bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tenecteplase 0.4 mg/kg in moderate and severe acute ischemic stroke: A pooled analysis of NOR-TEST & NOR-TEST 2A
Authors: Novotny Vojtech , Kvistad Christopher Elnan , Naess Halvor , Logallo Nicola , Fromm Annette , Khanevski Andrej Netland , Thomassen Lars 
Published: May 2023

AbstractBackgroundThe optimal dose of tenecteplase in acute ischaemic stroke remains to be defined. We present a pooled analysis of the two NOR-TEST trials exploring the efficacy and safety of tenecteplase 0.4 mg/kg in acute ischemic stroke.MethodsWe retrospectively reviewed two multi-center PROBE trials, NOR-TEST and NOR-TEST 2A, conducted in Norway. The patients were randomized to either 0.4 mg/kg single bolus tenecteplase or standard 0.9 mg/kg alteplase. The primary endpoint was favorable functional outcome at three months (mRS 0-1) or return to baseline if pre-stroke mRS was 2. The secondary endpoints included favorable functional outcome at three months (Modified Rankin Scale 0-2), major neurological improvement and safety data. The pooling project includes a pooled analysis of patients with moderate to severe stroke (NIHSS ≥6) from both trials and an additional post-hoc analysis of patients with mild stroke (NIHSS ≤5) from NOR-TEST.ResultsThe per-protocol analysis contains 483 patients, of which 235 were assigned to tenecteplase and 248 to alteplase. In per-protocol analysis, functional outcome was better in the alteplase arm with cut-off mRS 2 (OR 0.52, 95% CI 0.33-0.80, p=0.003) and expressed by ordinal shift analysis (OR 1.64, 95% CI 1.17-2.28, p=0.004). Mortality at 3 months was higher in the tenecteplase arm (OR 2.48, 95% CI 1.20-5.10, p=0.014). Mortality and intracranial hemorrhage rates were higher in the severe stroke group randomized to tenecteplase, whereas these rates were similar for alteplase and tenecteplase in moderate and mild stroke. High age was not associated with either higher mortality or intracranial hemorrhage rates.ConclusionsTenecteplase 0.4 mg/kg is unsafe in moderate and severe stroke and the risk of death and intracranial hemorrhage probably increases with stroke severity. A lower tenecteplase dose should be tested in future trials.Trial RegistrationClinicalTrials.govIdentifiers:NCT01949948,NCT03854500https://clinicaltrials.gov/ct2/show/NCT01949948https://clinicaltrials.gov/ct2/show/NCT03854500
A Series of Composited Tumor DNA Reference Materials Containing Three Genes and Ten Mutation Positions for CNV and SNV Detection
Authors: Fan Weijian , Shi Runyu , Zhang Hongyun , Li Cuicui , Zhang Jiawen , Su Shuixiu , Wu Ping , Tang Meifang 
Published: May 2023

AbstractProcesses in clinic for tumors diagnosis and treatment need reference materials (RMs) to evaluate and calibrate. However, no RMs can provides properties of copy number variation (CNV) and single nucleotide variants (SNV) of genesEGFR, HER2, MET, PIK3CA, KRAS, BRAF, NRASsimultaneously. In this study, we used commercial cell lines to construct a series of tumor RMs containing property mentioned above. Furthermore, we evaluated their stability, homogeneity, and commutability by droplet digital PCR and next generation sequencing technology. The results showed that, for tumor CNV gDNA RM, the copy number is 7.3 copies/μL (EGFR), 5.3 copies/μL (HER2) and 8.2 copies/μL (MET). For tumor 5% SNV gDNA RM, the mutation frequency of each mutation position showed as follow:EGFR-E746A750 (24.6%),EGFR-L858R (5.8%),EGFR-T790M (5.5%),EGFR-G719S (6.6%),PIK3CA-E545K (4.7%),PIK3CA-H1047R (5.8%),KRAS-G13D (8.2%),KRAS-G12D (6.5%),BRAF-V600E (4.6%),NRAS-Q61K (8.5%). All variable coefficient (CV) of tumor gDNA RM for homogeneity were less than 7%, that of CNV+SNV ctDNA RM were less than 17%. Besides, the CV for commutability of the all types of RMs were less than 17%. These RMs can be applied into a wide range type of sequencing panels and provides a closer simple background.
Imperfect gold standard gene sets yield inaccurate evaluation of causal gene identification methods
Authors: Wang Lijia , Wen Xiaoquan , Morrison Jean 
Published: May 2023

AbstractCausal gene discovery methods are often evaluated using gold-standard (GS) sets of causal genes. However, GS gene sets are always incomplete, leading to mis-estimation of sensitivity, specificity, AUC. Labeling biases in GS gene sets can also lead to inaccurate ordering of discovery methods. We argue that evaluation of these methods should rely on statistical techniques like those used for variant discovery, rather than on comparison with GS gene sets.
Testing a candidate meiotic drive locus identified by pool sequencing
Authors: Barbash Daniel A. , Jin Bozhou , Wei Kevin H-C , Dion-Côté Anne-Marie 
Published: May 2023

ABSTRACTMeiotic drive biases the transmission of alleles in heterozygous individuals, such that Mendel’s law of equal segregation is violated. Most examples of meiotic drive have been discovered over the past century based on causing sex-ratio distortion or the biased transmission of easily scoreable genetic markers that were linked to drive alleles. More recently, several approaches have been developed that attempt to identify distortions of Mendelian segregation genome-wide. Here we test a candidate female meiotic drive locus inDrosophila melanogaster, identified previously as causing a ∼54:46 distortion ratio using sequencing of large pools of backcross progeny. We inserted fluorescent visible markers near the candidate locus and scored transmission in thousands of individual progeny. We observed a small but significant deviation from the Mendelian expectation, however it was in the opposite direction to that predicted based on the original experiments. We discuss several possible causes of the discrepancy between the two approaches, noting that subtle viability effects are particularly challenging to disentangle from potential small-effect meiotic drive loci. We conclude that pool sequencing approaches remain a powerful method to identify candidate meiotic drive loci, but that genotyping of individual progeny at early developmental stages may be required for robust confirmation.
TDP-43 pathology inDrosophilainduces glial-cell type specific toxicity that can be ameliorated by knock-down of SF2/SRSF1
Authors: Krupp S. , Tam O , Gale Hammell M , Dubnau J 
Published: May 2023

AbstractAccumulation of cytoplasmic inclusions of TAR-DNA binding protein 43 (TDP-43) is seen in both neurons and glia in a range of neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD) and Alzheimer’s disease (AD). Disease progression involves non-cell autonomous interactions among multiple cell types, including neurons, microglia and astrocytes. We investigated the effects inDrosophilaof inducible, glial cell type-specific TDP-43 overexpression, a model that causes TDP-43 protein pathology including loss of nuclear TDP-43 and accumulation of cytoplasmic inclusions. We report that TDP-43 pathology inDrosophilais sufficient to cause progressive loss of each of the 5 glial sub-types. But the effects on organismal survival were most pronounced when TDP-43 pathology was induced in the perineural glia (PNG) or astrocytes. In the case of PNG, this effect is not attributable to loss of the glial population, because ablation of these glia by expression of pro-apoptotic reaper expression has relatively little impact on survival. To uncover underlying mechanisms, we used cell-type-specific nuclear RNA sequencing to characterize the transcriptional changes induced by pathological TDP-43 expression. We identified numerous glial cell-type specific transcriptional changes. Notably, SF2/SRSF1 levels were found to be decreased in both PNG and in astrocytes. We found that further knockdown ofSF2/SRSF1in either PNG or astrocytes lessens the detrimental effects of TDP-43 pathology on lifespan, but extends survival of the glial cells. Thus TDP-43 pathology in astrocytes or PNG causes systemic effects that shorten lifespan andSF2/SRSF1knockdown rescues the loss of these glia, and also reduces their systemic toxicity to the organism.
Identification of Pain-Associated Effusion-Synovitis from Knee Magnetic Resonance Imaging by Deep Generative Networks
Authors: Lian Pin-Hsun. , Chuang Tzu-Yi , Yen Yi-Hsuan , Chang Gary Han 
Published: May 2023

ABSTRACTObjectivesTo identify the source and location of osteoarthritis-induced pain symptoms, we used deep learning techniques to identify imaging abnormalities associated with pain from magnetic resonance imaging (MRI) of knees with symptoms of symptoms of osteoarthritis pain.MethodsPain-associated areas were detected from the difference between the MRI images of symptomatic knees and their respective counterfactual asymptomatic images generated by a Generative adversarial network. A total of 2,225 pairs of 3D MRI images were extracted from patients with unilateral pain symptoms in the baseline and follow-up cohorts of the Osteoarthritis Initiative. Subsequently, pain-associated effusion-synovitis were characterized into subregions (patellar, central, and posterior) using an anatomical segmentation model.ResultsWe found that the volumes of pain-associated effusion-synovitis were more sensitive and reliable indicators of pain symptoms than the overall volumes in the central and posterior subregions (odds ratio [OR]:3.23 versus 1.77 in the central region, and 3.18 versus 2.66 in the posterior region for severe effusion-synovitis). For mild effusion-synovitis, only pain-associated volume was found to be associated with pain symptoms, but not with overall volume. Patients with significant pain-associated effusion-synovitis in the patellar subregion had the highest increased odds of pain symptoms (OR=4.86).ConclusionTo the best of our knowledge, this is the first study to utilize deep-learning-based models for the detection and characterization of pain-associated imaging abnormalities. The developed algorithm can help identifying the source and location of pain symptoms and in designing targeted and individualized treatment regimens.
When population growth intensifies intergroup competition, female colobus monkeys free-ride less
Authors: Arseneau-Robar T. Jean , Teichroeb Julie A. , Macintosh Andrew J. , Saj Tania L. , Glotfelty Emily , Lucci Sarah , Sicotte Pascale , Wikberg Eva C. 
Published: May 2023

AbstractIn many social species, intergroup aggression is a cooperative activity that produces public goods such as a safe and stable social environment and a home range containing the resources required to survive and reproduce. In this study, we investigate temporal variation in intergroup aggression in a growing population of colobus monkeys to ask a novel question: “Who stepped-up to produce these public goods when the competitive landscape changed?”. Both whole-group encounters and male incursions occurred more frequently as the population grew. Males and females were both more likely to participate in whole-group encounters when monopolizable food resources were available, indicating both sexes engaged in food defence. However, only females increasingly did so over time, suggesting that when intergroup competition intensified, it was females who increasingly invested in home range defence. Females were also more active in male incursions at high population densities, suggesting they also worked harder to maintain a safe and stable social environment over time. This is not to say that males were chronic free-riders when it came to maintaining public goods. Males consistently participated in the majority of intergroup interactions throughout the study period, indicating they may have lacked the capacity to invest more time and effort.
A Chemical Reaction Similarity-Based Prediction Algorithm Identifies the Multiple Taxa Required to Catalyze an Entire Metabolic Pathway of Dietary Flavonoids
Authors: Gulsan Ebru Ece , Nowshad Farrhin , Yamaguchi Pomaikaimaikalani , Dong Xiaokun , Jayaraman Arul , Lee Kyongbum 
Published: May 2023

AbstractFlavonoids are polyphenolic phytochemicals abundant in plant-based, health-promoting foods. They are only partially absorbed in the small intestine, and gut microbiota plays a significant role in their metabolism. As flavonoids are not natural substrates of gut bacterial enzymes, reactions of flavonoid metabolism have been attributed to the ability of general classes of enzymes to metabolize non-natural substrates. To systematically characterize this promiscuous enzyme activity, we developed a prediction tool that is based on chemical reaction similarity. The tool takes a list of enzymes or organisms to match microbial enzymes with their non-native flavonoid substrates and orphan reactions. We successfully predicted the promiscuous activity of known flavonoid-metabolizing bacterial and plant enzymes.Next, we used this tool to identify the multiple taxa required to catalyze an entire metabolic pathway of dietary flavonoids. Tilianin is a flavonoid-O-glycoside having biological and pharmacological activities, including neuroprotection. Using our prediction tool, we defined a novel bacterial pathway of tilianin metabolism that includes O-deglycosylation to acacetin, demethylation of acacetin to apigenin, and hydrogenation of apigenin to naringenin. We predicted and confirmed using in vitro experiments and LC-MS techniques that Bifidobacterium longum subsp.animalis,Blautia coccoidesandFlavonifractor plautiican catalyze this pathway. Prospectively, the prediction-validation methodology developed in this work could be used to systematically characterize gut microbial metabolism of dietary flavonoids and other phytochemicals.The bioactivities of flavonoids and their metabolic products can vary widely. We used an in vitro rat neuronal model to show that tilianin metabolites exhibit protective effect against H2O2through reactive oxygen species (Delepine et al.) scavenging activity and thus, improve cell viability, while the parent compound, tilianin, was ineffective. These results are important to understand the gut microbiota-dependent physiological effects of dietary flavonoids.
PROTEOMICS OF HYPOTHERMIC ADAPTATION REVEALS THAT RBM3 ENHANCES MITOCHONDRIAL METABOLISM AND MUSCLE STEM-CELL DIFFERENTIATION
Authors: Dey Paulami , Rajalaxmi Srujanika , Thakur Purvi Singh , Hashmi Maroof Athar , Lal Heera , Saini Nistha , Muralidharan Sneha , Math Raviswamy G H , Saha Pushpita , Pundlik Swarang Sachin , Singh Nirpendra , Ramanathan Arvind 
Published: May 2023

AbstractAdaptation to hypothermic stress is important for skeletal muscle cells, but a comprehensive knowledge of molecular mediators is lacking. We show that adaptation to mild hypothermia (320C) improves the ability of skeletal muscle myoblasts to differentiate into myotubesin vitro. We performed proteomic analysis of mouse myoblasts exposed to mild hypothermia for various time points and identified dynamic changes in mitochondrial metabolism and proteostasis. This revealed that RBM3, an RNA-binding protein, increases progressively with acute and chronic exposure to hypothermic stress, and is necessary for the enhanced differentiation upon hypothermic adaptation. We also demonstrate that overexpression of RBM3 at physiological temperatures is sufficient to (i) enhance mitochondrial metabolism as judged by a decrease in the AMPK energy-sensing pathway, (ii) increase levels of proteins associated with translation and increase levels of 4E-BP1 phosphorylation, (iii) increase stem cell markers (MyoD1, PAX7), and improve differentiation of myoblasts from both young and aged mice.
OneNet – One network to rule them all: consensus network inference from microbiome data
Authors: Champion Camille , Momal Raphaelle , Chatelier Emmanuelle Le , Sola Mathilde , Mariadassou Mahendra , Berland Magali 
Published: May 2023

AbstractModeling microbial interactions as sparse and reproducible networks is a major challenge in microbial ecology. Direct interactions between the microbial species of a biome can help to understand the mechanisms through which microbial communities influence the system. Most state-of-the art methods reconstruct networks from abundance data using Gaussian Graphical Models, for which several statistically grounded and computationnally efficient inference approaches are available. However, the multiplicity of existing methods, when applied to the same dataset, generates very different networks. In this article, we present OneNet, a consensus network inference method that combines seven methods based on stability selection. This resampling procedure is used to tune a regularization parameter by computing how often edges are selected in the networks. We modified the stability selection framework to use edge selection frequencies directly and combine them in the inferred network to ensure that only reproducible edges are included in the consensus. We demonstrated on synthetic data that our method generally led to slightly sparser networks while achieving much higher precision than any single method. We further applied the method to gut microbiome data from liver-cirrothic patients and demonstrated that the resulting network exhibited a microbial guild that was meaningful in terms of human health.
A novel bacterial signal transduction system specifically senses and responds to peptidoglycan damage
Authors: Yin Jianhua , Xu Chaoyi , Hu Xiao , Zhang Ting , Liang Yanqun , Sun Yijuan , Zhen Xiangkai , Zhu Yiling , Luo Yuke , Shen Penshan , Cheng Dan , Sun Yiyang , Cai Jingxiao , Meng Qiu , Zhu Tingheng , Wan Fen , Gao Haichun , Yu Zhiliang 
Published: May 2023

AbstractThe peptidoglycan (PG) layer is a mesh-like structure within the cell envelope essential for maintenance of cell shape and resistance to osmotic stress, and therefore is a primary target of many important and widely used antibiotics, such as β-lactams. In Gram-negative bacteria, while signal transduction systems that monitor the state of the inner- and outer-membranes have been extensively studied and well understood, much less is known about how cells sense and respond to PG-targeting stresses. Here we show that a novel bacterial two-component system (PghKR) fromShewanella oneidensisis capable of sensing and responding to PG damage. This system is specifically activated in cells exposed to various PG-targeting antibiotics or carrying a defect in PG synthesis, resulting in induced expression ofblaAandrelV, which encode a β-lactamase conferring resistance to β-lactams and a small ppGpp synthetase responsible for antibiotic tolerance, respectively. Intriguingly, the PghKR homologs are widespread among several classes ofProteobacteriaand the periplasmic domain of sensor kinase PghK contains a family 9 carbohydrate-binding module that is required for signal perception, implying that the signals could be the glycan fragments of PG. Overall, our results provide critical insights into the regulation of PG homeostasis in Gram-negative bacteria.
Dysfunctional effector memory CD8 T cells in the bronchoalveolar compartment of people living with HIV
Authors: Mthembu Maphe , Claassen Helgard , Khuzwayo Sharon , Voillet Valentin , Naidoo Anneta , Nyamande Kennedy , Khan Dilshaad F. , Maharaj Priya , Mitha Mohammed , Mhlane Zoey , Karim Farina , Andersen-Nissen Erica , Ndung’u Thumbi , Pollara Gabriele , Wong Emily B. 
Published: May 2023

AbstractMechanisms by which HIV causes susceptibility to respiratory pathogens remain incompletely understood. We obtained whole blood and bronchoalveolar lavage (BAL) from people with latent TB infection in the presence or absence of antiretroviral-naïve HIV co-infection. Transcriptomic and flow cytometric analyses demonstrated HIV-associated cell proliferation plus type I interferon activity in blood and effector memory CD8 T-cells in BAL. Both compartments displayed reduced induction of CD8 T-cell-derived IL-17A in people with HIV, associated with elevated T-cell regulatory molecule expression. The data suggest that dysfunctional CD8 T-cell responses in uncontrolled HIV contribute to susceptibility to secondary bacterial infections, including tuberculosis.
Connectome-based prediction of functional impairment in experimental stroke models
Authors: Schmitt Oliver , Eipert Peter , Wang Yonggang , Kanoke Atsushi , Rabiller Gratianne , Liu Jialing 
Published: May 2023

AbstractExperimental rat models of stroke and hemorrhage are important tools to investigate cerebrovascular disease pathophysi- ology mechanisms, yet how significant patterns of functional impairment induced in various models of stroke are related to changes in connectivity at the level of neuronal populations and mesoscopic parcellations of rat brains remain unresolved. To address this gap in knowledge, we employed two middle cerebral artery occlusion models and one intracerebral hemorrhage model with variant extent and location of neuronal dysfunction. Motor and spatial memory function was assessed and the level of hippocampal activation via Fos immunohistochemistry. Contribution of connectivity change to functional impairment was analyzed for connection similarities, graph distances and spatial distances as well as the importance of regions in terms of network architecture based on theneuroVIISASrat connectome. We found that functional impairment correlated with not only the extent but also the locations of the injury among the models. In addition, via coactivation analysis in dynamic rat brain models, we found that lesioned regions led to stronger coactivations with motor function and spatial learning regions than with other unaffected regions of the connectome. Dynamic modeling with the weighted bilateral connectome detected changes in signal propagation in the remote hippocampus in all 3 stroke types, predicting the extent of hippocampal hypoactivation and impairment in spatial learning and memory function. Our study provides a comprehensive analytical framework in predictive identification of remote regions not directly altered by stroke events and their functional implication.
SKOOTS: Skeleton oriented object segmentation for mitochondria
Authors: Buswinka Christopher J , Nitta Hidetomi , Osgood Richard T. , Indzhykulian Artur A. 
Published: May 2023

ABSTRACTThe segmentation of individual instances of mitochondria from imaging datasets is informative, yet time-consuming to do by hand, sparking interest in developing automated algorithms using deep neural networks. Existing solutions for various segmentation tasks are largely optimized for one of two types of biomedical imaging: high resolution three-dimensional (whole neuron segmentation in volumetric electron microscopy datasets) or two-dimensional low resolution (whole cell segmentation of light microscopy images). The former requires consistently predictable boundaries to segment large structures, while the latter is boundary invariant but struggles with segmentation of large 3D objects without downscaling. Mitochondria in whole cell 3D EM datasets often occupy the challenging middle ground: large with ambiguous borders, limiting accuracy with existing tools. To rectify this, we have developedskeletonorientedobject segmentation (SKOOTS); a new segmentation approach which efficiently handles large, densely packed mitochondria. We show that SKOOTS can accurately, and efficiently, segment 3D mitochondria in previously difficult situations. Furthermore, we will release a new, manually annotated, 3D mitochondria segmentation dataset. Finally, we show this approach can be extended to segment objects in 3D light microscopy datasets. These results bridge the gap between existing segmentation approaches and increases the accessibility for three-dimensional biomedical image analysis.