bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pilot Study of a Digital Behavioral Therapy for Overactive Bladder in Women
Authors: Sooknarine Celine , Farrell Sylvia , Sarma Susmita , Salameh Fadi , Burke Naomi , Staunton Brendan , Carr Emma , Sexton K. , Agnew Gerry , Downey Andrew , D'Arcy Francis , Cundiff Geoffrey W. 
Published: March 2024

Importance
The burden and high prevalence of overactive bladder (OAB) underline the urgent need for effective treatment. This study provides an initial look at an alternative approach to behavioral therapy for overactive bladder (OAB) that is delivered as an app on a smartphone.

Objective
This study aimed to investigate feasibility, acceptability, and preliminary efficacy of a digital therapeutic for OAB.

Study Design
This was a multicentered prospective pilot study. We used a convenience sample (N = 30) from waiting lists of women referred for incontinence, excluding urinary tract infections, urinary retention, bladder pain syndrome, pelvic cancer, current pregnancy, kidney disease, dementia, stroke, and prior neuromodulation. The intervention, a smartphone app, provided an 8-week program with weekly modules combining evidence-based knowledge videos and skill-building exercises that incorporated behavioral therapy, cognitive behavioral therapy, pelvic muscle training, and general health information. Combined scores on the International Consultation on Incontinence Questionnaire was the primary outcome measure. Secondary outcomes included improvement in quality of life, based on International Consultation on Incontinence Questionnaire, a 72-hour urinary diary, and Patient Global Impression of Improvement. We evaluated usability with the Mobile Application Rating Scale. Statistical tests included Shapiro-Wilk tests and paired-sample t tests.

Results
Overall, 100% of participants reported a reduction in their OAB symptoms and 82% reported an improvement in quality of life. There was a significant improvement in diary parameters, including frequency (10.19–6.71 a day: SD, 1.25; P = 0.017) and incontinence (10–3.57: SD, 4.58). Participants rated the app highly on functionality, and 70% would recommend it. Patient Global Impression of Improvement improved for 69% of participants.

Conclusions
This study supports the application of a digital platform to over-come the real-world barriers for first-line treatment for OAB and offers information to inform further evaluation of the safety and efficacy of the NUIG OAB App.
Beta bursts in the parkinsonian cortico-basal ganglia network form spatially discrete ensembles
Authors: Grennan Isaac , Mallet Nicolas , Magill Peter J. , Cagnan Hayriye , Sharott Andrew 
Published: March 2024

AbstractDefining spatial synchronization of pathological beta oscillations is important, given that many theories linking them to parkinsonian symptoms propose a reduction in the dimensionality of the coding space within and/or across cortico-basal ganglia structures. Such spatial synchronization could arise from a single process, with widespread entrainment of neurons to the same oscillation. Alternatively, the partially segregated structure of cortico-basal ganglia loops could provide a substrate for multiple ensembles that are independently synchronized at beta frequencies. Addressing this question requires an analytical approach that identifiesgroupsof signals with a statistical tendency for beta synchronisation, which is unachievable using standard pairwise measures. Here, we utilized such an approach on multichannel recordings of background unit activity (BUA) in the external globus pallidus (GP) and subthalamic nucleus (STN) in parkinsonian rats. We employed an adapted version of a principle and independent component analysis-based method commonly used to define assemblies of single neurons (i.e., neurons that are synchronized over short timescales). This analysis enabled us to define whether changes in the power of beta oscillations in local ensembles of neurons (i.e., the BUA recorded from single contacts) consistently covaried over time, forming a “beta ensemble”. Multiple beta ensembles were often present in single recordings and could span brain structures. Membership of a beta ensemble predicted significantly higher levels of short latency (<5ms) synchrony in the raw BUA signal and phase synchronization with cortical beta oscillations, suggesting that they comprised clusters of neurons that are functionally connected at multiple levels, despite sometimes being non-contiguous in space. Overall, these findings suggest that beta oscillations do not comprise a single synchronization process, but rather multiple independent activities that can bind both spatially contiguous and non-contiguous pools of neurons within and across structures. As previously proposed, such ensembles provide a substrate for beta oscillations to constrain the coding space of cortico-basal ganglia circuits.
The neural dynamics of positive and negative expectations of pain
Authors: Wittkamp Christoph A. , Wolf Maren-Isabel , Rose Michael 
Published: March 2024

AbstractPain is heavily modulated by expectations. Whereas the integration of expectations with sensory information has been examined in some detail, little is known about how positive and negative expectations are generated and their neural dynamics from generation over anticipation to the integration with sensory information. The present preregistered study employed a novel paradigm to induce positive and negative expectations on a trial-by-trial basis and examined the neural mechanisms using combined EEG-fMRI measurements (n=50). We observed substantially different neural representations between the anticipatory and the actual pain period. In the anticipation phase i.e., before the nociceptive input, the insular cortex, dorsolateral prefrontal cortex (DLPFC), and anterior cingulate cortex (ACC) showed increased activity for directed expectations regardless of their valence. Interestingly, a differentiation between positive and negative expectations within the majority of areas only occurred after the arrival of nociceptive information. FMRI-informed EEG analyses could reliably track the temporal sequence of processing showing an early effect in the DLPFC, followed by the anterior insula and late effects in the ACC. The observed effects indicate the involvement of different expectation-related subprocesses, including the transformation of visual information into a value signal that is maintained and differentiated according to its valence only during stimulus processing.
De Novo TranscriptomeAnalysis Reveals Novel Insights into Secondary Metabolite Biosynthesis inTylophora indica(Burm. f) Merrill
Authors: Gupta Anamika , Singh Deeksha , Ranjan Rajiv 
Published: March 2024

AbstractTylophora indicahas been widely recognized for its therapeutic properties in traditional Indian medicine. Although its bioactive compounds are used extensively to treat a wide range of ailments, a comprehensive understanding of their genetic basis remains limited. In this study, we conducted a transcriptomic analysis ofT indicaleaf and root using the Illumina platform. High-quality RNA was isolated, and cDNA libraries were constructed for sequencing, generating4.67 GB and5.51 GB of data for leaf and root samples, respectively. 72,795 unigenes and 24,470 coding sequences (CDS) were predicted based on de novo assembly of reads, revealing a complex transcriptome landscape. Functional annotation and pathway analysis revealed biological processes and pathways associated withT indica. Based on the Gene Ontology (GO) mapping, the CDS was categorized into biological processes, cellular components, and molecular functions. An analysis of pathways using the KEGG database revealed involvement in critical metabolic pathways. Furthermore, SSRs contributed to the understanding of genetic diversity by identifying simple sequence repeats. In addition, differential gene expression analysis identified genes involved in secondary metabolite synthesis, among other physiological processes. The qRT-PCR validation of selected genes confirmed their differential expression profiles, with roots exhibiting higher expression than leaves. In this study, transcriptomics is conducted for the first time forT indica, which may be useful for future molecular research. The detailed findings help us understandT indica’sbiology, which can be used in biotechnology, and they also show how important it is to protect this species because it is used in medicine.
The Molecular Basis for Hydrodynamic Properties of PEGylated Human Serum Albumin
Authors: Fleming Patrick J. , Correia John J. , Fleming Karen G. 
Published: March 2024

ABSTRACTPolyethylene glycol conjugation provides a protective modification that enhances the pharmacokinetics and solubility of proteins for therapeutic use. A knowledge of the structural ensemble of these PEGylated proteins is necessary to understand the molecular details that contribute to their hydrodynamic and colligative properties. Because of the large size and dynamic flexibility of pharmaceutically important PEGylated proteins, the determination of structure is challenging. Here we demonstrate that structural ensembles, generated by coarse-grained simulations, can be analyzed with HullRad and used to predict sedimentation coefficients and concentration dependent hydrodynamic and diffusion nonideality coefficients of PEGylated proteins. A knowledge of these properties enhances the ability to design and analyze new modified protein therapeutics.STATEMENT OF SIGNIFICANCEProteins constitute a growing class of biotherapeutics. Chemical modification(s) with inert polymers are known to enhance the serum half-life and formulation of these biological therapeutics but the effects of modification on protein-protein interactions in solution have been difficult to predict. Here we describe methods for predicting the molecular basis for the hydrodynamic properties of polymer conjugated proteins that determine their solution behavior.
Introducing CHiDO – a No Code Genomic Prediction Software implementation for the Characterization & Integration of Driven Omics
Authors: González Francisco , García-Abadillo Julián , Jarquín Diego 
Published: March 2024

ABSTRACTClimate change represents a significant challenge to global food security by altering environmental conditions critical to crop growth. Plant breeders can play a key role in mitigating these challenges by developing more resilient crop varieties; however, these efforts require significant investments in resources and time. In response, it is imperative to use current technologies that assimilate large biological and environmental datasets into predictive models to accelerate the research, development, and release of new improved varieties. Leveraging large and diverse data sets can improve the characterization of phenotypic responses due to environmental stimuli and genomic pulses. A better characterization of these signals holds the potential to enhance our ability to predict trait performance under changes in weather and/or soil conditions with high precision. This paper introduces CHiDO, an easy-to-use, no-code platform designed to integrate diverse omics datasets and effectively model their interactions. With its flexibility to integrate and process data sets, CHiDO’s intuitive interface allows users to explore historical data, formulate hypotheses, and optimize data collection strategies for future scenarios. The platform’s mission emphasizes global accessibility, democratizing statistical solutions for situations where professional ability in data processing and data analysis is not available.Core ideasThe authors developed CHiDO, a platform for breeders to build predictive models integrating multi-omics data.CHiDO is a no-code tool that leverages the reaction norm model proposed by Jarquin et al. (2014).The platform aims to increase access to predictive analytics lowering relevant technical and financial barriers.
A model of task-level human stepping regulation yields semistable walking
Authors: Patil Navendu S. , Dingwell Jonathan B. , Cusumano Joseph P. 
Published: March 2024

AbstractA simple lateral dynamic walker, with swing leg dynamics and three adjustable input parameters, is used to study how motor regulation affects frontal plane stepping. Motivated by experimental observations and phenomenological models, we imposed task-level multiobjective regulation targeting the walker’s optimal lateral foot placement at each step. The regulator prioritizes achieving step width and lateral body position goals to varying degrees by choosing a mixture parameter. Our model thus integrates a lateralmechanical template, which captures fundamental mechanics of frontal-plane walking, with a lateralmotor regulation template, an empirically verified model of how humans manipulate lateral foot placements in a goal-directed manner. The model captures experimentally observed stepping fluctuation statistics and demonstrates how linear empirical models of stepping dynamics can emerge from first-principles nonlinear mechanics. We find that task-level regulation gives rise to a goal equivalent manifold in the system’s extended state space of mechanical states and inputs, a subset of which contains a continuum of period-1 gaits forming asemistableset: perturbations off of any of its gaits result in transients that return to the set, though typically to different gaits.
Maximum Likelihood Inference of Time-scaled Cell Lineage Trees with Mixed-type Missing Data
Authors: Mai Uyen , Chu Gillian , Raphael Benjamin J. 
Published: March 2024

AbstractRecent dynamic lineage tracing technologies combine CRISPR-based genome editing with single-cell sequencing to track cell divisions during development. A key computational problem in dynamic lineage tracing is to infer a cell lineage tree from the measured CRISPR-induced mutations. Three features of dynamic lineage tracing data distinguish this problem from standard phylogenetic tree inference. First, the CRISPR-editing process modifies a genomic location exactly once. Thisnon-modifiableproperty is not well described by the time-reversible models commonly used in phylogenetics. Second, as a consequence of non-modifiability, the number of mutations per time unit decreases over time. Third, CRISPR-based genome-editing and single-cell sequencing results in high rates of both heritable and non-heritable (dropout) missing data. To model these features, we introduce the Probabilistic Mixed-type Missing (PMM) model. We describe an algorithm, LAML (Lineage Analysis via Maximum Likelihood), to search for the maximum likelihood (ML) tree under the PMM model. LAML combines an Expectation Maximization (EM) algorithm with a heuristic tree search to jointly estimate tree topology, branch lengths and missing data parameters. We derive a closed-form solution for the M-step in the case of no heritable missing data, and a block coordinate ascent approach in the general case which is more efficient than the standard General Time Reversible (GTR) phylogenetic model. On simulated data, LAML infers more accurate tree topologies and branch lengths than existing methods, with greater advantages on datasets with higher ratios of heritable to non-heritable missing data. We show that LAML provides unbiasedtime-scaledestimates of branch lengths. In contrast, we demonstrate that maximum parsimony methods for lineage tracing data not only underestimate branch lengths, but also yield branch lengths which are not proportional to time, due to the nonlinear decay in the number of mutations on branches further from the root. On lineage tracing data from a mouse model of lung adenocarcinoma, we show that LAML infers phylogenetic distances that are more concordant with gene expression data compared to distances derived from maximum parsimony. The LAML tree topology is more plausible than existing published trees, with fewer total cell migrations between distant metastases and fewer reseeding events where cells migrate back to the primary tumor. Crucially, we identify three distinct time epochs of metastasis progression, which includes a burst of metastasis events to various anatomical sites during a single month.Softwarehttps://github.com/raphael-group/LAMLData availabilityhttps://github.com/raphael-group/laml-experiments
T cell polarization and NFAT translocation are stiffness-dependent and are differentially regulated by Piezo1 and Orai1
Authors: Zhao Renping , Zhang Jingnan , Schwarz Eva C. , del Campo Aránzazu , Hoth Markus , Qu Bin 
Published: March 2024

AbstractEffective T cell responses against tumor cells require diverse effector functions including polarization towards tumor cells to form immunological synapses and nuclear factor of activated T-cells (NFAT)-dependent gene transcription. While the role of tumor cell softening has been associated with malignancy, stemness, and metastasis, potentially contributing to immune evasion, its impact on cellular processes in T cells is not well understood. Here, we show that both T cell polarization and NFAT nuclear translocation are modulated by target stiffness in a Ca2+ dependent manner. Using both anti-CD3 antibody-functionalized substrates with varying stiffness as surrogates for target cells or softened tumor cells, we found that both, reorientation of microtubule organizing center (MTOC) towards the tumor cells, a hallmark for T cell polarization, and NFAT translocation were impaired on softer hydrogels or following contact with softer cancer cells. The amplitudes of intracellular Ca2+ signals were dependent on stiffness, and removal of extracellular Ca2+ inhibited stiffness-dependent T cell responsiveness. While stiffness-dependent Ca2+ signaling was crucial for both, T cell polarization and NFAT translocation, Ca2+ influx through Piezo1, a mechanosensitive ion channel, mediated stiffness-dependent MTOC reorientation but not NFAT translocation. In contrast, Ca2+ influx through store-operated Orai channels mediated NFAT translocation but not MTOC reorientation. Our results demonstrate that tumor cell stiffness directly influences T cell functionality through distinct Ca2+ influx pathways, revealing cell softening as an essential mechanism employed by malignant cells to evade immune surveillance.
LncRNA BRE-AS1 Regulates the JAK2/STAT3-mediated Inflammatory Activation via the miR-30b-5p/SOC3 Axis in THP-1 cells
Authors: Shin Jae-Joon , Suk Kyoungho , Lee Won-Ha 
Published: March 2024

AbstractLong non-coding RNAs (lncRNAs) have emerged as pivotal regulators in numerous biological processes, including macrophage-mediated inflammatory responses, which play a critical role in the progress of diverse diseases. This study focuses on the regulatory function of lncRNA BRE-AS1 in modulating the inflammatory activation of monocytes/macrophages. Employing the THP-1 cell line as a model, we demonstrate that lipopolysaccharide (LPS) treatment significantly upregulates BRE-AS1 expression. Notably, specific knockdown of BRE-AS1 via siRNA transfection enhances LPS-induced expression of interleukin (IL)-6 and IL-1β, while not affecting tumor necrosis factor (TNF)-α levels. This selective augmentation of pro-inflammatory cytokine production coincides with increased phosphorylation of JAK2 and STAT3. Furthermore, BRE-AS1 suppression results in the downregulation of SOCS3, an established inhibitor of the JAK2/STAT3 pathway. Bioinformatics analysis identified binding sites for miR-30b-5p on both BRE-AS1 and SOCS3 mRNA. Intervention with a miR-30b-5p inhibitor and a synthetic RNA fragment that represents the miR-30b-5p binding site on BRE-AS1 attenuates the pro-inflammatory effects of BRE-AS1 knockdown. Conversely, a miR-30b-5p mimic replicated the BRE-AS1 attenuation outcomes. Our findings elucidate the role of lncRNA BRE-AS1 in modulating inflammatory activation in THP-1 cells via the miR-30b-5p/SOCS3/JAK2/STAT3 signaling pathway, proposing that manipulation of macrophage BRE-AS1 activity may offer a novel therapeutic avenue in diseases characterized by macrophage-driven pathogenesis.
The activation ofChlamydomonas reinhardtiialpha amylase 2 by glutamine requires its N-terminal ACT domain
Authors: Scholtysek Lisa , Poetsch Ansgar , Hofmann Eckhard , Hemschemeier Anja 
Published: March 2024

AbstractThe coordination of assimilation pathways for all the elements that make up cellular components is a vital task for every organism. Integrating the assimilation and use of carbon (C) and nitrogen (N) is of particular importance because of the high cellular abundance of these elements. Starch is one of the most important storage polymers of photosynthetic organisms, and a complex regulatory network ensures that biosynthesis and degradation of starch are coordinated with photosynthetic activity and growth. Here, we analyzed three starch metabolism enzymes ofChlamydomonas reinhardtiithat we captured by a cyclic guanosine monophosphate-(cGMP-) affinity chromatography approach, namely soluble starch synthase STA3, starch branching enzyme SBE1 and α-amylase AMA2. While none of the recombinant enzymes was directly affected by the presence of cGMP or other nucleotides, suggesting an indirect binding to cGMP, AMA2 activity was stimulated in the presence of L-glutamine (Gln). This activating effect required the enzyme’s N-terminal aspartate kinase–chorismate mutase– tyrA (ACT) domain. Gln is the first N assimilation product and not only a central compound for the biosynthesis of N-containing molecules, but also a recognized signaling molecule for the N status. Our observation suggests that AMA2 might be a means to coordinate N- and C metabolism at the enzymatic level, increasing the liberation of C-skeletons from starch when high Gln levels signal an abundance of assimilated N.
The strength of sexual signals predicts same-sex paring in termites
Authors: Mizumoto Nobuaki , Lee Sang-Bin , Chouvenc Thomas 
Published: March 2024

AbstractSame-sex sexual behavior (SSB) is an enigma in behavioral ecology as it does not result in reproduction. Proximately, the evolution of sexual signals is critical for the evolution of SSB in a sex-specific manner. For signal receivers, the loss of sexual signals leads to smaller phenotypic sex differences, leading to frequent accidental SSB between receivers. Alternatively, for senders, sexual signals could help locate another sender, enhancing intentional SSB as in heterosexual pairing. Here, we demonstrate this link between sex pheromone signaling and the frequency of same-sex pairing in twoCoptotermestermites that use the same chemical as sex pheromones but in different quantities. In termites, mating pairs engage in tandem runs, where a male follows a female with sex pheromones. We found that female-female tandems were more stable inC. formosanus,whose females produce more pheromones, while the male-male interactions were more frequent inC. gestroi, whose females produce fewer pheromones. Thus, stronger pheromones lead to sender-sender SSB, while weaker pheromones lead to receiver-receiver SSB. In both species, same-sex tandems were less stable than heterosexual tandems, contrasting withReticulitermes, another termite group that shows frequent same-sex tandems. The proximate mechanism of SSB is diverse, reflecting the heterosexual context.