bluuebunny/crossref_metadata_2025_split huggingface dataset:
Muscle-specific Keap1 deletion enhances force production but does not prevent inactivity-induced muscle atrophy in mice
Authors: Miranda Edwin R. , Shahtout Justin L. , Watanabe Shinya , Milam Norah , Karasawa Takuya , Rout Subhasmita , Atkinson Donald L. , Holland William L. , Drummond Micah J. , Funai Katsuhiko 
Published: October 2024

AbstractImmobilization-associated muscle atrophy and weakness appear to be driven in part by oxidative stress. Nuclear Factor Erythroid 2-Related Factor 2 (NRF2) is a critical redox rheostat that regulates oxidative stress responses, and its deletion is known to accelerate muscle atrophy and weakness during aging (sarcopenia) or denervation. Conversely, pharmacologic activation of NRF2 extends mouse lifespan and attenuates sarcopenia. Similarly, deletion of Kelch-like ECH-associated Protein 1 (Keap1), negative regulator of NRF2, enhances exercise capacity. The purpose of this study was to determine whether muscle-specific Keap1 deletion is sufficient to prevent muscle atrophy and weakness in mice following 7-days of hindlimb unloading (HU). To test this hypothesis, control (Ctrl) and tamoxifen inducible, muscle-specific Keap1 knockout (mKO) mice were subjected to either normal housing (Sham) or HU for 7 days. Activation of NRF2 in muscle was confirmed by increased mRNA of NRF2 targets thioredoxin 1 (Txn1) and NAD(P)H quinone dehydrogenase 1 (NQO1) in mKO mice. Keap1 deletion had an effect to increase force-generating capacity at baseline. However, muscle masses, cross sectional area, andex vivoforce were not different between mKO and Ctrl HU mice. In addition, muscle 4-hydroxynonenal-modified proteins and protein carbonyls were unaffected by Keap1 deletion. These data suggest NRF2 activation improves muscle force production during ambulatory conditions but is not sufficient prevent muscle atrophy or weakness following 7-days of HU.Graphical Abstract
Long deletion signatures in repetitive genomic regions track somatic evolution and enable sensitive detection of microsatellite instability
Authors: Guo Qingli , Househam Jacob , Lakatos Eszter , Nowinski Salpie , Al Bakir Ibrahim , Grant Heather , Balarajah Vickna , Hughes Christine S. , Zapata Luis , Kocher Hemant M , Sottoriva Andrea , Baker Ann-Marie , Mustonen Ville , Graham Trevor A. 
Published: October 2024

AbstractDeficiency in the mismatch repair system (MMRd) causes microsatellite instability (MSI) in cancers and determines eligibility for immunotherapy. Here, we show that MMRd tumours harbour long-deletion signatures (≥2-5+ base pairs deleted in repetitive regions), which provide new insights into MSI evolution and enable sensitive MSI detection particularly in challenging clinical samples. Long deletions, accumulated through stepwise DNA slippage errors, are significantly more prevalent in metastatic MMRd tumours compared to primary tumours. Importantly, we show that long-deletion signatures harbour features that are distinct from background noise, making them robustly detectable even in shallow whole genome sequencing (sWGS, ∼0.1X coverage) of formalin-fixed samples. We constructed a machine learning classifier that uses these distinct features to detect Microsatellite Instability in LOw-quality (MILO) samples. MILO achieved 100% accuracy in detecting MSI in sWGS data with only 2%-15% tumour purity and demonstrated promise in identifying MMRd clones in precancerous intestinal lesions. We propose that MILO could be clinically used for the sensitive monitoring of MMRd cancer evolution from early to late stages, using minimal sequencing data from both archival and fresh-frozen samples with low tumour content.SignificanceMutational signatures characterised by long deletions in repetitive genomic regions provide a sensitive route to detect and track MMRd clone evolution, even with low purity shallow whole genome sequencing data.
Regulation of REM Sleep Onset and Homeostasis by Preoptic Glutamatergic Neurons
Authors: Mondino Alejandra , Jadidian Amir , Toth Brandon , Hambrecht-Wiedbusch Viviane S. , Floran-Garduno Leonor , Li Duan , York A. Kane , Torterolo Pablo , Pal Dinesh , Burgess Christian , Mashour George A. , Vanini Giancarlo 
Published: October 2024

ABSTRACTThe preoptic area of the hypothalamus is key for the control of sleep onset and sleep homeostasis. Although traditionally considered exclusively somnogenic, recent studies identified a group of preoptic glutamatergic neurons that promote wakefulness. Specifically, our previous investigations demonstrated that chemogenetic stimulation of glutamatergic neurons within the medial-lateral preoptic area (MLPO_VGLUT2) promotes wakefulness, fragments non-rapid eye movement sleep (NREMs), and suppresses REM sleep (REMs). This evidence is further supported by recent work showing that preoptic glutamatergic neurons are activated during microarousals that fragment sleep in response to stress, and optogenetic stimulation of these neurons promotes microarousals and wakefulness. Thus, while the wake-promoting function of MLPO_VGLUT2 is clear, their role in sleep homeostasis has not been assessed. We tested the hypothesis that MLPO_VGLUT2 are wake-active, and their activation will increase wakefulness and disrupt sleep homeostasis via projections to arousal-promoting systems. Using fiber photometry, we found that MLPO_VGLUT2 were highly active during REMs, wakefulness and brief arousals, and remained minimally active during NREMs. Chemogenetic stimulation of MLPO_VGLUT2 inhibited REMs onset and suppressed the REMs homeostatic response after total sleep deprivation. Chemogenetic inhibition of MLPO_VGLUT2 increased REMs time (during the light phase only) but did not influence REMs and NREMs homeostasis. Anterograde projection mapping revealed that MLPO_VGLUT2 innervate central regions that promote wakefulness and inhibit REMs. We conclude that MLPO_VGLUT2 powerfully suppress REMs and that exogenous —and possibly pathologic— activation of these neurons disrupts REMs recovery, presumably by directly or indirectly activating REMs-inhibitory mechanisms.SIGNIFICANCE STATEMENTThe preoptic area of the hypothalamus has been extensively studied and its role in sleep regulation is well-established. Importantly, recent work identified a group of preoptic glutamatergic neurons (MLPO_VGLUT2) that are wake-active and promote wakefulness. However, whether these neurons influence sleep homeostasis remains unknown. We demonstrate that MLPO_VGLUT2 are maximally active during REM sleep (REMs), wakefulness and brief arousals from sleep, and innervate wake-promoting and REMs-inhibitory regions. MLPO_VGLUT2 stimulation inhibits REMs and REMs rebound after sleep deprivation, whereas their inactivation increases REMs but does not alter REMs homeostatic response. We thus identified a preoptic mechanism that powerfully suppresses REMs, which we propose may engage during normal sleep-to-wake transitions to block REMs intrusions into subsequent wakefulness.
STRUCT: a statistical approach to identify RNA secondary structures from raw sequencing data, bypassing multiple sequence alignment
Authors: Wang Julie Fangran , Rustagi Arjun , Salzman Julia 
Published: October 2024

AbstractRNA secondary and tertiary structures are essential to life. Experimental methods to detect RNA structure, such as X-ray crystallography and chemical probing, are incisive but suffer from low throughput and dimensionality. Computational approaches, leveraging evolutionary signals from correlated mutations, provide an alternative means to infer RNA structures. However, these methods require assembly and face challenges due to statistical biases inherent in multiple sequence alignment (MSA). Furthermore, these methods cannot exploit a given RNA element’s full spectrum of natural sequence variations. Here, we introduce STRUCT (StatisticalTesting ofRNAUnits withCovariationTraits), an assembly-free, MSA-free, and metadata-free statistical method for identifying conserved RNA structures from raw sequencing data, quantifying base-pair covariations or stem variation exclusion in the putative RNA structures. We show STRUCT rediscovers known HIV structural elements and identifies conserved rRNA structures in metatranscriptomics samples. Moreover, STRUCT finds viral structures in mosquito metatranscriptomics samplesde novo, including previously unannotated viral genomes, highlighting the method’s potential for viral discovery. STRUCT is an ultra-fast, easy-to-use, and robust tool that excels in high-throughput RNA structure prediction and hypothesis generation, presenting a novel approach for discovering structural RNA elements.
Test-retest reliability of perturbation-evoked cortical activity reflects stable individual differences in reactive balance control
Authors: Mirdamadi Jasmine L. , Poorman Alex , Munter Gaetan , Jones Kendra , Ting Lena H. , Borich Michael R. , Payne Aiden M. 
Published: October 2024

AbstractThere is a growing interest in measuring cortical activity during balance control for understanding mechanisms of impaired balance with aging and neurological dysfunction. The most well-characterized electrophysiological signal elicited by a balance disturbance is the perturbation-evoked N1 potential that peaks 100-200 msec post-perturbation and is thought to reflect error processing. We previously found associations between the N1 and individual differences in balance ability, suggesting it may be a potential biomarker of balance health. However, a potential biomarker of balance function will be limited by its reliability and clinical feasibility, which has yet to be established. Here, we characterized the reliability of the N1 elicited by standing balance perturbations within and between sessions over a one-week interval in 10 younger and 14 older adults. A subset of older adults (n=12) completed a session approximately one year prior to the main experiment. We extracted N1 amplitude and latency from the Cz electrode using an advanced, computationally-intensive approach that relies on large amounts of data (e.g., 64 channels, many trials), Test-retest reliability was assessed using the intra-class correlation coefficient (ICC). Internal consistency was quantified by split-half reliability using the Spearman correlation coefficient. N1s varied across individuals (amplitude:12-82µV, latency: 142-282ms), yet within individuals, the N1 showed excellent test-retest reliability (ICC>0.9) across a one-week and one-year time span. N1 amplitude reached excellent internal reliability for each session and group (r>0.9), that generally plateaued within 6 trials, while more trials were needed to reliably measure N1 latency. Similar results were obtained when quantifying N1s using a minimal approach performed with only three electrodes and simple preprocessing. Overall, the N1 is stable within and across sessions, and is largely independent of approach suggesting it could be a clinically-feasible biomarker of balance function. Characterizing reliability in populations with neurologic dysfunction and in different environmental contexts will be necessary to enhance our understanding of the N1, optimize experimental design, and determine its predictive validity of clinical outcomes (e.g., falls risk).
More cells, more doublets in sample-barcoded single-cell data
Authors: Howitt George , Dixit Gunjan , Aharon Rotem , Streeton-Cook Victoria , Ling Ling , Hickey Peter F. , Amann-Zalcenstein Daniela , Gubbels Liam , Shanthikumar Shivanthan , Ranganathan Sarath , Neeland Melanie R. , Maksimovic Jovana , Oshlack Alicia 
Published: October 2024

AbstractSample-specific barcoding of each molecule in single-cell RNA-sequencing experiments allows deconvolution of RNA from different cells captured together within a droplet. However, this is only possible when each cell comes from a different sample. As the number of cells in a droplet increases, the probability of two or more cells coming from the same sample increases rapidly. We show that the number of these unresolvable multiplets is greater than previously estimated in the 10X Flex scRNA-seq protocol, and provide a formula for estimating the fraction of multiplets in a data set given a measured average droplet occupancy and number of unique samples in a pool. We also show that existing doublet detection tools should be applied to Flex data to identify these multiplets, and demonstrate that filtering out barcodes identified by these tools improves downstream analysis.
Monosynaptic ventral tegmental area glutamate projections to the locus coeruleus enhance aversive processing
Authors: Parker Kyle E. , Kuo Chao-Cheng , Buckley Alex R. , Patterson Abigail P. , Duong Vincent , Hunter Sarah C. , McCall Jordan G. 
Published: October 2024

AbstractDistinct excitatory synaptic inputs to the locus coeruleus (LC) modulate behavioral flexibility. Here we identify a novel monosynaptic glutamatergic input to the LC from the ventral tegmental area (VTA). We show robust VTA axonal projections provide direct glutamatergic transmission to LC. Despite weak synaptic summation, optogenetic activation of these axons enhances LC tonic firing and facilitates real-time and conditioned aversive behaviors. We hypothesized this projection may modulate synaptic integration with other excitatory inputs. We then used coincident VTA-LC photostimulation with local electrical stimulation and observed enhanced LC burst induction. To determine whether this integration also occursin vivo, we took an analogous approach measuring reward-seeking behavior during unpredictable probabilistic punishment. Here, glutamatergic VTA-LC photostimulation during a concurrent noxious stimulus did not delay reward-seeking behavior, but increased probability of task failure. Together, we identified a novel VTA-LC glutamatergic projection that drives concurrent synaptic summation during salient stimuli to promote behavioral avoidance.
Germplasm stability in zebrafish requires maternal Tdrd6a and Tdrd6c
Authors: Consorte Alessandro , El Sherif Yasmin , Kielisch Fridolin , Wittkopp Nadine , Ketting René F. 
Published: October 2024

AbstractGerm cell specification is driven, in many species, by germplasm: a collection of phase-separation-based structures in the embryo, formed by RNA and proteins that derive from the cytoplasm of the oocytes. How the formation of germplasm is regulated, especially in vertebrates, remains unclear. In this study, we show that two multi-Tudor proteins, Tdrd6a and Tdrd6c, together are necessary for the stability of germplasm in zebrafish, while the related Balbiani body in the oocyte is largely unaffected. Combined lack of maternal Tdrd6a and Tdrd6c still allows the initial germplasm formation but causes its dispersal during the first hours of development. This results in the absence of primordial germ cells during later development and in sterility of the resulting adult animals. Furthermore, our study suggests that the Prion-like domain of Tdrd6c is relevant for Tdrd6c self-interaction as well as for its interaction with Bucky ball, the organizer of germplasm in zebrafish and that these dynamics are modulated by Tdrd6c Tudor domains. The identification of Tdrd6a and Tdrd6c as required for germplasm stability is an important step in our understanding of how this phase-separated structure is controlled during development.Author SummaryWe show that maternal Tdrd6a and Tdrd6c proteins interact with Bucky Ball and are essential for embryonic germplasm stability, germ cell specification and fertility in zebrafish.
Representation of verbal thought in motor cortex and implications for speech neuroprostheses
Authors: Kunz Erin M. , Meschede-Krasa Benyamin , Kamdar Foram , Avansino Donald , Nason-Tomaszewski Samuel R. , Card Nicholas S. , Jacques Brandon , Bechefsky Payton , Hahn Nick , Iacobacci Carrina , Hochberg Leigh R. , Brandman David M. , Stavisky Sergey D. , AuYong Nicholas , Pandarinath Chethan , Druckmann Shaul , Henderson Jaimie M. , Willett Francis R. 
Published: October 2024

AbstractSpeech brain-computer interfaces show great promise in restoring communication for people who can no longer speak1–3, but have also raised privacy concerns regarding their potential to decode private verbal thought4–6. Using multi-unit recordings in three participants with dysarthria, we studied the representation of inner speech in the motor cortex. We found a robust neural encoding of inner speech, such that individual words and continuously imagined sentences could be decoded in real-time This neural representation was highly correlated with overt and perceived speech. We investigated the possibility of "eavesdropping" on private verbal thought, and demonstrated that verbal memory can be decoded during a non-speech task. Nevertheless, we found a neural "overtness" dimension that can help to avoid any unintentional decoding. Together, these results demonstrate the strong representation of verbal thought in the motor cortex, and highlight important design considerations and risks that must be addressed as speech neuroprostheses become more widespread.
Integrating Artificial Intelligence and Bioinformatics Methods to Identify Disruptive STAT1 Variants Impacting Protein Stability and Function
Authors: Kamal Ebtihal , Kaddam Lamis A. , Ahmed Mehad , Alabdulkarim Abdulaziz 
Published: October 2024

AbstractThe Signal Transducer and Activator of Transcription1 (STAT1)gene is an essential component of the JAK-STAT signalling pathway. This pathway has a pivotal role in regulating different cellular processes, including immune responses, cell growth, and apoptosis. Mutations in theSTAT1gene contribute to various body pathologies [OMIM #600555], including immune system dysfunction.In the current study, we used eighteen online computational approaches. Six pathogenic variants (R602W, I648T, V642D, L600P, I578N, and W504C) were predicted to significantly disrupt protein stability and function. These findings highlight the potential of approaches to pinpoint pathogenic single nucleotide polymorphisms, providing a time and cost effective alternative to experimental approaches. Up to the best of our knowledge, this is the original inclusive study, where we analyzeSTAT1gene variants using both bioinformatics and artificial intelligence based model tools.
Single-cell RNA sequencing on formalin-fixed and paraffin-embedded (FFPE) tissue identified multi-ciliary cells in breast cancer
Authors: González-Martínez Silvia , Carretero-Barrio Irene , Pérez-Mies Belén , Fernández-Lanza Val , García-Cosío Mónica , Caniego-Casas Tamara , Hardisson David , Esteban-Rodríguez Isabel , Cortés Javier , Palacios José 
Published: October 2024

AbstractThe purpose of this study was to evaluate the suitability of paraffin-embedded (FFPE) samples and fixed fresh (FF) samples for single-cell RNA sequencing (scRNAseq). To this end, we compared whether single-cell profiles from FFPE and matched FF tissue samples from one invasive carcinoma of no especial type carcinoma (invasive ductal carcinoma –IDC) and one invasive lobular carcinoma (ILC) were similar when captured using the common immunohistochemical (IHC) and immune features of the tumors.FF and FFPE tissue derived libraries showed high-quality parameters. The cell heterogeneity obtained was similar, although, there were some differences in the number of cells captured, but there were no specific cell populations captured exclusively by one of the two different approaches. The combined analysis of the four samples identified six types of epithelial cells (normal basal cells, four subpopulations of neoplastic cells in the IDC and one in the ILC), and different tumoral microenvironment populations.scRNAseq results from epithelial neoplastic cells were concordant with common IHC markers. In addition, after quantitative assessment of the whole slide images using QuPath, the proportion of immune cells identified by IHQ in FFPE sections were similar to those obtained by scRNAseq. Confirming the suitability of scRNAseq using FFPE tissue, this technique identified one subpopulation of neoplastic cells present only in the IDC, characterized by the expression of genes related with multi-ciliated cell (MCC) differentiation (FOXJ1, ROPN1L, TPPP3, CFAP45). IHC analysis ofFOXJ1expression confirmed the presence of positive cells only in the IDC in a similar proportion to that obtained by scRNAseq. Analysis ofFOXJ1in a cohort of 214 ER-positive invasive carcinomas demonstrated protein expression in at least 1% of cells in 33% of tumors, suggesting frequent focal MCC differentiation. Our results support the suitability of scRNAseq analysis using FFPE tissue and identified a subpopulation of neoplastic MCC in breast cancer.
Leveraging clinical sleep data across multiple pediatric cohorts for insights into neurodevelopment: the Retrospective Analysis of Sleep in Pediatric (RASP) cohorts study
Authors: Gong Naihua N. , Mahat Aditya , Ahmad Samya , Glaze Daniel , Maletic-Savatic Mirjana , McGinley Matthew , Morse Anne Marie , Rodriguez Alcibiades J. , Thurm Audrey , Redline Susan , Maski Kiran , Purcell Shaun , Buckley Ashura 
Published: October 2024

AbstractSleep disturbances are prominent across neurodevelopmental disorders (NDDs) and may reflect specific abnormalities in brain development and function. Overnight polysomnography (PSG) allows for detailed investigation of sleep architecture, offering a unique window into neurocircuit function. A better understanding of sleep in NDDs compared to typically developing children could therefore define mechanisms underlying abnormal development in NDDs and provide avenues for the development of therapeutic interventions to improve sleep quality and developmental outcomes. Here, we introduce and characterize a collection of 1527 pediatric overnight PSGs across five different sites. We first developed an automated stager trained on independent pediatric sleep data, which yielded better performance compared to a stager trained on adults. Using consistent staging across cohorts, we derived a panel of EEG micro-architectural features. This unbiased approach replicated broad trajectories previously described in typically developing sleep architecture. Further, we found sleep architecture disruptions in children with Down’s Syndrome (DS) that were consistent across independent cohorts. Finally, we built and evaluated a model to predict age from sleep EEG metrics, which recapitulated our previous findings of younger predicted brain age in children with DS. Altogether, by creating a resource pooled from existing clinical data we expanded the available datasets and computational resources to study sleep in pediatric populations, specifically towards a better understanding of sleep in NDDs. This Retrospective Analysis of Sleep in Pediatric (RASP) cohorts dataset, including staging annotation derived from our automated stager, will be deposited athttps://sleepdata.org.Statement of significanceWe introduce the RASP cohorts, a collection of 1527 clinical pediatric overnight polysomnographies that includes typically developing and neurodevelopmental disorder cases. As a first step towards addressing the analytic bottleneck inherent in manual sleep staging, we developed and validated a pediatric-specific sleep stager. Leveraging the retrospective RASP cohorts dataset, we redemonstrated known developmental trajectories in sleep architecture. To summarize changes in brain function reflected in sleep, we developed a model to predict brain age from sleep measures. We recapitulate younger predicted age in RASP Down’s Syndrome cases. This work not only enhances our understanding of sleep disturbances in NDDs, but also provides a valuable resource for future research and underscores the utility of existing clinical polysomnography studies.