Factors Associated with Nonalcoholic Fatty Liver Disease in a Non-Overweight/Obese and Overweight/Obese Chinese Population at Risk for Metabolic Syndrome: A Cross-Sectional Multicenter Study.

Background: To investigate the association of demographic, clinical, and metabolic factors with nonalcoholic fatty liver disease (NAFLD) in a non-overweight/obese and overweight/obese Chinese population at risk for metabolic syndrome. Patients and Method: A cross-sectional multicenter study was conducted using convenience sampling from eight selected counties/cities in Zhejiang, China, between May 2021 and September 2022. Demographics, epidemiological, anthropometric, and clinical characteristics were obtained from a questionnaire. Least absolute shrinkage and selection operator (LASSO)-logistic regression analysis was used to identify the variables associated with NAFLD. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to evaluate the diagnostic value and clinical utility of the variables and models. Results: A total of 1739 patients were enrolled in the final analysis, 345 (19.8%) were non-overweight/obese and 1394 (80.2%) were overweight/obese participants. There were 114 (33.0%) and 1094 (78.5%) patients who met the criteria for NAFLD in the non-overweight/obese participants and the overweight/obese participants respectively. Older age, current smoking, higher triglyceride (TG) levels, higher AST levels, higher albumin levels, lower insulin levels, and higher controlled attenuation parameter (CAP) scores were associated with NAFLD in both non-overweight/obese and overweight/obese participants. The combination of TG+CAP scores had strong predictive values for NAFLD, especially in non-overweight/obese (Area Under Curve = 0.812, 95% confidence interval: 0.764-0.863). DCA showed a superior net benefit of the TG+CAP score over other variables or models, suggesting a better clinical utility in identifying NAFLD. Conclusions: More stringent lipid management strategies remain essential, and the convenience and efficacy of transient elastography for liver steatosis should be recognized, especially in the non-overweight/obese population.

A 10-year retrospective cohort of diabetic patients in a large medical institution: Utilizing multiple machine learning models for diabetic kidney disease prediction.

Objective: As the prevalence of diabetes steadily increases, the burden of diabetic kidney disease (DKD) is also intensifying. In response, we have utilized a 10-year diabetes cohort from our medical center to train machine learning-based models for predicting DKD and interpreting relevant factors. Methods: Employing a large dataset from 73,101 hospitalized type 2 diabetes patients at The First Affiliated Hospital of Zhengzhou University, we analyzed demographic and medication data. Machine learning models, including XGBoost, CatBoost, LightGBM, Random Forest, AdaBoost, GBDT (gradient boosting decision tree), and SGD (stochastic gradient descent), were trained on these data, focusing on interpretability by SHAP. SHAP explains the output of the models by assigning an importance value to each feature for a particular prediction, enabling a clear understanding of how individual features influence the prediction outcomes. Results: The XGBoost model achieved an area under the curve (AUC) of 0.95 and an area under the precision-recall curve (AUPR) of 0.76, while CatBoost recorded an AUC of 0.97 and an AUPR of 0.84. These results underscore the effectiveness of these models in predicting DKD in patients with type 2 diabetes. Conclusions: This study provides a comprehensive approach for predicting DKD in patients with type 2 diabetes, employing machine learning techniques. The findings are crucial for the early detection and intervention of DKD, offering a roadmap for future research and healthcare strategies in diabetes management. Additionally, the presence of non-diabetic kidney diseases and diabetes with complications was identified as significant factors in the development of DKD.

Bibliometric analysis of research on gut microbiota and bile acids: publication trends and research frontiers.

The gut microbiota is widely regarded as a "metabolic organ" that could generate myriad metabolites to regulate human metabolism. As the microbiota metabolites, bile acids (BAs) have recently been identified as the critical endocrine molecules that mediate the cross-talk between the host and intestinal microbiota. This study provided a comprehensive insight into the gut microbiota and BA research through bibliometric analysis from 2003 to 2022. The publications on this subject showed a dramatic upward trend. Although the USA and China have produced the most publications, the USA plays a dominant role in this expanding field. Specifically, the University of Copenhagen was the most productive institution. Key research hotspots are the gut-liver axis, short-chain fatty acids (SCFAs), cardiovascular disease (CVD), colorectal cancer (CRC), and the farnesoid x receptor (FXR). The molecular mechanisms and potential applications of the gut microbiota and BAs in cardiometabolic disorders and gastrointestinal cancers have significant potential for further research.

Eâ ¡B Mutation Reduces the Pathogenicity of Listeria monocytogenes by Negatively Regulating Biofilm Formation Ability, Infective Capacity, and Virulence Gene Expression.

To explore the role of the membrane permease ⅡB (EⅡB) gene of Listeria pathogenicity island 4 (LIPI-4) in the virulence of Listeria monocytogenes, both an EⅡB deletion strain (∆EⅡB) and a complemented strain were constructed. In vitro experiments demonstrated that EⅡB deletion affected the biofilm formation ability of the wild-type strain (Lm928). Moreover, this deletion decreased the intracellular proliferation abilities of L. monocytogenes. Mice infected with ∆EⅡB survived longer and experienced less weight loss on days 1, 2, and 3 post-infection. The bacterial load in the liver tissue of ∆EⅡB-infected mice was significantly reduced, and a considerable decrease in the blood levels of inflammatory cytokines IL-ß, IL-6, IL-10, and TNF-α were observed. Following EⅡB deletion, 65% (13/20) of genes were downregulated, 25% (5/20) were upregulated, and 10% (2/20) showed no change. These findings suggest that EⅡB deletion may reduce both the in vivo and in vitro virulence levels as well as the biofilm formation ability of Lm928 by downregulating the transcription levels of genes associated with virulence and biofilm formation. These findings provide a foundation for further examining the pathogenic mechanisms of LIPI-4 and EⅡB in L. monocytogenes.

Biofilm Formation, Motility, and Virulence of Listeria monocytogenes Are Reduced by Deletion of the Gene lmo0159, a Novel Listerial LPXTG Surface Protein.

Listeria monocytogenes (L. monocytogenes) is a foodborne pathogen that causes listeriosis in humans and other animals. Surface proteins with the LPXTG motif have important roles in the virulence of L. monocytogenes. Lmo0159 is one such protein, but little is known about its role in L. monocytogenes virulence, motility, and biofilm formation. Here, we constructed and characterized a deletion mutant of lmo0159 (∆lmo0159). We analyzed not only the capacity of biofilm formation, motility, attachment, and intracellular growth in different cell types but also LD50; bacterial load in mice's liver, spleen, and brain; expression of virulence genes; and survival time of mice after challenge. The results showed that the cross-linking density of the biofilm of ∆lmo0159 strain was lower than that of WT by microscopic examination. The expression of biofilm-formation and virulence genes also decreased in the biofilm state. Subsequently, the growth and motility of ∆lmo0159 in the culture medium were enhanced. Conversely, the growth and motility of L. monocytogenes were attenuated by ∆lmo0159 at both the cellular and mouse levels. At the cellular level, ∆lmo0159 reduced plaque size; accelerated scratch healing; and attenuated the efficiency of adhesion, invasion, and intracellular proliferation in swine intestinal epithelial cells (SIEC), RAW264.7, mouse-brain microvascular endothelial cells (mBMEC), and human-brain microvascular endothelial cells (hCMEC/D3). The expression of virulence genes was also inhibited. At the mouse level, the LD50 of the ∆lmo0159 strain was 100.97 times higher than that of the WT strain. The bacterial load of the ∆lmo0159 strain in the liver and spleen was lower than that of the WT strain. In a mouse model of intraperitoneal infection, the deletion of the lmo0159 gene significantly prolonged the survival time of the mice, suggesting that the lmo0159 deletion mutant also exhibited reduced virulence. Thus, our study identified lmo0159 as a novel virulence factor among L. monocytogenes LPXTG proteins.

GP's GP, general practitioner's health and willingness to contract family doctors in China: a national cross-sectional study.

OBJECTIVES: General practitioners are trained to care for patients with a high level of responsibility and professional competency. However, there are few reports on the physical and mental health status of general practitioners (GPs) in China, particularly regarding help seeking and self-treatment. The primary aims of this study were to explore GPs' expectations of their own family doctors and their reflection on role positioning, and to explore the objective factors that hinder the system of family doctors. STUDY DESIGN: Cross-sectional study. METHODS: We conducted an online survey of Chinese GPs. Descriptive statistics were used to summarize the findings. RESULTS: More than half of the participants (57.20%) reported that their health was normal over the past year. A total of 420 participants (23.35%) reported having chronic diseases. For sleep duration, 1205 participants (66.98%) reported sleeping 6-8 h per day; 473 participants (26.29%) reported chronic insomnia. Two hundred thirty-one participants (12.84%) had possible depression. A total of 595 (33.07%) participants reported that they had contracted a fixed family doctor. In terms of preventing themselves from contracting for a family doctor, the following factors were identified: lack of sufficient time (54.81%), could solve obstacles themselves (50.97%), and embarrassment (24.24%). The proportion of the contract group (12.44%) taking personal relationship as a consideration was higher than that of the non-contract group (7.64%) (χ2 = 10.934 P = 0.01). Most participants (79.90%) in the non-signed group reported never having seen a family doctor. In terms of obstacles, more than half of the signed group thought that they could solve obstacles themselves, while the non-signed group (39.20%) was less confident in the ability of family doctors than the signed group (29.75%) (χ2 = 15.436, P < 0.01). CONCLUSIONS: GPs work under great pressure and lack of self-care awareness, resulting in an increased prevalence of health conditions. Most GPs did not have a regular family doctor. Having a family doctor with a fixed contract is more conducive to the scientific management of their health and provides a reasonable solution to health problems. The main factors hindering GPs from choosing a family doctor were time consumption, abilities to solve obstacles themselves, and trust in the abilities of GPs. Therefore, simplifying the process of family doctor visits, Changing the GPs' medical cognition, and strengthening the policy of GP training would be conducive to promoting a family doctor system that enhances hierarchical diagnosis and treatment. International collaboration could integrate GP health support into global healthcare system.

Associations between low muscle mass and clinical characteristics of health population in China.

Objectives: The primary aim of this study is to discern the association between specific clinical parameters and low muscle mass (LMM). We endeavor to elucidate the determinants of LMM and the predictive potency of individual factors. Methods: In this retrospective cross-sectional study, we encompassed 450 older adult Chinese participants (252 males and 198 females). Muscle mass quantifications were performed using bioelectrical impedance analysis. Comprehensive data encompassing demographic details (age, sex, height, and weight) and laboratory results (complete blood count, thyroid function, liver function, and renal function) were systematically recorded. Logistic regression models, coupled with receiver operating characteristic curve analytics, were employed to ascertain the variables influencing LMM and to evaluate the predictive validity of each parameter on LMM. Results: Upon confounding adjustment for age, gender, body mass index (BMI), and free thyroxine (FT4) persisted as a determinant of LMM. Specifically, individuals with an FT4 exceeding 1.105 ng/dL exhibited a 1.803-fold increased propensity for LMM relative to those with FT4 values below the specified threshold. Incorporating age, gender, BMI, and FT4 in the diagnostic algorithm enhanced the precision of LMM. The results differ between men and women. In the male population, we can still observe that FT4 has a certain value in the diagnosis of LMM, but this phenomenon is not found in the female population. Conclusions: Elevated FT4 concentrations, albeit within clinically accepted limits, are inversely associated with muscle mass. As such, FT4 could be postulated as a potential biomarker for LMM in geriatric individuals, especially in the male group.

Halide-free CO2 cycloaddition onto styrene oxide catalysed by first row transition-metal derivatives of polyoxotungstates.

Quaternary ammonium salts of metal derivatives of polyoxometalates [XW11O39M(H2O)]n- (X = P, Si; M = Cr, Mn, Co, Ni, Zn) were successfully tested instead of quaternary ammonium halides as catalysts in the cycloaddition of CO2 to styrene oxide. Remarkably, they gave very satisfactory yields of styrene carbonate at moderate temperature (80 °C).

A genome-wide CRISPR screening uncovers that TOB1 acts as a key host factor for FMDV infection via both IFN and EGFR mediated pathways.

The interaction between foot-and-mouth disease virus (FMDV) and the host is extremely important for virus infection, but there are few researches on it, which is not conducive to vaccine development and FMD control. In this study, we designed a porcine genome-scale CRISPR/Cas9 knockout library containing 93,859 single guide RNAs targeting 16,886 protein-coding genes, 25 long ncRNAs, and 463 microRNAs. Using this library, several previously unreported genes required for FMDV infection are highly enriched post-FMDV selection in IBRS-2 cells. Follow-up studies confirmed the dependency of FMDV on these genes, and we identified a functional role for one of the FMDV-related host genes: TOB1 (Transducer of ERBB2.1). TOB1-knockout significantly inhibits FMDV infection by positively regulating the expression of RIG-I and MDA5. We further found that TOB1-knockout led to more accumulation of mRNA transcripts of transcription factor CEBPA, and thus its protein, which further enhanced transcription of RIG-I and MDA5 genes. In addition, TOB1-knockout was shown to inhibit FMDV adsorption and internalization mediated by EGFR/ERBB2 pathway. Finally, the FMDV lethal challenge on TOB1-knockout mice confirmed that the deletion of TOB1 inhibited FMDV infection in vivo. These results identify TOB1 as a key host factor involved in FMDV infection in pigs.

Plasminogen activator urokinase interacts with the fusion protein and antagonizes the growth of Peste des petits ruminants virus.

Peste des petits ruminants is an acute and highly contagious disease caused by the Peste des petits ruminants virus (PPRV). Host proteins play a crucial role in viral replication. However, the effect of fusion (F) protein-interacting partners on PPRV infection is poorly understood. In this study, we found that the expression of goat plasminogen activator urokinase (PLAU) gradually decreased in a time- and dose-dependent manner in PPRV-infected goat alveolar macrophages (GAMs). Goat PLAU was subsequently identified using co-immunoprecipitation and confocal microscopy as an F protein binding partner. The overexpression of goat PLAU inhibited PPRV growth and replication, whereas silencing goat PLAU promoted viral growth and replication. Additionally, we confirmed that goat PLAU interacted with a virus-induced signaling adapter (VISA) to antagonize F-mediated VISA degradation, increasing the production of type I interferon. We also found that goat PLAU reduced the inhibition of PPRV replication in VISA-knockdown GAMs. Our results show that the host protein PLAU inhibits the growth and replication of PPRV by VISA-triggering RIG-I-like receptors and provides insight into the host protein that antagonizes PPRV immunosuppression.IMPORTANCEThe role of host proteins that interact with Peste des petits ruminants virus (PPRV) fusion (F) protein in PPRV replication is poorly understood. This study confirmed that goat plasminogen activator urokinase (PLAU) interacts with the PPRV F protein. We further discovered that goat PLAU inhibited PPRV replication by enhancing virus-induced signaling adapter (VISA) expression and reducing the ability of the F protein to degrade VISA. These findings offer insights into host resistance to viral invasion and suggest new strategies and directions for developing PPR vaccines.

Vimentin inhibits peste des petits ruminants virus replication by interaction with nucleocapsid protein.

The Peste des petits ruminant virus (PPRV) is a member of the Paramyxoviridae family and is classified into the genus Measles virus. PPRV predominantly infects small ruminants, leading to mortality rates of nearly 100%, which have caused significant economic losses in developing countries. Host proteins are important in virus replication, but the PPRV nucleocapsid (N) protein-host interacting partners for regulating PPRV replication remain unclear. The present study confirmed the interaction between PPRV-N and the host protein vimentin by co-immunoprecipitation and co-localization experiments. Overexpression of vimentin suppressed PPRV replication, whereas vimentin knockdown had the opposite effect. Mechanistically, N was subjected to degradation via the ubiquitin/proteasome pathway, where vimentin recruits the E3 ubiquitin ligase NEDD4L to fulfill N-ubiquitination, resulting in the degradation of the N protein. These findings suggest that the host protein vimentin and E3 ubiquitin ligase NEDD4L have an anti-PPRV effect.

African Swine Fever Virus I267L Is a Hemorrhage-Related Gene Based on Transcriptome Analysis.

African swine fever (ASF) is an acute and severe disease transmitted among domestic pigs and wild boars. This disease is notorious for its high mortality rate and has caused great losses to the world's pig industry in the past few years. After infection, pigs can develop symptoms such as high fever, inflammation, and acute hemorrhage, finally leading to death. African swine fever virus (ASFV) is the causal agent of ASF; it is a large DNA virus with 150-200 genes. Elucidating the functions of each gene could provide insightful information for developing prevention and control methods. Herein, to investigate the function of I267L, porcine alveolar macrophages (PAMs) infected with an I267L-deleted ASFV strain (named ∆I267L) and wild-type ASFV for 18 h and 36 h were taken for transcriptome sequencing (RNA-seq). The most distinct different gene that appeared at both 18 hpi (hours post-infection) and 36 hpi was F3; it is the key link between inflammation and coagulation cascades. KEGG analysis (Kyoto encyclopedia of genes and genomes analysis) revealed the complement and coagulation cascades were also significantly affected at 18 hpi. Genes associated with the immune response were also highly enriched with the deletion of I267L. RNA-seq results were validated through RT-qPCR. Further experiments confirmed that ASFV infection could suppress the induction of F3 through TNF-α, while I267L deletion partially impaired this suppression. These results suggest that I267L is a pathogenicity-associated gene that modulates the hemorrhages of ASF by suppressing F3 expression. This study provides new insights into the molecular mechanisms of ASFV pathogenicity and potential targets for ASFV prevention and control.

Building gender-specific sexually transmitted infection risk prediction models using CatBoost algorithm and NHANES data.

BACKGROUND AND AIMS: Sexually transmitted infections (STIs) are a significant global public health challenge due to their high incidence rate and potential for severe consequences when early intervention is neglected. Research shows an upward trend in absolute cases and DALY numbers of STIs, with syphilis, chlamydia, trichomoniasis, and genital herpes exhibiting an increasing trend in age-standardized rate (ASR) from 2010 to 2019. Machine learning (ML) presents significant advantages in disease prediction, with several studies exploring its potential for STI prediction. The objective of this study is to build males-based and females-based STI risk prediction models based on the CatBoost algorithm using data from the National Health and Nutrition Examination Survey (NHANES) for training and validation, with sub-group analysis performed on each STI. The female sub-group also includes human papilloma virus (HPV) infection. METHODS: The study utilized data from the National Health and Nutrition Examination Survey (NHANES) program to build males-based and females-based STI risk prediction models using the CatBoost algorithm. Data was collected from 12,053 participants aged 18 to 59 years old, with general demographic characteristics and sexual behavior questionnaire responses included as features. The Adaptive Synthetic Sampling Approach (ADASYN) algorithm was used to address data imbalance, and 15 machine learning algorithms were evaluated before ultimately selecting the CatBoost algorithm. The SHAP method was employed to enhance interpretability by identifying feature importance in the model's STIs risk prediction. RESULTS: The CatBoost classifier achieved AUC values of 0.9995, 0.9948, 0.9923, and 0.9996 and 0.9769 for predicting chlamydia, genital herpes, genital warts, gonorrhea, and overall STIs infections among males. The CatBoost classifier achieved AUC values of 0.9971, 0.972, 0.9765, 1, 0.9485 and 0.8819 for predicting chlamydia, genital herpes, genital warts, gonorrhea, HPV and overall STIs infections among females. The characteristics of having sex with new partner/year, times having sex without condom/year, and the number of female vaginal sex partners/lifetime have been identified as the top three significant predictors for the overall risk of male STIs. Similarly, ever having anal sex with a man, age and the number of male vaginal sex partners/lifetime have been identified as the top three significant predictors for the overall risk of female STIs. CONCLUSIONS: This study demonstrated the effectiveness of the CatBoost classifier in predicting STI risks among both male and female populations. The SHAP algorithm revealed key predictors for each infection, highlighting consistent demographic characteristics and sexual behaviors across different STIs. These insights can guide targeted prevention strategies and interventions to alleviate the impact of STIs on public health.

Generation and optimization of off-the-shelf immunotherapeutics targeting TCR-Vß2+ T cell malignancy.

Current treatments for T cell malignancies encounter issues of disease relapse and off-target toxicity. Using T cell receptor (TCR)Vß2 as a model, here we demonstrate the rapid generation of an off-the-shelf allogeneic chimeric antigen receptor (CAR)-T platform targeting the clone-specific TCR Vß chain for malignant T cell killing while limiting normal cell destruction. Healthy donor T cells undergo CRISPR-induced TRAC, B2M and CIITA knockout to eliminate T cell-dependent graft-versus-host and host-versus-graft reactivity. Second generation 4-1BB/CD3zeta CAR containing high affinity humanized anti-Vß scFv is expressed efficiently on donor T cells via both lentivirus and adeno-associated virus transduction with limited detectable pre-existing immunoreactivity. Our optimized CAR-T cells demonstrate specific and persistent killing of Vß2+ Jurkat cells and Vß2+ patient derived malignant T cells, in vitro and in vivo, without affecting normal T cells. In parallel, we generate humanized anti-Vß2 antibody with enhanced antibody-dependent cellular cytotoxicity (ADCC) by Fc-engineering for NK cell ADCC therapy.

The CUL5 E3 ligase complex negatively regulates central signaling pathways in CD8+ T cells.

CD8+ T cells play an important role in anti-tumor immunity. Better understanding of their regulation could advance cancer immunotherapies. Here we identify, via stepwise CRISPR-based screening, that CUL5 is a negative regulator of the core signaling pathways of CD8+ T cells. Knocking out CUL5 in mouse CD8+ T cells significantly improves their tumor growth inhibiting ability, with significant proteomic alterations that broadly enhance TCR and cytokine signaling and their effector functions. Chemical inhibition of neddylation required by CUL5 activation, also enhances CD8 effector activities with CUL5 validated as a major target. Mechanistically, CUL5, which is upregulated by TCR stimulation, interacts with the SOCS-box-containing protein PCMTD2 and inhibits TCR and IL2 signaling. Additionally, CTLA4 is markedly upregulated by CUL5 knockout, and its inactivation further enhances the anti-tumor effect of CUL5 KO. These results together reveal a negative regulatory mechanism for CD8+ T cells and have strong translational implications in cancer immunotherapy.

A few-shot disease diagnosis decision making model based on meta-learning for general practice.

BACKGROUND: Diagnostic errors have become the biggest threat to the safety of patients in primary health care. General practitioners, as the "gatekeepers" of primary health care, have a responsibility to accurately diagnose patients. However, many general practitioners have insufficient knowledge and clinical experience in some diseases. Clinical decision making tools need to be developed to effectively improve the diagnostic process in primary health care. The long-tailed class distributions of medical datasets are challenging for many popular decision making models based on deep learning, which have difficulty predicting few-shot diseases. Meta-learning is a new strategy for solving few-shot problems. METHODS AND MATERIALS: In this study, a few-shot disease diagnosis decision making model based on a model-agnostic meta-learning algorithm (FSDD-MAML) is proposed. The MAML algorithm is applied in a knowledge graph-based disease diagnosis model to find the optimal model parameters. Moreover, FSDD-MAML can learn learning rates for all modules of the knowledge graph-based disease diagnosis model. For n-way, k-shot learning tasks, the inner loop of FSDD-MAML performs multiple gradient update steps to learn internal features in disease classification tasks using n×k examples, and the outer loop of FSDD-MAML optimizes the meta-objective to find the associated optimal parameters and learning rates. FSDD-MAML is compared with the original knowledge graph-based disease diagnosis model and other meta-learning algorithms based on an abdominal disease dataset. RESULT: Meta-learning algorithms can greatly improve the performance of models in top-1 evaluation compared with top-3, top-5, and top-10 evaluations. The proposed decision making model FSDD-MAML outperforms all the other models, with a precision@1 of 90.02 %. We achieve state-of-the-art performance in the diagnosis of all diseases, and the prediction performance for few-shot diseases is greatly improved. For the two groups with the fewest examples of diseases, FSDD-MAML achieves relative increases in precision@1 of 29.13 % and 21.63 % compared with the original knowledge graph-based disease diagnosis model. In addition, we analyze the reasoning process of several few-shot disease predictions and provide an explanation for the results. CONCLUSION: The decision making model based on meta-learning proposed in this paper can support the rapid diagnosis of diseases in general practice and is especially capable of helping general practitioners diagnose few-shot diseases. This study is of profound significance for the exploration and application of meta-learning to few-shot disease assessment in general practice.

An Explainable and Personalized Cognitive Reasoning Model Based on Knowledge Graph: Toward Decision Making for General Practice.

General practice plays a prominent role in primary health care (PHC). However, evidence has shown that the quality of PHC is still unsatisfactory, and the accuracy of clinical diagnosis and treatment must be improved in China. Decision making tools based on artificial intelligence can help general practitioners diagnose diseases, but most existing research is not sufficiently scalable and explainable. An explainable and personalized cognitive reasoning model based on knowledge graph (CRKG) proposed in this article can provide personalized diagnosis, perform decision making in general practice, and simulate the mode of thinking of human beings utilizing patients' electronic health records (EHRs) and knowledge graph. Taking abdominal diseases as the application point, an abdominal disease knowledge graph is first constructed in a semiautomated manner. Then, the CRKG designed referring to dual process theory in cognitive science involves the update strategy of global graph representations and reasoning on a personal cognitive graph by adopting the idea of graph neural networks and attention mechanisms. For the diagnosis of diseases in general practice, the CRKG outperforms all the baselines with a precision@1 of 0.7873, recall@10 of 0.9020 and hits@10 of 0.9340. Additionally, the visualization of the reasoning process for each visit of a patient based on the knowledge graph enhances clinicians' comprehension and contributes to explainability. This study is of great importance for the exploration and application of decision making based on EHRs and knowledge graph.

Disease Burden and Epidemiological Trends of Chronic Kidney Disease at the Global, Regional, National Levels from 1990 to 2019.

BACKGROUND: Chronic kidney disease (CKD) is a serious public health issue worldwide, but the disease burden of CKD caused by different etiologies and changing trends has not been fully examined. METHODS: We collected data from Global Burden of Disease Study 2019 (GBD 2019), including incident cases, age-standardized incidence rate (ASIR), disability-adjusted life years (DALYs), and age-standardized DALY rate between 1990 and 2019 by region, etiology, age, and sex, and calculated the estimated annual percentage change (EAPC) of the rate to evaluate the epidemiological trends. RESULTS: Globally, incident cases of CKD increased from 7.80 million in 1990 to 18.99 million in 2019, and DALYs increased from 21.50 million to 41.54 million. ASIR increased with an EAPC of 0.69 (95% uncertainty interval [UI] 0.49-0.89) and reached 233.65 per 100,000 in 2019, while the age-standardized DALY rate increased with an EAPC of 0.30 (95% UI 0.17-0.43) and reached 514.86 per 100,000. North Africa and the Middle East, central Latin America, and North America had the highest ASIR in 2019. Central Latin America had the highest age-standardized DALY rate, meanwhile. Almost all countries experienced an increase in ASIR, and over 50% of countries had an increasing trend in age-standardized DALY rate from 1990 to 2019. CKD due to diabetes mellitus type 2 and hypertension accounted for the largest disease burden with 85% incident cases and 66% DALYs in 2019 of known causes, with the highest growth in age-standardized DALY rate and a similar geographic pattern to that of total CKD. Besides, the highest incidence rate of total and four specific CKDs were identified in people aged 70 plus years, who also had the highest DALY rate with a stable trend after 2010. Females had a higher ASIR, while males had a higher age-standardized DALY rate, the gap of which was most distinctive in CKD due to hypertension. CONCLUSION: The disease burden of CKD remains substantial and continues to grow globally. From 1990 to 2019, global incident cases of CKD have more than doubled and DALYs have almost doubled, and surpassed 40 million years. CKD due to diabetes mellitus type 2 and hypertension contributed nearly 2/3 of DALYs in 2019 of known causes, and had witnessed the highest growth in age-standardized DALY rate. Etiology-specific prevention strategies should be placed as a high priority on the goal of precise control of CKD.

Folate deficiency promotes cervical squamous carcinoma SiHa cells progression by targeting miR-375/FZD4/ß-catenin signaling.

Epidemiological studies suggest an association between folate deficiency (FD) and cervical squamous cell carcinoma (SCC) progression. However, the underlying mechanism is unclear. Our study showed that FD-driven downregulation of miR-375 promoted proliferation of SCC SiHa cells and progression of xenograft tumors developed from SiHa; however, the exact mechanism of this process remained unclear. The current study aimed to elucidate the underlying mechanisms by which FD promotes the progression of SiHa cells by downregulating miR-375 expression. The results showed that miR-375 acted as a suppressor of SCC and inhibited the proliferation, migration, and invasion of SiHa cells. The FZD4 gene was identified as a target gene of miR-375, which can reverse the anti-onco effect of miR-375 and promote the proliferation and migration of SiHa cells. Furthermore, the regulatory effects of miR-375 and FZD4 on SiHa cells may be achieved by activating the ß-catenin signaling pathway. Moreover, FD may regulate the expression of miR-375 by regulating its DNA methylation level in the promoter region. In conclusion, our study reveals that FD regulates the miR-375/FZD4 axis by increasing the methylation of the miR-375 promoter, thereby activating ß-catenin signaling to promote SiHa cells progression. This study may provide new insights into the role of folic acid in the prevention and treatment of SCC.

Differential Roles of Interleukin-6 in Severe Acute Respiratory Syndrome-Coronavirus-2 Infection and Cardiometabolic Diseases.

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection can lead to a cytokine storm, unleashed in part by pyroptosis of virus-infected macrophages and monocytes. Interleukin-6 (IL-6) has emerged as a key participant in this ominous complication of COVID-19. IL-6 antagonists have improved outcomes in patients with COVID-19 in some, but not all, studies. IL-6 signaling involves at least 3 distinct pathways, including classic-signaling, trans-signaling, and trans-presentation depending on the localization of IL-6 receptor and its binding partner glycoprotein gp130. IL-6 has become a therapeutic target in COVID-19, cardiovascular diseases, and other inflammatory conditions. However, the efficacy of inhibition of IL-6 signaling in metabolic diseases, such as obesity and diabetes, may depend in part on cell type-dependent actions of IL-6 in controlling lipid metabolism, glucose uptake, and insulin sensitivity owing to complexities that remain to be elucidated. The present review sought to summarize and discuss the current understanding of how and whether targeting IL-6 signaling ameliorates outcomes following SARS-CoV-2 infection and associated clinical complications, focusing predominantly on metabolic and cardiovascular diseases.