bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epoxy fatty acid dysregulation and neuroinflammation in Alzheimer’s disease is resolved by a soluble epoxide hydrolase inhibitor
Authors: Ghosh Anamitra , Comerota Michele E. , Wan Debin , Chen Fading , Propson Nicholas E. , Hwang Sung Hee , Hammock Bruce D. , Zheng Hui 
Published: July 2020

AbstractNeuroinflammation has been increasingly recognized to play critical roles in Alzheimer’s disease (AD). The epoxy fatty acids (EpFAs) are derivatives of the arachidonic acid metabolism with anti-inflammatory activities. However, their efficacy is limited due to the rapid hydrolysis by the soluble epoxide hydrolase (sEH). We found that sEH is predominantly expressed in astrocytes where its levels are significantly elevated in postmortem human AD brains and in β-amyloid mouse models, and the latter is correlated with drastic reductions of brain EpFA levels. Using a highly potent and specific small molecule sEH inhibitor, 1-trifluoromethoxyphenyl-3-(1-propionylpiperidin-4-yl) urea (TPPU), we report here that TPPU treatment potently protected against LPS-induced inflammation in vitro and in vivo. Long-term administration of TPPU to the 5xFAD mouse model via drinking water reversed microglia and astrocyte reactivity and immune pathway dysregulation, and this is associated with reduced β–amyloid pathology and improved synaptic integrity and cognitive function. Importantly, TPPU treatment reinstated and positively correlated EpFA levels in the 5xFAD mouse brain, demonstrating its brain penetration and target engagement. These findings support TPPU as a novel therapeutic target for the treatment of AD and related disorders.One Sentence SummaryWe show that soluble epoxide hydrolase is upregulated in AD patients and mouse models, and that inhibition of this lipid metabolic pathway using an orally bioavailable small molecule inhibitor is effective in restoring brain epoxy fatty acids, ameliorating AD neuropathology and improving synaptic and cognitive function.
Males deploy multifaceted strategies and hijack longevity pathways to induce premature demise of the opposite sex
Authors: Booth Lauren N. , Shi Cheng , Tantilert Cindy , Yeo Robin W. , Hebestreit Katja , Hollenhorst Cecilia N. , Murphy Coleen T. , Brunet Anne 
Published: July 2020

AbstractInteractions between the sexes negatively impact health in many species, including mammals1–9. In mice, sexual interactions induce weight gain and shorten lifespan in females, independent of fertilization6,9. InCaenorhabditis, males shorten the lifespan of the opposite sex (females or hermaphrodites)1–3,8. However, the mechanisms underlying the negative influence of males on lifespan – and their overlap with known longevity pathways – are still largely unknown. Here, we use transcriptomic profiling and targeted screens to systematically uncover new conserved genes involved in male-induced demise. Interestingly, deficiency of these genes individually, and especially in combination, induces strong protection, highlighting the benefit of combining interventions to extend lifespan. Some genes (e.g.acbp-3, col-43) only extend hermaphrodite lifespan when knocked-down in the presence of males, suggesting specific protective mechanisms against male-induced demise. However, we also uncover two previously unknown longevity genes (sri-40anddelm-2) that, when knocked-down, extend hermaphrodite lifespan both with and without males, which points to new broad mechanisms of resistance. In sharp contrast, many classical long-lived mutants are actually short-lived in the presence of males, suggesting that males hijack and suppress known longevity pathways. This systematic analysis reveals striking differences in longevity in single sex versus mixed sex environments and uncovers the elaborate network of functional regulation elicited by sexual interactions, which could extend to other species.
Consistent cross-modal identification of cortical neurons with coupled autoencoders
Authors: Gala Rohan , Budzillo Agata , Baftizadeh Fahimeh , Miller Jeremy , Gouwens Nathan , Arkhipov Anton , Murphy Gabe , Tasic Bosiljka , Zeng Hongkui , Hawrylycz Michael , Sümbül Uygar 
Published: July 2020

AbstractConsistent identification of neurons in different experimental modalities is a key problem in neuroscience. While methods to perform multimodal measurements in the same set of single neurons have become available, parsing complex relationships across different modalities to uncover neuronal identity is a growing challenge. Here, we present an optimization framework to learn coordinated representations of multimodal data, and apply it to a large multimodal dataset profiling mouse cortical interneurons. Our approach reveals strong alignment between transcriptomic and electrophysiological characterizations, enables accurate cross-modal data prediction, and identifies cell types that are consistent across modalities.HighlightsCoupled autoencoders for multimodal assignment, Analysis of Patch-seq data consisting of more than 3000 cells
Tissue specific muscle extracellular matrix hydrogel improves skeletal muscle regenerationin vivoover non-matched tissue source
Authors: Ungerleider Jessica L. , Dzieciatkowska Monika , Hansen Kirk C. , Christman Karen L. 
Published: July 2020

AbstractDecellularized extracellular matrix (ECM) hydrogels present a novel, clinical intervention for a myriad of regenerative medicine applications. The source of ECM is typically the same tissue to which the treatment is applied; however, the need for tissue specific ECM sources has not been rigorously studied. We hypothesized that tissue specific ECM would improve regeneration through preferentially stimulating physiologically relevant processes (e.g. progenitor cell proliferation and differentiation). One of two decellularized hydrogels (tissue specific skeletal muscle or non mesoderm-derived lung) or saline were injected intramuscularly two days after notexin injection in mice (n=7 per time point) and muscle was harvested at days 5 and 14 for histological and gene expression analysis. Both injectable hydrogels were decellularized using the same detergent and were controlled for donor characteristics (i.e. species, age). At day 5, the skeletal muscle ECM hydrogel significantly increased the density of Pax7+ satellite cells in the muscle. Gene expression analysis at day 5 showed that skeletal muscle ECM hydrogels increased expression of genes implicated in muscle contractility. By day 14, skeletal muscle ECM hydrogels improved muscle regeneration over saline and lung ECM hydrogels as shown through a shift in fiber cross sectional area distribution towards larger fibers. This data indicates a potential role for muscle-specific regenerative capacity of decellularized, injectable muscle hydrogels. Further transcriptomic analysis of whole muscle mRNA indicates the mechanism of tissue specific ECM-mediated tissue repair may be immune and metabolism pathway-driven. Taken together, this suggests there is benefit in using tissue specific ECM for regenerative medicine applications.
Computational Psychiatry Research Map (CPSYMAP): a New Database for Visualizing Research Papers
Authors: Kato Ayaka , Kunisato Yoshihiko , Katahira Kentaro , Okimura Tsukasa , Yamashita Yuichi 
Published: July 2020

AbstractThe field of computational psychiatry is growing in prominence along with the recent advances in computational neuroscience, machine learning, and the cumulative scientific evidence of psychiatric disorders. Computational approaches provide an understanding of disorders using psychological and neuroscience terms and help to determine treatment protocols based on high-dimensional data. However, the multidisciplinary nature of this field seems to limit the development of computational psychiatry studies. Computational psychiatry combines knowledge from neuroscience, psychiatry, and computation; thus, there is an emerging need for a platform to integrate and coordinate these perspectives. In this study, we developed a new database for visualizing research papers as a two-dimensional “map” called the Computational Psychiatry Research Map (CPSYMAP). This map shows the distribution of papers along neuroscientific, psychiatric, and computational dimensions to enable anyone to find niche research and deepen their understanding of the field.
Lockdown measures and relative changes in the age-specific incidence of SARS-CoV-2 in Spain
Authors: De Salazar PM , Gómez-Barroso D , Pampaka D , Gil JM , Peñalver B , Fernández-Escobar C , Lipsitch M , Larrauri A , Goldstein E , Hernán MA 
Published: July 2020

AbstractBackgroundThe first months of the SARS-CoV-2 epidemic in Spain resulted in high incidence and mortality. A national sero-epidemiological survey suggests higher cumulative incidence of infection in older individuals than in younger individuals. However, little is known about the epidemic dynamics in different age groups, including the relative effect of the lockdown measures introduced on March 15, and strengthened on March 30 to April 14, 2020 when only essential workers continued to work.MethodsWe used data from the National Epidemiological Surveillance Network (RENAVE in Spanish) on the daily number of reported COVID-19 cases (by date of symptom onset) in eleven 5-year age groups: 15-19y through 65-69y. For each age group g, we computed the proportion E(g) of individuals in age group g among all reported cases aged 15-69y during the pre-lockdown period (March 1-10, 2020) and the corresponding proportion L(g) during two lockdown periods (March 25-April 3 and April 8-17, 2020). For each lockdown period, we computed the proportion ratios PR(g)= L(g)/E(g). For each pair of age groups g1,g2, PR(g1)>PR(g2) implies a relative increase in the incidence of detected SARS-CoV-2 infection in the age group g1 compared with g2 for the later vs. early period.ResultsFor the first lockdown period, the highest PR values were in age groups 50-54y (PR=1.21; 95% CI: 1.12,1.30) and 55-59y (PR=1.19; 1.11,1.27). For the second lockdown period, the highest PR values were in age groups 15-19y (PR=1.26; 0.95,1.68) and 50-54y (PR=1.20; 1.09,1.31).ConclusionsOur results suggest that different outbreak control measures led to different changes in the relative incidence by age group. During the first lockdown period, when non-essential work was allowed, individuals aged 40-64y, particularly those aged 50-59y presented with higher COVID-19 relative incidence compared to pre-lockdown period, while younger adults/older adolescents (together with persons aged 50-59y) had increased relative incidence during the later, strengthened lockdown. The role of different age groups during the epidemic should be considered when implementing future mitigation efforts.
Identifying main and interaction effects of risk factors to predict intensive care admission in patients hospitalized with COVID-19: a retrospective cohort study in Hong Kong
Authors: Zhou Jiandong , Tse Gary , Lee Sharen , Liu Tong , Wu William KK , Cao Zhidong , Zeng Daniel Dajun , Kei Wong Ian Chi , Zhang Qingpeng , Cheung Bernard Man Yung 
Published: July 2020

ABSTRACTBackgroundThe coronavirus disease 2019 (COVID-19) has become a pandemic, placing significant burdens on the healthcare systems. In this study, we tested the hypothesis that a machine learning approach incorporating hidden nonlinear interactions can improve prediction for Intensive care unit (ICU) admission.MethodsConsecutive patients admitted to public hospitals between 1st January and 24th May 2020 in Hong Kong with COVID-19 diagnosed by RT-PCR were included. The primary endpoint was ICU admission.ResultsThis study included 1043 patients (median age 35 (IQR: 32-37; 54% male). Nineteen patients were admitted to ICU (median hospital length of stay (LOS): 30 days, median ICU LOS: 16 days). ICU patients were more likely to be prescribed angiotensin converting enzyme inhibitors/angiotensin receptor blockers, anti-retroviral drugs lopinavir/ritonavir and remdesivir, ribavirin, steroids, interferon-beta and hydroxychloroquine. Significant predictors of ICU admission were older age, male sex, prior coronary artery disease, respiratory diseases, diabetes, hypertension and chronic kidney disease, and activated partial thromboplastin time, red cell count, white cell count, albumin and serum sodium. A tree-based machine learning model identified most informative characteristics and hidden interactions that can predict ICU admission. These were: low red cells with 1) male, 2) older age, 3) low albumin, 4) low sodium or 5) prolonged APTT. A five-fold cross validation confirms superior performance of this model over baseline models including XGBoost, LightGBM, random forests, and multivariate logistic regression.ConclusionsA machine learning model including baseline risk factors and their hidden interactions can accurately predict ICU admission in COVID-19.
Spatiotemporal Trends in Bed Bug Metrics, New York City
Authors: Hacker Kathryn P. , Greenlee Andrew J. , Hill Alison L. , Schneider Daniel , Levy Michael Z. 
Published: July 2020

AbstractBed bug outbreaks pose a major challenge in urban environments and cause significant strain on public resources. Few studies have systematically analyzed the epidemic or the potential effects of policies to combat bed bugs. Here we use three sources of administrative data to characterize the spatial-temporal trends of bed bug inquiries, complaints, and reports in New York City. From 2014–2020, Bed bug complaints have significantly decreased (p < 0.01), the absolute number of complaints per month dropping by half (875 average complaints per month to 440 average complaints per month); conversely cockroach-specific complaints increased over the same period. Despite the decrease of bed bug complaints, areas with reported high bed bug infestation tend to remain infested, highlighting the persistence of these pests. There are limitations to the datasets; still the evidence available suggests that interventions employed by New York City residents and lawmakers are stemming the bed bug epidemic and may serve as a model for other large cities.
Multitask learning from clinical text and acute physiological conditions differentially improve the prediction of mortality and diagnosis at the ICU
Authors: Reichmann L.G. , Valdes G. , Pirrachio Romain , Interian Y. 
Published: July 2020

AbstractThe prediction of mortality of critically ill patients has stimulated the development of many severity scoring algorithms. The majority of the models use physiological measurements obtained during the first hours of admission (i.e., heart rate, arterial blood pressure, or respiratory rate). In this study, we propose to improve the performance of current scoring system by including free text from patient’s medical history. Although the primary outcome was in-hospital mortality, we chose a model architecture to provide simultaneous assessment of ICD-9 codes and groupings. We hypothesized that including patients’ medical history with a multitask learning approach would improve model performance. We compared the predictive performance obtained with our approach to the best models previously proposed in the literature (baseline models). We used the MIMIC publicly available database which includes > 60,000 ICU admissions between 2001 and 2012. The patients’ condition at admission was accounted for by the preliminary diagnosis at admission and the medical history extracted from the discharge summaries notes. Unstructured data was processed through a Gated Recurrent Units layer with pre-trained word embeddings, and the hidden states were concatenated to the remaining structured-tabular data. Baseline models achieved similar results than in previously published work, but our artificial neural networks models showed significant improvement towards classification of mortality (AUC-ROC = 0.90). Including the medical history improved all tasks but relatively more the ICD-9 codes prediction than the mortality. The clinical prediction model presented here could be used to identify patients’ risk groups, which would improve the quality of ICU care, and further help to efficiently allocate hospital resources.
COVID-MATCH65 – A prospectively derived clinical decision rule for severe acute respiratory syndrome coronavirus 2
Authors: Trubiano Jason A , Vogrin Sara , Smibert Olivia C , Marhoon Nada , Alexander Adrian A , Chua Kyra Y L , James Fiona L , Jones Nicholas RL , Grigg Sam E , Xu Cecilia LH , Moini Nasreen , Stanley Sam R , Birrell Michael T , Rose Morgan T , Gordon Claire L , Kwong Jason C , Holmes Natasha E 
Published: July 2020

AbstractDue to the ongoing COVID-19 pandemic and increased pressure on testing resources, understanding the clinical and epidemiological features closely associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is vital at point of care to enable risk stratification. We demonstrate that an internally derived and validated clinical decision rule, COVID-MATCH65, has a high sensitivity (92.6%) and NPV (99.5%) for SARS-CoV-2 and could be used to aid COVID-19 risk-assessment and resource allocation for SARS-CoV-2 diagnostics.
Characterization of redox sensitive algal mannitol-1-phosphatases of the haloacid dehalogenase superfamily of proteins
Authors: Le Strat Yoran , Tonon Thierry , Leblanc Catherine , Groisillier Agnès 
Published: July 2020

AbstractMacroalgae (or seaweeds) are the dominant primary producers in marine vegetated coastal habitats and largely contribute to global ocean carbon fluxes. They also represent attractive renewable production platforms for biofuels, food, feed, and bioactives, notably due to their diverse and peculiar polysaccharides and carbohydrates. Among seaweeds, brown algae produce alginates and sulfated fucans as constituents of their cell wall, and the photoassimilates laminarin and mannitol for carbon storage. Availability of brown algal genomes, including those of the kelpSaccharina japonicaand the filamentousEctocarpussp., has paved the way for biochemical characterization of recombinant enzymes involved in their polysaccharide and carbohydrates synthesis, notably mannitol. Biosynthesis of mannitol in brown algae starts from fructose-6-phospate, which is converted into mannitol-1-phosphate (M1P), and this intermediate is then hydrolysed by a haloacid dehalogenase type M1P phosphatase (M1Pase) to produce mannitol. We report here the biochemical characterization of a second M1Pase inEctocarpussp after heterologous expression inEscherichia coli. (EsM1Pase1). Our results show that bothEctocarpusM1Pases were redox sensitive, with EsM1Pase1 being active only in presence of reducing agent. Such catalytic properties have not been observed for any of the M1Pase characterized so far. EsM1Pases were specific to mannitol, in contrast toS. japonicaM1Pases that can use other phosphorylated sugars as substrates. Finally, brown algal M1Pases grouped into two well-supported clades, with potential different subcellular localization and physiological role(s) under diverse environmental conditions and/or stages of life cycle.
Recalled parental bonding interacts with oxytocin receptor gene polymorphism in modulating anxiety and avoidance in adult relationships
Authors: Cataldo Ilaria , Bonassi Andrea , Lepri Bruno , Foo Jia Nee , Setoh Peipei , Esposito Gianluca 
Published: July 2020

AbstractEarly interactions with significant individuals affect social experience throughout the course of a lifetime, as a repeated and prolonged perception of different levels of care, independence or control influences the modulation of emotional regulatory processes. As many factors play a role in shaping the expectations and features of social interaction, in this study we consider the influence of parental bonding and genetic allelic variation of oxytocin receptor gene polymorphism (rs53576) over levels of experienced anxiety and avoidance in 313 young adults belonging to two different cultural contexts, namely Italy and Singapore. Results highlight a major effect of maternal characteristics, care and overprotection, with differences between the two cultural groups. Additionally, the interaction between rs53576 and maternal overprotection suggest different environmental susceptibility in the Italian sample and the Singaporean one. Implication in clinical work and future steps are described in the conclusion.
Predictive Metabolic Pathways of Lactic Acid Bacterial Strains Isolated from Fermented Foods
Authors: Kharnaior Pynhunlang , Halami Prakash M. , Tamang Jyoti Prakash 
Published: July 2020

AbstractWe attempted to use PICTRUSt2 software and bioinformatics tool to infer the raw sequences obtained from pure strains of Lactococcus lactis and Lactobacillus plantarum isolated from some fermented foods in India, which were identified by 16S rRNA gene sequencing method. Predictive metabolic pathways of 16S sequences of LAB strains were predicted by PICRUSt2 mapped against KEGG database, which showed genes associated with metabolism (36.74%), environmental information processing (32.34%), genetic information processing (9.86%) and the unclassified (21.06%). KGGE database also showed the dominant genes related to predictive sub-pathways of metabolism at level-2 were membrane transport (31.16%) and carbohydrate metabolism (12.42%).
Phosphoregulation of HORMA domain protein HIM-3 promotes asymmetric synaptonemal complex disassembly in meiotic prophase inC. elegans
Authors: Sato-Carlton Aya , Nakamura-Tabuchi Chihiro , Li Xuan , Boog Hendrik , Lehmer Madison K , Rosenberg Scott C , Barroso Consuelo , Martinez-Perez Enrique , Corbett Kevin D , Carlton Peter Mark 
Published: July 2020

AbstractIn the two cell divisions of meiosis, diploid genomes are reduced into complementary haploid sets through the discrete, two-step removal of chromosome cohesion, a task carried out in most eukaryotes by protecting cohesion at the centromere until the second division. In eukaryotes without defined centromeres, however, alternative strategies have been innovated. The best-understood of these is that used by the nematodeCaenorhabditis elegans, where upon division of the chromosome into two segments or arms by the single off-center crossover, several chromosome-associated proteins or post-translational modifications become specifically partitioned to either the short or long arm, where they affect the timing of cohesion loss through as-yet unknown mechanisms. Here, we investigate the meiotic axis HORMA-domain protein HIM-3 and show that it becomes phosphorylated at its C-terminus, within the conserved “closure motif” region bound by the related HORMA-domain proteins HTP-1 and HTP-2. Binding of HTP-2 is abrogated by phosphorylation of the closure motif inin vitroassays, strongly suggesting thatin vivophosphorylation of HIM-3 likely modulates the hierarchical structure of the chromosome axis. Phosphorylation of HIM-3 only occurs on synapsed chromosomes, and similarly to previously-described phosphorylated proteins of the synaptonemal complex, becomes restricted to the short arm after designation of crossover recombination sites. Regulation of HIM-3 phosphorylation status is required for timely disassembly of synaptonemal complex central elements from the long arm, and is also required for proper timing of HTP-1 and HTP-2 dissociation from the short arm. Phosphorylation of HIM-3 thus plays a role in establishing the identity of short and long arms, thereby contributing to the robustness of the two-step chromosome segregation.