bluuebunny/crossref_metadata_2025 huggingface dataset:
Acidovorax pan-genome reveals specific functional traits for plant beneficial and pathogenic plant-associations
Authors: Siani Roberto , Stabl Georg , Gutjahr Caroline , Schloter Michael , Radl Viviane
Published: December 2021

Beta-proteobacteria belonging to the genus

Acidovorax

have been described from various environments. Many strains can interact with a range of hosts, including humans and plants, forming neutral, beneficial or detrimental associations. In the frame of this study, we investigated the genomic properties of 52 bacterial strains of the genus

Acidovorax

, isolated from healthy roots of Lotus japonicus, with the intent of identifying traits important for effective plant-growth promotion. Based on single-strain inoculation bioassays with L. japonicus, performed in a gnotobiotic system, we distinguished seven robust plant-growth promoting strains from strains with no significant effects on plant-growth. We showed that the genomes of the two groups differed prominently in protein families linked to sensing and transport of organic acids, production of phytohormones, as well as resistance and production of compounds with antimicrobial properties. In a second step, we compared the genomes of the tested isolates with those of plant pathogens and free-living strains of the genus

Acidovorax

sourced from public repositories. Our pan-genomics comparison revealed features correlated with commensal and pathogenic lifestyle. We showed that commensals and pathogens differ mostly in their ability to use plant-derived lipids and in the type of secretion-systems being present. Most free-living

Acidovorax

strains did not harbour any secretion-systems. Overall, our data indicate that

Acidovorax

strains undergo extensive adaptations to their particular lifestyle by horizontal uptake of novel genetic information and loss of unnecessary genes.
Characterization of the mitochondrial genomes of three powdery mildew pathogens reveals remarkable variation in size and nucleotide composition
Authors: Zaccaron Alex Z. , Stergiopoulos Ioannis
Published: December 2021

Powdery mildews comprise a large group of economically important phytopathogenic fungi. However, limited information exists on their mitochondrial genomes. Here, we assembled and compared the mitochondrial genomes of the powdery mildew pathogens Blumeria graminis f. sp. tritici, Erysiphe pisi, and Golovinomyces cichoracearum. Included in the comparative analysis was also the mitochondrial genome of Erysiphe necator that was previously analysed. The mitochondrial genomes of the four Erysiphales exhibit a similar gene content and organization but a large variation in size, with sizes ranging from 109800 bp in B. graminis f. sp. tritici to 332165 bp in G. cichoracearum, which is the largest mitochondrial genome of a fungal pathogen reported to date. Further comparative analysis revealed an unusual bimodal GC distribution in the mitochondrial genomes of B. graminis f. sp. tritici and G. cichoracearum that was not previously observed in fungi. The cytochrome b (cob) genes of E. necator, E. pisi, and G. cichoracearum were also exceptionally rich in introns, which in turn harboured rare open reading frames encoding reverse transcriptases that were likely acquired horizontally. Golovinomyces cichoracearum had also the longest cob gene (45 kb) among 703 fungal cob genes analysed. Collectively, these results provide novel insights into the organization of mitochondrial genomes of powdery mildew pathogens and represent valuable resources for population genetics and evolutionary studies.
Using patient biomarker time series to determine mortality risk in hospitalised COVID-19 patients: a comparative analysis across two New York hospitals
Authors: Lambert Ben , Stopard Isaac J. , Momeni-Boroujeni Amir , Mendoza Rachelle , Zuretti Alejandro
Published: December 2021

A large range of prognostic models for determining the risk of COVID-19 patient mortality exist, but these typically restrict the set of biomarkers considered to measurements available at patient admission. Additionally, many of these models are trained and tested on patient cohorts from a single hospital, raising questions about the generalisability of results. We used a Bayesian Markov model to analyse time series data of biomarker measurements taken throughout the duration of a COVID-19 patient’s hospitalisation for n = 1540 patients from two hospitals in New York: State University of New York (SUNY) Downstate Health Sciences University and Maimonides Medical Center. Our main focus was to quantify the mortality risk associated with both static (e.g. demographic and patient history variables) and dynamic factors (e.g. changes in biomarkers) throughout hospitalisation, by so doing, to explain the observed patterns of mortality. By using our model to make predictions across the hospitals, we assessed how predictive factors generalised between the two cohorts. The individual dynamics of the measurements and their associated mortality risk were remarkably consistent across the hospitals. The model accuracy in predicting patient outcome (death or discharge) was 72.3% (predicting SUNY; posterior median accuracy) and 71.3% (predicting Maimonides) respectively. Model sensitivity was higher for detecting patients who would go on to be discharged (78.7%) versus those who died (61.8%). Our results indicate the utility of including dynamic clinical measurements when assessing patient mortality risk but also highlight the difficulty of identifying high risk patients.
Clinical characteristics of Chilean patients with rheumatic diseases and COVID-19: data from the Covid-19 Global Rheumatology Alliance physician-reported registry
Authors: Martínez Oriela , Valenzuela Francisca , Ibáñez Sebastián
Published: December 2021

Objective

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), has registered more than 234 million confirmed cases and more than 4.7 million deaths throughout the world until October 2, 2021. During the last few months, a significant number of reports of COVID-19 in patients with rheumatic diseases have been published. In this study the objective is to report the clinical characteristics of Chilean patients with rheumatic diseases and COVID-19 reported in the “Global Rheumatology Alliance” (GRA) physician registration platform.

Methods

Chilean patients with rheumatic diseases and COVID-19 were included in the Covid-19 GRA physician-reported registry.

Results

54 patients were included. The most common primary rheumatic disease was rheumatoid arthritis (RA) with 28 cases (51.9%). 30 patients (55.6%) used corticosteroids, of which 20 (66.7%) used a dose of 10 mg or less. 33 patients (61.1%) only used conventional DMARDs, 4 (7.4%) only biological, and 6 (11.1%) the combination. A total of 35 patients (64.8%) had to be hospitalized. 2 patients (3.7%) died. 26 patients of the 35 hospitalized (74.2%) required some type of ventilatory support, of which 5 (19.2%) required non-invasive and 8 (30.8%) invasive mechanical ventilation or extracorporeal membrane oxygenation (ECMO).

Discussion

Most of included Chilean rheumatic patients were hospitalized, with a low mortality rate but with a high percentage of patients requiring at least non-invasive mechanical ventilation.

Key Points

-

The most common primary rheumatic disease was rheumatoid arthritis (RA) followed by lupus (LES)

-

Most of the included Chilean rheumatic patients were hospitalized, with a high percentage of patients requiring at least non-invasive mechanical ventilation, but with a low mortality rate.

-

Worsening of arthralgias or activation of the rheumatic disease was not reported.
Computational models reveal how chloride dynamics determine the optimal distribution of inhibitory synapses to minimise dendritic excitability
Authors: Currin Christopher Brian , Raimondo Joseph Valentino
Published: December 2021

Abstract

Many neurons in the mammalian central nervous system have complex dendritic arborisations and active dendritic conductances that enable these cells to perform sophisticated computations. How dendritically targeted inhibition affects local dendritic excitability is not fully understood. Here we use computational models of branched dendrites to investigate where GABAergic synapses should be placed to minimise dendritic excitability over time. To do so, we formulate a metric we term the “Inhibitory Level” (IL), which quantifies the effectiveness of synaptic inhibition for reducing the depolarising effect of nearby excitatory input. GABAergic synaptic inhibition is dependent on the reversal potential for GABAA receptors (EGABA), which is primarily set by the transmembrane chloride ion (Cl-) concentration gradient. We, therefore, investigated how variable EGABA and dynamic chloride affects dendritic inhibition. We found that the inhibitory effectiveness of dendritic GABAergic synapses combines at an encircled branch junction, “inhibitory accumulation”. The extent of inhibitory accumulation is dependent on the number of branches and location of synapses but is independent of EGABA. This inhibitory accumulation occurs even for very distally placed inhibitory synapses when they are hyperpolarising – but not when they are shunting. When accounting for Cl- fluxes and dynamics in Cl- concentration, we observed that Cl- loading is detrimental to inhibitory effectiveness. This enabled us to determine the most inhibitory distribution of GABAergic synapses which is close to – but not at – a shared branch junction. This distribution balances a trade-off between a stronger combined inhibitory influence when synapses closely encircle a branch junction with the deleterious effects of increased Cl- loading that occurs when inhibitory synapses are co-located.
RNA2Immune: A Manually Curated Database of Experimentally Supported Data Linking Noncoding RNA Regulation to the Immune System
Authors: Wang Jianjian , Li Shuang , Wang Tianfeng , Xu Si , Wang Xu , Kong Xiaotong , Lu Xiaoyu , Zhang Huixue , Li Lifang , Feng Meng , Ning Shangwei , Wang Lihua
Published: December 2021

Non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), have emerged as important regulators of the immune system and are involved in the control of immune cell biology, disease pathogenesis as well as vaccine responses. A repository of ncRNA−immune associations will facilitate our understanding of ncRNA-dependent mechanisms in the immune system and advance the development of therapeutics for immune disorders as well as vaccines. Here, we describe a comprehensive database, RNA2Immune, which aims to provide a high-quality resource of experimentally supported database linking ncRNA regulatory mechanisms to immune cell function, immune disease, cancer immunology, and vaccines. The current version of RNA2Immune documents 50,433 immune−ncRNA associations in 42 host species, including: (i) 6690 ncRNA associations with immune functions involving 31 immune cell types; (ii) 38,672 ncRNA associations with 348 immune diseases; (iii) 4833 ncRNA associations with cancer immunology; and (iv) 238 ncRNA associations with vaccine responses involving 26 vaccine types targeting 22 diseases. RNA2Immune provides a user-friendly interface for browsing, searching and downloading ncRNA−immune system associations. Collectively, RNA2Immune provides important information about how ncRNAs influence immune cell function, the pathological consequences of dysregulation of these ncRNAs (immune diseases and cancers), and how ncRNAs affect immune responses to vaccines. RNA2Immune is available at http://bio-bigdata.hrbmu.edu.cn/rna2immune/home.jsp.
Enabling complex fibre geometries using 3D printed axon-mimetic phantoms
Authors: Kuehn Tristan K. , Mushtaha Farah N. , Khan Ali R. , Baron Corey A.
Published: December 2021

Purpose

To introduce a method to create 3D-printed axon-mimetic phantoms with complex fibre orientations to characterize the performance of diffusion MRI models and representations in the presence of orientation dispersion.

Methods

An extension to an open source 3D printing package was created to 3D print a set of five 3D-printed axon-mimetic (3AM) phantoms with various combinations of bending and crossing fibre orientations. A two-shell diffusion MRI scan of the five phantoms in water was performed at 9.4T. Diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), the ball and stick model, neurite orientation density and dispersion imaging (NODDI), and Bingham-NODDI were all fit to the resulting diffusion MRI data. A fiducial in each phantom was used to register a ground truth map of that phantom’s crossing angles and/or arc radius to the diffusion-weighted images. Metrics from each model and representation were compared to the ground-truth maps, and a quadratic regression model was fit to each combination of output metric and ground-truth metric.

Results

The mean diffusivity (MD) metric defined by DTI was insensitive to crossing angle, but increased with fibre curvature. Axial diffusivity (AD) decreased sharply with increasing crossing angle. DKI’s diffusivity metrics replicated the trends seen in DTI, and its mean kurtosis (MK) metric, decreased with fibre curvature, except in regions with high crossing angles. The estimated stick volume fraction in the ball and stick model decreased with increasing fibre curvature and crossing angle. NODDI’s intra-neurite volume fraction was insensitive to crossing angle, and its orientation dispersion index (ODI) was strongly correlated to crossing angle. Bingham-NODDI’s intra-neurite volume fraction was also insensitive to crossing angle, while its primary ODI (ODIP) was also strongly correlated to crossing angle and its secondary ODI (ODIS) was insensitive to crossing angle. For both NODDI models, the volume fractions of the extra-neurite and CSF compartments had low reliability with no clear relationship to crossing angle.

Conclusions

This study demonstrates that inexpensive 3D-printed axon-mimetic phantoms can be used to investigate the effect of fibre curvature and crossings on diffusion MRI representations and models of diffusion signal. As a proof of concept, the dependence of several representations and models on fibre dispersion/crossing were investigated. As expected, Bingham-NODDI was best able to characterize planar fibre dispersion in the phantoms.
Single cell gene expression profiling of nasal ciliated cells reveals distinctive biological processes related to epigenetic mechanisms in patients with severe COVID-19
Authors: Diambra Luis , Alonso Andres M , Sookoian Silvia , Pirola Carlos J
Published: December 2021

Objective

To explore the molecular processes associated with cellular regulatory programs in patients with COVID-19, including gene activation or repression mediated by epigenetic mechanisms. We hypothesized that a comprehensive gene expression profiling of nasopharyngeal epithelial cells might expand understanding of the pathogenic mechanisms of severe COVID-19.

Methods

We used single-cell RNA sequencing (scRNAseq) profiling of ciliated cells (n = 12725) from healthy controls (SARS-CoV-2 negative n =13) and patients with mild/moderate (n =13) and severe (n =14) COVID-19. ScRNAseq data at the patient level were used to perform gene set and pathway enrichment analyses. We prioritized candidate miRNA-target interactions and epigenetic mechanisms.

Results

Pathways linked to mitochondrial function, misfolded proteins, and membrane permeability were upregulated in patients with mild/moderate disease compared to healthy controls. Besides, we noted that compared to mild/moderate disease, cells derived from severe COVID-19 patients had downregulation of sub-networks associated with epigenetic mechanisms, including DNA and histone H3K4 methylation and chromatin remodeling regulation. We found 11-ranked miRNAs that may explain miRNA-dependent regulation of histone methylation, some of which share seed sequences with SARS-CoV-2 miRNAs.

Conclusion

Our results may provide novel insights into the epigenetic mechanisms mediating the clinical course of SARS-CoV-2 infection.
Risk of hospitalization and mortality after breakthrough SARS-CoV-2 infection by vaccine type and previous SARS-CoV-2 infection utilizing medical claims data
Authors: Kshirsagar Meghana , Mukherjee Sumit , Nasir Md , Becker Nicholas , Ferres Juan Lavista , Richardson Barbra A.
Published: December 2021

We compare the risks of hospitalization (n=1121) and mortality (n=138) in a cohort of 17,881 breakthrough SARS-CoV-2 infections for the Pfizer, Moderna and Janssen vaccines for those with and without SARS-CoV-2 infections prior to vaccination. Cox regression analysis results in a lower hazard ratio for breakthroughs receiving the Moderna vaccine, but a significantly higher hazard ratio for breakthroughs receiving the Janssen vaccine, as compared to breakthroughs who got the Pfizer vaccine. Further, the risk of hospitalization (P<0.001) and death (P<0.05) were lower among breakthroughs who had a SARS-CoV-2 infection prior to vaccination, independent of age, sex, comorbidities, and vaccine type.

Note

We do not study the role of natural immunity in SARS-CoV-2 infections, as our cohort does not contain unvaccinated individuals.
Deep learning-driven risk-based subtyping of cognitively impaired individuals
Authors: Romano Michael F. , Zhou Xiao , Balachandra Akshara R. , Jadick Michalina F. , Qiu Shangran , Nijhawan Diya A. , Joshi Prajakta S. , Lee Peter H. , Smith Maximilian J. , Paul Aaron B. , Mian Asim Z. , Small Juan E. , Chin Sang P. , Au Rhoda , Kolachalama Vijaya B.
Published: December 2021

Quantifying heterogeneity in Alzheimer’s disease (AD) risk is critical for individualized care and management. Recent attempts to assess AD heterogeneity have used structural (magnetic resonance imaging (MRI)-based) or functional (Aβ or tau) imaging, which focused on generating quartets of atrophy patterns and protein spreading, respectively. Here we present a computational framework that facilitated the identification of subtypes based on their risk of progression to AD. We used cerebrospinal fluid (CSF) measures of Aβ from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (n=544, discovery cohort) as well as the National Alzheimer’s Coordinating Center (NACC) (n=508, validation cohort), and risk-stratified individuals with mild cognitive impairment (MCI) into quartiles (high-risk (H), intermediate-high risk (IH), intermediate-low risk (IL), and low-risk (L)). Patients were divided into subgroups utilizing patterns of brain atrophy found in each of these risk-stratified quartiles. We found H subjects to have a greater risk of AD progression compared to the other subtypes at 2- and 4-years in both the discovery and validation cohorts (ADNI: H subtype versus all others, p < 0.05 at 2 and 4 years; NACC: H vs. IL and LR at 2 years, p < 0.05, and a trend toward higher risk vs. IH, and p < 0.05 vs. IH, and L risk groups at 48 months with a trend toward lower survival vs. IL). Using MRI-based neural models that fused various deep neural networks with survival analysis, we then predicted MCI to AD conversion. We used these models to identify subtype-specific regions that demonstrate the largest levels of atrophy-related importance, which had minimal overlap (Average pairwise Jaccard Similarity in regions between the top 5 subtypes, 0.25±0.05 (± std)). Neuropathologic changes characteristic of AD were present across all subtypes in comparable proportions (Chi-square test, p>0.05 for differences in ADNC, n=31). Our risk-based approach to subtyping individuals provides an objective means to intervene and tailor care management strategies at early stages of cognitive decline.
Pulmonary Embolism Readmission Trend Over the Years: A National Readmission Database Study
Authors: Murthi Mukunthan , Velagapudi Sujitha , Park Dae Yong , Shaka Hafeez
Published: December 2021

Introduction

Acute pulmonary embolism (PE) is known to be associated with significant short-term and long-term complications. However, with the evolution of PE management, the outcomes of PE-related complications and the need for readmission have not been well studied. The aim of this study is to see the trend in readmissions in PE patients from the years 2010 to 2018.

Methods

We utilized the National Readmission Database from 2010 to 2018 to identify hospitalized patients with a principal diagnosis of acute pulmonary embolism. Identified the total number of readmissions for acute PE from 2010 to 2018. A multivariate cox regression model was used to identify independent predictors of readmission.

Results

The number of patients with 30-day readmissions has gradually increased from 14,508 in 2010 to 19,703 in 2018. The proportion of females admitted was higher than males in all years. The 30-day all-cause readmission after principal admission for PE decreased from 11.2% to 9.7% from 2010 to 2014 but increased to 11.8% in 2018 (p<0.001). Risk-adjusted readmission specific for PE showed a decrease from 1.2 to 1% (p=0.023) from 2010 to 2018. When adjusted to age and gender, an increase in the proportion of readmissions with intracranial bleeding was seen among both the 30-day (0.7% in 2010 to 1.2% in 2018, aOR 1.06, p<0.001) and 90-day (0.7% in 2010 to 1.2% in 2018, aOR 1.06, p-trend 0.003) cohorts. Similarly, an increasing trend of readmissions for UGI bleed was seen among both 30-day (0.9% vs 4.3%, aOR=1.26, p-trend <0.001) and 90-day readmissions (0.7% vs 3.8%, aOR=1.27, p-trend <0.001). The units of blood transfusion required per readmission reduced in both cohorts during the study period.

Conclusion

Our study suggests that there is a statistically significant decrease in PE-specific readmission from 2010 to 2018, but an increase in all-cause readmissions. We also report an increase in non-major bleeding during readmissions, including ICH and UGI bleed. These findings warrant further studies to elucidate the mechanism for decreasing PE-specific readmission but possible causes for the increase in all-cause readmission in the hope of optimizing management and continuing improving outcomes.
Stress-impaired reward pathway promotes distinct feeding behavior patterns
Authors: Fujioka Yusuke , Kawai Kaori , Endo Kuniyuki , Ishibashi Minaka , Iwade Nobuyuki , Tuerde Dilina , Kaibuchi Kozo , Yamashita Takayuki , Yamanaka Akihiro , Katsuno Masahisa , Watanabe Hirohisa , Ishigaki Shinsuke , Sobue Gen
Published: December 2021

Psychosocial stress can impact feeding behavior outcomes. Although many studies have examined alterations to food intake, little is known about how stress affects feeding behavior patterns. To determine the impact of psychological stress on feeding behavior patterns, mice were subjected to various psychosocial stressors (social isolation, intermittent high-fat-diet, or physical restraint) prior to timed observations in a feeding arena that incorporated multiple bait loci. In addition, in vivo microdialysis was used to assess the effects of stressors on the reward system by measuring dopamine levels in the nucleus accumbens (NAcc) shell. Impaired feeding behavior patterns characterized by significant deviations in bait selection (i.e. fixated feeding) and prolonged periods of eating (i.e. protracted feeding) were observed in stressed mice relative to non-stressed controls. In addition to clear behavioral effects, the stressors also negatively impacted dopamine levels at the nucleus accumbens shell. Normalization of dopamine reversed the fixated feeding behavior, whereas specifically inhibiting neuronal activity in the dopaminergic neurons of the ventral tegmental area that project to the nucleus accumbens shell caused similar impairments in feeding. Given that the deviations were not consistently accompanied by changes in the amount of bait consumed, body weight, or metabolic factors, the qualitative effects of psychosocial stressors on feeding behavior likely reflect perturbations to a critical pathway in the mesolimbic dopamine system. These findings provide compelling evidence that aberrations in feeding behavior patterns can be developed as sensitive biomarkers of psychosocial stress and possibly a prodromal state of neuropsychiatric diseases.

Significance Statement

Feeding behavior can be affected by neuropsychiatric disorders including psychosocial stressors, and the evaluation of eating behavior was mainly based on food intake. However, it is speculated that not only food intake but also feeding behavior patterns can be affected in such disorders. The biological processes underlying the feeding behavior patterns have not been clarified yet. We found that aberrant feeding behaviors in mice characterized by fixated feeding were provoked by psychosocial stressors. The qualitative effects of psychosocial stressors on feeding behavior reflect perturbations in the mesolimbic dopamine system. These findings provide compelling evidence that aberrations in feeding behavior patterns can be developed as sensitive biomarkers of psychosocial stress and possibly a prodromal state of neuropsychiatric diseases.
Hypergravity is more challenging than microgravity for the human sensorimotor system
Authors: Chomienne L. , Sainton P. , Sarlegna F. , Bringoux L.
Published: December 2021

While recent findings demonstrated the importance of contextual estimates about gravity for optimal motor control, it remains unclear how gravitational changes are taken into account by the central nervous system to perform complex motor skills. Here, we investigated the effect of microgravity and hypergravity on the neuromuscular control of whole-body reaching movements compared to normogravity. Standing participants (n=9) had to reach toward visual targets during parabolic flights, which allowed us to test the influence of gravity level on sensorimotor planning and control processes. Also, to specifically test the efficiency of online motor control mechanisms, unexpected mechanical perturbations were used. Whole-body kinematics and muscular activity were adjusted in microgravity, allowing arm reaching to be as accurate as in normogravity. In contrast, systematic undershooting was observed in hypergravity, where main parameters of whole-body kinematics remained unchanged and muscle activations insufficiently adjusted to keep the same accuracy as in normogravity. Conversely, muscular synergies exhibited during whole-body reaching were found similar in the various gravitational contexts, as were local muscular adjustments in response to unexpected mechanical perturbations. This suggests that online feedback control remains functional across very distinct gravitational environments. Overall, our findings demonstrates that hypergravity creates challenges that the human sensorimotor system is unable to solve rapidly, contrary to microgravity.
Novel and known transcriptional targets of ALS/FTD protein TDP-43: Meta-analysis and interactive graphical databases
Authors: Cao Maize C. , Scotter Emma L.
Published: December 2021

TDP-43 proteinopathy is the major pathological hallmark of amyotrophic lateral sclerosis (ALS) and tau-negative frontotemporal dementia (FTD). Mounting evidence implicates a loss of normal TDP-43 function in neurodegeneration, either resultant from or independent of TDP-43 aggregation. TDP-43 knockdown is therefore a common paradigm for modelling ALS and FTD. However, because TDP-43 can interact directly with thousands of mRNA targets and regulate the function of other RNA binding proteins, the phenotype of TDP-43 depletion is likely to differ depending on the proteomic and transcriptomic profile of the model cell type. Here, we conducted a meta-analysis of publicly available RNA-sequencing datasets that utilized TDP-43 knockdown to model ALS or FTD, and validated these against RNA-sequencing data from TDP-43-immunonegative neuronal nuclei from ALS/FTD brain. We present these analyses as easy-to-use interactive graphical databases. Of 9 TDP-43-knockdown datasets identified, 4 showed significant depletion of TARDBP (human HeLa and SH-SY5Y cell lines, induced human motor neurons, and mouse striatal tissue). There was little overlap in differentially expressed genes between TDP-43-knockdown model cell types, but PFKP, RANBP1, KIAA1324, ELAVL3, and STMN2 were among the common TDP-43 targets. Similarly, there were few genes that showed common patterns of differential exon usage between cell types and which validated in TDP-43-immunonegative neurons, but these included well-known targets POLDIP3, RANBP1, STMN2, and UNC13A, and novel targets EXD3, CEP290, KPNA4, and MMAB. Enrichment analysis showed that TDP-43 knockdown in different cell types affected a unique range of biological pathways. Together, these data identify novel TDP-43 targets, validate known TDP-43 targets, and show that TDP-43 plays both conserved and cell-type-specific roles in the regulation of gene expression and splicing. Identification of cell-type-specific TDP-43 targets will enable sensitive mapping of cell-autonomous TDP-43 dysfunction beyond just neurons, while shared TDP-43 targets are likely to have therapeutic value across myriad cell types.
Estimating abundance of a recovering transboundary brown bear population with capture-recapture models
Authors: Vanpé Cécile , Piédallu Blaise , Quenette Pierre-Yves , Sentilles Jérôme , Queney Guillaume , Palazón Santiago , Jordana Ivan Afonso , Jato Ramón , Irurtia Miguel Mari Elósegui , de la Torre Jordi Solà , Gimenez Olivier
Published: December 2021

Abstract

Estimating the size of small populations of large mammals can be achieved via censuses, or complete counts, of recognizable individuals detected over a time period: minimum detected (population) size (MDS). However, as a population grows larger and its spatial distribution expands, the risk of under-estimating population size using MDS rapidly increases because the assumption of perfect detection of all individuals in the population is violated. The need to report uncertainty around population size estimates consequently becomes crucial. We explored these biases using the monitoring framework of the critically endangered Pyrenean brown bear that was close to extinction in the mid-1990s, with only five individuals remaining, but was subsequently bolstered by the introduction of 11 bears from Slovenia. Each year since 1996, the abundance of the population has been assessed using MDS and minimum retained (population) size (MRS), which corresponded to a reassessment of the MDS in the light of the new information collected in subsequent years (e.g., adding bears which were not detected the previous years but detected the current year). We used Pollock’s closed robust design (PCRD) capture-recapture models applied to the cross-border non-invasive sampling data from France, Spain and Andorra to provide the first published annual abundance and temporal trend estimates of the Pyrenean brown bear population since 2008. Annual population size increased fivefold between 2008 and 2020, going from 13 to 66 individuals. PCRD estimates were globally close to MRS counts and had reasonably narrow associated 95% Credibility Intervals. Even in cases where sampling effort is large compared to population size, the PCRD estimates of population size can diverge from the MDS counts. We report individual heterogeneity in detection that might stem from intraspecific home range size variation that result in individuals that move the most being most likely to be detected. We also found that cubs had a higher mortality rate than adults and subadults, because of infanticide by males, predation, maternal death, or abandonment. Overall, the PCRD capture-recapture modelling approach provides estimates of abundance and demographic rates of the Pyrenean brown bear population, together with associated uncertainty, while minimizing bias due to inter-individual heterogeneity in detection probabilities. We strongly encourage wildlife ecologists and managers to use robust approaches when researching large mammal populations. Such information is vital for informing management decision-making and assessing population conservation status.
Can pyrethroid-piperonyl butoxide (PBO) nets reduce the efficacy of indoor residual spraying with pirimiphos-methyl against pyrethroid-resistant malaria vectors?
Authors: Syme Thomas , Gbegbo Martial , Obuobi Dorothy , Fongnikin Augustin , Agbevo Abel , Todjinou Damien , Ngufor Corine
Published: December 2021

As the uptake of pyrethroid-PBO ITNs increases, their combination with IRS insecticides could become an operational reality in many malaria-endemic communities. Pirimiphos-methyl is a pro-insecticide requiring activation by mosquito cytochrome P450 enzymes to induce toxicity while PBO blocks activation of these enzymes in pyrethroid-resistant vector mosquitoes. PBO may thus antagonise the toxicity of pirimiphos-methyl IRS when combined with pyrethroid-PBO ITNs. The impact of combining two major brands of pyrethroid-PBO ITNs (Olyset® Plus, PermaNet® 3.0) with pirimiphos-methyl IRS (Actellic® 300CS) was evaluated against pyrethroid-resistant Anopheles gambiae sl in two parallel experimental hut trials in southern Benin in comparison to bendiocarb IRS and each intervention alone. The wild vector population was resistant to pyrethroids but susceptible to pirimiphos-methyl and bendiocarb. PBO pre-exposure partially restored deltamethrin toxicity but not permethrin. Mosquito mortality in experimental huts was significantly improved in the combinations of bendiocarb IRS with Olyset® Plus (33%) and PermaNet® 3.0 (38%) compared to bendiocarb IRS alone (14–16%, p<0.001), demonstrating an additive effect. Conversely, mortality was significantly reduced in the combinations of pirimiphos-methyl IRS with Olyset® Plus (59%) and PermaNet® 3.0 (55%) compared to pirimiphos-methyl IRS alone (77–78%, p<0.001), demonstrating an antagonistic effect. Combining pirimiphos-methyl IRS with the pyrethroid-PBO ITNs provided significantly improved mosquito mortality (55-59%) compared to the pyrethroid-PBO ITNs alone (22-26%) and improved blood-feeding inhibition relative to the IRS alone. This study provided evidence of an antagonistic effect when pyrethroid-PBO ITNs were combined with pirimiphos-methyl IRS in the same household resulting in lower levels of vector mosquito mortality compared to the IRS alone. Pirimiphos-methyl IRS also showed potential to significantly enhance malaria control when deployed to complement pyrethroid-PBO ITNs in an area where PBO fails to fully restore susceptibility to pyrethroids.
Ca2+ oscillations, waves, and networks in islets from human donors with and without type 2 diabetes
Authors: Gosak Marko , Yan-Do Richard , Lin Haopeng , MacDonald Patrick E. , Stožer Andraž
Published: December 2021

Pancreatic islets are highly interconnected structures that produce pulses of insulin and other hormones, maintaining normal homeostasis of glucose and other nutrients. Normal stimulus-secretion and intercellular coupling are essential to regulated secretory responses and these hallmarks are known to be altered in diabetes. In the present study, we used calcium imaging of isolated human islets to assess their collective cell behavior. The activity occurred in the form of calcium oscillations, was synchronized across different regions of islets through calcium waves, and was glucose-dependent: higher glucose enhanced the activity, elicited a greater proportion of global calcium waves, and led to denser and less fragmented functional networks. Hub regions were identified in stimulatory conditions, and they represented the most active islet regions. Moreover, calcium waves were found to be initiated in different subregions and the roles of initiators and hubs did not overlap. In type 2 diabetes, glucose-dependence was retained, but a reduced activity, locally restricted waves, and more segregated networks were detected compared with control islets. Interestingly, hub regions seemed to suffer the most by losing a disproportionately large fraction of connections. These changes affected islets from donors with diabetes in a heterogeneous manner.
The channel capacity of multilevel linguistic features constrains speech comprehension
Authors: Giroud Jérémy , Lerousseau Jacques Pesnot , Pellegrino François , Morillon Benjamin
Published: December 2021

Humans are expert at processing speech but how this feat is accomplished remains a major question in cognitive neuroscience. Capitalizing on the concept of channel capacity, we developed a unified measurement framework to investigate the respective influence of seven acoustic and linguistic features on speech comprehension, encompassing acoustic, sub-lexical, lexical and supra-lexical levels of description. We show that comprehension is independently impacted by all these features, but at varying degrees and with a clear dominance of the syllabic rate. Comparing comprehension of French words and sentences further reveals that when supra-lexical contextual information is present, the impact of all other features is dramatically reduced. Finally, we estimated the channel capacity associated with each linguistic feature and compared them with their generic distribution in natural speech. Our data point towards supra-lexical contextual information as the feature limiting the flow of natural speech. Overall, this study reveals how multilevel linguistic features constrain speech comprehension.
Differential Compositional Variation Feature Selection: A Machine Learning Framework with Log Ratios for Compositional Metagenomic Data
Authors: Hinton Andrew L. , Mucha Peter J.
Published: December 2021

The demand for tight integration of compositional data analysis and machine learning methodologies for predictive modeling in high-dimensional settings has increased dramatically with the increasing availability of metagenomics data. We develop the differential compositional variation machine learning framework (DiCoVarML) with robust multi-level log ratio bio-marker discovery for metagenomic datasets. Our framework makes use of the full set of pairwise log ratios, scoring ratios according to their variation between classes and then selecting out a small subset of log ratios to accurately predict classes. Importantly, DiCoVarML supports a targeted feature selection mode enabling researchers to define the number of predictors used to develop models. We demonstrate the performance of our framework for binary classification tasks using both synthetic and real datasets. Selecting from all pairwise log ratios within the DiCoVarML framework provides greater flexibility that can in demonstrated cases lead to higher accuracy and enhanced biological insight.
Induced fit with replica exchange improves protein complex structure prediction
Authors: Harmalkar Ameya , Mahajan Sai Pooja , Gray Jeffrey J.
Published: December 2021

Despite the progress in prediction of protein complexes over the last decade, recent blind protein complex structure prediction challenges revealed limited success rates (less than 20% models with DockQ score > 0.4) on targets that exhibit significant conformational change upon binding. To overcome limitations in capturing backbone motions, we developed a new, aggressive sampling method that incorporates temperature replica exchange Monte Carlo (T-REMC) and conformational sampling techniques within docking protocols in Rosetta. Our method, ReplicaDock 2.0, mimics induced-fit mechanism of protein binding to sample backbone motions across putative interface residues on-the-fly, thereby recapitulating binding-partner induced conformational changes. Furthermore, ReplicaDock 2.0 clocks in at 150-500 CPU hours per target (protein-size dependent); a runtime that is significantly faster than Molecular Dynamics based approaches. For a benchmark set of 88 proteins with moderate to high flexibility (unbound-to-bound iRMSD over 1.2 Å), ReplicaDock 2.0 successfully docks 61% of moderately flexible complexes and 35% of highly flexible complexes. Additionally, we demonstrate that by biasing backbone sampling particularly towards residues comprising flexible loops or hinge domains, highly flexible targets can be predicted to under 2 Å accuracy. This indicates that additional gains are possible when mobile protein segments are known.

Significance Statement

Proteins bind each other in a highly specific and regulated manner, and these associated dynamics of binding are intimately linked to their function. Conventional techniques of structure determination such as cryo-EM, X-ray crystallography and NMR are time-consuming and arduous. Using a temperature-replica exchange Monte Carlo approach that mimics the kinetic mechanism of “induced fit” binding, we improved prediction of protein complex structures, particularly for targets that exhibit considerable conformational changes upon binding (Interface root mean square deviation (unbound-bound) > 1.2 Å. Capturing these binding-induced conformational changes in proteins can aid us in better understanding biological mechanisms and suggest intervention strategies for disease mechanisms.
A Graph Convolutional Network-based screening strategy for rapid identification of SARS-CoV-2 cell-entry inhibitors
Authors: Gao Peng , Xu Miao , Zhang Qi , Chen Catherine Z , Guo Hui , Ye Yihong , Zheng Wei , Shen Min
Published: December 2021

The cell entry of SARS-CoV-2 has emerged as an attractive drug development target. We previously reported that the entry of SARS-CoV-2 depends on the cell surface heparan sulfate proteoglycan (HSPG) and the cortex actin, which can be targeted by therapeutic agents identified by conventional drug repurposing screens. However, this drug identification strategy requires laborious library screening, which is time-consuming and often limited number of compounds can be screened. As an alternative approach, we developed and trained a graph convolutional network (GCN)-based classification model using information extracted from experimentally identified HSPG and actin inhibitors. This method allowed us to virtually screen 170,000 compounds, resulting in ∼2000 potential hits. A hit confirmation assay with the uptake of a fluorescently labeled HSPG cargo further shortlisted 256 active compounds. Among them, 16 compounds had modest to strong inhibitory activities against the entry of SARS-CoV-2 pseudotyped particles into Vero E6 cells. These results establish a GCN-based virtual screen workflow for rapid identification of new small molecule inhibitors against validated drug targets.

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Functional modulation of PTH1R activation and signalling by RAMP2
Authors: Nemec Katarina , Schihada Hannes , Kleinau Gunnar , Zabel Ulrike , Grushevskyi Eugene O. , Scheerer Patrick , Lohse Martin J. , Maiellaro Isabella
Published: December 2021

Receptor-activity-modifying proteins (RAMPs) are ubiquitously expressed membrane proteins that associate with different G protein-coupled receptors (GPCRs) including the parathyroid hormone 1 receptor (PTH1R), a class B GPCR and an important modulator of mineral ion homeostasis and bone metabolism. However, it is unknown whether and how RAMP proteins may affect PTH1R function.

Using different optical biosensors to measure the activation of PTH1R and its downstream signalling, we describe here that RAMP2 acts as a specific allosteric modulator of PTH1R, shifting PTH1R to a unique pre-activated state that permits faster activation in a ligand-specific manner. Moreover, RAMP2 modulates PTH1R downstream signalling in an agonist-dependent manner, most notably increasing the PTH-mediated Gi3 signalling sensitivity. Additionally, RAMP2 increases both PTH- and PTHrP-triggered β-arrestin2 recruitment to PTH1R. Employing homology modelling we describe the putative structural molecular basis underlying our functional findings.

These data uncover a critical role of RAMPs in the activation and signalling of a GPCR that may provide a new venue for highly specific modulation of GPCR function and advanced drug design.
Simultaneous quantification of ankle, muscle, and tendon impedance in humans
Authors: Jakubowski Kristen L. , Ludvig Daniel , Bujnowski Daniel , Lee Sabrina S.M. , Perreault Eric J.
Published: December 2021

Objective

Regulating the impedance of our joints is essential for the effective control of posture and movement. The impedance of a joint is governed mainly by the mechanical properties of the muscle-tendon units spanning it. Many studies have quantified the net impedance of joints but not the specific contributions from the muscles and tendons. The inability to quantify both muscle and tendon impedance limits the ability to determine the causes underlying altered movement control associated with aging, neuromuscular injury, and other conditions that have different effects on muscle and tendon properties. Therefore, we developed a technique to quantify joint, muscle, and tendon impedance simultaneously and evaluated this technique at the human ankle.

Methods

We used a single degree of freedom actuator to deliver pseudorandom rotations to the ankle while measuring the corresponding torques. We simultaneously measured the displacement of the medial gastrocnemius muscle-tendon junction with B-mode ultrasound. From these experimental measurements, we were able to estimate ankle, muscle, and tendon impedance using non-parametric system identification.

Results

We validated our estimates by comparing them to previously reported muscle and tendon stiffness, the position-dependent component of impedance, to demonstrate that our technique generates reliable estimates of these properties.

Conclusion

Our approach can be used to clarify the respective contributions from the muscle and tendon to the net mechanics of a joint.

Significance

This is a critical step forward in the ultimate goal of understanding how muscles and tendons govern ankle impedance during posture and movement.