bluuebunny/crossref_metadata_2025_split huggingface dataset:
Boundary updating as a source of history effect on decision uncertainty
Authors: Lee Heeseung , Lee Sang-Hun 
Published: March 2023

SUMMARYWhen sorting a sequence of stimuli into binary classes, current choices are often negatively correlated with recent stimulus history. This phenomenon—dubbed the repulsive bias—can be explained by boundary updating, a process of shifting the class boundary to previous stimuli. This explanation implies that recent stimulus history can also influence “decision uncertainty,” the probability of making incorrect decisions, since it depends on the location of the boundary. However, there have been no previous efforts to elucidate the impact of previous stimulus history on decision uncertainty. Here, from the boundary-updating process that accounts for the repulsive bias, we derived a prediction that decision uncertainty increases as current choices become more congruent with previous stimuli. We confirmed this prediction in behavioral, physiological, and neural correlates of decision uncertainty. Our work demonstrates that boundary updating offers a principled account of how previous stimulus history concurrently relates to choice bias and decision uncertainty.
OsNLP3/4-OsRFL module regulates nitrogen-promoted panicle architecture in rice
Authors: Wu Jie , Sun Liang-Qi , Zhang Zi-Sheng , Song Ying , Bai Yu , Wan Guang-Yu , Wang Jing-Xian , Xia Jin-Qiu , Zhang Zheng-Yi , Xiang Cheng-Bin 
Published: March 2023

AbstractRice panicles, a major component of yield, are regulated by phytohormones and nutrients. How mineral nutrients promote panicle architecture remains largely unknown. Here, we report that NIN-LIKE PROTEIN3 and 4 (OsNLP3/4) are crucial positive regulators of rice panicle architecture in response to nitrogen (N). Loss-of- function mutants of eitherOsNLP3orOsNLP4produced smaller panicles with reduced primary and secondary branches and fewer grains compared with wild type, whereas their overexpression plants showed the opposite phenotypes. Notably, the OsNLP3/4-regulated panicle architecture was positively correlated with N availability. OsNLP3/4 directly bind to the promoter ofOsRFLand activate its expression to promote inflorescence meristem development. Furthermore, OsRFL activatesOsMOC1expression by binding to its promoter. Our findings reveal the novel N- responsive OsNLP3/4-OsRFL-OsMOC1 module that integrates N availability to regulate panicle architecture, shedding light on how nutrient signals regulate panicle architecture and providing candidate targets for the improvement of crop yield.
Migration and establishment of progenitor pool of melanocytes is governed by SEMA3E-PLXND1 signaling
Authors: Subramaniam Yogaspoorthi , Sharma Babita , Aggarwal Ayush , Raja Desingu Ayyappa , Gupta Iti , Ghazi Madeeha , Sivasubbu Sridhar , Natarajan Vivek T 
Published: March 2023

AbstractVertebrate pigmentation is an outcome of an interplay of several signaling pathways that result in immense diversity of pigment patterns observed across the animal kingdom. Transitory nature of these signaling events impedes deciphering pathways that control migration and establishment of melanocyte stem cells (McSC), necessary for pigment patterning. Using zebrafish and cultured mammalian melanocytes, we uncover a hitherto unknown role for Plexin D1 signaling. This pathway directs migration by F-actin modulation and further dictates subsequent functional states of melanocytes through a transcriptional response. In zebrafish, abrogation of PLXND1 derails melanocyte migration and reduces mid-line melanophores emerging from the regeneration competent McSC pool. In cultured melanocytes, activation of PLXND1 by the ligand semaphorin 3E reduces the velocity of migration, influences directional correlation, and promotes movement towards positive cues such as SCF. PLXND1 activation results in EGFR signaling necessary for McSC establishment, and induces GNAS, an effector of MC1R pathway involved in melanocyte maturation. Identification of this long-range secreted negative chemotactic signaling provides a missing player and enriches reaction diffusion model for pigment patterning.
Early Detection of Lung Cancer in the NLST Dataset*
Authors: Mukherjee Pritam , Brezhneva Anna , Napel Sandy , Gevaert Olivier 
Published: March 2023

AbstractLung Cancer is the leading cause of cancer mortality in the U.S. The effectiveness of standard treatments, including surgery, chemotherapy or radiotherapy, depends on several factors like type and stage of cancer, with the survival rate being much worse for later cancer stages. The National Lung Screening Trial (NLST) established that patients screened using low-dose Computed Tomography (CT) had a 15 to 20 percent lower risk of dying from lung cancer than patients screened using chest X-rays. While CT excelled at detecting small early stage malignant nodules, a large proportion of patients (>25%) screened positive and only a small fraction (<10%) of these positive screens actually had or developed cancer in the subsequent years. We developed a model to distinguish between high and low risk patients among the positive screens, predicting the likelihood of having or developing lung cancer at the current time point or in subsequent years non-invasively, based on current and previous CT imaging data. However, most of the nodules in NLST are very small, and nodule segmentations or even precise locations are unavailable. Our model comprises two stages: the first stage is a neural network model trained on the Lung Image Database Consortium (LIDC-IDRI) cohort which detects nodules and assigns them malignancy scores. The second part of our model is a boosted tree which outputs a cancer probability for a patient based on the nodule information (location and malignancy score) predicted by the first stage. Our model, built on a subset of the NLST cohort (n= 1138) shows excellent performance, achieving an area under the receiver operating characteristics curve (ROC AUC) of 0.85 when predicting based on CT images from all three time points available in the NLST dataset.
A whole blood-based transcriptional risk score for nonobese type 2 diabetes predicts dynamic changes in glucose metabolic traits
Authors: Hou Yanan , Dai Huajie , Chen Na , Zhao Zhiyun , Wang Qi , Hou Tianzhichao , Zheng Jie , Wang Tiange , Li Mian , Lin Hong , Wang Shuangyuan , Zheng Ruizhi , Lu Jieli , Xu Yu , Chen Yuhong , Liu Ruixin , Ning Guang , Wang Weiqing , Bi Yufang , Wang Jiqiu , Xu Min 
Published: March 2023

AbstractBackgroundThe performance of peripheral blood transcriptional markers in evaluating the risk of type 2 diabetes (T2D) with normal weight is unknown. We developed a whole blood-based transcriptional risk score (wb-TRS) for nonobese T2D and assessed its contributions to disease risk and dynamic changes in glucose metabolism.Methods and findingsWe developed the wb-TRS in 1105 participants aged ≥40 years and in normal weight for up to 10 years from a well-defined community-based cohort with blood transcriptome data and validated it in an external dataset (253 overweight/obese participants from a dietary intervention trial with 3 repeated transcriptome data). Potential biology significance and causal inference were also explored. The wb-TRS included 144 transcripts. Compared to the lowest tertile, wb-TRS in tertile 3 associated with 8.68-folds (95% confidence interval [CI], 3.51-21.5), and each 1-unit increment associated with 2.57-folds (95% CI, 1.86-3.56) higher risk of nonobese T2D, after adjustments for traditional risk factors. Furthermore, baseline wb-TRS was significantly associated with dynamic changes in average, daytime, nighttime and 24h glucose and HbA1c, and area under the curve of glucose measured in the continuous glucose monitoring during 6-month of intervention. The wb-TRS improved the predicting performance for nonobese T2D in a model with fasting glucose, triglycerides and demographic and anthropometric parameters. Mitch analysis implicated oxidative phosphorylation, cholesterol metabolism and mTORC1 signaling involved in nonobese T2D pathogenesis. Transcriptome-wide Mendelian randomization supported causal effects of gene transcripts such as RAB1A and GCC1-PAX4 on nonobese T2D risk.ConclusionsA whole blood based nonobese T2D associated TRS was validated to predict dynamic changes in glucose metabolism. These findings also suggested several genes and biological pathways that might involve in the pathogenesis of nonobese T2D.
Sedentary time in adults with cystic fibrosis: A prospective observational cross-sectional study
Authors: Bishop Ines , Cobb Robyn , Hall Kathleen , Kuys Suzanne 
Published: March 2023

AbstractObjectiveAdults with cystic fibrosis remain susceptible to comorbidities associated with high sedentary time, increasing their risk of poor health outcomes. Evidence about sedentary time in adults with cystic fibrosis is limited. This study investigated sedentary time and physical activity in adults with cystic fibrosis across disease severity groups and the relationship with clinical measures.MethodsA SenseWear armband was worn by adults with cystic fibrosis, measuring sedentary time, time spent in moderate-vigorous physical activity and steps per day. Lung function, quadriceps strength, exercise capacity and health-related quality of life were assessed.ResultsOn average, the armband was worn for 20 hours (Standard Deviation (SD) 6) over 6 (SD 1) days. Forty-eight participants (28 males) spent 815 (SD 379) minutes sedentary, 137 (SD 13) minutes engaged in moderate-vigorous physical activity and took 5660 (SD 2749) steps per day. Sedentary time did not vary across disease severity groups nor correlate with clinical measures.ConclusionsAdults with cystic fibrosis spent a large proportion of time in sedentary behaviours, took insufficient steps, but conversely engaged in sufficient moderate-vigorous physical activity. Targeted interventions to break up sedentary time are required to reduce the risk of adverse health outcomes in this population.ImpactAdults with cystic fibrosis spend a large proportion of their time sedentary, placing them at risk of future metabolic disorders. Interventions to break up sedentary time are needed.
Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data
Authors: Mo Ziyi , Siepel Adam 
Published: March 2023

AbstractInvestigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does not adequately resemble data from the real world. Here, we show that this “simulation mis-specification” problem can be framed as a “domain adaptation” problem, where a model learned from one data distribution is applied to a dataset drawn from a different distribution. By applying an established domain-adaptation technique based on a gradient reversal layer (GRL), originally introduced for image classification, we show that the effects of simulation mis-specification can be substantially mitigated. We focus our analysis on two state-of-the-art deep-learning population genetic methods—SIA, which infers positive selection from features of the ancestral recombination graph (ARG), and ReLERNN, which infers recombination rates from genotype matrices. In the case of SIA, the domain adaptive framework also compensates for ARG inference error. Using thedomain-adaptive SIA (dadaSIA) model, we estimate improved selection coefficients at selected loci in the 1000 Genomes CEU population. We anticipate that domain adaptation will prove to be widely applicable in the growing use of supervised machine learning in population genetics.Author SummaryPopulation genetic simulation is a powerful tool in the study of evolution. A number of supervised machine learning methods have been developed that take advantage of inexpensive simulations as training data. Despite their outstanding performance in benchmarks, these models can fail when the simulated training data deviate from the real data. In this work, we employed domain adaptation techniques to address this “simulation mis-specification” problem by training the machine learning model jointly with simulated and real data. We performed extensive benchmark experiments to demonstrate the improvement of the domain-adaptive models over standard machine learning models in the presence of different types of mis-specification. In addition, we applieddadaSIA, a domain-adaptive selection inference model, to improve the estimates of selection coefficients at selected loci in a European population. The domain adaptation framework proposed in our work is widely applicable to models relying on synthetic training data and therefore opens the door to many more applications in population genetics.
Title: AKI and CKD Worsen Outcomes in Experimental Sepsis: Creating a Reverse-translational Model of Acute Peritoneal Infection and Recovery in an Immunocompromised Rodent
Authors: Floyd Deana F. , Colbert James T. , Furgeson Seth B. , Montford John R 
Published: March 2023

AbstractIntroductionInfection is a leading cause of morbidity and mortality in individuals with kidney disease. Both acute kidney injury (AKI), and chronic kidney disease (CKD) are clinical states that have been associated with higher risk of incident infection, and poor outcomes once infection has been established. A variety of host-and pathogen-specific factors are implicated as potential causes for these disparate outcomes including an altered host microbiome, innate and adaptive immune defects, and poor renal clearance and cytokines. However, there remains significant difficulty in modeling both human kidney disease and infection into an animal host. Likewise, there remains a poor understanding of the mechanisms underlying the unique immunodeficiency imparted by AKI and CKD, and if either condition imparts disparate risk.MethodsC57BL/6J mice were given vehicle or aristolochic acid (AA) to create AKI (control, AKI groups) or CKD (control, CKD groups). Donor mice from all four groups underwent sterile cecal dissection and creation of cecal slurry (CS) preparations, which was later injected into separate mice in a matched host-recipient manner, at either high or lower doses. Animals were clinically monitored for either 24- or 72-hours after inoculation, then euthanized. Animal survival, sepsis severity, temperature, weights, and transcutaneous glomerular filtration rate (tGFR) were tracked longitudinally throughout the study. Histology for kidney injury, peripheral blood flow cytometry for leukocyte counts, plasma cytokines, and typical markers for organ injury were determined.ResultsCompared to controls, animals with AKI experienced much more severe sepsis across virtually all tracked metrics, and no animals with AKI survived high-dose CS injection past 24-hours. AKI mice manifested with a peripheral defect in leukocytes early after sepsis, with severe and persistent cytopenias, and a dramatically heightened early pro-inflammatory cytokine response. Septic CKD mice also had worse outcomes than controls, though less severe, and occurring later than in animals with AKI. Interestingly, animals with AKI had worse clinical outcomes and evidence of organ injury than mice with CKD at any dose or time-point after inoculation, despite a higher mean baseline measured GFR.ConclusionsRodents with established AKI and CKD experience worse clinical outcomes and organ injury versus controls in a CS model intraperitoneal live-bacterial infection. Additionally, mice with AKI experienced earlier and more severe morbidity and mortality than animals with CKD.
A conserved pressure-driven mechanism for regulating cytosolic osmolarity
Authors: Velle Katrina B. , Garner Rikki M. , Beckford Tatihana K. , Weeda Makaela , Liu Chunzi , Kennard Andrew S. , Edwards Marc , Fritz-Laylin Lillian K. 
Published: March 2023

ABSTRACTControlling intracellular osmolarity is essential to all cellular life. Cells that live in hypo-osmotic environments like freshwater must constantly battle water influx to avoid swelling until they burst. Many eukaryotic cells use contractile vacuoles to collect excess water from the cytosol and pump it out of the cell. Although contractile vacuoles are essential to many species, including important pathogens, the mechanisms that control their dynamics remain unclear. To identify basic principles governing contractile vacuole function, we here investigate the molecular mechanisms of two species with distinct vacuolar morphologies from different eukaryotic lineages—the discobanNaegleria gruberi, and the amoebozoan slime moldDictyostelium discoideum. Using quantitative cell biology we find that, although these species respond differently to osmotic challenges, they both use actin for osmoregulation, as well as vacuolar-type proton pumps for filling contractile vacuoles. We also use analytical modeling to show that cytoplasmic pressure is sufficient to drive water out of contractile vacuoles in these species, similar to findings from the alveolateParamecium multimicronucleatum. Because these three lineages diverged well over a billion years ago, we propose that this represents an ancient eukaryotic mechanism of osmoregulation.
Batch Action PoTential Analyser (BAPTA): an open source tool for automated high throughput analysis of cardiac action potentials
Authors: Leonov Vladislav , Torre Eleonora , Ronchi Carlotta , Crotti Lia , Schwartz Peter J , Rocchetti Marcella , Zaza Antonio , Sala Luca 
Published: March 2023

AbstractThe cardiac action potential (AP) is a key species-specific feature of cardiomyocytes that occurs in response to coordinated actions of ion channels. It represents the first step of the cardiac excitation-contraction coupling and it is crucial for cardiomyocyte (CM) physiology. Changes in the cardiac AP may primarily occur as a consequence of diseases or as a direct or unwanted response to drugs. Our ability to quantify these changes defines the reliability of our measurements and its throughput.Cardiac AP parameters are often quantified through manual time-consuming data analysis protocols or custom-made and proprietary data analysis pipelines; to the best of our knowledge, no tools are currently available for automated cardiac AP analysis and AP parameter quantification.Here we introduce a free and open source software tool named Batch Action PoTential Analyser (BAPTA), written in the R language, designed to i) overcome the inherent operator-dependent bias on trace selection affecting reproducibility, ii) vastly improve the throughput of the analyses of large datasets and iii) analyse both spontaneous and triggered APs from CMs of multiple species and origin.We present here four use-cases in which BAPTA can be used at high throughput to investigate the effects of: 1) a disease (cardiomyopathy) on rat CMs, 2) drugs on mouse pacemaker cells, 3) rate-dependency of AP duration in guinea pig CMs and 4) metabolic electrophysiological maturation in human stem-cell-derived CMs. Overall, BAPTA consistently provides faster, more reproducible and scalable readouts which excellently correlate with manual analyses performed by experienced electrophysiologists.
A genetic variation in the adenosine A2A receptor gene contributes to variability in oscillatory alpha power in wake and sleep EEG and A1adenosine receptor availability in the human brain
Authors: Tichelman Naemi L. , Foerges Anna L. , Elmenhorst Eva-Maria , Lange Denise , Hennecke Eva , Baur Diego M. , Beer Simone , Kroll Tina , Neumaier Bernd , Bauer Andreas , Landolt Hans-Peter , Aeschbach Daniel , Elmenhorst David 
Published: March 2023

AbstractThe EEG alpha rhythm (8-13 Hz) is one of the most salient human brain activity rhythms. Spectral power in the alpha range in wakefulness and sleep varies among individuals based on genetical predisposition, yet knowledge about the underlying genes is scarce. The EEG alpha oscillations are related to cerebral energy metabolism and modulated by the level of attention and vigilance. The neuromodulator adenosine is directly linked to energy metabolism as product of adenosine tri-phosphate (ATP) breakdown and acts as a sleep promoting molecule by activitating A1and A2Aadenosine receptors. We quantified EEG oscillatory alpha power in wakefulness and sleep, as well as A1adenosine receptor availability by positron emission tomography with18F-CPFPX, in a large sample of healthy volunteers carrying different alleles of gene variant rs5751876 ofADORA2Aencoding A2Aadenosine receptors. Oscillatory alpha power was higher in homozygous C-allele carriers (n = 27, 11 females) compared to heterozygous and homozygous carriers of the T-allele (n(C/T) = 23, n(T/T) = 5, 13 females) (F(18,37)= 2.35, p = 0.014, Wilk’s Λ = 0.467). Across considered brain regions an effect ofADORA2Agenotype on A1adenosine receptor binding potential was found (F(18,40)= 2.62, p = 0.006, Wilk’s Λ = 0.459) and after correction for multiple testing this effect was shown to be significant for circumscribed occipital region of calcarine fissures.A correlation between individual differences in oscillatory alpha power and adenosine receptor availability was found for the subgroup of female participants only. In conclusion: a genetic variation in the adenosinergic system affects individual alpha power, although a direct modulatory effect via the A1AR has been demonstrated for females only.
Temporal single-cell transcriptomic analysis of thesox1a:eGFPtransgenic line identified the lateral floor plate progenitor cells as the origin of intraspinal serotonergic neurons
Authors: Chen Fushun , Köhler Melina , Cucun Gokhan , Takamiya Masanari , Kizil Caghan , Cosacak Mehmet Ilyas , Rastegar Sepand 
Published: March 2023

AbstractThe Sox family of transcription factors plays a crucial role in the development of the vertebrate nervous system. In the zebrafish embryo,sox1genes are expressed in neural progenitor cells and neurons of the ventral spinal cord. We recently reported that the loss of function ofsox1aandsox1bleads to a significant decline in a subtype of V2 neurons, called V2s, in zebrafish. Here, a single-cell RNA sequencing approach was used to analyse the transcriptome ofsox1alineage progenitors and neurons in the zebrafish spinal cord at four different time points during the first five days of embryonic development, using the Tg(sox1a:eGFP) line. In addition to the previously describedsox1a-expressing neurons, we found thatsox1ais also expressed in late-developing intraspinal serotonergic neurons (ISNs). Analysis of developmental trajectories from single-cell data and depletion of lateral floor plate (LFP) cells bynkx2.9morpholino knockdown suggest that ISNs arise from LFP precursor cells. Pharmacological inhibition of the Notch signalling pathway indicates that this pathway is required for the negative regulation of the development of LFP progenitor cells into ISN populations. Our results show that the zebrafish LFP is a precursor domain that longitudinally gives rise to ISNs in addition to the previously described KA” and V3 interneurons.