bluuebunny/crossref_metadata_2025 huggingface dataset:
Apoplast-localized β-Glucosidase Elevates Isoflavone Accumulation in the Soybean Rhizosphere
Authors: Matsuda Hinako , Yamazaki Yumi , Moriyoshi Eiko , Nakayasu Masaru , Yamazaki Shinichi , Aoki Yuichi , Takase Hisabumi , Okazaki Shin , Nagano Atsushi J. , Kaga Akito , Yazaki Kazufumi , Sugiyama Akifumi
Published: December 2022

Plant specialized metabolites (PSMs) are often stored as glycosides within cells and released from the roots with some chemical modifications. While isoflavones are known to function as symbiotic signals with rhizobia and to modulate the soybean rhizosphere microbiome, the underlying mechanisms of root-to-soil delivery are poorly understood. In addition to transporter-mediated secretion, the hydrolysis of isoflavone glycosides in the apoplast by an isoflavone conjugate-hydrolyzing β-glucosidase (ICHG) has been proposed but not yet verified. To clarify the role of ICHG in isoflavone supply to the rhizosphere, we have isolated two independent mutants defective in ICHG activity from a soybean high-density mutant library. In theichgmutants, the isoflavone contents and composition in the root apoplast and root exudate significantly changed. When grown in a field, the lack of ICHG activity considerably reduced isoflavone aglycone contents in roots and the rhizosphere soil, although the transcriptomes showed no distinct differences between theichgmutants and WTs. Despite the change in isoflavone contents and composition of the root and rhizosphere of the mutants, root and rhizosphere bacterial communities were not distinctive from those of the WTs. Root bacterial communities and nodulation capacities of theichgmutants did not differ from the WTs under nitrogen-deficient conditions, either. Taken together, these results indicate that ICHG elevates the accumulation of isoflavones in the soybean rhizosphere but is not essential in isoflavone-mediated plant-microbe interactions.
Disentangling shared and group-specific variations in single-cell transcriptomics data with multiGroupVI
Authors: Weinberger Ethan , Lopez Romain , Hütter Jan-Christian , Regev Aviv
Published: December 2022

Single-cell RNA sequencing (scRNA-seq) technologies have enabled a greater understanding of previously unexplored biological diversity. Based on the design of such experiments, individual cells from scRNA-seq datasets can often be attributed to non-overlapping “groups”. For example, these group labels may denote the cell’s tissue or cell line of origin. In this setting, one important problem consists in discerning patterns in the data that are shared across groups versus those that are group-specific. However, existing methods for this type of analysis are mainly limited to (generalized) linear latent variable models. Here we introduce multiGroupVI, a deep generative model for analyzing grouped scRNA-seq datasets that decomposes the data into shared and group-specific factors of variation. We first validate our approach on a simulated dataset, on which we significantly outperform state-of-the-art methods. We then apply it to explore regional differences in an scRNA-seq dataset sampled from multiple regions of the mouse small intestine. We implemented multiGroupVI using the scvi-tools library [1], and released it as open-source software athttps://github.com/Genentech/multiGroupVI.
Host-derived protease promotes aggregation ofStaphylococcus aureusby cleaving the surface protein SasG
Authors: Crosby Heidi A. , Keim Klara , Kwiecinski Jakub M. , Langouët-Astrié Christophe J. , Oshima Kaori , LaRivière Wells B. , Schmidt Eric P. , Horswill Alexander R.
Published: December 2022

Staphylococcus aureusis one of the leading causes of hospital acquired infections, many of which begin following attachment and accumulation on indwelling medical devices or diseased tissue. These infections are often linked to establishment of biofilms, but another often overlooked key characteristic allowingS. aureusto establish persistent infection is formation of planktonic aggregates. Such aggregates are physiologically similar to biofilms and protect pathogen from innate immune clearance and increase its antibiotic tolerance. The cell wall-associated protein SasG has been implicated in biofilm formation via mechanisms of intercellular aggregation, but the mechanism in the context of disease is largely unknown. We have previously shown that expression of cell wall-anchored proteins involved in biofilm formation is controlled by the ArlRS-MgrA regulatory cascade. In this work, we demonstrate that the ArlRS two-component system controls aggregation, by repressing expression ofsasGby activation of the global regulator MgrA. We also demonstrate that SasG must be proteolytically processed by a non-native protease to induce aggregation, and that strains expressing functional full-lengthsasGaggregate significantly upon proteolysis by a mucosal-derived host protease found in human saliva. We used fractionation and N-terminal sequencing to demonstrate that human trypsin within saliva cleaves within the A domain of SasG to expose the B domain and induce aggregation. Finally, we demonstrated that SasG is involved in virulence during mouse lung infection. Together, our data point to SasG, its processing by host proteases, and SasG-driven aggregation as important elements ofS. aureusadaptation to host environment.
Impact of exposure to per- and polyfluoroalkyl substances on fecal microbiota composition in mother-infant dyads
Authors: Lamichhane Santosh , Härkönen Taina , Vatanen Tommi , Hyötyläinen Tuulia , Knip Mikael , Orešič Matej
Published: December 2022

Current evidence suggests that chemical exposure alters gut microbiota composition, with higher exposure to environmental chemicals being associated with reduced microbiome diversity. However, not much is known about the impact of per- and polyfluoroalkyl substances (PFAS) on gut bacteria. Here we set out to identify the gut bacterial species that associate with chemical exposure before (maternal) and after (maternal, infant) birth in a mother-infant series. Paired blood and stool samples were collected from mother-infant dyads (n = 30) in a longitudinal setting. PFAS were quantified in maternal blood to examine their associations with the microbial compositions (determined by shotgun metagenomic sequencing) in mothers and infants. High maternal exposure to PFAS was persistently associated with increased abundance ofMethanobrevibacter smithiiin maternal stool. Among individual PFAS compounds, PFOS and PFHpS showed the strongest connection withM. smithii. However, maternal PFAS exposure associated only weakly with the infant microbiome. Our findings suggest that PFAS exposure contributes to the modulation of the adult gut microbiome composition.
A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records
Authors: Shuey Megan M. , Lee Kyung Min , Keaton Jacob , Khankari Nikhil K. , Breeyear Joseph H. , Walker Venexia M. , Miller Donald R. , Heberer Kent R. , Reaven Peter D. , Clarke Shoa L. , Lee Jennifer , Lynch Julie A. , Vujkovic Marijana , Edwards Todd L.
Published: December 2022

Objectives

The identification of novel uses for existing drug therapies has the potential to provide a rapid, low-cost approach to drug (re)discovery. In the current study we developed and tested a genetically-informed drug-repurposing pipeline for diabetes management.

Design

We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).

Setting

The SCCS experiments were completed using two EHRs: the Million Veterans Program (USA) as the discovery and the Vanderbilt University Medical Center (Tennessee, USA) as the replication.

Results

After filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p=0.01 and -0.85 mg/dL, p=0.02, respectively; MR: OR=0.84, 95% CI=0.81, 0.87, p=5.0×10-25).

Conclusions

Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions.

Summary Boxes

Section 1: What is already known on this topic

Medications with genetic support are significantly more likely to make it through clinical trials.

Section 2: What this study adds

Our results identified two anti-hypertensive medication classes, calcium channel blockers and angiotensin-converting enzyme inhibitors, as genetically supported drug-repurposing targets that demonstrated glycemic measurement reduction in real-world clinical populations. These results suggest patients with diabetes or pre-diabetes could benefit from preferential use of these medication classes when they present with comorbid hypertension or other cardiovascular conditions. Finally, this study demonstrates a successful implementation of a novel genetically-supported drug-repurposing pipeline for diabetes treatment that can be readily adapted and applied to other diseases and as such it has the potential to identify/prioritize drug repurposing targets for these other conditions.
Structural Variants in Linkage Disequilibrium with GWAS-Significant SNPs
Authors: Liang Hao , Sedillo Joni , Schrodi Steven J. , Ikeda Akihiro
Published: December 2022

With the recent expansion of structural variant identification in the human genome, understanding the role of these impactful variants in disease architecture is critically important. Currently, a large proportion of genome-wide-significant GWAS SNPs are functionally unresolved, raising the possibility that some of these SNPs are associated with disease through linkage disequilibrium with causal structural variants. Hence, understanding the linkage disequilibrium between newly discovered structural variants and statistically significant SNPs may provide a resource for further investigation into disease-associated regions in the genome. Here we present a resource cataloging structural variant-significant SNP pairs in high linkage disequilibrium.

Availability

All data files including those detailing SV and GWAS SNP associations and results of GWAS-SNP-SV pairs are available athttps://github.com/hliang-SchrodiLab/SV_SNPs.
Eye structure shapes neuron function inDrosophilamotion vision
Authors: Zhao Arthur , Gruntman Eyal , Nern Aljoscha , Iyer Nirmala A. , Rogers Edward M. , Koskela Sanna , Siwanowicz Igor , Dreher Marisa , Flynn Miriam A. , Laughland Connor W. , Ludwig Henrique D.F. , Thomson Alex G. , Moran Cullen P. , Gezahegn Bruck , Bock Davi D. , Reiser Michael B.
Published: December 2022

Many animals rely on vision to navigate through their environment. The pattern of changes in the visual scene induced by self-motion is theoptic flow1, which is first estimated in local patches by directionally selective (DS) neurons2–4. But how should the arrays of DS neurons, each responsive to motion in a preferred direction at a specific retinal position, be organized to support robust decoding of optic flow by downstream circuits? Understanding this global organization is challenging because it requires mapping fine, local features of neurons across the animal’s field of view3. InDrosophila, the asymmetric dendrites of the T4 and T5 DS neurons establish their preferred direction, making it possible to predict DS responses from anatomy4,5. Here we report that the preferred directions of fly DS neurons vary at different retinal positions and show that this spatial variation is established by the anatomy of the compound eye. To estimate the preferred directions across the visual field, we reconstructed hundreds of T4 neurons in a full brain EM volume6and discovered unexpectedly stereotypical dendritic arborizations that are independent of location. We then used whole-head μCT scans to map the viewing directions of all compound eye facets and found a non-uniform sampling of visual space that explains the spatial variation in preferred directions. Our findings show that the organization of preferred directions in the fly is largely determined by the compound eye, exposing an intimate and unexpected connection between the peripheral structure of the eye, functional properties of neurons deep in the brain, and the control of body movements.
Prediction of white matter hyperintensities evolution one-year post-stroke from a single-point brain MRI and stroke lesions information
Authors: Rachmadi Muhammad Febrian , Valdés-Hernández Maria del C. , Makin Stephen , Wardlaw Joanna , Skibbe Henrik
Published: December 2022

Predicting the evolution of white matter hyperintensities (WMH), a common feature in brain magnetic resonance imaging (MRI) scans of older adults (i.e., whether WMH will grow, remain stable, or shrink with time) is important for personalised therapeutic interventions. However, this task is difficult mainly due to the myriad of vascular risk factors and comorbidities that influence it, and the low specificity and sensitivity of the image intensities and textures alone for predicting WMH evolution. Given the predominantly vascular nature of WMH, in this study, we evaluate the impact of incorporating stroke lesion information to a probabilistic deep learning model to predict the evolution of WMH 1-year after the baseline image acquisition, taken soon after a mild stroke event, using T2-FLAIR brain MRI. The Probabilistic U-Net was chosen for this study due to its capability of simulating and quantifying the uncertainties involved in the prediction of WMH evolution. We propose to use an additional loss called volume loss to train our model, and incorporate stroke lesions information, an influential factor in WMH evolution. Our experiments showed that jointly segmenting the disease evolution map (DEM) of WMH and stroke lesions, improved the accuracy of the DEM representing WMH evolution. The combination of introducing the volume loss and joint segmentation of DEM of WMH and stroke lesions outperformed other model configurations with mean volumetric absolute error of 0.0092ml(down from 1.7739ml) and 0.47% improvement on average Dice similarity coefficient in shrinking, growing and stable WMH.
DNA metabarcoding reveals the dietary profiles of a benthic marine crustacean,Nephrops norvegicus
Authors: Shum Peter , Wäge-Recchioni Janine , Sellers Graham S , Johnson Magnus L , Joyce Domino A.
Published: December 2022

Norwegian lobster,Nephrops norvegicus, are a generalist scavenger and predator capable of short foraging excursions but can also suspension feed. Existing knowledge about their diet relies on a combination of methods including morphology-based stomach content analysis and stable isotopes, which often lack the resolution to distinguish prey items to species level particularly in species that thoroughly masticate their prey. DNA metabarcoding overcomes many of the challenges associated with traditional methods and it is an attractive approach to study the dietary profiles of animals. Here, we present the diet of the commercially valuableNephrops norvegicususing DNA metabarcoding of gut contents. Despite difficulties associated with host amplification, our cytochrome oxidase I (COI) molecular assay successfully achieves higher resolution information than traditional approaches. We detected taxa that were likely consumed during different feeding strategies. Dinoflagellata, Chlorophyta and Bacillariophyta accounted for almost 50% of the prey items consumed, and are associated with suspension feeding, while fish with high fisheries discard rates were detected which are linked to active foraging. In addition, we were able to characterise biodiversity patterns by consideringNephropsas natural samplers, as well as detecting parasitic dinoflagellates (e.g.,Hematodiniumsp.), which are known to influence burrow related behaviour in infected individuals in over 50% of the samples. The metabarcoding data presented here greatly enhances a better understanding of a species’ ecological role and could be applied as a routine procedure in future studies for proper consideration in the management and decision-making of fisheries.
A Noninvasive Skin Biopsy of Free Nerve Endings via Realtime Third-Harmonic Microscopy
Authors: Wu Pei-Jhe , Tseng Hsiao-Chieh , Chao Chi-Chao , Liao Yi-Hua , Yen Chen-Tung , Lin Wen-Ying , Hsieh Sung-Tsang , Sun Wei-Zen , Sun Chi-Kuang
Published: December 2022

Skin biopsy was the only method to provide free-intraepidermal-nerve-endings (FINEs) structural information for the differential diagnosis of small fiber neuropathy (SFN). Its invasive nature was particularly unfavorable for patients with diabetic coagulation abnormalities thus there is an unmet clinical need for a non-invasive FINEs imaging tool. Here we show a tightly-focused epi-Third-harmonic-generation microscope (TFETM) for unmyelinated FINEs imaging. Its label-free capability was confirmed by PGP9.5 immunohistochemistry staining and a longitudinal spared nerve injury model study. Moreover, through proposing a dot-connecting algorithm, we established the operational protocol to count three-dimensionally the intraepidermal nerve fibers (IENF) and define the quantitative IENF index. Our clinical trial showed that the label-free IENF index can differentially identify SFN (P-value=0.0102) and was well correlated with IENF density of skin biopsy (Pearson’s correlation, R-value= 0.98) in the DPN group. Our study suggested that the unstained dot-connecting third-harmonic microscopy imaging can noninvasively provide FINEs structure information assisting diagnosing SFN.
Kestrels of the same colony do not overwinter together
Authors: García-Macía Jorge , Chaouni Munir , Morollón Sara , Bustamante Javier , López-Ricaurte Lina , Martínez-Dalmau Juan , Rodríguez-Moreno Beatriz , Urios Vicente
Published: December 2022

Coloniality is one of the most common strategies in birds. While the lesser kestrel (Falco naumanni) is a colonial raptor during the breeding period, it is not known whether individuals from the same breeding colony aggregate during the non-breeding period too. We GPS-tracked 40 adult lesser kestrels from different Spanish breeding colonies to study the degree of spatial aggregation between individuals from the same breeding colony in their West African non-breeding range. Lesser kestrels in our study used a large area from a wide longitudinal strip in the western Sahel: individuals used 143,697 ± 98,048 km2on average during the entire non-breeding period (95% KDE), and 1,359 ± 1,424 km2per week. On the other hand, the individuals traveled 6205 ± 2407 km on average during the entire non-breeding period, and 41.1 ± 11.8 km per day. There were no differences between the sexes in any of those variables. Individuals from the same breeding colony were not aggregated during the non-breeding period because the overlap between their areas (38.8 ± 21.4 %) was not higher than that randomly expected. In conclusion, our study reveals some aspects of the non-breeding spatial ecology of the lesser kestrel, allowing a better understanding of the relationship of colonial birds out of the breeding season.
Trapalyzer: A computer program for quantitative analyses in fluorescent live-imaging studies of Neutrophil Extracellular Trap formation
Authors: Ciach Michał Aleksander , Bokota Grzegorz , Manda-Handzlik Aneta , Kuźmicka Weronika , Demkow Urszula , Gambin Anna
Published: December 2022

Neutrophil extracellular traps (NETs), pathogen-ensnaring structures formed by neutrophils by expelling their DNA into the environment, are believed to play an important role in immunity and autoimmune diseases. In recent years, a growing attention has been put into developing software tools to quantify NETs in fluorescent microscopy images. However, current solutions require extensive training data sets, are difficult to use for users without background in computer science, or have limited capabilities.

In this work we present Trapalyzer, a computer program for an automatic quantification of NETs in terms of their area and an approximation of their number. In addition, Trapalyzer counts neutrophils at different stages of NET formation, and is the first tool that makes this possible without extensive training data sets. We validate our approach on a publicly available benchmark data set and apply it in a neutrophil-bacteria co-culture experiment. The software and usage tutorials are available athttps://github.com/Czaki/Trapalyzer.
Atypical language network lateralization is reflected throughout the macroscale functional organization of cortex
Authors: Labache Loïc , Ge Tian , Yeo B.T. Thomas , Holmes Avram J.
Published: December 2022

Hemispheric specialization is a fundamental feature of human brain organization. However, it is not yet clear to what extent the lateralization of specific cognitive processes may be evident throughout the broad functional architecture of cortex. While the majority of people exhibit left-hemispheric language dominance, a substantial minority of the population shows reverse lateralization. Using twin and family data from the Human Connectome Project, we provide evidence that atypical language dominance is associated with global shifts in cortical organization. Individuals with atypical language organization exhibited corresponding hemispheric differences in the macroscale functional gradients that situate discrete large-scale networks along a continuous spectrum, extending from unimodal through association territories. Analyses revealed that both language lateralization and gradient asymmetries are, in part, driven by genetic factors. These findings pave the way for a deeper understanding of the origins and relationships linking population-level variability in hemispheric specialization and global properties of cortical organization.
Autofluorescence is a biomarker of neural stem cell activation state
Authors: Morrow Christopher S. , Tweed Kelsey , Arndt Zachary P. , Walsh Alex J. , Peng Bo , Risgaard Ryan D. , Klosa Payton C. , Chi Michelle M. , Wallace Eli P. , Jones Mathew V. , Roopra Avtar , Skala Melissa C. , Moore Darcie L.
Published: December 2022

Neural stem cells (NSCs) in the adult brain are primarily quiescent but can activate and enter the cell cycle to produce newborn neurons. NSC quiescence can be regulated by disease, injury, and age, however our understanding of NSC quiescence is limited by technical limitations imposed by the bias of markers used to isolate each population of NSCs and the lack of live-cell labeling strategies. Fluorescence lifetime imaging (FLIM) of autofluorescent metabolic cofactors has previously been used in other cell types to study shifts in cell states driven by metabolic remodeling that change the optical properties of these endogenous fluorophores. Here we asked whether autofluorescence could be used to discriminate NSC activation state. We found that quiescent NSCs (qNSCs) and activated NSCs (aNSCs) each have unique autofluorescence intensity and fluorescence lifetime profiles. Additionally, qNSCs specifically display an enrichment of a specific autofluorescent signal localizing to lysosomes that is highly predictive of cell state. These signals can be used as a graded marker of NSC quiescence to predict cell behavior and track the dynamics of quiescence exit at single cell resolutionin vitroandin vivo. Through coupling autofluorescence imaging with single-cell RNA sequencingin vitroandin vivo, we provide a high-resolution resource revealing transcriptional features linked to rapid NSC activation and deep quiescence. Taken together, we describe a single-cell resolution, non-destructive, live-cell, label-free strategy for measuring NSC activation statein vitroandin vivoand use this tool to expand our understanding of adult neurogenesis.
Deep learning-based image-analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra
Authors: Burkert Nicole , Roy Shoumik , Häusler Max , Wuttke Dominik , Müller Sonja , Wiemer Johanna , Hollmann Helene , Oldrati Marvin , Ramirez-Franco Jorge , Benkert Julia , Fauler Michael , Duda Johanna , Goaillard Jean-Marc , Pötschke Christina , Münchmeyer Moritz , Parlato Rosanna , Liss Birgit
Published: December 2022

Here we present a deep learning-based image analysis platform (DLAP), tailored to autonomously quantify cell numbers, and fluorescence signals within cellular compartments, derived from RNAscope or immunohistochemistry. We utilized DLAP to analyse subtypes of tyrosine hydroxylase (TH)-positive dopaminergic midbrain neurons in mouse and human brain sections. These neurons modulate complex behaviour, and are differentially affected in Parkinson’s and other diseases. DLAP allows the analysis of large cell numbers, and facilitates the identification of small cellular subpopulations. Specifically, we identified a small subpopulation of TH-positive neurons (∼5%), mainly located in the very lateral Substantia nigra (SN), that was immunofluorescence-negative for the plasmalemma dopamine transporter (DAT), with ∼40% smaller cell bodies. These neurons were negative for aldehyde dehydrogenase 1A1, with a lower co-expression rate for dopamine-D2-autoreceptors, but a ∼7-fold higher likelihood of calbindin-d28k co-expression (∼70%). Our results have important implications, as DAT is crucial for dopamine-signalling, and is commonly used as a marker for dopaminergic SN neurons.
Amphetamine disrupts dopamine axon growth in adolescence by a sex-specific mechanism
Authors: Reynolds Lauren M. , Hernandez Giovanni , Popescu Christina , MacGowan Del , Nouel Dominique , Cuesta Santiago , Burke Samuel , Savell Katherine E. , Zhao Janet , Restrepo-Lozano Jose Maria , Pokinko Matthew , Giroux Michel , Israel Sonia , Orsini Taylor , He Susan , Wodzinski Michael , Epelbaum Julia G. , Trudeau Louis-Éric , Kolb Bryan , Day Jeremy J. , Flores Cecilia
Published: December 2022

Initiating drug use during adolescence increases the risk of developing addiction and psychiatric disorders later in life, with long-term outcomes varying according to sex and exact timing of use. Even though most individuals begin experimenting with drugs of abuse in adolescence, to date, the cellular and molecular underpinnings explaining differential sensitivity to detrimental drug effects remain unknown. The Netrin-1/DCC guidance cue system plays a critical role in the adolescent development of mesocorticolimbic dopamine circuitry, segregating the cortical and limbic pathways. Adolescent experiences, including exposure to drugs of abuse, can regulateDccexpression in male mice, placing Netrin-1/DCC signaling as a potential molecular link between experience and enduring changes to circuitry and behavior. Here we show that exposure to a recreational-like regimen of amphetamine (AMPH) in adolescence induces sex- and age-specific alterations inDccexpression in the ventral tegmental area. Female mice are protected against the deleterious long-term effects of AMPH-inducedDccregulation by compensatory changes in the expression of its binding partner, Netrin-1. AMPH induces targeting errors in mesolimbic dopamine axons and triggers their ectopic growth to the prefrontal cortex, only in early-adolescent male mice, underlying a male-specific vulnerability to its enduring cognitive effects. Upregulating DCC receptor expression in dopamine neurons in adolescent males using a neuron-optimized CRISPR/dCas9 Activation System induces female-like protection against the persistent effects of AMPH in early adolescence on inhibitory control. Netrin-1/DCC signaling is therefore a molecular switch which can be differentially regulated in response to the same experience as function of age and sex of the individual, leading to divergent long-term outcomes associated with vulnerable or resilient phenotypes.
Crowdsourcing Temporal Transcriptomic Coronavirus Host Infection Data: resources, guide, and novel insights
Authors: Flynn James , Ahmadi Mehdi M. , McFarland Chase T. , Kubal Michael D. , Taylor Mark A. , Cheng Zhang , Torchia Enrique C. , Edwards Michael G.
Published: December 2022

The emergence of SARS-CoV-2 reawakened the need to rapidly understand the molecular etiologies, pandemic potential, and prospective treatments of infectious agents. The lack of existing data on SARS-CoV-2 hampered early attempts to treat severe forms of COVID-19 during the pandemic. This study coupled existing transcriptomic data from SARS-CoV-1 lung infection animal studies with crowdsourcing statistical approaches to derive temporal meta-signatures of host responses during early viral accumulation and subsequent clearance stages. Unsupervised and supervised machine learning approaches identified top dysregulated genes and potential biomarkers (e.g., CXCL10, BEX2, and ADM). Temporal meta-signatures revealed distinct gene expression programs with biological implications to a series of host responses underlying sustained Cxcl10 expression and Stat signaling. Cell cycle switched from G1/G0 phase genes, early in infection, to a G2/M gene signature during late infection that correlated with the enrichment of DNA Damage Response and Repair genes. The SARS-CoV-1 meta-signatures were shown to closely emulate human SARS-CoV-2 host responses from emerging RNAseq, single cell and proteomics data with early monocyte-macrophage activation followed by lymphocyte proliferation. The circulatory hormone adrenomedullin was observed as maximally elevated in elderly patients that died from COVID-19. Stage-specific correlations to compounds with potential to treat COVID-19 and future coronavirus infections were in part validated by a subset of twenty-four that are in clinical trials to treat COVID-19. This study represents a roadmap to leverage existing data in the public domain to derive novel molecular and biological insights and potential treatments to emerging human pathogens. The data from this study is available in an interactive portal (http://18.222.95.219:8047).
Scale space calibrates present and subsequent spatial learning in Barnes maze in mice
Authors: Tachiki Yuto , Suzuki Yusuke , Kurahashi Mutsumi , Oki Keisuke , Mavuk Özgün , Nakagawa Takuma , Ishihara Shogo , Gyoten Yuichiro , Yamamoto Akira , Imayoshi Itaru
Published: December 2022

Animals including humans are capable of representing different scale spaces from smaller to larger ones. However, most laboratory animals live their life in a narrow range of scale spaces like home-cages and experimental setups, making it hard to extrapolate the spatial representation and learning process in large scale spaces from those in conventional scale spaces. Here, we developed a 3-meter diameter Barnes maze (BM3), then explored whether spatial learning in Barnes maze (BM) is calibrated by scale spaces. In the BM3, mice exhibited lower learning rate compared to a conventional 1-meter diameter Barnes maze (BM1), suggesting that the BM3 requires more trial-and-error and larger computational resources to solve the task than the BM1. Analyzing network structures of moving trajectories, betweenness centrality would contrast spatial learning in a larger scale space with that in a smaller one, as it diverges between the BM1 and the BM3 along with the learning progression. We then explored whether prior learning in either BM scale calibrates subsequent spatial learning in the other BM scale, and found asymmetric facilitation such that the prior learning in the BM3 facilitated the subsequent learning in the BM1, but notvice versa. Network structures of trajectories in the subsequent BM scale were changed by both prior and subsequent BM scale. These results suggest that scale space calibrates both the present and subsequent BM learning. This is the first study to explore and demonstrate scale-dependent spatial learning in Barnes maze in mice.

Significance Statement

Animals are capable of representing different scale spaces. However, whether scale space calibrates goal-directed spatial learning remains unclear. The Barnes maze is a well-established experimental paradigm to evaluate spatial learning in rodents. Here, we developed a larger scale 3-meter diameter Barnes maze (BM3) then compared various navigation features in mice between the BM3 and a conventional 1-meter diameter Barnes maze (BM1). We demonstrated that learning on the BM3 required more computational resources than in the BM1, prompting mice to exploit unique navigation patterns. Such learning experiences in the BM3 facilitated subsequent spatial learning in the BM1, but notvice versa. These results suggest that scale space calibrates immediate and subsequent spatial learning.
Survival of people with untreated tuberculosis: effects of time, geography and setting
Authors: Rodriguez Carly A , Leavitt Sarah V , Bouton Tara C. , Horsburgh C Robert , zur Wiesch Pia Abel , Nichols Brooke , Jenkins Helen E , White Laura F
Published: December 2022

Background

An estimated 40% of people who developed tuberculosis in 2021 were not diagnosed or treated. Pre-chemotherapy era data are a rich resource on survival for people with untreated TB. We aimed to identify heterogeneities in these data to inform more precise use of them.

Methods

We extracted survival data from pre-chemotherapy era papers reporting TB specific mortality and/or natural recovery data. We used Bayesian parametric survival analysis to model the survival distribution, stratifying by geography (North America versus Europe), time (pre-1930 versus post-1930), and setting (sanitoria versus non-sanitoria).

Results

We found 12 studies with TB-specific mortality data. Ten-year survival was 69% in North America (95 CI: 54%-81%) and 36% in Europe (95% CI: 10%-71%). Only 38% (95% CI: 18%-63%) of non-sanitorium individuals survived to 10 years compared to 69% (95% CI: 41%-87%) of sanitoria/hospitalized patients. There were no significant differences between people diagnosed pre-1930 and post-1930 (five-year survival pre-1930: 65%; 95% CI: 44%-88% versus post-1930: 72%; 95% CI: 41%-94%).

Conclusions

Mortality and natural recovery risks vary substantially by location and setting. These heterogeneities need to be considered when using pre-chemotherapy data to make inferences about expected survival of people with undiagnosed TB.
Associations of inflammation-related proteome with demographic and clinical characteristics of people with HIV in South Africa
Authors: Chen Junyu , Hui Qin , Liu Chang , Brijkumar Jaysingh , Edwards Johnathan A. , Ordóñez Claudia E. , Dudgeon Mathew R. , Sunpath Henry , Pillay Selvan , Moodley Pravi , Kuritzkes Daniel R. , Moosa Mohamed Y. S. , Nemoto Tooru , Marconi Vincent C. , Sun Yan V.
Published: December 2022

Elevated levels of inflammation associated with HIV infection are considered one of the primary causes for the excess burden of age-related morbidity and mortality among people with HIV (PWH). Circulating protein levels can be used to investigate biological pathways contributing to persistent inflammation among PWH. In this study, we profiled 73 inflammation-related protein markers and assessed their associations with chronological age, sex and CD4+ cell count among 87 black South African PWH prior to initiating ART. We identified 1, 1 and 14 inflammatory proteins significantly associated with sex, CD4+ T-cell count, and age respectively among PWH. Twelve out of 14 age-associated proteins have been reported to be associated with age in the general population, and 4 have previously shown significant associations with age for PWH. Furthermore, many of the age-associated proteins such as CST5, CCL23, SLAMF1, MMP-1, MCP-1, and CDCP1 have been linked to chronic diseases such as cardiovascular disease and neurocognitive decline in the general population. We also found a synergistic interaction between male sex and older age accounting for excessive expression of CST5. In conclusion, we found that age may lead to the elevation of multiple inflammatory proteins among PWH. We also demonstrated the potential utility of proteomics for evaluating and characterizing the inflammatory status among PWH.
Polygenic score for sleep duration in relation to risk of Alzheimer’s disease: results from the UK Biobank
Authors: Wong Angel TY , Floud Sarah , Reeves Gillian K , Holmes Michael V , Travis Ruth , van Duijn Cornelia M , Doherty Aiden , Smith-Byrne Karl
Published: December 2022

INTRODUCTION

Studies have suggested sleep duration may be associated with Alzheimer’s disease risk, but findings based on self-reported sleep duration are likely to be influenced by reverse causation and residual confounding bias.

METHODS

A polygenic score (PGS) for device-measured sleep duration was constructed using LDpred2-auto in 77,770 white British UK Biobank participants. We applied the PGS to 264,746 white British participants independent of the sample from which the PGS was developed. We assessed the association of fifths of genetically predicted sleep duration with Alzheimer’s disease risk (1,451 cases/264,746 individuals over median 12.5y of follow-up).

RESULTS

The PGS explained ∼2% of variation in device-measured sleep duration. Compared to individuals in the middle fifth of PGS, those in the highest fifth (indicating ∼15 mins/day longer sleep) had a lower risk of Alzheimer’s disease (HR=0.79[95%CI,0.67-0.94]).

DISCUSSION

Our results indicate that genetic predisposition to relatively long sleep duration is associated with a lower Alzheimer’s disease risk.
Using Computer Vision and Artificial Intelligence to Track the Healing of Severe Burns
Authors: Ethier Olivier , Chan Hannah O. , Abdolahnejad Mahla , Morzycki Alexander , Tchango Arsene Fansi , Joshi Rakesh , Wong Joshua N. , Hong Collin
Published: December 2022

Burn care management includes assessing the severity of burns accurately, especially distinguishing superficial partial thickness (SPT) burns from deep partial thickness (DPT) burns, in the context of providing definitive, downstream treatment. Moreover, the healing of the wound in the sub-acute care setting requires continuous tracking to avoid complications. Artificial intelligence (AI) and computer vision (CV) provide a unique opportunity to build low-cost and accessible tools to classify burn severity and track changes of wound parameters, both in the clinic by physicians and nurses, and asynchronously in the remote setting by the patient themselves. Wound assessments can be achieved by AI-CV using the principles of Image-Guided Therapy (IGT) using high-quality 2D colour images. Wound parameters can include wound 2D spatial dimension and the characterization of wound colour changes which demonstrates physiological changes such as presentation of eschar/necrotic tissue, pustulence, granulation tissue and scabbing. Here we present the development of AI-CV-based Skin Abnormality Tracking Algorithm (SATA) pipeline. Additionally we provide proof-of-concept results on a severe localized burn tracked for a 6-week period in clinic, and an additional 2-week period of home monitoring.
Molecular identification of SARS-CoV-2 variants of concern at urban wastewater treatment plants across South Africa
Authors: Yousif Mukhlid , Rachida Said , Taukobong Setshaba , Ndlovu Nkosenhle , Iwu-Jaja Chinwe , Howard Wayne , Moonsamy Shelina , Mhlambi Nompilo , Gwala Sipho , Levy Joshua I. , Andersen Kristian G. , Scheepers Cathrine , Gottberg Anne von , Wolter Nicole , Ismail Arshad , Suchard Melinda , McCarthy Kerrigan ,   the SACCESS network
Published: December 2022

The use of wastewater for SARS-CoV-2 surveillance is a useful complementary tool to clinical surveillance. The aims of this study were to characterize SARS-CoV-2 from wastewater samples, and to identify variants of concern present in samples collected from wastewater treatment plants in South African urban metros from April 2021 to January 2022. A total of 325 samples were collected from 15 wastewater treatment plants. Nucleic acids were extracted from concentrated samples, and subjected to amplicon-based whole genome sequencing. To identify variants of concerns and lineages, we used the Freyja tool (https://github.com/andersen-lab/Freyja), which assigns each sample with the prevalence of each variant present. We also used signature mutation analysis to identify variants in each wastewater treatment site. A heatmap was generated to identify patterns of emerging mutations in the spike gene using Excel conditional formatting. Using the Freyja tool, the Beta variant was detected and became predominate from April to June 2021 followed by the Delta variant and lastly the Omicron variant. Our heatmap approach was able to identify a pattern during the changes of predominate variant in wastewater with the emergence of mutations and the loss of others. In conclusion, sequencing of SARS-CoV-2 from wastewater largely corresponded with sequencing from clinical specimens. Our heatmap has the potential to detect new variants prior to emergence in clinical samples and this may be particularly useful during times of low disease incidence between waves, when few numbers of positive clinical samples are collected and submitted for testing. A limitation of wastewater sequencing is that it is not possible to identify new variants, as variants are classified based on known mutations in clinical strains.
Endogenous oxytocin levels in children with autism: Associations with cortisol levels and oxytocin receptor gene methylation
Authors: Margaux Evenepoel , Matthijs Moerkerke , Nicky Daniels , Viktoria Chubar , Stephan Claes , Jonathan Turner , Bart Vanaudenaerde , Lynn Willems , Johan Verhaeghe , Jellina Prinsen , Jean Steyaert , Bart Boets , Kaat Alaerts
Published: December 2022

Background

Alterations in the brain’s oxytocinergic system have been suggested to play an important role in the pathophysiology of autism spectrum disorder (ASD), but insights from pediatric populations are sparse.

Methods

We examined salivary oxytocin in school-aged children with (n=80) and without (n=40) ASD (boys/girls 4/1), as well as characterizations of DNA methylation (DNAm) of the oxytocin receptor gene (OXTR). Cortisol levels were also assessed to examine links between the oxytocinergic system and hypothalamic-pituitary-adrenal (HPA) axis signaling.

Results

Children with ASD displayed altered (diminished) oxytocin levels in the morning, but not in the afternoon, after a mildly stress-inducing social interaction session. Notably, in the control group, higher oxytocin levels were predictive of lower stress-induced cortisol, likely reflective of aprotectivestress-regulatory mechanism for buffering HPA stress activity. In children with ASD, on the other hand, a morereactivestress regulatory mechanism was evident, involving a significant rise in oxytocin levels from the morning to the afternoon upon stress-induced cortisol release, i.e., to reactively cope with heightened HPA activity.

Regarding epigenetic modifications, no overall pattern ofOXTRhypo- or hypermethylation was evident in ASD. In control children, a notable association betweenOXTRmethylation and levels of cortisol was evident, likely indicative of a compensatory downregulation ofOXTRmethylation (higher oxytocin receptor expression) in children with heightened HPA axis activity.

Conclusion

Together, these observations bear important insights into altered oxytocinergic signaling in ASD, which may aid in establishing relevant biomarkers for diagnostic and/or treatment evaluation purposes targeting the oxytocinergic system in ASD.
Health Outcome Predictive Modelling in Intensive Care Units
Authors: Xian Chengqian , de Souza Camila P. E. , Rodrigues Felipe F.
Published: December 2022

The literature in Intensive Care Units (ICUs) data analysis focuses on predictions of length-of-stay (LOS) and mortality based on patient acuity scores such as Acute Physiology and Chronic Health Evaluation (APACHE), Sequential Organ Failure Assessment (SOFA), to name a few. Unlike ICUs in other areas around the world, ICUs in Ontario, Canada, collect two primary intensive care scoring scales, a therapeutic acuity score called the “Multiple Organs Dysfunctional Score” (MODS) and a nursing workload score called the “Nine Equivalents Nursing Manpower Use Score” (NEMS). The dataset analyzed in this study contains patients’ NEMS and MODS scores measured upon patient admission into the ICU and other characteristics commonly found in the literature. Data were collected between January 1st, 2015 and May 31st, 2021, at two teaching hospital ICUs in Ontario, Canada. In this work, we developed logistic regression, random forests (RF) and neural networks (NN) models for mortality (discharged or deceased) and LOS (short or long stay) predictions. Considering the effect of mortality outcome on LOS, we also combined mortality and LOS to create a new categorical health outcome called LMClass (short stay & discharged, short stay & deceased, or long stay without specifying mortality outcomes), and then applied multinomial regression, RF and NN for its prediction. Among the models evaluated, logistic regression for mortality prediction results in the highest area under the curve (AUC) of 0.795 and also for LMClass prediction the highest accuracy of 0.630. In contrast, in LOS prediction, RF outperforms the other methods with the highest AUC of 0.689. This study also demonstrates that MODS and NEMS, as well as their components measured upon patient arrival, significantly contribute to health outcome prediction in ICUs.
Synthesizing evidence on the impacts of COVID-19 regulatory changes on methadone treatment for opioid use disorder: Implications for U.S. federal policy
Authors: Krawczyk Noa , Rivera Bianca D. , Levin Emily , Dooling Bridget C.E.
Published: December 2022

As the U.S. faces a worsening overdose crisis, improving access to evidence-based treatment for opioid use disorder (OUD) remains a central policy priority. Federal regulatory changes in response to the COVID-19 pandemic significantly expanded flexibilities on take-home doses for methadone treatment for OUD. These changes have fueled critical questions about the impact of new regulations on OUD outcomes, and the potential health impact of permanently integrating these flexibilities into treatment policy going forward. To aide US policy makers as they consider implementing permanent methadone regulatory changes, we conducted a review synthesizing peer-reviewed research evidence on the impact of the COVID-19 methadone-take-home flexibilities on methadone program operations, OUD patient and provider experiences, and patient health outcomes. We interpret this evidence in the context of the federal rulemaking process and discuss avenues by which these important findings can be incorporated and implemented into U.S. substance use treatment policy going forward.