ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

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.

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

Based on serum metabolomics and gut microbiota technology, this study explores the effects and mechanisms of the water extract of Ziziphi Spinosae Semen(SZRW) and the petroleum ether extract of Ziziphi Spinosae Semen(SZRO) in improving depressive-like behaviors induced by sleep deprivation. A modified multi-platform water environment method was employed to establish a rat model of sleep deprivation. Depressive-like behaviors in rats were assessed through the sucrose preference test and forced swim test. The expression of barrier proteins, such as Occludin, in the colon was determined by immunofluorescence. UPLC-Q-Orbitrap MS was utilized to analyze the serum metabolic profiles of sleep-deprived rats, screen for differential metabolites, and analyze metabolic pathways. The diversity of the gut microbiota was detected using 16S rRNA gene sequencing. Spearman correlation coefficient analysis was conducted to assess the correlation between differential metabolites and gut microbiota. The results indicated that SZRO significantly increased the sucrose preference index and decreased the immobility time in the forced swim test in rats. A total of 34 differential metabolites were identified through serum metabolomics. SZRW and SZRO shared five metabolic pathways, including phenylalanine metabolism. SZRW uniquely featured taurine and hypotaurine metabolism, while SZRO uniquely featured linoleic acid metabolism and tyrosine metabolism. Correlation analysis revealed that SZRW could upregulate the abundance of Bilophila, promoting the production of indole-3-propionic acid and subsequently upregulating the expression levels of intestinal tight junction proteins such as ZO-1, Occludin, and Claudin-1. SZRO could indirectly influence metabolic pathways such as arginine metabolism and linoleic acid metabolism by upregulating the abundance of gut microbiota such as Coprococcus and Eubacterium species. Both SZRW and SZRO can regulate endogenous metabolism, including amino acids, energy, and lipids, alter the gut microbiota microecology, and improve depressive-like behaviors. SZRO demonstrated superior effects in regulating metabolic pathways and gut microbiota structure compared to SZRW. The findings of this study provide a scientific basis for elucidating the pharmacodynamic material basis of Ziziphi Spinosae Semen.
Animals ; Rats ; Gastrointestinal Microbiome/drug effects* ; Male ; Metabolomics ; Drugs, Chinese Herbal/administration & dosage* ; Depression/blood* ; Rats, Sprague-Dawley ; Sleep Deprivation/complications* ; Ziziphus/chemistry* ; Antidepressive Agents/administration & dosage* ; Behavior, Animal/drug effects* ; Humans

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.

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.

In this study, the pharmacokinetic characteristics and tissue distribution of cannabidiol(CBD)/γ-polyglutamic acid-g-cholesterol(γ-PGA-g-CHOL) nanomicelles [CBD/(γ-PGA-g-CHOL)NMs] were investigated by pharmacokinetic experiments, and the effect of CBD/(γ-PGA-g-CHOL)NMs on the lipopolysaccharide(LPS)-induced inflammatory damage of cells was evaluated by cell experiments. CBD/(γ-PGA-g-CHOL)NMs were prepared by dialysis. The CBD concentrations in the plasma samples of male SD rats treated with CBD and CBD/(γ-PGA-g-CHOL)NMs were investigated, and the pharmacokinetic parameters were calculated and compared. UPLC-MS/MS was employed to determine the concentration of CBD in tissue samples. The heart, liver, spleen, lung, kidney, and muscle samples were collected at different time points to explore the tissue distribution of CBD and CBD/(γ-PGA-g-CHOL)NMs. The Caco-2 cell model of LPS-induced inflammation was established, and the cell viability, transepithelial electrical resistance(TEER), and secretion levels of inflammatory cytokines were determined to compare the anti-inflammatory activity between the two groups. The results showed that CBD/(γ-PGA-g-CHOL)NMs had the average particle size of(163.1±2.3)nm, drug loading of 8.78%±0.28%, and encapsulation rate of 84.46%±0.35%. Compared with CBD, CBD/(γ-PGA-g-CHOL)NMs showed increased peak concentration(C_(max)) and prolonged peak time(t_(max)) and mean residence time(MRT_(0-t)). Within 24 h, the tissue distribution concentration of CBD/(γ-PGA-g-CHOL)NMs was higher than that of CBD. In addition, both CBD and CBD/(γ-PGA-g-CHOL)NMs significantly enhanced Caco-2 cell viability and TEER, lowered the secretion levels of inflammatory cytokines, and alleviated inflammation. Moreover, CBD/(γ-PGA-g-CHOL)NMs demonstrated stronger anti-inflammatory effect. It can be inferred that γ-PGA-g-CHOL blank nanomicelles are good carriers of CBD, being capable of prolonging the circulation time of CBD in the blood, improving the bioavailability and tissue distribution concentration of CBD, and protecting against LPS-induced inflammatory injury. The findings can provide an experimental basis for the development and clinical application of oral CBD preparations.
Animals ; Cannabidiol/administration & dosage* ; Polyglutamic Acid/analogs & derivatives* ; Humans ; Male ; Rats ; Rats, Sprague-Dawley ; Anti-Inflammatory Agents/administration & dosage* ; Micelles ; Caco-2 Cells ; Cholesterol/pharmacokinetics* ; Tissue Distribution ; Nanoparticles/chemistry*