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.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective To compare the clinical effects of total hip arthroplasty(THA)with and without femoral osteotomy in Crowe Ⅳ developmental hip dislocation(DDH).Methods The data on 46 patients who underwent THA for unilateral Crowe ⅣDDH between 2012 and 2017 were analyzed retrospectively.They were divided into two groups according to the different surgical methods.There were 24 patients in the osteotomy group,3 males and 21 females,with an average age of(47.3±9.0)years old ranged from 34 to 57 years old;and 22 patients in the non-osteotomy group,2 males and 20 females,with an average age of(51.6±8.3)years old ranged from 40 to 61 years old.The operative time,bleed loss,postoperative drainage volume,postoperative com-plications,ROM of hip,Harris hip score,limb length discrepancy(LLD),and radiological data were recorded.The femoral dislo-cation height and the implantation depth of sleeve were measured.Results All patients were followed up.The mean follow-up time was(3.8±1.2)years ranged from 2 to 6 years in the osteotomy group and(3.2±0.9)years ranged from 1 to 5 years in the non-os-teotomy group.The operative time(136.8±18.9)min,bleed loss(709.8±89.4)ml,postoperative drainage volume(308.8±98.2)ml of osteotomy group were all significantly greater than those of non-osteotomy group(100.7±15.8)min,(516.5±103.3)ml,(245.3±79.3)ml(P＜0.05).The Harris score at the latest follow up was significantly increased compared with preoperative score in two groups(P＜0.05),but there was no significant difference between two groups(P＞0.05).The LLD at last follow up was sig-nificantly increased compared with preoperative LLD in two groups,the LLD in non-osteotomy group(0.7±0.2)cm showed signif-cant smaller than the two osteotomy group(1.2±0.4)cm.Between osteotomy and non-osteotomy groups,the preoperative range of motion of hip joint[(89.5±19.7)°vs(102.5±16.8)°],the preoperative height of dislocation of femoral head[(4.56±0.61)cm vs(3.10±0.73)cm],the proximal implant depth of S-ROM[(0.93±0.36)cm vs(1.67±0.28)cm]was significantly different(P＜0.05).Eleven patients in the osteotomy group still had claudication,and 4 patients in the non-osteotomy group had mild claudica-tion(P＜0.05).In non-osteotomy group,3 patients developed nerve injury(1 patient of sciatic nerve,2 patients of femoral nerve)and 1 case developed periprosthetic fracture.In osteotomy group,2 case of dislocation and 2 cases of periprosthetic fractures.Conclusion Whether osteotomy or not can achieve satisfactory results for treating Crowe type Ⅳ DDH and significantly improve LLD.However,osteotomy is more complex and time-consuming,limb length difference is greater,and the incidence of claudica-tion is higher.Furthermore,patients with smaller preoperative hip mobility,higher femoral dislocation,limb lengthening≥4 cm and severely narrow femoral proximal canals are prone to be peformed with subtrochanteric osteotomy.

The aim of this study was to investigate the impact of overexpressing 70-kD heat shock pro-teins(Hsp70)on glycolysis in C2C12 cells during myogenesis and adipogenesis.Using C2C12 cells as the research material,adenovirus was used to overexpress the Hsp70 gene,and changes in the expression of glycolytic genes were detected using fluorescence quantitative PCR and Western blotting techniques.The study indicated that during C2C12 cell myogenic differentiation,the expression trend of the Hsp70 gene was consistent with that of Gsk3β,Pkm,Prkag3,Pfkm,and Hk-2 genes,suggesting a relationship between Hsp70 and the glycolytic pathway during myogenic differentiation.Overexpression of Hsp70 in the later stages of myogenic differentiation significantly upregulated the expression of Gsk3β,Pkm,Prk-ag3,and Pfkm genes(P＜0.05),with no significant impact on Hk-2 gene expression(P＞0.05).Dur-ing C2C12 cell adipogenic induction,the expression trend of the Hsp70 gene was similar to that of Gsk3β,Pkm,Prkag3,Pfkm,and Hk-2 genes,indicating a relationship between Hsp70 and the glycolytic path-way during adipogenic induction.Following Hsp70 overexpression,in the later stages of adipogenic in-duction,the number of lipid droplets was significantly higher compared to the control group,with a sig-nificant upregulation of Gsk3β,Pkm,Prkag3,and Pfkm gene expression(P＜0.05),while Hk-2 gene expression was not significantly affected(P＞0.05).In conclusion,Hsp70 in C2C12 cells in myogenic and adipogenic states promoted the breakdown of glycogen into 6-phospho-glucose,thereby enhancing the glycolytic pathway,providing insights into the functional role of the Hsp70 gene in glycolysis in C2C12 cells.

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.

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.

In recent years, nucleic acid therapy, as a revolutionary therapeutic tool, has shown great potential in the treatment of genetic diseases, infectious diseases and cancer. Lipid nanoparticles (LNPs) are currently the most advanced mRNA delivery carriers, and their emergence is an important reason for the rapid approval and use of COVID-19 mRNA vaccines and the development of mRNA therapy. Currently, mRNA therapeutics using LNP as a carrier have been widely used in protein replacement therapy, vaccines and gene editing. Conventional LNP is composed of four components: ionizable lipids, phospholipids, cholesterol, and polyethylene glycol (PEG) lipids, which can effectively load mRNA to improve the stability of mRNA and promote the delivery of mRNA to the cytoplasm. However, in the face of the complexity and diversity of clinical diseases, the structure, properties and functions of existing LNPs are too homogeneous, and the lack of targeted delivery capability may result in the risk of off-targeting. LNPs are flexibly designed and structurally stable vectors, and the adjustment of the types or proportions of their components can give them additional functions without affecting the ability of LNPs to deliver mRNAs. For example, by replacing and optimizing the basic components of LNP, introducing a fifth component, and modifying its surface, LNP can be made to have more precise targeting ability to reduce the side effects caused by treatment, or be given additional functions to synergistically enhance the efficacy of mRNA therapy to respond to the clinical demand for nucleic acid therapy. It is also possible to further improve the efficiency of LNP delivery of mRNA through machine learning-assisted LNP iteration. This review can provide a reference method for the rational design of engineered lipid nanoparticles delivering mRNA to treat diseases.

Objective To explore the postmortem diffusion rule of Aconitum alkaloids and their metabo-lites in poisoned rabbits,and to provide a reference for identifying the antemortem poisoning or post-mortem poisoning of Aconitum alkaloids.Methods Twenty-four rabbits were sacrificed by tracheal clamps.After 1 hour,the rabbits were administered with aconitine LD50 in decocting aconite root powder by intragastric administration.Then,they were placed supine and stored at 25℃.The biological samples from 3 randomly selected rabbits were collected including heart blood,peripheral blood,urine,heart,liver,spleen,lung and kidney tissues at 0 h,4 h,8 h,12 h,24 h,48 h,72 h and 96 h after intragastric administration,respectively.Aconitum alkaloids and their metabolites in the biological samples were ana-lyzed by high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS).Results At 4 h after intragastric administration,Aconitum alkaloids and their metabolites could be detected in heart blood,peripheral blood and major organs,and the contents of them changed dynamically with the preservation time.The contents of Aconitum alkaloids and their metabolites were higher in the spleen,liver and lung,especially in the spleen which was closer to the stomach.The average mass fraction of benzoylmesaconine metabolized in rabbit spleen was the highest at 48 h after intragastric administration.In contrast,the contents of Aconitum alkaloids and their metabolites in kidney were all lower.Aconi-tum alkaloids and their metabolites were not detected in urine.Conclusion Aconitum alkaloids and their metabolites have postmortem diffusion in poisoned rabbits,diffusing from high-content organs(stomach)to other major organs and tissues as well as the heart blood.The main mechanism is the dispersion along the concentration gradient,while urine is not affected by postmortem diffusion,which can be used as the basis for the identification of antemortem and postmortem Aconitum alkaloids poisoning.