bluuebunny/crossref_metadata_2025_split huggingface dataset:
Methods used to Account for Concurrent Analgesic Use in Randomized Controlled Trials of Interventional Pain Treatments: A Meta-Epidemiologic Study
Authors: Sridhar Balaji V , Humbert Andrew , Babitts Adam , Staab Carina , Daniels Clinton J. , Dhillon Malka , Heagerty Patrick , Goldenberg Joshua , Jensen Mark , Suri Pradeep 
Published: November 2024

ABSTRACTObjectiveThe modest effect sizes of most pain treatments make it essential that randomized controlled trials (RCTs) use methods that clearly define treatment effects of interest and consider the role of concurrent treatments. This study aims to determine how frequently concurrent analgesic use is reported in interventional pain RCTs and how accounting for analgesic use can affect pain intensity outcomes.DesignMeta-epidemiologic study.MethodsWe conducted a study of concurrent analgesic use among RCTs from a recent systematic review of non-surgical interventional pain treatments (n= 37). We calculated the prevalence of different methods used to report concurrent analgesic use. We performed meta-analyses to compare treatment effects on pain intensity with vs. without accounting for concurrent analgesic use via a novel quantitative composite outcome, the “QPAC1.5.”ResultsAbout half of interventional pain RCTs reported concurrent analgesic use, but only one RCT directly accounted for concurrent analgesic use in their pain intensity outcome. Analyses accounting for concurrent analgesic use using the QPAC1.5substantially increased the estimated treatment effect of interventions on pain intensity by an average of −0.45 numeric rating scale points (95% CI −0.76 to −0.14; p<0.001), as compared to analyses that did not adjust for analgesic use.ConclusionConcurrent analgesic use is sometimes reported in interventional pain RCTs, but rarely accounted for when examining treatment effects on pain intensity. Accounting for concurrent analgesic use changes the treatment effect of interest to remove differential analgesic rates and has the potential to significantly affect estimates of effect sizes on pain treatments.
Polygenic risk scores for precision psychiatry: a study on the effect heterogeneity of antidepressants
Authors: Goto Ryunosuke , Naito Tatsuhiko , Skokauskas Norbert , Inoue Kosuke 
Published: November 2024

AbstractDepression continues to be a major contributor to the global burden of diseases. Antide-pressants are recommended as the initial choice of treatment for moderate and severe depression among adults, but the choice of antidepressant class can be challenging, as efficacies of commonly used antidepressants are generally comparable between classes. As such, to determine which medication to prescribe to each patient, clinicians often rely on the adverse effect profile of antidepressants. One of the most discussed adverse effects is the possibility of increased suicidality with antidepressant initiation, a rare but serious adverse event. Efforts to predict this have mostly relied on clinical and sociodemographic characteristics of patients, but we do not yet have a clear picture. A promising avenue is to use patients’ genetic data, but the evidence on its utility has so far been mixed, and few large scale databases have both clinical and genetic data that can evaluate its utility. Here, using genetic and clinical data on more than 7,000 patients, both children and adults, with major depressive disorder from the All of Us Research Program, we show that the genetic predisposition for psychiatric disorders may underlie the substantial heterogeneity in the risk of suicidal thoughts with antidepressant use. Specifically, using a target trial emulation framework, we show that patients with higher polygenic risk scores for psychiatric disorders, particularly for attention deficit-hyperactivity disorder, are more likely than those with lower scores to experience suicidal thoughts with the use of selective serotonin reuptake inhibitors, relative to bupropion. In the personalized medicine framework, PRSs for various psychiatric disorders may help tailor antidepressants to each patient to avoid serious adverse effects such as suicidal thoughts.
Transcriptome analysis ofatad3-null zebrafish embryos elucidates possible disease mechanisms
Authors: Ezer Shlomit , Ronin Nathan , Yanovsky-Dagan Shira , Rotem-Bamberger Shahar , Halstuk Orli , Wexler Yair , Ben-Moshe Zohar , Plaschkes Inbar , Benyamini Hadar , Saada Ann , Inbal Adi , Harel Tamar 
Published: November 2024

ABSTRACTATAD3A, a nuclear gene encoding the ATAD3A protein, has diverse roles in mitochondrial processes, encompassing mitochondrial dynamics, mitochondrial DNA maintenance, metabolic pathways and inter-organellar interactions. Pathogenic variants in this gene cause neurological diseases in humans with recognizable genotype-phenotype correlations. To further investigate the gene function and its implication in health and disease, we utilized CRISPR/Cas9 genome editing to generate a knockout (KO) model of the zebrafish ortholog gene,atad3. Analysis ofatad3-null zebrafish embryos revealed microcephaly, small eyes, pericardial edema and musculature thinning, closely mirroring with the human rare disease phenotype. Larvae exhibited delayed hatching and embryonic lethality by 13 days post-fertilization (dpf). Locomotor activity, ATP content, mitochondrial content, and mitochondrial activity were all reduced in the mutant embryos. Transcriptome analysis at 3 dpf via RNA-sequencing indicated decline in most mitochondrial pathways, accompanied by a global upregulation of cytosolic tRNA synthetases, presumably secondary to mitochondrial stress and possibly endoplasmic reticulum (ER)-stress. Differential expression of select genes was corroborated in fibroblasts from an affected individual. Theatad3-null zebrafish model emerges as a reliable representation of humanATAD3A-associated disorders, with similarities in differentially expressed pathways and processes. Furthermore, our study underscores mitochondrial dysfunction as the primary underlying pathogenic mechanism inATAD3A-associated disorders and identifies potential readouts for therapeutic studies.
A Bidirectional Brain-Fat Body Axis for Pathogen Avoidance
Authors: Wang Yujie , Saito Kokoro , Tanimoto Hiromu , Grunwald Kadow Ilona C. 
Published: November 2024

AbstractIngesting pathogens through spoiled food can cause serious harm, including infections, tissue damage, and even death. To prevent these outcomes, many animals have evolved behaviors to avoid consuming harmful pathogens. While pathogen avoidance behavior is conserved across species, the mechanisms linking immune responses of the body with neuron-controlled behavior remain unclear. Building on our previous findings, we here present a new bidirectional body-brain communication between the fat body and the nervous system that drives immune receptor-induced avoidance behavior. We show that immune receptor signaling and a specific antimicrobial peptide (AMP) are essential in both octopaminergic neuromodulatory neurons and the fat body for rapidly reducing pathogen intake after initial ingestion. Mechanistically, the octopaminergic neurons innervate the fly’s fat body where they trigger a calcium response through a specific octopamine receptor. This octopaminergic signal prompts the fat body to release dopamine. In turn, Dop1R1 signaling in output neurons of the mushroom body, the insect higher brain center, drives pathogen avoidance. Together, our data suggest that ingested pathogens are detected by immune receptors in neurons, which, through synaptic connections, trigger the release of dopamine and AMPs from fat cells. While AMPs combat the pathogens, dopamine reduces further ingestion by inducing behavioral changes. This mechanism demonstrates efficient communication between the body and brain, coordinating survival behaviors through systemic dopamine signaling from the fat body to the brain.
Theperiodgene alters daily and seasonal timing inOstrinia nubilalis
Authors: Dayton Jacob N. , Dopman Erik B. 
Published: November 2024

SummaryThe timing of insects’ daily (feeding, movement) and seasonal (diapause, migration) rhythms affects their population dynamics and distribution. Yet, despite their implications for insect conservation and pest management, the genetic mechanisms underlying variation in timing are poorly understood. Prior research in the European corn borer moth (Ostrinia nubilalis) associated ecotype differences in seasonal diapause and daily activity with genetic variation at the circadian clock geneperiod(per). Here, we demonstrate that populations with divergent allele frequencies atperexhibit differences in daily behavior, seasonal development, and the expression of circadian clock genes. Specifically, later daily activity and shortened diapause were associated with a reduction and delay in the abundance of cyclingpermRNA. CRISPR/Cas9-mediated mutagenesis revealed thatperand/or an intact circadian clock network were essential for the appropriate timing of daily behavior and seasonal responsiveness. Furthermore, a reduction ofpergene dosage inperheterozygous mutants (per-/+) pleiotropically decreased the diapause incidence, shortened post-diapause development, and delayed the timing of daily behavior, in a manner phenotypically reminiscent of wild-type individuals. Altogether, this combination of observational and experimental research strongly suggests thatperis a master regulator of biological rhythms and may contribute to the observed life cycle differences between bivoltine (two generation) and univoltine (one generation)O. nubilalis.HighlightsNatural ecotypes with divergentperiod(per) genotypes differ in their daily and seasonal responses to photoperiodLater daily activity, reduced diapause incidence, and shorter post-diapause development is associated with reducedpermRNA abundanceperis essential for short-day recognition and daily timingReducedpergene dosage shortened post-diapause development and delayed locomotor activity
Strip cropping designed for maintaining productivity increases ground beetle biodiversity
Authors: Croijmans Luuk , Cuperus Fogelina , van Apeldoorn Dirk F. , Bianchi Felix J.J.A. , Rossing Walter A.H. , Poelman Erik H. 
Published: November 2024

AbstractGlobal biodiversity is declining at an unprecedented rate, with agriculture as a major driver. There is mounting evidence that intercropping can increase insect biodiversity while maintaining or increasing yield. Yet, intercropping is often considered impractical for mechanized farming systems. Strip cropping is pioneered by Dutch farmers as it is compatible with standard farm machinery. Here, we use ground beetle data from four experimental locations across four years of measurements because these are good agrobiodiversity indicators and hold keystone positions in agroecosystem foodwebs. We show that strip cropping systems that are designed for retaining productivity can also enhance ground beetle biodiversity, without incurring major yield loss. Strip cropped fields had on average 15% more ground beetle species and 30% more individuals than monocultural fields. The increase in field-level beetle species richness in organic agriculture through strip cropping approached increases found for other readily deployed biodiversity conservation methods, like shifting from conventional to organic agriculture (+19% - +23%). This makes strip cropping a useful tool for bending the curve of biodiversity loss without compromising food production.
Reciprocal regulation of autophagy and exosome pathway is mediated by GABARAPL2 and Alix to facilitate cellular homeostasis
Authors: Soni Naveen , Chaudhary Megha , Bissa Bhawana 
Published: November 2024

AbstractThe continuous reliance of cancer cells to acquire energy and communicate their nutrient needs makes them resilient and vulnerable. It provides an opportunity to stifle cancer cells by restricting their energy generation and communication ability. Autophagy and exosome biogenesis are two such pathways that are essential in maintaining the robust growth and survival of cancer cells. In this study we observed that inhibition of one pathway altered the expression of genes in other pathway. Exosome biogenesis, when blocked, led to an increase in breast cancer cell proliferation, while inhibition of autophagy did not significantly affect cancer cell proliferation. Therefore, the two pathways, when independently inhibited, did not present any significant effect on restricting cancer cell growth. However, we observed a substantial reduction in cancer cell proliferation upon combined inhibition of two pathways. To evaluate the reciprocal regulation of two pathways, we blocked the autophagy pathway and observed increase in the secretion of exosomes from MDA-MB-231 cells, along with decreased expression of Alix and CD63. On contrary, inhibition of exosome biogenesis led to an increase in the expression of ATG5 and ATG16L1, which caused a significant decrease in expression of GABARAPL2. Interestingly, the knockdown of GABARAPL2 abrogated the decrease in Alix expression upon autophagy inhibition, thus highlighting the essential role of GABARAPL2 in Alix secretion. Thus, our study highlights for the first time the synergistic effects of autophagy and exosome pathway inhibition in restricting cancer cell growth as well as the involvement of GABARAPL2 in the regulation of exosome secretion via modulating Alix expression.
Mild focal cooling selectively impacts computations in dendritic trees
Authors: Matin Meisam Habibi , Xiao Shulan , Jayant Krishna 
Published: November 2024

ABSTRACTFocal cooling is a powerful technique to temporally scale neural dynamics. However, the underlying cellular mechanisms causing this scaling remain unresolved. Here, using targeted focal cooling (with a spatial resolution of 100 micrometers), dual somato-dendritic patch clamp recordings, two-photon calcium imaging, transmitter uncaging, and modeling we reveal that a 5°C drop can enhance synaptic transmission, plasticity, and input-output transformations in the distal apical tuft, but not in the basal dendrites of intrinsically bursting L5 pyramidal neurons. This enhancement depends on N-methyl-D-aspartate (NMDA) and Kv4.2, suggesting electrical structure modulation. Paradoxically, and despite the increase in tuft excitability, we observe a reduced rate of recovery from inactivation for apical Na+ channels, thereby regulating back-propagating action potential invasion, coincidence detection, and overall burst probability, resulting in an “apparent” slowing of somatic spike output. Our findings reveal a differential temperature sensitivity along the basal-tuft axis of L5 neurons analog modulates cortical output.
Quantifying the intricacies of biological pattern formation: A new perspective through complexity measures
Authors: Riedel Jurgen , Barnes Chris P. 
Published: November 2024

AbstractIn this study we examine the emergence of complex biological patterns through the lens of reaction-diffusion systems. We introduce two novel complexity metrics — Diversity of Number of States (DNOS) and Diversity of Pattern Complexity (DPC)— which aim to quantify structural intricacies in pattern formation, enhancing traditional linear stability analysis methods. We demonstrate this approach to different systems including the linear Turing, Gray-Scott and FitzHugh-Nagumo models. These measures reveal insights into nonlinear dynamics, multistability, and the conditions under which complex biological patterns stabilize. We then apply the approach to gene regulatory networks, including models of the toggle switch in developmental biology, demonstrating how diffusion and self-activation contribute to robust spatial patterning. Additionally, simulations of the Notch-Delta-EGF signaling pathway in Drosophila neurogenesis highlight the role of gene regulation and parameter variations in modulating pattern complexity and state diversity. Overall, this work establishes complexity-based approaches as valuable tools for exploring the conditions that drive diverse and stable biological pattern formation, offering a pathway for future applications in synthetic biology and tissue engineering.
The Causal Pivot: A Structural Approach to Genetic Heterogeneity and Variant Discovery in Complex Diseases
Authors: Shaw Chad , Williams Christopher , Tan Tao Tao , Di Nicholas , Shulman Joshua , Belmont John W. 
Published: November 2024

AbstractWe present the Causal Pivot (CP) as a structural causal model (SCM) for analyzing genetic heterogeneity in complex diseases. The CP leverages one established causal factor to detect the contribution of a second suspected cause. Specifically, polygenic risk scores (PRS) serve as known causes, while rare variants (RV) or RV ensembles are evaluated as candidate causes. The CP incorporates outcome-induced association by conditioning on disease status. We derive a conditional maximum likelihood procedure for binary and quantitative traits and develop the Causal Pivot Likelihood Ratio Test (CP-LRT) to detect causal signals.Through simulations, we demonstrate the CP-LRT’s robust power and superior error control compared to alternatives. We apply the CP-LRT to UK Biobank (UKB) data, analyzing three exemplar diseases: hypercholesterolemia (HC, LDL-c ≥ 4.9 mmol/L; nc=24,656), breast cancer (BC, ICD10 C50; nc=12,479), and Parkinson’s disease (PD, ICD10 G20; nc=2,940). For PRS, we utilize UKB-derived values, and for RVs, we analyze ClinVar pathogenic/likely pathogenic variants and loss-of-function mutations in disease-relevant genes:LDLRfor HC,BRCA1for BC, andGBAfor PD. Significant CP-LRT signals were detected for all three diseases. Cross-disease and synonymous variant analyses serve as controls. We further develop ancestry adjustment using matching and inverse probability weighting, and we extend the CP to examine oligogenic burden in the lysosomal storage pathway for PD. The CP reveals an approach to address heterogeneity and is an extensible method for inference and discovery in complex disease genetics.
Longer internal exons tend to have more tandem repeats and more frequently experience insertions and deletions that are mostly in intrinsically disordered regions of the encoded proteins
Authors: Homma Keiichi , Anbo Hiroto , Ota Motonori , Fukuchi Satoshi 
Published: November 2024

AbstractInsertions and deletions (indels) in eukaryotic proteins are known to preferentially encode intrinsically disordered regions (IDRs), protein regions that by themselves do not form unique three-dimensional structures. As a previous investigation showed that long internal exons tend to encode IDRs in eukaryotes in general, we thought it worthwhile to analyze how indels alter internal exons and affect IDRs of the encoded proteins. For consideration of evolutionary roles indels play, we decided to select indels commonly observed in all variants (“fixed” indels) since indels in minor variants may represent transient aberrations in splicing. Here, by comparison of orthologous variants of closely related species together with those of outgroups, we identified fixed indels in the internal exons in four mammals and two flies. The fixed indels are nearly always nonframeshifting, short, and mostly encode IDRs. On average 51% of inserted and 40% of deleted residues are attributable to alterations in tandem repeats. Deletion tends to occur more frequently than insertion does and indels are generally more prevalent in long internal exons. Tandem repeats occur preferentially in long internal exons, indicating that their alterations account for the high frequency of indels in long internal exons. Also, since tandem repeats mostly encode IDRs, this finding at least partially explains the high incidence of IDRs in long internal exons. We propose that long internal exons had been produced in early eukaryotes mainly by repeat expansion that added IDRs to the encoded proteins but are experiencing frequent indels by alterations in tandem repeats.
Data driven refinement of gene expression signatures for enrichment analysis
Authors: Wenzel Alexander T. , Faraji Farhoud , Sato Kuniaki , Medetgul-Ernar Kwat , Castanza Anthony , Sagatelian Romella , Donepudi Gayathri , Halawa Omar , Wang Jean Y. J. , Gutkind J. Silvio , Tamayo Pablo , Mesirov Jill P. 
Published: November 2024

AbstractGene set enrichment methods measure biological process or pathway activation in gene expression data by testing coordinate up- or down-regulation of pathway members in a ranked list of genes. These methods rely on curated, annotated gene sets whose members’ coordinate expression is an indicator of a process or state. We therefore developed the Molecular Signatures Database (MSigDB), a collection of expertly annotated gene sets. While using, enhancing, and expanding MSigDB, we have observed that some gene sets can lack coordinate expression, especially those derived from canonical pathways. To address this challenge, we developed gene set refinement (GSR), a data-driven approach leveraging large-scale multi-omics compendia to extract context-specific sets, deconvolve heterogeneity, and reveal multiple downstream signaling. We applied this method to address cancer biology questions, and demonstrated successful, targeted refinement of existing MSigDB gene sets.
Programmable 3D cell alignment of bioprinted tissue via soft robotic dynamic stimulation
Authors: Rosalia Luca , Mosle Katelyn , Sinha Soham , Du Yi Yi , Solberg Fredrik , Jia Allison , Weiss Jonathan , Tam Tony , Herrmann Jessica E. , Cutkosky Mark , Skylar-Scott Mark 
Published: November 2024

AbstractRecent breakthroughs in biofabrication have enabled the development of engineered tissues for various organ systems, supporting applications in drug testing and regenerative medicine. However, current approaches do not allow for dynamic mechanical maturation of engineered tissue in 3D. Although uniaxial mechanostimulation techniques have shown promise in generating anisotropic tissues, they fail to recapitulate the biomechanics of complex tissues. As a result, existing biofabricated tissues lack the ability to replicate complex 3D alignment patterns essential for functional biomimicry. Here, we present a soft robotics-driven approach for programmable 3D alignment in 3D bioprinted tissue. Our method introduces the co-printing of biological tissue with a silicone-based soft robot via a custom core-double shell nozzle. The application of 3D, exogenous, dynamic expansion and torsional forces to the tissue via the co-printed silicone robot was found to drive cell alignment. Confocal imaging revealed pronounced anisotropy of the stimulated tissue samples compared to the unstimulated controls. In addition, different cellular orientation patterns resulted from each mode of stimulation, demonstrating the versatility of the soft robotic approach in tailoring the pattern of tissue alignment based on programmed mechanostimulation.