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.

Background::Cardiovascular disease (CVD) has emerged as the leading cause of death from prostate cancer (PCa) in recent decades, bringing a great disease burden worldwide. Men with preexisting CVD have an increased risk for major adverse cardiovascular events when treated with androgen deprivation therapy (ADT). The present study aimed to explore the prevalence and risk evaluation of CVD among people with newly diagnosed PCa in China.Methods::Clinical data of newly diagnosed PCa patients were retrospectively collected from 34 centers in China from 2010 to 2022 through convenience sampling. CVD was defined as myocardial infarction, arrhythmia, heart failure, stroke, ischemic heart disease, and others. CVD risk was estimated by calculating Framingham risk scores (FRS). Patients were accordingly divided into low-, medium-, and high-risk groups. χ2 or Fisher’s exact test was used for comparison of categorical variables. Results::A total of 4253 patients were enrolled in the present study. A total of 27.0% (1147/4253) of patients had comorbid PCa and CVD, and 7.2% (307/4253) had two or more CVDs. The enrolled population was distributed in six regions of China, and approximately 71.0% (3019/4253) of patients lived in urban areas. With imaging and pathological evaluation, most PCa patients were diagnosed at an advanced stage, with 20.5% (871/4253) locally progressing and 20.5% (871/4253) showing metastasis. Most of them initiated prostatectomy (46.6%, 1983/4253) or regimens involving ADT therapy (45.7%, 1944/4253) for prostate cancer. In the present PCa cohort, 43.1% (1832/4253) of patients had hypertension, and half of them had poorly controlled blood pressure. With FRS stratification, as expected, a higher risk of CVD was related to aging and metabolic disturbance. However, we also found that patients with treatment involving ADT presented an originally higher risk of CVD than those without ADT. This was in accordance with clinical practice, i.e., aged patients or patients at advanced oncological stages were inclined to accept systematic integrative therapy instead of surgery. Among patients who underwent medical castration, only 4.0% (45/1118) received gonadotropin releasing hormone antagonists, in stark contrast to the grim situation of CVD prevalence and risk.Conclusions::PCa patients in China are diagnosed at an advanced stage. A heavy CVD burden was present at the initiation of treatment. Patients who accepted ADT-related therapy showed an original higher risk of CVD, but the awareness of cardiovascular protection was far from sufficient.

This study was aimed at investigating the pathogenic and molecular characteristics of Klebsiella pneumoniae(KP)in fecal samples of diarrhea cases in a district of Beijing.Fecal samples from diarrhea cases in an outpatient department in a district of Beijing from 2018 to 2021 were collected,and used for isolation and culture of KP.The KP strains isolated strains were subjected to drug resistance phenotype testing and whole-genome sequencing.Multilocus sequence typing and whole-genome phyletic evolution analysis were performed on the sequencing results.The cases'epidemiological and clinical characteristics were analyzed.From 2018 to 2021,1 103 fecal samples were collected and detected.The total detection rate of KP was 10.43％(115/1 103),and the infection rate of KP mixed with other diarrhea-causing pathogens was 42.61％(49/115).The positivity rate was slightly high(12.47％,61/489)a-mong females and was highest in young adults 16-45 years of age.Small peaks were observed in January,April to May,and August to September.The gastrointestinal symptoms in cases were mainly nausea and watery stool,and the suspicious food was unknown.Ampicillin,tetracycline,and sulfafurazole were the top three antibiotics to which these 115 KP strains showed resistance,and 29 strains were resistant to multiple antibiotics.The strains were divided into 72 sequence types,among which ST23 was dominant.According to the phylogenetic tree,the strains were divided into four main branches,among which 14 ST23 strains had a very close genetic relationship with the highly virulent NTUH-K2044 reference strain.KP infection persisted in fecal samples from diarrhea cases in the district of Beijing.Women and young adults were particularly susceptible.The drug resistance of KP strains in this region was very serious,and the ST types were diverse.Moreover,the ST23 pathogenic strains were closely related to high virulence strains.

Objective:To explore the risk factors affecting the survival and efficacy of patients with acute myeloid leukemia with myelodysplasia-related changes(AML-MRC)transformed from myelodysplastic syndrome(MDS).Methods:The clinical data of 60 patients with AML-MRC transformed from MDS who hospitalized in The Third Affiliated Hospital of Soochow University from January 2010 to December 2021 were retrospectively analyzed.The demographic data and laboratory parameters,cytogenetic karyotypes,target genes of AML detected by next generation sequence,risk stratification,treatment regimen,therapeutic efficacy and survival outcome were documented.Rank sum test and Chi-square test or Fisher exact test were used to compare the survival and efficacy.The effects of clinical parameters,risk stratification and treatment regimens on the survival and efficacy of the AML-MRC patients were analyzed by univariate and multivariate analysis.Results:The median overall survival(OS)of the AML-MRC patients was 4.5 months,the 1-year OS rate was 28.3％,and the complete remission(CR)rate after treatment was 33.3％.The univariate analysis showed that age≥60 years,leukocytosis,severe thrombocytopenia,poor-risk group and only accepted hypomethylating agents(HMAs)or supportive therapy were the risk factors affecting OS.COX multivariate analysis showed that thrombocytopenia(HR=4.46),HMAs therapy(compared to transplantation,HR=10.47),supportive therapy(compared to transplantation,HR=25.80)and poor-risk group(compared to medium-risk group,HR=13.86)were independent hazard factors for median OS of patients with AML-MRC.The univariate analysis showed that the risk factors affecting 1-year OS in patients with AML-MRC were age ≥ 60 years,thrombocytopenia,time of transformation from MDS to AML(TTA)≥3 months,fibrinogen-albumin ratio index(FARI)≥ 0.07,CONUT score≥5,poor-risk group and supportive therapy.Binary logistic regression analysis showed that the independent risk factors for 1-year OS in AML-MRC patients were age ≥ 60 years(HR=11.23),thrombocytopenia(HR=8.71),FARI ≥ 0.07(HR=5.19)and poor-risk group(HR=14.00).The risk factors affecting CR of AML-MRC patients in univariate analysis were age ≥ 60 years,thrombocytopenia,FARI ≥ 0.1,CONUT score ≥ 5,poor-risk group and supportive therapy,while binary logistic regression analysis showed that age ≥ 60 years(HR=7.35),CONUT score ≥ 5(HR=9.60),thrombocytopenia(HR=12.05)and poor-risk group(HR=32.5)were independent risk factors affecting CR of the patients.Conclusion:The OS of AML-MRC patients is poor,old age(≥ 60 years old),supportive therapy,HMA therapy,poor-risk,thrombocytopenia,FARI ≥ 0.07 and CONUT score ≥ 5 may be associated with poor prognosis.

Objective:To investigate the prognostic significance of DTA(DNMT3A,TET2,ASXL1)gene mutations in patients with non-M3 acute myeloid leukemia(AML).Methods:The clinical data of 180 newly diagnosed AML patients hospitalized in the First People's Hospital of Changzhou from January 2018 to April 2022 were retrospectively analyzed.Next-generation sequencing technology was used to detect 150 gene mutations in the patients,and log-rank tests and Cox regression models were used to analyze the prognostic factors.Results:DTA gene mutations were detected in 83(46.1％)of 180 AML patients.Compared to patients without DTA mutations,patients with DTA mutations were significantly older(P＜0.001).The median overall survival(OS)time and disease-free survival(DFS)time in the DTA mutation group were significantly shorter than those in the group without DTA mutation(both P＜0.05).Multivariate analysis showed that age ≥ 60 years(P＜0.001),with DTA mutation(P=0.018),and intermediate-risk(relative to favorable-risk)(P=0.005)were independent risk factors for OS in AML patients.Conclusion:AML patients with DTA mutations are relatively older,with shorter median OS time and DFS time,and poor prognosis.

Objective To evaluate the quality of hypoglycemia fear assessment tools for adults,so as to provide references for the selection of high-quality research tools.Methods PubMed,Embase,Web of Science,CNKI,VIP,Wanfang,CBM were retrieved to collect the literature on the measurement properties of hypoglycemic fear.There were 2 researchers who screened the literature and extracted data,independently.Based on the consensus-based standards for the selection of health measurement instruments(COSMIN)guideline,the methodological and measure-ment properties quality of the included assessment tools were evaluated by the COSMIN risk of bias checklist and quality criteria.Results A total of 17 studies involving 6 hypoglycemia fear assessment tools for adults were included,none of which reported cross-cultural validity,measurement error,and responsiveness.All assessment tools were recommended by grade B.Conclusion The 15-item Fear of Hypoglycemia Scale(FH-15)has the most comprehensive measurement properties in its evaluation,and can be provisionally recommended for use,but it needs further testing.