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Abstract. The hydrological cycle of sub-arctic areas is dominated by the snowmelt event. An understanding of the mechanisms that control water fluxes during high-volume infiltration events in sub-arctic till soils is needed to assess how future changes in the timing and magnitude of snowmelt can affect soil water storage dynamics. We conducted a tracer experiment in which deuterated water was used to irrigate a plot on a forested hilltop in Lapland, tracked water fluxes of different mobility and monitored how the later snowmelt modifies the labelled soil water storage. We used lysimeters and destructive soil coring for soil water sampling and monitored and sampled the groundwater. Large spatiotemporal variability between the waters of different mobility was observed in the subsurface, while surface water flow during the tracer experiment was largely controlled by a fill-and-spill mechanism. Extensive soil saturation induced the flow of labelled water into the roots of nearby trees. We found that labelled water remained in deeper soil layers over the winter, but the snowmelt event gradually displaced all deuterated water and fully homogenized all water fluxes at the soil–vegetation interface. The conditions required for the full displacement of the old soil water occur only during a snowmelt with a persistently high groundwater table. We propose a conceptual model where infiltration into the soil and eventual soil water replenishment occur in three stages. First, unsaturated macropore flow is initiated via the surface microtopography and is directed towards the groundwater storage. The second stage is characterized by groundwater rise through the macropore network, subsequent pore water saturation and increased horizontal connectivity of macropores. Shallow subsurface lateral fluxes develop in more permeable shallow soil layers. In the third stage, which materializes during a long period with a high groundwater table and high hydrological connectivity within the soil, the soil water is replenished via enhanced matrix flow and pore water exchange with the macropore network.

The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present Phenopacket Store. Phenopacket Store v.0.1.19 includes 6,668 phenopackets representing 475 Mendelian and chromosomal diseases associated with 423 genes and 3,834 unique pathogenic alleles curated from 959 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.

Abstract: We incorporate Se into the 3D halide perovskite framework using the zwitterionic ligand: SeCYS (+NH3(CH2)2Se−), which occupies both the X− and A+ sites in the prototypical ABX3 perovskite. The new organoselenide‐halide perovskites: (SeCYS)PbX2 (X=Cl, Br) expand upon the recently discovered organosulfide‐halide perovskites. Single‐crystal X‐ray diffraction and pair distribution function analysis reveal the average structures of the organoselenide‐halide perovskites, whereas the local lead coordination environments and their distributions were probed through solid‐state 77Se and 207Pb NMR, complemented by theoretical simulations. Density functional theory calculations illustrate that the band structures of (SeCYS)PbX2 largely resemble those of their S analogs, with similar band dispersion patterns, yet with a considerable band gap decrease. Optical absorbance measurements indeed show band gaps of 2.07 and 1.86 eV for (SeCYS)PbX2 with X=Cl and Br, respectively. We further demonstrate routes to alloying the halides (Cl, Br) and chalcogenides (S, Se) continuously tuning the band gap from 1.86 to 2.31 eV–straddling the ideal range for tandem solar cells or visible‐light photocatalysis. The comprehensive description of the average and local structures, and how they can fine‐tune the band gap and potential trap states, respectively, establishes the foundation for understanding this new perovskite family, which combines solid‐state and organo‐main‐group chemistry.

We incorporate Se into the 3D halide perovskite framework using the zwitterionic ligand: SeCYS (+NH3(CH2)2Se-), which occupies both the X- and A+ sites in the prototypical ABX3 perovskite. The new organoselenide-halide perovskites: (SeCYS)PbX2 (X=Cl, Br) expand upon the recently discovered organosulfide-halide perovskites. Single-crystal X-ray diffraction and pair distribution function analysis reveal the average structures of the organoselenide-halide perovskites, whereas the local lead coordination environments and their distributions were probed through solid-state 77Se and 207Pb NMR, complemented by theoretical simulations. Density functional theory calculations illustrate that the band structures of (SeCYS)PbX2 largely resemble those of their S analogs, with similar band dispersion patterns, yet with a considerable band gap decrease. Optical absorbance measurements indeed show band gaps of 2.07 and 1.86 eV for (SeCYS)PbX2 with X=Cl and Br, respectively. We further demonstrate routes to alloying the halides (Cl, Br) and chalcogenides (S, Se) continuously tuning the band gap from 1.86 to 2.31 eV-straddling the ideal range for tandem solar cells or visible-light photocatalysis. The comprehensive description of the average and local structures, and how they can fine-tune the band gap and potential trap states, respectively, establishes the foundation for understanding this new perovskite family, which combines solid-state and organo-main-group chemistry.

BackgroundStandard treatment for patients with newly diagnosed glioblastoma includes surgery, radiotherapy (RT), and temozolomide (TMZ) chemotherapy (TMZ/RT→TMZ). The proteasome has long been considered a promising therapeutic target because of its role as a central biological hub in tumor cells. Marizomib is a novel pan-proteasome inhibitor that crosses the blood-brain barrier.MethodsEuropean Organisation for Research and Treatment of Cancer 1709/Canadian Cancer Trials Group CE.8 was a multicenter, randomized, controlled, open-label phase 3 superiority trial. Key eligibility criteria included newly diagnosed glioblastoma, age > 18 years and Karnofsky performance status > 70. Patients were randomized in a 1:1 ratio. The primary objective was to compare overall survival (OS) in patients receiving marizomib in addition to TMZ/RT→TMZ with patients receiving the only standard treatment in the whole population and in the subgroup of patients with MGMT promoter-unmethylated tumors.ResultsThe trial was opened at 82 institutions in Europe, Canada, and the U.S. A total of 749 patients (99.9% of the planned 750) were randomized. OS was not different between the standard and the marizomib arm (median 17 vs. 16.5 months; HR = 1.04; P = .64). PFS was not statistically different either (median 6.0 vs. 6.3 months; HR = 0.97; P = .67). In patients with MGMT promoter-unmethylated tumors, OS was also not different between standard therapy and marizomib (median 14.5 vs. 15.1 months, HR = 1.13; P = .27). More CTCAE grade 3/4 treatment-emergent adverse events were observed in the marizomib arm than in the standard arm.ConclusionsAdding marizomib to standard temozolomide-based radiochemotherapy resulted in more toxicity, but did not improve OS or PFS in patients with newly diagnosed glioblastoma.

Scintigraphy and Positron Emission Tomography (PET) are both nuclear medicine imaging techniques, providing functional information of the imaged areas. Scintigraphy is a two-dimensional projected imaging technique that was introduced in equine imaging in the late 1970s. Scintigraphy allows imaging of large body parts and can cover multiple areas, remaining the only technique commonly used in horses for whole body imaging. PET is a cross-sectional imaging technique, first used in horses in 2015, allowing higher resolution three-dimensional functional imaging of the equine distal limb. This manuscript will cover current use and values of these two modalities in equine lameness diagnosis.

The properties of excitons, or correlated electron-hole pairs, are of paramount importance to optoelectronic applications of materials. A central component of exciton physics is the electron-hole interaction, which is commonly treated as screened solely by electrons within a material. However, nuclear motion can screen this Coulomb interaction as well, with several recent studies developing model approaches for approximating the phonon screening of excitonic properties. While these model approaches tend to improve agreement with experiment, they rely on several approximations that restrict their applicability to a wide range of materials, and thus far they have neglected the effect of finite temperatures. Here, we develop a fully first-principles, parameter-free approach to compute the temperature-dependent effects of phonon screening within the ab initio [Formula: see text]-Bethe-Salpeter equation framework. We recover previously proposed models of phonon screening as well-defined limits of our general framework, and discuss their validity by comparing them against our first-principles results. We develop an efficient computational workflow and apply it to a diverse set of semiconductors, specifically AlN, CdS, GaN, MgO, and [Formula: see text]. We demonstrate under different physical scenarios how excitons may be screened by multiple polar optical or acoustic phonons, how their binding energies can exhibit strong temperature dependence, and the ultrafast timescales on which they dissociate into free electron-hole pairs.

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenias alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Flavonoids exert vasculoprotective effects in humans, but interindividual variability in their action has also been reported. This study aims to identify genes that are associated with vascular health effects of flavonoids and whose polymorphisms could explain interindividual variability in response to their intake. Applying the predetermined literature search criteria, we identified five human intervention studies reporting positive effects of flavonoids on vascular function together with global genomic changes analyzed using microarray methods. Genes involved in vascular dysfunction were identified from genome-wide association studies (GWAS). By extracting data from the eligible human intervention studies, we obtained 5807 differentially expressed genes (DEGs). The number of identified upstream regulators (URs) varied across the studies, from 227 to 1407. The search of the GWAS Catalog revealed 493 genes associated with vascular dysfunction. An integrative analysis of transcriptomic data with GWAS genes identified 106 candidate DEGs and 42 candidate URs, while subsequent functional analyses and a search of the literature identified 20 top priority candidate genes: ALDH2, APOE, CAPZA1, CYP11B2, GNA13, IL6, IRF5, LDLR, LPL, LSP1, MKNK1, MMP3, MTHFR, MYO6, NCR3, PPARG, SARM1, TCF20, TCF7L2, and TNF. In conclusion, this integrated analysis identifies important genes to design future nutrigenetic studies for development of precision nutrition for polyphenols.

BACKGROUND: Schizophrenia is associated with an increased risk of aggressive behaviour, which may partly be explained by illness-related changes in brain structure. However, previous studies have been limited by group-level analyses, small and selective samples of inpatients and long time lags between exposure and outcome. METHODS: This cross-sectional study pooled data from 20 sites participating in the international ENIGMA-Schizophrenia Working Group. Sites acquired T1-weighted and diffusion-weighted magnetic resonance imaging scans in a total of 2095 patients with schizophrenia and 2861 healthy controls. Measures of grey matter volume and white matter microstructural integrity were extracted from the scans using harmonised protocols. For each measure, normative modelling was used to calculate how much patients deviated (in z-scores) from healthy controls at the individual level. Ordinal regression models were used to estimate the associations of these deviations with concurrent aggressive behaviour (as odds ratios [ORs] with 99% confidence intervals [CIs]). Mediation analyses were performed for positive symptoms (i.e., delusions, hallucinations and disorganised thinking), impulse control and illness insight. Aggression and potential mediators were assessed with the Positive and Negative Syndrome Scale, Scale for the Assessment of Positive Symptoms or Brief Psychiatric Rating Scale. RESULTS: Aggressive behaviour was significantly associated with reductions in total cortical volume (OR [99% CI] = 0.88 [0.78, 0.98], p = .003) and global white matter integrity (OR [99% CI] = 0.72 [0.59, 0.88], p = 3.50 × 10-5) and additional reductions in dorsolateral prefrontal cortex volume (OR [99% CI] = 0.85 [0.74, 0.97], p =.002), inferior parietal lobule volume (OR [99% CI] = 0.76 [0.66, 0.87], p = 2.20 × 10-7) and internal capsule integrity (OR [99% CI] = 0.76 [0.63, 0.92], p = 2.90 × 10-4). Except for inferior parietal lobule volume, these associations were largely mediated by increased severity of positive symptoms and reduced impulse control. CONCLUSIONS: This study provides evidence that the co-occurrence of positive symptoms, poor impulse control and aggressive behaviour in schizophrenia has a neurobiological basis, which may inform the development of therapeutic interventions.

The transcription factor and cell cycle regulator p53 is marked for degradation by the ubiquitin ligase MDM2. The interaction between these 2 proteins is mediated by a conserved binding motif in the disordered p53 transactivation domain (p53TAD) and the folded SWIB domain in MDM2. The conserved motif in p53TAD from zebrafish displays a 20-fold weaker interaction with MDM2, compared to the interaction in human and chicken. To investigate this apparent difference, we tracked the molecular evolution of the p53TAD/MDM2 interaction among ray-finned fishes (Actinopterygii), the largest vertebrate clade. Intriguingly, phylogenetic analyses, ancestral sequence reconstructions, and binding experiments showed that different loss-of-affinity changes in the canonical binding motif within p53TAD have occurred repeatedly and convergently in different fish lineages, resulting in relatively low extant affinities (KD = 0.5 to 5 μM). However, for 11 different fish p53TAD/MDM2 interactions, nonconserved regions flanking the canonical motif increased the affinity 4- to 73-fold to be on par with the human interaction. Our findings suggest that compensating changes at conserved and nonconserved positions within the motif, as well as in flanking regions of low conservation, underlie a stabilizing selection of functional affinity in the p53TAD/MDM2 interaction. Such interplay complicates bioinformatic prediction of binding and calls for experimental validation. Motif-mediated protein-protein interactions involving short binding motifs and folded interaction domains are very common across multicellular life. It is likely that the evolution of affinity in motif-mediated interactions often involves an interplay between specific interactions made by conserved motif residues and nonspecific interactions by nonconserved disordered regions.

This paper describes a dataset collected by infrared thermography, a non-contact, non-intrusive technique to acquire data and analyze the built environment in various aspects. While most studies focus on the city and building scales, an observatory installed on a rooftop provides high temporal and spatial resolution observations with dynamic interactions on the district scale. The rooftop infrared thermography observatory with a multi-modal platform capable of assessing a wide range of dynamic processes in urban systems was deployed in Singapore. It was placed on the top of two buildings that overlook the outdoor context of the National University of Singapore campus. The platform collects remote sensing data from tropical areas on a temporal scale, allowing users to determine the temperature trend of individual features such as buildings, roads, and vegetation. The dataset includes 1,365,921 thermal images collected on average at approximately 10-second intervals from two locations during ten months.

Excitons are prevalent in semiconductors and insulators, and their binding energies are critical for optoelectronic applications. The state-of-the-art method for first-principles calculations of excitons in extended systems is the ab initio GW-Bethe-Salpeter equation (BSE) approach, which can require a fine sampling of reciprocal space to accurately resolve solid-state exciton properties. Here we show, for a range of semiconductors and insulators, that the commonly employed approach of uniformly sampling the Brillouin zone can lead to underconverged exciton binding energies, as impractical grid sizes are required to achieve adequate convergence. We further show that nonuniform sampling of the Brillouin zone, focused on the region of reciprocal space where the exciton wave function resides, enables efficient rapid numerical convergence of exciton binding energies at a given level of theory. We propose a well-defined convergence procedure, which can be carried out at relatively low computational cost and which in some cases leads to a correction of previous best theoretical estimates by almost a factor of 2, qualitatively changing the predicted exciton physics. These results call for the adoption of nonuniform sampling methods for ab initio GW-BSE calculations and for revisiting previously computed values for exciton binding energies of many systems.

OBJECTIVE: Developing accurate phenotype definitions is critical in obtaining reliable and reproducible background rates in safety research. This study aims to illustrate the differences in background incidence rates by comparing definitions for a given outcome. MATERIALS AND METHODS: We used 16 data sources to systematically generate and evaluate outcomes for 13 adverse events and their overall background rates. We examined the effect of different modifications (inpatient setting, standardization of code set, and code set changes) to the computable phenotype on background incidence rates. RESULTS: Rate ratios (RRs) of the incidence rates from each computable phenotype definition varied across outcomes, with inpatient restriction showing the highest variation from 1 to 11.93. Standardization of code set RRs ranges from 1 to 1.64, and code set changes range from 1 to 2.52. DISCUSSION: The modification that has the highest impact is requiring inpatient place of service, leading to at least a 2-fold higher incidence rate in the base definition. Standardization showed almost no change when using source code variations. The strength of the effect in the inpatient restriction is highly dependent on the outcome. Changing definitions from broad to narrow showed the most variability by age/gender/database across phenotypes and less than a 2-fold increase in rate compared to the base definition. CONCLUSION: Characterization of outcomes across a network of databases yields insights into sensitivity and specificity trade-offs when definitions are altered. Outcomes should be thoroughly evaluated prior to use for background rates for their plausibility for use across a global network.

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

INTRODUCTION: Ethylene glycol (EG) is a frequently considered toxicant in poisoned patients. Definitive diagnosis relies on gas chromatography (GC), but this is unavailable at most hospitals. A glycerol dehydrogenase (GDH)-based assay rapidly detects EG. A rapid turnaround time and wide availability of necessary instrumentation suggest this method could facilitate the rapid detection of EG. METHODS: This is a prospective, observational analysis of banked, remnant serum samples submitted to the laboratory of a large, multi-hospital healthcare system. Samples were submitted over a 12-month period for the explicit purpose of testing for suspected EG ingestion. All samples underwent GC and the GDH-based assay. RESULTS: Of the 118 analyzed samples, 88 had no EG detected by GC, and 30 were positive. At the manufacturers threshold of 6 mg/dL EG, there was 100% (95%CI; 88.7-100) positive percent agreement (PPA) and 98% (92.1-99.6) negative percent agreement (NPA). Adjusted to a threshold of 9 mg/dL, both the PPA and NPA were 100%. Deming regression of the observed concentrations revealed a slope of 1.16 (1.01 to 1.32) and intercept of -5.3 (-8.9 to -1.7). CONCLUSIONS: The GDH assay provides a sensitive and specific method for the detection and quantification of EG that is comparable to a GC-based method. More widespread use of this rapid, inexpensive assay could improve the care of patients with suspected toxic alcohol exposure. Further study is needed to evaluate the test performance in real-time patient treatment decisions.

Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis.

The fluorescent glutamate indicator iGluSnFR enables imaging of neurotransmission with genetic and molecular specificity. However, existing iGluSnFR variants exhibit low in vivo signal-to-noise ratios, saturating activation kinetics and exclusion from postsynaptic densities. Using a multiassay screen in bacteria, soluble protein and cultured neurons, we generated variants with improved signal-to-noise ratios and kinetics. We developed surface display constructs that improve iGluSnFR's nanoscopic localization to postsynapses. The resulting indicator iGluSnFR3 exhibits rapid nonsaturating activation kinetics and reports synaptic glutamate release with decreased saturation and increased specificity versus extrasynaptic signals in cultured neurons. Simultaneous imaging and electrophysiology at individual boutons in mouse visual cortex showed that iGluSnFR3 transients report single action potentials with high specificity. In vibrissal sensory cortex layer 4, we used iGluSnFR3 to characterize distinct patterns of touch-evoked feedforward input from thalamocortical boutons and both feedforward and recurrent input onto L4 cortical neuron dendritic spines.

BRAFV600E alterations are prevalent across multiple tumors. Here we present final efficacy and safety results of a phase 2 basket trial of dabrafenib (BRAF kinase inhibitor) plus trametinib (MEK inhibitor) in eight cohorts of patients with BRAFV600E-mutated advanced rare cancers: anaplastic thyroid carcinoma (n = 36), biliary tract cancer (n = 43), gastrointestinal stromal tumor (n = 1), adenocarcinoma of the small intestine (n = 3), low-grade glioma (n = 13), high-grade glioma (n = 45), hairy cell leukemia (n = 55) and multiple myeloma (n = 19). The primary endpoint of investigator-assessed overall response rate in these cohorts was 56%, 53%, 0%, 67%, 54%, 33%, 89% and 50%, respectively. Secondary endpoints were median duration of response (DoR), progression-free survival (PFS), overall survival (OS) and safety. Median DoR was 14.4 months, 8.9 months, not reached, 7.7 months, not reached, 31.2 months, not reached and 11.1 months, respectively. Median PFS was 6.7 months, 9.0 months, not reached, not evaluable, 9.5 months, 5.5 months, not evaluable and 6.3 months, respectively. Median OS was 14.5 months, 13.5 months, not reached, 21.8 months, not evaluable, 17.6 months, not evaluable and 33.9 months, respectively. The most frequent (≥20% of patients) treatment-related adverse events were pyrexia (40.8%), fatigue (25.7%), chills (25.7%), nausea (23.8%) and rash (20.4%). The encouraging tumor-agnostic activity of dabrafenib plus trametinib suggests that this could be a promising treatment approach for some patients with BRAFV600E-mutated advanced rare cancers. ClinicalTrials.gov registration: NCT02034110 .

BackgroundAdverse events of special interest (AESIs) were pre-specified to be monitored for the COVID-19 vaccines. Some AESIs are not only associated with the vaccines, but with COVID-19. Our aim was to characterise the incidence rates of AESIs following SARS-CoV-2 infection in patients and compare these to historical rates in the general population.MethodsA multi-national cohort study with data from primary care, electronic health records, and insurance claims mapped to a common data model. This study's evidence was collected between Jan 1, 2017 and the conclusion of each database (which ranged from Jul 2020 to May 2022). The 16 pre-specified prevalent AESIs were: acute myocardial infarction, anaphylaxis, appendicitis, Bell's palsy, deep vein thrombosis, disseminated intravascular coagulation, encephalomyelitis, Guillain- Barré syndrome, haemorrhagic stroke, non-haemorrhagic stroke, immune thrombocytopenia, myocarditis/pericarditis, narcolepsy, pulmonary embolism, transverse myelitis, and thrombosis with thrombocytopenia. Age-sex standardised incidence rate ratios (SIR) were estimated to compare post-COVID-19 to pre-pandemic rates in each of the databases.FindingsSubstantial heterogeneity by age was seen for AESI rates, with some clearly increasing with age but others following the opposite trend. Similarly, differences were also observed across databases for same health outcome and age-sex strata. All studied AESIs appeared consistently more common in the post-COVID-19 compared to the historical cohorts, with related meta-analytic SIRs ranging from 1.32 (1.05 to 1.66) for narcolepsy to 11.70 (10.10 to 13.70) for pulmonary embolism.InterpretationOur findings suggest all AESIs are more common after COVID-19 than in the general population. Thromboembolic events were particularly common, and over 10-fold more so. More research is needed to contextualise post-COVID-19 complications in the longer term.FundingNone.

Giardia duodenalis (syn. G. intestinalis, G. lamblia) is a widespread gastrointestinal protozoan parasite with debated taxonomic status. Currently, eight distinct genetic sub-groups, termed assemblages A-H, are defined based on a few genetic markers. Assemblages A and B may represent distinct species and are both of human public health relevance. Genomic studies are scarce and the few reference genomes available, in particular for assemblage B, are insufficient for adequate comparative genomics. Here, by combining long- and short-read sequences generated by PacBio and Illumina sequencing technologies, we provide nine annotated genome sequences for reference from new clinical isolates (four assemblage A and five assemblage B parasite isolates). Isolates chosen represent the currently accepted classification of sub-assemblages AI, AII, BIII and BIV. Synteny over the whole genome was generally high, but we report chromosome-level translocations as a feature that distinguishes assemblage A from B parasites. Orthologue gene group analysis was used to define gene content differences between assemblage A and B and to contribute a gene-set-based operational definition of respective taxonomic units. Giardia is tetraploid, and high allelic sequence heterogeneity (ASH) for assemblage B vs. assemblage A has been observed so far. Noteworthy, here we report an extremely low ASH (0.002%) for one of the assemblage B isolates (a value even lower than the reference assemblage A isolate WB-C6). This challenges the view of low ASH being a notable feature that distinguishes assemblage A from B parasites, and low ASH allowed assembly of the most contiguous assemblage B genome currently available for reference. In conclusion, the description of nine highly contiguous genome assemblies of new isolates of G. duodenalis assemblage A and B adds to our understanding of the genomics and species population structure of this widespread zoonotic parasite.

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

This study examines the computational challenges in elucidating intricate chemical systems, particularly through ab-initio methodologies. This work highlights the Divide-Expand-Consolidate (DEC) approach for coupled cluster (CC) theory-a linear-scaling, massively parallel framework-as a viable solution. Detailed scrutiny of the DEC framework reveals its extensive applicability for large chemical systems, yet it also acknowledges inherent limitations. To mitigate these constraints, the cluster perturbation theory is presented as an effective remedy. Attention is then directed towards the CPS (D-3) model, explicitly derived from a CC singles parent and a doubles auxiliary excitation space, for computing excitation energies. The reviewed new algorithms for the CPS (D-3) method efficiently capitalize on multiple nodes and graphical processing units, expediting heavy tensor contractions. As a result, CPS (D-3) emerges as a scalable, rapid, and precise solution for computing molecular properties in large molecular systems, marking it an efficient contender to conventional CC models.

Introduction: The left (LV) and right (RV) ventricles are linked biologically, hemodynamically, and mechanically, a phenomenon known as ventricular interdependence. While LV function has long been known to impact RV function, the reverse is increasingly being realized to have clinical importance. Investigating ventricular interdependence clinically is challenging given the invasive measurements required, including biventricular catheterization, and confounding factors such as comorbidities, volume status, and other aspects of subject variability. Methods: Computational modeling allows investigation of mechanical and hemodynamic interactions in the absence of these confounding factors. Here, we use a threesegment biventricular heart model and simple circulatory system to investigate ventricular interdependence under conditions of systolic and diastolic dysfunction of the LV and RV in the presence of compensatory volume loading. We use the end-diastolic pressure-volume relationship, end-systolic pressure-volume relationship, Frank Starling curves, and cardiac power output as metrics. Results: The results demonstrate that LV systolic and diastolic dysfunction lead to RV compensation as indicated by increases in RV power. Additionally, RV systolic and diastolic dysfunction lead to impaired LV filling, interpretable as LV stiffening especially with volume loading to maintain systemic pressure. Discussion: These results suggest that a subset of patients with intact LV systolic function and diagnosed to have impaired LV diastolic function, categorized as heart failure with preserved ejection fraction (HFpEF), may in fact have primary RV failure. Application of this computational approach to clinical data sets, especially for HFpEF, may lead to improved diagnosis and treatment strategies and consequently improved outcomes.

BackgroundNearly all patients with newly diagnosed glioblastoma experience recurrence following standard-of-care radiotherapy (RT) + temozolomide (TMZ). The purpose of the phase III randomized CheckMate 548 study was to evaluate RT + TMZ combined with the immune checkpoint inhibitor nivolumab (NIVO) or placebo (PBO) in patients with newly diagnosed glioblastoma with methylated MGMT promoter (NCT02667587).MethodsPatients (N = 716) were randomized 1:1 to NIVO [(240 mg every 2 weeks × 8, then 480 mg every 4 weeks) + RT (60 Gy over 6 weeks) + TMZ (75 mg/m2 once daily during RT, then 150-200 mg/m2 once daily on days 1-5 of every 28-day cycle × 6)] or PBO + RT + TMZ following the same regimen. The primary endpoints were progression-free survival (PFS) and overall survival (OS) in patients without baseline corticosteroids and in all randomized patients.ResultsAs of December 22, 2020, median (m)PFS (blinded independent central review) was 10.6 months (95% CI, 8.9-11.8) with NIVO + RT + TMZ vs 10.3 months (95% CI, 9.7-12.5) with PBO + RT + TMZ (HR, 1.1; 95% CI, 0.9-1.3) and mOS was 28.9 months (95% CI, 24.4-31.6) vs 32.1 months (95% CI, 29.4-33.8), respectively (HR, 1.1; 95% CI, 0.9-1.3). In patients without baseline corticosteroids, mOS was 31.3 months (95% CI, 28.6-34.8) with NIVO + RT + TMZ vs 33.0 months (95% CI, 31.0-35.1) with PBO + RT + TMZ (HR, 1.1; 95% CI, 0.9-1.4). Grade 3/4 treatment-related adverse event rates were 52.4% vs 33.6%, respectively.ConclusionsNIVO added to RT + TMZ did not improve survival in patients with newly diagnosed glioblastoma with methylated or indeterminate MGMT promoter. No new safety signals were observed.

Decades of structure-function studies have established our current extensive understanding of enzymes. However, traditional structural models are snapshots of broader conformational ensembles of interchanging states. We demonstrate the need for conformational ensembles to understand function, using the enzyme ketosteroid isomerase (KSI) as an example. Comparison of prior KSI cryogenic x-ray structures suggested deleterious mutational effects from a misaligned oxyanion hole catalytic residue. However, ensemble information from room-temperature x-ray crystallography, combined with functional studies, excluded this model. Ensemble-function analyses can deconvolute effects from altering the probability of occupying a state (P-effects) and changing the reactivity of each state (k-effects); our ensemble-function analyses revealed functional effects arising from weakened oxyanion hole hydrogen bonding and substrate repositioning within the active site. Ensemble-function studies will have an integral role in understanding enzymes and in meeting the future goals of a predictive understanding of enzyme catalysis and engineering new enzymes.

Phylogeographic analyses aim to extract information about pathogen spread from genomic data, and visualising spatio-temporal reconstructions is a key aspect of this process. Here we present SPREAD 4, a feature-rich web-based application that visualises estimates of pathogen dispersal resulting from Bayesian phylogeographic inference using BEAST on a geographic map, offering zoom-and-filter functionality and smooth animation over time. SPREAD 4 takes as input phylogenies with both discrete and continuous location annotation and offers customised visualisation as well as generation of publication-ready figures. SPREAD 4 now features account-based storage and easy sharing of visualisations by means of unique web addresses. SPREAD 4 is intuitive to use and is available online at https://spreadviz.org, with an accompanying web page containing answers to frequently asked questions at https://beast.community/spread4.

BACKGROUND: Cognitive tasks delivered during ecological momentary assessment (EMA) may elucidate the short-term dynamics and contextual influences on cognition and judgements of performance. This paper provides initial validation of a smartphone task of facial emotion recognition in serious mental illness. METHODS: A total of 86 participants with psychotic disorders (non-affective and affective psychosis), aged 19-65, were administered in-lab gold standard affect recognition, neurocognition, and symptom assessments. They subsequently completed 10 days of the mobile facial emotion recognition task, assessing both accuracy and self-assessed performance, along with concurrent EMA of psychotic symptoms and mood. Validation focused on task adherence and predictors of adherence, gold standard convergent validity, and symptom and diagnostic group variation. RESULTS: The mean rate of adherence to the task was 79%; no demographic or clinical variables predicted adherence. Convergent validity was observed with in-lab measures of facial emotion recognition, and no practice effects were observed on the mobile facial emotion recognition task. EMA reports of more severe voices, sadness, and paranoia were associated with worse performance, whereas mood more strongly associated with self-assessed performance. CONCLUSION: The mobile facial emotion recognition task was tolerated and demonstrated convergent validity with in-lab measures of the same construct. Social cognitive performance, and biased judgements previously shown to predict function, can be evaluated in real-time in naturalistic environments.

Schizophrenia is frequently associated with obesity, which is linked with neurostructural alterations. Yet, we do not understand how the brain correlates of obesity map onto the brain changes in schizophrenia. We obtained MRI-derived brain cortical and subcortical measures and body mass index (BMI) from 1260 individuals with schizophrenia and 1761 controls from 12 independent research sites within the ENIGMA-Schizophrenia Working Group. We jointly modeled the statistical effects of schizophrenia and BMI using mixed effects. BMI was additively associated with structure of many of the same brain regions as schizophrenia, but the cortical and subcortical alterations in schizophrenia were more widespread and pronounced. Both BMI and schizophrenia were primarily associated with changes in cortical thickness, with fewer correlates in surface area. While, BMI was negatively associated with cortical thickness, the significant associations between BMI and surface area or subcortical volumes were positive. Lastly, the brain correlates of obesity were replicated among large studies and closely resembled neurostructural changes in major depressive disorders. We confirmed widespread associations between BMI and brain structure in individuals with schizophrenia. People with both obesity and schizophrenia showed more pronounced brain alterations than people with only one of these conditions. Obesity appears to be a relevant factor which could account for heterogeneity of brain imaging findings and for differences in brain imaging outcomes among people with schizophrenia.

Quark interactions with topological gluon configurations can induce local chirality imbalance and parity violation in quantum chromodynamics, which can lead to the chiral magnetic effect (CME) - an electric charge separation along the strong magnetic field in relativistic heavy-ion collisions. The CME-sensitive azimuthal correlator observable (Δγ) is contaminated by background arising, in part, from resonance decays coupled with elliptic anisotropy (v2). We report here differential measurements of the correlator as a function of the pair invariant mass (minv) in 20-50% centrality Au+Au collisions at sNN=200 GeV by the STAR experiment at the BNL Relativistic Heavy Ion Collider. Strong resonance background contributions to Δγ are observed. At large minv where this background is significantly reduced, the Δγ value is found to be significantly smaller. An event-shape-engineering technique is deployed to determine the v2 background shape as a function of minv. We extract a v2-independent and minv-averaged signal Δγsig=(0.03±0.06±0.08)×10-4, or (2±4±5)% of the inclusive Δγ(minv>0.4 GeV/c2)=(1.58±0.02±0.02)×10-4, within pion pT=0.2-0.8 GeV/c and averaged over pseudorapidity ranges of -1

AimMacroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert-based information is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert-based information with detailed empirical evidence. Here, we compared expert-based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS-tracking data of 1,498 individuals from 49 mammal species.LocationWorldwide.Time period1998-2021.Major taxa studiedForty-nine terrestrial mammal species.MethodsUsing GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types.ResultsIUCN habitat suitability data were in accordance with the GPS data (> 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a > 50% probability of agreement based on proportional habitat use and selection ratios, respectively.Main conclusionsWe show how GPS-tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, we show that GPS-tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data.

We report the first multi-differential measurements of strange hadrons of K−, ϕ and Ξ− yields as well as the ratios of ϕ/K− and ϕ/Ξ− in Au+Au collisions at sNN=3 GeV with the STAR experiment fixed target configuration at RHIC. The ϕ mesons and Ξ− hyperons are measured through hadronic decay channels, ϕ→K+K− and Ξ−→Λπ−. Collision centrality and rapidity dependence of the transverse momentum spectra for these strange hadrons are presented. The 4π yields and ratios are compared to thermal model and hadronic transport model predictions. At this collision energy, thermal model with grand canonical ensemble (GCE) under-predicts the ϕ/K− and ϕ/Ξ− ratios while the result of canonical ensemble (CE) calculations reproduce ϕ/K−, with the correlation length rc∼2.7 fm, and ϕ/Ξ−, rc∼4.2 fm, for the 0-10% central collisions. Hadronic transport models including high mass resonance decays could also describe the ratios. While thermal calculations with GCE work well for strangeness production in high energy collisions, the change to CE at 3 GeV implies a rather different medium property at high baryon density.

Background: Mental health (MH) apps are growing in popularity. While MH apps may be helpful, less is known about how crises such as suicidal ideation are addressed in apps. Aims: We examined the proportion of MH apps that contained language mentioning suicide or suicidal ideation and how apps communicated these policies and directed users to MH resources through app content, terms of services, and privacy policies. Method: We chose apps using an Internet search of "top mental health apps," similar to how a user might find an app, and extracted information about how crisis language was presented in these apps. Results: We found that crisis language was inconsistent among apps. Overall, 35% of apps provided crisis-specific resources in their app interface and 10.5% contained crisis language in terms of service or privacy policies. Limitations: This study employed a nonsystematic approach to sampling apps, and therefore the findings may not broadly represent apps for MH. Conclusion: To address the inconsistency of crisis resources, crisis language should be included as part of app evaluation frameworks, and internationally accessible, vetted resources should be provided to app users.

Interlayer organic cations in quasi-two-dimensional halide perovskites are a versatile tuning vehicle for the optoelectronic properties of these complex systems, but chemical intuition for this design route is yet to be established. Here, we use density functional theory, the GW approximation, and the Bethe-Salpeter equation approach to understand the contribution of the organic cation to the quasiparticle band gap and exciton binding energy of layered perovskites. We show that organic cations in quasi-two-dimensional perovskites contribute significantly to the dielectric screening in these systems, countering quantum confinement effects on the quasiparticle band gap and the exciton binding energy. Using a simple electrostatics model inspired by parallel-plate capacitors, we decouple the organic cation and inorganic layer contributions to the effective dielectric constants and show that dielectric properties of layered perovskites are broadly tunable via the interlayer cation, providing a direct means of tuning photophysical properties for a variety of applications.

We report cumulants of the proton multiplicity distribution from dedicated fixed-target Au+Au collisions at sqrt[s_{NN}]=3.0  GeV, measured by the STAR experiment in the kinematic acceptance of rapidity (y) and transverse momentum (p_{T}) within -0.5

Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioural inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behaviour and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a handheld device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from nine humans and eight canines with epilepsy, and then implemented prospectively in out-of-sample testing in two pet canines and four humans with drug-resistant epilepsy living in their natural environments. Accurate seizure diaries are needed as the primary clinical outcome measure of epilepsy therapy and to guide brain-stimulation optimization. The brain co-processor system described here enables tracking interictal epileptiform spikes, seizures and correlation with patient behavioural reports. In the future, correlation of spikes and seizures with behaviour will allow more detailed investigation of the clinical impact of spikes and seizures on patients.

The dependence of ab initio many-body perturbation theory within the GW approximation on the eigensystem used in calculating quasiparticle corrections limits this method's predictive power. Here, we investigate the accuracy of the recently developed Wannier-localized optimally tuned screened range-separated hybrid (WOT-SRSH) functional as a generalized Kohn-Sham starting point for single-shot GW (G0W0) calculations for a range of semiconductors and insulators. Comparison to calculations based on well-established functionals, namely, PBE, PBE0, and HSE, as well as to self-consistent GW schemes and to experiment, shows that band gaps computed via G0W0@WOT-SRSH have a level of precision and accuracy that is comparable to that of more advanced methods such as quasiparticle self-consistent GW and eigenvalue self-consistent GW. We also find that G0W0@WOT-SRSH improves the description of states deeper in the valence band manifold. Finally, we show that G0W0@WOT-SRSH significantly reduces the sensitivity of computed band gaps to ambiguities in the underlying WOT-SRSH tuning procedure.

We report measurements of the longitudinal double-spin asymmetry, ALL, for inclusive jet and dijet production in polarized proton-proton collisions at midrapidity and center-of-mass energy s=510 GeV, using the high luminosity data sample collected by the STAR experiment in 2013. These measurements complement and improve the precision of previous STAR measurements at the same center-of-mass energy that probe the polarized gluon distribution function at partonic momentum fraction 0.015≲x≲0.25. The dijet asymmetries are separated into four jet-pair topologies, which provide further constraints on the x dependence of the polarized gluon distribution function. These measurements are in agreement with previous STAR measurements and with predictions from current next-to-leading-order global analyses. They provide more precise data at low dijet invariant mass that will better constrain the shape of the polarized gluon distribution function of the proton.

In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground- and excited-state estimation on near-term hardware. We derive the theoretical ground on which the approach stands, and demonstrate that it provides one of the most compact variational expansions to date for solving strongly correlated Hamiltonians, when starting from an appropriate reference state. At the center of VQPE lies a set of equations, with a simple geometrical interpretation, which provides conditions for the time evolution grid in order to decouple eigenstates out of the set of time-evolved expansion states, and connects the method to the classical filter-diagonalization algorithm. Furthermore, we introduce what we call the unitary formulation of VQPE, in which the number of matrix elements that need to be measured scales linearly with the number of expansion states, and we provide an analysis of the effects of noise that substantially improves previous considerations. The unitary formulation allows for a direct comparison to iterative phase estimation. Our results mark VQPE as both a natural and highly efficient quantum algorithm for ground- and excited-state calculations of general many-body systems. We demonstrate a hardware implementation of VQPE for the transverse field Ising model. Furthermore, we illustrate its power on a paradigmatic example of strong correlation (Cr2 in the def2-SVP basis set), and show that it is possible to reach chemical accuracy with as few as approximately 50 time steps.

CRISPR/Cas9-mediated genome editing has become an extremely powerful technique used to modify gene expression in many organisms, including parasitic protists. Giardia intestinalis, a protist parasite that infects approximately 280 million people around the world each year, has been eluding the use of CRISPR/Cas9 to generate knockout cell lines due to its tetraploid genome. In this work, we show the ability of the in vitro assembled CRISPR/Cas9 components to successfully edit the genome of G. intestinalis. The cell line that stably expresses Cas9 in both nuclei of G. intestinalis showed effective recombination of the cassette containing the transcription units for the gRNA and the resistance marker. This highly efficient process led to the removal of all gene copies at once for three independent experimental genes, mem, cwp1 and mlf1. The method was also applicable to incomplete disruption of the essential gene, as evidenced by significantly reduced expression of tom40. Finally, testing the efficiency of Cas9-induced recombination revealed that homologous arms as short as 150 bp can be sufficient to establish a complete knockout cell line in G. intestinalis.

We report on the measurements of directed flow v1 and elliptic flow v2 for hadrons (π±, K±, KS0, p, ϕ, Λ and Ξ−) from Au+Au collisions at sNN=3 GeV and v2 for (π±, K±, p and p‾) at 27 and 54.4 GeV with the STAR experiment. While at the two higher energy midcentral collisions the number-of-constituent-quark (NCQ) scaling holds, at 3 GeV the v2 at midrapidity is negative for all hadrons and the NCQ scaling is absent. In addition, the v1 slopes at midrapidity for almost all observed hadrons are found to be positive, implying dominant repulsive baryonic interactions. The features of negative v2 and positive v1 slope at 3 GeV can be reproduced with a baryonic mean-field in transport model calculations. These results imply that the medium in such collisions is likely characterized by baryonic interactions.

Platelets have a wide range of functions including critical roles in hemostasis, thrombosis, and immunity. We hypothesized that during acute inflammation, such as in life-threatening sepsis, there are fundamental changes in the sites of platelet production and phenotypes of resultant platelets. Here, we showed during sepsis that the spleen was a major site of megakaryopoiesis and platelet production. Sepsis provoked an adrenergic-dependent mobilization of megakaryocyte-erythrocyte progenitors (MEPs) from the bone marrow to the spleen, where IL-3 induced their differentiation into megakaryocytes (MKs). In the spleen, immune-skewed MKs produced a CD40 ligandhi platelet population with potent immunomodulatory functions. Transfusions of post-sepsis platelets enriched from splenic production enhanced immune responses and reduced overall mortality in sepsis-challenged animals. These findings identify a spleen-derived protective platelet population that may be broadly immunomodulatory in acute inflammatory states such as sepsis.

The STAR collaboration presents jet substructure measurements related to both the momentum fraction and the opening angle within jets in p+p and Au+Au collisions at sNN =200GeV. The substructure observables include SoftDrop groomed momentum fraction (zg), groomed jet radius (Rg), and subjet momentum fraction (zSJ) and opening angle (θSJ). The latter observable is introduced for the first time. Fully corrected subjet measurements are presented for p+p collisions and are compared to leading-order Monte Carlo models. The subjet θSJ distributions reflect the jets leading opening angle and are utilized as a proxy for the resolution scale of the medium in Au+Au collisions. We compare data from Au+Au collisions to those from p+p which are embedded in minimum-bias Au+Au events in order to include the effects of detector smearing and the heavy-ion collision underlying event. The subjet observables are shown to be more robust to the background than zg and Rg. We observe no significant modifications of the subjet observables within the two highest-energy, back-to-back jets, resulting in a distribution of opening angles and the splittings that are vacuumlike. We also report measurements of the differential dijet momentum imbalance (AJ) for jets of varying θSJ. We find no qualitative differences in energy loss signatures for varying angular scales in the range 0.1< θSJ

The chiral magnetic effect (CME) refers to charge separation along a strong magnetic field due to imbalanced chirality of quarks in local parity and charge-parity violating domains in quantum chromodynamics. The experimental measurement of the charge separation is made difficult by the presence of a major background from elliptic azimuthal anisotropy. This background and the CME signal have different sensitivities to the spectator and participant planes, and could thus be determined by measurements with respect to these planes. We report such measurements in Au+Au collisions at a nucleon-nucleon center-of-mass energy of 200 GeV at the Relativistic Heavy-Ion Collider. It is found that the charge separation, with the flow background removed, is consistent with zero in peripheral (large impact parameter) collisions. Some indication of finite CME signals is seen in midcentral (intermediate impact parameter) collisions. Significant residual background effects may, however, still be present.

BackgroundNVX-CoV2373 is an adjuvanted, recombinant spike protein nanoparticle vaccine that was shown to have clinical efficacy for the prevention of coronavirus disease 2019 (Covid-19) in phase 2b-3 trials in the United Kingdom and South Africa, but its efficacy had not yet been tested in North America.MethodsWe conducted a phase 3, randomized, observer-blinded, placebo-controlled trial in the United States and Mexico during the first half of 2021 to evaluate the efficacy and safety of NVX-CoV2373 in adults (≥18 years of age) who had not had severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Participants were randomly assigned in a 2:1 ratio to receive two doses of NVX-CoV2373 or placebo 21 days apart. The primary objective was to determine vaccine efficacy against reverse-transcriptase-polymerase-chain-reaction-confirmed Covid-19 occurring at least 7 days after the second dose. Vaccine efficacy against moderate-to-severe disease and against different variants was also assessed.ResultsOf the 29,949 participants who underwent randomization between December 27, 2020, and February 18, 2021, a total of 29,582 (median age, 47 years; 12.6% ≥65 years of age) received at least one dose: 19,714 received vaccine and 9868 placebo. Over a period of 3 months, 77 cases of Covid-19 were noted - 14 among vaccine recipients and 63 among placebo recipients (vaccine efficacy, 90.4%; 95% confidence interval [CI], 82.9 to 94.6; P

Measurement by the STAR experiment at RHIC of the cold nuclear matter (CNM) effects experienced by inclusive J/ψ at mid-rapidity in 0-100% p+Au collisions at sNN = 200 GeV is presented. Such effects are quantified utilizing the nuclear modification factor, RpAu, obtained by taking a ratio of J/ψ yield in p+Au collisions to that in p+p collisions scaled by the number of binary nucleon-nucleon collisions. The differential J/ψ yield in both p+p and p+Au collisions is measured through the dimuon decay channel, taking advantage of the trigger capability provided by the Muon Telescope Detector in the RHIC 2015 run. Consequently, the J/ψ RpAu is derived within the transverse momentum (pT) range of 0 to 10 GeV/c. A suppression of approximately 30% is observed for pT

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

BackgroundHuman immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is still among the leading causes of disease burden and mortality in sub-Saharan Africa (SSA), and the world is not on track to meet targets set for ending the epidemic by the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the United Nations Sustainable Development Goals (SDGs). Precise HIV burden information is critical for effective geographic and epidemiological targeting of prevention and treatment interventions. Age- and sex-specific HIV prevalence estimates are widely available at the national level, and region-wide local estimates were recently published for adults overall. We add further dimensionality to previous analyses by estimating HIV prevalence at local scales, stratified into sex-specific 5-year age groups for adults ages 15-59 years across SSA.MethodsWe analyzed data from 91 seroprevalence surveys and sentinel surveillance among antenatal care clinic (ANC) attendees using model-based geostatistical methods to produce estimates of HIV prevalence across 43 countries in SSA, from years 2000 to 2018, at a 5 × 5-km resolution and presented among second administrative level (typically districts or counties) units.ResultsWe found substantial variation in HIV prevalence across localities, ages, and sexes that have been masked in earlier analyses. Within-country variation in prevalence in 2018 was a median 3.5 times greater across ages and sexes, compared to for all adults combined. We note large within-district prevalence differences between age groups: for men, 50% of districts displayed at least a 14-fold difference between age groups with the highest and lowest prevalence, and at least a 9-fold difference for women. Prevalence trends also varied over time; between 2000 and 2018, 70% of all districts saw a reduction in prevalence greater than five percentage points in at least one sex and age group. Meanwhile, over 30% of all districts saw at least a five percentage point prevalence increase in one or more sex and age group.ConclusionsAs the HIV epidemic persists and evolves in SSA, geographic and demographic shifts in prevention and treatment efforts are necessary. These estimates offer epidemiologically informative detail to better guide more targeted interventions, vital for combating HIV in SSA.

The chiral magnetic effect (CME) is predicted to occur as a consequence of a local violation of P and CP symmetries of the strong interaction amidst a strong electromagnetic field generated in relativistic heavy-ion collisions. Experimental manifestation of the CME involves a separation of positively and negatively charged hadrons along the direction of the magnetic field. Previous measurements of the CME-sensitive charge-separation observables remain inconclusive because of large background contributions. To better control the influence of signal and backgrounds, the STAR Collaboration performed a blind analysis of a large data sample of approximately 3.8 billion isobar collisions of Ru4496+Ru4496 and Zr4096+Zr4096 at sNN=200 GeV. Prior to the blind analysis, the CME signatures are predefined as a significant excess of the CME-sensitive observables in Ru+Ru collisions over those in Zr+Zr collisions, owing to a larger magnetic field in the former. A precision down to 0.4% is achieved, as anticipated, in the relative magnitudes of the pertinent observables between the two isobar systems. Observed differences in the multiplicity and flow harmonics at the matching centrality indicate that the magnitude of the CME background is different between the two species. No CME signature that satisfies the predefined criteria has been observed in isobar collisions in this blind analysis.