Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Objective:To investigate the correlation between the expression of GLI1 and im-mune invasion and clinical prognosis in gastric cancer.To study the effect of GLI1 expression on drug resistance in gastric cancer.Methods:The expression difference of GLI1 in gastric cancer and normal tissues was analyzed by using TCGA database,and the effect of clinical features and GLI1 gene ex-pression level on prognosis of patients with gastric cancer was analyzed.The correlation between GLI1 gene expression and tumor immune cell infiltration in gastric cancer tissues was analyzed to explore its influence on drug resistance of chemotherapy drugs and targeted drugs.Clinical samples were collect-ed to analyze the difference of GLI1 expression in gastric cancer and paracancer tissues.Results:The expression of GLI1 in gastric cancer tissues was 1.7 times that in normal tissues,and the overall sur-vival and disease-free survival of patients with high expression are shorter than those with low ex-pression(P＜0.05).The interstitial score,immune score and abundance of immunoinfiltrating cells were higher in the high expression of GLI1 in gastric cancer tissues.High expression of GLI1 reduces drug sensitivity and is positively correlated with the expression of immune checkpoint markers PDCD1(P＜0.05).GLI1 expression was significantly increased in patients with subdifferentiated gastric cancer.Conclusions:GLI1 expression is associated with the prognosis and immune infiltration of patients with gastric cancer,and it may lead to poor prognosis of patients by regulating chemotherapy resis-tance,which may be a potential therapeutic target and molecular marker for gastric cancer.

Objective To analyze the diagnostic quality of imported malaria in Hubei Province from 2019 to 2022, and to further improve the diagnostic level and consolidate the achievements in eliminating malaria. Methods The samples of reported malaria cases in Hubei were collected by the provincial reference laboratory (PRL) from 2019 to 2022. The microscopy and fluorescent PCR were performed to confirm the infection of plasmodium species of each case．The positive coincidence rate and species coincidence rate were analyzed and compared． Results A total of 257 imported malaria cases were reported in Hubei Province from 2019 to 2022. Among 229 malaria cases were confirmed, the overall coincidence for malaria diagnosis was 91.24% (229/251), and the overall coincidence rate for parasite species identification was 86.03% (197/229). The difference in species coincidence rate among different years was statistically significant (χ²=10.458, P<0.05). The coincidence rates of malaria diagnosis and parasite species identification in different cities (prefectures) of Hubei Province were 71.43% to 100.00% and 50.00% to 100.00%, respectively, with significant differences among different regions (χ²=29.283, P<0.05). The coincidence rates of malaria diagnosis and parasite species identification were 72.73% to 100.00% and 0.00% to 100.00% in different diagnostic institutions, and the coincidence rate of species identification in hospitals (87.61%) was higher than that in Centers for Disease Control institutions (54.55%) (χ²=81.275, P<0.05). The coincidence rates of Plasmodium falciparum, P. vivax, P. malariae, and P. ovale identification were 91.50%, 88.57%, 80.00%, and 58.06%, respectively (χ²=19.777, P<0.05). Conclusion The quality of the qualitative diagnosis of malaria cases reported online from 2019 to 2022 is generally high. However, the ability of Plasmodium typing needs to be improved. In the future, technical training and quality control should be strengthened to improve the malaria surveillance capability during the post-elimination stage.

Aim To investigate the effect of histamine H, receptor (HjR) on the immune responses in astrocytes induced by lipopolysaccharide (LPS) and the regulatory mechanism of its signaling pathway. Methods LPS was used to establish an in vitro astrocyte inflammation model. Rat primary astrocytes were divided into the control group, LPS group, LPS + Hj R agonist group (2-pyridylethlamine, Pyri), and HjR agonist group. Astrocytes were treated with Pyri 100 p,mol • L~ for 1 h, then stimulated with LPS at 100 p,g • L~ for 24 h. Cell viability was measured using the CCK-8 assay. The expression of GFAP and HjR was detected by immunofluorescence. Glial morphological changes were observed under a microscope. The levels of proinflammatory mediators (TNF-a and IL-6) were detected by ELISA. The protein expressions of p-Akt, Akt, p-NF-KB p65, and NF-KB p65 were detected by Western blot. Results Compared with the control group, more activated astrocytes with fewer cell processes and branches were observed in the LPS group. Besides, LPS enhanced the GFAP expression level, reduced the H,R expression level and stimulated the production of TNF-a and IL-6 from astrocytes. Pre treatment with Pyri for 1 h ameliorated the glial morphological changes stimulated by LPS, inhibited LPS-induced upregulation of GFAP level and the inflammatory factors secretion. In addition, LPS stimulated astrocytes showed a higher phosphorylation of Akt and NF-KB p65, which was also ameliorated by Pyri. Conclusions H, R agonist can inhibit LPS-induced astrocyte activation and inflammatory factor secretion, and the Akt/NF-KB signaling pathway may be an important pathway for the involvement of H,R in immune regulation.

To explore the mechanism of spleen- were obtained for the treatment of acute-on-chronic livstrengthening and moisture-nourishing liver prescription er failure, and 244 intersecting target genes and 7 core (JPLSYGF) in the treatment of acute-on-chronic liver target genes were screened. Molecular docking showed failure using network pharmacology and the molecular that the core target genes AKT1, SRC, VEGFA, docking. Methods Relying on TCMSP and Gene- STAT3 , EGFR, MAPK3 , HRAS had good affinity with Cards and other databases, the relevant targets of JPL- quercetin, the main active component in the JPLSYGF in the treatment of acute-on-chronic liver failure SYGF, and had strong binding activity. In addition, in were obtained. String and Cytoscape were used to con- vivo tests verified that the JPLSYGF could reduce the struct PPI networks of targets, core targets were expression of HRAS, EGFR, STAT3 , SRC, and VEGscreened out, and DAVID was used for GO function FA, to delay the progression of acute-on-chronic liver annotation and KEGG pathway enrichment analysis. failure. Conclusions JPLSYGF may act on core tar- The main active ingredients of the traditional Chinese gets such as HRAS, EGFR, STAT3, SRC, VEGFA medicine compound formula for JPLSYGF were select- and so on, to achieve the effect of treating acute-oned with a bioavailability OB value of =Э 30% and a chronic liver failure. drug-like DL^O. 18 as the screening conditions, and.

Primary hypertrophic osteoarthropathy(PHO)is a rare disease also known as pachydermo-periostosis.We reported a painless case whose diagnosis was confirmed by genetic test.A 24-year-old male presented a series of symptoms that first began at 14.He suffered from progressive clubbed-fingers accompa-nied by swelling of the wrist and ankle joints.Facial skin concentric thickening and alar nose broadening ap-peared simultaneously and increased progressively.He was also prone to acne and hyperhidrosis.X-rays showed thickening of the metacarpal and phalangeal bones,as well as symmetrical periosteal ossification of both the tibia and fibula.Clinical diagnosis of PHO is difficult because of the variable features.With acromeg-aly excluded,the diagnosis was confirmed by a genetic test.Whole exome sequencing revealed a heterozygous SLCO2A1 c.611C＞T(p.Ser204Lue)and SLCO2A1 c.1602C＞A(p.Asn534Lys)mutation from each par-ent.It suggests that primary hypertrophic osteoarthropathy should be considered for young limb hypertrophic patients especially when periosteal thickening signs were showed in X-ray.A confirmatory diagnosis can be made through the genetic test.

Objective To estimate adolescents and children age using stepwise regression and machine learning methods based on the pulp and tooth volumes of the left maxillary central incisor and cuspid on cone beam computed tomography(CBCT)images,and to compare and analyze the estimation re-sults.Methods A total of 498 Shanghai Han adolescents and children CBCT images of the oral and maxillofacial regions were collected.The pulp and tooth volumes of the left maxillary central incisor and cuspid were measured and calculated.Three machine learning algorithms(K-nearest neighbor,ridge regression,and decision tree)and stepwise regression were used to establish four age estimation models.The coefficient of determination,mean error,root mean square error,mean square error and mean ab-solute error were computed and compared.A correlation heatmap was drawn to visualize and the monotonic relationship between parameters was visually analyzed.Results The K-nearest neighbor model(R2=0.779)and the ridge regression model(R2=0.729)outperformed stepwise regression(R2=0.617),while the decision tree model(R2=0.494)showed poor fitting.The correlation heatmap demon-strated a monotonically negative correlation between age and the parameters including pulp volume,the ratio of pulp volume to hard tissue volume,and the ratio of pulp volume to tooth volume.Con-clusion Pulp volume and pulp volume proportion are closely related to age.The application of CBCT-based machine learning methods can provide more accurate age estimation results,which lays a founda-tion for further CBCT-based deep learning dental age estimation research.

Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.