Objective To investigate the independent risk factors affecting the prognosis of chronic active antibody-mediated rejection (caAMR) after kidney transplantation. Methods A retrospective analysis was conducted on 61 patients who underwent renal biopsy and were diagnosed with caAMR. The patients were divided into caAMR group (n=41) and caAMR+TCMR group (n=20) based on the presence or absence of concurrent acute T cell-mediated rejection (TCMR). The patients were followed up for 3 years. The value of 24-hour urinary protein and estimated glomerular filtration rate (eGFR) at the time of biopsy in predicting graft loss was assessed using receiver operating characteristic (ROC) curves. The independent risk factors affecting caAMR prognosis were analyzed using the LASSO-Cox regression model. The correlation between grouping, outcomes, and Banff scores was compared using Spearman rank correlation matrix analysis. Kaplan-Meier analysis was used to evaluate the renal allograft survival rates of each subgroup. Results The 3-year renal allograft survival rates for the caAMR group and the caAMR+TCMR group were 83% and 79%, respectively. The area under the ROC curve (AUC) for predicting 3-year renal allograft loss was 0.83 ［95% confidence interval (CI) 0.70-0.97］ for eGFR and 0.78 (95% CI 0.61-0.96) for 24-hour urinary protein at the time of biopsy. LASSO-Cox regression analysis and Kaplan-Meier analysis showed that eGFR≤25.23 mL/(min·1.73 m²) and the presence of donor-specific antibody (DSA) against human leukocyte antigen (HLA) class I might be independent risk factors affecting renal allograft prognosis, with hazard ratios of 7.67 (95% CI 2.18-27.02) and 5.13 (95% CI 1.33-19.80), respectively. A strong correlation was found between the Banff chronic lesion indicators of renal interstitial fibrosis and tubular atrophy (P<0.05). Conclusions The presence of HLA class I DSA and eGFR≤25.23 mL/(min·1.73 m²) at the time of biopsy may be independent risk factors affecting the prognosis of caAMR.

ObjectiveTo investigate the content of trihalomethanes (THMs) in treated water after different water treatment processes and their correlations with premanganate index, so as to provide data support for the renovation of water production process and optimization of water quality improvement. MethodsFrom 2022 to 2023, seven centralized water supply units using raw water from Qingcaosha reservoir were selected as the testing sites, among which three units with the conventional treatment process, two units with the advanced treatment process, and two units with the advanced treatment process combined CO₂ treatment. Monthly water quality testing data were collected, focusing on testing the concentration variations of THMs, trichloromethane, dibromochloromethane, bromodichloromethane, bromoform, and permanganate index. ResultsThe comparison between conventional treatment process and advanced treatment process demonstrated that the conventional treatment process exhibited significantly higher concentrations of trihalomethanes, trichloromethane, bromodichloromethane, and permanganate index in water samples (all P<0.05). When comparing conventional treatment process with advanced treatment process combined with carbon dioxide treatment, the conventional treatment process showed significantly elevated levels of trihalomethanes, dibromochloromethane, bromodichloromethane, and permanganate index (all P<0.05). No statistically significant differences were observed in the comparison of various indicators between advanced treatment process and advanced treatment process combined with carbon dioxide treatment for any of the measured parameters (all P>0.05). Analysis of seasonal variations revealed that finished water during the high-temperature period (May to November) contained significantly higher concentrations of trihalomethanes, trichloromethane, bromodichloromethane, and tribromomethane compared to the low-temperature period (December to April of the following year) (all P<0.05). Significant positive correlations were identified between permanganate index and trihalomethanes (r=0.213, P=0.007), permanganate index and dibromochloromethane (r=0.186, P=0.019), permanganate index and bromodichloromethane (r=0.243, P=0.002), permanganate index and tribromomethane (r=0.193, P=0.014). ConclusionCompared to the conventional water treatment process, advanced treatment process and advanced treatment combined with CO₂ injection process can significantly reduce the concentrations of THMs in the treated effluent water. Besides, the generation of THMs is affected by seasonal temperatures, with higher concentrations of THMs, trichloromethane, bromodichloromethane, and bromoform being observed in the high-temperature season. Additionally, the permanganate index shows a significant positive correlation with THMs concentrations, indicating that the content of organic matter in the source of raw water contributes to the generation of THMs in the treated water.

ObjectiveTo investigate the mechanism by which Feixin decoction treats hypoxic pulmonary hypertension （HPH） by regulating the peroxisome proliferator-activated receptor gamma （PPARγ）/nuclear factor-kappa B （NF-κB）/NOD-like receptor pyrin domain containing 3 （NLRP3） signaling pathway. MethodsForty-eight male SD rats were randomly allocated into normal， hypoxia， and low-， medium- and high-dose （5.85， 11.7， 23.4 g·kg^-1， respectively） Feixin decoction groups， with 8 rats in each group. Except the normal group， the remaining five groups were placed in a hypoxia chamber with an oxygen concentration of （10.0±0.5）% for 8 h per day， 28 days， and administrated with corresponding drugs during the modeling process. After 4 weeks of treatment， echocardiographic parameters ［pulmonary artery acceleration time （PAT）， pulmonary artery ejection time （PET）， right ventricular anterior wall thickness （RVAWd）， and tricuspid annular plane systolic excursion （TAPSE）］ were measured for each group. The right ventricular systolic pressure （RVSP） was measured by the right heart catheterization method， and the right ventricular hypertrophy index （RVHI） was calculated by weighing the heart. The pathological changes in pulmonary arterioles were observed by hematoxylin-eosin staining. The co-localization of α-smooth muscle actin （α-SMA） with NLRP3， N-terminal gasdermin D （N-GSDMD）， and cysteinyl aspartate-specific proteinase-1 （Caspase-1） in pulmonary arteries was detected by immunofluorescence. The protein levels of PPARγ， NF-κB， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， N-GSDMD， interleukin-1β （IL-1β）， interleukin-18（IL-18）， and cleaved Caspase-1 in the lung tissue was determined by Western blot. The ultrastructural changes in pulmonary artery smooth muscle cells （PASMCs） were observed by transmission electron microscopy. ResultsCompared with the normal group， the hypoxia group showed increased RVSP and RVHI （P<0.01）， decreased right heart function （P<0.01）， increased pulmonary vascular remodeling （P<0.01）， increased co-localization of α-SMA with NLRP3， N-GSDMD， and Caspase-1 in pulmonary arterioles （P<0.01）， up-regulated protein levels of NF-κB， NLRP3， ASC， N-GSDMD， IL-1β， IL-18， and cleaved Caspase-1 in the lung tissue （P<0.05， P<0.01）， a down-regulated protein level of PPARγ （P<0.05， P<0.01）， and pyroptosis in PASMCs. Compared with the hypoxia group， Feixin decoction reduced RVSP and RVHI， improved the right heart function and ameliorated pulmonary vascular remodeling （P<0.05， P<0.01）， decreased the co-localization of α-SMA with NLRP3， N-GSDMD， and Caspase-1 （P<0.05， P<0.01）， down-regulated the protein levels of NF-κB， NLRP3， ASC， N-GSDMD， IL-1β， IL-18， and cleaved Caspase-1 in the lung tissue （P<0.05， P<0.01）， up-regulated the protein level of PPARγ （P<0.05， P<0.01）， and alleviated pyroptosis in PASMCs. ConclusionFeixin decoction can ameliorate pulmonary vascular remodeling and right heart dysfunction in chronically induced HPH rats by regulating pyroptosis in PASMCs through the PPARγ/NF-κB/NLRP3 pathway.

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.

ObjectiveBased on the AMP-activated protein kinase （AMPK）/mammalian target of rapamycin （mTOR） signaling pathway， this study aimed to observe the effect of the Huazhuo Jiedu prescription on renal fibrosis in 5/6 nephrectomy rats and explore its underlying mechanism. MethodsA total of 67 SPF-grade male SD rats were used， of which 11 were randomly selected as the normal group. A chronic renal failure （CRF） model was established using 5/6 nephrectomy. The successfully modeled rats were randomly assigned to the model group， losartan potassium group （4.5 mg·kg^-1）， and low- （1.175 g·kg^-1）， medium- （2.35 g·kg^-1） and high-dose （4.7 g·kg^-1） Huazhuo Jiedu prescription groups， with 9 rats per group. Each group received an equivalent volume of saline or the corresponding concentration of Huazhuo Jiedu prescription by gavage once daily for 8 weeks. Hematoxylin-eosin （HE） and Masson staining were used to observe renal tissue pathological changes. Transmission electron microscopy examined renal ultrastructure. Immunohistochemistry （IHC） detected expressions of α-smooth muscle actin （α-SMA） and transforming growth factor-β₁ （TGF-β₁）. Western blot analyzed expression levels of microtubule-associated protein Ⅰ light chain 3Ⅱ （LC3Ⅱ）， Beclin1， p62， AMPK， phosphorylated AMPK （p-AMPK）， mTOR， and phosphorylated mTOR （p-mTOR）. ResultsCompared with the normal group， the model group exhibited glomerular shrinkage， mesangial and interstitial thickening， and tubular vacuolar degeneration， with no evident autophagosomes or autophagolysosome structures. Expression levels of α-SMA and TGF-β₁ were significantly increased （P0.01）， while p-AMPK/AMPK， Beclin1， and LC3Ⅱ were significantly decreased （P0.01）， and p-mTOR/mTOR and p62 were significantly increased （P0.01）. Compared with the model group， the medium- and high-dose Huazhuo Jiedu prescription groups and the losartan potassium group showed varying degrees of pathological improvement. Autophagosomes with double- or multiple-layer membranes and autophagolysosomes with monolayer membranes containing undegraded organelles were observed. Renal α-SMA and TGF-β₁ protein expression levels were markedly reduced （P0.05， P0.01）， p-mTOR/mTOR and p62 were significantly decreased （P0.05， P0.01）， and p-AMPK/AMPK， Beclin1， and LC3Ⅱ expression levels were significantly increased （P0.05， P0.01）. ConclusionHuazhuo Jiedu prescription may improve renal fibrosis in 5/6 nephrectomy rats by regulating the AMPK/mTOR signaling pathway and enhancing autophagy.

Poloxamer， as a non-ionic surfactant， exhibits a unique triblock [polyethylene oxide-poly （propylene oxide）-polyethylene oxide] structure， which endows it with broad application potential in various fields， including solid dispersion technology， nanotechnology， gel technology， biologics， gene engineering and 3D printing. As a carrier， it enhances the solubility and bioavailability of poorly soluble drugs. In the field of nanotechnology， it serves as a stabilizer etc.， enriching preparation methods. In gel technology， its self-assembly behavior and thermosensitive properties facilitate controlled drug release. In biologics， it improves targeting efficiency and reduces side effects. In gene engineering， it enhances delivery efficiency and expression levels. In 3D printing， it provides novel strategies for precise drug release control and the production of high-quality biological products. As a versatile material， poloxamer holds promising prospects in the pharmaceutical field.

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.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.