bluuebunny/crossref_metadata_2025_split huggingface dataset:
A survey investigating United States federal grant submissions proposing to investigate therapeutic applications of psychedelics
Authors: Barnett Brian S. 
Published: October 2024

AbstractThis study surveyed researchers to assess the contents and funding success of federal grant applications for research into therapeutic applications of psychedelics in the United States. The author emailed an anonymous survey to the corresponding authors of the 50 most-cited articles on psychedelics published after 2000 and disseminated it via Twitter. Ten researchers responded, reporting on 24 grant submissions for psilocybin, ibogaine, LSD, MDMA, and other psychedelics, all to the National Institutes of Health (NIH), from the early 1990s onward. The number of grant applications rose noticeably starting in 2006. Of all grant applications assessed,16.7% were funded, lower than the NIH’s 23.4% average funding rate for R-01 equivalent grants between 1998-2023. More specifically, while no relevant grant applications submitted prior to 2006-2010 were funded by NIH, the funding rate of applications since then, estimated at 19.05% to 22.2%, is close to the average annual NIH funding rate of 20.6 ± 1.9% for R-01 equivalent grant applications from 2006 to early 2023. Respondents generally believed applications for this line of research had a lower chance of success compared to other lines of research, although they felt the funding landscape has improved in recent years, in line with this study’s other findings.
Analyzing greedy vaccine allocation algorithms for metapopulation disease models
Authors: Keithley Jeffrey , Choudhuri Akash , Adhikari Bijaya , Pemmaraju Sriram V. 
Published: October 2024

AbstractAs observed in the case of COVID-19, effective vaccines for an emerging pandemic tend to be in limited supply initially and must be allocated strategically. The allocation of vaccines can be modeled as a discrete optimization problem that prior research has shown to be computationally difficult (i.e., NP-hard) to solve even approximately.Using a combination of theoretical and experimental results, we show that this hardness result may be circumvented. We present our results in the context of a metapopulation model, which views a population as composed of geographically dispersed heterogeneous subpopulations, with arbitrary travel patterns between them. In this setting, vaccine bundles are allocated at a subpopulation level, and so the vaccine allocation problem can be formulated as a problem of maximizing an integer lattice functionsubject to a budget constraint ∥x∥1≤D. We consider a variety of simple, well-known greedy algorithms for this problem and show the effectiveness of these algorithms for three problem instances at different scales: New Hampshire (10 counties, population 1.4 million), Iowa (99 counties, population 3.2 million), and Texas (254 counties, population 30.03 million). We provide a theoretical explanation for this effectiveness by showing that the approximation factor of these algorithms depends on thesubmodularity ratioof objective functiong, a measure of how distantgis from being submodular.Author summaryStrategic and timely allocation of vaccines is crucial in combating epidemic outbreaks. Developing strategies to allocate vaccines over sub-populations rather than to individuals leads to policy recommendations that are more feasible in practice. Despite this, vaccine allocation over sub-populations has only received limited research interest, and the associated computational challenges are relatively unknown. To address this gap, we study vaccine allocation problems over geographically distinct subpopulations in this paper. We formulate our problems to reduce eitheri)the total infections orii)the sum of peak infections over meta-population disease models. We first demonstrate that these problems are computationally challenging even to approximate and then show that a family of simple, well-known greedy algorithms exhibit provable guarantees. We conduct realistic experiments on state-level mobility networks derived from real-world data in three states of distinct population levels: New Hampshire, Iowa, and Texas. Our results show that the greedy algorithms we consider arei)scalable andii)outperform both state-of-the-art and natural baselines in a majority of settings.
High-dimensional confounding in causal mediation: a comparison study of double machine learning and regularized partial correlation network
Authors: Chen Ming , Nguyen Tanya T. , Liu Jinyuan 
Published: October 2024

AbstractIn causal mediation analyses, of interest are the direct or indirect pathways from exposure to an outcome variable. For observation studies, massive baseline characteristics are collected as potential confounders to mitigate selection bias, possibly approaching or exceeding the sample size. Accordingly, flexible machine learning approaches are promising in filtering a subset of relevant confounders, along with estimation using the efficient influence function to avoid overfitting. Among various confounding selection strategies, two attract growing attention. One is the popular debiased, or double machine learning (DML), and another is the penalized partial correlation via fitting a Gaussian graphical network model between the confounders and the response variable. Nonetheless, for causal mediation analyses when encountering high-dimensional confounders, there is a gap in determining the best strategy for confounding selection. Therefore, we exemplify a motivating study on the human microbiome, where the dimensions of mediator and confounders approach or exceed the sample size to compare possible combinations of confounding selection methods. By deriving the multiply robust causal direct and indirect effects across various hypotheses, our comprehensive illustrations offer methodological implications on how the confounding selection impacts the final causal target parameter estimation while generating causality insights in demystifying the “gut-brain axis”. Our results highlighted the practicality and necessity of the discussed methods, which not only guide real-world applications for practitioners but also motivate future advancements for this crucial topic in the era of big data.
Asymmetric spin echo multi-echo echo planar imaging (ASEME-EPI) sequence for pre-clinical high-field fMRI
Authors: Johnson Kyle A. , Pawela Christopher P. , Nencka Andrew S. , Sidabras Jason W. 
Published: October 2024

AbstractIn functional magnetic resonance imaging (fMRI) of the blood oxygen level-dependent (BOLD) contrast, gradient-recalled echo (GRE) acquisitions offer high sensitivity but suffer from susceptibility-induced signal loss and lack specificity to microvasculature. In contrast, spin echo (SE) acquisitions provide improved specificity at the cost of reduced sensitivity. This study introduces Asymmetric Spin Echo Multi-Echo Echo Planar Imaging (ASEME-EPI), a technique designed to combine the benefits of both GRE and SE for high-field preclinical fMRI. ASEME-EPI employs a spin echo readout followed by two asymmetric spin echo (ASE) GRE readouts, providing an initial T2-weighted SE image and subsequent T2*-weighted ASE images. A feasibility study for the technique was implemented on a 9.4 T pre-clinical MRI system and tested using a visual stimulation in northern tree shrews. Comparing ASEME-EPI with conventional GRE echo planar imaging (GRE-EPI) and SE echo planar imaging (SE-EPI) acquisitions, results showed that ASEME-EPI achieved BOLD contrast-to-noise ratio (CNR) comparable to GRE-EPI while offering improved specificity in activation maps. ASEME-EPI activation was more confined to the primary visual cortex (V1), unlike GRE-EPI which showed activation extending beyond anatomical boundaries. Additionally, ASEME-EPI demonstrated the ability to recover signal in areas of severe field inhomogeneity where GRE-EPI suffered from signal loss. The performance of ASEME-EPI is attributed to its multi-echo nature, allowing for SNR-optimized combination of echoes, effectively denoising the data. The inclusion of the initial SE also contributes to signal recovery in areas prone to susceptibility artifacts. This feasibility study demonstrates the potential of ASEME-EPI for high-field pre-clinical fMRI, offering a promising compromise between GRE sensitivity and SE specificity while addressing challenges of T2*decay at high field strengths.
Quantitative measurements of shear stress-dependent adhesion and motion ofDictyostelium discoideumcells in a microfluidic device
Authors: Fakhari Sepideh , Belleannée Clémence , Charrette Steve J. , Greener Jesse 
Published: October 2024

AbstractShear stress plays a crucial role in modulating cell adhesion and signaling. We present a microfluidic shear stress generator used to investigate the adhesion dynamics ofDictyostelium discoideum, an amoeba cell model organism with well-characterized adhesion properties. We applied shear stress and tracked cell adhesion, motility, and detachment using time-lapse videomicroscopy. In the precise shear conditions generated on-chip, our results show cell migration patterns influenced by shear stress, with cells displaying an adaptive response to shear forces as they alter their adhesion and motility behavior in reaction to shear stress. Additionally, we observed that DH1-10 wild-typeD. discoideumcells exhibit stronger adhesion and resistance to shear-induced detachment compared tophg2adhesion-defective mutant cells and also highlighted the influence of initial cell density on detachment behavior.
Impacts of sequence and structure on pyrrolocytosine fluorescence in RNA
Authors: Coulson Taylor L. , Widom Julia R. 
Published: October 2024

ABSTRACTFluorescence spectroscopy encompasses many useful methods for studying the structures and dynamics of biopolymers. Applications to nucleic acids require the use of extrinsic fluorophores such as fluorescent base analogues (FBAs), which mimic the native bases but have enhanced fluorescence quantum yields. In this work, we use multiple complementary methods to systematically investigate the sequence- and structure-dependence of the fluorescence of the FBA pyrrolocytosine (pC) within RNA. We demonstrate that pC is typically brightest in conformations in which it is base-stacked but not base-paired, properties that distinguish it from more widely used FBAs. This effect is strongly sequence-dependent, with adjacent adenosine and cytidine residues conferring the greatest contrast between stacked and unstacked structures. Structural heterogeneity was resolved in single-stranded RNA and fully complementary and mismatched double-stranded RNA using time-resolved fluorescence measurements and fluorescence-detected circular dichroism spectroscopy. Double-stranded contexts are distinguished from single-stranded contexts by the presence of inter-strand energy transfer from opposing bases, while base-paired pC is distinguished by its short excited state lifetime. This work will enhance the value of pC as a structural probe for biologically and medicinally significant RNAs by guiding the selection of labeling sites and interpretation of the resulting data.GRAPHICAL ABSTRACT
A computational principle of habit formation
Authors: Lakshminarasimhan Kaushik 
Published: October 2024

1AbstractActions are influenced by multiple decision-making systems – including a goal-directed system that favors rewarded actions and a habit system that repeats past actions – but precisely when one system prevails is not known. We show that when competition between these systems is resolved by a winner-take-all mechanism, the precise condition for the emergence of habits can be cast in terms of the well-known probability matching principle. The theory embodies a trade-off in which exploitation, or overmatching, maximizes reward but strengthens habits, while paradoxically, exploration preserves goal-directed behavior by sacrificing rewards. This tradeoff can be averted if learning operates on abstract latent state representations whereby knowing the broader context allows for switching between two habits instead of avoiding one, thus maximizing rewards without forfeiting flexibility. The theory explains a range of animal behaviors as well as task-dependent effects of striatal manipulation, and suggests that neural mechanisms governing exploration implicitly control arbitration between decision-making systems.
Integration of distinct cortical inputs to primary and higher order inhibitory cells of the thalamus
Authors: Puzzo Christian D. , Martinez-Garcia Rosa I. , Liu Hero , Dyson Levi F. , Gilbert William O. , Cruikshank Scott J. 
Published: October 2024

SummaryThe neocortex controls its own sensory input in part through top-down inhibitory mechanisms. Descending corticothalamic projections drive GABAergic neurons of the thalamic reticular nucleus (TRN), which govern thalamocortical cell activity via inhibition. Neurons in sensory TRN are organized into primary and higher order (HO) subpopulations, with separate intrathalamic connections and distinct genetic and functional properties. Here, we investigated top-down neocortical control over primary and HO neurons of somatosensory TRN. Projections from layer 6 of somatosensory cortex evoked stronger and more state-dependent activity in primary than in HO TRN, driven by more robust synaptic inputs and potent T-type calcium currents. However, HO TRN received additional, physiologically distinct, inputs from motor cortex and layer 5 of S1. Thus, in a departure from the canonical focused sensory layer 6 innervation characteristic of primary TRN, HO TRN integrates broadly from multiple corticothalamic systems, with unique state-dependence, extending the range of mechanisms for top-down control.
MMP21 behaves as a fluid flow transported morphogen to impart laterality during development
Authors: Ott Tim , Brugger Amelie , Szenker-Ravi Emmanuelle , Kurrle Yvonne , Aberle Olivia , Tisler Matthias , Blum Martin , Whalen Sandra , Bouvagnet Patrice , Reversade Bruno , Schweickert Axel 
Published: October 2024

AbstractHeterotaxy (HTX) is frequently caused by deleterious variants in the gene encoding Matrix metallopeptidase 21 (MMP21). However, the underlying pathomechanism has not been ascertained. In this study, we report on a novel HTX-associatedMMP21knockout allele in humans and investigate the peptidase’s role during laterality development usingXenopusembryos as animal model. The targeted inactivation ofmmp21in f0 mutantXenopussuccessfully phenocopied the human HTX condition, yet the cilia-driven leftward fluid flow, which initiates asymmetric gene activity at the left-right organizer (LRO), was unaltered inmmp21null frogs. Instead, our analysis of downstream events revealed that flow response, the left-sided repression ofdand5, could not take place. Remarkably, gain-of-function experiments demonstrated that Mmp21 spreads over LRO cells and triggers flow response. Additionally, Mmp21 functions upstream of Cirop, another metallopeptidase, which we found specifically localized to LRO cilia. Thus, our findings suggest that Mmp21 may be the long-sought morphogen, which is actively transported by the leftward fluid flow to Cirop-laden cilia, in order to specify the left side of the embryo.
Cryo-electron tomography reveals coupled flavivirus replication, budding and maturation
Authors: Dahmane Selma , Schexnaydre Erin , Zhang Jianguo , Rosendal Ebba , Chotiwan Nunya , Kumari Singh Bina , Yau Wai-Lok , Lundmark Richard , Barad Benjamin , Grotjahn Danielle A. , Liese Susanne , Carlson Andreas , Överby Anna K. , Carlson Lars-Anders 
Published: October 2024

AbstractFlaviviruses replicate their genomes in replication organelles (ROs) formed as bud-like invaginations on the endoplasmic reticulum (ER) membrane, which also functions as the site for virion assembly. While this localization is well established, it is not known to what extent viral membrane remodeling, genome replication, virion assembly, and maturation are coordinated. Here, we imaged tick-borne flavivirus replication in human cells using cryo-electron tomography. We find that the RO membrane bud is shaped by a combination of a curvature-establishing coat and the pressure from intraluminal template RNA. A protein complex at the RO base extends to an adjacent membrane, where immature virions bud. Naturally occurring furin site variants determine whether virions mature in the immediate vicinity of ROs. We further visualize replication in mouse brain tissue by cryo-electron tomography. Taken together, these findings reveal a close spatial coupling of flavivirus genome replication, budding, and maturation.
PEPITEM Tripeptides and Peptidomimetics: Next-Generation Modulators of Inflammation in Immune-Mediated Conditions
Authors: Saviano Anella , Apta Bonita , Tull Samantha , Pezhman Laleh , Fatima Areeba , Mete Antonio , Sevim Mustafa , Chimen Myriam , Schettino Anna , Marigliano Noemi , McGettrick Helen M. , Iqbal Asif J. , Maione Francesco , Ed Rainger G. 
Published: October 2024

AbstractPEPITEM is an immune-modulatory peptide that effectively regulates inflammation and mitigates immune-mediated inflammatory diseases (IMIDs). Here we identify two independently active tripeptide pharmacophores within PEPITEM and engineered peptidomimetics with enhanced pharmacodynamic properties. These peptidomimetics regulate T-cell traffickingin vitroand reduce T-cell, neutrophil and macrophage numbers in the inflamed peritoneal cavity in vivo. In a plaque psoriasis model, topical administration reduced disease severity, inflammation and immune cell infiltration, while regulating cytokine release in macrophages and fibroblasts, as well as keratinocyte proliferation. Th1 and Th17 cell abundance, along with their cytokines, was reduced in secondary lymphoid organs. This expanded functional repertoire of PEPITEM and its derivatives provides innovative tools for countering immune and stromal cell-induced pathology in IMIDs, paving the way for a novel class of anti-inflammatory agents.
The Dynamic Genetic Atlas of 122 Gestational Phenotypes
Authors: Liu Siyang , Zheng Hao , Gu Yuqin , Yang Zijing , Liu Yanhong , Wei Yuandan , Guo Xinxin , Chen Yanchao , Hu Liang , Chen Xiaohang , Zhang Fuquan , Chen Guo-Bo , Qiu Xiu , Huang Shujia , Zhen Jianxin , Wei Fengxiang 
Published: October 2024

AbstractThe gestational period, spanning approximately 40 weeks from fertilization to birth, is pivotal in human reproduction. Monitoring the health of pregnant women and newborns during this period involves systematic prenatal and postpartum examinations, guided by indicators established under the national medical insurance system, collectively termed gestational phenotypes. However, our understanding of the genetic basis of these phenotypes and their intricate relationship with maternal long-term health outcomes remain markedly limited. We conducted comprehensive genetic investigations into 122 gestational phenotypes among 121,579 Chinese pregnancies. These phenotypes included anthropometric metrics, comprehensive blood biomarker measurements, and common gestational complications and outcomes. We identified 3,845 genetic loci, 1,385 of which are novel. Our analyses revealed gestation-specific genetic effects, ranging from proportion 0% to 100% for 23 phenotypes, highlighting genes and pathways predominantly enriched in response to hormones, growth and immune function. Longitudinal trajectory genome-wide association study (GWAS) analyses of repeated measures across 24 complete blood cell phenotypes revealed that 17.8% of the genetic variants exhibited significant interactions with gestational timing across five gestational and postpartum periods. Two-sample univariable and multivariable Mendelian Randomization (MR) analyses of 220 mid- and old-age phenotypes suggested causal associations between gestational phenotypes and the risk of chronic diseases in later life. These findings provide initial insights into the genetic foundations of human gestational phenotypes and their relationship with long-term health, laying a basis for advanced population health during gestation.
Protocol for developing the reporting guidelines for the use CHatbots and other gEnerative AI tools in mEdical Research (CHEER)
Authors: Luo Xufei , Tham Yih Chung , Daher Mohammad , Bian Zhaoxiang , Chen Yaolong , Estill Janne 
Published: October 2024

AbstractBackgroundThe integration of artificial intelligence (AI) has revolutionized medical research, offering innovative solutions for data collection, patient engagement, and information dissemination. Powerful generative AI (GAI) tools like ChatGPT and other similar chatbots have emerged, facilitating user interactions with virtual conversational agents. However, the increasing use of GAI tools in medical research presents challenges, including ethical concerns, data privacy issues, and the potential for generating false content. These issues necessitate standardization of reporting to ensure transparency and scientific rigor.ObjectiveThe development of the CHatbots and other gEnerative AI tools in mEdical Research (CHEER) reporting guidelines aims to establish a comprehensive, standardized guideline for reporting the use of GAI tools in medical research.MethodsThe CHEER guidelines are being developed following the methodology recommended by the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) network, involving scoping reviews and expert Delphi consensus. The process consists of three stages: preparatory work, Delphi survey, and testing and dissemination. The study is approved by the Ethics Committee of the Institute of Health Data Science at Lanzhou University (approval number: HDS-202406-01).Expected resultsThe CHEER project was launched in July 2023 by the Evidence-Based Medicine Center of Lanzhou University and the WHO Collaborating Centre for Guideline Implementation and Knowledge Translation, and is scheduled to conclude in July 2024. The expected outcome of the CHEER project is a reporting checklist, accompanied by relevant terminology, examples, and explanations, to guide stakeholders in better reporting the use of GAI tools.ConclusionCHEER aims to guide researchers, reviewers, and editors in the transparent and scientific application of GAI tools in medical research. By providing a standardized reporting framework, CHEER seeks to enhance the clarity, completeness, and integrity of research involving GAI tools, promoting collaboration, comparability, and cumulative knowledge generation in AI-driven healthcare technologies.Trial RegistrationWe registered this protocol on the EQUATOR Network (https://www.equator-network.org/library/reporting-guidelines-under-development/reporting-guidelines-under-development-for-other-study-designs/#CHEER).