bluuebunny/crossref_metadata_2025 huggingface dataset:
Utility of Metabolomic Biomarkers to Identify Nonalcoholic Fatty Liver Disease in Liver Transplant Recipients
Authors: Mowry Christopher J. , Alonso Cristina , Iruarrizaga-Lejarreta Marta , Ortiz Pablo , Levitsky Josh , Rinella Mary
Published: November 2021

Background.

Nonalcoholic fatty liver disease (NAFLD) is a rising indication for liver transplantation (LT). Identification of NAFLD recurrence and those at risk for more progressive disease after LT remains elusive as the diagnosis requires biopsy, which is invasive and impractical for serial monitoring. We therefore aimed to identify metabolites in the blood associated with recurrent NAFLD that could potentially be used for detection and monitoring.

Methods.

This cross-sectional pilot study included 37 LT recipients who underwent simultaneous liver biopsy and plasma collection for metabolomic analysis. Metabolic profiles were compared between patients with recurrent NAFLD, normal liver (negative control), and acute rejection (rejection control).

Results.

Univariate analysis revealed 14 metabolites that were significantly altered in patients with recurrence of NAFLD compared with negative controls and 19 compared with rejection controls (P < 0.05). In addition, metabolomic profiling identified 16 metabolites that distinguished nonalcoholic fatty liver versus nonalcoholic steatohepatitis. Metabolite class trends among patients with recurrent NAFLD following LT were consistent with prior metabolomics data in patients with NAFLD in the non-LT setting.

Conclusions.

In conclusion, we identified candidate metabolites that could be used in the clinical setting to noninvasively identify recurrent NAFLD and differentiate NAFL from the more progressive nonalcoholic steatohepatitis. Further investigation with a larger sample size is warranted to validate these results.
Leviviricetes: expanding and restructuring the taxonomy of bacteria-infecting single-stranded RNA viruses
Authors: Callanan Julie , Stockdale Stephen R. , Adriaenssens Evelien M. , Kuhn Jens H. , Rumnieks Janis , Pallen Mark J. , Shkoporov Andrey N. , Draper Lorraine A. , Ross R. Paul , Hill Colin
Published: November 2021

The vast majority of described prokaryotic viruses have double-stranded or single-stranded DNA or double-stranded RNA genomes. Until 2020, a mere four prokaryotic single-stranded, positive-sense RNA viruses have been classified in two genera (Riboviria; Lenarviricota; Allassoviricetes; Leviviridae). Several recent metagenomic and metatranscriptomic studies revealed a vastly greater diversity of these viruses in prokaryotic soil communities than ever anticipated. Phylogenetic analysis of these newly discovered viruses prompted the reorganization of class Allassoviricetes, now renamed Leviviricetes, to include two orders, Norzivirales and Timlovirales, and a total of six families, 428 genera and 882 species. Here we outline the new taxonomy of Leviviricetes, approved and ratified in 2021 by the International Committee on Taxonomy of Viruses, and describe open-access hidden Markov models to accommodate the anticipated identification and future classification of hundreds, if not thousands, of additional class members into this new taxonomic framework.
A Genetic Model for Central Chondrosarcoma Evolution Correlates with Patient Outcome
Authors: Cross William , Lyskjær Iben , Lesluyes Tom , Hargreaves Steven , Strobl Anna-Christina , Davies Christopher , Waise Sara , Hames Shadi , Oukrif Dahmane , Ye Hongtao , Amary Fernanda , Tirabosco Roberto , Baker Toby , Barnes David , Steele Christopher , Alexandrov Ludmil , Bond Gareth ,   Genomics England Research Consortium, Cool Paul , Pillay Nischalan , Van Loo Peter , Flanagan Adrienne M
Published: November 2021

The treatment options for central chondrosarcoma are limited, and prognoses are generally unreliable. The presence and absence of mutations in IDH1, and IDH2 are defining events, and TERT mutations have been recently been associated with poor outcome. Despite this, molecular biomarkers are lacking. Here, analysing data from 356 patients, comprising results from whole genome sequencing (n=68), digital droplet PCR (n=346), and methylation arrays (n=57), we present a comprehensive genetic analysis of chondrosarcoma and suggest its clinical utility. Methylation profiles, TERT promoter mutations, genome doubling with prior haploidisation, and age at diagnosis of high grade, distinguish IDH1-mutant, IDH2-mutant and IDH wildtype tumours. The majority of IDH2-mutant tumours harbour TERT mutations, though a significant reduction in survival is only found in the less common mutational combination of IDH1 and TERT. We suggest that diagnostic testing for IDH1, IDH2 and TERT mutations could guide clinical monitoring and prognostication.
The Ecology of Palm Genomes: Repeat-associated genome size expansion is constrained by aridity
Authors: Schley Rowan J. , Pellicer Jaume , Ge Xue-Jun , Barrett Craig , Bellot Sidonie , S. Guignard Maïté , Novák Petr , Suda Jan , Fraser Donald , Baker William J. , Dodsworth Steven , Macas Jiří , Leitch Andrew R. , Leitch Ilia J.
Published: November 2021

Genome size varies 2,400-fold across plants, influencing their evolution through changes in cell size and cell division rates which impact plants’ environmental stress tolerance. Repetitive element expansion explains much genome size diversity, and the processes structuring repeat ‘communities’ are analogous to those structuring ecological communities. However, which environmental stressors influence repeat community dynamics has not yet been examined from an ecological perspective.

We measured genome size and leveraged climatic data for 91% of genera within the ecologically diverse palm family (Arecaceae). We then generated genomic repeat profiles for 141 palm species, and analysed repeats using phylogenetically-informed linear models to explore relationships between repeat dynamics and environmental factors.

We show that palm genome size and repeat ‘community’ composition are best explained by aridity. Specifically,EnSpm CACTArepeats were more abundant in palm species from wetter environments, which generally had larger genomes (>2.15Gbp/1C), suggesting amplification. In contrast,Ty1-copia Angelaelements were more abundant in drier environments.

Our results suggest water stress inhibits the expansion of repeats through selection on upper genome size limits. However,Ty1-copia Angelaelements, which may associate with stress-response genes, have amplified in arid-adapted palm species. Overall, we provide novel evidence of climate influencing the assembly of repeat ‘communities’.
Epidemiological Analysis of Lower Limb Revascularization for Peripheral Arterial Disease over 12 years in the Public Health System in Brazil
Authors: Wolosker Nelson , da Silva Marcelo Fiorelli Alexandrino , Cassino Portugal Maria Fernanda , Stabellini Nickolas , Zerati Antônio Eduardo , Szlejf Claudia , Amaro Edson , Teivelis Marcelo Passos
Published: November 2021

Objectives

Worldwide, peripheral arterial disease (PAD) is a disorder with high morbidity, affecting more than 200 million people. Our objective was to analyse the surgical treatment for PAD performed in the Unified Health System of Brazil over 12 years based on publicly available data.

Methods

The study was conducted with data analysis available on the DATASUS platform of the Brazilian Health Ministry, assessing procedure technique distribution throughout the years, mortality and cost.

Results

A total of 129,424 procedures were analysed (either for claudicants or critical ischemia, proportion unknown). The vast majority of procedures were Endovascular (65.49%), with a tendency for increase in this disproportion (p<0.001). There were 3,306 in-hospital deaths (mortality of 2.55%), with lower mortality in the Endovascular group (1.2% vs. 5.0%, p=0.008). The overall governmental investment for these procedures was U$ 238,010,096.51, and Endovascular Procedures were on average significantly more expensive than Open Surgery (U$ 1,932.27 v. U$ 1,517.32; p=0.016).

Conclusions

In the Brazilian Public Health System, lower limb revascularizations occurred with gradual growing frequency between 2008 and 2019. Endovascular procedures were vastly more common, and related to lower in-hospital mortality rates, but higher procedural costs.
CPTAC Pancancer Phosphoproteomics Kinase Enrichment Analysis with ProKAP Provides Insights into Immunogenic Signaling Pathways
Authors: Calinawan Anna , Ma Weiping , Evangelista John Erol , Reva Boris , Petralia Francesca , Ma’ayan Avi , Wang Pei
Published: November 2021

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) initiative has generated extensive phosphoproteomics and proteomics data for tumor and tumor-adjacent normal tissue across multiple cancer types. This dataset provides an unprecedented opportunity to systematically characterize pan-cancer kinase activities, which is essential for coupling tumor subtypes with kinase inhibitors as potential treatment. In this work, we performed Kinase Enrichment Analysis (KEA) using a CPTAC phosphoproteomics dataset to identify putative differences in kinase state between tumor and normal tissues within and across five types of cancer. We then implemented an interactive web-portal, the ProTrack Kinase Activity Portal (ProKAP), for querying, visualizing, and downloading the derived pan-cancer kinase activity scores together with the corresponding sample metadata, and protein and phosphoprotein expression profiles. To illustrate the usage of this digital resource, we analyzed the association between kinase activity scores and immune subtypes of clear cell renal cell carcinoma (ccRCC) derived from the CPTAC ccRCC study. We found multiple kinases, whose inhibition has been suggested to have therapeutic effect in other tumor types, are highly active in CD8+-enriched ccRCC tumors. The ProTrack Kinase Activity Portal (ProKAP) is available at: https://pancan-kea3.cptac-data-view.org.
Development of novel PCR primer sets for DNA metabarcoding of aquatic insects, and the discovery of some cryptic species
Authors: Takenaka Masaki , Yano Koki , Suzuki Tomoya , Tojo Koji
Published: November 2021

DNA barcoding is a powerful tool that provides rapid, accurate, and automatable species identification by using standardized genetic region(s). It can be a powerful tool in various fields of biology such as for revealing the existence of cryptic species and/or rare species and in environmental science such as when monitoring river biota. Biodiversity reduction in recent times has become one of the most serious environmental issues on a worldwide scale. DNA barcoding techniques require the development of sets of universal PCR primers for DNA metabarcoding. We tried to develop universal primer sets for the DNA barcoding of all insect groups. In this study, we succeeded in designing not only universal primer sets for DNA barcoding regions of almost all insects, which were designed to include a hypervariable site between highly conserved sites, but also primer sets for longer fragment sequences for registration in a database. We confirmed successful amplification for 14 orders, 43 families, and 68 species with DNA barcoding in the mtDNA 16S rRNA region, and for 13 orders, 42 families, and 66 species with DNA barcoding in the mtDNA 12S rRNA region. A key feature is that the DNA fragments of the DNA barcoding regions amplified by these primer sets are both short at about 200-bp, and longer fragment sequences will increase the level of data registration in the DNA database. Such resulting database enhancements will serve as a powerful tool for increasingly accurate assessment of biodiversity and genetic diversity.
Fast and optimal sequence-to-graph alignment guided by seeds
Authors: Ivanov Pesho , Bichsel Benjamin , Vechev Martin
Published: November 2021

We present a novel A⋆seed heuristic that enables fast and optimal sequence-to-graph alignment, guaranteed to minimize the edit distance of the alignment assuming non-negative edit costs.

We phrase optimal alignment as a shortest path problem and solve it by instantiating the A⋆ algorithm with our seed heuristic. The seed heuristic first extracts non-overlapping substrings (seeds) from the read, finds exact seed matches in the reference, marks preceding reference positions by crumbs, and uses the crumbs to direct the A⋆ search. The key idea is to punish paths for the absence of foreseeable seed matches. We prove admissibility of the seed heuristic, thus guaranteeing alignment optimality.

Our implementation extends the free and open source aligner and demonstrates that the seed heuristic outperforms all state-of-the-art optimal aligners including GraphAligner, Vargas, PaSGAL, and the prefix heuristic previously employed by AStarix. Specifically, we achieve a consistent speedup of >60× on both short Illumina reads and long HiFi reads (up to 25kbp), on both the E. coli linear reference genome (1Mbp) and the MHC variant graph (5Mbp). Our speedup is enabled by the seed heuristic consistently skipping >99.99% of the table cells that optimal aligners based on dynamic programming compute.

AStarix aligner and evaluations: https://github.com/eth-sri/astarix Full paper: https://www.biorxiv.org/content/10.1101/2021.11.05.467453
Obesity and adiposity have opposing genetic impacts on human blood traits
Authors: Thom Christopher S , Wilken Madison B , Chou Stella T , Voight Benjamin F
Published: November 2021

Obesity, hyperlipidemia, and truncal adiposity concordantly elevate cardiovascular disease risks, but have unknown genetic effects on blood trait variation. Using Mendelian randomization, we define unexpectedly opposing roles for generalized obesity and truncal adiposity on blood traits. Elevated genetically determined body mass index (BMI) and lipid levels decreased hemoglobin and hematocrit levels, explaining consistent with clinical observations associating obesity and anemia. However, lipid-related effects were confined to erythroid traits, whereas BMI affected multiple blood lineages, indicating broad effects on hematopoiesis. BMI-related effects were unexpectedly opposed by truncal adipose distribution, which increased hemoglobin and blood cell counts across lineages. Conditional analyses indicated genes, pathways, and cell types responsible for these effects, including Leptin Receptor and other blood cell-extrinsic factors in adipocytes and endothelium, which regulate hematopoietic stem and progenitor cell biology. Our findings identify novel roles for obesity and adipose distribution on hematopoiesis and show that genetically determined adiposity plays a previously underappreciated role in determining blood cell formation and function.
Making Common Fund data more findable: Catalyzing a Data Ecosystem
Authors: Charbonneau Amanda L , Brady Arthur , Czajkowski Karl , Aluvathingal Jain , Canchi Saranya , Carter Robert , Chard Kyle , Clarke Daniel J.B. , Creasy Heather H , D’Arcy Mike , Giglio Michelle , Gingrich Alicia , Harris Rayna M , Hodges Theresa K , Ifeonu Olukemi , Jeon Minji , Kropiwnicki Eryk , Lim Marisa C.W. , Liming R. Lee , Mandal Meisha , Munro James B , Nadendla Suvarna , Richter Rudyard , Romano Cia , Rocca-Serra Philippe , Schuler Robert E. , Tangmunarunkit Hongsuda , Waldrop Alex , Williams Cris , Word Karen , Sansone Susanna-Assunta , Ma’ayan Avi , Wagner Rick , Foster Ian , Kesselman Carl , Brown C. Titus , White Owen
Published: November 2021

The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables users to discover datasets from across the U.S. National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. The CFDE’s federation system is centered on a catalog that ingests metadata from individual Common Fund Program’s Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This uniform Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by the individual DCCs and is designed to enable easy expansion to accommodate new data types. We describe its use to ingest and index data from ten DCCs.
SARS-CoV-2 specific T cell and humoral immune responses upon vaccination with BNT162b2: A 9 months longitudinal study
Authors: Takeuchi Junko S. , Fukunaga Ami , Yamamoto Shohei , Tanaka Akihito , Matsuda Kouki , Kimura Moto , Kamikawa Azusa , Kito Yumiko , Maeda Kenji , Ueda Gohzoh , Mizoue Tetsuya , Ujiie Mugen , Mitsuya Hiroaki , Ohmagari Norio , Sugiura Wataru
Published: November 2021

Introduction

The humoral and cellular immune responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) upon coronavirus disease 2019 (COVID-19) vaccination remain to be clarified. Hence, we aimed to investigate the long-term chronological changes in SARS-CoV-2 specific IgG antibody, neutralizing antibody, and T cell responses during and after receiving the BNT162b2 vaccine.

Methods

We performed serological, neutralization, and T cell assays among 100 hospital workers aged 22-73 years who received the vaccine. We conducted seven surveys up to eight months after the second vaccination dose.

Results

SARS-CoV-2 spike protein-specific IgG (IgG-S) titers and T cell responses increased significantly following the first vaccination dose. The highest titers were observed on day 29 and decreased gradually until the end of the follow-up period. There was no correlation between IgG-S and T cell responses. Notably, T cell responses were detected on day 15, earlier than the onset of neutralizing activity.

Conclusions

This study demonstrated that both IgG-S and T cell responses were detected before acquiring sufficient levels of SARS-CoV-2 neutralizing antibodies. These immune responses are sustained for approximately six–ten weeks but not for seven months or later following the second vaccination, indicating the need for the booster dose (i.e., third vaccination).
Crosstalk between β-catenin and WT1 signalling activity in acute myeloid leukemia
Authors: Wagstaff M , Tsaponina O , Caalim G , Greenfield H , Milton-Harris L , Mancini EJ , Blair A , Heesom KJ , Tonks A , Darley RL , Roberts SG , Morgan RG
Published: November 2021

Wnt signalling is an evolutionary conserved signal transduction pathway heavily implicated in normal development and disease. The central mediator of this pathway, β-catenin, is frequently overexpressed, mislocalised and overactive in acute myeloid leukaemia (AML) where it mediates the establishment, maintenance and drug resistance of leukaemia stem cells. Critical to the stability, localisation and activity of β-catenin are the protein-protein interactions it forms, yet these are poorly defined in AML. We recently performed the first β-catenin interactome study in blood cells of any kind and identified a plethora of novel interacting partners. This study shows for the first time that β-catenin interacts with Wilms tumour protein (WT1), a protein frequently overexpressed and mutated in AML, in both myeloid cell lines and also primary AML samples. We demonstrate crosstalk between the signalling activity of these two proteins in myeloid cells, and show that modulation of either protein can affect expression of the other. Finally, we demonstrate that WT1 mutations frequently observed in AML can increase stabilise β-catenin and augment Wnt signalling output. This study has uncovered new context-dependent molecular interactions for β-catenin which could inform future therapeutic strategies to target this dysregulated molecule in AML.

Article summary

β-Catenin is frequently dysregulated in acute myeloid leukemia (AML) and protein interactions govern its stability, localization and activity, but these are poorly defined in AML.

This study shows for the first time that β-catenin and Wilms tumour protein (WT1) interact and influence each other’s expression level and signalling activity in AML cells, which could inform future therapeutic strategies.
Normalization by orientation-tuned surround in human V1-V3
Authors: Fang Zeming , Bloem Ilona , Olsson Catherine , Ma Wei Ji , Winawer Jonathan
Published: November 2021

An influential account of neuronal responses in primary visual cortex is the normalized energy model. This model is often implemented as a two-stage computation. The first stage is the extraction of contrast energy, whereby a complex cell computes the squared and summed outputs of a pair of linear filters in quadrature phase. The second stage is normalization, in which a local population of complex cells mutually inhibit one another. Because the population includes cells tuned to a range of orientations and spatial frequencies, the result is that the responses are effectively normalized by the local stimulus contrast. Here, using evidence from human functional MRI, we show that the classical model fails to account for the relative responses to two classes of stimuli: straight, parallel, band-passed contours (gratings), and curved, band-passed contours (snakes). The snakes elicit fMRI responses that are about twice as large as the gratings, yet a traditional divisive normalization model predicts responses that are about the same. Here, motivated by these observations and others from the literature, we implement a divisive normalization model, in which there is a preferential inhibition between cells matched in orientation tuning (“tuned normalization”). We first show that this model accounts for differential responses to these two classes of stimuli. We then show that the model successfully generalizes to other band-pass textures, both in V1 and in extrastriate cortex (V2 and V3). We conclude that even in primary visual cortex, complex features of images such as the degree of heterogeneity, can have large effects on neural responses.
Lipopolysaccharide induces placental mitochondrial dysfunction by reducing MNRR1 levels via a TLR4-independent pathway
Authors: Purandare Neeraja , Kunji Yusef , Xi Yue , Romero Roberto , Gomez-Lopez Nardhy , Fribley Andrew , Grossman Lawrence I. , Aras Siddhesh
Published: November 2021

Mitochondria play a key role in the growth and development of the placenta, an organ essential for pregnancy in eutherian mammals. Mitochondrial dysfunction has been associated with pregnancy pathologies. However, the mechanisms whereby placental mitochondria sense inflammatory signals at a cellular and mechanistic level are unknown. Mitochondrial Nuclear Retrograde Regulator 1 (MNRR1) is a bi-organellar protein responsible for optimal mitochondrial function to achieve energy and redox homeostasis. In addition, MNRR1 also is required for optimal induction of cellular stress-responsive signaling pathways such as the mitochondrial unfolded protein response (UPRmt). Here, in a lipopolysaccharide-induced model of placental inflammation, we show that MNRR1 levels are reduced in placental tissues and cell lines. Reduction in MNRR1 is associated with mitochondrial dysfunction and enhanced oxidative stress along with activation of pro-inflammatory signaling. Mechanistically, we uncover a non-conventional pathway independent of Toll-like receptor 4 (TLR4) that results in a specific ATM kinase-dependent threonine phosphorylation and activation of a mitochondrial protease, YME1L1, degrading MNRR1. Furthermore, enhancing MNRR1 levels in placental cells either genetically or with specific activators abrogates the bioenergetic defect and induces an anti-inflammatory phenotype, suggesting that MNRR1 is upstream of the mitochondrial dysfunction observed in our model. Reduction in MNRR1 levels is a generalized phenomenon observed in cells under an inflammatory stimulus. We therefore propose MNRR1 as a novel anti-inflammatory therapeutic target in pathologies associated with placental inflammation.
Gestational Cd Exposure in the CD-1 Mouse Sex-Specifically Disrupts Essential Metal Ion Homeostasis
Authors: Jackson Thomas W. , Baars Oliver , Belcher Scott M.
Published: November 2021

In CD-1 mice, gestational-only exposure to cadmium (Cd) causes female-specific hepatic insulin resistance, metabolic disruption, and obesity. To evaluate whether sex differences in cadmium uptake and changes in essential metal concentrations contribute to metabolic outcomes, placental and liver cadmium and essential metal concentrations were quantified in male and female offspring perinatally exposed to 500 ppb CdCl2. Exposure resulted in increased maternal liver Cd+2 concentrations (364 μg/kg) similar to concentrations found in non-occupationally exposed human liver. At gestational day (GD) 18, placental cadmium and manganese concentrations were significantly increased in exposed males and females, and zinc was significantly decreased in females. Placental efficiency was significantly decreased in GD18 exposed males. Increases in hepatic Cd concentrations and a transient prenatal increase in zinc were observed in exposed female liver. Fetal and adult liver iron concentrations were decreased in both sexes, and decreases in hepatic zinc, iron, and manganese were observed in exposed females. Analysis of GD18 placental and liver metallothionein mRNA expression revealed significant Cd-induced upregulation of placental metallothionein in both sexes, and a significant decrease in fetal hepatic metallothionein in exposed females. In placenta, expression of metal ion transporters responsible for metal ion uptake was increased in exposed females. In liver of exposed adult female offspring, expression of the divalent cation importer (Slc39a14/Zip14) decreased, whereas expression of the primary exporter (Slc30a10) increased. These findings demonstrate that Cd can preferentially cross the female placenta, accumulate in the liver, and cause lifelong dysregulation of metal ion concentrations associated with metabolic disruption.
Identification of Low Population States in Cryo-EM Using Deep Learning
Authors: Fraser Alec , Prokhorov Nikolai S. , Miller John-Mark , Knyazhanskaya Ekaterina S. , Leiman Petr G.
Published: November 2021

Cryo-EM has made extraordinary headway towards becoming a semi-automated, high-throughput structure determination technique. In the general workflow, high-to-medium population states are grouped into two- and three-dimensional classes, from which structures can be obtained with near-atomic resolution and subsequently analyzed to interpret function. However, low population states, which are also functionally important, are often discarded. Here, we describe a technique whereby low population states can be efficiently identified with minimal human effort via a deep convolutional neural network classifier. We use this deep learning classifier to describe a transient, low population state of bacteriophage A511 in the midst of infecting its bacterial host. This method can be used to further automate data collection and identify other functionally important low population states.
Three-dimensional in vitro model of the device-tissue interface reveals innate neuroinflammation can be mitigated by antioxidant ceria nanoparticles
Authors: Atherton Elaina , Hu Yue , Brown Sophie , Papiez Emily , Ling Vivian , Colvin Vicki L. , Borton David A.
Published: November 2021

The recording instability of neural implants due to neuroinflammation at the device-tissue interface (DTI) is a primary roadblock to broad adoption of brain-machine interfaces. While a multiphasic immune response, marked by glial scaring, oxidative stress (OS), and neurodegeneration, is well-characterized, the independent contributions of systemic and local “innate” immune responses are not well-understood. Three-dimensional primary neural cultures provide a unique environment for studying the drivers of neuroinflammation by decoupling the innate and systemic immune systems, while conserving an endogenous extracellular matrix and structural and functional network complexity. We created a three-dimensional in vitro model of the DTI by seeding primary cortical cells around microwires. Live imaging of microtissues over time revealed independent innate neuroinflammation, marked by increased OS, decreased neuronal density, and increased functional connectivity. We demonstrated the use of this model for therapeutic screening by directly applying drugs to neural tissue, bypassing low bioavailability through the in vivo blood brain barrier. As there is growing interest in long-acting antioxidant therapies, we tested efficacy of “perpetual” antioxidant ceria nanoparticles, which reduced OS, increased neuronal density, and protected functional connectivity. Overall, our avascular in vitro model of the DTI exhibited symptoms of OS-mediated innate neuroinflammation which were mitigated by antioxidant intervention.
RUV-III-NB: Normalization of single cell RNA-seq Data
Authors: Salim Agus , Molania Ramyar , Wang Jianan , De Livera Alysha , Thijssen Rachel , Speed Terence P.
Published: November 2021

Despite numerous methodological advances, the normalization of single cell RNA-seq (scRNA-seq) data remains a challenging task and the performance of different methods can vary greatly across datasets. Part of the reason for this is the different kinds of unwanted variation, including library size, batch and cell cycle effects, and the association of these with the biology embodied in the cells. A normalization method that does not explicitly take into account cell biology risks removing some of the signal of interest. Furthermore, most normalization methods remove the effects of unwanted variation for the cellembeddingused for clustering-based analysis but not from gene-level data typically used for differential expression (DE) analysis to identify marker genes. Here we propose RUV-III-NB, a statistical method that can be used to remove unwanted variation from both the cellembeddingand gene-level counts. RUV-III-NB explicitly takes into account its potential association with biology when removing unwanted variation via the use of pseudo-replicates. The method can be used for both UMI or sequence read counts and returns adjusted counts that can be used for downstream analyses such as clustering, DE and pseudotime analyses. Using five publicly available datasets that encompass different technological platforms, kinds of biology and levels of association between biology and unwanted variation, we show that RUV-III-NB manages to remove library size and batch effects, strengthen biological signals, improve differential expression analyses, and lead to results exhibiting greater concordance with independent datasets of the same kind. The performance of RUV-III-NB is consistent across the five datasets and is not sensitive to the number of factors assumed to contribute to the unwanted variation. It also shows promise for removing other kinds of unwanted variation such as platform effects. The method is implemented as a publicly available R package available fromhttps://github.com/limfuxing/ruvIIInb.
Circuit-specific sonogenetic stimulation of the deep brain elicits distinct signaling and behaviors in freely moving mice
Authors: Xian Quanxiang , Qiu Zhihai , Kala Shashwati , Wong Kin Fung , Murugappan Suresh , Wu Yong , Hou Xuandi , Zhu Jiejun , Guo Jinghui , Sun Lei
Published: November 2021

Sonogenetics uses heterologously-expressed proteins to sensitize neurons to ultrasound, enabling selective, non-invasive, and deep brain stimulation. However, its ability to modulate specific circuits or induce behavioral changes remains to be studied and characterized. Here, we demonstrate that sonogenetics enables efficient activation of well-defined neural circuits by transcranial low-intensity, low-frequency ultrasonic stimulation with high spatiotemporal resolution. Targeted neurons in subcortical regions were made to express a mechanosensitive ion channel (MscL-G22S). Ultrasound could trigger activity in MscL-expressing neurons in the dorsal striatum without increased activation in neighboring regions, and increase locomotion in freely-moving mice. Ultrasound stimulation of MscL-expressing neurons in the ventral tegmental area could activate the mesolimbic pathway to trigger dopamine release in the nucleus accumbens and modulate appetitive conditioning. In MscL-expressing cells, neuronal responses to ultrasound pulses were rapid, reversible and repeatable. Altogether, we show that sonogenetics can selectively manipulate targeted cells to activate defined neural pathways and affect behaviors.
Oxytocinergic modulation of stress-associated amygdala-hippocampus pathways in humans is mediated by serotonergic mechanisms
Authors: Lan Chunmei , Liu Congcong , Li Keshuang , Zhao Zhiying , Yang Jiaxin , Ma Yina , Scheele Dirk , Shuxia Yao , Kendrick Keith M. , Becker Benjamin
Published: November 2021

Background

The hypothalamic neuropeptide oxytocin (OXT) may exert anxiolytic and stress-reducing actions via modulatory effects on amygdala circuits. Animal models and initial findings in humans suggest that some of these effects are mediated by interactions with other neurotransmitter systems, in particular the serotonin (5-HT) system. Against this background, the present pharmacological resting state fMRI study aimed at determining whether effects of OXT on stress-associated amygdala intrinsic networks are mediated by 5-HT.

Methods

We employed a randomized placebo-controlled double-blind parallel-group pharmacological fMRI resting state experiment during which n = 112 healthy male participants underwent a transient decrease in 5-HT signaling via acute tryptophan depletion (ATD) or the corresponding placebo-control protocols (ATDc) before the administration of intranasal OXT or placebo intranasal spray, respectively.

Results

OXT and 5-HT modulation exerted interactive effects on the coupling of the left amygdala with the ipsilateral hippocampus and adjacent midbrain. OXT increased intrinsic coupling in this pathway, while this effect of OXT was significantly attenuated during transiently decreased central serotonergic signaling induced via ATD. In the absence of OXT or 5-HT modulation this pathway showed a trend for an association with self-reported stress perception in everyday life. No interactive effects were observed for the right amygdala.

Conclusions

Together, the findings provide first evidence that effects of OXT on stress-associated amygdala-hippocampal-midbrain pathways are critically mediated by the 5-HT system in men.
specificity: an R package for analysis of feature specificity to environmental and higher dimensional variables, applied to microbiome species data
Authors: Darcy John L. , Amend Anthony S. , Swift Sean O. I. , Sommers Pacifica S. , Lozupone Catherine A.
Published: November 2021

Background

Understanding the factors that influence microbes’ environmental distributions is important for deter-mining drivers of microbial community composition. These include environmental variables like temperature and pH, and higher-dimensional variables like geographic distance and host species phylogeny. In microbial ecology, “specificity” is often described in the context of symbiotic or host parasitic interactions, but specificity can be more broadly used to describe the extent to which a species occupies a narrower range of an environmental variable than expected by chance. Using a standardization we describe here, Rao’s (1982, 2010) Quadratic Entropy can be conveniently applied to calculate specificity of a feature, such as a species, to many different environmental variables.

Results

We present our R package specificity for performing the above analyses, and apply it to four real-life microbial data sets to demonstrate its application. We found that many fungi within the leaves of native Hawaiian plants had strong specificity to rainfall and elevation, even though these variables showed minimal importance in a previous analysis of fungal beta-diversity. In Antarctic cryoconite holes, our tool revealed that many bacteria have specificity to co-occurring algal community composition. Similarly, in the human gut microbiome, many bacteria showed specificity to the composition of bile acids. Finally, our analysis of the Earth Microbiome Project data set showed that most bacteria show strong ontological specificity to sample type. Our software performed as expected on synthetic data as well.

Conclusions

specificity is well-suited to analysis of microbiome data, both in synthetic test cases, and across multiple environment types and experimental designs. The analysis and software we present here can reveal patterns in microbial taxa that may not be evident from a community-level perspective. These insights can also be visualized and interactively shared among researchers using specificity’s companion package, specificity.shiny.
Temporal variation in the behaviour of a cooperatively breeding bird, Jungle Babbler (Argya striata) at diel and seasonal scale
Authors: Yambem Soniya Devi , Jain Manjari
Published: November 2021

Time is an important and limited resource that can drive the trade-off between various essential activities in the lives of animals. Group-living animals need to perform different behaviour to meet their individual needs and also participate in group activities. They must, therefore, partition the available time between these activities which may vary considerably with environmental and ecological conditions. We examined time-activity budget of a cooperative passerine, Jungle Babbler (Argya striata) and how their behaviour vary across diel and seasonal scales. A repertoire of 13 behaviour was recorded of which 12 behaviour that occur throughout the year were examined further in detail. This included individual behaviour such as foraging, grooming, rest, shower and group behaviour such as allogrooming, movement, play, sentinel, mobbing and inter-group fight. Our results indicate that most of the time (about 70%) was spent performing individual behaviour and the remaining time (about 30%) was allocated to social behaviour. We also found almost all behaviour varied across diel and seasonal scale with respect to proportion of time spent performing them. This highlights the impact of environmental factors on how animals partition their time to perform various activities. Our study also lays the foundation for future studies examining the role of ecological factors such as habitat type and predation pressure in driving these patterns of behaviour in Jungle Babblers.
Association between long working hours and psychological distress: The effect of sick leave criteria in the workplace during the COVID-19 pandemic
Authors: Hino Ayako , Inoue Akiomi , Mafune Kosuke , Tsuji Mayumi , Tateishi Seiichiro , Ogami Akira , Nagata Tomohisa , Muramatsu Keiji , Fujino Yoshihisa ,   for the CORoNaWork Project
Published: November 2021

Objective

This study investigated the effect of sick leave criteria on the association between long working hours and psychological distress.

Methods

We conducted a cross-sectional survey in December 2020, and 27,032 workers completed the questionnaire. First, after testing the interaction effect of overtime work hours and sick leave criteria on psychological distress, we conducted stratified analyses using sick leave criteria.

Results

A significant interaction effect was found. When we conducted stratified analyses, the odds ratios increased with longer working hours, both with and without sick leave criteria groups; however, the risk was greater in the without sick leave criteria group, compared with the criteria group.

Conclusion

We revealed that working without sick leave criteria could strengthen the association between long working hours and psychological distress during the COVID-19 pandemic.

Clinical significance

Workers working without sick leave criteria had a significantly higher risk of psychological distress due to long working hours than those who worked with the criteria. Our findings contribute to preventing the deterioration of mental health during the COVID-19 pandemic.
Differential richness inference for 16S rRNA marker gene surveys
Authors: Kumar M. Senthil , Slud Eric V. , Hehnly Christine , Zhang Lijun , Broach James , Irizarry Rafael P. , Schiff Steven J. , Paulson Joseph N.
Published: November 2021

Individual and environmental health outcomes are frequently linked to changes in the diversity of associated microbial communities. This makes deriving health indicators based on microbiome diversity measures essential.

While microbiome data generated using high throughput 16S rRNA marker gene surveys are appealing for this purpose, 16S surveys also generate a plethora of spurious microbial taxa. When this artificial inflation in the observed number of taxa (i.e., richness, a diversity measure) is ignored, we find that changes in the abundance of detected taxa confound current methods for inferring differences in richness.

Here we argue that the evidence of our own experiments, theory guided exploratory data analyses and existing literature, support the conclusion that most sub-genus discoveries are spurious artifacts of clustering 16S sequencing reads. We proceed based on this finding to model a 16S survey’s systematic patterns of sub-genus taxa generation as a function of genus abundance to derive a robust control for false taxa accumulation.

Such controls unlock classical regression approaches for highly flexible differential richness inference at various levels of the surveyed microbial assemblage: from sample groups to specific taxa collections. The proposed methodology for differential richness inference is available through an R package, Prokounter.

Package availability: https://github.com/mskb01/prokounter
Distinct cell death pathways induced by granzymes collectively protect against intestinalSalmonellainfection
Authors: Chawla Amanpreet Singh , Vandereyken Maud , Arias Maykel , Santiago Llipsy , Dikovskaya Dina , Nguyen Chi , Skariah Neema , Wenner Nicolas , Golovchenko Natasha B. , Thomson Sarah J. , Ondari Edna , Garzón-Tituaña Marcela , Anderson Christopher J. , Bergkessel Megan , Hinton Jay C. D. , Edelblum Karen L. , Pardo Julian , Swamy Mahima
Published: November 2021

Intestinal intraepithelial T lymphocytes (IEL) constitutively express high amounts of the cytotoxic proteases Granzymes (Gzm) A and B and are therefore thought to protect the intestinal epithelium against infection by killing infected epithelial cells. However, the role of IEL granzymes in a protective immune response has yet to be demonstrated. We show that GzmA and GzmB are required to protect mice against oral, but not intravenous, infection withSalmonella entericaserovar Typhimurium, consistent with an intestine-specific role. IEL-intrinsic granzymes mediate the protective effects by controlling intracellular bacterial growth and aiding in cell-intrinsic pyroptotic cell death of epithelial cells. Surprisingly, we found that both granzymes play non- redundant roles.GzmB-/-mice carried significantly lower burdens ofSalmonella, as predominant GzmA-mediated cell death effectively reduced bacterial translocation across the intestinal barrier. Conversely, inGzmA-/-mice, GzmB-driven apoptosis favored luminalSalmonellagrowth by providing nutrients, while still reducing translocation across the epithelial barrier. Together, the concerted actions of both GzmA and GzmB balance cell death mechanisms at the intestinal epithelium to provide optimal control thatSalmonellacannot subvert.

Abstract Figure
Sonogenetic stimulation of the brain at a spatiotemporal resolution suitable for vision restoration
Authors: Cadoni S. , Demené C. , Provansal M. , Nguyen D. , Nelidova D. , Labernede G. , Alcala I. , Lubetzki J. , Goulet R. , Burban E. , Dégardin J. , Simonutti M. , Gauvain G. , Arcizet F. , Marre O. , Dalkara D. , Roska B. , Sahel J. A. , Tanter M. , Picaud S.
Published: November 2021

Remote, precisely controlled activation of the brain is a fundamental challenge in the development of brain-machine interfaces providing feasible rehabilitation strategies for neurological disorders. Low-frequency ultrasound stimulation can be used to modulate neuronal activity deep in the brain1–7, but this approach lacks spatial resolution and cellular selectivity and loads the brain with high levels of acoustic energy. The combination of the expression of ultrasound-sensitive proteins with ultrasound stimulation (‘sonogenetic stimulation’) can provide cellular selectivity and higher sensitivity, but such strategies have been subject to severe limitations in terms of spatiotemporal resolution in vivo8–10, precluding their use for real-life applications. We used the expression of large-conductance mechanosensitive ion channels (MscL) with high-frequency ultrasonic stimulation for a duration of milliseconds to activate neurons selectively at a relatively high spatiotemporal resolution in the rat retina ex vivo and the primary visual cortex of rodents in vivo. This spatiotemporal resolution was achieved at low energy levels associated with negligible tissue heating and far below those leading to complications in ultrasound neuromodulation6,11. We showed, in an associative learning test, that sonogenetic stimulation of the visual cortex generated light perception. Our findings demonstrate that sonogenetic stimulation is compatible with millisecond pattern presentation for visual restoration at the cortical level. They represent a step towards the precise transfer of information over large distances to the cortical and subcortical regions of the brain via an approach less invasive than that associated with current brain-machine interfaces and with a wide range of applications in neurological disorders.
Emergence and maintenance of variable-length actin filaments in a limiting pool of building blocks
Authors: Banerjee Deb Sankar , Banerjee Shiladitya
Published: November 2021

Actin is one of the key structural components of the eukaryotic cytoskeleton that regulates cellular architecture and mechanical properties. Dynamic regulation of actin filament length and organization is essential for the control of many physiological processes including cell adhesion, motility and division. While previous studies have mostly focused on the mechanisms controlling the mean length of individual actin filaments, it remains poorly understood how distinct actin filament populations in cells maintain different lengths using the same set of molecular building blocks. Here we develop a theoretical model for the length regulation of multiple actin filaments by nucleation and growth rate modulation by actin binding proteins in a limiting pool of monomers. We first show that spontaneous nucleation of actin filaments naturally leads to heterogeneities in filament length distribution. We then investigate the effects of filament growth inhibition by capping proteins and growth promotion by formin proteins on filament length distribution. We find that filament length heterogeneity can be increased by growth inhibition, whereas growth promoters do not significantly affect length heterogeneity. Interestingly, a competition between filament growth inhibitors and growth promoters can give rise to bimodal filament length distribution as well as a highly heterogeneous length distribution with large statistical dispersion. We quantitatively predict how heterogeneity in actin filament length can be modulated by tuning F-actin nucleation and growth rates in order to create distinct filament subpopulations with different lengths.

SIGNIFICANCE

Actin filaments organize into different functional network architectures within eukaryotic cells. To maintain distinct actin network architectures, it is essential to regulate the lengths of actin filaments. While the mechanisms controlling the lengths of individual actin filaments have been extensively studied, the regulation of length heterogeneity in actin filament populations is not well understood. Here we show that the modulation of actin filament growth and nucleation rates by actin binding proteins can regulate actin length distribution and create distinct sub-populations with different lengths. In particular, by tuning concentrations of formin, profilin and capping proteins, various aspects of actin filament length distribution can be controlled. Insights gained from our results may have significant implications for the regulation of actin filament length heterogeneity and architecture within a cell.