Miracle-dz/UniFAR-FTUs huggingface dataset:
Causal relationship between type 1 diabetes mellitus and six high-frequency infectious diseases: A two-sample mendelian randomization study

Purpose Type 1 diabetes mellitus (T1DM) is associated with different types of infections; however, studies on the causal relationship between T1DM and infectious diseases are lacking. Therefore, our study aimed to explore the causalities between T1DM and six high-frequency infections using a Mendelian randomization (MR) approach. Methods Two-sample MR studies were conducted to explore the causalities between T1DM and six high-frequency infections: sepsis, acute lower respiratory infections (ALRIs), intestinal infections (IIs), infections of the genitourinary tract (GUTIs) in pregnancy, infections of the skin and subcutaneous tissues (SSTIs), and urinary tract infections (UTIs). Data on summary statistics for T1DM and infections were obtained from the European Bioinformatics Institute database, the United Kingdom Biobank, FinnGen biobank, and Medical Research Council Integrative Epidemiology Unit. All data obtained for summary statistics were from European countries. The inverse-variance weighted (IVW) method was employed as the main analysis. Considering the multiple comparisons, statistical significance was set at p< 0.008. If univariate MR analyses found a significant causal association, multivariable MR (MVMR) analyses were performed to adjust body mass index (BMI) and glycated hemoglobin (HbA1c). MVMR-IVW was performed as the primary analysis, and the least absolute shrinkage and selection operator (LASSO) regression and MVMR-Robust were performed as complementary analyses. Results MR analysis showed that susceptibility to IIs increased in patients with T1DM by 6.09% using the IVW-fixed method [odds ratio (OR)=1.0609; 95% confidence interval (CI): 1.0281–1.0947, p=0.0002]. Results were still significant after multiple testing. Sensitivity analyses did not show any significant horizontal pleiotropy or heterogeneity. After adjusting for BMI and HbA1c, MVMR-IVW (OR=1.0942; 95% CI: 1.0666–1.1224, p<0.0001) showed significant outcomes that were consistent with those of LASSO regression and MVMR-Robust. However, no significant causal relationship was found between T1DM and sepsis susceptibility, ALRI susceptibility, GUTI susceptibility in pregnancy, SSTI susceptibility, and UTI susceptibility. Conclusions Our MR analysis genetically predicted increased susceptibility to IIs in T1DM. However, no causality between T1DM and sepsis, ALRIs, GUTIs in pregnancy, SSTIs, or UTIs was found. Larger epidemiological and metagenomic studies are required to further investigate the observed associations between the susceptibility of certain infectious diseases with T1DM.
Prevalence of nonalcoholic fatty liver disease and the related risk factors among healthy adults: A cross-sectional study in Chongqing, China

Background Epidemiological characteristics of nonalcoholic fatty liver disease (NAFLD) in Chongqing, a west-central city of China, remain unclear. The objective of this study was to investigate the prevalence of NAFLD and the related risk factors among healthy adults for physical examination in Chongqing. Methods A total of 110,626 subjects were enrolled in the present study. Each of the participants underwent physical examination, laboratory measurements, and abdominal ultrasonography. The chi-square test was employed to compare differences in the NAFLD prevalence, and logistic regression analysis was used to estimate the odds ratio for risk factors of NAFLD. Results The prevalence of NAFLD in individuals in the population of Chongqing was 28.5%, and the prevalence in men (38.1%) was significantly higher than that in women (13.6%) (OR = 2.44; 95% CI: 2.31–2.58). NAFLD was more common in men aged 51–60 years and women over 60 years. Approximately 79.1% of the people with obesity and 52.1% of the people with central obesity had NAFLD. The prevalence of NAFLD in people with hypertension and cholelithiasis was 48.9 and 38.4%, respectively. Logistic regression showed that gender, age, body max index (BMI), central obesity, hypertension, impaired fasting glucose/diabetes mellitus (DM), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), hyperuricemia (HUA), alanine transaminase (ALT), and cholelithiasis were independently associated with the presence of NAFLD. Conclusion The prevalence of NAFLD among healthy adults in Chongqing was high. To improve the prevention and management of NAFLD, special attention should be paid to the factors associated with the presence of NAFLD, including higher BMI, higher waist circumference, higher blood glucose, hypertension, hypertriglyceridemia, hyperuricemia, cholelithiasis, and elevated ALT.
Innate immune cellular therapeutics in transplantation

Successful organ transplantation provides an opportunity to extend the lives of patients with end-stage organ failure. Selectively suppressing the donor-specific alloimmune response, however, remains challenging without the continuous use of non-specific immunosuppressive medications, which have multiple adverse effects including elevated risks of infection, chronic kidney injury, cardiovascular disease, and cancer. Efforts to promote allograft tolerance have focused on manipulating the adaptive immune response, but long-term allograft survival rates remain disappointing. In recent years, the innate immune system has become an attractive therapeutic target for the prevention and treatment of transplant organ rejection. Indeed, contemporary studies demonstrate that innate immune cells participate in both the initial alloimmune response and chronic allograft rejection and undergo non-permanent functional reprogramming in a phenomenon termed “trained immunity. ” Several types of innate immune cells are currently under investigation as potential therapeutics in transplantation, including myeloid-derived suppressor cells, dendritic cells, regulatory macrophages, natural killer cells, and innate lymphoid cells. In this review, we discuss the features and functions of these cell types, with a focus on their role in the alloimmune response. We examine their potential application as therapeutics to prevent or treat allograft rejection, as well as challenges in their clinical translation and future directions for investigation.
Language athletes: Dual-language code-switchers exhibit inhibitory control advantages

Recent studies have begun to examine bilingual cognition from more nuanced, experienced-based perspectives. The present study adds to this body of work by investigating the potential impact of code-switching on bilinguals’ inhibitory control abilities. Crucially, our bilingual participants originated from a predominantly dual-language environment, the interactional context which is believed to require (and therefore, potentially train) cognitive control processes related to goal-monitoring and inhibition. As such, 266 French Canadian bilinguals completed an online experiment wherein they were asked to complete a domain-general (Flanker) and a language-specific (bilingual Stroop) inhibitory control task, as well as extensive demographic and language background questionnaires. Stepwise multiple regressions (including various potential demographic and linguistic predictors) were conducted on the participants’ Flanker and Stroop effects. The results indicated that the bilinguals’ propensity to code-switch consistently yielded significant positive (but unidirectional) inhibitory control effects: dual-language bilinguals who reported more habitual French-to-English switching exhibited better goal-monitoring and inhibition abilities. For the language-specific task, the analysis also revealed that frequent unintentional code-switching may mitigate these inhibition skills. As such, the findings demonstrate that dual-language code-switchers may experience inhibitory control benefits, but only when their switching is self-reportedly deliberate. We conclude that the bilinguals’ interactional context is thus of primary importance, as the dual-language context is more conducive to intentional code-switching. Overall, the current study highlights the importance of considering individualistic language experience when it comes to examining potential bilingual executive functioning advantages.
Green biosynthesis of rare DHA-phospholipids by lipase-catalyzed transesterification with edible algal oil in solvent-free system and catalytic mechanism study

Docosahexaenoic acid (DHA)-enriched phosphatidylcholine (PC) has received significant scientific attention due to the health benefits in food and pharmaceutical products. In this work, the edible algal oil rich in DHA-triacylglycerol (DHA-TAG) without pretreatment was first used as the DHA donor for the transesterification of phospholipids (PLs) to prepare three kinds of rare PLs, including DHA-PC, DHA-phosphatidylethanolamine (DHA-PE), and DHA-phosphatidylserine (DHA-PS). Here, 153 protein structures of triacylglycerol lipase (EC 3.1.1.3) were virtually screened and evaluated by transesterification. PLA1 was the best candidate due to a higher DHA incorporation. Results showed that the transesterification of PC with DHA-TAG at 45°C and 0.7% water content (without additional water addition) could produce DHA-PC with 39.1% DHA incorporation at 30 min. The different DHA donors, including forms of fatty acid, methyl ester, and triglycerides, were compared. Molecular dynamics (MD) was used to illustrate the catalytic mechanism at the molecular level containing the diffusions of substrates, the structure-activity relationship of PLA1, and the effect of water content.
Development and validation of a new prognostic immune–inflammatory–nutritional score for predicting outcomes after curative resection for intrahepatic cholangiocarcinoma: A multicenter study

Background Immune function, nutrition status, and inflammation influence tumor initiation and progression. This was a retrospective multicenter cohort study that investigated the prognostic value and clinical relevance of immune-, inflammatory-, and nutritional-related biomarkers to develop a novel prognostic immune–inflammatory–nutritional score (PIIN score) for patients with intrahepatic cholangiocarcinoma (ICC). Methods The clinical data of 571 patients (406 in the training set and 165 in the validation set) were collected from four large hepato-pancreatico-biliary centers of patients with ICC who underwent surgical resection between January 2011 and September 2017. Twelve blood biomarkers were collected to develop the PIIN score using the LASSO Cox regression model. The predictive value was further assessed using validation datasets. Afterward, nomograms combining the PIIN score and other clinicopathological parameters were developed and validated based on the calibration curve, time-dependent AUC curves, and decision curve analysis (DCA). The primary outcomes evaluated were overall survival (OS) and recurrence-free survival (RFS) from the day of primary resection of ICC. Results Based on the albumin–bilirubin (ALBI) grade, neutrophil- to- lymphocyte ratio (NLR), prognostic nutritional index (PNI), and systemic immune- inflammation index (SII) biomarkers, the PIIN score that classified patients into high-risk and low-risk groups could be calculated. Patients with high-risk scores had shorter OS (training set, p < 0.001; validation set, p = 0.003) and RFS (training set, p < 0.001; validation set, p = 0.002) than patients with low-risk scores. The high PIIN score was also associated with larger tumors (≥5 cm), lymph node metastasis (N1 stage), multiple tumors, and high tumor grade or TNM (tumor (T), nodes (N), and metastases (M)) stage. Furthermore, the high PIIN score was a significant independent prognostic factor of OS and RFS in both the training (p < 0.001) and validation (p = 0.003) cohorts, respectively. A PIIN-nomogram for individualized prognostic prediction was constructed by integrating the PIIN score with the clinicopathological variables that yielded better predictive performance than the TNM stage. Conclusion The PIIN score, a novel immune–inflammatory–nutritional-related prognostic biomarker, predicts the prognosis in patients with resected ICC and can be a reliable tool for ICC prognosis prediction after surgery. Our study findings provide novel insights into the role of cancer-related immune disorders, inflammation, and malnutrition.
Online breath analysis with SESI/HRMS for metabolic signatures in children with allergic asthma

Introduction: There is a need to improve the diagnosis and management of pediatric asthma. Breath analysis aims to address this by non-invasively assessing altered metabolism and disease-associated processes. Our goal was to identify exhaled metabolic signatures that distinguish children with allergic asthma from healthy controls using secondary electrospray ionization high-resolution mass spectrometry (SESI/HRMS) in a cross-sectional observational study. Methods: Breath analysis was performed with SESI/HRMS. Significant differentially expressed mass-to-charge features in breath were extracted using the empirical Bayes moderated t-statistics test. Corresponding molecules were putatively annotated by tandem mass spectrometry database matching and pathway analysis. Results: 48 allergic asthmatics and 56 healthy controls were included in the study. Among 375 significant mass-to-charge features, 134 were putatively identified. Many of these could be grouped to metabolites of common pathways or chemical families. We found several pathways that are well-represented by the significant metabolites, for example, lysine degradation elevated and two arginine pathways downregulated in the asthmatic group. Assessing the ability of breath profiles to classify samples as asthmatic or healthy with supervised machine learning in a 10 times repeated 10-fold cross-validation revealed an area under the receiver operating characteristic curve of 0.83. Discussion: For the first time, a large number of breath-derived metabolites that discriminate children with allergic asthma from healthy controls were identified by online breath analysis. Many are linked to well-described metabolic pathways and chemical families involved in pathophysiological processes of asthma. Furthermore, a subset of these volatile organic compounds showed high potential for clinical diagnostic applications.
Three-dimensional and single-cell sequencing of liver cancer reveals comprehensive host-virus interactions in HBV infection

Backgrounds Hepatitis B virus (HBV) infection is a major risk factor for chronic liver diseases and liver cancer (mainly hepatocellular carcinoma, HCC), while the underlying mechanisms and host-virus interactions are still largely elusive. Methods We applied HiC sequencing to HepG2 (HBV-) and HepG2-2.2. 15 (HBV+) cell lines and combined them with public HCC single-cell RNA-seq data, HCC bulk RNA-seq data, and both genomic and epigenomic ChIP-seq data to reveal potential disease mechanisms of HBV infection and host-virus interactions reflected by 3D genome organization. Results We found that HBV enhanced overall proximal chromatin interactions (CIs) of liver cells and primarily affected regional CIs on chromosomes 13, 14, 17, and 22. Interestingly, HBV altered the boundaries of many topologically associating domains (TADs), and genes nearby these boundaries showed functional enrichment in cell adhesion which may promote cancer metastasis. Moreover, A/B compartment analysis revealed dramatic changes on chromosomes 9, 13 and 21, with more B compartments (inactive or closed) shifting to A compartments (active or open). The A-to-B regions (closing) harbored enhancers enriched in the regulation of inflammatory responses, whereas B-to-A regions (opening) were enriched for transposable elements (TE). Furthermore, we identified large HBV-induced structural variations (SVs) that disrupted tumor suppressors, NLGN4Y and PROS1. Finally, we examined differentially expressed genes and TEs in single hepatocytes with or without HBV infection, by using single-cell RNA-seq data. Consistent with our HiC sequencing findings, two upregulated genes that promote HBV replication, HNF4A and NR5A2, were located in regions with HBV-enhanced CIs, and five TEs were located in HBV-activated regions. Therefore, HBV may promote liver diseases by affecting the human 3D genome structure. Conclusion Our work promotes mechanistic understanding of HBV infection and host-virus interactions related to liver diseases that affect billions of people worldwide. Our findings may also have implications for novel immunotherapeutic strategies targeting HBV infection.
Ramulus mori (Sangzhi) alkaloids regulates gut microbiota disorder and its metabolism profiles in obese mice induced by a high-fat diet

The imbalance of gut microbiota has been confirmed to have a close pathological and physiological correlation with obesity and metabolic syndrome. Ramulus Mori (Sangzhi) Alkaloids (SZ-A) derived from twigs of mulberry was approved by the National Medical Products Administration of China in 2020 for the treatment of type 2 diabetes mellitus. In addition to its hypoglycemic effect, previous studies have confirmed that SZ-A also alleviates high-fat diet-induced obesity and non-alcoholic fatty liver disease and ameliorates obesity-linked adipose tissue metabolism and inflammation, indicating the potential of SZ-A to regulate obesity and metabolic syndrome. However, whether SZ-A can improve obesity and metabolic syndrome by regulating gut microbiota and its metabolism profiles remains unclear. The purpose of this study was to assess the effect of SZ-A on gut microbiota in obese mice and to explore the association among changes in gut microbiota, obesity, and lipid metabolism. The results showed that oral administration of SZ-A could significantly reduce body weight, fat mass, and the level of total cholesterol and low-density lipoprotein in serum in obese mice induced by a high-fat diet. Interestingly, SZ-A also regulated gut microbiota and changed the fecal metabolite composition of obese mice. Compared with the high-fat diet group, the ratio of Firmicutes to Bacteroides changed at the phylum level and the abundance of Bifidobacterium and Akkermansia muciniphila significantly increased at the genus level in the SZ-A group. The gut microbiota of the SZ-A group was reshaped and the relative abundance of microbial genes in bile acid metabolism and fatty acid metabolism were altered, which was consistent with the metabolomics results. Additionally, SZ-A greatly enriched the number of goblet cells and reduced inflammatory colon injury and pro-inflammatory macrophage infiltration induced by a high-fat diet in obese mice. In conclusion, SZ-A can alleviate obesity and metabolic syndrome by improving the gut microbiota and its metabolism profiles of obese mice induced by a high-fat diet.
Causal effects of gut microbiota on the risk of chronic kidney disease: a Mendelian randomization study

Background Previous studies have reported that gut microbiota is associated with an increased risk of chronic kidney disease (CKD) progression. However, whether gut microbiota has a causal effect on the development of CKD has not been revealed. Thus, we aimed to analyze the potential causal effect of gut microbiota on the risk of CKD using mendelian randomization (MR) study. Materials and Methods Independent single nucleotide polymorphisms closely associated with 196 gut bacterial taxa (N = 18340) were identified as instrumental variables. Two-sample MR was performed to evaluate the causal effect of gut microbiota on CKD (N = 480698), including inverse-variance-weighted (IVW) method, weighted median method, MR-Egger, mode-based estimation and MR-PRESSO. The robustness of the estimation was tested by a series of sensitivity analyses including Cochran’s Q test, MR-Egger intercept analysis, leave-one-out analysis and funnel plot. Statistical powers were also calculated. Results The genetically predicted higher abundance of order Desulfovibrionales was causally associated with an increased risk of CKD (odds ratio = 1.15, 95% confidence interval: 1.05-1.26; p = 0.0026). Besides, we also detected potential causalities between nine other taxa (Eubacterium eligens group, Desulfovibrionaceae, Ruminococcaceae UCG-002, Deltaproteobacteria, Lachnospiraceae UCG-010, Senegalimassilia, Peptostreptococcaceae, Alcaligenaceae and Ruminococcus torques group) and CKD (p < 0.05). No heterogeneity or pleiotropy was detected for significant estimates. Conclusion We found that Desulfovibrionales and nine other taxa are associated with CKD, thus confirming that gut microbiota plays an important role in the pathogenesis of CKD. Our work also provides new potential indicators and targets for screening and prevention of CKD.
Regularization in Regression : Partial Least Squares and Related Models

High-dimensional data sets with a large number of explanatory variables are increasingly important in applications of regression analysis. It is well known that most traditional statistical techniques, such as the Ordinary Least Square (OLS) estimation do not perform well with such data and are either ill-conditioned or undefined. Thus a need for regularization arises. In the literature, various regularization methods have been suggested; amongst the most famous is the Partial Least Squares (PLS) regression method. The aim of this thesis is to consolidate and extend results in the literature to (a) show that PLS estimation can be regarded as estimation under a statistical model based on the so-called “Krylov hypothesis”, (b) introduce a derivation of the PLS estimator as an approximate maximum likelihood estimator under this model and (c) propose an algorithm to modify the PLS estimator to yield an exact maximum likelihood estimator under the same model. It will be shown that the constrained optimization problem in (c) can be recast as an unconstrained optimization problem on the Grassmann manifold. Two simulation studies consisting of a number of examples (using artificial data) in low dimensions will be presented. These allow us to make a visual inspection of the Krylov maximum likelihood as it varies over the Grassmann manifolds and hence characteristics of the data for which KML can be expected to give better results than PLS can be identified. However it was observed that these ideas make sense only when there is a small number of explanatory variables. As soon as the number of explanatory variables is moderate (say p = 10) or of order thousands, exploring how the different parameters effect the behaviour of the objective function is not straight forward. The predictive ability of the Ordinary Least Squares (OLS), Partial Least Squares (PLS) and Krylov Maximum Likelihood (KML) regression methods when applied to artificial data (for which the sample size is bigger than the number of explanatory variables) with and without multicollinearity is explored. Finally the predictive ability of the Partial Least Squares (PLS) and Krylov Maximum Likelihood (KML) regression methods was also compared on two real life high-dimensional data sets from the literature.