bluuebunny/crossref_metadata_2025_split huggingface dataset:
Maximizing meiotic crossover rate reveals the map of Crossover Potential
Authors: Jing Juli , Lian Qichao , Durand Stephanie , Mercier Raphael 
Published: November 2024

AbstractMeiotic crossovers are limited in number and unevenly distributed along chromosomes, both features often differing between sexes. The mechanisms imposing a different crossover landscape in female and male meiosis remain elusive. Here, we simultaneously disrupted multiple anti-crossover mechanisms in Arabidopsis and analyzed the whole genome sequence of thousands of female- and male-derived progenies. The largest crossover increase was reached inzyp1 recq4, with 12-fold in females and a 4.5-fold increase in males. Despite this unprecedented level of crossovers, fertility is marginally affected, opening new possibilities for plant breeding. Manipulating additional crossover regulators inzyp1 recq4did not further elevate the frequency of crossovers, but modified the relative contributions of the two known crossover pathways. This suggests an upper limit was reached and the two pathways compete for a large but limited set of recombination intermediates. Remarkably, while wild-type crossover distribution differs markedly between sexes, the crossover landscapes of diverse mutants in both females and males converge to a single novel profile, which we termed Crossover Potential (COP). The COPprofile, which we defined using 49,482 crossovers, can be accurately predicted using only sequence divergence and chromatin features. We propose that the COPrepresents the density of eligible recombination precursors, which is determined by genomic features and is thus identical in females and males. It suggests that the sexual dimorphism in the crossover landscape results exclusively from differential regulation of the likeness of precursors to mature into crossovers.
The Impact of Brain-Derived Neurotrophic Factor Polymorphism and Stimulation Parameters on the Response to Repetitive Transcranial Magnetic Stimulation: A Systematic Review
Authors: Kuo Yi-Ling , Lin Gracy , Glatt Stephen J. 
Published: November 2024

ABSTRACTIntroductionTMS has been a common technique used to stimulate neuromodulatory changes, which can have therapeutic effects. The underlying mechanism is still unknown, however it is thought to cause neuroplastic changes via LTD or LTP. However, the effects are highly variable, with demographics and baseline physiology thought to be playing a role.ObjectivesThe purposes of this systematic review were to 1) examine how BDNF polymorphisms are related to the after-effects of rTMS in humans and 2) investigate the association between BDNF polymorphism and rTMS stimulation parameters as contributing factors to the response to rTMS.Materials and MethodsStudies identified from PubMed, The Cochrane Library, and Embase were screened for eligibility. Data were extracted from the selected studies by one reviewer and verified by another reviewer. Risk of Bias was assessed using the Cochrane Collaboration’s tool. Results were synthesized narratively.ResultsOf the 224 initial studies, 35 were included in this systematic review. 33 out of 35 studies had at least one domain of high or unclear risk of bias. 53% of the studies in healthy individuals showed differences in TMS-derived or behavioral measures between Val/Val homozygotes and Met allele carriers. The neuromodulatory effects were more reliable in Val/Val homozygotes than Met allele carriers. In stroke, neuromodulatory effects on corticospinal excitability and motor deficits were more evident in Val/Val homozygotes than Met allele carriers. Similarly, in depression, Val/Val homozygotes demonstrated more improvement in depression symptoms compared with Met allele carriers following rTMS. The role of BDNF polymorphism in other disorders remained unclear.ConclusionIt remains inconclusive whether and how BDNF genotype impacts the effects of rTMS. Methodological heterogeneity in the stimulation parameters, such as dosage and excitatory or inhibitory protocols, interact with BDNF polymorphism and contribute to the response to rTMS.
A functional neuroimaging biomarker of mild cognitive impairment using TD-fNIRS
Authors: Dubois Julien , Duffy John Gregory , Field Ryan M. , Koch Erin M. , M. Aghajan Zahra , Miller Naomi , Perdue Katherine L. , Sahagian Gregory , Taylor Moriah 
Published: November 2024

AbstractINTRODUCTIONDiagnostic assessments of mild cognitive impairment (MCI) are lengthy and burdensome, highlighting the need for new tools to detect MCI. Time-domain functional near-infrared spectroscopy (TD-fNIRS) can measure brain function in clinical settings and may address this need.METHODSMCI patients (n=50) and age-matched healthy controls (HC; n=51) underwent TD-fNIRS recordings during cognitive tasks (verbal fluency, N-back). Machine learning models were trained to distinguish MCI from HC using neural activity, cognitive task behavior, and self-reported impairment as input features.RESULTSSignificant group-level differences (MCI vs HC) were demonstrated in self-report, N-back and verbal fluency behavior, and task-related brain activation. Classifier performance was similar when using self-report (AUC=0.76) and self-report plus behavior (AUC=0.79) as input features, but was strongest when neural metrics were included (AUC=0.92).DISCUSSIONThis study demonstrates the potential of TD-fNIRS to assess MCI with short brain scans in clinical settings.
Changing patterns of nicotine product use and nicotine dependence among US high school students: the National Youth Tobacco Survey, 2014-2023
Authors: Jackson Sarah E. , Brown Jamie , Tattan-Birch Harry , Jarvis Martin J. 
Published: November 2024

AbstractBackgroundConcerns have been raised that e-cigarettes have created a new generation of people addicted to nicotine. This study aimed to examine changes in the proportion of US high-school students reporting symptoms of nicotine dependence over the past decade, in the context of changing patterns of nicotine product use.MethodsRepeat cross-sectional analyses of a nationally-representative sample of 107,968 US high-school students (14-18y) participating in the 2014-2023 National Youth Tobacco Surveys. Nicotine product use was categorised based on self-reported past-30-day use of cigarettes, other combustible tobacco, smokeless/non-combustible products, and e-cigarettes. Nicotine dependence was operationalised as (i) strong past-30-day cravings to use tobacco and (ii) wanting to use nicotine products within 30 minutes of waking.ResultsPast-30-day use of any nicotine product decreased from 24.5% [22.5-26.6%] to 19.6% [16.8-22.4%] between 2014 and 2017, increased sharply reaching 31.4% [29.0-33.7%] in 2019, then fell to the lowest level at 12.5% [10.9-14.1%] by 2023. The proportion who reported symptoms of nicotine dependence was substantially lower, but followed a similar pattern of changes over time. For example, the proportion reporting strong cravings decreased from 7.8% [6.6-9.0%] to 5.5% [4.3-6.7%] between 2014 and 2017, increased to 7.9% [6.8-9.0%] between 2017 and 2018 and remained stable up to 2020, then fell to the lowest level at 2.5% [1.9-3.1%] by 2023. Use of cigarettes fell considerably across the period (from 9.0% [7.9-10.3%] to 1.8% [1.4-2.4%]); this was the product category consistently associated with the highest levels of dependence. The proportion using only e-cigarettes increased rapidly between 2017 and 2019 (from 5.4% [4.2-6.8%] to 17.0% [15.3-18.7%]) then fell to 6.7% [5.6-7.9%] by 2023; symptoms of nicotine dependence within this group increased non-linearly over time with increases through to 2022 before possible declines in 2023.ConclusionsThe sharp rise in the prevalence of nicotine product use (in particular, e-cigarettes) among US high-school students in the late 2010s was short-lived and was not accompanied by a sustained increase in the overall population burden of nicotine dependence. By 2023, both nicotine product use and nicotine dependence had reached historic lows.
MEDiCINe: Motion Correction for Neural Electrophysiology Recordings
Authors: Watters Nicholas , Buccino Alessio , Jazayeri Mehrdad 
Published: November 2024

AbstractElectrophysiology recordings from the brain using laminar multielectrode arrays allow researchers to measure the activity of many neurons simultaneously. However, laminar microelectrode arrays move relative to their surrounding neural tissue for a variety of reasons, such as pulsation, changes in intracranial pressure, and decompression of neural tissue after insertion. Inferring and correcting for this motion stabilizes the recording and is critical to identify and track single neurons across time. Such motion correction is a preprocessing step of standard spike sorting methods. However, estimating motion robustly and accurately in electrophysiology recordings is challenging due to the stochasticity of the neural data. To tackle this problem, we introduce MEDiCINe (Motion Estimation by Distributional Contrastive Inference for Neurophysiology), a novel motion estimation method. We show that MEDiCINe outperforms existing motion estimation methods on an extensive suite of simulated neurophysiology recordings and leads to more accurate spike sorting. We also show that MEDiCINe correctly estimates the motion in primate electrophysiology recordings with a variety of motion and stability statistics. We open-source MEDiCINe, usage instructions, examples integrating MEDiCINe with common tools for spike-sorting, and data and code for reproducing our results. This open software will enable other researchers to use MEDiCINe to improve spike sorting results and get the most out of their electrophysiology datasets.
C-C bond cleavage and generation in TCA cycle driven by radicals and peroxo-bridge like interaction
Authors: Yang Lin , Fang Yijun , Gong Weimin 
Published: November 2024

AbstractTricarboxylic acid (TCA) cycle is one of the most important and common metabolic pathways in different kingdoms of life, in which citrate synthase catalyzes the first irreversible reaction and the rate-limiting step. Reversed oxidative tricarboxylic acid (roTCA) cycle is a newly discovered autotrophic CO2fixation pathway based on the reversal of TCA cycle, in which citrate synthase catalyzes the thermodynamically unfavorable citrate cleavage reaction. In this work, we proposed that radicals promote C-C bond cleavage of citrate in roTCA cycle based on series intermediate catalytic state of citrate synthases fromDesulfurella acetivoran(DaCS) andThermosulfidibacter takaii(TtCS) obtained by electron paramagnetic resonance (EPR) and X-ray crystallography. We also proposed that the peroxo-bridge like interaction promotes C-C bond generation between acetyl group and oxaloacetate in citrate synthesis reaction based on intermediate state of human citrate synthase by time-resolved characteristic Raman spectroscopy and X-ray diffraction methods. Results also indicate these mechanisms would be widespread among conserved citrate synthases.
When Little Means a Lot: Impact of a Brief Early-life Motor Training on Mouse Neuromuscular Development
Authors: Quilgars Camille , Boué-Grabot Eric , de Deurwaerdère Philipe , Cazalets Jean-René , Perrin Florence E. , Bertrand Sandrine S. 
Published: November 2024

ABSTRACTIn this study, we aimed to determine the impact of an increase in motor activity during the highly plastic period of development of the motor spinal cord and hindlimb muscles in newborn mice. A swim training regimen, consisting of two sessions per day for two days, was conducted in 1 and 2-day-old (P1, P2) pups. P3-trained pups showed a faster acquisition of a four-limb swimming pattern, accompanied by dysregulated gene expression in the lateral motor column, alterations in the intrinsic membrane properties of motoneurons (MNs) and synaptic plasticity, as well as increased axonal myelination in motor regions of the spinal cord. Network-level changes were also observed, as synaptic events in MNs and spinal noradrenaline and serotonin contents were modified by training. At the muscular level, slight changes in neuromuscular junction morphology and myosin subtype expression in hindlimb muscles were observed in trained animals. Furthermore, the temporal sequence of acquiring the adult-like swimming pattern and postural development in trained pups showed differences persisting until almost the second postnatal week. A very short motor training performed just after birth is thus able to induce functional adaptation in the developing neuromuscular system that could persist several days. This highlights the vulnerability of the neuromuscular apparatus during development and the need to evaluate carefully the impact of any given sensorimotor procedure when considering its application to improve motor development or in rehabilitation strategies.
Lifetime brain atrophy estimated from a single MRI: measurement characteristics and genome-wide correlates
Authors: Fürtjes Anna E. , Foote Isabelle F. , Xia Charley , Davies Gail , Moodie Joanna , Taylor Adele , Liewald David C. , Redmond Paul , Corley Janie , McIntosh Andrew M. , Whalley Heather C. , Maniega Susana Muñoz , Hernández Maria Valdés , Backhouse Ellen , Ferguson Karen , Bastin Mark E. , Wardlaw Joanna , de la Fuente Javier , Grotzinger Andrew D. , Luciano Michelle , Hill W. David , Deary Ian J. , Tucker-Drob Elliot M. , Cox Simon R. 
Published: November 2024

AbstractA measure of lifetime brain atrophy (LBA) obtained from a single magnetic resonance imaging (MRI) scan could be an attractive candidate to boost statistical power in uncovering novel genetic signals and mechanisms of neurodegeneration. We analysed data from five young and old adult cohorts (MRi-Share, Human Connectome Project, UK Biobank, Generation Scotland Subsample, and Lothian Birth Cohort 1936 [LBC1936]) to test the validity and utility of LBA inferred from cross-sectional MRI data, i.e., a single MRI scan per participant. LBA was simply calculated based on the relationship between total brain volume (TBV) and intracranial volume (ICV), using three computationally distinct approaches: the difference (ICV-TBV), ratio (TBV/ICV), and regression-residual method (TBV∼ICV). LBA derived with all three methods were substantially correlated with well-validated neuroradiological atrophy rating scales (r= 0.37-0.44). Compared with the difference or ratio method, LBA computed with the residual method most strongly captured phenotypic variance associated with cognitive decline (r= 0.36), frailty (r= 0.24), age-moderated brain shrinkage (r= 0.45), and longitudinally-measured atrophic changes (r= 0.36). LBA computed using a difference score was strongly correlated with baseline (i.e., ICV;r= 0.81) and yielded GWAS signal similar to ICV (rg= 0.75). We performed the largest genetic study of LBA to date (N= 43,110), which was highly heritable (h2SNP GCTA= 41% [95% CI = 38-43%]) and had strong polygenic signal (LDSCh2= 26%; meanχ2= 1.23). The strongest association in our genome-wide association study (GWAS) implicatedWNT16, a gene previously linked with neurodegenerative diseases such as Alzheimer, and Parkinson disease, and amyotrophic lateral sclerosis. This study is the first side-by-side evaluation of different computational approaches to estimate lifetime brain changes and their measurement characteristics. Careful assessment of methods for LBA computation had important implications for the interpretation of existing phenotypic and genetic results, and showed that relying on the residual method to estimate LBA from a single MRI scan captured brain shrinkage rather than current brain size. This makes this computationally-simple definition of LBA a strong candidate for more powerful analyses, promising accelerated genetic discoveries by maximising the use of available cross-sectional data.
Details matter! Multimodal personalization increases the efficacy of transcranial direct current stimulation for modulation of sensorimotor integration
Authors: Radecke Jan-Ole , Kühn Alexander , Erdbrügger Tim , Buschermöhle Yvonne , Rashidi Sogand , Stöckler Hannah , Sack Benjamin , Borgwardt Stefan , Schneider Till R. , Gross Joachim , Wolters Carsten H. , Sprenger Andreas , Lencer Rebekka 
Published: November 2024

AbstractNeural networks subserving smooth pursuit eye movements provide an ideal model for investigating the modulation of sensorimotor integration during ongoing movements by transcranial direct current stimulation (tDCS). Within these networks, visual motion area V5 is a core hub to integrate visual motion information with oculomotor control. Here, we applied personalized tDCS explicitly targeting individual V5 in healthy human participants using algorithmic optimization informed by functional MRI and combined EEG/MEG. We hypothesized subtle impairment or facilitation of sensorimotor integration during pursuit and assessed the gain by personalized, compared to conventional normative tDCS. Indeed, pursuit initiation was specifically delayed during personalized cathodal tDCS targeting right V5 pointing towards the involvement of distinct functional subareas of V5. The results were well- controlled by anodal and sham tDCS, different pursuit tasks, and by two additional control experiments, one that applied personalized tDCS targeting FEF and another that applied normative tDCS over V5, for all of which no pursuit modulation was observed. Importantly, in contrast to normative tDCS, personalized tDCS effectively modulated pursuit by adapting electric fields to individual anatomical and functional V5 properties. Our results indicate the huge potential of personalized tDCS and transcranial electric stimulation in general to alter behavior as the main aspect of interest in human neuromodulation.
Measuring Stimulus Information Transfer Between Neural Populations through the Communication Subspace
Authors: Weiss Oren , Coen-Cagli Ruben 
Published: November 2024

AbstractSensory processing arises from the communication between neural populations across multiple brain areas. While the widespread presence of neural response variability shared throughout a neural population limits the amount of stimulus-related information those populations can accurately represent, how this variability affects the interareal communication of sensory information is unknown. We propose a mathematical framework to understand the impact of neural population response variability on sensory information transmission. We combine linear Fisher information, a metric connecting stimulus representation and variability, with the framework of communication subspaces, which suggests that functional mappings between cortical populations are low-dimensional relative to the space of population activity patterns. From this, we partition Fisher information depending on the alignment between the population covariance and the mean tuning direction projected onto the communication subspace or its orthogonal complement. We provide mathematical and numerical analyses of our proposed decomposition of Fisher information and examine theoretical scenarios that demonstrate how to leverage communication subspaces for flexible routing and gating of stimulus information. This work will provide researchers investigating interareal communication with a theoretical lens through which to understand sensory information transmission and guide experimental design.
Effects of Aging on the Immune and Periosteal Response to Fracture in Mice
Authors: King Justin S , Wan Matthew , Kim Adam , Novak Sanja , Prabhu Shagun , Kalajzic Ivo , Delany Anne M , Sanjay Archana 
Published: November 2024

AbstractAging predisposes individuals to reduced bone mass and fragility fractures, which are costly and linked to high mortality. Understanding how aging affects fracture healing is essential for developing therapies to enhance bone regeneration in older adults. During the inflammatory phase of fracture healing, immune cells are recruited to the injury site as periosteal skeletal stem/progenitor cells (pSSPCs) rapidly proliferate and differentiate into osteochondral lineages, allowing for fibrocartilaginous callus formation and complete bone healing. Irrespective of age, how periosteal mesenchymal and immune cells interact during early fracture healing is incompletely understood, limiting our ability to potentially modulate these processes. To address this, we directly analyzed, in parallel, at a single-cell level, isolated murine CD45(+) and CD45(-) periosteal cells dissected from intact and fractured bones, collected three days after injury. Through comprehensive analysis, corroborated by bulk RNA-sequencing, flow cytometry, and histology, we found aging decreases pSSPCs proliferative, marked by a reduced expression of genes required for callus formation and an increased senescence signature. We found that the chemokineCxcl9was highly upregulated in aged intact Prrx1+ pSSPCs, predicted to interact with other pSSPCs directly, and associated with increased recruitment of CD8+ T cells at the fracture site three days after injury. Cell-to-cell communication analysis provided insight into the complexity of interactions among the many cell types regulating fracture healing and the impact of aging on these processes. Together, these results provide insight into age-induced alterations in fracture healing, informing the development of improved therapeutic approaches for fragility fractures.
Olfactory bulb tracks breathing rhythms and place in freely behaving mice
Authors: Sterrett Scott C. , Findley Teresa M. , Rafilson Sidney E. , Brown Morgan A. , Weible Aldis P , Marsden Rebecca , Tarvin Takisha , Wehr Michael , Murray James M. , Fairhall Adrienne L. , Smear Matthew C. 
Published: November 2024

AbstractVertebrates sniff to control the odor samples that enter their nose. These samples can not only help identify odorous objects, but also locations and events. However, there is no receptor for place or time. Therefore, to take full advantage of olfactory information, an animal’s brain must contextualize odor-driven activity with information about when, where, and how they sniffed. To better understand contextual information in the olfactory system, we captured the breathing and movements of mice while recording from their olfactory bulb. In stimulus- and task-free experiments, mice structure their breathing into persistent rhythmic states which are synchronous with statelike structure in ongoing neuronal population activity. These population states reflect a strong dependence of individual neuron activity on variation in sniff frequency, which we display using “sniff fields” and quantify using generalized linear models. In addition, many olfactory bulb neurons have “place fields” that display significant dependence of firing on allocentric location, which were comparable with hippocampal neurons recorded under the same conditions. At the population level, a mouse’s location can be decoded from olfactory bulb with similar accuracy to hippocampus. Olfactory bulb place sensitivity cannot be explained by breathing rhythms or scent marks. Taken together, we show that the mouse olfactory bulb tracks breathing rhythms and self-location, which may help unite internal models of self and environment with olfactory information as soon as that information enters the brain.