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Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires knowledge of the spatial drivers of river microbiomes. However, understanding of the core microbial processes governing river biogeochemistry is hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we used a community science effort to accelerate the sampling, sequencing and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb profiles the identity, distribution, function and expression of microbial genomes across river surface waters covering 90% of United States watersheds. Specifically, GROWdb encompasses microbial lineages from 27 phyla, including novel members from 10 families and 128 genera, and defines the core river microbiome at the genome level. GROWdb analyses coupled to extensive geospatial information reveals local and regional drivers of microbial community structuring, while also presenting foundational hypotheses about ecosystem function. Building on the previously conceived River Continuum Concept1, we layer on microbial functional trait expression, which suggests that the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures2,3, so that it can be widely accessed across disciplines for watershed predictive modelling and microbiome-based management practices.

Candida parapsilosis is known to cause severe and persistent outbreaks in clinical settings. Patients infected with multidrug-resistant C. parapsilosis (MDR Cp) isolates were identified in a large Turkish hospital from 2017-2020. We subsequently identified three additional patients infected with MDR Cp isolates in 2022 from the same hospital and two echinocandin-resistant (ECR) isolates from a single patient in another hospital. The increasing number of MDR and ECR isolates contradicts the general principle that the severe fitness cost associated with these phenotypes could prevent their dominance in clinical settings. Here, we employed a multidimensional approach to systematically assess the fitness costs of MDR and ECR C. parapsilosis isolates. Whole-genome sequencing revealed a novel MDR genotype infecting two patients in 2022. Despite severe in vitro defects, the levels and tolerances of the biofilms of our ECR and MDR isolates were generally comparable to those of susceptible wild-type isolates. Surprisingly, the MDR and ECR isolates showed major alterations in their cell wall components, and some of the MDR isolates consistently displayed increased tolerance to the fungicidal activities of primary human neutrophils and were more immunoevasive during exposure to primary human macrophages. Our systemic infection mouse model showed that MDR and ECR C. parapsilosis isolates had comparable fungal burden in most organs relative to susceptible isolates. Overall, we observed a notable increase in the genotypic diversity and frequency of MDR isolates and identified MDR and ECR isolates potentially capable of causing persistent outbreaks in the future.

Exposure to social adversity has been associated with cortisol dysregulation during pregnancy and in later childhood; less is known about how prenatal exposure to social stressors affects postnatal cortisol of infants. In a secondary analysis of data from a longitudinal study, we tested whether a pregnant woman's reports of social adversity during the third trimester were associated with their infant's resting cortisol at 1, 6, and 12 months postnatal. Our hypothesis was that prenatal exposure to social adversity would be associated with elevation of infants' cortisol. Measures included prenatal survey reports of social stressors and economic hardship, and resting cortisol levels determined from infant saliva samples acquired at each postnatal timepoint. Data were analyzed using linear mixed effects models. The final sample included 189 women and their infants (46.56% assigned female sex at birth). Prenatal economic hardship was significantly associated with infant cortisol at 6 months postnatal; reports of social stressors were not significantly associated with cortisol at any time point. Factors associated with hardship, such as psychological distress or nutritional deficiencies, may alter fetal HPA axis development, resulting in elevated infant cortisol levels. Developmental changes unique to 6 months of age may explain effects at this timepoint. More work is needed to better comprehend the complex pre- and post-natal physiologic and behavioral factors that affect infant HPA axis development and function, and the modifying role of environmental exposures.

BACKGROUNDDespite an overall poor prognosis, about 15% of patients with advanced-stage tubo-ovarian high-grade serous carcinoma (HGSC) survive 10 or more years after standard treatment.METHODSWe evaluated the tumor microenvironment of this exceptional, understudied group using a large international cohort enriched for long-term survivors (LTS; 10+ years; n = 374) compared with mid-term (MTS; 5-7.99 years; n = 433) and short-term survivors (STS; 2-4.99 years; n = 416). Primary tumor samples were immunostained and scored for intraepithelial and intrastromal densities of 10 immune-cell subsets (including T cells, B cells, plasma cells, myeloid cells, PD-1+ cells, and PD-L1+ cells) and epithelial content.RESULTSPositive associations with LTS compared with STS were seen for 9 of 10 immune-cell subsets. In particular, the combination of intraepithelial CD8+ T cells and intrastromal B cells showed near 5-fold increased odds of LTS compared with STS. All of these associations were stronger in tumors with high epithelial content and/or the C4/Differentiated molecular subtype, despite immune-cell densities generally being higher in tumors with low epithelial content and/or the C2/Immunoreactive molecular subtype.CONCLUSIONThe tumor microenvironment of HGSC LTS is distinguished by the intersection of T and B cell coinfiltration, high epithelial content, and C4/differentiated molecular subtype, features which may inspire new approaches to immunotherapy.FUNDINGOvarian Cancer Research Program (OCRP) of the Congressionally Directed Medical Research Program (CDMRP), U.S. Department of Defense (DOD); American Cancer Society; BC Cancer Foundation; Canada's Networks of Centres of Excellence; Canadian Cancer Society; Canadian Institutes of Health Research; Cancer Councils of New South Wales, Victoria, Queensland, South Australia, and Tasmania, Cancer Foundation of Western Australia; Cancer Institute NSW; Cancer Research UK; Deutsche Forschungsgesellschaft; ELAN Funds of the University of Erlangen-Nuremberg; Fred C. and Katherine B. Andersen Foundation; Genome BC; German Cancer Research Center; German Federal Ministry of Education and Research, Programme of Clinical Biomedical Research; Instituto de Salud Carlos III; Mayo Foundation; Minnesota Ovarian Cancer Alliance; Ministerio de Economía y Competitividad; Medical Research Council (MRC); National Center for Advancing Translational Sciences; National Health and Medical Research Council of Australia (NHMRC); Ovarian Cancer Australia; Peter MacCallum Foundation; Sydney West Translational Cancer Research Centre; Terry Fox Research Institute; The Eve Appeal (The Oak Foundation); UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; University of Pittsburgh School of Medicine; U.S. National Cancer Institute of the National Institutes of Health; VGH & UBC Hospital Foundation; Victorian Cancer Agency.

The Cryogenic Underground Observatory for Rare Events (CUORE) is a detector array comprised by 988 5  cm×5  cm×5  cm TeO_{2} crystals held below 20 mK, primarily searching for neutrinoless double-beta decay in ^{130}Te. Unprecedented in size among cryogenic calorimetric experiments, CUORE provides a promising setting for the study of exotic throughgoing particles. Using the first tonne year of CUORE's exposure, we perform a search for hypothesized fractionally charged particles (FCPs), which are well-motivated by various standard model extensions and would have suppressed interactions with matter. Across the searched range of charges e/24-e/2 no excess of FCP candidate tracks is observed over background, setting leading limits on the underground FCP flux with charges e/24-e/5 at 90% confidence level. Using the low background environment and segmented geometry of CUORE, we establish the sensitivity of tonne-scale subkelvin detectors to diverse signatures of new physics.

Single-crystal X-ray diffraction and electron paramagnetic resonance (EPR) spectroscopic experiments, complemented by quantum chemical DFT calculations, were carried out on the copper-doped metal-organic hybrid and Tutton salt analogue zinc creatininium sulfate to determine its crystal structure, to characterize the electronic structure of the doped Cu(II) binding site, and to propose a pathway for an excited-state, proton-coupled electron transfer (PCET) process in UV-exposed crystals. The crystal structure is isomorphous to that of cadmium creatininium sulfate, which has the transition ion, not in direct coordination with the creatinine, but forming a hexahydrate complex, which is bridged to a creatininium through an intervening sulfate ion. The EPR g (2.446, 2.112, 2.082) and copper hyperfine (ACu: -327, -59.6, 10.8 MHz) tensor parameters are consistent with doped copper replacing host zinc in the metal-hexahydrate complex. These parameters are similar to those observed for copper hexahydrate in doped Tutton salt systems at low temperature, where the unpaired electron occupies mainly the copper 3dx2-y2 orbital. At room temperature in the Tutton systems, vibration couplings stemming from a dynamic Jahn-Teller effect cause tensor averaging which results in a reduction in their maximum g-tensor and hyperfine tensor values. However, like for the doped isomorphous Cd creatinine crystal, the Cu(II) EPR exhibits little, or no room temperature averaging compared to its low temperature pattern. Samples exposed to 254 nm UV light generate a carbon-centered free radical species, characterized by an isotropic g-tensor (g = 2.0029) and an alpha-proton hyperfine coupling (-24 -14 +4 G). These parameters identify it as a creatinine radical cation formed by the oxidative release of one of its C2 methylene hydrogens. DFT calculations confirm the unpaired electronic structures of both the Cu(II) site and free radical. The growth in radical concentration with an increase in the UV exposure time coincides with a decrease in the copper EPR signal, indicating a coupled light-induced oxidation reduction process. A comparison of the crystal structure with the EPR parameters and DFT results provides evidence for a UV-induced PCET.

ABSTRACT: Gravitational lensing magnification of Type Ia supernovae (SNe Ia) allows information to be obtained about the distribution of matter on small scales. In this paper, we derive limits on the fraction $\alpha$ of the total matter density in compact objects (which comprise stars, stellar remnants, small stellar groupings, and primordial black holes) of mass M > 0.03 ${\rm M}_{\odot }$ over cosmological distances. Using 1532 SNe Ia from the Dark Energy Survey Year 5 sample (DES-SN5YR) combined with a Bayesian prior for the absolute magnitude M, we obtain α < 0.12 at the 95 per cent confidence level after marginalization over cosmological parameters, lensing due to large-scale structure, and intrinsic non-Gaussianity. Similar results are obtained using priors from the cosmic microwave background, baryon acoustic oscillations, and galaxy weak lensing, indicating our results do not depend on the background cosmology. We argue our constraints are likely to be conservative (in the sense of the values we quote being higher than the truth), but discuss scenarios in which they could be weakened by systematics of the order of $\Delta \alpha \sim 0.04$.

White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables us to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (i) LNM-informed markers surpass WMH volumes in predicting cognitive performance; and (ii) WMH contributing to cognitive impairment map to specific brain networks. We analysed cross-sectional data of 3485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in four cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based grey and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in grey and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson-Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.

A search for heavy right-handed Majorana neutrinos is performed with the ATLAS detector at the CERN Large Hadron Collider, using the 140  fb−1 of proton–proton collision data at s=13  TeV collected during Run 2. This search targets tt¯ production, in which both top quarks decay into a bottom quark and a W boson, where one of the W bosons decays hadronically and the other decays into an electron or muon and a heavy neutral lepton. The heavy neutral lepton is identified through a decay into an electron or muon and another W boson, resulting in a pair of same-charge same-flavor leptons in the final state. This paper presents the first search for heavy neutral leptons in the mass range of 15–75 GeV using tt¯ events. No significant excess is observed over the background expectation, and upper limits are placed on the signal cross sections. Assuming a benchmark scenario of the phenomenological type-I seesaw model, these cross section limits are then translated into upper limits on the mixing parameters of the heavy Majorana neutrino with Standard Model neutrinos. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

IntroductionIdentifying low-cost, minimally-invasive screening instruments for Alzheimer's disease (AD) trial enrichment will improve the efficiency of AD trials.MethodsA total of 685 cognitively normal (CN) individuals and individuals with mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were grouped according to cutoffs of genetic risk factor (G) polygenic hazard score (PHS) and tau pathology (T) plasma phosphorylated tau-181 (p-tau181) into four groups: G+T+, G-T-, G+T-, and G-T+. We assessed the associations between group level and longitudinal cognitive decline and AD conversion. Power analyses compared the estimated sample size required to detect differences in cognitive decline.ResultsThe G+T+ group was associated with faster cognitive decline and higher AD risk. Clinical trials enrolling G+T+ participants would benefit from significantly reduced sample sizes compared with similar trials using only single makers as an inclusion criterion.DiscussionThe combination of two low-cost, minimally-invasive measures-genetics and plasma biomarkers-would be a promising screening procedure for clinical trial enrollment.HighlightsParticipants with unimpaired or mildly impaired cognition were grouped based on cutoffs on genetic risk factors (G: polygenic hazardous score [PHS]) and Alzheimer's pathology (T: baseline plasma phosphorylated tau-181 [p-tau181]). Participants with high PHSs and plasma p-tau181 levels (G+T+) were at risk of faster cognitive decline and AD progression. The combination of PHS and plasma p-tau181 could enhance clinical trial enrichment more effectively than using single biomarkers.

BACKGROUND: The IMvigor210 trial demonstrated clinical benefit and manageable toxicity with atezolizumab monotherapy [anti-programmed death-ligand 1 (PD-L1)] in patients with metastatic urothelial carcinoma (UC) in primary analyses. Final efficacy and safety results after long-term follow-up are reported. PATIENTS AND METHODS: This phase II single-arm trial of atezolizumab monotherapy in patients with advanced UC included two cohorts: untreated patients ineligible for cisplatin-based chemotherapy (cohort 1; n = 119) and those previously treated with platinum-based chemotherapy (cohort 2; n = 310). Atezolizumab was administered i.v. (1200 mg every 21 days) until progression or unacceptable toxicity. Primary endpoints were independent review facility-assessed confirmed objective response rate (ORR) per RECIST 1.1 in cohort 1 and independent review facility-assessed ORR per RECIST 1.1 and investigator-assessed modified (m)RECIST in cohort 2. Overall survival (OS), efficacy by PD-L1 status, and safety were also assessed. RESULTS: At data cut-off (1 June 2023), the median survival follow-up was 96.4 months (range, 0.2-103.4 months) in cohort 1 and 46.2 months [0.2 (censored)-54.9 months] in cohort 2. In cohort 1, the ORR [95% confidence interval (CI)] was 23.5% (16.2% to 32.2%) in all patients and 28.1% (13.8% to 46.8%) in the PD-L1 tumor-infiltrating immune cell (IC)2/3 subgroup. Median OS (95% CI) was 16.3 months (10.4-24.5 months) overall and 12.3 months (6.0-49.8 months) in the PD-L1 IC2/3 subgroup. In cohort 2, the ORR (95% CI) was 16.5% (12.5% to 21.1%) per RECIST 1.1 and 19.7% (95% CI 15.4% to 24.6%) per mRECIST in all patients and 27.0% (18.6% to 36.8%) and 28.0% (19.5% to 37.9%), respectively, in the PD-L1 IC2/3 subgroup. Median OS (95% CI) was 7.9 months (6.7-9.3 months) in all patients and 11.9 months (9.0-22.8 months) in the IC2/3 subgroup. Treatment-related grade 3/4 adverse events occurred in 21.8% (cohort 1) and 18.7% (cohort 2); one treatment-related death occurred in cohort 1. CONCLUSIONS: With long-term follow-up, atezolizumab monotherapy demonstrated clinically meaningful efficacy with durable responses in a subset of patients with metastatic UC; there were no new safety signals.

The organophosphate (OP)-hydrolyzing enzyme phosphotriesterase (PTE, variant L7ep-3a) immobilized within a partially oxidized mesoporous silicon nanoparticle cage is synthesized and the catalytic performance of the enzyme@nanoparticle construct for hydrolysis of a simulant, dimethyl p-nitrophenyl phosphate (DMNP), and the live nerve agent VX is benchmarked against the free enzyme. In a neutral aqueous buffer, the optimized construct shows a ≈2-fold increase in the rate of DMNP turnover relative to the free enzyme. Enzyme@nanoparticles with more hydrophobic surface chemistry in the interior of the pores show lower catalytic activity, suggesting the importance of hydration of the pore interior on performance. The enzyme@nanoparticle construct is readily separated from the neutralized agent; the nanoparticle is found to retain DMNP hydrolysis activity through seven decontamination/recovery cycles. The nanoparticle cage stabilizes the enzyme against thermal denaturing and enzymatic (trypsin) degradation conditions relative to free enzyme. When incorporated into a topical gel formulation, the PTE-loaded nanoparticles show high activity toward the nerve agent VX in an ex vivo rabbit skin model. In vitro acetylcholinesterase (AChE) assays in human blood show that the enzyme@nanoparticle construct decontaminates VX, preserving the biological function of AChE when exposed to an otherwise incapacitating dose.

Regional and global environmental challenges have become increasingly complex and require broader solutions than a single discipline can provide. Although there is a growing need for interdisciplinary research, many graduate education programs still train students within the confines of a particular discipline or specialty. The Ridge 2 Reef research traineeship program at the University of California, Irvine, aimed to provide transferable and interdisciplinary skill training to prepare graduate students from different disciplines to address current and future environmental challenges. The program achieved its goals through a ‘culture of improvement’ that ensured trainee needs shaped program management and curriculum. Due to trainee feedback and leaders dedicated to program improvement, there was a complete course overhaul during the first two years of the program, resulting in a final curriculum structure that was more effective and aligned with revised program goals. Program evaluations suggest that the flexibility of the program, diversity of training, overhauled courses offered, and partnership-focused opportunities contributed to more confident graduate students who were more broadly trained and better prepared in their chosen environmental career paths. Based on evaluation surveys, graduate students reported significant gains in scientific, technical, and career knowledge as well as transferrable skills in communication, data analysis, leadership, mentoring, and interdisciplinary collaboration. The structure and evolution of the Ridge 2 Reef traineeship can provide a framework for other graduate education programs to better incorporate interdisciplinary training and student feedback, ultimately improving programs and preparing scientists for the 21st century workforce.

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

BackgroundIndividuals with Down syndrome (DS) are at high risk of early-onset Alzheimer's disease (AD); yet, some 20 percent do not develop any signs of dementia until after 65 years or in their lifetime. Mosaicism could contribute to this phenotypic variation, where some disomic cells could lead to lower levels of gene products from chromosome 21.MethodsWe examined longitudinal neuropsychological and biomarker data from two large studies of DS: the Alzheimer Biomarker Consortium-Down syndrome study (ABC-DS) (n = 357); and a legacy study (n = 468). We assessed mosaicism using karyotyping or GWAS data. Participants had data on plasma AD biomarkers (Aβ40, Aβ42, tau, and NfL) and longitudinal cognitive measures. A subset had cerebrospinal fluid biomarkers (Aβ40, Aβ42, tau, ptau181, and NfL) and amyloid and tau PET data.FindingsFor both cohorts, the prevalence of mosaicism was

We examined the relationship between subjective and objective sleep outcomes and loneliness in older women at risk for Alzheimer's disease (AD). Our sample consisted of 39 participants (aged 65+) with mild cognitive deficits who completed the UCLA Loneliness Scale, the Pittsburgh Sleep Quality Index (PSQI), and an at home sleep test, to determine presence of obstructive sleep apnea. Based on sleep quality scores, individuals categorized as "poor sleepers" had significantly higher loneliness scores than "good sleepers." However, total loneliness scores did not significantly differ between groups with or without sleep apnea. We found that higher loneliness was significantly associated to lower habitual sleep efficiency and sleep duration and was also influenced by use of sleep medication. Our findings suggest that increased loneliness relates to worse subjective sleep quality, but not to sleep apnea. These findings suggest that combined interventions targeting loneliness and sleep quality may be important for older women.

BackgroundGestational nutrition can protect against adverse neurodevelopmental outcomes.ObjectivesWe developed a short tool for collecting maternal nutritional intake during pregnancy to facilitate research in this area and compared its retrospective use to prospectively-collected food frequency questionnaires (FFQ).MethodsMaternal nutritional intake was retrospectively assessed using three versions (full interview, full self-administered online, and shortened interview) of the Early Life Exposure Assessment Tool (ELEAT) among participants of the MARBLES pregnancy cohort study of younger siblings of autistic children. Retrospective responses were compared with responses to supplement questions and the validated 2005 Block FFQ prospectively collected in MARBLES during pregnancies 2-7 years prior. ELEAT nutrient values were calculated using reported food intake frequencies and nutrient values from the USDA nutrient database. Correlations between retrospectively- and prospectively-reported intake were evaluated using Kappa coefficients, Youden's J, and Spearman Rank Correlation Coefficients (rs).ResultsMARBLES FFQ dietary intakes were compared among 54 women who completed the ELEAT full form including 12 online, and among 23 who completed the ELEAT short form. Correlations across most foods were fair to moderate. Most ELEAT quantified nutrient values were moderately correlated (rs = 0.3-0.6) with those on the Block FFQ. Supplement questions in both MARBLES and the ELEAT were completed by 114 women. Kappas were moderate for whether or not supplements were taken, but modest for timing. Correlations varied by version and child diagnosis or concerns, and were higher when mothers completed the ELEAT when their child was 4 years old or younger.ConclusionsWith recall up to several years, ELEAT dietary and supplement module responses were modestly to moderately reliable and produced nutrient values moderately correlated with prospectively-collected measures. The ELEAT dietary and vitamin supplements modules can be used to rank participants in terms of intake of several nutrients relevant for neurodevelopment.

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pile-up) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two.

The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R&D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments.

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.

Our understanding of brain iron regulation and its disruption in disease is limited. Excess iron affects motor circuitry, contributing to Parkinson's disease (PD) risk. The molecular mechanisms regulating central iron levels, beyond a few well-known genes controlling peripheral iron, remain unclear. We generated scores based on the archetypal brain iron accumulation observed in magnetic resonance imaging scans of individuals with excessive dietary iron absorption and hemochromatosis risk. Genome-wide analysis revealed that this score is highly heritable, identifying loci associated with iron homeostasis, and driven by peripheral iron levels. Our score predicted gait abnormalities and showed a U-shaped relationship with PD risk, identifying individuals with threefold increased risk. These results establish a hormetic relationship between brain iron and PD risk, where central iron levels are strongly determined by genetics via peripheral iron. This framework combining forward and reverse genetics is a powerful study design to understand genomic drivers underlying high dimensional phenotypes.

Psychedelics hold promise as alternate treatments for neuropsychiatric disorders. However, the neural mechanisms by which they drive adaptive behavioral effects remain unclear. We isolated the specific neurons modulated by a psychedelic to determine their role in driving behavior. Using a light- and calcium-dependent activity integrator, we genetically tagged psychedelic-responsive neurons in the medial prefrontal cortex (mPFC) of mice. Single-nucleus RNA sequencing revealed that the psychedelic drove network-level activation of multiple cell types beyond just those expressing 5-hydroxytryptamine 2A receptors. We labeled psychedelic-responsive mPFC neurons with an excitatory channelrhodopsin to enable their targeted manipulation. We found that reactivation of these cells recapitulated the anxiolytic effects of the psychedelic without driving its hallucinogenic-like effects. These findings reveal essential insight into the cell-type-specific mechanisms underlying psychedelic-induced behavioral states.

In this work we use Lagrangian perturbation theory to analyze the harmonic space galaxy clustering signal of the Bright Galaxy Survey (BGS) and luminous red galaxies (LRGs) targeted by the dark energy spectroscopic instrument (DESI), combined with the galaxy-galaxy lensing signal measured around these galaxies using Dark Energy Survey Year 3 source galaxies. The BGS and LRG galaxies are extremely well characterized by DESI spectroscopy and, as a result, lens galaxy redshift uncertainty and photometric systematics contribute negligibly to the error budget of our "2×2-point"analysis. On the modeling side, this work represents the first application of the spinosaurus code, implementing an effective field theory model for galaxy intrinsic alignments, and we additionally introduce a new scheme (maiar) for marginalizing over the large uncertainties in the redshift evolution of the intrinsic alignment signal. Furthermore, this is the first application of a hybrid effective field theory model for galaxy bias based on the aemulus ν simulations. Our main result is a measurement of the amplitude of the lensing signal, S8=σ8(ωm/0.3)0.5=0.850-0.050+0.042, consistent with values of this parameter derived from the primary cosmic microwave background. This constraint is artificially improved by a factor of 51% if we assume a more standard, but restrictive parametrization for the redshift evolution and sample dependence of the intrinsic alignment signal, and 63% if we additionally assume the nonlinear alignment model. We show that when fixing the cosmological model to the best-fit values from Planck PR4 there is >5σ evidence for a deviation of the evolution of the intrinsic alignment signal from the functional form that is usually assumed in cosmic shear and galaxy-galaxy lensing studies.

Galaxy scaling relations provide insights into the processes that drive galaxy evolution. The extension of these scaling relations into the dwarf galaxy regime is of particular interest. This is because dwarf galaxies represent a crucial stage in galaxy evolution, and understanding them could also shed light on their role in reionizing the early Universe. There is currently no consensus on the processes that dominate the evolution of dwarfs. In this work, we constrain the atomic gas sequence (stellar mass versus atomic gas fraction) and mass–metallicity relation (stellar mass versus gas-phase metallicity) from dwarf (106.5 M) to massive (1011.5 M) galaxies in the local Universe. The combined optical and 21-cm spectroscopic observations of the Dark Energy Spectroscopic Instrument and Arecibo Legacy Fast ALFA surveys allow us to constrain both scaling relations simultaneously. We find a slope change of the atomic gas sequence at a stellar mass of ∼109 M. We also find that the shape and scatter of the atomic gas sequence and mass–metallicity relation are strongly linked for both dwarfs and more massive galaxies. Consequently, the low-mass slope change of the atomic gas sequence is imprinted onto the mass–metallicity relation of dwarf galaxies. The mass scale of the measured slope change is consistent with a predicted escape velocity threshold below which low-mass galaxies experience significant supernova-driven gas loss, as well as with a reduction in cold gas accretion onto more massive galaxies.

A high-nuclearity {Ni18} complex (1) with a unique 'flying saucer' motif has been prepared from the organic chelate, α-methyl-2-pyridine-methanol (mpmH), in conjunction with bridging azido (N3 -) and peroxido (O2 2-) ligands. Magnetic susceptibility measurements revealed the presence of both ferro- and antiferromagnetic exchange interactions between the metal centres in 1, and the stabilization of spin states with appreciable S values at two different temperature regimes. The end-on bridging azido and alkoxido groups are in all likelihood the ferromagnetic mediators, while the η3:η3:μ6-bridging peroxides most likely promote the antiparallel alignment of the metals' spin vectors, yielding an overall non-zero spin ground state for the centrosymmetric compound 1. Furthermore, the {Ni18} nanosized cluster behaves as a single-molecule magnet, exhibiting magnetic hysteresis at low temperatures and two relaxation processes at 15 K and 1.3 K, a very rare phenomenon in polynuclear magnetic 3d-metal clusters.

This manuscript details the development of an asymmetric variant for the Ni-photoredox α-arylation of tetrahydrofuran (THF), which was originally reported in a racemic fashion by Doyle and Molander. Leveraging the enantioselectivity data that we obtained, a complex mechanistic scenario different from those originally proposed is uncovered. Specifically, an unexpected dependence of the product enantiomeric ratio was observed on both the halide identity (aryl chloride vs bromide substrates) and the Ni source. Stoichiometric experiments and time course analyses of the evolution of product enantioselectivity with time revealed a different initial behavior for reactions carried out with Ni(II) and Ni(0) precatalysts that later converge into a common mechanism. For studying the predominant pathway, this paper describes a rare example of the syntheses of chiral bisoxazoline Ni(II) aryl halide complexes, which proved essential for probing enantioselectivity via stochiometric experiments. These experiments identify the Ni(II) aryl halide complex as the primary species involved in the key THF radical trapping event. A multivariate linear regression model is presented that further validates the dominant mechanism and delineates structure-selectivity relationships between ligand properties and enantioselectivity. EPR analysis of Ni(0)/aryl halide mixtures highlights the fast access to a variety of Ni complexes in 0, +1, and +2 oxidation states that are proposed to be responsible for the initial divergence in mechanism observed when using Ni(0) precatalysts. More broadly, beyond advancing the mechanistic understanding of this THF arylation protocol, this work underscores the potential of leveraging enantioselectivity data to unravel intricate mechanistic manifolds within Ni-photoredox catalysis.

The recent advent of autonomous laboratories, coupled with algorithms for high-throughput screening and active learning, promises to accelerate materials discovery and innovation. As these autonomous systems grow in complexity, the demand for robust and efficient workflow management software becomes increasingly critical. In this paper, we introduce AlabOS, a general-purpose software framework for orchestrating experiments and managing resources, with an emphasis on automated laboratories for materials synthesis and characterization. AlabOS features a reconfigurable experiment workflow model and a resource reservation mechanism, enabling the simultaneous execution of varied workflows composed of modular tasks while eliminating conflicts between tasks. To showcase its capability, we demonstrate the implementation of AlabOS in a prototype autonomous materials laboratory, the A-Lab, with around 3500 samples synthesized over 1.5 years.

Genome-wide association studies typically evaluate the autosomes and sometimes the X Chromosome, but seldom consider the Y or mitochondrial (MT) Chromosomes. We genotyped the Y and MT Chromosomes in heterogeneous stock (HS) rats (Rattus norvegicus), an outbred population created from 8 inbred strains. We identified 8 distinct Y and 4 distinct MT Chromosomes among the 8 founders. However, only 2 types of each nonrecombinant chromosome were observed in our modern HS rat population (generations 81-97). Despite the relatively large sample size, there were virtually no significant associations for behavioral, physiological, metabolome, or microbiome traits after correcting for multiple comparisons. However, both Y and MT Chromosomes were strongly associated with the expression of a few genes located on those chromosomes, which provided a positive control. Our results suggest that within modern HS rats there are no Y and MT Chromosomes differences that strongly influence behavioral or physiological traits. These results do not address other ancestral Y and MT Chromosomes that do not appear in modern HS rats, nor do they address effects that may exist in other rat populations, or in other species.

Exposure to polychlorinated biphenyls (PCBs) is linked to neurotoxic effects. This study aims to close knowledge gaps regarding the specific modes of action of PCBs in female C57BL/6J mice (>6 weeks) orally exposed for 7 weeks to a human-relevant PCB mixture (MARBLES mix) at 0, 0.1, 1, and 6 mg/kg body weight/day. PCB and hydroxylated PCB (OH-PCBs) levels were quantified in the brain, liver, and serum; RNA sequencing was performed in the striatum, prefrontal cortex, and liver, and metabolomic analyses were performed in the striatum. Profiles of PCBs but not their hydroxylated metabolites were similar in all tissues. In the prefrontal cortex, PCB exposure activated the oxidative phosphorylation respiration pathways, while suppressing the axon guidance pathway. PCB exposure significantly changed the expression of genes associated with neurodevelopmental and neurodegenerative diseases in the striatum, impacting pathways like growth hormone synthesis and dendrite development. PCBs did not affect the striatal metabolome. In contrast to the liver, which showed activation of metabolic processes following PCB exposure and the induction of cytochrome P450 enzymes, the expression of xenobiotic processing genes was not altered by PCB exposure in either brain region. Network analysis revealed complex interactions between individual PCBs (e.g., PCB28 [2,4,4'-trichlorobiphenyl]) and their hydroxylated metabolites and specific differentially expressed genes (DEGs), underscoring the need to characterize the association between specific PCBs and DEGs. These findings enhance the understanding of PCB neurotoxic mechanisms and their potential implications for human health.

In the United States, hundreds of thousands of undocumented orphan wells have been abandoned, leaving the burden of managing environmental hazards to governmental agencies or the public. These wells, a result of over a century of fossil fuel extraction without adequate regulation, lack basic information like location and depth, emit greenhouse gases, and leak toxic substances into groundwater. For most of these wells, basic information such as well location and depth is unknown or unverified. Addressing this issue necessitates innovative and interdisciplinary approaches for locating, characterizing, and mitigating their environmental impacts. Our survey of the United States revealed the need for tools to identify well locations and assess conditions, prompting the development of technologies including machine learning to automatically extract information from old records (95%+ accuracy), remote sensing technologies like aero-magnetometers to find buried wells, and cost-effective methods for estimating methane emissions. Notably, fixed-wing drones equipped with magnetometers have emerged as cost-effective and efficient for discovering unknown wells, offering advantages over helicopters and quadcopters. Efforts also involved leveraging local knowledge through outreach to state and tribal governments as well as citizen science initiatives. These initiatives aim to significantly contribute to environmental sustainability by reducing greenhouse gases and improving air and water quality.

The copy number of a plasmid is linked to its functionality, yet there have been few attempts to optimize higher-copy-number mutants for use across diverse origins of replication in different hosts. We use a high-throughput growth-coupled selection assay and a directed evolution approach to rapidly identify origin of replication mutations that influence copy number and screen for mutants that improve Agrobacterium-mediated transformation (AMT) efficiency. By introducing these mutations into binary vectors within the plasmid backbone used for AMT, we observe improved transient transformation of Nicotiana benthamiana in four diverse tested origins (pVS1, RK2, pSa and BBR1). For the best-performing origin, pVS1, we isolate higher-copy-number variants that increase stable transformation efficiencies by 60-100% in Arabidopsis thaliana and 390% in the oleaginous yeast Rhodosporidium toruloides. Our work provides an easily deployable framework to generate plasmid copy number variants that will enable greater precision in prokaryotic genetic engineering, in addition to improving AMT efficiency.

Abstract: Boasting a 6.5 m mirror in space, JWST can increase by several times the number of supernovae (SNe) to which a redshift-independent distance has been measured with a precision distance indicator (e.g., tip of the red giant branch (TRGB) or Cepheids); the limited number of such SN calibrators currently dominates the uncertainty budget in distance ladder Hubble constant (H 0) experiments. JWST/NIRCAM imaging of the Virgo Cluster galaxy NGC 4536 is used here to preview JWST program GO-1995, which aims to measure H 0 using three stellar distance indicators (Cepheids, TRGB, and J-branch asymptotic giant branch/carbon stars). Each population of distance indicator was here successfully detected—with sufficiently large number statistics, well-measured fluxes, and characteristic distributions consistent with ingoing expectations—so as to confirm that we can acquire distances from each method precise to about 0.05 mag (statistical uncertainty only). We leverage overlapping Hubble Space Telescope imaging to identify TRGB stars, crossmatch them with the JWST photometry, and present a preliminary constraint on the slope of the TRGB’s F115W versus (F115W – F444W) relation equal to −0.99 ± 0.16 mag mag−1. This slope is consistent with prior slope measurements in the similar Two Micron All-Sky Survey J band, as well as with predictions from the BaSTI isochrone suite. We use the new TRGB slope estimate to flatten the 2D TRGB feature and measure a (blinded) TRGB distance relative to a set of fiducial TRGB colors, intended to represent the absolute fiducial calibrations expected from geometric anchors such as NGC 4258 and the Magellanic Clouds. In doing so, we empirically demonstrate that the TRGB can be used as a standardizable candle at the IR wavelengths accessible with JWST.

We present the Lyα Continuum Analysis Network (LyCAN), a convolutional neural network that predicts the unabsorbed quasar continuum within the rest-frame wavelength range of 1040-1600 Å based on the red side of the Lyα emission line (1216-1600 Å). We developed synthetic spectra based on a Gaussian mixture model representation of nonnegative matrix factorization (NMF) coefficients. These coefficients were derived from high-resolution, low-redshift (z < 0.2) Hubble Space Telescope/Cosmic Origins Spectrograph (COS) quasar spectra. We supplemented this COS-based synthetic sample with an equal number of DESI Year 5 mock spectra. LyCAN performs extremely well on testing sets, achieving a median error in the forest region of 1.5% on the DESI mock sample, 2.0% on the COS-based synthetic sample, and 4.1% on the original COS spectra. LyCAN outperforms principal component analysis (PCA) and NMF-based prediction methods using the same training set by 40% or more. We predict the intrinsic continua of 83,635 DESI Year 1 spectra in the redshift range of 2.1 ≤ z ≤ 4.2 and perform an absolute measurement of the evolution of the effective optical depth. This is the largest sample employed to measure the optical depth evolution to date. We fit a power law of the form τ ( z ) = τ 0 ( 1 + z ) γ to our measurements and find τ 0 = (2.46 ± 0.14) × 10−3 and γ = 3.62 ± 0.04. Our results show particular agreement with high-resolution, ground-based observations around z = 2, indicating that LyCAN is able to predict the quasar continuum in the forest region with only spectral information outside the forest.

Pressure solution is inferred to be a significant contributor to sediment compaction and lithification, especially in carbonate sediments. For a sediment deforming primarily by pressure solution, the compaction rate should be directly related to the rate of calcite dissolution, transport along grain contacts, and calcite reprecipitation. Previous experimental work has shown that there is evidence that deformation in wet calcite grain packs is consistent with control by pressure solution, but considerable ambiguity remains regarding the rate limiting mechanism. We present the results of laboratory compaction experiments designed to directly measure calcite dissolution and precipitation rates (recrystallization rates) concurrently with strain rate to test whether measured rates are consistent with predicted rates both in absolute magnitude and time evolution. Recrystallization rates are measured using trace element chemistry (Sr/Ca, Mg/Ca) and isotopes (87Sr/86Sr) of fluids flowing slowly through a compacting grain pack as it is being triaxially compressed. Imaging techniques are used to characterize the grain contacts and strain effects in the post-experiment grain pack. Our data show that calcite recrystallization rates calculated from all three geochemical parameters are in approximate agreement and that the rates closely track strain rate. The geochemically inferred rates are close to predicted rates in absolute magnitude. Uncertainty in grain contact dimensions makes distinguishing between surface reaction control and diffusion control difficult. Measured reaction rates decrease faster than predicted from standard pressure solution creep flow laws. This inconsistency may indicate that calcite dissolution rates at grain contacts are more complex, and more time-dependent, than suggested by geometric models designed to predict grain contact stresses.

Traumatic brain injuries (TBI) are the seventh leading cause of disability globally with 48.99 million prevalent cases and 7.08 million years lived with diability. Approximately 80 % of TBI patients are diagnosed with mild TBI (mTBI), or concussion, caused by nonpenetrating mechanical trauma to the head or body along with sudden rotational motion of the head. Studies investigating the temporal dynamics of neuroinflammation after mTBI are greatly needed. Without longitudinal studies, translating preclinical studies to clinical studies remains challenging as the difference in timing remains poorly understood. In this study, we describe a method of minimally invasive serial cerebrospinal fluid (CSF) collection that enables longitudinal investigation of CSF inflammation. The method described in this study can easily be adapted by any laboratory prepared for animal studies. Multiplex immunoassay of serially collected and singly collected CSF samples show collection frequency does not alter protein expression in the CSF. Further, sex-dependent differences in TBI have been reported, but remain poorly understood. This study establishes a framework for assessing sex difference in neuroinflammation after a concussion. We showed that results vary based on the framing of the statistical test. However, it is evident that males experience a more robust inflammatory response to a single concussion than females.

ObjectiveThe COVID-19 pandemic had profound effects on society, including those living with chronic pain. This study sought to examine pandemic impacts on individuals enrolled in pragmatic clinical trials focused on nonpharmacological treatments for chronic pain.MethodsWe evaluated responses to a questionnaire on COVID-19 impacts that had been administered to participants (n=2024) during study enrollment in 3 pragmatic clinical trials for chronic pain treatment. All trials were part of the National Institutes of Health (NIH)-Department of Veterans Affairs (VA)-Department of Defense (DOD) Pain Management Collaboratory. COVID-19-related impacts on access to health care, mental health, finances, ability to meet basic needs, and social support were assessed.ResultsPandemic impacts were found in all domains assessed, including access to health care, mental and emotional health, ability to meet basic needs, finances, and social support. Impacts varied by demographic and clinical characteristics. The participants most negatively impacted by the pandemic were younger, Black or Latino, female, more educated, and unemployed and had screened positive for depression. No impact differences were found with regard to alcohol use disorder screenings or a prior history of COVID-19. Higher levels of pain were associated with worse pandemic impacts, and negative impacts declined over time.ConclusionsNegative impacts of the pandemic on individuals living with chronic pain cut across aspects of life that are also central to effective pain management, including access to health care, social support, and mental and emotional health, with differential impacts found across key demographic and clinical factors. These findings should yield consideration of pandemic impacts in clinical practice and as moderating effects of treatment outcomes in clinical trials conducted during the pandemic.

Durable and conductive interfaces that enable chronic and high-resolution recording of neural activity are essential for understanding and treating neurodegenerative disorders. These chronic implants require long-term stability and small contact areas. Consequently, they are often coated with a blend of conductive polymers and are crosslinked to enhance durability despite the potentially deleterious effect of crosslinking on the mechanical and electrical properties. Here the grafting of the poly(3,4 ethylenedioxythiophene) scaffold, poly(styrenesulfonate)-b-poly(poly(ethylene glycol) methyl ether methacrylate block copolymer brush to gold, in a controlled and tunable manner, by surface-initiated atom-transfer radical polymerization (SI-ATRP) is described. This "block-brush" provides high volumetric capacitance (120 F cm─3), strong adhesion to the metal (4 h ultrasonication), improved surface hydrophilicity, and stability against 10 000 charge-discharge voltage sweeps on a multiarray neural electrode. In addition, the block-brush film showed 33% improved stability against current pulsing. This approach can open numerous avenues for exploring specialized polymer brushes for bioelectronics research and application.

BackgroundSubstance use is a public crisis in the U.S. Substance use can be understood as a series of events in the life course, from initiation to mortality. Social Determinants of Health (SDoH) have increasingly been recognized as essential contributors to individuals' health. This scoping review aims to examine available evidence of SDoH impact on the life course of substance use disorder (SUD).MethodsThis study identified peer-reviewed articles that reported longitudinal studies with SDoH factors as independent variables and substance use and disorders as dependent variables from PubMed, Embase, and Web of Science. The reported associations between SDoH and substance use stages over the life course were narratively and graphically summarized.ResultsAmong the 50 studies identified, ten revealed parental monitoring/support and early childhood education as protective factors, while negative peer influences and neighborhood instability were risk factors of substance use initiation. Nineteen articles reported factors associated with escalation in substance use, including unemployment, neighborhood vulnerability, negative peer influence, violence/trauma, and criminal justice system (CJS) involvement. Ten articles suggested that employment, social support, urban living, and low-barrier medication treatment facilitated treatment participation, while stigma and CJS involvement had negative impact on treatment trajectory. Social support and employment could foster progress in recovery and CJS involvement and unstable housing deterred recovery. Four studies suggested that unemployment, unstable housing, CJS involvement, and lack of social support were associated with overdose and mortality.ConclusionsThis review underscores the influence of social networks and early life experiences on the life course of SUD. Future SDoH research should investigate overdose and mortality and the impact of broader upstream SDoH on SUD. Interventions addressing these social factors are needed to mitigate their detrimental effects on the trajectories of SUD over the life course.

We report the p+p and p+d differential cross sections measured in the SeaQuest experiment for J/ψ and ψ(2S) production at [Formula presented] beam energy covering the forward x-Feynman (xF) range of 0.5

A search is presented for direct pair production of the stop, the supersymmetric partner of the top quark, in a decay through an R-parity violating coupling to a charged lepton and a b-quark. The dataset corresponds to an integrated luminosity of 140  fb−1 of proton-proton collisions at a center-of-mass energy of s=13  TeV collected between 2015 and 2018 by the ATLAS detector at the LHC. The final state has two charged leptons (electrons or muons) and two b-jets. The results of the search are interpreted in the context of a Minimal Supersymmetric Standard Model with an additional B−L gauge symmetry that is spontaneously broken. No significant excess is observed over the Standard Model background, and exclusion limits on stop pair production are set at 95% confidence level. The corresponding lower limits on the stop mass for 100% branching ratios to a b-quark and an electron, muon, or tau-lepton are 1.9 TeV, 1.8 TeV and 800 GeV, respectively, extending the reach of previous LHC searches. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Previous studies have reported alterations in cortical thickness in autism. However, few have included enough autistic females to determine if there are sex specific differences in cortical structure in autism. This longitudinal study aimed to investigate autistic sex differences in cortical thickness and trajectory of cortical thinning across childhood. Participants included 290 autistic (88 females) and 139 nonautistic (60 females) individuals assessed at up to 4 timepoints spanning ~2-13 years of age (918 total MRI timepoints). Estimates of cortical thickness in early and late childhood as well as the trajectory of cortical thinning were modeled using spatiotemporal linear mixed effects models of age-by-sex-by-diagnosis. Additionally, the spatial correspondence between cortical maps of sex-by-diagnosis differences and neurotypical sex differences were evaluated. Relative to their nonautistic peers, autistic females had more extensive cortical differences than autistic males. These differences involved multiple functional networks, and were mainly characterized by thicker cortex at ~3 years of age and faster cortical thinning in autistic females. Cortical regions in which autistic alterations were different between the sexes significantly overlapped with regions that differed by sex in neurotypical development. Autistic females and males demonstrated some shared differences in cortical thickness and rate of cortical thinning across childhood relative to their nonautistic peers, however these areas were relatively small compared to the widespread differences observed across the sexes. These results support evidence of sex-specific neurobiology in autism and suggest that processes that regulate sex differentiation in the neurotypical brain contribute to sex differences in the etiology of autism.

The tauopathies are defined by pathological tau protein aggregates within a spectrum of clinically heterogeneous neurodegenerative diseases. The primary tauopathies meet the definition of rare diseases in the United States. There is no approved treatment for primary tauopathies. In this context, designing the most efficient development programs to translate promising targets and treatments from preclinical studies to early-phase clinical trials is vital. In September 2022, the Rainwater Charitable Foundation convened an international expert workshop focused on the translation of tauopathy therapeutics through early-phase trials. Our report on the workshop recommends a framework for principled drug development and a companion lexicon to facilitate communication focusing on reproducibility and achieving common elements. Topics include the selection of targets, drugs, biomarkers, participants, and study designs. The maturation of pharmacodynamic biomarkers to demonstrate target engagement and surrogate disease biomarkers is a crucial unmet need. HIGHLIGHTS: Experts provided a framework to translate therapeutics (discovery to clinical trials). Experts focused on the "5 Rights" (target, drug, biomarker, participants, trial). Current research on frontotemporal degeneration, progressive supranuclear palsy, and corticobasal syndrome therapeutics includes 32 trials (37% on biologics) Tau therapeutics are being tested in Alzheimer's disease; primary tauopathies have a large unmet need.

BackgroundChronic pain leads to tau accumulation and hippocampal atrophy, which may be moderated through inflammation. In older men, we examined associations of chronic pain with Alzheimer's disease (AD)-related plasma biomarkers and hippocampal volume as moderated by systemic inflammation.MethodsParticipants were men without dementia. Chronic pain was defined as moderate-to-severe pain in 2+ study waves at average ages 56, 62, and 68. At age 68, we measured plasma amyloid-beta (Aβ42, n = 871), Aβ40 (n = 887), total tau (t-tau, n = 841), and neurofilament light chain (NfL, n = 915), and serum high-sensitivity C-reactive protein (hs-CRP, n = 968), a marker of systemic inflammation. A subgroup underwent structural MRI to measure hippocampal volume (n = 385). Analyses adjusted for medical morbidities, depressive symptoms, and opioid use.ResultsChronic pain was related to higher Aβ40 (β = 0.25, p = .009), but hs-CRP was unrelated to AD-related biomarkers (ps > .05). There was a significant interaction such that older men with both chronic pain and higher levels of hs-CRP had higher levels of Aβ42 (β = 0.36, p = .001) and Aβ40 (β = 0.29, p = .003). Chronic pain and hs-CRP did not interact to predict levels of Aβ42/Aβ40, t-tau, or NfL. Furthermore, there were significant interactions such that Aβ42 and Aβ40 were associated with lower hippocampal volume, particularly when levels of hs-CRP were elevated (hs-CRP × Aβ42: β = -0.19, p = .002; hs-CRP × Aβ40: β = -0.21, p = .001), regardless of chronic pain status.ConclusionsChronic pain was associated with higher plasma Aβ, especially when hs-CRP was also elevated. Higher hs-CRP and Aβ levels were both related to smaller hippocampal volumes. Chronic pain, when accompanied by systemic inflammation, may elevate the risk of neurodegeneration in AD-vulnerable regions.

The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. The hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described.