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.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

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 investigate the expression and prognostic value of spindle and kinetochore-associated complex subunit 2(SKA2)in cervical cancer tissues,as well as its impact on the proliferation,migration and invasion of cervical cancer cells.Methods The expression of SKA2 in cervical cancer tissues was analyzed by bioinformatics database and immunohistochemical SP method,and the relationship between SKA2 expression level and clinicopathological features of cervical cancer patients and its prognostic value was analyzed.The mRNA expression of SKA2 in human normal cervical cells(HcerEpic)and cervical cancer cells(HeLa,SiHa,CaSki,C-33A)was detected by RT-qPCR.Cervical cancer cells SiHa with higher SKA2 expression level was selected for further study.SiHa cell model with down-regulated SKA2 expression was constructed,and its knockdown effect was verified.Cell proliferation capacity was detected by CCK-8 method,cell migration capacity was detected by cell scratch wound healing assay,and cell migration and invasion capacity was detected by Transwell assay.Results Compared with normal cervical tissues and cells,the expression levels of SKA2 mRNA and protein were higher in cervical cancer tissues and cells,and the differences were statistically significant(P<0.05).High SKA2 expression was associated with FIGO staging in patients with cervical cancer.Furthermore,SKA2 knockdown could inhibit the proliferation,migration and invasion of SiHa cells in cervical cancer(P<0.05).Conclusion SKA2 is up-regulated in cervical cancer tissues and cells,and can promote the proliferation,migration and invasion of cervical cancer cells.The expression level of SKA2 is associated with the progression of cervical cancer,and the prognosis of cervical cancer patients with high SKA2 expression is worse.

Objective:To analyze the distribution characteristics of prognostic factors affecting recurrence in peripheral T-cell lymphoma(PTCL)patients with different levels of histone deacetylase(HDAC)based on latent class analysis.Methods:112 PTCL patients who were treated in our hospital from September 2012 to September 2019 were selected and divided into recurrence group and non-recurrence group.The clinical data of the two groups of patients were compared.Multivariate logistic regression was used to analyze the risk factors for recurrence.Latent class analysis was used to compare the distribution characteristics of prognostic factors affecting recurrence between the high-risk group and the low-risk group.Results:There were 87 patients(77.68％)in recurrence group and 25 patients(22.32％)in non-recurrence group.The result of multivariate logistic regression showed that ECOG score ≥2,Ann Arbor stage Ⅲ-Ⅳ,IPI score＞2,bone marrow involvement,elevated serum β2-microglobulin(β2-MG),short-term efficacy not reaching complete remission(CR)or partial remission(PR),and the high expression of HDAC were all independent risk factors for recurrence in patients with PTCL(P＜0.05).The recurrence rate of patients with high HDAC levels was significantly higher than that of patiens with low HDAC levels(P＜0.05).The results of cluster analysis showed that the risk of recurrence was obviously clustered,and the patients could be divided into high recurrence risk group(HDAC＞5 points)and low recurrence risk group(HDAC≤5 points).The results of latent class analysis showed that patients with multiple risk factors account for a higher proportion in the high recurrence risk group,compared with the low recurrence risk group(P＜0.05).Conclusion:There are differences in recurrence rates among PTCL patients with different HDAC levels and in distribution characteristics of risk factors between high recurrence risk and low recurrence risk groups.

AIM To explore the clinical effects of Polygonum cuspidatum Sieb.et Zucc.on patients with type 2 diabetes mellitus of Dampness-Heat Pattern.METHODS One hundred and forty patients were randomly assigned into control group(70 cases)for 8-week intervention of conventional treatment,and observation group(70 cases)for 8-week intervention of both P.cuspidatum granules and conventional treatment.The changes in body weight,BMI,blood glucose indices(FBG,2 h PG,HbA1C,GA),blood lipid indices(TC,TG,HDL-C,LDL-C,ApoA-I,ApoB,ApoA,ApoE,sdLDL-C),liver function indices(ALT,AST),fatty liver progression,TyG,HSI,TCM syndrome score and effects were detected.RESULTS The observation group demonstrated higher total effective rates of TCM syndromes than the control group(P＜0.01),along with slighter fatty liver progression(P＜0.01).After the treatment,the observation group displayed decreased body weight,BMI,FBG,GA,TG,ApoE,TyG,HSI,ALT and TCM syndrome score(P＜0.05,P＜0.01),and 2 h PG,TyG,HSI,ALT,TCM syndrome score were lower than those in the control group(P＜0.05,P＜0.01).CONCLUSION For the patients with type 2 diabetes mellitus of Dampness-Heat Pattern,P.cuspidatum can improve glucose and lipid metabolism disorders,which is worthy of clinical popularization and application.

The main components and working principle of the negative pressure isolation treatment equipment were described,and the classification and application scopes of the negative pressure isolation treatment equipment from foreign countries and China were reviewed.The structure,key technical parameters and characteristics of different types of negative pressure isolation treatment equipment were analyzed under different conditions.The problems of the negative pressure isolation treatment equipment were analyzed,and it's pointed out it would be enhanced in component simplification,comfort,intelligence and multifunctionality.[Chinese Medical Equipment Journal,2024,45(2):97-104]

Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]