 × 106 cm3). Hot-water extracted miscanthus, hydrolyzate, and lignin recovered from hydrolyzate were characterized and evaluated for potential uses aiming at complete utilization of miscanthus. Effects of scale-up on digester yield, removal of hemicelluloses, deashing, delignification degree, lignin recovery and purity, and cellulose retention were studied. The scale-dependent results demonstrated that before implementation, hot-water extraction (HWE) should be evaluated on a scale larger than a laboratory scale. The production of energy-enriched fuel pellets from hot-water extracted miscanthus, especially in combination with recovered lignin is recommended, as energy of combustion increased gradually from native to hot-water extracted miscanthus to recovered lignin. The native and pilot-scale hot-water extracted miscanthus samples were also subjected to enzymatic hydrolysis using a cellulase-hemicellulase cocktail, to produce fermentable sugars. Hot-water extracted biomass released higher amount of glucose and xylose verifying benefits of HWE as an effective pretreatment for xylan-rich lignocellulosics. The recovered lignin was used to prepare a formaldehyde-free alternative to phenol-formaldehyde resins and as an antioxidant. Promising results were obtained for these lignin valorization pathways.

Understanding how spermatozoa approach the egg is a central biological issue. Recently a considerable amount of experimental evidence has accumulated on the relation between oscillations in intracellular calcium ion concentration ([Ca2+]i) in the sea urchin sperm flagellum, triggered by peptides secreted from the egg, and sperm motility. Determination of the structure and dynamics of the signaling pathway leading to these oscillations is a fundamental problem. However, a biochemically based formulation for the comprehension of the molecular mechanisms operating in the axoneme as a response to external stimulus is still lacking. Based on experiments on the S. purpuratus sea urchin spermatozoa, we propose a signaling network model where nodes are discrete variables corresponding to the pathway elements and the signal transmission takes place at discrete time intervals according to logical rules. The validity of this model is corroborated by reproducing previous empirically determined signaling features. Prompted by the model predictions we performed experiments which identified novel characteristics of the signaling pathway. We uncovered the role of a high voltage-activated Ca2+ channel as a regulator of the delay in the onset of fluctuations after activation of the signaling cascade. This delay time has recently been shown to be an important regulatory factor for sea urchin sperm reorientation. Another finding is the participation of a voltage-dependent calcium-activated K+ channel in the determination of the period of the [Ca2+]i fluctuations. Furthermore, by analyzing the spread of network perturbations we find that it operates in a dynamically critical regime. Our work demonstrates that a coarse-grained approach to the dynamics of the signaling pathway is capable of revealing regulatory sperm navigation elements and provides insight, in terms of criticality, on the concurrence of the high robustness and adaptability that the reproduction processes are predicted to have developed throughout evolution.

Abstract Refractory high-entropy alloys (RHEAs) are of interest for ultrahigh-temperature applications. To overcome their drawbacks — low-temperature brittleness and poor creep strength at high temperatures — improved fundamental understanding is needed. Using experiments, theory, and modeling, we investigated prototypical body-centered cubic (BCC) RHEAs, TiZrHfNbTa and VNbMoTaW. The former is compressible to 77 K, whereas the latter is not below 298 K. Hexagonal close-packed (HCP) elements in TiZrHfNbTa lower its dislocation core energy, increase lattice distortion, and lower its shear modulus relative to VNbMoTaW whose elements are all BCC. Screw dislocations dominate TiZrHfNbTa plasticity, but equal numbers of edges and screws exist in VNbTaMoW. Dislocation cores are compact in VNbTaMoW and extended in TiZrHfNbTa, and different macroscopic slip planes are activated in the two RHEAs, which we attribute to the concentration of HCP elements. Our findings demonstrate how ductility and strength can be controlled through the ratio of HCP to BCC elements in RHEAs.

Individuals with advanced liver disease (AdvLD), such as decompensated cirrhosis (DC) and hepatocellular carcinoma (HCC), have significant palliative needs. However, little research is available to guide health care providers on how to improve key domains related to palliative care (PC). We sought to identify priority areas for future research in PC by performing a comprehensive literature review and conducting iterative expert panel discussions. We conducted a literature review using search terms related to AdvLD and key PC domains. Individual reviews of these domains were performed, followed by iterative discussions by a panel consisting of experts from multiple disciplines, including hepatology, specialty PC, and nursing. Based on these discussions, priority areas for research were identified. We identified critical gaps in the available research related to PC and AdvLD. We developed and shared five key priority questions incorporating domains related to PC. Conclusion: Future research endeavors focused on improving PC in AdvLD should consider addressing the five key priorities areas identified from literature reviews and expert panel discussions.

Arterial aging results in a progressive reduction in elasticity of the vessel wall and an impaired ability of aged blood vessels to control local blood flow and pressure. Recently, a new concept has emerged that the stiffness and decreased contractility of vascular smooth muscle (VSM) cells are important contributors to age-induced arterial dysfunction. This study investigated the hypothesis that aging alters integrin function in a matrix stiffness-dependent manner, which contributes to decreased VSM contractility in aged soleus muscle feed arteries (SFA). The effect of RGD-binding integrins on contractile function of cannulated SFA isolated from young (4 months) and old (24 months) Fischer 344 rats was assessed by measuring constrictor responses to norepinephrine, phenylephrine, and angiotensin II. Results indicated that constrictor responses in presence of RGD were impaired in old compared to young SFA. VSM cells isolated from young and old SFA were used for functional experiments using atomic force microscopy and high-resolution imaging. Aging was associated with a modulation of integrin β1 recruitment at cell-matrix adhesions that was matrix and substrate stiffness dependent. Our data showed that substrate stiffening drives altered integrin β1 expression in aging, while soft substrates abolish age-induced differences in overall integrin β1 expression. In addition, substrate stiffness and matrix composition contribute to the modulation of SMα-actin cytoskeleton architecture with soft substrates reducing age effects. Our results provide new insights into age-induced structural changes at VSM cell level that translates to decreased functionality of aged resistance soleus feed arteries.

Abstract Background Inappropriate antibiotic use is linked to the spread of antimicrobial resistance worldwide, but there are limited systemic data on antibiotic utilization in low- and middle-income countries. The purpose of this study was to evaluate the prevalence and patterns of antibiotic prescription in an ambulatory care setting in Sri Lanka. Methods This cross-sectional survey was conducted at the Outpatient Department of a public tertiary medical center in Southern Province, Sri Lanka from February to April 2019. Among consecutive outpatients presenting for care, questionnaires were verbally administered to a systematic random sample to capture information about patient demographics, illness characteristics, and visit outcomes. Prescription data were obtained from the outpatient pharmacy’s electronic prescribing system. Results Of 409 surveyed patients, 146 (35.7%) were prescribed an antibiotic. The most frequently prescribed agents were amoxicillin (41 patients, 28.1% of antibiotic recipients) and first-generation cephalosporins (38, 26.0%). Respiratory indications were the most common reason for antibiotic use, comprising 69 (47.3%) of all antibiotic prescriptions. Antibiotics were prescribed for 66.1% of patients presenting with cough and 78.8% of those presenting with rhinorrhea or nasal congestion. Among all antibiotic recipients, 6 (4.1%) underwent diagnostic studies. Conclusions A high prevalence of antibiotic prescription was observed, in particular for treatment of respiratory conditions. These data support the need for improved antimicrobial stewardship in the Sri Lankan outpatient setting.

Digital health technologies, such as smartphones and wearable devices, promise to revolutionize disease prevention, detection, and treatment. Recently, there has been a surge of digital health studies where data are collected through a bring-your-own-device (BYOD) approach, in which participants who already own a specific technology may voluntarily sign up for the study and provide their digital health data. BYOD study design accelerates the collection of data from a larger number of participants than cohort design; this is possible because researchers are not limited in the study population size based on the number of devices afforded by their budget or the number of people familiar with the technology. However, the BYOD study design may not support the collection of data from a representative random sample of the target population where digital health technologies are intended to be deployed. This may result in biased study results and biased downstream technology development, as has occurred in other fields. In this viewpoint paper, we describe demographic imbalances discovered in existing BYOD studies, including our own, and we propose the Demographic Improvement Guideline to address these imbalances.

Efficient triaging of incident tickets is a critical task in Information Technology Service Management. Introducing interventional measures on tickets that are difficult to resolve can help improve the triaging of complex tickets. This work reports a method to predict the resolution complexity of a reported incident. The number of times a ticket is reassigned is a measure of difficulty in resolving the incident. Ticket resolution is associated with a variable workflow. A graph representation of ticket resolution offers advantages from the standpoint of running ad hoc queries. Predicting ticket reassignments requires the application of machine learning to this graph. A Relational Graph Convolutional Network is used for this purpose. The developed model provides benefits beyond predicting ticket reassignments accurately. It provides embeddings that can be used to derive insights about the operation of the help desk organization and the users of the help desk.

Macrophage activation syndrome (MAS) is a life-threatening cytokine storm complicating systemic juvenile idiopathic arthritis (SJIA) driven by IFN-γ. SJIA and MAS are also associated with an unexplained emerging inflammatory lung disease (SJIA-LD), with our recent work supporting pulmonary activation of IFN-γ pathways pathologically linking SJIA-LD and MAS. Our objective was to mechanistically define the potentially novel observation of pulmonary inflammation in the TLR9 mouse model of MAS. In acute MAS, lungs exhibit mild but diffuse CD4-predominant, perivascular interstitial inflammation with elevated IFN-γ, IFN-induced chemokines, and alveolar macrophage (AMϕ) expression of IFN-γ–induced genes. Single-cell RNA sequencing confirmed IFN-driven transcriptional changes across lung cell types with myeloid expansion and detection of MAS-specific macrophage populations. Systemic MAS resolution was associated with increased AMϕ and interstitial lymphocytic infiltration. AMϕ transcriptomic analysis confirmed IFN-γ–induced proinflammatory polarization during acute MAS, which switches toward an antiinflammatory phenotype after systemic MAS resolution. Interestingly, recurrent MAS led to increased alveolar inflammation and lung injury, and it reset AMϕ polarization toward a proinflammatory state. Furthermore, in mice bearing macrophages insensitive to IFN-γ, both systemic features of MAS and pulmonary inflammation were attenuated. These findings demonstrate that experimental MAS induces IFN-γ–driven pulmonary inflammation replicating key features of SJIA-LD and provides a model system for testing potentially novel treatments directed toward SJIA-LD.

Computer-aided design (CAD) for synthetic biology promises to accelerate the rational and robust engineering of biological systems. It requires both detailed and quantitative mathematical and experimental models of the processes to (re)design biology, and software and tools for genetic engineering and DNA assembly. Ultimately, the increased precision in the design phase will have a dramatic impact on the production of designer cells and organisms with bespoke functions and increased modularity. CAD strategies require quantitative models of cells that can capture multiscale processes and link genotypes to phenotypes. Here, we present a perspective on how whole-cell, multiscale models could transform design-build-test-learn cycles in synthetic biology. We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems. We also discuss several challenges for the realization of our vision. The possibility to describe and build whole-cells in silico offers an opportunity to develop increasingly automatized, precise and accessible CAD tools and strategies.

Signatories to the United Nations Framework Convention on Climate Change (UNFCCC) are required to annually report economy-wide greenhouse gas emissions and removals, including the forest sector. National forest inventory (NFI) is considered the main source of data for reporting forest carbon stocks and changes to UNFCCC. However, NFI samples are often collected asynchronously across regions in intervals of 5–10 years or sub-sampled annually, both introducing uncertainties in estimating annual carbon stock changes by missing a wide range of forest disturbance and recovery processes. Here, we integrate satellite observations with forest inventory data across the conterminous United States to improve the spatial and temporal resolution of NFI for estimating annual carbon stocks and changes. We used more than 120 000 permanent plots from the US forest inventory and analysis (FIA) data, surveyed periodically at sampling rate of 15%–20% per year across the US to develop non-parametric remote sensing-based models of aboveground biomass carbon density (AGC) at 1 ha spatial resolution for the years 2005, 2010, 2015, 2016, and 2017. The model provided a relatively unbiased estimation of AGC compared to ground inventory estimates at plot, county, and state scales. The uncertainty of the biomass maps and their contributions to estimates of forest carbon stock changes at county and state levels were quantified. Our results suggest that adding spatial and temporal dimensions to the forest inventory data, will significantly improve the accuracy and precision of carbon stocks and changes at jurisdictional scales.

Abstract Land use and management activities have a substantial impact on carbon stocks and associated greenhouse gas emissions and removals. However, it is challenging to discriminate between anthropogenic and non-anthropogenic sources and sinks from land. To address this problem, the Intergovernmental Panel on Climate Change developed a managed land proxy to determine which lands are contributing anthropogenic greenhouse gas emissions and removals. Governments report all emissions and removals from managed land to the United Nations Framework Convention on Climate Change based on this proxy, and policy interventions to reduce emissions from land use are expected to focus on managed lands. Our objective was to review the use of the managed land proxy, and summarize the criteria that governments have applied to classify land as managed and unmanaged. We found that the large majority of governments are not reporting on their application of the managed land proxy. Among the governments that do provide information, most have assigned all area in specific land uses as managed, while designating all remaining lands as unmanaged. This designation as managed land is intuitive for croplands and settlements, which would not exist without management interventions, but a portion of forest land, grassland, and wetlands may not be managed in a country. Consequently, Brazil, Canada and the United States have taken the concept further and delineated managed and unmanaged forest land, grassland and wetlands, using additional criteria such as functional use of the land and accessibility of the land to anthropogenic activity. The managed land proxy is imperfect because reported emissions from any area can include non-anthropogenic sources, such as natural disturbances. However, the managed land proxy does make reporting of GHG emissions and removals from land use more tractable and comparable by excluding fluxes from areas that are not directly influenced by anthropogenic activity. Moreover, application of the managed land proxy can be improved by incorporating additional criteria that allow for further discrimination between managed and unmanaged land.

Abstract  Crystals of Perphenazine (P), obtained from water/propanol, are triclinic, space group P1, with a = 8.149 (2), b = 11.879 (2), c = 12.093 (2) Å, α = 60.49(1), β = 89.54(2), γ = 89.98(2)°, V = 1018.9 Å3, Z = 2, D obs = 1.32 g/cm3, D calc = 1.317 g/cm3. The crystal structure was solved with CAD-4 data (4287 reflections, 2267 ≥ 3σ) using the SHELX-86 programs and refined to a final R value of 0.059. There are two independent molecules in the asymmetric unit, each with slightly different conformations. The dihedral angle between the planes of the butterfly tricyclic ring system is 142° and 138° in the two molecules respectively whereas it is 141° in the published monoclinic form of Perphenazine. The C–S–C angle in the tricyclic groups are 97° and 100° and the C–S distances are 1.707 and 1.738 Å. The piperazine has the chair conformation. An analysis of the conformation of the phenothiazine ring system in the different structures solved to date shows a conformational variability in the dihedral angle between the tricyclic ring systems (134–155°). Index Abstract  Crystals of Perphenazine, obtained from water/propanol, are triclinic and their structure was determined using single crystal diffractometric data. There are two independent molecules in the asymmetric unit, each with slightly different conformations. An analysis of the conformation of the phenothiazine ring system in the different structures solved to date shows a conformational variability in the dihedral angle between the tricyclic ring systems (134–155˚). [ABSTRACT FROM AUTHOR]

The high-voltage distribution and transmission of electricity are associated with a range of environmental effects that are increasingly contentious and are leading to difficult land-use planning issues. In the UK, local planning authorities have been taking an anticipatory approach to such efforts by the formation of policy in statutory land-use plans; this seeks to set constraints on the location and form of high-voltage installations and nearby development. This emerging body of policy reveals a number of consistently occurring themes that focus explicitly on the protection of local environmental conditions. This is indicative of broader trends apparent throughout plan-making in the last decade, in which environmental emphases have become more central, but the policy area also indicates that local authorities are responding to structural changes in the electricity industry and to changing patterns of energy generation. Copyright © 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Providers of Disability Management services were surveyed regarding their perceptions of major job functions and corresponding knowledge and skill requirements. The results indicated that knowledge in the areas of Case Management Techniques, Psychosocial Intervention, Vocational Aspects of Disability, Managed Care and Managed Disability, and Human Resources/Business is essential to perform Disability Management job functions. Implications for Disability Management training and clinical practice are discussed. [ABSTRACT FROM AUTHOR]

This article examines recent developments in Disability Management (DM) programs and practices, as well as their potential impact in the context of significant changes in workplace demographics. Recent trends are highlighted, in particular the integrated disability management (IDM) approach and broadening perspective on managing all workplace absences to support employees and enhance productivity. Emerging absence management models that encompass the elements of DM and IDM to deal with all work interruptions are identified as the cutting edge of best practices. The authors further discuss how this movement impacts the roles and functions of practitioners in the field based on the findings of recent research by the Commission on Disability Management Specialist Certification (CDMSC). Suggestions for professional and organizational development are offered. [ABSTRACT FROM AUTHOR]

e-width: 0px; "> For the duration of the New Order era (1966–98), the position of Chinese Indonesians was considered a problematic question: they were not “Pribumi” (native), but also not entirely Chinese. This “Chinese Problem” was discussed by a variety of speakers and writers, including several authors of literary works. In Di Kaki Bukit Cibalak (1977), Ahmad Tohari presents two ethnic Chinese characters, Nyonya Wibawa and Mulyani, the first as the employer and the second as the lover of the main character, Pambudi. By applying Goldmann’s theory of genetic structuralism, we show that through his depiction of the physical and behavioural aspects of the characters, Tohari promotes an assimilationist approach as the only possible solution to the Chinese problem (if it can be solved): the dichotomies between ethnic Chinese and Native Indonesians must be erased. However, Tohari continues to differentiate the ethnic Chinese by positioning them as persons who must only act to support the welfare of the Pribumi. Keywords: “The Chinese Problem”, Ahmad Tohari, position of Chinese Indonesians, Di Kaki Bukit Cibalak

Group-based reasons are reasons to play one’s part in some pattern of action that the members of some group could perform, because of the good features of the pattern. This paper discusses three broad conceptions of such reasons. According to the agency-first conception, there are no group-based reasons in cases where the relevant group is not or would not be itself an agent. According to the behaviour-first conception, what matters is that the other members of the group would play their parts in the relevant pattern, not whether they would have the cooperative intentional states constitutive of group agency in doing so. This paper argues against these conceptions and in favour of the powers-first conception, according to which what matters is that the members of the group have practically relevant powers.