What Distinguishes Weight-Loss Maintainers from the Treatment-Seeking Obese? Analysis of Environmental, Behavioral, and Psychosocial Variables in Diverse Populations

Background Understanding the factors that influence successful weight control is critical for developing interventions. Purpose The purpose of the study was to provide a comprehensive understanding of the role of psychosocial, environmental, and behavioral variables in distinguishing weight-loss maintainers (WLM) from treatment-seeking obese (TSO). Methods WLM (n=167) had lost ≥10% of their maximum body weight, had kept the weight off for ≥5 years, and were now of normal weight. TSO-1 and TSO-2 had a history of dieting and body mass index ≥25. TSO-1 was predominantly Caucasian; TSO-2 was predominantly African-American. Bayesian model averaging was used to identify the variables that distinguished WLM from TSO-1 and TSO-2. Results The variables that most consistently discriminated WLM from TSO were more physical activity (ORs = 3.95 and 2.85), more dietary restraint (ORs = 1.63 and 1.41), and less dietary disinhibition (ORs = 0.69 and 0.83). Environmental variables, including the availability of physical activity equipment, TVs, and high-fat foods in the home, also distinguished WLM from TSO. Conclusions Obesity treatment should focus on increasing conscious control over eating, engaging in physical activity, and reducing disinhibition. Changes in the home environment may help facilitate these behavioral changes

Developmental differences in the influence of phonological similarity on spoken word processing in Mandarin Chinese.

The developmental trajectory of spoken word recognition has been well established in Indo-European languages, but to date remains poorly characterized in Mandarin Chinese. In this study, typically developing children (N=17; mean age 10; 5) and adults (N=17; mean age 24) performed a picture-word matching task in Mandarin while we recorded ERPs. Mismatches diverged from expectations in different components of the Mandarin syllable; namely, word-initial phonemes, word-final phonemes, and tone. By comparing responses to different mismatch types, we uncovered evidence suggesting that both children and adults process words incrementally. However, we also observed key developmental differences in how subjects treated onset and rime mismatches. This was taken as evidence for a stronger influence of top-down processing on spoken word recognition in adults compared to children. This work therefore offers an important developmental component to theories of Mandarin spoken word recognition

MicroRNA profiling reveals marker of motor neuron disease in ALS models

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder marked by the loss of motor neurons (MNs) in the brain and spinal cord, leading to fatally debilitating weakness. Because this disease predominantly affects MNs, we aimed to characterize the distinct expression profile of that cell type to elucidate underlying disease mechanisms and to identify novel targets that inform on MN health during ALS disease time course. microRNAs (miRNAs) are short, noncoding RNAs that can shape the expression profile of a cell and thus often exhibit cell-type-enriched expression. To determine MN-enriched miRNA expression, we used Cre recombinase-dependent miRNA tagging and affinity purification in mice. By defining thein vivomiRNA expression of MNs, all neurons, astrocytes, and microglia, we then focused on MN-enriched miRNAs via a comparative analysis and found that they may functionally distinguish MNs postnatally from other spinal neurons. Characterizing the levels of the MN-enriched miRNAs in CSF harvested from ALS models of MN disease demonstrated that one miRNA (miR-218) tracked with MN loss and was responsive to an ALS therapy in rodent models. Therefore, we have used cellular expression profiling tools to define the distinct miRNA expression of MNs, which is likely to enrich future studies of MN disease. This approach enabled the development of a novel, drug-responsive marker of MN disease in ALS rodents.SIGNIFICANCE STATEMENTAmyotrophic lateral sclerosis (ALS) is a neurodegenerative disease in which motor neurons (MNs) in the brain and spinal cord are selectively lost. To develop tools to aid in our understanding of the distinct expression profiles of MNs and, ultimately, to monitor MN disease progression, we identified small regulatory microRNAs (miRNAs) that were highly enriched or exclusive in MNs. The signal for one of these MN-enriched miRNAs is detectable in spinal tap biofluid from an ALS rat model, where its levels change as disease progresses, suggesting that it may be a clinically useful marker of disease status. Furthermore, rats treated with ALS therapy have restored expression of this MN RNA marker, making it an MN-specific and drug-responsive marker for ALS rodents.</jats:p

Visualizing Exotic Orbital Texture in the Single-Layer Mott Insulator 1T-TaSe2

Mott insulating behavior is induced by strong electron correlation and can lead to exotic states of matter such as unconventional superconductivity and quantum spin liquids. Recent advances in van der Waals material synthesis enable the exploration of novel Mott systems in the two-dimensional limit. Here we report characterization of the local electronic properties of single- and few-layer 1T-TaSe2 via spatial- and momentum-resolved spectroscopy involving scanning tunneling microscopy and angle-resolved photoemission. Our combined experimental and theoretical study indicates that electron correlation induces a robust Mott insulator state in single-layer 1T-TaSe2 that is accompanied by novel orbital texture. Inclusion of interlayer coupling weakens the insulating phase in 1T-TaSe2, as seen by strong reduction of its energy gap and quenching of its correlation-driven orbital texture in bilayer and trilayer 1T-TaSe2. Our results establish single-layer 1T-TaSe2 as a useful new platform for investigating strong correlation physics in two dimensions

Larger females have more calves: influence of maternal body length on fecundity in North Atlantic right whales

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Stewart, J., Durban, J., Europe, H., Fearnbach, H., Hamilton, P., Knowlton, A., Lynn, M., Miller, C., Perryman, W., Tao, B., & Moore, M. Larger females have more calves: influence of maternal body length on fecundity in North Atlantic right whales. Marine Ecology Progress Series, 689, (2022): 179–189, https://doi.org/10.3354/meps14040.North Atlantic right whales (NARW) are critically endangered and have been declining in abundance since 2011. In the past decade, human-caused mortalities from vessel strikes and entanglements have been increasing, while birth rates in the population are at a 40 yr low. In addition to declining abundance, recent studies have shown that NARW length-at-age is decreasing due to the energetic impacts of sub-lethal entanglements, and that the body condition of the population is poorer than closely related southern right whales. We examined whether shorter body lengths are associated with reduced fecundity in female NARW. We compared age-corrected, modeled metrics of body length with 3 metrics of fecundity: age at first reproduction, average inter-birth interval, and the number of calves produced per potential reproductive year. We found that body length is significantly related to birth interval and calves produced per reproductive year, but not age at first reproduction. Larger whales had shorter inter-birth intervals and produced more calves per potential reproductive year. Larger whales also had higher lifetime calf production, but this was a result of larger whales having longer potential reproductive spans, as body lengths have generally been declining over the past 40 yr. Declining body sizes are a potential contributor to low birth rates over the past decade. Efforts to reduce entanglements and vessel strikes could help maintain population viability by increasing fecundity and improving resiliency of the population to other anthropogenic and climate impacts.Funding to the New England Aquarium for curation of the photo-identification catalog is provided by NOAA Contract 1305M2- 18-P-NFFM-0108

Donor whole blood DNA methylation is not a strong predictor of acute graft versus host disease in unrelated donor allogeneic haematopoietic cell transplantation

Allogeneic hematopoietic cell transplantation (HCT) is used to treat many blood-based disorders and malignancies. While this is an effective treatment, it can result in serious adverse events, such as the development of acute graft-versus-host disease (aGVHD). This study aimed to develop a donor-specific epigenetic classifier that could be used in donor selection in HCT to reduce the incidence of aGVHD. The discovery cohort of the study consisted of 288 donors from a population receiving HLA-A, -B, -C and -DRB1 matched unrelated donor HCT with T cell replete peripheral blood stem cell grafts for treatment of acute leukaemia or myelodysplastic syndromes after myeloablative conditioning. Donors were selected based on recipient aGVHD outcome; this cohort consisted of 144 cases with aGVHD grades III-IV and 144 controls with no aGVHD that survived at least 100 days post-HCT matched for sex, age, disease and GVHD prophylaxis. Genome-wide DNA methylation was assessed using the Infinium Methylation EPIC BeadChip (Illumina), measuring CpG methylation at &gt;850,000 sites across the genome. Following quality control, pre-processing and exploratory analyses, we applied a machine learning algorithm (Random Forest) to identify CpG sites predictive of aGVHD. Receiver operating characteristic (ROC) curve analysis of these sites resulted in a classifier with an encouraging area under the ROC curve (AUC) of 0.91. To test this classifier, we used an independent validation cohort (n=288) selected using the same criteria as the discovery cohort. Different attempts to validate the classifier using the independent validation cohort failed with the AUC falling to 0.51. These results indicate that donor DNA methylation may not be a suitable predictor of aGVHD in an HCT setting involving unrelated donors, despite the initial promising results in the discovery cohort. Our work highlights the importance of independent validation of machine learning classifiers, particularly when developing classifiers intended for clinical use

IRF5 promotes influenza-induced inflammatory responses in human iPSC-derived myeloid cells and murine models.

Recognition of Influenza A virus (IAV) by the innate immune system triggers pathways that restrict viral replication, activates innate immune cells, and regulates adaptive immunity. However, excessive innate immune activation can exaggerate disease. The pathways promoting excessive activation are incompletely understood, with limited experimental models to investigate mechanisms driving influenza-induced inflammation in humans. Interferon regulatory factor (IRF5) is a transcription factor that plays important roles in induction of cytokines after viral sensing. In an in vivo model of IAV infection, IRF5 deficiency reduced IAV-driven immune pathology and associated inflammatory cytokine production, specifically reducing cytokine-producing myeloid cell populations in Irf5-/- mice, but not impacting type 1 IFN production or virus replication. Using cytometry by time-of-flight (CyTOF), we identified that human lung IRF5 expression was highest in cells of the myeloid lineage. To investigate the role of IRF5 in mediating human inflammatory responses by myeloid cells to IAV, we employed human induced pluripotent stem cells (hIPSCs) with biallelic mutations in IRF5, demonstrating for the first time iPS-derived dendritic cells (iPS-DCs) with biallelic mutations can be used to investigate regulation of human virus-induced immune responses. Using this technology, we reveal that IRF5 deficiency in human DCs, or macrophages, corresponded with reduced virus-induced inflammatory cytokine production, with IRF5 acting downstream of TLR7 and, possibly, RIG-I after viral sensing. Thus, IRF5 acts as a regulator of myeloid cell inflammatory cytokine production during IAV infection in mice and humans, and drives immune-mediated viral pathogenesis independently of type 1 IFN and virus replication.ImportanceThe inflammatory response to Influenza A virus (IAV) participates in infection control but contributes to disease severity. After viral detection intracellular pathways are activated, initiating cytokine production, but these pathways are incompletely understood. We show that interferon regulatory factor 5 (IRF5) mediates IAV-induced inflammation and, in mice, drives pathology. This was independent of antiviral type 1 IFN and virus replication, implying that IRF5 could be specifically targeted to treat influenza-induced inflammation. We show for the first time that human iPSC technology can be exploited in genetic studies of virus-induced immune responses. Using this technology, we deleted IRF5 in human myeloid cells. These IRF5-deficient cells exhibited impaired influenza-induced cytokine production and revealed that IRF5 acts downstream of Toll-like receptor 7 and possibly retinoic acid-inducible gene-I. Our data demonstrate the importance of IRF5 in influenza-induced inflammation, suggesting genetic variation in the IRF5 gene may influence host susceptibility to viral diseases.This work was supported by The Wellcome Trust. This work was funded by a Wellcome 641 Trust Senior Research Fellowship to Ian Humphreys (207503/Z/17/Z); Medical Research 642 Council, United Kingdom (MR/L018942/1 and MRC Human Immunology Unit Core); 643 Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences 644 (CIFMS), China (grant number: 2018-I2M-2-002). The Wellcome Trust Sanger Institute was 645 the source of the Kolf2 human induced pluripotent cell line which was generated under the 646 Human Induced Pluripotent Stem Cell Initiative funded by a grant from the Wellcome Trust Downloaded from http://jvi.asm.org/ on March 2, 2020 at CAMBRIDGE UNIV27 and Medical Research Council, supported 647 by the Wellcome Trust (WT098051) and the 648 NIHR/Wellcome Trust Clinical Research Facility, and Life Science Technologies 649 Corporation provided Cytotune for reprogramming. We thank the Wellcome Trust Sanger Institute Gene editing pipeline for generation of IRF5-/- 650 iPSCs and the Mass spectrometry 651 Facility at the Weatherall Institute of Molecular Medicine for help with CyTOF experiments

Towards Accurate Differential Diagnosis with Large Language Models

An accurate differential diagnosis (DDx) is a cornerstone of medical care, often reached through an iterative process of interpretation that combines clinical history, physical examination, investigations and procedures. Interactive interfaces powered by Large Language Models (LLMs) present new opportunities to both assist and automate aspects of this process. In this study, we introduce an LLM optimized for diagnostic reasoning, and evaluate its ability to generate a DDx alone or as an aid to clinicians. 20 clinicians evaluated 302 challenging, real-world medical cases sourced from the New England Journal of Medicine (NEJM) case reports. Each case report was read by two clinicians, who were randomized to one of two assistive conditions: either assistance from search engines and standard medical resources, or LLM assistance in addition to these tools. All clinicians provided a baseline, unassisted DDx prior to using the respective assistive tools. Our LLM for DDx exhibited standalone performance that exceeded that of unassisted clinicians (top-10 accuracy 59.1% vs 33.6%, [p = 0.04]). Comparing the two assisted study arms, the DDx quality score was higher for clinicians assisted by our LLM (top-10 accuracy 51.7%) compared to clinicians without its assistance (36.1%) (McNemar's Test: 45.7, p < 0.01) and clinicians with search (44.4%) (4.75, p = 0.03). Further, clinicians assisted by our LLM arrived at more comprehensive differential lists than those without its assistance. Our study suggests that our LLM for DDx has potential to improve clinicians' diagnostic reasoning and accuracy in challenging cases, meriting further real-world evaluation for its ability to empower physicians and widen patients' access to specialist-level expertise

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin