bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alterations in amperometric cholinergic signals accompanied by synaptic plasticity and γ oscillations in the hippocampus-medial prefrontal cortex pathway
Authors: Chen XiaoYu , Li Li , Sui Li 
Published: November 2021

Objective
Neural projections from the ventral hippocampal CA1 (vCA1) to the medial prefrontal cortex (mPFC) and from the posterior dorsal hippocampal CA1 (pdCA1) to the mPFC are important for information processing. Previous studies have revealed that two forms of long-term synaptic plasticity, long-term potentiation (LTP) and long-term depression (LTD), and γ oscillations, which are all believed to be neural bases for learning and memory in the vCA1-mPFC and the pdCA1-mPFC pathways, exhibited distinct profiles. However, the underlying mechanism is unclear.

Methods
In the present study, amperometric cholinergic signals were monitored during in-vivo electrophysiological recordings of evoked extracellular postsynaptic potentials and spontaneous local field potentials.

Results
The results demonstrated that in the vCA1-mPFC pathway, increased cholinergic currents and γ power of the amperometric cholinergic signals were accompanied by the induction of LTD and increased γ power of local field potentials, whereas, in the pdCA1-mPFC pathway, decreased cholinergic currents and increased γ power of the amperometric cholinergic signals were accompanied by the induction of LTP and increased γ power of local field potentials.

Conclusion
These findings indicated that some correlations may exist between amperometric cholinergic signals and synaptic plasticity in the hippocampus-mPFC pathway. The pattern of alterations in cholinergic signals may help to illustrate the specific properties of synaptic plasticity and γ oscillations in the vCA1-mPFC and the pdCA1-mPFC pathways.
Peer audience effects on children's vocal masculinity and femininity
Authors: Cartei Valentina , Reby David , Garnham Alan , Oakhill Jane , Banerjee Robin 
Published: November 2021

Existing evidence suggests that children from around the age of 8 years strategically alter their public image in accordance with known values and preferences of peers, through the self-descriptive information they convey. However, an important but neglected aspect of this ‘self-presentation’ is the medium through which such information is communicated: the voice itself. The present study explored peer audience effects on children's vocal productions. Fifty-six children (26 females, aged 8–10 years) were presented with vignettes where a fictional child, matched to the participant's age and sex, is trying to make friends with a group of same-sex peers with stereotypically masculine or feminine interests (rugby and ballet, respectively). Participants were asked to impersonate the child in that situation and, as the child, to read out loud masculine, feminine and gender-neutral self-descriptive statements to these hypothetical audiences. They also had to decide which of those self-descriptive statements would be most helpful for making friends. In line with previous research, boys and girls preferentially selected masculine or feminine self-descriptive statements depending on the audience interests. Crucially, acoustic analyses of fundamental frequency and formant frequency spacing revealed that children also spontaneously altered their vocal productions: they feminized their voices when speaking to members of the ballet club, while they masculinized their voices when speaking to members of the rugby club. Both sexes also feminized their voices when uttering feminine sentences, compared to when uttering masculine and gender-neutral sentences. Implications for the hitherto neglected role of acoustic qualities of children's vocal behaviour in peer interactions are discussed.This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part II)’.
Chimpanzee vowel-like sounds and voice quality suggest formant space expansion through the hominoid lineage
Authors: Grawunder Sven , Uomini Natalie , Samuni Liran , Bortolato Tatiana , Girard-Buttoz Cédric , Wittig Roman M. , Crockford Catherine 
Published: November 2021

The origins of human speech are obscure; it is still unclear what aspects are unique to our species or shared with our evolutionary cousins, in part due to a lack of a common framework for comparison. We asked what chimpanzee and human vocal production acoustics have in common. We examined visible supra-laryngeal articulators of four major chimpanzee vocalizations (hoos, grunts, barks, screams) and their associated acoustic structures, using techniques from human phonetic and animal communication analysis. Data were collected from wild adult chimpanzees, Taï National Park, Ivory Coast. Both discriminant and principal component classification procedures revealed classification of call types. Discriminating acoustic features include voice quality and formant structure, mirroring phonetic features in human speech. Chimpanzee lip and jaw articulation variables also offered similar discrimination of call types. Formant maps distinguished call types with different vowel-like sounds. Comparing our results with published primate data, humans show less F1–F2 correlation and further expansion of the vowel space, particularly for [i] sounds. Unlike recent studies suggesting monkeys achieve human vowel space, we conclude from our results that supra-laryngeal articulatory capacities show moderate evolutionary change, with vowel space expansion continuing through hominoid evolution. Studies on more primate species will be required to substantiate this.
This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part II)’.
Finger stick blood test to assess post vaccination SARS-CoV-2 neutralizing antibody response against variants
Authors: Lim Sing Mei , Cheng Hoi Lok , Jia Huan , Kongsuphol Patthara , D/O Shunmuganathan Bhuvaneshwari , Chen Ming Wei , Ng Say Yong , Gao Xiaohong , Turaga Shuvan Prashant , Heussler Sascha P. , Somani Joyti , Sengupta Sharmila , Tay Dousabel MY , McBee Megan E. , Young Barnaby E. , MacAry Paul A. , Sikes Hadley D. , Preiser Peter R. 
Published: November 2021

ABSTRACTThere is clinical need for a quantifiable point-of-care (PoC) SARS-CoV-2 neutralizing antibody (nAb) test that is adaptable with the pandemic’s changing landscape. Here, we present a rapid and semi-quantitative nAb test that uses finger stick or venous blood to assess the nAb response of vaccinated population against wild-type, alpha, beta, gamma, and delta variant receptor binding domains. It captures a clinically relevant range of nAb levels, and effectively differentiates pre-vaccination, post 1st dose and post 2nd dose vaccination samples within 10 minutes. The data observed against alpha, beta, gamma, and delta variants agrees with published results evaluated in established serology tests. Finally, our test revealed a substantial reduction in nAb level for beta, gamma, and delta variants between early BNT162b2 vaccination group (within 3 months) and later vaccination group (post 3 months). This test is highly suited for PoC settings and provides an insightful nAb response in a post-vaccinated population.
Clinical trial emulation can identify new opportunities to enhance the regulation of drug safety in pregnancy
Authors: Challa Anup P. , Niu Xinnan , Garrison Etoi A. , Van Driest Sara L. , Bastarache Lisa M. , Lippmann Ethan S. , Lavieri Robert R. , Goldstein Jeffery A. , Aronoff David M. 
Published: November 2021

AbstractFrom the perspective of most regulatory agencies, it is usually unethical to perform interventional clinical trials on pregnant people. While this policy recognizes the vulnerability of an expectant mother and unborn child, it has created a public health emergency for millions of pregnant patients through a dearth of robust safety data for many common drugs. To address this problem, we harnessed an enterprise collection of 2.8M electronic health records (EHRs) originally collected from routine primary care, leveraging the data linkage between mothers and their babies to create a surrogate for randomized, controlled drug trials in this population. To demonstrate the feasibility of our clinical trial emulation platform to stimulate new hypotheses for post-market drug surveillance, we identified 1,054 drugs historically prescribed to pregnant patients and developed a medication history-wide association study and follow-up evidence synthesis platform—leveraging expert clinician review and real-world data analysis—to test the effects of maternal exposure to these drugs on the incidence of neurodevelopmental defects in their children. Our results replicate known teratogenic risks and existing knowledge on drug structure-related teratogenic risks. Herein, we highlight 5 common drug classes that we believe warrant further assessment of their safety in pregnancy. We also discuss our efforts to develop a discovery-to-regulatory framework that could allow for pragmatic translation of our results to enhanced regulatory policy. Collectively, our work presents a simple approach to evaluating the utility of EHRs in guiding new regulatory review programs focused on improving the delicate equipoise of accuracy and ethics inherent to assessing drug safety in an extremely vulnerable patient population.
Rationale and design of the Health Professional Students at the University of Illinois Chicago (HOLISTIC) Cohort Study
Authors: Dommaraju Sunil R. , Rivera Stephanie Gordon , Rocha Ethan G. , Bicknell Scott , Loizzo Daniel , Mohammad Ayesha , Rajan Priya , Seballos Alexandria , Datta Avisek , Ahmed Rashid , Krishnan Jerry A. , Keehn Mary 
Published: November 2021

ABSTRACTObjectivesThe objectives of the HOLISTIC Cohort Study are to establish a 3-year prospective cohort study that characterizes the health of students within and across health professionals’ education programs during the coronavirus disease 2019 (COVID-19) pandemic, implement an interprofessional student research team, and inform initiatives to improve student health. This report describes the rationale and design of the HOLISTIC Cohort Study, including recruitment strategy, survey development, data management, and descriptive statistics of the first wave of study participants.MethodsAn interprofessional student research team was formed to continuously inform study design. The first wave of recruitment was conducted from April 14, 2021 to May 5, 2021 across seven health science colleges (applied health, dentistry, medicine, nursing, pharmacy, public health, social work) at the University of Illinois Chicago in Chicago, IL. Eligible students were sent an invitation via email to complete an online survey after providing electronic informed consent. The online survey was based on the U.S. Centers for Disease Control and Prevention’s Behavioral Risk Factor Surveillance System 2019 survey and the 2014 World Health Organization Report of the Strategic Advisory Group of Experts Working Group Questionnaire. Two additional recruitment waves are planned in the Spring 2022 and Spring 2023; follow-up of participants previously enrolled will occur during these second and third recruitment waves.ResultsOf 5,118 students invited to participate in the first wave, 553 (10.8%) completed the survey and includes participants from all seven health science colleges. The average age of participants is 27.3 years, 435 (78.8%) identify as female, and 137 (24.8%) identify as an underrepresented minority. Overall, 465 (84.6%) participants reported being currently employed for wages. Just over half (51%) reported no days with poor physical health within a month but only 11.2% reported no days with poor mental health within a month. Nearly one in ten (9.4%) reported having ever had a positive test for COVID-19.ConclusionThe HOLISTIC Cohort Study of health professional students across seven health science colleges has completed the first of three waves of enrollment during the COVID-19 pandemic. Based on the first wave of study participants, increased attention to supporting the mental and physical health of health professional students is needed.
Movement ecology of vulnerable lowland tapirs across a gradient of human disturbance
Authors: Medici EP , Mezzini S , Fleming CH , Calabrese JM , Noonan MJ 
Published: November 2021

AbstractAnimal movement is a key ecological process that is tightly coupled to local environmental conditions. While agriculture, urbanisation, and transportation infrastructure are critical to human socio-economic improvement, these have spurred substantial changes in animal movement across the globe with potential impacts on fitness and survival. Notably, however, human disturbance can have differential effects across species, and responses to human activities are thus largely taxa and context specific. As human disturbance is only expected to worsen over the next decade it is critical to better understand how species respond to human disturbance in order to develop effective, case-specific conservation strategies. Here, we use an extensive telemetry dataset collected over 22 years to fill a critical knowledge gap in the movement ecology of lowland tapirs (Tapirus terrestris) across a gradient of human disturbance within three biomes in southern Brazil: the Pantanal, Cerrado, and Atlantic Forest.From these data we found that the mean home range size across all monitored tapirs was 8.31 km2 (95% CI: 6.53 - 10.42), with no evidence that home range sizes differed between sexes nor age groups. Interestingly, although the Atlantic Forest, Cerrado, and Pantanal vary substantially in habitat composition, levels of human disturbance, and tapir population densities, we found that lowland tapir movement behaviour and space use were consistent across all three biomes. Human disturbance also had no detectable effect on lowland tapir movement. Lowland tapirs living in the most altered habitats we monitored exhibited movement behaviour that was comparable to that of tapirs living in a near pristine environment.Contrary to our expectations, we observed very little individual variability in lowland tapir space use and movement, and human impacts on the landscape also had no measurable effect on their movement. Lowland tapir movement behaviour thus appears to exhibit very little phenotypic plasticity. Crucially, the lack of any detectable response to anthropogenic disturbance suggests that human modified habitats risk being ecological traps for tapirs and this information should be factored into conservation actions and species management aimed towards protecting lowland tapir populations.
ORYX-MRSI: A Fully-Automated Open-Source Software for Three-Dimensional Proton Magnetic Resonance Spectroscopic Imaging Data Analysis
Authors: Cengiz Sevim , Yildirim Muhammed , Bas Abdullah , Ozturk-Isik Esin 
Published: November 2021

AbstractProton magnetic resonance spectroscopic imaging (1H-MRSI) provides noninvasive evaluation of brain metabolism. However, there are some limitations of 1H-MRSI preventing its wider use in the clinics, including the spectral quality issues, partial volume effect and chemical shift artifact. Additionally, it is necessary to create metabolite maps for analyzing spectral data along with other MRI modalities. In this study, a MATLAB-based open-source data analysis software for 3D1H-MRSI, called Oryx-MRSI, which includes modules for visualization of raw1H-MRSI data and LCModel outputs, chemical shift correction, tissue fraction calculation, metabolite map production, and registration onto standard MNI152 brain atlas while providing automatic spectral quality control, is presented. Oryx-MRSI implements region of interest analysis at brain parcellations defined on MNI152 brain atlas. All generated metabolite maps are stored in NIfTI format. Oryx-MRSI is publicly available athttps://github.com/sevimcengiz/Oryx-MRSIalong with six example datasets.
Cortical-subcortical structural connections support transcranial magnetic stimulation engagement of the amygdala
Authors: Sydnor Valerie J. , Cieslak Matthew , Duprat Romain , Deluisi Joseph , Flounders Matthew W. , Long Hannah , Scully Morgan , Balderston Nicholas L. , Sheline Yvette I. , Bassett Dani S. , Satterthwaite Theodore D. , Oathes Desmond J. 
Published: November 2021

AbstractThe amygdala processes valenced stimuli, influences affective states, and exhibits aberrant activity across anxiety disorders, depression, and PTSD. Interventions that modulate amygdala activity hold promise for treating transdiagnostic affective symptoms. We investigated (N=45) whether transcranial magnetic stimulation (TMS) elicits indirect changes in amygdala activity when applied to ventrolateral prefrontal cortex (vlPFC), a region important for affect regulation. Harnessing in-scanner interleaved TMS/functional MRI (fMRI), we reveal that vlPFC neurostimulation evoked acute, dose-dependent modulations of amygdala fMRI BOLD signal. Larger TMS-evoked changes in amygdala fMRI signal were associated with higher fiber density in a vlPFC-amygdala white matter pathway, suggesting this pathway facilitated stimulation-induced communication between cortex and subcortex. This work provides evidence of amygdala engagement by TMS, highlighting stimulation of vlPFC-amygdala circuits as a candidate treatment for affective psychopathology. More broadly, it indicates that targeting cortical-subcortical connections may enhance the impact of TMS on subcortical neural activity and, by extension, subcortex-subserved behaviors.TeaserIndividualized, connectivity-guided transcranial magnetic stimulation modulates the amygdala, demonstrating therapeutic potential.
Optimization algorithm for omic data subspace clustering
Authors: Ciortan Madalina , Defrance Matthieu 
Published: November 2021

Subspace clustering identifies multiple feature subspaces embedded in a dataset together with the underlying sample clusters. When applied to omic data, subspace clustering is a challenging task, as additional problems have to be addressed: the curse of dimensionality, the imperfect data quality and cluster separation, the presence of multiple subspaces representative of divergent views of the dataset, and the lack of consensus on the best clustering method.First, we propose a computational method (discover) to perform subspace clustering on tabular high dimensional data by maximizing the internal clustering score (i.e. cluster compactness) of feature subspaces. Our algorithm can be used in both unsupervised and semi-supervised settings. Secondly, by applying our method to a large set of omic datasets (i.e. microarray, bulk RNA-seq, scRNA-seq), we show that the subspace corresponding to the provided ground truth annotations is rarely the most compact one, as assumed by the methods maximizing the internal quality of clusters. Our results highlight the difficulty of fully validating subspace clusters (justified by the lack of feature annotations). Tested on identifying the ground-truth subspace, our method compared favorably with competing techniques on all datasets. Finally, we propose a suite of techniques to interpret the clustering results biologically in the absence of annotations. We demonstrate that subspace clustering can provide biologically meaningful sample-wise and feature-wise information, typically missed by traditional methods.CCS Concepts: • Computing methodologies → Genetic algorithms; Mixture models; Cluster analysis.ACM Reference FormatMadalina Ciortan and Matthieu Defrance. 2021. Optimization algorithm for omic data subspace clustering. 1, 1 (September 2021), 40 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn
Formal meta-analysis of hypoxic gene expression profiles reveals a universal gene signature and cell type-specific effects
Authors: Puente-Santamaria Laura , Sanchez-Gonzalez Lucia , Gonzalez-Serrano Barbara P. , Pescador Nuria , Martinez-Costa Oscar H. , Ramos-Ruiz Ricardo , del Peso Luis 
Published: November 2021

AbstractBackgroundIntegrating transcriptional profiles results in the identification of gene expression signatures that are more robust than those obtained for individual datasets. However, direct comparison of datasets derived from heterogeneous experimental conditions is not possible and their integration requires the application of specific meta-analysis techniques. The transcriptional response to hypoxia has been the focus of intense research due to its central role in tissue homeostasis and in prevalent diseases. Accordingly, a large number of studies have determined the gene expression profile of hypoxic cells. Yet, in spite of this wealth of information, little effort have been done to integrate these dataset to produce a robust hypoxic signature.ResultsWe applied a formal meta-analysis procedure to a dataset comprising 425 RNAseq samples derived from 42 individual studies including 33 different cell types, to derive a pooled estimate of the effect of hypoxia on gene expression. This approach revealed that a large proportion of the transcriptome (8556 genes out of 20888) is significantly regulated by hypoxia. However, only a small fraction of the differentially expressed genes (1265 genes, 15%) show an effect size that, according to comparisons to gene pathways known to be regulated by hypoxia, is likely to be biologically relevant. By focusing on genes ubiquitously expressed we identified a signature of 291 genes robustly and consistently regulated by hypoxia. Finally, by a applying a moderator analysis we found that endothelial cells show a characteristic gene expression pattern that is significantly different from other cell types.ConclusionBy the application of a formal meta-analysis to hypoxic gene profiles, we have developed a robust gene signature that characterizes the transcriptomic response to low oxygen. In addition to identifying a universal set of hypoxia-responsive genes, we found a set of genes whose regulation is cell-type specific and suggest a unique metabolic response of endothelial cells to reduced oxygen tension.
Teaching a computer to assess hypnotic depth: A pilot study
Authors: Obukhov Nikita V. , L.N.Naish Peter , Solnyshkina Irina E. , Siourdaki Tatiana G. , Martynov Ilya A. 
Published: November 2021

AbstractThe therapeutic effects of hypnosis in some cases seem to be most marked when the patient has achieved sufficient hypnotic depth. It could be possible to monitor the deepening process using electrophysiological data to obtain information on depth changes throughout the session. However, although hypnosis is characterized by some common EEG patterns, significant differences between subjects are also observed. Therefore, an individualized approach is required to quantify the depth continuously during a session. To achieve this, we proposed the machine learning approach, using an EEG-based Brain-Computer interface, and tested it on video-EEG recordings of 8 outpatients. Based on the data from the first sessions, we trained the classification models to discriminate between conditions of wakefulness and deep hypnosis. Then, we applied them to subsequent sessions to predict the probability of deep hypnosis, i.e., to continuously measure depth level in real time. The models trained using frequency ranges of 1.5-14 and 4-15 Hz provided high accuracy. The applications and perspectives are discussed.