bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influenza Virus Genomic Surveillance, Arizona, USA, 2023-2024
Authors: Maqsood Rabia , Smith Matthew F. , Holland LaRinda A. , Sullins Regan A. , Holland Steven. C. , Tan Michelle , Hernandez Barrera Gabrielle M. , Thomas Alexis W. , Islas Mario , Kramer Joanna L. , Nordstrom Lora , Mulrow Mary , White Michael , Murugan Vel , Lim Efrem S. 
Published: February 2024

AbstractWe conducted genomic sequencing of 110 influenza A and 30 influenza B viruses from specimens collected between October 2023 and February 2024 in Arizona, USA. We identified mutations in the hemagglutinin (HA) antigenic sites. Real-time genomic surveillance is important to ensure influenza vaccine effectiveness.
Reconsider photoplethysmogram signal quality assessment in the free living environment
Authors: Su Yan-Wei , Hao Chia-Cheng , Liu Gi-Ren , Sheu Yuan-Chung , Wu Hau-Tieng 
Published: February 2024

AbstractBackgroundAssessing signal quality is crucial for biomedical signal processing, yet a precise mathematical model for defining signal quality is often lacking, posing challenges for experts in labeling signal qualities. The situation is even worse in the free living environment.MethodWe propose to model a PPG signal by the adaptive non-harmonic model (ANHM) and apply a decomposition algorithm to explore its structure, based on which we advocate a reconsideration of the concept of signal quality.ResultWe demonstrate the necessity of this reconsideration and highlight the relationship between signal quality and signal decomposition with examples recorded from the free living environment. We also demonstrate that relying on mean and instantaneous heart rates derived from PPG signals labeled as high quality by experts without proper reconsideration might be problematic.ConclusionA new method, distinct from visually inspecting the raw PPG signal to assess its quality, is needed. Our proposed ANHM model, combined with advanced signal processing tools, shows potential for establishing a systematic signal decomposition based signal quality assessment model.
A targetable PREX2/RAC1/PI3Kβ signalling axis confers resistance to clinically relevant therapeutic approaches in melanoma
Authors: Ford Catriona A. , Koludrovic Dana , Centeno Patricia P. , Foth Mona , Tsonou Elpida , Vlahov Nikola , Sphyris Nathalie , Gilroy Kathryn , Bull Courtney , Nixon Colin , Serrels Bryan , Munro Alison F. , Dawson John C. , Carragher Neil O. , Pavet Valeria , Hornigold David C. , Dunne Philip D. , Downward Julian , Welch Heidi C. E. , Barry Simon T. , Sansom Owen J. , Campbell Andrew D. 
Published: February 2024

AbstractMetastatic melanoma remains a major clinical challenge. Large-scale genomic sequencing of melanoma has identifiedbona fideactivating mutations inRAC1, with mutations of its upstream regulator, the RAC-GEFPREX2, also commonly detected. Crucially,RAC1mutations are associated with resistance to BRAF-targeting therapies. Despite the role of its homologue PREX1 in melanomagenesis, and evidence that some truncatingPREX2mutations drive increased RAC1 activity, no hotspot mutations have been identified, and the impact ofPREX2mutation remains contentious. Here, we use genetically engineered mouse models and patient-derived BRAFV600E-driven melanoma cell lines to dissect the role of PREX2 in melanomagenesis and response to therapy. We show that while PREX2 is dispensable for the initiation and progression of melanoma, its loss confers sensitivity to clinically relevant therapeutics. Importantly, genetic and pharmacological targeting of the RAC1 effector kinase PI3Kβ phenocopiesPREX2loss, sensitizing our model systems to therapy. Our data reveal a druggable PREX2/RAC1/PI3Kβ signalling axis inBRAF-mutant melanoma that could be exploited clinically.Statement of SignificanceMetastatic melanoma remains both a clinical problem, and an opportunity for therapeutic benefit. Co-targeting of the MAPK pathway and the PREX2/RAC1/PI3Kβ has remarkable efficacy and outperforms monotherapy MAPK targetingin vivo.
Proteomic Analysis of Urine from Youths Indulging in Gaming
Authors: Yang Minhui , Liu Yuqing , Shen Ziyun , Wang Haitong , Gao Youhe 
Published: February 2024

AbstractVideo game addiction manifests as an escalating enthusiasm and uncontrolled use of digital games, yet there are no objective indicators for gaming addiction. This study employed mass spectrometry proteomics to analyze the proteomic differences in the urine of adolescents addicted to gaming compared to those who do not play video games. The study included 10 adolescents addicted to gaming and 9 non-gaming adolescents as a control group. The results showed that there were 125 significantly different proteins between the two groups. Among these, 11 proteins have been reported to change in the body after the intake of psychotropic drugs and are associated with addiction: Calmodulin, ATP synthase subunit alpha, ATP synthase subunit beta, Acid ceramidase, Tomoregulin-2, Calcitonin, Apolipoprotein E, Glyceraldehyde-3-phosphate dehydrogenase, Heat shock protein beta-1, CD63 antigen, Ephrin type-B receptor 4, Tomoregulin-2. Additionally, several proteins were found to interact with pathways related to addiction: Dickkopf-related protein 3, Nicastrin, Leucine-rich repeat neuronal protein 4, Cerebellin-4. Enriched biological pathways discovered include those related to nitric oxide synthase, amphetamine addiction, and numerous calcium ion pathways, all of which are associated with addiction. Moreover, through the analysis of differentially expressed proteins, we speculated about some proteins not yet fully studied, which might play a significant role in the mechanisms of addiction: Protein kinase C and casein kinase substrate in neurons protein, Cysteine-rich motor neuron 1 protein, Bone morphogenetic protein receptor type-2, Immunoglobulin superfamily member 8. In the analysis of urinary proteins in adolescents addicted to online gaming, we identified several proteins that have previously been reported in studies of drug addiction.
Decoding the spatiotemporal dynamic neural representation of repetitive facial expression imitation
Authors: Liu Qi , Zhou Xinqi , Zhu Siyu , Liu Can , Yang Yanmiao , Lan Chunmei , Song Xinwei , Becker Benjamin , Kendrick Keith M. , Zhao Weihua 
Published: February 2024

AbstractImitating facial emotion expressions can facilitate social interactions, although the behavioral and neural spatiotemporal dynamics is unclear. Here participants (N=100) imitated facial emotions repeatedly over one month (16 times in total) with neural activity measured on three occasions using functional near-infrared spectroscopy. Additionally, the transfer effect of repeated imitation on emotional face and scene perception was assessed by fMRI with multivariate pattern analysis. Valence specific imitation performance was facilitated by the alterations in the similarity of spatiotemporal patterns evoked in the mirror neuron system (MNS) with information flow moving progressively towards the inferior frontal gyrus as the as the number of times of imitation increase. Furthermore, MNS representation predictive patterns of processing emotional faces, but not scenes, were enhanced. Overall, these findings provide a neural changes of information flow within MNS and advance our understanding of the spatiotemporal dynamics from novice to proficient of facial emotion imitation.
Selection of movement rules to simulate species dispersal in a mosaic landscape model
Authors: Gold Susannah , Croft Simon , Budgey Richard , Aegerter James 
Published: February 2024

AbstractDispersal is an ecological process central to population dynamics, representing an important driver of movement between populations and across landscapes. In spatial population models for terrestrial vertebrates, capturing plausible dispersal behaviour is of particular importance when considering the spread of disease or invasive species. The distribution of distances travelled by dispersers, or the dispersal kernel, is typically highly skewed, with most individuals remaining close to their origin but some travelling substantially further. Using mechanistic models to simulate individual dispersal behaviour, the dispersal kernel can be generated as an emergent property. Through stepwise simulation of the entire movement path, models can also account for the influence of the local environment, and contacts during the dispersal event which may spread disease. In this study, we explore a range of simple rules to emulate individual dispersal behaviour within a mosaic model generated using irregular geometry. Movement rules illustrate a limited range of behavioural assumptions and when applied across these simple synthetic landscapes generated a wide range of emergent kernels. Given the variability in dispersal distances observed within species, our results highlight the importance of considering landscape heterogeneity and individual-level variation in movement, with simpler rules approximating random walks providing less plausible emergent kernels. As a case study, we demonstrate how rule sets can be selected by comparison to an empirical kernel for a study species (red fox;Vulpes vulpes). These results provide a foundation for the selection of movement rules to represent dispersal in spatial agent-based models, however, we also emphasise the need to corroborate rules against the behaviour of specific species and within chosen landscapes to avoid the potential for these rules to bias predictions.
The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality
Authors: Srinivasan Keshav , Ribeiro Tiago L. , Kells Patrick , Plenz Dietmar 
Published: February 2024

AbstractScaling relationships are key in characterizing complex systems at criticality. In the brain, they are evident in neuronal avalanches—scale-invariant cascades of neuronal activity quantified by power laws. Avalanches manifest at the cellular level as cascades of neuronal groups that fire action potentials simultaneously. Such spatiotemporal synchronization is vital to theories on brain function yet avalanche synchronization is often underestimated when only a fraction of neurons is observed. Here, we investigate biases from fractional sampling within a balanced network of excitatory and inhibitory neurons with all-to-all connectivity and critical branching process dynamics. We focus on how mean avalanche size scales with avalanche duration. For parabolic avalanches, this scaling is quadratic, quantified by the scaling exponent,χ= 2, reflecting rapid spatial expansion of simultaneous neuronal firing over short durations. However, in networks sampled fractionally,χis significantly lower. We demonstrate that applying temporal coarse-graining and increasing a minimum threshold for coincident firing restoresχ= 2, even when as few as 0.1% of neurons are sampled. This correction crucially depends on the network being critical and fails for near sub- and supercritical branching dynamics. Using cellular 2-photon imaging, our approach robustly identifiesχ= 2 over a wide parameter regime in ongoing neuronal activity from frontal cortex of awake mice. In contrast, the common ’crackling noise’ approach fails to determineχunder similar sampling conditions at criticality. Our findings overcome scaling bias from fractional sampling and demonstrate rapid, spatiotemporal synchronization of neuronal assemblies consistent with scale-invariant, parabolic avalanches at criticality.
A high throughput CRISPR perturbation screen identifies epigenetic regulators impacting primordial germ cell development
Authors: Li Liangdao , Ding Xinbao , Sheft Alex P. , Schimenti John C. 
Published: February 2024

AbstractCertain environmental factors can impact fertility and reproductive parameters such as the number and quality of sperm and eggs. One possible mechanism is the perturbation of epigenetic landscapes in the germline. To explore this possibility, we conducted a CRISPRi screen of epigenetic-related genes to identify those that specifically perturb the differentiation of embryonic stem cells (ESCs) into primordial germ cell-like cells (PGCLCs), exploiting a highly scalable cytokine-free platform. Of the 701 genes screened, inhibition of 53 decreased the efficiency of PGCLC formation. NCOR2, a transcriptional repressor that acts via recruitment of Class I and Class IIa histone deacetylases (HDACs) to gene targets, was particularly potent in suppressing PGCLC differentiation. Consistent with evidence that histone deacetylation is crucial for germline differentiation, we found that the HDAC inhibitors (HDACi) valproic acid (VPA; an anti-convulsant) and sodium butyrate (SB; a widely-used dietary supplement) also suppressed ESC>PGCLC differentiation. Furthermore, exposure of developing mouse embryos to SB or VPA caused hypospermatogenesis. Transcriptome analyses of HDACi-treated, differentiating ESC>PGCLC cultures revealed suppression of germline-associated pathways and enhancement of somatic pathways. This work demonstrates the feasibility of conducting large-scale functional screens of genes, chemicals, or other agents that may impact germline development.
A 2D Gabor-wavelet baseline model out-performs a 3D surface model in scene-responsive cortex
Authors: Shafer-Skelton Anna , Brady Timothy F. , Serences John T. 
Published: February 2024

AbstractUnderstanding 3D representations of spatial information, particularly in naturalistic scenes, remains a significant challenge in vision science. This is largely because of conceptual difficulties in disentangling higher-level 3D information from co-occurring features and cues (e.g., the 3D shape of a scene image is necessarily defined by spatial frequency and orientation information). Recent work has employed newer models and analysis techniques that attempt to mitigate these in-principle difficulties. For example, one such study reported 3D-surface features were uniquely present in areas OPA, PPA, and MPA/RSC (areas typically referred to as ‘scene- selective’), above and beyond a Gabor-wavelet baseline (“2D”) model. Here, we tested whether these findings generalized to a new stimulus set that, on average, dissociated static Gabor- wavelet baseline (“2D”) features from 3D scene-surface features. Surprisingly, we found evidence that a Gabor-wavelet baseline model better fit voxel responses in areas OPA, PPA and MPA/RSC compared to a model with 3D-surface information. This raises the question of whether previous findings of greater 3D information could have been due to a baseline condition that didn’t model some potentially critical low-level features (e.g., motion). Our findings also emphasize that much of the information in “scene-selective” regions—potentially even information about 3D surfaces—may be in the form of spatial frequency and orientation information often considered 2D or low-level, and they highlight continued fundamental conceptual challenges in disentangling the contributions of low-level vs. high-level features in visual cortex.
Yemeni university students public perceptions toward the use of artificial intelligence in healthcare: A cross-sectional study
Authors: Hatem Najmaddin A. H. , Ibrahim Mohamed Izham Mohamed , Yousuf Seena A. 
Published: February 2024

AbstractThe integration of artificial intelligence (AI) in healthcare has emerged as a transformative force, promising to enhance medical diagnosis, treatment, and overall healthcare delivery. Hence, this study investigates the university students perceptions toward using AI in healthcare. A cross-sectional survey was conducted at two major universities using a paper-based questionnaire from September 2023 to November 2023. Participants’ views regarding using artificial intelligence in healthcare were investigated using 25 items distributed across five domains. The Mann-Whitney U test was applied for the comparison of variables. The response rate for the survey was 75%, with a sample size of 279. More than half of the participants (52%, n = 145) expressed their belief in AI’s potential to reduce treatment errors in the future. However, about (61.6%, n = 172) of participants fear the influence of AI that could prevent doctors from learning to make correct patient care judgments, and it was widely agreed (69%) that doctors should ultimately maintain final control over patient care. Participants with experience with AI, such as engaging with AI chatbots, significantly reported higher scores in both the “Benefits and Positivity Toward AI in Healthcare” and “Concerns and Fears” domains (p= 0.024) and (p= 0.026), respectively. The identified cautious optimism, concerns, and fears highlight the delicate balance required for successful AI integration. The findings emphasize the importance of addressing specific concerns, promoting positive experiences with AI, and establishing transparent communication channels. Insights from such research can guide the development of ethical frameworks, policies, and targeted interventions, fostering a harmonious integration of AI into the healthcare landscape in developing countries.
Attitudes and Perceptions of Medical Researchers Towards the Use of Artificial Intelligence Chatbots in the Scientific Process: A Large-Scale, International Cross-Sectional Survey
Authors: Ng Jeremy Y. , Maduranayagam Sharleen G. , Suthakar Nirekah , Li Amy , Lokker Cynthia , Iorio Alfonso , Haynes R. Brian , Moher David 
Published: February 2024

AbstractBackgroundChatbots are artificial intelligence (AI) programs designed to simulate conversations with human users through text or speech. The use of artificial intelligence chatbots (AICs) in scientific research presents benefits and challenges. Although the stances of journals and publishing organizations on AIC use is increasingly clear, little is known about researchers’ perceptions of AICs in research. This survey study explores attitudes, familiarity, perceived benefits, limitations, and factors influencing adoption of AIC by researchers.MethodsA cross-sectional online survey of published researchers was conducted. Corresponding authors and their e-mail addresses were identified by querying PubMed for articles (any type) published in a MEDLINE indexed journal in the most recent two months and using R script on PubMed metadata. e-Mail invitations were sent to 61560 study authors. The survey, administered on SurveyMonkey, opened on July 9, 2023, and closed on August 11, 2023. Respondents had 3 weeks to complete the survey and were sent 2 reminder e-mails during the weeks of July 17, 2023, and July 24, 2023.Results2165 respondents completed the survey (4.0% response rate; 94% completion rate of those who responded). Most were familiar with the concept of AICs (n=1294/2138, 60.5%). About half had used an AIC previously for purposes relating to the scientific process (n=1107/2125, 52.1%). Only 244/2137 (11.4%) respondents reported that their institution offered training on using AI tools of whom 64/244 (26.2%) completed the training. 211/2131 (9.9%) reported that their institution implemented policies regarding AIC use in the scientific process. Most respondents expressed interest in learning more and receiving training on AIC use in the scientific process (n=1428/2048, 69.7%). Respondents had mixed opinions about the potential benefits of using AICs, whereas most agreed on their cons/challenges. Respondents agreed AICs were most beneficial in reducing the workload and administrative burden on researchers (n=1299/1941, 66.9%) and they were most concerned about the lack of understanding behind how AICs make decisions and generate responses (n=1484/1923, 77.2%).ConclusionsMost respondents are familiar with AICs and half used AICs in their own research. Although there is clear interest in understanding how AICs can be used, many hesitate due to existing limitations. Little formal instruction on using AICs is available across academic institutions.
Evaluating treatments for the protection of grapevine pruning wounds from natural infection by trunk disease fungi
Authors: Leal C. , Bujanda R. , López-Manzanares B. , Ojeda S. , Berbegal M. , Villa-Llop A. , Santesteban L. G. , Palacios J. , Gramaje D. 
Published: February 2024

AbstractInfection of grapevines by fungal pathogens causing grapevine trunk diseases (GTDs) primarily arises from annual pruning wounds made during the dormant season. While various studies have showcased the efficacy of products in shielding pruning wounds against GTDs infections, most of these investigations hinge on artificial pathogen inoculations, which may not faithfully mirror real field conditions. This study aimed to evaluate and compare the efficacy of various liquid formulation fungicides (pyraclostrobin + boscalid) and paste treatments, as well as biological control agents (BCA:Trichoderma atrovirideSC1,T. atrovirideI-1237, andT. asperellumICC012 +T. gamsiiICC080), for their potential to prevent natural infection of grapevine pruning wounds by trunk disease fungi in two field trials located in Samaniego (Northern Spain) and Madiran (Southern France) over three growing seasons. Wound treatments were applied immediately after pruning in February. One year after pruning, canes were harvested from vines and brought to the laboratory for assessment ofTrichodermaspp. and fungal trunk pathogens. More than 1,200 fungal isolates associated with five GTDs (esca, Botryophaeria, Diaporthe and Eutypa diebacks, and Cytospora canker) were collected from the two vineyards each growing season. Our findings reveal that none of the products under investigation exhibited complete effectiveness against all the GTDs. The efficacy of these products was particularly influenced by the specific year of study. A notable exception was observed with the biocontrol agentT. atrovirideI-1237, which consistently demonstrated effectiveness against Botryosphaeria dieback infections throughout each year of the study, irrespective of the location. The remaining products exhibited efficacy in specific years or locations against particular diseases, with the physical barrier (paste) showing the least overall effectiveness. The recovery rates ofTrichodermaspp. in treated plants were highly variable, ranging from 17% to 100%, with both strains ofT. atrovirideyielding the highest isolation rates. This study underscores the importance of customizing treatments for specific diseases, taking into account the influence of environmental factors for BCA applications.