Cardiovascular diseases that develop from hypercholesterolemia-induced atherosclerosis have emerged as a significant threat to human health.Recently,probiotics exhibiting cholesterol-lowering properties have emerged as a prominent area of research.Numerous studies have demonstrated that Lactobacillus reuteri can effectively reduce endogenous cholesterol synthesis,regulate cholesterol transport,and promote cholesterol degradation by modulating the expression of key genes,such as sterol-regulatory element binding protein 2,3-hydroxy-3-methyl-glutaryl coenzyme A reductase,and cholesterol 7 alpha-hydroxylase,in both the liver and intestinal epithelial cells of the host.This leads to a notable decrease in total cholesterol and low-density lipoprotein cholesterol levels in the host serum.The present paper offers a comprehensive overview of the underlying mechanisms responsible for the cholesterol-lowering effects exerted by L.reuteri,aiming to provide valuable insights into the treatment of hypercholesterolemia and the development of probiotics with cholesterol-lowering properties.

Objective:Near-infrared(NIR)spectroscopy technology faces the problem of insufficient model generalization due to individual differences in non-invasive blood glucose testing,in order to solve this problem,to improve data utilization,and to build predictive models with stronger generalization ability,this study introduces a transfer learning method to study the NIR spectroscopy non-invasive glucose testing.Methods:Migration learning is a machine learning technique that aims to improve task performance in the target domain by transferring knowledge from the source domain to the target domain.In this study,we used community population data as the source domain and student population data as the target domain to improve the performance of the noninvasive glucose detection model on the target domain.In order to verify the effectiveness of migration learning,this study compares the performance of the model before and after migration learning.Results:the model's performance on the noninvasive glucose detection task is significantly improved by the migration learning strategy,and the MAPE and MAE of the migrated model decreases by 52.5460％and 6.0805％,respectively,and the RMSE and MSE decreases by 10.7215％and 12.1135％.Conclusions:This study demonstrates the promising application of transfer learning in the field of non-invasive blood glucose detection,which is expected to realize portable and continuous blood glucose monitoring in the future by migrating the features that are difficult to access in the source domain but are related to blood glucose values to the target domain,which will greatly improve the quality of life of diabetic patients.Advances in noninvasive glucose testing technology will not only reduce patients' pain,but also provide a more convenient means of glucose monitoring,which will provide strong support for diabetes management.

Objective:To analyze the relationship between microRNA-21(miR-21)expression and the risk of very early relapse post-induction chemotherapy in children with acute lymphoblastic leukemia(ALL).Methods:A total of 110 newly diagnosed children with ALL admitted to Huanggang Central Hospital from March 2020 to September 2022 were included.All patients received induction chemotherapy according to the CCLG-2008 protocol.The patients who achieved complete response(CR)after induction chemotherapy were followed up for 18 months,with very early relapse as the endpoint event.Then the patients were divided into a relapse group and a non-relapse group.Cox regression was used to analyze the influencing factors of very early relapse after induction chemotherapy in children with ALL.ROC curve and decision curve were used to evaluate the predictive value of peripheral blood miR-21 for very early relapse after induction chemotherapy in children with ALL.Restricted cubic splines were used to analyze the dose-response relationship between peripheral blood miR-21 and very early relapse after induction chemotherapy in children with ALL.Results:A total of 102 children with ALL achieved CR after induction chemotherapy,among whom 24 cases(23.53％)experienced very early relapse,with a median relapse time of 14 months.The proportions of patients with high-risk stratification at initial diagnosis,extramedullary infiltration,and minimal residual disease(MRD)positivity were significantly higher in the relapse group than those in the non-relapse group;The absolute lymphocyte count(ALC)in peripheral blood was significantly lower,while the expression levels of miR-21 and lactate dehydrogenase(LDH)were significantly higher in the relapse group compared with the non-relapse group(all P＜0.05).Cox regression analysis showed that very early relapse after induction chemotherapy in children with ALL was associated with medium risk and high risk at initial diagnosis,extramedullary infiltration,decreased ALC in peripheral blood,MRD positivity,as well as high expression levels of miR-21 and LDH(all P＜0.05).ROC curve analysis indicated that the area under the curve(AUC)of peripheral blood miR-21 for predicting very early relapse after induction chemotherapy in children with ALL was 0.800,with an optimal cutoff value of 4.830.Restricted cubic spline analysis revealed that there was a non-linear dose-response relationship between peripheral blood miR-21 and the risk of very early relapse after induction chemotherapy in children with ALL.When the expression level of peripheral blood miR-21 exceeded 4.830,the risk of very early relapse increased with the elevation of miR-21 expression.Decision curve analysis demonstrated that combining peripheral blood miR-21 with other risk factors enhanced the predictive performance for the risk of very early relapse after induction chemotherapy in children with ALL.Conclusion:Very early relapse after induction chemotherapy in children with ALL is associated with elevated expression of miR-21 in peripheral blood,and high expression of miR-21 may increase the risk of very early relapse.Detecting miR-21 before induction chemotherapy has predictive significance for very early relapse in children with ALL,and combining it with other risk factors can improve the predictive efficacy.

Objective:Near-infrared(NIR)spectroscopy technology faces the problem of insufficient model generalization due to individual differences in non-invasive blood glucose testing,in order to solve this problem,to improve data utilization,and to build predictive models with stronger generalization ability,this study introduces a transfer learning method to study the NIR spectroscopy non-invasive glucose testing.Methods:Migration learning is a machine learning technique that aims to improve task performance in the target domain by transferring knowledge from the source domain to the target domain.In this study,we used community population data as the source domain and student population data as the target domain to improve the performance of the noninvasive glucose detection model on the target domain.In order to verify the effectiveness of migration learning,this study compares the performance of the model before and after migration learning.Results:the model's performance on the noninvasive glucose detection task is significantly improved by the migration learning strategy,and the MAPE and MAE of the migrated model decreases by 52.5460％and 6.0805％,respectively,and the RMSE and MSE decreases by 10.7215％and 12.1135％.Conclusions:This study demonstrates the promising application of transfer learning in the field of non-invasive blood glucose detection,which is expected to realize portable and continuous blood glucose monitoring in the future by migrating the features that are difficult to access in the source domain but are related to blood glucose values to the target domain,which will greatly improve the quality of life of diabetic patients.Advances in noninvasive glucose testing technology will not only reduce patients' pain,but also provide a more convenient means of glucose monitoring,which will provide strong support for diabetes management.

ObjectiveTo explore the characteristics of traditional Chinese medicine （TCM） syndromes in the patients with concurrent knee osteoarthritis （KOA） and postmenopausal osteoporosis （PMOP） and provide a scientific basis for precise TCM syndrome differentiation， diagnosis， and treatment of such concurrent diseases. MethodsA prospective， multicenter， cross-sectional clinical survey was conducted to analyze the characteristics of TCM syndromes in the patients with concurrent PMOP and KOA. Excel 2021 was used to statistically analyze the general characteristics of the included patients. Continuous variables were reported as x¯±s， and binary variables were reported as percentages. UCINET and Gephi were used to construct a complex "isease-syndrome-symptom" network for in-depth mining. Topological structure indicators， edge connection information between nodes， and weighted adjacency matrices were calculated by UCINET and Python. Gephi was used for complex network visualization. ResultsA total of 157 patients with concurrent PMOP and KOA from 12 TCM hospitals or community health service centers were selected for the collection of TCM syndrome and symptom information. A total of 4 main TCM syndromes were obtained， which were kidney-Yang deficiency （47.13%）， liver-kidney Yin deficiency （36.94%）， spleen-kidney Yang deficiency （8.92%）， and kidney Yin-Yang deficiency （7.01%）. In addition， 10 concurrent syndromes （mainly Qi stagnation and blood stasis， Qi and blood deficiency， spleen Yang deficiency， and cold-dampness） were identified. Based on the results of comprehensive frequency statistics and complex network analysis， as well as TCM theoretical knowledge and relevant guidelines， the general characteristics of concurrent PMOP and KOA and the main TCM syndromes in the dimensions of physical symptoms， pain， tongue and pulse manifestations， and defecation and urination were obtained. ConclusionThe main TCM syndromes in the patients with concurrent PMOP and KOA may be kidney Yang deficiency， liver-kidney Yin deficiency， spleen-kidney Yang deficiency， and kidney Yin-Yang deficiency， among which kidney Yang deficiency and liver-kidney Yin deficiency are the core TCM syndromes.

ObjectiveTo explore the characteristics of traditional Chinese medicine （TCM） syndromes in the patients with concurrent knee osteoarthritis （KOA） and postmenopausal osteoporosis （PMOP） and provide a scientific basis for precise TCM syndrome differentiation， diagnosis， and treatment of such concurrent diseases. MethodsA prospective， multicenter， cross-sectional clinical survey was conducted to analyze the characteristics of TCM syndromes in the patients with concurrent PMOP and KOA. Excel 2021 was used to statistically analyze the general characteristics of the included patients. Continuous variables were reported as x¯±s， and binary variables were reported as percentages. UCINET and Gephi were used to construct a complex "isease-syndrome-symptom" network for in-depth mining. Topological structure indicators， edge connection information between nodes， and weighted adjacency matrices were calculated by UCINET and Python. Gephi was used for complex network visualization. ResultsA total of 157 patients with concurrent PMOP and KOA from 12 TCM hospitals or community health service centers were selected for the collection of TCM syndrome and symptom information. A total of 4 main TCM syndromes were obtained， which were kidney-Yang deficiency （47.13%）， liver-kidney Yin deficiency （36.94%）， spleen-kidney Yang deficiency （8.92%）， and kidney Yin-Yang deficiency （7.01%）. In addition， 10 concurrent syndromes （mainly Qi stagnation and blood stasis， Qi and blood deficiency， spleen Yang deficiency， and cold-dampness） were identified. Based on the results of comprehensive frequency statistics and complex network analysis， as well as TCM theoretical knowledge and relevant guidelines， the general characteristics of concurrent PMOP and KOA and the main TCM syndromes in the dimensions of physical symptoms， pain， tongue and pulse manifestations， and defecation and urination were obtained. ConclusionThe main TCM syndromes in the patients with concurrent PMOP and KOA may be kidney Yang deficiency， liver-kidney Yin deficiency， spleen-kidney Yang deficiency， and kidney Yin-Yang deficiency， among which kidney Yang deficiency and liver-kidney Yin deficiency are the core TCM syndromes.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Cardiovascular diseases that develop from hypercholesterolemia-induced atherosclerosis have emerged as a significant threat to human health.Recently,probiotics exhibiting cholesterol-lowering properties have emerged as a prominent area of research.Numerous studies have demonstrated that Lactobacillus reuteri can effectively reduce endogenous cholesterol synthesis,regulate cholesterol transport,and promote cholesterol degradation by modulating the expression of key genes,such as sterol-regulatory element binding protein 2,3-hydroxy-3-methyl-glutaryl coenzyme A reductase,and cholesterol 7 alpha-hydroxylase,in both the liver and intestinal epithelial cells of the host.This leads to a notable decrease in total cholesterol and low-density lipoprotein cholesterol levels in the host serum.The present paper offers a comprehensive overview of the underlying mechanisms responsible for the cholesterol-lowering effects exerted by L.reuteri,aiming to provide valuable insights into the treatment of hypercholesterolemia and the development of probiotics with cholesterol-lowering properties.

OBJECTIVE: Poxviruses are zoonotic pathogens that infect humans, mammals, vertebrates, and arthropods. However, the specific role of ticks in transmission and evolution of these viruses remains unclear. METHODS: Transcriptomic and metatranscriptomic raw data from 329 sampling pools of seven tick species across five continents were mined to assess the diversity and abundance of poxviruses. Chordopoxviral sequences were assembled and subjected to phylogenetic analysis to trace the origins of the unblasted fragments within these sequences. RESULTS: Fifty-eight poxvirus species, representing two subfamilies and 20 genera, were identified, with 212 poxviral sequences assembled. A substantial proportion of AT-rich fragments were detected in the assembled poxviral genomes. These genomic sequences contained fragments originating from rodents, archaea, and arthropods. CONCLUSION Our findings indicate that ticks play a significant role in the transmission and evolution of poxviruses. These viruses demonstrate the capacity to modulate virulence and adaptability through horizontal gene transfer, gene recombination, and gene mutations, thereby promoting co-existence and co-evolution with their hosts. This study advances understanding of the ecological dynamics of poxvirus transmission and evolution and highlights the potential role of ticks as vectors and vessels in these processes.
Animals ; Poxviridae/physiology* ; Ticks/virology* ; Phylogeny ; Transcriptome ; Evolution, Molecular ; Poxviridae Infections/virology* ; Genome, Viral

The innate immune sensor NLRP3 inflammasome overactivation is involved in the pathogenesis of ulcerative colitis. PGAM5 is a mitochondrial phosphatase involved in NLRP3 inflammasome activation in macrophages. However, the role of PGAM5 in ulcerative colitis and the mechanisms underlying PGAM5 regulating NLRP3 activity remain unknown. Here, we show that PGAM5 deficiency ameliorates dextran sodium sulfate (DSS)-induced colitis in mice via suppressing NLRP3 inflammasome activation. By combining APEX2-based proximity labeling focused on PGAM5 with quantitative proteomics, we identify NEK7 as the new binding partner of PGAM5 to promote NLRP3 inflammasome assembly and activation in a PGAM5 phosphatase activity-independent manner upon inflammasome induction. Interfering with PGAM5-NEK7 interaction by punicalagin inhibits the activation of the NLRP3 inflammasome in macrophages and ameliorates DSS-induced colitis in mice. Altogether, our data demonstrate the PGAM5-NEK7 interaction in macrophages for NLRP3 inflammasome activation and further provide a promising therapeutic strategy for ulcerative colitis by blocking the PGAM5-NEK7 interaction.