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 study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.

Objective To detect the changes of mitophagy level in rats with endplate cartilage degeneration induced by spinal instability,and explore the role of PINK1/Parkin-mediated mitophagy in endplate cartilage and intervertebral disc degeneration.Methods The rat spinal instability model was established by surgically removing the superspinal and interspinal ligaments of L2 to L5,and cleaning the bilateral articular processes of the L2 to L5.Eighteen SD rats were divided into the normal group,the degenerative group,and the carbonyl cyanide 3-chlorophenylhydrazone(CCCP)group,with 6 rats in each group.The rats in the normal group had no special treatment,the rats in the degenerative group constructed a rat spinal instability model,and the rats in the CCCP group were injected with 5 μL of CCCP(10 μmol/L)in the intervertebral disc after the construction of spinal instability model.The changes of histomorphology in the endplate cartilage and intervertebral disc were abserved by HE staining,and the change of extracellular matrix of endplate cartilage was observed by safranin O-fast green staining.RT-PCR detected the mRNA expression of type Ⅱ collagen(COL-2A),aggrecan(ACAN),PINK1 and Parkin in each group.The changes of the protein expression levels of COL-2A,ACAN,PINK1,Parkin and mitochondrial membrane proteins of Tomm20 and Timm23 were detected by Western blot.Results Compared with the normal group,the intervertebral disc nucleus pulposus of rats in the degenerative group was significantly destroyed and the secretion of extracellular matrix of endplate chondrocytes decreased;while the structure of intervertebral discs for rats in the CCCP group was more intact,and the secretion of extracellular matrix of endplate chondrocytes was significantly increased compared with that in the degenerative group.Compared with the normal group,the expression of COL-2A and ACAN in endplate cartilage tissues of rats in the degenerative group were significantly down-regulated(P<0.05),the expression of mitochon-drial autophagy-related genes of PINK1 and Parkin were significantly decreased(P<0.05),and the expression of mitochondrial membrane proteins of Tomm20 and Timm23 were increased(P<0.05).Compared with the degenerative group,the expression of COL-2A,ACAN,PINKI and Parkin in the endplate cartilage tissue of rats in the CCCP group were significantly up-regulated(P<0.05),and the protein levels of Tomm20 and Timm23 were significantly down-regulated(P<0.05).Conclusion Rat spinal instability leads to a decrease level of mitophagy mediated by PINK1/Parkin signaling pathway in endplate cartilage,thereby inducing endplate cartilage and intervertebral disc degeneration,and the activation of mitophagy can significantly reduce endplate cartilage and intervertebral disc degeneration.

Following the principles of evidence-based medicine,in accordance with the structure and drafting rules of standardized documents,based on literature research,according to the characteristics of chronic cough in children and issues that need to form a consensus,the TCM Guidelines for Diagnosis and Treatment of Chronic Cough in Children was formulated based on the Delphi method,expert discussion meetings,and public solicitation of opinions.The guideline includes scope of application,terms and definitions,eti-ology and diagnosis,auxiliary examination,treatment,prevention and care.The aim is to clarify the optimal treatment plan of Chinese medicine in the diagnosis and treatment of this disease,and to provide guidance for improving the clinical diagnosis and treatment of chronic cough in children with Chinese medicine.

Objective To investigate the expression of Nanog and its regulatory relationship with MMP-2/MMP-9 proteins in esophageal squamous cell carcinoma(ESCC).Methods We detected Nanog and MMP-2/MMP-9 protein expressions in 127 ESCC tissues and 82 adjacent normal tissues using immunohistochemistry and explored their correlations with the clinicopathological parameters and prognosis of the patients.GEO database was utilized to analyze the pathways enriched with the stemness-related molecules including Nanog,and TIMER online tool was used to analyze the correlations among TβR1,MMP-2,and MMP-9 in esophageal cancer.Results Nanog and MMP-2/MMP-9 proteins were significantly upregulated in ESCC tissues and positively intercorrelated.Their expression levels were closely correlated with infiltration depth and lymph node metastasis of ESCC but not with age,gender,or tumor differentiation.The patients with high expressions of Nanog and MMP-2/MMP-9 had significantly shorter survival time.Bioinformatics analysis showed enrichment of stemness-associated molecules in the TGF-β signaling pathway,and the expressions of MMP-2/MMP-9 and TβR1 were positively correlated.In cultured ESCC cells,Nanog knockdown significantly decreased the expression of TβR1,p-Smad2/3,MMP-2,and MMP-9 and strongly inhibited cell migration.Conclusion The high expressions of Nanog,MMP-2,and MMP-9,which are positively correlated,are closely related with invasion depth,lymph node metastasis,and prognosis of ESCC.Nanog regulates the expressions of MMP-2/MMP-9 proteins through the TGF-β signaling pathway,and its high expression promotes migration of ESCC cells.

Objective:To construct and validate the best predictive model for 28-day death risk in patients with septic shock based on different supervised machine learning algorithms.Methods:The patients with septic shock meeting the Sepsis-3 criteria were selected from Medical Information Mart for Intensive Care-Ⅳ v2.0 (MIMIC-Ⅳ v2.0). According to the principle of random allocation, 70% of these patients were used as the training set, and 30% as the validation set. Relevant predictive variables were extracted from three aspects: demographic characteristics and basic vital signs, serum indicators within 24 hours of intensive care unit (ICU) admission and complications possibly affecting indicators, functional scoring and advanced life support. The predictive efficacy of models constructed using five mainstream machine learning algorithms including decision tree classification and regression tree (CART), random forest (RF), support vector machine (SVM), linear regression (LR), and super learner [SL; combined CART, RF and extreme gradient boosting (XGBoost)] for 28-day death in patients with septic shock was compared, and the best algorithm model was selected. The optimal predictive variables were determined by intersecting the results from LASSO regression, RF, and XGBoost algorithms, and a predictive model was constructed. The predictive efficacy of the model was validated by drawing receiver operator characteristic curve (ROC curve), the accuracy of the model was assessed using calibration curves, and the practicality of the model was verified through decision curve analysis (DCA).Results:A total of 3?295 patients with septic shock were included, with 2?164 surviving and 1?131 dying within 28 days, resulting in a mortality of 34.32%. Of these, 2?307 were in the training set (with 792 deaths within 28 days, a mortality of 34.33%), and 988 in the validation set (with 339 deaths within 28 days, a mortality of 34.31%). Five machine learning models were established based on the training set data. After including variables at three aspects, the area under the ROC curve (AUC) of RF, SVM, and LR machine learning algorithm models for predicting 28-day death in septic shock patients in the validation set was 0.823 [95% confidence interval (95% CI) was 0.795-0.849], 0.823 (95% CI was 0.796-0.849), and 0.810 (95% CI was 0.782-0.838), respectively, which were higher than that of the CART algorithm model (AUC = 0.750, 95% CI was 0.717-0.782) and SL algorithm model (AUC = 0.756, 95% CI was 0.724-0.789). Thus above three algorithm models were determined to be the best algorithm models. After integrating variables from three aspects, 16 optimal predictive variables were identified through intersection by LASSO regression, RF, and XGBoost algorithms, including the highest pH value, the highest albumin (Alb), the highest body temperature, the lowest lactic acid (Lac), the highest Lac, the highest serum creatinine (SCr), the highest Ca 2+, the lowest hemoglobin (Hb), the lowest white blood cell count (WBC), age, simplified acute physiology score Ⅲ (SAPSⅢ), the highest WBC, acute physiology score Ⅲ (APSⅢ), the lowest Na +, body mass index (BMI), and the shortest activated partial thromboplastin time (APTT) within 24 hours of ICU admission. ROC curve analysis showed that the Logistic regression model constructed with above 16 optimal predictive variables was the best predictive model, with an AUC of 0.806 (95% CI was 0.778-0.835) in the validation set. The calibration curve and DCA curve showed that this model had high accuracy and the highest net benefit could reach 0.3, which was significantly outperforming traditional models based on single functional score [APSⅢ score, SAPSⅢ score, and sequential organ failure assessment (SOFA) score] with AUC (95% CI) of 0.746 (0.715-0.778), 0.765 (0.734-0.796), and 0.625 (0.589-0.661), respectively. Conclusions:The Logistic regression model, constructed using 16 optimal predictive variables including pH value, Alb, body temperature, Lac, SCr, Ca 2+, Hb, WBC, SAPSⅢ score, APSⅢ score, Na +, BMI, and APTT, is identified as the best predictive model for the 28-day death risk in patients with septic shock. Its performance is stable, with high discriminative ability and accuracy.

Objective:To analyze the safety and efficacy of ultrasound-guided percutaneous thermal ablation treatment for multiple T1N0M0 papillary thyroid carcinoma(PTC)with over 5 years follow-up.Methods:From January 2014 to January 2019,a retrospective analysis was conducted on patients with multiple T1N0M0 PTC who underwent ultrasound-guided thermal ablation.Patients with bilateral or unilateral lobes with isthmus PTC were enrolled in this study and were followed up at 1,3,6,12,24,36,48,and 60 months after ablation.The clinical data,ultrasound characteristics and ablation parameters of recurrent and non-recurrent patients were compared,and the efficacy and influencing factors of thermal ablation for multiple T1N0M0 PTC were analyzed.Results:After over 5 years follow-up,a total of 11 patients(16.18％)relapsed,57 patients(83.82％)did not re-lapse.No lymph node and distant metastasis were found.No significant correlation was detected between the recurrence and clinical features,ultrasound findings and ablation parameters(P＞0.05).Among the patients with recurrence,1 patient underwent observation,2 patients underwent total thyroidectomy,and the other 8 patients successfully underwent secondary ablation,all of which had no obvious adverse reactions.Conclusion:The ablation of multiple PTC in T1N0M0 stage is safe and effective,with a recurrence rate of 16.18％over 5 years follow-up,and ablation has no effect on second treatment for recurrent patients.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.