bluuebunny/crossref_metadata_2025_split huggingface dataset:
A highly conserved A-to-I RNA editing event within the glutamate-gated chloride channel GluClα is necessary for olfactory-based behaviors inDrosophila
Authors: Zak Hila , Rosenfeld Eyal , Deng Tricia , Gorelick David , Israel Shai , Levi Mali , Paas Yoav , Li Jin Billy , Parnas Moshe , Shohat-Ophir Galit 
Published: May 2023

AbstractA-to-I RNA editing is an important cellular process that modifies genomically encoded information during transcription, to generate various RNA isoforms from a single DNA sequence. It involves the conversion of specific adenosines in the RNA sequence to inosines by ADAR proteins, resulting in their recognition as guanosines by cellular machinery, and as such plays a vital role in neuronal and immune functions. Given the widespread occurrence of A-to-I RNA editing events across the animal kingdom, with thousands to millions of editing sites found in the transcriptomes of organisms such as flies and humans, identifying the critical sites and understanding theirin-vivofunctions remains a challenging task. Here we show for the first time the physiological importance of a single editing site, found within the extracellular domain of the glutamate-gated chloride channel (GluClα), and bridge the gap between its evolutionary conservation acrossDrosophilaspecies and its function in shaping the behavior of adult flies. We used genomic editing to ablate editing at this specific site, such that the endogenous channel harbors only the unedited version and used a battery of behavioral paradigms to analyze the effects on various features of adult behavior. We provide evidence thatGluClαuneditedflies exhibit reduced olfactory responses to both appetitive and aversive odors, as well as impaired pheromone-dependent social interactions, and that editing of this site is required for proper processing of olfactory information in olfactory projection neurons. Our findings demonstrate that evolutionary conservation is a useful criterion to pinpoint which of the many editing events has the potential of having a function and pave the path for dissecting the link between RNA modification, neuronal physiology, and behavior.
Using the visual cliff and pole descent assays to detect binocular disruption in mice
Authors: De Jesús-Cortés Héctor , Cramer Teresa L.M. , Bowen Daniel A. , Reilly-Andújar Francis , Lu Sophie , Gaier Eric D. , Bear Mark F. 
Published: May 2023

AbstractAmblyopia, a neurodevelopmental visual disorder characterized by impaired stereoacuity, is commonly modeled in animals using monocular deprivation (MD) during a critical period of visual development. Despite extensive research at the synaptic, cellular and circuit levels of analysis, reliable behavioral assays to study stereoscopic deficits in mice are limited. This study aimed to characterize the Visual Cliff Assay (VCA) and the Pole Descent Cliff Task (PDCT) in mice, and to evaluate their utility in detecting binocular dysfunction. Using these assays, we investigated the impact of clinically relevant manipulations of binocular vision, including monocular occlusion, pupillary dilation, and amblyopia induced by long-term MD. Our findings reveal that optimal performance in both the VCA and PDCT are dependent on balanced binocular input. However, deficits after MD in the VCA exhibited relatively small effect sizes (7-14%), requiring large sample sizes for statistical comparisons. In contrast, the PDCT demonstrated larger effect sizes (43-61%), allowing for reliable detection of binocular dysfunction with a smaller sample size. Both assays were validated using multiple monocular manipulations relevant to clinical paradigms, with the PDCT emerging as the preferred assay for detecting deficits in stereoscopic depth perception in mice. These findings provide a robust framework for using the VCA and PDCT in mechanistic and therapeutic studies in mice, offering insights into the neural mechanisms of binocular vision and potential interventions for amblyopia
ABCB1 overexpression through locus amplification represents an actionable target to combat paclitaxel resistance in pancreatic cancer cells
Authors: Bergonzini Cecilia , Gregori Alessandro , Hagens Tessa M.S. , van der Noord Vera E. , van de Water Bob , Zweemer Annelien J.M. , Capula Mjriam , Mantini Giulia , Botto Asia , Finamore Francesco , Garajova Ingrid , McDonnell Liam A. , Schmidt Thomas , Giovannetti Elisa , Danen Erik H.J. 
Published: May 2023

ABSTRACTAimsChemotherapies such as gemcitabine/nab-paclitaxel are confronted with intrinsic or acquired resistance in pancreatic ductal adenocarcinoma (PDAC). We aimed to identify novel actionable mechanisms to overcome such resistance.MethodsThree paclitaxel (PR) and gemcitabine resistant (GR) PDAC models were established. Transcriptomics and proteomics were used to identify conserved mechanisms of drug resistance. Genetic and pharmacological approaches were used to overcome paclitaxel resistance.ResultsUpregulation of ABCB1 through locus amplification was identified as a conserved feature unique to PR cells. ABCB1 was not affected in any of the GR models and no cross resistance was observed. The ABCB1 inhibitor verapamil or siRNA mediated ABCB1 depletion sensitized PR cells to paclitaxel and prevented efflux of ABCB1 substrates in all models. ABCB1 expression was detected in PDAC patients that had received gemcitabine/nab-paclitaxel treatment. A pharmacological screen identified known and novel kinase inhibitors that attenuate efflux of ABCB1 substrates and sensitize PR PDAC cells to paclitaxel.ConclusionUpregulation of ABCB1 through locus amplification represents a novel, conserved mechanism of PDAC paclitaxel resistance. ABCB1 has not been previously implicated in PR PDAC. The synthetic lethal interactions identified in this study can be further (pre)clinically explored as therapeutic strategies to overcome paclitaxel resistance in PDAC.
Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels
Authors: Shi Mingyang , Tanikawa Chizu , Munter Hans Markus , Akiyama Masato , Koyama Satoshi , Tomizuka Kohei , Matsuda Koichi , Lathrop Gregory Mark , Terao Chikashi , Koido Masaru , Kamatani Yoichiro 
Published: May 2023

AbstractLarge-scale imputation reference panels are now available and have contributed to efficient genome-wide association studies through genotype imputation. However, it is still under debate whether large-size multi-ancestry or small-size population-specific reference panels are the optimal choices for under-represented populations. We imputed genotypes of East Asian (EAS; 180k Japanese) subjects using the Trans-Omics for Precision Medicine (TOPMed) reference panel and found that the standard imputation quality metric (Rsq) substantially overestimated the dosage r2(squared correlation between imputed dosage and true genotype). Variance component analysis of Rsq revealed that the increased imputed-genotype certainty (dosages closer to 0, 1, or 2) caused upward bias, indicating some systemic bias in the imputation. Through systematic simulations using different template switching rates (θ value) in the hidden Markov model, we uncovered that the lower θ value increased the imputed-genotype certainty and Rsq; however, dosage r2was insensitive to the θ value, thereby causing a deviation. In simulated reference panels with different sizes and ancestral diversities, the θ value estimates from Minimac decreased with the size of a single ancestry and increased with the ancestral diversity. Thus, Rsq could overestimate or underestimate dosage r2for a subpopulation in the multi-ancestry panel and the deviation represents different imputed-dosage distributions. Finally, despite the impact of θ value, distant ancestries in the reference panel contributed only a few additional variants passing a predefined Rsq threshold. We conclude that the θ value has a substantial impact on the imputed dosage and the imputation quality metric value.
Network depth affects inference of gene sets from bacterial transcriptomes using denoising autoencoders
Authors: Kion-Crosby Willow , Barquist Lars 
Published: May 2023

AbstractThe increasing number of publicly available bacterial gene expression data sets provides an unprecedented resource for the study of gene regulation in diverse conditions, but emphasizes the need for self-supervised methods for the automated generation of new hypotheses. One approach for inferring coordinated regulation from bacterial expression data is through the use of neural networks known as denoising autoencoders (DAEs), which encode large datasets in a reduced bottleneck layer. We have generalized this application of DAEs to include deep networks and explore the effects of network architecture on gene set inference using deep learning. We developed a DAE-based pipeline to extract gene sets from a large compendium of transcriptomic data inEscherichia coli, independently of the DAE network parameters and architecture. We validate our method by identifying many of the inferred gene sets with known pathways inE. coli, and have subsequently used this pipeline to explore how the choice of network architecture impacts gene sets recovery. We find that increasing network depth leads the DAEs to explain gene expression in terms of fewer, more concisely defined gene sets, and that adjusting the network compression results in a trade-off between generalizability and overall biological inference. Finally, leveraging our understanding of the impact of DAE architecture choices on gene set inference, we apply our pipeline to an independent uropathogenicE. colidataset collected directly from infected patients to identify genes which are uniquely induced during human colonization.
VEGF-C promotes brain-derived fluid drainage, confers neuroprotection, and improves stroke outcomes
Authors: Simoes Braga Boisserand Ligia , Bouchart Jean , Geraldo Luiz Henrique , Lee Seyoung , Sanganahalli Basavaraju G. , Parent Maxime , Zhang Shenqi , Xue Yuechuan , Skarica Mario , Guegan Justine , Li Mingfeng , Liu Xiodan , Poulet Mathilde , Askanase Michael , Osherov Artem , Spajer Myriam , Kamouh Marie-Renee El , Eichmann Anne , Alitalo Kari , Zhou Jiangbing , Sestan Nenad , Sansing Lauren H. , Benveniste Helene , Hyder Fahmeed , Thomas Jean-Leon 
Published: May 2023

AbstractMeningeal lymphatic vessels promote tissue clearance and immune surveillance in the central nervous system (CNS). Vascular endothelium growth factor-C (VEGF-C) is essential for meningeal lymphatic development and maintenance and has therapeutic potential for treating neurological disorders, including ischemic stroke. We have investigated the effects of VEGF-C overexpression on brain fluid drainage, single cell transcriptome in the brain, and stroke outcomes in adult mice. Intra-cerebrospinal fluid administration of an adeno-associated virus expressing VEGF-C (AAV-VEGF-C) increases the CNS lymphatic network. Post-contrast T1 mapping of the head and neck showed that deep cervical lymph node size and drainage of CNS-derived fluids were increased. Single nuclei RNA sequencing revealed a neuro-supportive role of VEGF-C via upregulation of calcium and brain-derived neurotrophic factor (BDNF) signaling pathways in brain cells. In a mouse model of ischemic stroke, AAV-VEGF-C pretreatment reduced stroke injury and ameliorated motor performances in the subacute stage. AAV-VEGF-C thus promotes CNS-derived fluid and solute drainage, confers neuroprotection, and reduces ischemic stroke damage.Short abstractIntrathecal delivery of VEGF-C increases the lymphatic drainage of brain-derived fluids confers neuroprotection, and improves neurological outcomes after ischemic stroke.
Species composition determines bioplastics production in photosynthetic microbiomes: strategy to enrich cyanobacteria PHB-producers
Authors: Altamira-Algarra Beatriz , Lage Artai , García Joan , Gonzalez-Flo Eva 
Published: May 2023

AbstractThe aim of this study was to set the operating mode in regards to nutrients, temperature and light to use as a strategy to enrich a microbiome rich in cyanobacteria in polyhidroxybutyrate (PHB)-producers in order to enhance this biopolymer production. Alternate growth and accumulation phases were conducted for 179 days in a 3 L photobioreactor. Although, presence of green microalgae potentially reduced PHB production, the microbiome produced up to 22 % dry cell weight (dcw) PHB. Results suggested that this methodology could be applied to a robust microbiome rich in cyanobacteria to boost PHB production.
Dietary fiber induces a fat preference associated with the gut microbiota
Authors: Liow Yijia , Kamimura Itsuka , Masahiro Umezaki , Suda Wataru , Takayasu Lena 
Published: May 2023

AbstractEating behavior is essential to human health. However, whether future eating behavior is subjected to the conditioning of precedent dietary composition is unknown. This study aimed to investigate the effect of dietary fiber consumption on subsequent nutrient-specific food preferences between palatable high-fat and high-sugar diets and explore its correlation with the gut microbiota. C57BL/6NJcl male mice were subjected to a 2-week dietary intervention and fed either a control (n = 6) or inulin (n = 6) diet. Afterwards, all mice were subjected to a 3-day eating behavioral test to self-select a high-fat or a high-sugar diet. The test diet feed intakes were recorded, and the mice’s fecal samples were analyzed to evaluate the gut microbiota composition. The inulin mice exhibited a preference for a high-fat diet over a high-sugar diet, associated with distinct gut microbiota compositions profiles between the inulin and control mice. The gut microbiotaBacteroides acidifaciens(99.68%),Bacteroides caecemuris(99.37%), andBacteroides xylanolyticus(92.28%) positively correlated with a preference for fat. Further studies involving fecal microbiota transplantation and eating behavior-related neurotransmitter analyses may clarify the role of gut microbiota on food preferences. Food preferences induced by dietary intervention are a novel observation, and the gut microbiome may be significantly associated with this preference.
The appearance ofsugImixed loci in three individuals during treatment for MDR-TB, supports the involvement ofsugIinMycobacterium tuberculosisd-cycloserine resistancein vivo
Authors: Anthony R.M , Molemans M. , Akkerman O. , Sturkenboom M.G.G. , Mulder A. , de Zwaan R. , van Soolingen D. , Alffenaar J. , van Leth F.C.M. , Ghimire S. , Yatskevich N. , Skrahina A. , Ciobanu N. , Turcan N. , Crudu V. 
Published: May 2023

AbstractTo study the adaptation of multi-drug resistantMycobacterium tuberculosis(MDR-TB) during treatment patients diagnosed with MDR-TB were recruited into an observational study. Clinical data andM. tuberculosisDNA at diagnosis and between seven days and two months of MDR-TB treatment were collected. The drugs prescribed were recorded. Interpretable WGS data from 118 isolates from 54 participants was obtained (11 in Belarus and 43 in Moldova) and screened for the presence of unfixed single nucleotide polymorphisms (mixed SNPs / loci).This study was performed shortly after the publication of the 2019 WHO consolidated guidelines on drug-resistant tuberculosis treatment. Existing drug supplies and procurement in one country after the switch to the all oral MDR-TB regimen in addition to patient factors, influenced the selection of and exposure to drugs.Confidently mixed SNPs were identified in samples from multiple participants in only five genes (gyrA, pncA, Rv1129c, Rv1148c, andsugI). All other genes with confidently mixed SNPs were identified in isolates from only a single individual. A significant proportion of the participants (52 of 54 participants) received d-cycloserine as part of their initial treatment, most participants who initially received d-cycloserine did not receive bedaquiline in their initial regimen (all at one site). Three different mixed SNPs were identified insugIgene from a follow up isolate from three participants (P7A, P7T, and Q6stop). Mutations insugIhave previously been reported in spontaneousin vitrod-cycloserine resistant mutants. Alterations in thesugIgene may indicate a sub optimal d-cycloserine containing regimen and potentially be of clinical significance with respect to adaptation to d-cycloserine. Monitoring the accumulation of low frequency escape mutants may help identify regimens insufficiently powerful to block the accumulation of antimicrobial resistance mutants and identify drug(s) at risk of resistance selection.
Transcription Factor EB (TFEB) activity increases resistance of TNBC stem cells to metabolic stress
Authors: Soleimani Milad , Goyal Ria , Somma Alexander , Kaoud Tamer S. , Dalby Kevin N. , Kowalski Jeanne , Eckhardt S. Gail , Berg Carla L. Van Den 
Published: May 2023

ABSTRACTBreast Cancer Stem Cells (CSCs) are difficult to therapeutically target, but continued efforts are critical given their contribution to tumor heterogeneity and treatment resistance in Triple-Negative Breast Cancer (TNBC). CSC properties are influenced by metabolic stress, but specific mechanisms are lacking for effective drug intervention. Our previous work on TFEB suggested a key function in CSC metabolism. Indeed, TFEB knockdown (KD) inhibited mammosphere formationin vitroand tumor initiation/growthin vivo. These phenotypic effects were accompanied by a decline in CD44high/CD24lowcells. Glycolysis inhibitor 2-deoxy-D-glucose (2-DG) induced TFEB nuclear translocation, indicative of TFEB transcriptional activity. TFEB KD blunted, whereas TFEB (S142A) augmented 2-DG-driven UPR mediators, notably BiP/HSPA5 and CHOP. Like TFEB KD, silencing BiP/HSPA5 inhibited CSC self-renewal, suggesting that TFEB augments UPR-related survival. Further studies showed that TFEB KD attenuated 2-DG-directed autophagy, suggesting a mechanism whereby TFEB protects CSCs against 2-DG-induced stress. Our data indicate that TFEB modulates CSC metabolic stress response via autophagy and UPR. These findings reveal the novel role of TFEB in regulating CSCs during metabolic stress in TNBC.Financial SupportThis work was supported by CPRIT Grant RR160093 (to S.G. Eckhardt), CPRIT Grant RP210088 (to K.N. Dalby), UT College of Pharmacy Non-discretionary Funds (to C. Van Den Berg), and UT Graduate Continuing Fellowship (to M. Soleimani).
Organic food purchases: does green trust play a part?
Authors: Rashid Irfana , Lone Aashiq Hussain 
Published: May 2023

PurposeOrganic food consumption has received great attention due to the increase in consumer environmental and health concerns. This study intends to analyse how customers' green purchasing intentions for organic food are affected by internal factors of attitude and health consciousness and external factors of social norms and environmental concern, as well as how green trust operates as a moderator between green purchase intention and actual purchase.Design/methodology/approachA quantitative research methodology was employed in this study. The data (n = 323) were gathered via a self-administered questionnaire. The respondents, who were current purchasers of organic food, were chosen through a purposive sampling technique. Data were analysed using exploratory factor analysis and structural equation modelling with the aid of IBM SPSS 25.0 and AMOS 25.FindingsThe results reveal that customers' green purchase intention for organic products is positively influenced by internal factors (attitude and health consciousness) and external factors (social norms and environmental concern). This study also shows the moderating effect of green trust on intention and action, demonstrating the necessity of building green trust among customers to diminish green purchasing inconsistency.Practical implicationsThe study's results have ramifications for producers of organic goods, merchants and market oversight organizations. Establishing a viable strategy while considering customers' concerns about health and the environment is necessary. The formulated strategy must target specific customer niches, therefore strengthening customers' trust in and understanding of organic food items, which will in turn diminish green purchasing inconsistency in the organic industry.Originality/valueThis study contributes to the existing literature by extending the Theory of Planned Behaviour model to organic food consumption and by visualizing how various factors (internal, external and green trust) affect a consumer's inclination to make organic food purchases. The authors added to the empirical evidence that green trust plays a crucial role in stimulating green buying intentions into behaviour and ultimately diminishing green purchasing inconsistency.
The role of Industry 4.0 on supply chain cost and supply chain flexibility
Authors: Erboz Gizem , Yumurtacı Hüseyinoğlu Işık Özge 
Published: May 2023

PurposeIndustry 4.0 accelerates the performance of supply chains, in particular, the reduction in supply chain cost (SCC) and improvement in supply chain flexibility (SCF). The aim of this study is to examine the role of Industry 4.0 on SCC and SCF, using network theory to explain the interrelationships.Design/methodology/approachData were collected from 182 manufacturing firms in Turkey. The partial least square structural equation modelling (PLS-SEM) was employed in testing the research hypotheses.FindingsThe results showed that Industry 4.0 positively affects SCC; however, no direct relationship was found between Industry 4.0 and SCF. Moreover, SCC was found to have a positive impact on SCF, while SCC was found to mediate the relationship between Industry 4.0 and SCF. An additional finding was that customer integration (CI) moderates the relationship between Industry 4.0 and SCC; however, CI does not moderate the relationship between Industry 4.0 and SCF.Practical implicationsThe research validates the role of Industry 4.0 on supply chain processes and thus provides valuable insights into supply chain practitioners and decision-makers interested in Industry 4.0 for supply chain management.Originality/valueIn view of the limited number of studies, this study empirically contributes to the literature on the relationships among Industry 4.0, SCC, SCF and CI.
Tracking indoor construction progress by deep-learning-based analysis of site surveillance video
Authors: Wong Johnny Kwok Wai , Bameri Fateme , Ahmadian Fard Fini Alireza , Maghrebi Mojtaba 
Published: May 2023

Purpose
Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

Design/methodology/approach
A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

Findings
The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

Originality/value
The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.