Miracle-dz/UniFAR-FTUs huggingface dataset:
Accumulation of the GSK3 target protein β-catenin is lethal for B cell precursors and malignant B cells

Glycogen synthase kinase 3 (GSK3) is a ubiquitously expressed kinase involved in a myriad of biological processes. Although GSK3 mediated phosphorylation has been shown to induce the degradation of many pro-survival and pro-proliferation factors, cancer cells of different origin show reduced proliferation or survival after GSK3 inhibition. Our current understanding of the role GSK3 plays in normal mature B cells, B cell precursors and transformed B cells is incomplete and does not allow to assess whether GSK3 inhibitors can be used to treat B cell derived malignancies. Here we identify β-catenin as the major factor driving GSK3-inhibition induced changes in B cells. We show that β-catenin accumulation has opposing effects on cell metabolism and survival in mature B cells and B cell precursors. Moreover, we demonstrate that β-catenin destabilizes the commitment to the B cell lineage. In summary, our study identifies β-catenin induced signaling as a factor that can be exploited to limit the survival of malignant B cells.
Long term nasopharyngeal colonization by Staphylococcus aureus determinants of adaptation

Staphylococcus aureus nasal colonization is a risk factor for infection. A large proportion of the population are identified as potential S. aureus carriers yet we only partially understand the repertoire of genetic factors that promote long-term nasal colonization. Here we present a novel murine model of nasopharyngeal colonization that requires a low S. aureus inoculum and is amenable to experimental evolution approaches. We used this model to experimentally evolve S. aureus using successive passages in the nasopharynx to identify those genetic loci under selection. After 3 cycles of colonization, mutations were identified in mannitol, sorbitol, arginine, nitrite and lactate metabolism genes promoting key pathways in nasal colonization. Stress responses were identified as being under selective pressure, with mutations in DNA repair genes including dnaJ and recF and key stress response genes clpL, rpoB and ahpF. Peptidoglycan synthesis pathway genes also revealed mutations indicating potential selection for alteration of the cell surface. The infection model used here is versatile to assist decolonization and persistence studies.
A Computational Framework to Identify Metabolic Engineering Strategies for the Co-Production of Metabolites

Microbial production of chemicals is a more sustainable alternative to traditional chemical processes. However, the shift to bioprocess is usually accompanied by a drop in economic feasibility. Co-production of more than one chemical can improve the economy of bioprocesses, enhance carbon utilization and also ensure better exploitation of resources. While a number of tools exist for in silico metabolic engineering, there is a dearth of computational tools that can co-optimize the production of multiple metabolites. In this work, we propose an eXtended version of Flux Scanning based on Enforced Objective Flux (XFSEOF), identify intervention strategies to co-optimize for a set of metabolites. XFSEOF can be used to identify all pairs of products that can be co-optimized with ease, by a single intervention. Beyond this, it can also identify higher-order intervention strategies for a given set of metabolites. We have employed this tool on the genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae, and identified intervention targets that can co-optimize the production of pairs of metabolites under both aerobic and anaerobic conditions. Anaerobic conditions were found to support the co-production of a higher number of metabolites when compared to aerobic conditions in both organisms. The proposed computational framework will enhance the ease of study of metabolite co-production and thereby aid the design of better bioprocesses.
A condensate dynamic instability orchestrates oocyte actomyosin cortex activation

A key event at the onset of development is the activation of a contractile actomyosin cortex during the oocyte-to-embryo transition. We here report on the discovery that in C. elegans oocytes, actomyosin cortex activation is supported by the emergence of thousands of short-lived protein condensates rich in F-actin, N-WASP, and ARP2/3 that form an active micro-emulsion. A phase portrait analysis of the dynamics of individual cortical condensates reveals that condensates initially grow, and then switch to disassembly before dissolving completely. We find that in contrast to condensate growth via diffusion, the growth dynamics of cortical condensates are chemically driven. Remarkably, the associated chemical reactions obey mass action kinetics despite governing both composition and size. We suggest that the resultant condensate dynamic instability suppresses coarsening of the active micro-emulsion, ensures reaction kinetics that are independent of condensate size, and prevents runaway F-actin nucleation during the formation of the first cortical actin meshwork.
Circulating MicroRNAs in the Second Trimester From Pregnant Women Who Subsequently Developed Preeclampsia: Potential Candidates as Predictive Biomarkers and Pathway Analysis for Target Genes of miR-204-5p

MicroRNAs (miRNAs) play an important role in the pathophysiology of preeclampsia (PE). However, the expression of circulating miRNAs was not analyzed in the second trimester of pregnancy, a period of major relevance to identify predictive biomarkers for PE. Therefore, we examined the expression profiles of 84 circulating miRNAs using a PCR array in plasma collected between 20 and 25 weeks of gestation from pregnant women, who subsequently developed PE and those who remained healthy during pregnancy, randomly selected from a prospective cohort. Overall, 23 miRNAs had a fold change > 2.0 and were considered to be upregulated in plasma from pregnant women who subsequently developed PE, even before the onset of clinical symptoms of PE. However, only miR-204-5p was statistically significant (P = 0.0082). Experimentally validated interactions for the target genes of miR-204-5p extracted from miRTarBase were used in the gene set functional enrichment analysis to identify Reactome pathways. The network connecting the 37 target genes for miR-204-5p revealed pathways of known pathophysiological relevance during the early development of PE and included key genes related to PE, such as BDNF, MMP-9, MALAT1, TGFBR2, and SIRT1. We further depicted downstream targets of SIRT1 that are related to the vascular endothelial function or implicated in the pathophysiology of PE, namely, FOXO1, NFκB, HIF-1α, NOS3, and PPAR-γ. Our novel findings provide for circulating miRNAs upregulated in the second trimester on plasma from pregnant women who subsequently developed PE that is potentially related to the early development of PE, which may guide further studies focused on the validation of potential predictive biomarkers in PE.
Comparison of the Direct Oral Anticoagulants and Warfarin in Patients With Atrial Fibrillation and Valvular Heart Disease: Updated Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background: Direct oral anticoagulants (DOACS) are approved for use in non-valvular atrial fibrillation (AF). This systematic review and meta-analysis aimed to evaluate the efficacy and safety of DOACs vs. warfarin and update the evidence for treatment of AF and valvular heart disease (VHD). Methods: We identified randomized clinical trials (RCTs) and post-hoc analyses comparing the use of DOACS and Warfarin in AF and VHD, including biological and mechanical heart valves (MHV), updating from 2010 to 2020. Through systematic review and meta-analysis, by using the “Rev Man” program 5.3, the primary effectiveness endpoints were stroke and systemic embolism (SE). The primary safety outcome was major bleeding, while the secondary outcome included intracranial hemorrhage. We performed prespecified subgroup analyses. Data were analyzed by risk ratio (RR) and 95% confidence interval (CI) and the I-square (I2) statistic as a quantitative measure of inconsistency. Risk of bias and methodological quality assessment of included trials was evaluated with the modified Cochrane risk-of-bias tool. Results: We screened 326 articles and included 8 RCTs (n = 14.902). DOACs significantly reduced the risk of stroke/SE (RR 0.80, 95% CI: 0.68–0.94; P = 0.008; moderate quality evidence; I2 = 2%) and intracranial hemorrhage (RR 0.40, 95% CI: 0.24–0.66; P = 0.0004; I2 = 49%) with a similar risk of major bleeding (RR 0.83, 95% CI: 0.56–1.24; P = 0.36; I2 = 88%) compared to Warfarin. Conclusions: In this update, DOACs remained with similar efficacy and safety compared to warfarin in thromboprophylaxis for AF and VHD.
Long-Term Survival Outcomes and Comparison of Different Treatment Modalities for Stage I-III Cervical Esophageal Carcinoma

Purpose: To investigate the survival outcomes, prognostic factors and treatment modalities of stage I-III cervical esophageal carcinoma (CEC) patients using data from the Surveillance, Epidemiology, and End Results (SEER) database from the period 2004–2016. Methods: Patients with a histopathologic diagnosis of CEC were included. The primary endpoint was overall survival (OS). Univariate and multivariate analyses of OS were performed using Cox proportional hazards models, and OS was compared using the Kaplan-Meier method and log-rank test. Results: A total of 347 patients in the SEER database were enrolled. The median OS was 14.0 months, with a 5-year OS rate of 20.9%. The parameters that were found to significantly correlate with OS in the multivariate analysis were age at diagnosis [P < 0.001, hazard ratio (HR) = 1.832], sex [P < 0.001, HR= 1.867], histology [P = 0.001, HR = 0.366], surgery at the primary site [P = 0.021, HR = 0.553], radiotherapy (RT, P = 0.017, HR = 0.637) and chemotherapy (CT, P < 0.001, HR = 0.444). Comparison among the three treatment modalities demonstrated that a triple therapy regimen consisting of surgery, RT and CT was associated with a longer survival time than the other two treatment modalities before and after propensity score matching (PSM). However, triple therapy showed no significant survival benefit over double therapy (P = 0.496 before PSM and P = 0.184 after PSM). Conclusions: The survival of patients with CEC remains poor. Surgery, RT and CT were all strongly correlated with OS. We recommend a triple therapy regimen for select CEC patients based on the findings of the current study, although this recommendation should be further confirmed by prospective studies with large sample sizes.
Distinct Endophytic Bacterial Communities Inhabiting Seagrass Seeds

Seagrasses are marine angiosperms that can live completely or partially submerged in water and perform a variety of significant ecosystem services. Like terrestrial angiosperms, seagrasses can reproduce sexually and, the pollinated female flower develop into fruits and seeds, which represent a critical stage in the life of plants. Seed microbiomes include endophytic microorganisms that in terrestrial plants can affect seed germination and seedling health through phytohormone production, enhanced nutrient availability and defence against pathogens. However, the characteristics and origins of the seagrass seed microbiomes is unknown. Here, we examined the endophytic bacterial community of six microenvironments (flowers, fruits, and seeds, together with leaves, roots, and rhizospheric sediment) of the seagrass Halophila ovalis collected from the Swan Estuary, in southwestern Australia. An amplicon sequencing approach (16S rRNA) was used to characterize the diversity and composition of H. ovalis bacterial microbiomes and identify core microbiome bacteria that were conserved across microenvironments. Distinct communities of bacteria were observed within specific seagrass microenvironments, including the reproductive tissues (flowers, fruits, and seeds). In particular, bacteria previously associated with plant growth promoting characteristics were mainly found within reproductive tissues. Seagrass seed-borne bacteria that exhibit growth promoting traits, the ability to fix nitrogen and anti-pathogenic potential activity, may play a pivotal role in seed survival, as is common for terrestrial plants. We present the endophytic community of the seagrass seeds as foundation for the identification of potential beneficial bacteria and their selection in order to improve seagrass restoration.
Case Report: An Atypical Angelman Syndrome Case With Obesity and Fulfilled Autism Spectrum Disorder Identified by Microarray

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders which are etiologically heterogeneous. Chromosomal microarray is now recommended as the first-tier clinical diagnostic test for ASD. We performed chromosomal microarray in 16 Thai patients with ASD using an Illumina HumanCytoSNP-12 v2.1 array and found one case with uniparental disomy (UPD) of chromosome 15. Methylation-specific PCR showed abnormal methylation of the maternal SNRPN allele. Haplotype analysis revealed that the patient had received both chromosomes 15 from his father. These results were consistent with Angelman syndrome. However, his clinical features had no clinical significance for classic Angelman syndrome. He had first presented at the pediatric clinic with no speech, poor social interaction skills and repetitive behaviors consistent with ASD based on the DSM-IV criteria at 2 years of age and later confirmed by ADOS at 5 years of age. He was strikingly overweight but had no dysmorphic facies, seizures nor ataxia and was diagnosed as non-syndromic ASD, a diagnosis which was believed until at 10 years of age, his DNA was included for analysis in this current cohort study. Our findings suggest that ASD patients with unknown etiology should be considered for methylation-specific PCR testing for Angelman syndrome where chromosomal microarray is not available. In the study, we also review the clinical features of Angelman syndrome caused by UPD and the frequency of ASD in individuals with Angelman syndrome.
An Analysis of Personalized Learning Opportunities in 3D VR

Due to its constantly developing technological background, VR and AR technology has been gaining increasing popularity not just in industry or business but in education as well. Research in the field of Cognitive Infocommunications (CogInfoCom) shows that using existing digital technologies, online collaboration and cooperation technologies in 3D VR supports cognitive processes, including the finding, processing, memorization and recalling of information. 3D VR environments are also capable of providing users with a much higher level of comprehension when it comes to sharing and interpreting digital workflows. The paper presents a study carried out with the participation of 90 students. The aim of this study is to investigate how the application of 3D VR platforms as personalized educational environments can also increase VR learning efficiency. Besides considering participants’ test performance, metrics such as results on visual, auditory and reading-based learning tests for information acquisition, as well as responses on Kolb’s learning styles questionnaires are taken into consideration. The participants’ learning styles, information acquisition habits were also observed, allowing us to create and offer a variety of learning pathways based on a variety of content types in the 3D VR environment. The students within the study were divided into two groups: a test group receiving personalized training in the MaxWhere 3D VR classroom, and a control group that studied in a general MaxWhere 3D VR space. This research applies both quantitative and qualitative methods to report findings. The goal was to create adaptive learning environments capable of deriving models of learners and providing personalized learning experiences. We studied the correlation between effectiveness of the tasks and Kolb’s learning styles. The study shows the major importance of choosing the optimal task type regarding each Kolb learning style and personalized learning environment. The MaxWhere 3D spaces show a high potential for personalizing VR education. The non-intrusive guiding capabilities of VR environments and of the educational content integrated in the 3D VR spaces were very successful, because the students were able to score 20 percent higher on the tests after studying in VR than after using traditional educational tools. Students also performed the same tasks with 8-10 percent faster response times.
A Clinical-Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Gallbladder Cancer

Objectives The aim of the current study was to develop and validate a nomogram based on CT radiomics features and clinical variables for predicting lymph node metastasis (LNM) in gallbladder cancer (GBC). Methods A total of 353 GBC patients from two hospitals were enrolled in this study. A Radscore was developed using least absolute shrinkage and selection operator (LASSO) logistic model based on the radiomics features extracted from the portal venous-phase computed tomography (CT). Four prediction models were constructed based on the training cohort and were validated using internal and external validation cohorts. The most effective model was then selected to build a nomogram. Results The clinical-radiomics nomogram, which comprised Radscore and three clinical variables, showed the best diagnostic efficiency in the training cohort (AUC = 0.851), internal validation cohort (AUC = 0.819), and external validation cohort (AUC = 0.824). Calibration curves showed good discrimination ability of the nomogram using the validation cohorts. Decision curve analysis (DCA) showed that the nomogram had a high clinical utility. Conclusion The findings showed that the clinical-radiomics nomogram based on radiomics features and clinical parameters is a promising tool for preoperative prediction of LN status in patients with GBC.
Inflow Occlusion Combined With Bleomycin Sclerotherapy for Management of Macro/Mixed Cystic Lymphatic Malformation in Children

Background: The link between cystic lymphatic malformation (cLM) and normal lymphatic system has become the focus of research. This study aimed to assess the outcomes of indocyanine green (ICG) lymphography-guided inflow occlusion combined with bleomycin sclerotherapy for the management of macro or mixed cLM in children. Methods: Between June 2018 and October 2020, inflow occlusion combined with bleomycin sclerotherapy was performed in 81 cLM patients (age range from 6 months to 8 years). All cases were evaluated by the following parameters: cLM location, histological typing, number of afferent lymph vessels, dermal backflow, curative effects, treatment frequency, and postoperative complications. The duration of postoperative follow-up was from 10 to 16 months. Results: All cLM cases could be found with at least one lymphatic inflow. Excellent outcomes were observed in 68 cases (84.0%), 11 cases (13.6%) experienced good outcomes, and two (2.5%) cases had fair outcome. No case experienced repeated treatment for more than three times. Wound infection, fever, and scar hyperplasia were the independent adverse events, which were managed by symptomatic treatment. Conclusion: Inflow occlusion combined with bleomycin sclerotherapy renders a safe and efficient approach for the management of macro or mixed cLM.
NEO: NEuro-Inspired Optimization—A Fractional Time Series Approach

Solving optimization problems is a recurrent theme across different fields, including large-scale machine learning systems and deep learning. Often in practical applications, we encounter objective functions where the Hessian is ill-conditioned, which precludes us from using optimization algorithms utilizing second-order information. In this paper, we propose to use fractional time series analysis methods that have successfully been used to model neurophysiological processes in order to circumvent this issue. In particular, the long memory property of fractional time series exhibiting non-exponential power-law decay of trajectories seems to model behavior associated with the local curvature of the objective function at a given point. Specifically, we propose a NEuro-inspired Optimization (NEO) method that leverages this behavior, which contrasts with the short memory characteristics of currently used methods (e.g., gradient descent and heavy-ball). We provide evidence of the efficacy of the proposed method on a wide variety of settings implicitly found in practice.
Comparative Study of Pulmonary Combined Large-Cell Neuroendocrine Carcinoma and Combined Small-Cell Carcinoma in Surgically Resected High-Grade Neuroendocrine Tumors of the Lung

Objectives Pulmonary large-cell neuroendocrine carcinoma (LCNEC) and small-cell lung cancer (SCLC) are both classified as pure and combined subtypes. Due to the low incidence and difficult diagnosis of combined LCNEC (C-LCNEC) and combined SCLC (C-SCLC), few studies have compared their clinical features and prognosis. Materials and Methods We compared the clinical features, mutation status of driver genes (EGFR, ALK, ROS1, KRAS, and BRAF), and prognosis between C-LCNEC and C-SCLC. Univariate and multivariate Cox regression analyses were applied for survival analysis. Results We included a total of 116 patients with C-LCNEC and 76 patients with C-SCLC in the present study. There were significant differences in distribution of smoking history, tumor location, pT stage, pN stage, pTNM stage, visceral pleural invasion (VPI), and combined components between C-LCNEC and C-SCLC (P<0.05 for all). C-SCLC was more advanced at diagnosis as compared to C-LCNEC. The incidence of EGFR mutations in C-LCNEC patients was higher than C-SCLC patients (25.7 vs. 5%, P=0.004). We found that tumor size, pN stage, peripheral CEA level, and adjuvant chemotherapy were independently prognostic factors for DFS and OS in C-LCNEC patients, while peripheral NSE level, pT stage, pN stage, VPI and adjuvant chemotherapy were independently associated with DFS and OS for C-SCLC patients (P<0.05 for all). Propensity score matching with adjustment for the confounders confirmed a more favorable DFS (P=0.032) and OS (P=0.019) in patients with C-LCNEC in comparison with C-SCLC patients upon survival analysis. Conclusions The mutation landscape of driver genes seemed to act in different way between C-SCLC and C-LCNEC, likely by which result in clinical phenotype difference as well as better outcome in C-LCNEC.
Tourism Demand Forecasting Based on an LSTM Network and Its Variants

The need for accurate tourism demand forecasting is widely recognized. The unreliability of traditional methods makes tourism demand forecasting still challenging. Using deep learning approaches, this study aims to adapt Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit networks (GRU), which are straightforward and efficient, to improve Taiwan’s tourism demand forecasting. The networks are able to seize the dependence of visitor arrival time series data. The Adam optimization algorithm with adaptive learning rate is used to optimize the basic setup of the models. The results show that the proposed models outperform previous studies undertaken during the Severe Acute Respiratory Syndrome (SARS) events of 2002–2003. This article also examines the effects of the current COVID-19 outbreak to tourist arrivals to Taiwan. The results show that the use of the LSTM network and its variants can perform satisfactorily for tourism demand forecasting.