bluuebunny/crossref_metadata_2025_split huggingface dataset:
Telomere-to-telomere assembly by preserving contained reads
Authors: Kamath Sudhanva Shyam , Bindra Mehak , Pal Debnath , Jain Chirag 
Published: November 2023

AbstractAutomated telomere-to-telomere (T2T)de novoassembly of diploid and polyploid genomes remains a formidable task. A string graph is a commonly used assembly graph representation in the overlap-based algorithms. The string graph formulation employs graph simplification heuristics, which drastically reduce the count of vertices and edges. One of these heuristics involves removing the reads contained in longer reads. However, this procedure is not guaranteed to be safe. In practice, it occasionally introduces gaps in the assembly by removing all reads that cover one or more genome intervals. The factors contributing to such gaps remain poorly understood. In this work, we mathematically derived the frequency of observing a gap near a germline and a somatic heterozygous variant locus. Our analysis shows that (i) an assembly gap due to contained read deletion is an order of magnitude more frequent in Oxford Nanopore reads than PacBio HiFi reads due to differences in their read-length distributions, and (ii) this frequency decreases with an increase in the sequencing depth. Drawing cues from these observations, we addressed the weakness of the string graph formulation by developing the RAFT assembly algorithm. RAFT addresses the issue of contained reads by fragmenting reads and producing a more uniform readlength distribution. The algorithm retains spanned repeats in the reads during the fragmentation. We empirically demonstrate that RAFT significantly reduces the number of gaps using simulated datasets. Using real Oxford Nanopore and PacBio HiFi datasets of the HG002 human genome, we achieved a twofold increase in the contig NG50 and the number of haplotype-resolved T2T contigs compared to Hifiasm.
Ultrasound-guided Photoacoustic image Annotation Toolkit in MATLAB (PHANTOM) for preclinical applications
Authors: Sweeney Allison , Arora Aayush , Edwards Skye , Mallidi Srivalleesha 
Published: November 2023

ABSTRACTDepth-dependent fluence-compensation in photoacoustic (PA) imaging is paramount for accurate quantification of chromophores from deep tissues. Here we present a user-friendly toolkit named PHANTOM (PHotoacoustic ANnotation TOolkit for MATLAB) that includes a graphical interface and assists in the segmentation of ultrasound-guided PA images. We modelled the light source configuration with Monte Carlo eXtreme and utilized 3D segmented tissues from ultrasound to generate fluence maps to depth compensate PA images. The methodology was used to analyze PA images of phantoms with varying blood oxygenation and results were validated with oxygen electrode measurements. Two preclinical models, a subcutaneous tumor and a calcified placenta, were imaged and fluence-compensated using the PHANTOM toolkit and the results were verified with immunohistochemistry. The PHANTOM toolkit provides scripts and auxiliary functions to enable biomedical researchers not specialized in optical imaging to apply fluence correction to PA images, enhancing accessibility of quantitative PAI for researchers in various fields.
Memory control deficits in the sleep-deprived human brain
Authors: Harrington Marcus O. , Karapanagiotidis Theodoros , Phillips Lauryn , Smallwood Jonathan , Anderson Michael C. , Cairney Scott A. 
Published: November 2023

SummarySleep disturbances are associated with intrusive memories, but the neurocognitive mechanisms underpinning this relationship are poorly understood. Here, we show that an absence of sleep disrupts prefrontal inhibition of memory retrieval, and that the overnight restoration of this inhibitory mechanism is predicted by time spent in rapid eye movement (REM) sleep. The functional impairments arising from sleep loss are linked to a behavioural deficit in the ability to suppress unwanted memories, and coincide with a deterioration of deliberate patterns of self-generated thought. We conclude that sleep deprivation gives rise to intrusive memories via the disruption of neural circuits governing mnemonic inhibitory control, which may rely on REM sleep.
Hypoxia evokes a sequence of raphe-pontomedullary network operations for inspiratory drive amplification and gasping
Authors: Nuding Sarah C. , Segers Lauren S. , Iceman Kimberly E. , O’Connor Russell , Dean Jay B. , Valarezo Pierina A. , Shuman Dale , Solomon Irene C. , Bolser Donald C. , Morris Kendall F. , Lindsey Bruce G. 
Published: November 2023

AbstractHypoxia can trigger a sequence of breathing-related behaviors, from tachypnea to apneusis to apnea and gasping, an autoresuscitative behavior that, via large tidal volumes and altered intrathoracic pressure, can enhance coronary perfusion, carotid blood flow, and sympathetic activity, and thereby coordinate cardiac and respiratory functions. We tested the hypothesis that hypoxia-evoked gasps are amplified through a disinhibitory microcircuit within the inspiratory neuron chain and a distributed efference copy mechanism that generates coordinated gasp-like discharges concurrently in other circuits of the raphe-pontomedullary respiratory network. Data were obtained from 6 decerebrate, vagotomized, neuromuscularly-blocked, and artificially ventilated adult cats. Arterial blood pressure, phrenic nerve activity, end-tidal CO2, and other parameters were monitored. Hypoxia was produced by ventilation with a gas mixture of 5% O2in nitrogen (N2). Neuron spike trains were recorded at multiple pontomedullary sites simultaneously and evaluated for firing rate modulations and short-time scale correlations indicative of functional connectivity. Experimental perturbations evoked reconfiguration of raphe-pontomedullary circuits during tachypnea, apneusis and augmented bursts, apnea, and gasping. The functional connectivity, altered firing rates, efference copy of gasp drive, and coordinated step increments in blood pressure reported here support a distributed brain stem network model for amplification and broadcasting of inspiratory drive during autoresuscitative gasping that begins with a reduction in inhibition by expiratory neurons and an initial loss of inspiratory drive during hypoxic apnea.
The trade-off between growth and risk in Kelly’s gambling and beyond
Authors: Cavallero S. , Rousselot A. , Pugatch R. , Dinis L. , Lacoste D. 
Published: November 2023

AbstractWe study a generalization of Kelly’s horse model to situations where gambling on horses other than the winning horse does not lead to a complete loss of the investment. In such a case, the odds matrix is non-diagonal, a case which is of special interest for biological applications. We derive a trade-off for this model between the mean growth rate and the volatility as a proxy for risk. We show that this trade-off is related to a game-theoretic formulation of this problem developed previously. Since the effect of fluctuations around the average growth rate is asymmetric, we also study how the risk-growth trade-off is modified when risk is evaluated more accurately by the probability of the gamble’s ruin.
Quantification of healthspan in aging mice: Introducing FAMY and GRAIL
Authors: Lamming Dudley W. 
Published: November 2023

AbstractThe population around the world is graying, and as many of these individuals will spend years suffering from the burdens of age associated diseases, understanding how to increase healthspan, defined as the period of life free from disease and disability, is an urgent priority of geroscience research. The lack of agreed-upon quantitative metrics for measuring healthspan in aging mice has slowed progress in identifying interventions that do not simply increase lifespan, but also healthspan. Here, we define FAMY (Frailty-Adjusted Mouse Years) and GRAIL (Gauging Robust Aging when Increasing Lifespan) as new summary statistics for quantifying healthspan in mice. FAMY integrates lifespan data with longitudinal measurements of a widely utilized clinical frailty index, while GRAIL incorporates these measures and also adds information from widely utilized healthspan assays and the hallmarks of aging. Both metrics are conceptually similar to quality-adjusted life years (QALY), a widely-utilized measure of disease burden in humans, and can be readily calculated from data acquired during longitudinal and cross-sectional studies of mouse aging. We find that interventions generally thought to promote health, including calorie restriction, robustly improve healthspan as measured by FAMY and GRAIL. Finally, we show that the use of GRAIL provides new insights, and identify dietary restriction of protein or isoleucine as interventions that robustly promote healthspan but not longevity in female HET3 mice. We suggest that the routine integration of these measures into studies of aging in mice will allow the identification and development of interventions that promote healthy aging even in the absence of increased lifespan.
Using Multivariate Pattern Analysis to Increase Effect Sizes for Event-Related Potential Analyses
Authors: Carrasco Carlos Daniel , Bahle Brett , Simmons Aaron Matthew , Luck Steven J. 
Published: November 2023

AbstractMultivariate pattern analysis approaches can be applied to the topographic distribution of event-related potential (ERP) signals to ‘decode’ subtly different stimulus classes, such as different faces or different orientations. These approaches are extremely sensitive, and it seems possible that they could also be used to increase effect sizes and statistical power in traditional paradigms that ask whether an ERP component differs in amplitude across conditions. To assess this possibility, we leveraged the open-source ERP CORE dataset and compared the effect sizes resulting from conventional univariate analyses of mean amplitude with two multivariate pattern analysis approaches (support vector machine decoding and the cross-validated Mahalanobis distance, both of which are easy to compute using open-source software). We assessed these approaches across seven widely studied ERP components (N170, N400, N2pc, P3b, lateral readiness potential, error related negativity, and mismatch negativity). Across all components, we found that multivariate approaches yielded effect sizes that were as large or larger than the effect sizes produced by univariate approaches. These results indicate that researchers could obtain larger effect sizes, and therefore greater statistical power, by using multivariate analysis of topographic voltage patterns instead of traditional univariate analyses in many ERP studies.
Clustering of colon, lung, and other cancer susceptibility genes with protein tyrosine phosphatases and protein kinases in multiple short genomic regions
Authors: Quan Lei , Demant Peter 
Published: November 2023

AbstractInteractions of large gene families are poorly understood. We found that human, mouse, and rat colon and lung cancer susceptibility genes, presently considered as separate gene families, were frequently pairwise linked. The orthologous mouse map positions of 142 of 159 early discovered colon and lung cancer susceptibility genes formed 41 genomic clusters conserved >70 million years. These linked gene pairs concordantly affected both tumors and their majority was linked with two other gene families - protein tyrosine phosphatases and cancer driver protein kinases. 25% of both protein tyrosine phosphatases and protein kinases mapped <1 cM from a colon or lung cancer susceptibility gene, and 50% in <3 cM. Similar linkage was detected with most other human susceptibility genes that controlled 29 different cancer types. This concentration of tumor susceptibility genes with protein tyrosine phosphatases and driver protein kinases in multiple relatively short genomic regions suggests their possible functional diversity.
Molecular identification of a peroxidase gene controlling body size in the entomopathogenic nematodeSteinernema hermaphroditum
Authors: Schwartz Hillel T. , Tan Chieh-Hsiang , Peraza Jackeline , Raymundo Krystal Louise T. , Sternberg Paul W. 
Published: November 2023

AbstractThe entomopathogenic nematodeSteinernema hermaphroditumwas recently rediscovered and is being developed as a genetically tractable experimental system for the study of previously unexplored biology, including parasitism of its insect hosts and mutualism with its bacterial endosymbiontXenorhabdus griffiniae. Through whole-genome re-sequencing and genetic mapping we have for the first time molecularly identified the gene responsible for a mutationally defined phenotypic locus in an entomopathogenic nematode. In the process we observed an unexpected mutational spectrum following EMS mutagenesis in this species. We find that the ortholog of the essentialC. elegansperoxidase geneskpo-2controls body size and shape inS. hermaphroditum. We confirmed this identification by inactivating the gene using CRISPR-Cas9. We propose that the identification ofskpo-2will accelerate gene targeting in otherSteinernemaentomopathogenic nematodes used commercially in pest control, asskpo-2is X-linked and males hemizygous for loss of its function can mate, makingskpo-2an easily recognized and maintained marker for use in co-CRISPR.
High clonal diversity and spatial genetic admixture in early prostate cancer and surrounding normal tissue
Authors: Zhang Ning , Harbers Luuk , Simonetti Michele , Diekmann Constantin , Verron Quentin , Berrino Enrico , Bellomo Sara E. , Longo Gabriel M.C. , Ratz Michael , Schultz Niklas , Tarish Firas , Su Peng , Han Bo , Wang Wanzhong , Onorato Sofia , Giordano Silvia , Yang Qifeng , Sapino Anna , Frisén Jonas , Alkass Kanar , Druid Henrik , Roukos Vassilis , Helleday Thomas , Marchiò Caterina , Bienko Magda , Crosetto Nicola 
Published: November 2023

AbstractSomatic copy number alterations (SCNAs) are pervasive in advanced human cancers, but their prevalence and spatial distribution in early-stage, localized tumors and their surrounding normal tissues are poorly characterized. Here, we performed multi-region, single-cell DNA sequencing to characterize the SCNA landscape across multiple tumor-rich and normal tissue regions (∼125 mm3tissue cubes) obtained from prostatectomy performed in two patients with localized prostate cancer. We identified two distinct populations of cells with abnormal karyotypes, one marked by sparse deletions or amplifications (‘pseudo-diploid’ cells) and the second characterized by genome-wide copy number changes reminiscent of ‘monster’ cells previously described in colorectal cancer. Pseudo-diploid cells formed numerous small-sized subclones ranging from highly spatially localized to broadly spread subclones mainly featuring (sub-)chromosomal arm deletions. In contrast, monster cells harbored whole-chromosome gains and losses and were mostly singular events detected throughout the prostate, including normal tissue regions. Targeted deep sequencing of cancer-associated genes revealed a more confined pattern of mutations overlapping with tumor-rich regions, although we also detected mutations in regions deemed normal based on morphological assessment and bulk RNA-seq. Highly localized pseudo-diploid subclones were confined within tumor-rich regions and typically carried deletions involving chromosome (chr) 6 and 13, resulting in simultaneous loss of multiple tumor-suppressor genes, includingFOXO1andFOXO3encoding two transcription factors belonging to the Forkhead family previously implicated in prostate carcinogenesis. Tumor-rich regions also contained mutations in genes frequently mutated in prostate cancer, includingFOXA1,LRP1B,SPOP, andSPTA1.Our study reveals that SCNAs are widespread in both normal and tumor regions across the prostate gland of patients with localized prostate cancer and suggests that a subset of pseudo-diploid cells harboring chromosomal deletions that result in the loss of specific tumor-suppressor genes drive tumorigenesis in the aging prostate.
FFCM-MRF: An accurate and generalizable cerebrovascular segmentation pipeline for humans and rhesus monkeys based on TOF-MRA
Authors: Cui Yue , Huang Haibin , Liu Jialu , Zhao Mingyang , Li Chengyi , Han Xinyong , Luo Na , Gao Jinquan , Yan Dongming , Zhang Chen , Jiang Tianzi , Yu Shan 
Published: November 2023

AbstractPurposeCerebrovascular segmentation and quantification of vascular morphological features on humans and rhesus monkeys are essential for prevention, diagnosis, and treatment of brain diseases. However, current automated whole-brain vessel segmentation methods are often not generalizable to independent datasets, limiting their usefulness in real-world environments with their heterogeneity in participants, scanners, and species.Materials and MethodsIn this study, we proposed an automated, accurate and generalizable segmentation method for magnetic resonance angiography images called FFCM-MRF. This method integrates fast fuzzy c-means clustering and Markov random field optimization using blood vessel shape priors and spatial constraints. We used a total of 123 human and 44 macaque MRA images scanned at 1.5 T, 3 T, and 7 T MRI from 9 datasets to develop and validate the method.ResultsThe average Dice score coefficients for multiple independent datasets were 69.16-89.63%, with the improvements in FFCM-MRF ranged from 0.16-16.14% compared with state-of-the-art machine learning methods. Quantitative analysis showed that FFCM-MRF can accurately segment major arteries in the Circle of Willis at the base of the brain and smaller distal pial arteries while effectively suppressing noise. Test-retest analysis showed that the model yielded high vascular volume and diameter reliability.ConclusionsOur results demonstrate that the proposed method is highly accurate and reliable and largely independent of variations in field strength, scanner platforms, acquisition parameters, and species. The macaque MRA data and user-friendly open-source toolbox are freely available at OpenNeuro and GitHub to facilitate studies of imaging biomarkers for cerebrovascular and neurodegenerative diseases.
Comprehensive analysis of computational approaches in plant transcription factors binding regions discovery
Authors: Jyoti  , Ritu  , Gupta Sagar , Shankar Ravi 
Published: November 2023

ABSTRACTTranscription factors (TFs) are regulatory proteins which bind to a specific DNA region known as the transcription factor binding regions (TFBRs) to regulate the rate of transcription process. The identification of TFBRs has been made possible by a number of experimental and computational techniques established during the past few years. The process of TFBR identification involves peak identification in the binding data, followed by the identification of motif characteristics. Using the same binding data attempts have been made to raise computational models to identify such binding regions which could save time and resources spent for binding experiments. These computational approaches depend a lot on what way they learn and how. These existing computational approaches are skewed heavily around human TFBRs discovery, while plants have drastically different genomic setup for regulation which these approaches have grossly ignored. Here, we provide a comprehensive study of the current state of the matters in plant specific TF discovery algorithms. While doing so, we encountered several software tools’ issues rendering the tools not usable to researches. We fixed them and have also provided the corrected scripts for such tools. We expect this study to serve as a guide for better understanding of software tools’ approaches for plant specific TFBRs discovery and the care to be taken while applying them, especially during cross-species applications. The corrected scripts of these software tools are made available athttps://github.com/SCBB-LAB/Comparative-analysis-of-plant-TFBS-software.
Identification and Pharmacological Targeting of Treatment-Resistant, Stem-like Breast Cancer Cells for Combination Therapy
Authors: Worley Jeremy , Noh Heeju , You Daoqi , Turunen Mikko M. , Ding Hongxu , Paull Evan , Griffin Aaron T. , Grunn Adina , Zhang Mingxuan , Guillan Kristina , Bush Erin C. , Brosius Samantha J. , Hibshoosh Hanina , Mundi Prabhjot S. , Sims Peter , Dalerba Piero , Dela Cruz Filemon S. , Kung Andrew L. , Califano Andrea 
Published: November 2023

AbstractTumors frequently harbor isogenic yet epigenetically distinct subpopulations of multi-potent cells with high tumor-initiating potential—often called Cancer Stem-Like Cells (CSLCs). These can display preferential resistance to standard-of-care chemotherapy. Single-cell analyses can help elucidate Master Regulator (MR) proteins responsible for governing the transcriptional state of these cells, thus revealing complementary dependencies that may be leveraged via combination therapy. Interrogation of single-cell RNA sequencing profiles from seven metastatic breast cancer patients, using perturbational profiles of clinically relevant drugs, identified drugs predicted to invert the activity of MR proteins governing the transcriptional state of chemoresistant CSLCs, which were then validated by CROP-seq assays. The top drug, the anthelmintic albendazole, depleted this subpopulationin vivowithout noticeable cytotoxicity. Moreover, sequential cycles of albendazole and paclitaxel—a commonly used chemotherapeutic —displayed significant synergy in a patient-derived xenograft (PDX) from a TNBC patient, suggesting that network-based approaches can help develop mechanism-based combinatorial therapies targeting complementary subpopulations.Statement of significanceNetwork-based approaches, as shown in a study on metastatic breast cancer, can develop effective combinatorial therapies targeting complementary subpopulations. By analyzing scRNA-seq data and using clinically relevant drugs, researchers identified and depleted chemoresistant Cancer Stem-Like Cells, enhancing the efficacy of standard chemotherapies.
Whole genome assembly and annotation of the King Angelfish (Holacanthus passer) gives insight into the evolution of marine fishes of the Tropical Eastern Pacific
Authors: Gatins Remy , Arias Carlos F. , Sánchez Carlos , Bernardi Giacomo , León Luis F. De 
Published: November 2023

AbstractHolacanthusangelfishes are some of the most iconic marine fishes of the Tropical Eastern Pacific (TEP). However, very limited genomic resources currently exist for the genus. In this study we: i) assembled and annotated the nuclear genome of the King Angelfish (Holacanthus passer),and ii) examined the demographic history ofH. passerin the TEP. We generated 43.8 Gb of ONT and 97.3 Gb Illumina reads representing 75X and 167X coverage, respectively. The final genome assembly size was 583 Mb with a contig N50 of 5.7 Mb, which captured 97.5% complete Actinoterygii Benchmarking Universal Single-Copy Orthologs (BUSCOs). Repetitive elements account for 5.09% of the genome, and 33,889 protein-coding genes were predicted, of which 22,984 have been functionally annotated. Our demographic model suggests that population expansions ofH. passeroccurred prior to the last glacial maximum (LGM) and were more likely shaped by events associated with the closure of the Isthmus of Panama. This result is surprising, given that most rapid population expansions in both freshwater and marine organisms have been reported to occur globally after the LGM. Overall, this annotated genome assembly will serve as a resource to improve our understanding of the evolution ofHolacanthusangelfishes while facilitating novel research into local adaptation, speciation, and introgression in marine fishes.