bluuebunny/crossref_metadata_2025_split huggingface dataset:
Higher knee hypertension in patients with hemiplegia correlates lower lateral and medial meniscus volume in the paretic leg
Authors: Li Wenshan , Li Tiancong , Xi Xiaoshuang , Zhang Rong , Sun Weishuang , Han Conglin , Zhang Dan , Gong Weijun 
Published: February 2022

ABSTRACTStroke is a disease with high morbidity and disability rate. After stroke, slower walking velocity, shorter step length, higher cadence, larger step width, and longer stance phase duration can be apparently observed. Additionally, these abnormal gait parameters eventually lead to knee hyperextension, known as genu recurvatum. Walking with such knee hyperextension usually induces knee pain and joint lesions, leading to cumulative damage and degenerative changes and further decreasing the standing phase’s stability. However, do higher angles of knee hyperextension have any correlation between the gait parameters, the kinematics, the kinetic parameters, the meniscus volume, and the water content of meniscus in paretic and non-paretic legs? This study attempted to answer these questions. The results revealed that 1) longer time since hemiplegia led to larger angles of knee hyperextension, 2) larger angles of knee hyperextension led to more tears in medial/lateral meniscus, and 3) larger angles of knee hyperextension decreased water content of the lateral meniscus in the non-paretic leg but increased water content of the medial meniscus. This was the first study to demonstrate these three above-mentioned observations through magnetic resonance imaging and motion capture system. These results suggested that 1) the knee hyperextension needed to be diagnosed and treated as early as possible; 2) the time since hemiplegia could be an indicator of sign of knee hyperextension; and 3) it might be not effective to identify the knee hyperextension by using spatial-temporal gait parameters.
Characterizing Affective Variability in Bipolar Disorder and Borderline Personality Disorder, and the Effects of Lithium, Using a Generative Model of Affect
Authors: Pulcu Erdem , Saunders Kate E.A. , Harmer Catherine J. , Harrison Paul J. , Goodwin Guy M. , Geddes John R. , Browning Michael 
Published: February 2022

AbstractThe affective variability of Bipolar Disorder (BD) is thought to qualitatively differ from that of Borderline Personality Disorder (BPD), with changes in affect persisting for longer in BD. However, quantitative studies have not been able to confirm this distinction. It has therefore not been possible to accurately quantify how treatments like lithium influence affective variability in BD. We assessed the affective variability associated with BD and BPD as well as the effect of lithium using a novel computational model that defines two subtypes of variability: affective changes that persist (volatility) and changes that do not (noise). We hypothesized that affective volatility would be raised in the BD group, noise would be raised in the BPD group and that lithium would impact affective volatility. Daily affect ratings were prospectively collected for up to 3 years from patients with BD, BPD and non-clinical controls. In a separate experimental-medicine study, patients with BD were randomized to receive lithium or placebo, with affect ratings collected from week -2 to +4. We found a diagnostically specific pattern of affective variability. Affective volatility was raised in patients with BD whereas affective noise was raised in patients with BPD. Rather than suppressing affective variability, lithium increased the volatility of positive affect in both studies. These results provide a quantitative measure of the affective variability associated with BD and BPD. They suggest a novel mechanism of action for lithium, whereby periods of persistently low or high affect are avoided by increasing the volatility of affective responses.
Estimating the distribution of livestock in space and time: a time-series contribution to livestock density mapping
Authors: Meisner Julianne , Kato Agapitus , Lemerani Marshall , Miaka Erick Mwamba , Taban Acaga Ismail , Wakefield Jonathan , Rowhani-Rahbar Ali , Pigott David , Mayer Jonathan , Rabinowitz Peter 
Published: February 2022

ABSTRACTMore than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock thus have broad utility across a range of applications, efforts to map the distribution of livestock on a large scale are limited to the Gridded Livestock of the World (GLW) project. We present a complimentary effort to map the distribution of cattle and pigs in Malawi, Uganda, Democratic Republic of Congo (DRC), and South Sudan. In contrast to GLW, which uses dasymmetric modeling applied to census data to produce time-stratified estimates of livestock counts and spatial density, our work uses complex survey data and distinct modeling methods to generate a time-series of livestock distribution, defining livestock density as the ratio of animals to humans. In addition to favorable cross-validation results and general agreement with national density estimates derived from external data on national human and livestock populations, our results demonstrate extremely good agreement with GLW-3 estimates, supporting the validity of both efforts. Our results furthermore offer a high-resolution time series result and employ a definition of density which is particularly well-suited to the study of livestock-origin zoonoses.
A comprehensive comparison on cell type composition inference for spatial transcriptomics data
Authors: Chen Jiawen , Liu Weifang , Luo Tianyou , Yu Zhentao , Jiang Minzhi , Wen Jia , Gupta Gaorav P. , Giusti Paola , Zhu Hongtu , Yang Yuchen , Li Yun 
Published: February 2022

AbstractSpatial transcriptomic (ST) technologies allow researchers to examine high-quality RNA-sequencing data along with maintained two-dimensional positional information as well as a co-registered histology image. A popular use of ST omics data is to provide insights about tissue structure and spatially unique features. However, due to the technical nature unique to most ST data, the resolution varies from a diameter of 2-10μm to 50-100μm instead of single-cell resolution, which brings uncertainty into cell number and cell mixture within each ST spot. Motivated by the important role for spatial arrangement of cell types within a tissue in physiology and disease pathogenesis, several ST deconvolution methods have been developed and are being used to explore gene expression variation and identification of spatial domains. The aim of this work is to review state-of-the-art methods for ST deconvolution, while comparing their strengths and weaknesses. Specifically, we use four real datasets to examine the performance of eight methods across different tissues and technological platforms.Key PointsCell mixture inference is a critical step in the analysis of spatial transcriptomics (ST) data to prevent downstream analysis suffering from confounding factors at the spot level.Existing ST deconvolution methods can be classified into three groups: probabilistic-based, non-negative matrix factorization and non-negative least squares based, and other deep learning framework-based methods.We compared eight ST deconvolution methods by using two single cell level resolution datasets and two spot level resolution ST datasets. We provided practical guidelines for the choice of method under different scenarios as well as the optimal subsets of genes to use for each method.
Natural language signatures of psilocybin microdosing
Authors: Sanz Camila , Cavanna Federico , Muller Stephanie , de la Fuente Laura , Zamberlan Federico , Palmucci Matías , Janeckova Lucie , Kuchar Martin , Carrillo Facundo , García Adolfo M. , Pallavicini Carla , Tagliazucchi Enzo 
Published: February 2022

AbstractSerotonergic psychedelics are being studied as novel treatments for mental health disorders and as facilitators of improved well-being, mental function and creativity. Recent studies have found mixed results concerning the effects of low doses of psychedelics (“microdosing”) on these domains. However, microdosing is generally investigated using instruments designed to assess larger doses of psychedelics, which might lack sensitivity and specificity for this purpose. Following a double-blind and placebo-controlled experimental design, we explored natural language as a resource to identify speech produced under the acute effects of psilocybin microdoses, focusing on variables known to be affected by higher doses: verbosity, semantic variability and sentiment scores. Except for semantic variability, these metrics presented significant differences between a typical active microdose of 0.5 g of psilocybin mushrooms and an inactive placebo condition. Moreover, machine learning classifiers trained using these metrics were capable of distinguishing between conditions with high accuracy (AUC≈0.8). Our results constitute first proof that low doses of serotonergic psychedelics can be identified from unconstrained natural speech, with potential for widely applicable, affordable, and ecologically valid monitoring of microdosing schedules.
Competition contributes to both warm and cool range edges
Authors: Lyu Shengman , Alexander Jake M. 
Published: February 2022

AbstractCompetition plays an important role in shaping species’ spatial distributions. However, it remains unclear where and how competition regulates species’ range limits. In a field experiment with plants originating from low and high elevations and conducted across an elevation gradient in the Swiss Alps, we find that both lowland and highland species can better persist in the presence of competition within than beyond their elevation ranges, suggesting that competition helps set both lower and upper elevation range limits of these species. Furthermore, the reduced ability of pairs of lowland or highland species to coexist beyond their range edges is mainly driven by diminishing niche differences; changes in both niche differences and relative fitness differences drive weakening competitive dominance of lowland over highland species with increasing elevation. These results highlight the need to account for competitive interactions and investigate underlying coexistence mechanisms to understand current and future species distributions.
Gut microbiome disturbances of altricial Blue and Great tit nestlings are countered by continuous microbial inoculations from parental microbiomes
Authors: Diez-Méndez David , Bodawatta Kasun H. , Freiberga Inga , Klečková Irena , Jønsson Knud A. , Poulsen Michael , Sam Katerina 
Published: February 2022

AbstractGut microbial communities are complex and heterogeneous and play critical roles for animal hosts. Early-life disruptions to microbiome establishment can negatively impact host fitness and development. However, the consequences of such early-life disruptions are unknown in wild birds. To help fill this gap, after validating the disruptive influence of antibiotic and probiotic treatments on the gut microbiome in adult Great tits (Parus major) (efficacy experiment), we investigated the effect of continuous early-life gut microbiome disruptions on the establishment and development of gut communities in wild Great and Blue tit (Cyanistes caeruleus) nestlings (field experiment). Despite negative impacts of treatments on microbial alpha and beta diversities in the efficacy experiment, treatment did not affect the composition of nestling microbiomes in the field experiment. Independent of treatment, nestling gut microbiomes of both species grouped by brood, sharing high numbers of bacterial taxa with both the nest environment and their mother. The distance between nests increased inter-brood microbiome dissimilarity, but only in Great tits, indicating species-specific influence of environment on microbiomes. The strong maternal effect, driven by continuous recolonization from the nest environment and vertical transfer of microbes during feeding thus appear to provide resilience towards early-life disruptions in nestling gut microbiomes.
From bacteria to plants: a repurposing strategy in the pursuit for novel herbicides
Authors: Mackie Emily R. R. , Barrow Andrew S. , Giel Marie-Claire , Hulett Mark D. , Gendall Anthony R. , Panjikar Santosh , Soares da Costa Tatiana P. 
Published: February 2022

ABSTRACTHerbicide resistance represents one of the biggest threats to our natural environment and agricultural sector. Thus, new herbicides are urgently needed to tackle the rise in herbicideresistant weeds. Here, we employed a novel strategy to repurpose a ‘failed’ antibiotic into a new and target-specific herbicidal compound. Specifically, we identified an inhibitor of bacterial dihydrodipicolinate reductase (DHDPR), an enzyme involved in lysine biosynthesis in plants and bacteria, that exhibited no antibacterial activity but severely attenuated germination of the plant Arabidopsis thaliana. We confirmed that the inhibitor targets plant DHDPR orthologues in vitro, and exhibits no toxic effects against human cell lines. A series of analogues were then synthesised with improved efficacy in germination assays and against soil-grown A. thaliana plants. We also showed that our lead compound is the first lysine biosynthesis inhibitor with herbicidal activity against a weed species, providing proof-of-concept that DHDPR inhibition may represent a much-needed new herbicide mode of action. Furthermore, this study exemplifies the untapped potential of repurposing ‘failed’ antibiotic scaffolds to fast-track the development of herbicide candidates targeting the respective plant enzymes to combat the global rise in herbicide-resistant weeds.
Allosteric interactions prime androgen receptor dimerization and activation
Authors: Wasmuth Elizabeth V. , Broeck Arnaud Vanden , LaClair Justin R. , Hoover Elizabeth A. , Lawrence Kayla E. , Paknejad Navid , Pappas Kyrie , Matthies Doreen , Wang Biran , Feng Weiran , Watson Philip A. , Zinder John C. , Karthaus Wouter R. , de la Cruz M. Jason , Hite Richard K. , Manova-Todorova Katia , Yu Zhiheng , Weintraub Susan T. , Klinge Sebastian , Sawyers Charles L. 
Published: February 2022

SummaryThe androgen receptor (AR) is a steroid receptor and master transcription factor that governs gene expression programs required for luminal development of prostate epithelium, formation of muscle tissue and maintenance of the male phenotype. AR misregulation is a hallmark of multiple malignancies, including prostate cancer, where AR hyperactivation and expansion of its transcriptome occur in part through AR gene amplification and interaction with oncoprotein cofactors. Despite its biological importance, how AR’s individual domains and its protein cofactors cooperate to bind DNA have remained elusive. Using a combination of reconstitution biochemistry and single particle cryo-electron microscopy (EM), we have isolated three conformational states of AR bound to DNA. We observe that AR forms a non-obligate dimer, with the buried dimer interface utilized by related ancestral nuclear receptors repurposed to facilitate cooperative DNA binding. We identify surfaces bridging AR’s domains responsible for allosteric communication, that are compromised in partial androgen insensitivity syndrome (PAIS), and are reinforced by AR’s oncoprotein cofactor, ERG, and DNA binding site motifs. Finally, we present evidence that this plastic dimer interface for transcriptional activation may have been adopted by AR at the expense of DNA binding. Our work highlights how fine-tuning of AR’s cooperative interactions translate to consequences in development and disease.
Persisting pulmonary dysfunction in pediatric post-acute Covid-19
Authors: Heiss Rafael , Wagner Alexandra , Tan Lina , Schmidt Sandy , Regensburger Adrian P. , Ewert Franziska , Mammadova Dilbar , Buehler Adrian , Vogel-Claussen Jens , Voskrebenzev Andreas , Rauh Manfred , Rompel Oliver , Nagel Armin M. , Lévy Simon , Bickelhaupt Sebastian , May Matthias S. , Uder Michael , Metzler Markus , Trollmann Regina , Woelfle Joachim , Knieling Ferdinand 
Published: February 2022

AbstractThe frequency and extent of persistent sequelae in children and adolescents after infection with SARS-CoV-2 still needs to be comprehensively determined. In this cross-sectional clinical trial, we used non-invasive, label-free morphologic and free-breathing phase-resolved functional low-field magnetic resonance imaging (LF-MRI) to identify pulmonary changes in children and adolescents from 5 to <18 years after previously PCR-confirmed SARS-CoV-2 infection. While morphological pathologies were less frequent in children, functional LF-MRI visualized widespread ventilation, perfusion and combined ventilation/perfusion defects compared to healthy controls. The loss of functional lung parenchyma was more pronounced in long Covid than recovered patients. While pulmonary dysfunction was persistent even month after primary infection, LF-MRI demonstrated high capability to visualize and detect these changes in children and adolescents. (Clinicaltrials.org ID NCT04990531)
Discrimination of bacterial and viral infection using host-RNA signatures integrated in a lab-on-a-chip technology
Authors: Pennisi Ivana , Moniri Ahmad , Miscourides Nicholas , Miglietta Luca , Moser Nicolas , Habgood-Coote Dominic , Herberg Jethro A. , Levin Michael , Kaforou Myrsini , Rodriguez-Manzano Jesus , Georgiou Pantelis 
Published: February 2022

ABSTRACTThe unmet clinical need for accurate point-of-care (POC) diagnostic tests able to discriminate bacterial from viral infection demands a solution that can be used both within healthcare settings and in the field and that can also stem the tide of antimicrobial resistance. Our approach to solve this problem is to combine the use of Host-gene signatures with our Lab-on-a-chip (LoC) technology enabling low-cost LoC expression analysis to detect Infectious Disease.Host-gene expression signatures have been extensively study as a potential tool to be implemented in the diagnosis of infectious disease. On the other hand LoC technologies using Ion-sensitive field-effect transistor (ISFET) arrays, in conjunction with isothermal chemistries, are offering a promising alternative to conventional lab-based nucleic acid amplification instruments, owing to their portable and affordable nature. Currently, the data analysis of ISFET arrays are restricted to established methods by averaging the output of every sensor to give a single time-series. This simple approach makes unrealistic assumptions, leading to insufficient performance for applications that require accurate quantification such as RNA host transcriptomics. In order to reliably quantify host-gene expression on our LoC platform enabling the classification of bacterial and viral infection on chip, we propose a novel data-driven algorithm for extracting time-to-positive values from ISFET arrays. The algorithm proposed is based on modelling sensor drift with adaptive signal processing and clustering sensors based on their behaviour with unsupervised learning methods. Results show that the approach correctly outputs a time-to-positive for all the reactions, with a high correlation to RT-qLAMP (0.85, R2 = 0.98, p < 0.01), resulting in a classification accuracy of 100 % (CI, 95 - 100). By leveraging more advanced data processing methods for ISFET arrays, this work aims to bridge the gap between translating assays from microarray analysis (expensive lab-based discovery method) to ISFET arrays (cheap point-of-care diagnostics) providing benefits on tackling infectious disease outbreak and diagnostic testing in hard-to-reach areas of the world.
A prefrontal to lateral entorhinal pathway disrupts memory
Authors: Hisey Erin , Soderling Scott H. 
Published: February 2022

AbstractWhile the neural circuits underlying memory encoding, storage, and retrieval are well characterized, the circuits that act to disrupt memory are enigmatic. Here we find that silencing a projection from the prefrontal cortex to the lateral entorhinal cortex surprisingly improves spatial working memory and contextual memory. We then found that the same cell type shows increased activity during errors in a spatial working memory test. Finally we found that optogenetic activation of the same activity patterns can disrupt working memory performance. By using a combination of intersectional genetic and in vivo imaging techniques we advance evidence that a novel prefrontal-entorhinal pathway critically participates in memory disruption.
Consistent measurement of LAG-3 expression across multiple staining platforms with the 17B4 antibody clone
Authors: Wojcik John B. , Desai Keyur , Avraam Konstantinos , Vandebroek Arno , Dillon Lloye M. , Giacomazzi Giorgia , Rypens Charlotte , Benci Joseph L. 
Published: February 2022

AbstractContextAn immunohistochemistry (IHC) assay developed to detect lymphocyte-activation gene 3 (LAG-3), a novel immune checkpoint inhibitor target, has demonstrated high analytical precision and interlaboratory reproducibility using a Leica staining platform, but has not been investigated on other IHC staining platforms.ObjectiveTo evaluate the performance of LAG-3 IHC assays using the 17B4 antibody clone across widely used IHC staining platforms: Agilent/Dako Autostainer Link 48 (ASL-48) and VENTANA BenchMark ULTRA (VBU) compared with Leica BOND-RX (BOND-RX).DesignEighty formalin-fixed paraffin-embedded melanoma tissue blocks were cut into consecutive sections and evaluated using staining platform–specific IHC assays with the 17B4 antibody clone. Duplicate testing was performed on the BOND-RX platform to assess intraplatform agreement. LAG-3 expression using a numerical score was evaluated by a pathologist and with a digital scoring algorithm. LAG-3 positivity was determined from manual scores using a ≥ 1% cutoff.ResultsLAG-3 IHC staining patterns and intensities were visually similar across all 3 staining platforms. Pearson correlation was ≥ 0.88 for interplatform and BOND-RX intraplatform concordance when LAG-3 expression was evaluated with a numerical score determined by a pathologist. Correlation increased with a numerical score determined with a digital scoring algorithm (Pearson correlation ≥ 0.93 for all comparisons). Overall percentage agreement was ≥ 77.5% for interplatform and BOND-RX intraplatform comparisons when a ≥ 1% cutoff was used to determine LAG-3 positivity.ConclusionsData from this study demonstrate that LAG-3 expression can be robustly and reproducibly assessed across 3 major commercial IHC staining platforms using the 17B4 antibody clone.