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.

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 fidelity of chronic obstructive pulmonary disease(COPD)models established using two methods:exposure to cigarette smoke(CS)and exposure to motor vehicle exhaust(MVE)in rats.Methods Twenty-four male SD rats were randomly divided into control,CS-exposed(CS),and MVE-exposed(MVE)groups,with 8 rats per group.Rats in CS and MVE groups were exposed to CS or MVE,respectively,to induce COPD models.After COPD model established,lung function of each group was assessed.Bronchoalveolar lavage fluid(BALF)was collected to measure inflammatory cell counts,levels of inflammatory cytokines interleukin-6(IL-6)and tumor necrosis factor(TNF)-α,and expression levels of mucin 5AC(MUC5AC).Lung tissue sections were stained with hematoxylin and eosin(HE)to observe pulmonary tissue and airway pathological changes.Periodic acid-Schiff(PAS)staining was used to detect goblet cell hyperplasia in airways.Results Compared with control group,rats in CS and MVE groups showed significantly increased inspiratory resistance(RI),total lung capacity(TLC),and lung static compliance(Cchord)(P<0.05),while expiratory flow parameters FEV50/FVC were significantly decreased(P<0.05).Compared with MVE group,rats in CS group had significantly higher RI,TLC,and Cchord(P<0.05),and lower FEV50/FVC(P<0.05).HE staining of lung tissues showed that mean linear intercept(MLI)was significantly higher in both CS and MVE groups compared with control group(P<0.05),with CS group having higher MLI than MVE group(P<0.05).BALF analysis revealed that white blood cells,neutrophils,macrophages,lymphocytes,IL-6,and TNF-α levels were significantly higher in both CS and MVE groups compared with control group(P<0.05),and inflammatory cell counts,IL-6,and TNF-α levels were higher in CS group compared with MVE group(P<0.05).PAS staining of lung tissues indicated that goblet cells in large airways were significantly increased in both CS and MVE groups compared with control group(P<0.05),with CS group showing higher goblet cell counts than MVE group(P<0.05).Expression levels of MUC5AC in BALF were significantly higher in both CS and MVE groups compared with control group(P<0.05),with CS group having significantly higher MUC5AC levels than MVE group(P<0.05).Conclusions Exposure to CS or MVE can establish a rat model of COPD,with CS exposure better mimicking characteristics of acute exacerbation of COPD compared to MVE exposure.

OBJECTIVE: To study the in vitro and in vivo antitumor effects of the polysaccharide of Alocasia cucullata (PAC) and the underlying mechanism. METHODS: B16F10 and 4T1 cells were cultured with PAC of 40 µg/mL, and PAC was withdrawn after 40 days of administration. The cell viability was detected by cell counting kit-8. The expression of Bcl-2 and Caspase-3 proteins were detected by Western blot and the expressions of ERK1/2 mRNA were detected by quantitative real-time polymerase chain reaction (qRT-PCR). A mouse melanoma model was established to study the effect of PAC during long-time administration. Mice were divided into 3 treatment groups: control group treated with saline water, positive control group (LNT group) treated with lentinan at 100 mg/(kg·d), and PAC group treated with PAC at 120 mg/(kg·d). The pathological changes of tumor tissues were observed by hematoxylin-eosin staining. The apoptosis of tumor tissues was detected by TUNEL staining. Bcl-2 and Caspase-3 protein expressions were detected by immunohistochemistry, and the expressions of ERK1/2, JNK1 and p38 mRNA were detected by qRT-PCR. RESULTS: In vitro, no strong inhibitory effects of PAC were found in various tumor cells after 48 or 72 h of administration. Interestingly however, after 40 days of cultivation under PAC, an inhibitory effect on B16F10 cells was found. Correspondingly, the long-time administration of PAC led to downregulation of Bcl-2 protein (P<0.05), up-regulation of Caspase-3 protein (P<0.05) and ERK1 mRNA (P<0.05) in B16F10 cells. The above results were verified by in vivo experiments. In addition, viability of B16F10 cells under long-time administration culture in vitro decreased after drug withdrawal, and similar results were also observed in 4T1 cells. CONCLUSIONS Long-time administration of PAC can significantly inhibit viability and promote apoptosis of tumor cells, and had obvious antitumor effect in tumor-bearing mice.
Mice ; Animals ; Alocasia/metabolism* ; MAP Kinase Signaling System ; Caspase 3/metabolism* ; Apoptosis ; RNA, Messenger/metabolism*

AIM:To explore the expression of RhoC in oral squamous cell carcinoma(OSCC)and its effects on the malignant biological behavior of OSCC cells.METHODS:The UALCAN and K-M plotter databases,alongside tis-sue sample analyses,facilitated understanding RhoC expression in cancer and its links to clinicopathological traits.Two small interfering RNAs(RhoC-siRNA)were constructed according to the RhoC gene sequence.The mRNA and protein ex-pression levels of RhoC in OSCC cells were determined.The protein levels of FAK,p-FAK,MAPK,p-MAPK,matrix me-talloproteinase-2(MMP-2)and MMP-9 were also examined by Western blot.Furthermore,the invasion and migration of OSCC cells were analyzed by Transwell assay and scratch test.Finally,the pulmonary metastasis model of nude mice was established.RESULTS:The results of the databases showed that RhoC was highly expressed in OSCC tissues,which was closely related to pathological stage,pathological grade and lymph node metastasis,but not significantly related to the sur-vival rate of patients.Furthermore,compared with paracancer tissues,the mRNA and protein expression levels of RhoC were increased in OSCC tissues(P<0.01).Silencing of RhoC prominently reduced the migration and invasion of OSCC cells as well as the protein levels of p-FAK,p-MAPK,MMP2 and MMP9(P<0.05).The protein levels of MAPK and FAK were unchanged(P>0.05).The fluorescence intensity of the experimental group was significantly lower than that of the control group,and the results of HE staining showed that the number of lung nodules in the experimental group was sig-nificantly reduced(P<0.05).CONCLUSION:RhoC can effectively influence the migration and invasion of OSCC cells,and its potential mechanism may be related to FAK/MAPK/MMPs signaling pathway.

Objective To analyze the atrioventricular synchronization rate after implantation of Micra AV leadless pacemaker,and the impact of postoperative programming optimization on atrioventricular synchronization rate.Methods A prospective cohort study was conducted to select patients with complete atrioventricular block who underwent Micra AV leadless pacemaker implantation at Beijing Anzhen Hospital from August 2022 to June 2023.Programming optimization were performed at 1 week,1 month,and 3 months postoperatively,and atrioventricular synchronization rate,electrical parameters,and echocardiography were recorded.Results A total of 68 patients with complete atrioventricular block implanted with Micra AV were selected,with an average age of(68.2±9.7)years,including 47 males(69.1％).All patients were successfully implanted with Micra AV,and there were no serious postoperative complications;The average threshold,sense,and impedance parameters were stable during 1 week,1 month,and 3 months after the procedure;There was no significant difference in the EF value of postoperative echocardiography(P=0.162);The average atrioventricular synchronization rates at 1 week,1 month,and 3 months postoperatively were(75.2％vs.83.8％vs.91.6％,P=0.001).Conclusions As an mechanical atrial sensing,Micra AV requires personalized adjustment of relevant parameters;Postoperative follow-up programming optimization plays an important role in the atrioventricular synchronization and comfort level in patients with complete atrioventricular block after implantation of Micra AV leadless pacemaker.

Objective: To investigate the factors affecting depression and anxiety symptoms among the elderly, so as to provide the basis for promoting mental health among the elderly. Methods: The elderly aged 60 years and above in Ningbo City, Zhejiang Province were recruited using the multistage stratified random sampling method from June to August 2022, and demographic information, lifestyle and self-rated health status were collected by questionnaires. The symptoms of depression and anxiety were assessed by the Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder-7 (GAD-7), respectively. The presence of depressive and anxiety symptoms was determined when both the PHQ-9 score and the GAD-7 score were 10 points and higher. Factors affecting depressive and anxiety symptoms were identified using a multivariable logistic regression model. Results: A total of 7 771 individuals were surveyed, including 3 490 males (44.91%) and 4 281 females (55.09%), and had a mean age of (72.11±6.79) years. The prevalence of depression and anxiety symptoms was 2.05%. Multivariable logistic regression analysis identified residence (urban area, OR=0.316, 95%CI: 0.201-0.498), sedentary duration (<3 h/d, OR=0.349, 95%CI: 0.232-0.525; 3-5 h/d, OR=0.458, 95%CI: 0.313-0.671), physical activity (≥3 times/week, OR=0.551, 95%CI: 0.373-0.815), sleep quality (poor, OR=2.491, 95%CI: 1.738-3.571), social isolation (OR=1.688, 95%CI: 1.148-2.481) and self-rated health (poor, OR=5.857, 95%CI: 3.547-9.671; normal, OR=1.903, 95%CI: 1.234-2.937) as the influencing factors for depression and anxiety symptoms among the elderly. Conclusion The prevalence of depression and anxiety symptoms among the elderly is associated with residence, sedentary duration, sleep quality, physical activity, social interactions and self-rated health status.