Miracle-dz/UniFAR-FTUs huggingface dataset:
ALLSorts: an RNA-Seq subtype classifier for B-cell acute lymphoblastic leukemia

B-cell acute lymphoblastic leukemia (B-ALL) is the most common childhood cancer. Subtypes within B-ALL are distinguished by characteristic structural variants and mutations, which in some instances strongly correlate with responses to treatment. The World Health Organisation (WHO) recognises seven distinct classifications, or subtypes, as of 2016. However, recent studies have demonstrated that B-ALL can be segmented into 23 subtypes based on a combination of genomic features and gene expression profiles. A method to identify a patient's subtype would have clear utility. Despite this, no publically available classification methods using RNA-Seq exist for this purpose. Here we present ALLSorts: a publicly available method that uses RNA-Seq data to classify B-ALL samples to 18 known subtypes and five meta-subtypes. ALLSorts is the result of a hierarchical supervised machine learning algorithm applied to a training set of 1223 B-ALL samples aggregated from multiple cohorts. Validation revealed that ALLSorts can accurately attribute samples to subtypes and can attribute multiple subtypes to a sample. Furthermore, when applied to both paediatric and adult cohorts, ALLSorts was able to classify previously undefined samples into subtypes. ALLSorts is available and documented on GitHub (https://github.com/Oshlack/AllSorts/).
Efficacy and safety of FOLFIRINOX as second-line chemotherapy for advanced pancreatic cancer after gemcitabine-based therapy: A systematic review and meta-analysis

Objective To undertake a meta-analysis of the treatment effects of different second-line chemotherapy regimens compared with FOLFIRINOX (FOL [folinic acid], F [fluorouracil], IRIN [irinotecan], OX [oxaliplatin]) after failure of gemcitabine-based first-line therapy in patients with pancreatic cancer. Methods This meta-analysis searched electronic databases, including Embase®, Medline, PubMed® and the Cochrane library, for eligible studies that reported the use of FOLFIRINOX and other drug regimens as second-line chemotherapy after failure of gemcitabine-based chemotherapy. Pooled analyses for progression-free survival (PFS), overall survival (OS), objective response rate (ORR), disease control rate (DCR) and grade 3/4 treatment-emergent adverse events (TRAEs) were undertaken. Results The analysis included six studies with a total of 858 patients. Compared with the three other second-line regimens, FOLFIRINOX had a significantly longer PFS (hazard ratio [HR] 0.68, 95% confidence interval [CI] 0.52, 0.89) and OS (HR 0.71, 95% CI 0.59, 0.86); and a significantly better ORR (HR 0.43, 95% CI 0.23, 0.80) and DCR (HR 0.71, 95% CI 0.58, 0.88). However, grade 3/4 adverse events were more frequently reported in patients administered FOLFIRINOX compared with the other three regimens. Conclusion FOLFIRINOX is recommended as a second-line chemotherapy regimen for patients with pancreatic cancer that have failed on gemcitabine-based first-line therapy. Research Registry number: reviewregistry1300
An improved multi-view attention network inspired by coupled P system for node classification

Most of the existing graph embedding methods are used to describe the single view network and solve the single relation in the network. However, the real world is made up of networks with multiple views of complex relationships, and the existing methods can no longer meet the needs of people. To solve this problem, we propose a novel multi-view attention network inspired by coupled P system(MVAN-CP) to deal with node classification. More specifically, we design a multi-view attention network to extract abundant information from multiple views in the network and obtain a learning representation for each view. To enable the views to collaborate, we further apply attention mechanism to facilitate the view fusion process. Taking advantage of the maximum parallelism of P system, the process of learning and fusion will be realized in the coupled P system, which greatly improves the computational efficiency. Experiments on real network data sets indicate that our model is effective.
Accuracy of atrial fibrillation detection by an insertable cardiac monitor in patients undergoing catheter ablation: Results of the BioVAD study

Insertable cardiac monitors (ICMs) are increasingly used to evaluate the atrial fibrillation (AF) burden after catheter ablation of AF. BioMonitor III (BM3) is an ICM with a long sensing vector, which enhances sensing capabilities. The AF detection algorithm of the BM3 is based on R–R interval variability.
Topic modeling revisited: New evidence on algorithm performance and quality metrics

Topic modeling is a popular technique for exploring large document collections. It has proven useful for this task, but its application poses a number of challenges. First, the comparison of available algorithms is anything but simple, as researchers use many different datasets and criteria for their evaluation. A second challenge is the choice of a suitable metric for evaluating the calculated results. The metrics used so far provide a mixed picture, making it difficult to verify the accuracy of topic modeling outputs. Altogether, the choice of an appropriate algorithm and the evaluation of the results remain unresolved issues. Although many studies have reported promising performance by various topic models, prior research has not yet systematically investigated the validity of the outcomes in a comprehensive manner, that is, using more than a small number of the available algorithms and metrics. Consequently, our study has two main objectives. First, we compare all commonly used, non-application-specific topic modeling algorithms and assess their relative performance. The comparison is made against a known clustering and thus enables an unbiased evaluation of results. Our findings show a clear ranking of the algorithms in terms of accuracy. Secondly, we analyze the relationship between existing metrics and the known clustering, and thus objectively determine under what conditions these algorithms may be utilized effectively. This way, we enable readers to gain a deeper understanding of the performance of topic modeling techniques and the interplay of performance and evaluation metrics.
Dysregulated ligand–receptor interactions from single-cell transcriptomics

Abstract Motivation Intracellular communication is crucial to many biological processes, such as differentiation, development, homeostasis and inflammation. Single-cell transcriptomics provides an unprecedented opportunity for studying cell-cell communications mediated by ligand–receptor interactions. Although computational methods have been developed to infer cell type-specific ligand–receptor interactions from one single-cell transcriptomics profile, there is lack of approaches considering ligand and receptor simultaneously to identifying dysregulated interactions across conditions from multiple single-cell profiles. Results We developed scLR, a statistical method for examining dysregulated ligand–receptor interactions between two conditions. scLR models the distribution of the product of ligands and receptors expressions and accounts for inter-sample variances and small sample sizes. scLR achieved high sensitivity and specificity in simulation studies. scLR revealed important cytokine signaling between macrophages and proliferating T cells during severe acute COVID-19 infection, and activated TGF-β signaling from alveolar type II cells in the pathogenesis of pulmonary fibrosis. Availability and implementation scLR is freely available at https://github.com/cyhsuTN/scLR. Supplementary information Supplementary data are available at Bioinformatics online.
Chromosome-Level Genome Assembly of the Hemiparasitic Taxillus chinensis (DC.) Danser

Abstract The hemiparasitic Taxillus chinensis (DC.) Danser is a root-parasitizing medicinal plant with photosynthetic ability, which is lost in other parasitic plants. However, the cultivation and medical application of the species are limited by the recalcitrant seeds of the species, and even though the molecular mechanisms underlying this recalcitrance have been investigated using transcriptomic and proteomic methods, genome resources for T. chinensis have yet to be reported. Accordingly, the aim of the present study was to use nanopore, short-read, and high-throughput chromosome conformation capture sequencing to construct a chromosome-level assembly of the T. chinensis genome. The final genome assembly was 521.90 Mb in length, and 496.43 Mb (95.12%) could be grouped into nine chromosomes with contig and scaffold N50 values of 3.80 and 56.90 Mb, respectively. In addition, a total of 33,894 protein-coding genes were predicted, and gene family clustering identified 11 photosystem-related gene families, thereby indicating photosynthetic ability, which is a characteristic of hemiparasitic plants. This chromosome-level genome assembly of T. chinensis provides a valuable genomic resource for elucidating the genetic basis underlying the recalcitrant characteristics of T. chinensis seeds and the evolution of photosynthesis loss in parasitic plants.
Impact of autograft-absolute lymphocyte count on survival in double/triple hit lymphomas post-autologous stem cell transplantation

Abstract The autograft absolute lymphocyte count (A-ALC) ≥0.5 × 109 cells/kg is a survival prognostic factor for lymphoma patients undergoing autologous peripheral blood hematopoietic stem cell transplantation (APBHSCT). However, the A-ALC has not be tested as prognostic factor against double hit/triple hit lymphomas (DHL/THL). Thus, we set up to investigate if A-ALC is a prognostic factor for overall survival (OS) and progression-free survival (PFS) for DHL/THL post-APBHSCT. From January 2012 until December 2020, we identified 77 DHL/THL patients treated with APBHSCT. All patients required to have the diagnosis of DHL/THL by FISH for rearrangements of MYC, BCL2, and BCL6. With a median follow-up of 20.4 months (range, 0.4-94.5 months), DHL/THL patients infused with A-ALC ≥0.5 x 109 cells/kg experienced superior OS (HR = 0.251, 95%CI 0.117–0.539, p < 0.0004) and PFS (HR = 0.347, 95%CI 0.160–0.753, p < 0.007). Multivariate analysis showed that A-ALC was an independent predictor for OS (HR =0.119, 95%CI 0.030–0.473, p < 0.003) and PFS (HR = 0.400, 95%CI 0.189–0.850, p < 0.02). Our study showed that A-ALC is a prognostic factor for survival in DHL/THL. Our current practice for lymphoma patients is to collect enough stem cell but also A-ALC to improve clinical outcomes post-APBHSCT.
The Same-Day Delivery Problem for Online Purchases

Same-day delivery for online purchases is a recent trend in online retail. We introduce a multi-vehicle dynamic pickup and delivery problem with time constraints that incorporates key features associated with same-day delivery logistics. To make better informed decisions, our solution approach incorporates information about future requests into routing decisions. We also introduce an analytical result that identifies when it is beneficial for vehicles to wait at the depot. We present a wide range of computational experiments that demonstrate the value of our approach. The results show that more requests can be filled when time windows are evenly spread throughout the day compared to when many requests' time windows occur late in the day. However, the anticipation of future requests is most valuable when many requests' time windows occur late in the day. As a result of increased flexibility, experiments also demonstrate that the value of anticipating the future decreases when the number of vehicles or the .
Construction of a Linked Data Set of COVID-19 Knowledge Graphs: Development and Applications

Background With the continuous spread of COVID-19, information about the worldwide pandemic is exploding. Therefore, it is necessary and significant to organize such a large amount of information. As the key branch of artificial intelligence, a knowledge graph (KG) is helpful to structure, reason, and understand data. Objective To improve the utilization value of the information and effectively aid researchers to combat COVID-19, we have constructed and successively released a unified linked data set named OpenKG-COVID19, which is one of the largest existing KGs related to COVID-19. OpenKG-COVID19 includes 10 interlinked COVID-19 subgraphs covering the topics of encyclopedia, concept, medical, research, event, health, epidemiology, goods, prevention, and character. Methods In this paper, we introduce the key techniques exploited in building COVID-19 KGs in a top-down manner. First, the schema of the modeling process for each KG in OpenKG-COVID19 is described. Second, we propose different methods for extracting knowledge from open government sites, professional texts, public domain–specific sources, and public encyclopedia sites. The curated 10 COVID-19 KGs are further linked together at both the schema and data levels. In addition, we present the naming convention for OpenKG-COVID19. Results OpenKG-COVID19 has more than 2572 concepts, 329,600 entities, 513 properties, and 2,687,329 facts, and the data set will be updated continuously. Each COVID-19 KG was evaluated, and the average precision was found to be above 93%. We have developed search and browse interfaces and a SPARQL endpoint to improve user access. Possible intelligent applications based on OpenKG-COVID19 for further development are also described. Conclusions A KG is useful for intelligent question-answering, semantic searches, recommendation systems, visualization analysis, and decision-making support. Research related to COVID-19, biomedicine, and many other communities can benefit from OpenKG-COVID19. Furthermore, the 10 KGs will be continuously updated to ensure that the public will have access to sufficient and up-to-date knowledge.
Genomewide CRISPR knockout screen identified PLAC8 as an essential factor for SADS-CoVs infection

Significance A potential outbreak of swine acute diarrhea syndrome coronavirus (SADS-CoV) in the human population could be devastating. Using genomewide CRISPR knockout screening, we identified the placenta-associated 8 protein (PLAC8) as an essential host factor for SADS-CoV infection, uncovering a novel antiviral target for CoV infection. The PLAC8-related pathway may also have implications for other CoV infections. Given the ability of SADS-CoV to infect human primary cultures without adaptation, our findings lay the foundation for pandemic preparedness for the potential emergence of SADS-CoVs in response to the One Health Initiative.
The Relationship of School Connectedness to Adolescents’ Engagement in Co-Occurring Health Risks: A Meta-Analytic Review

School connectedness is an important factor in the lives of youth and are a leverage point for optimizing youth’s social, emotional, and physical health. This study presents a meta-analysis examining the relationship between school connectedness and four health domains that are prevalent in adolescence, have implications for adult health, and often co-occur: mental health, sexual health, violence, and high-risk substance use. Ninety articles published between 2009 and 2019 were included in the analysis. The study found that school connectedness had a protective average effect size across all health domains (Hedges’ g = −0.345, p-value<0.001). When examined separately, school connectedness had a significant protective relationship with substance use (g = −0.379, p < 0.001), mental health (Hedges’ g = −0.358, p < 0.001), violence (Hedges’ g = −0.318, p < 0.001), sexual health (Hedges’ g = −0.145, p < 0.001), and with co-occurring risks (Hedges’ g = −0.331, p < 0.001). These results provide strong evidence that school connectedness has the potential to prevent and mitigate multiple health risks during adolescence.
A generalized algorithm for the automatic diagnosis of sleep apnea from per-sample encoding of airflow and oximetry

Objective. Sleep apnea is a common sleep breathing disorder that can significantly decrease sleep quality and have major health consequences. It is diagnosed based on the apnea hypopnea index (AHI). This study explored a novel, generalized algorithm for the automatic diagnosis of sleep apnea employing airflow (AF) and oximetry (SpO2) signals. Approach. Of the 988 polysomnography records, 45 were randomly selected for developing the automatic algorithm and the remainder 943 for validating purposes. The algorithm detects apnea events by a per-sample encoding process applied to the peak excursion of AF signal. Hypopnea events were detected from the per-sample encoding of AF and SpO2 with an adjustment to time lag in SpO2. Total recording time was automatically processed and optimized for computation of total sleep time (TST). Total number of detected events and computed TST were used to estimate AHI. The estimated AHI was validated against the scored data from the Sleep Heart Health Study. Main results. Intraclass correlation coefficient of 0.94 was obtained between estimated and scored AHIs. The diagnostic accuracies were 93.5%, 92.4%, and 96.6% for AHI cut-off values of ≥5, ≥15, and ≥30 respectively. The overall accuracy for the combined severity categories (normal, mild, moderate, and severe) and kappa were 83.4% and 0.77 respectively. Significance. This new automatic technique was found to be superior to the other existing methods and can be applied to any portable sleep devices especially for home sleep apnea tests.
Confidence, accuracy judgments and feedback in schizophrenia and bipolar disorder: a time series network analysis

Abstract Background Inaccurate self-assessment of performance is common among people with serious mental illness, and it is associated with poor functional outcomes independent from ability. However, the temporal interdependencies between judgments of performance, confidence in accuracy, and feedback about performance are not well understood. Methods We evaluated two tasks: the Wisconsin Card Sorting Test (WCST) and the Penn Emotion recognition task (ER40). These tasks were modified to include item-by-item confidence and accuracy judgments, along with feedback on accuracy. We evaluated these tasks as time series and applied network modeling to understand the temporal relationships between momentary confidence, accuracy judgments, and feedback. The sample constituted participants with schizophrenia (SZ; N = 144), bipolar disorder (BD; N = 140), and healthy controls (HC; N = 39). Results Network models for both WCST and ER40 revealed denser and lagged connections between confidence and accuracy judgments in SZ and, to a lesser extent in BD, that were not evidenced in HC. However, associations between feedback regarding accuracy with subsequent accuracy judgments and confidence were weaker in SZ and BD. In each of these comparisons, the BD group was intermediate between HC and SZ. In analyses of the WCST, wherein incorporating feedback is crucial for success, higher confidence predicted worse subsequent performance in SZ but not in HC or BD. Conclusions While network models are exploratory, the results suggest some potential mechanisms by which challenges in self-assessment may impede performance, perhaps through hyperfocus on self-generated judgments at the expense of incorporation of feedback.
Differential modulation of C. elegans motor behavior by NALCN and two-pore domain potassium channels

Two-pore domain potassium channels (K2P) are a large family of “background” channels that allow outward “leak” of potassium ions. The NALCN/UNC80/UNC79 complex is a non-selective channel that allows inward flow of sodium and other cations. It is unclear how K2Ps and NALCN differentially modulate animal behavior. Here, we found that loss of function (lf) in the K2P gene twk-40 suppressed the reduced body curvatures of C. elegans NALCN(lf) mutants. twk-40(lf) caused a deep body curvature and extended backward locomotion, and these phenotypes appeared to be associated with neuron-specific expression of twk-40 and distinct twk-40 transcript isoforms. To survey the functions of other less studied K2P channels, we examined loss-of-function mutants of 13 additional twk genes expressed in the motor circuit and detected defective body curvature and/or locomotion in mutants of twk-2, twk-17, twk-30, twk-48, unc-58, and the previously reported twk-7. We generated presumptive gain-of-function (gf) mutations in twk-40, twk-2, twk-7, and unc-58 and found that they caused paralysis. Further analyses detected variable genetic interactions between twk-40 and other twk genes, an interdependence between twk-40 and twk-2, and opposite behavioral effects between NALCN and twk-2, twk-7, or unc-58. Finally, we found that the hydrophobicity/hydrophilicity property of TWK-40 residue 159 could affect the channel activity. Together, our study identified twk-40 as a novel modulator of the motor behavior, uncovered potential behavioral effects of five other K2P genes and suggests that NALCN and some K2Ps can oppositely affect C. elegans behavior.
Optineurin promotes myogenesis during muscle regeneration in mice by autophagic degradation of GSK3β

Skeletal muscle regeneration is essential for maintaining muscle function in injury and muscular disease. Myogenesis plays key roles in forming new myofibers during the process. Here, through bioinformatic screen for the potential regulators of myogenesis from 5 independent microarray datasets, we identify an overlapping differentially expressed gene (DEG) optineurin (OPTN). Optn knockdown (KD) delays muscle regeneration in mice and impairs C2C12 myoblast differentiation without affecting their proliferation. Conversely, Optn overexpression (OE) promotes myoblast differentiation. Mechanistically, OPTN increases nuclear levels of β-catenin and enhances the T-cell factor/lymphoid enhancer factor (TCF/LEF) transcription activity, suggesting activation of Wnt signaling pathway. The activation is accompanied by decreased protein levels of glycogen synthase kinase 3β (GSK3β), a negative regulator of the pathway. We further show that OPTN physically interacts with and targets GSK3β for autophagic degradation. Pharmacological inhibition of GSK3β rescues the impaired myogenesis induced by Optn KD during muscle regeneration and myoblast differentiation, corroborating that GSK3β is the downstream effector of OPTN-mediated myogenesis. Together, our study delineates the novel role of OPTN as a potential regulator of myogenesis and may open innovative therapeutic perspectives for muscle regeneration.