The gut microbiota is regarded as the "eighth organ" of the human body and plays a critical regulatory role in the occurrence and progression of various diseases. Ulcerative colitis （UC） is a chronic inflammatory bowel disease with a complex etiology and a tendency toward recurrent episodes. In recent years， studies have shown that gut microbiota dysbiosis plays a key role in its pathological processes. Meanwhile， an increasing number of studies have demonstrated that imbalances in the gut microbiota and abnormalities in its metabolites are closely associated with the development of atrial fibrillation （AF）. Although UC and AF belong to diseases of the digestive system and cardiovascular system， respectively， both exhibit systemic inflammatory characteristics and are often accompanied by gut microbiota dysregulation and abnormal metabolic products. However， systematic investigations into the mechanisms by which gut microbiota-derived metabolites act in these two diseases remain limited. Based on this， the present study adopts literature review and theoretical analysis methods， taking the "gut microbiota-gut-heart" axis as the entry point， to systematically summarize the signaling networks of three key classes of metabolites， i.e.， short-chain fatty acids （SCFAs）， bile acids （BAs）， and trimethylamine N-oxide （TMAO）， in the comorbidity mechanism of UC and AF. The findings indicate that these metabolites may activate key inflammatory pathways， such as NF-κB and NLRP3， thereby synergistically mediating intestinal barrier dysfunction and systemic inflammation and constructing a potential comorbidity network. On this basis， potential intervention strategies for the treatment of UC-AF comorbidity， including probiotic intervention and fecal microbiota transplantation， are further discussed. This study aims to provide new theoretical evidence and research perspectives for prevention and treatment strategies of cross-system diseases.

AIM: To detect the distribution and expression of vascular endothelial growth factor(VEGF)in radiation retinopathy(RR)through fluorescence targeted imaging.METHODS:Covalent binding of fluorescein FITC with VEGF antibody ranibizumab to prepare targeted fluorescent imaging probe ranibizumab-FITC. SD rats were randomly divided into three groups based on the principle of weight balance: a normal control group(Con group), a low-dose radiation group(10 Gy group), and a high-dose radiation group(30 Gy group). Medical linear accelerators and lead blocks were used to locally irradiate the rat eyeballs for modeling. Western blot and qRT-PCR were used to detect the expression levels of VEGF-A in each group and to screen for appropriate modeling dose. The inverted fluorescence microscope and the confocal microscope were used to observe the distribution of VEGF and imaging probes in the retinas of control and RR model group rats, and to verify the effectiveness of targeted probes.RESULTS:The expression level of VEGF-A in the retina of rats in the high-dose radiation group(30 Gy group)was higher than that in the normal control group(Con group). In early RR, VEGF expression was observed to be associated with microaneurysms and abnormal microvessels in the retina. VEGF accumulation was observed at the site of capillary wall damage. When retinal capillary endothelial damage occurred, targeted probes gathered on the outer surface of the vessel wall.CONCLUSION:The expression level of VEGF in the retina of RR model rats is elevated, and fluorescent targeted molecular imaging probes can detect the spatial distribution of VEGF at the microvascular lesions in the retina of RR rats.

This paper proposes a two-stage method integrating visual foundation models （VFM） and diffusion models. The segment anything model （SAM） as VFM is combined with the SegRefiner diffusion model to construct the SAM-SegRefiner framework for automated segmentation of edema， inflammation， and thrombus regions in histopathological images of hemorrhoidal tissue， providing a reproducible technical tool for the objective quantification of pathological morphology and its application in traditional Chinese medicine （TCM） syndrome research. Trained and validated on multi-center retrospective data， the SAM-SegRefiner model achieved an average pixel accuracy of 95.32% and a mean intersection over union （mIoU） of 66.81% on an independent test set， significantly outperfor-ming comparative models such as U-Net， MixU-Net， and SAM-Med2D， and also demonstrating robust cross-center generalization capability. Furthermore， by correlating the quantitatively segmented results from the model with the patients' TCM syndrome types， the potential associations between pathomorphological features and TCM syndrome differentiation have been explored. The analysis revealed no statistically significant differences in the degree of inflammatory infiltration and thrombus formation among different syndrome types， suggesting a complex relationship between local pathological changes and systemic syndrome manifestations.

OBJECTIVE To compare the efficacy and safety of tildrakizumab versus secukinumab in the treatment of moderate-to-severe plaque psoriasis. METHODS A retrospective analysis was conducted on 141 patients with moderate-to-severe plaque psoriasis treated at the First Affiliated Hospital of Nanyang Medical College from January 2024 to April 2025. According to the treatment regimen，the patients were divided into tildrakizumab g roup （ n ＝61） and secukinumab group （ n ＝80）. The PASI 75，PASI 90，and PASI 100 response rates， the Psoriasis Area and Severity Index （PASI） and Dermatology Life Quality Index （DLQI） scores， skin barrier function （sebum content and stratum corneum water content）， inflammatory factor levels [interleukin-17 （IL-17）， tumor necrosis factor-α （TNF-α）， and IL-23 ] before and after treatment， and the incidence of adverse drug reactions during treatment were compared between the two groups. RESULTS After 12 weeks of treatment， the PASI 75， PASI 90， and PASI 100 response rates in the tildrakizumab group were significantly higher than those in the secukinumab group （ P ＜0.05）. After treatment， PASI and DLQI scores as well as serum levels of IL-17， TNF-α， and IL-23 in both groups were significantly reduced compared to before treatment in the same group； sebum content and stratum corneum water content were significantly increased compared to before treatment in the same group （ P ＜0.05）； the tildrakizumab group showed better results than the secukinumab group （ P ＜0.05）. The overall incidence of adverse drug reactions was also significantly lower in the tildrakizumab group compared with the secukinumab group （ P ＜0.05）. CONCLUSIONS Compared with secukinumab， tildrakizumab demonstrates superior efficacy in the treatment of moderate-to-severe plaque psoriasis， providing improved symptom relief， enhanced skin barrier function， reduced levels of inflammatory factors， and higher safety.

Background: Xiaochaihu capsules are a widely used traditional Chinese patent medicine. The extraction process, a critical step in their production, necessitates online monitoring to determine the levels of key indicators, thereby informing subsequent processing stages. Objective: The objective of this study was to establish online quantitative models for 6 key indicators (solid content, liquiritin, baicalin, wogonoside, glycyrrhizic acid, and saikosaponin B ) during the extraction process of Xiaochaihu capsules. This approach aims to provide a technical foundation for enhanced process control and to serve as a methodological reference for the application of multisource information fusion in monitoring the extraction of multi-herb traditional Chinese medicine formulations. Methods: Online quantitative models were developed based on multiple sensors, ultraviolet-visible spectroscopy (UV-Vis), and near-infrared spectroscopy (NIR) to monitor 6 indicators during the extraction process of Xiaochaihu capsules. Different preprocessing methods for spectroscopic data were optimized, and data fusion strategies were integrated to improve the predictive performance of the online quantitative models. Results: The optimal modeling strategies for the 6 indicators were as follows: for solid content, a second-order polynomial model was established using the measurement results from 2 sensors (pH and conductivity), with a predictive coefficient of determination (R ) of 0.9821. For baicalin, the optimal model was developed using UV-Vis spectra pretreated with the first derivative (1stD), achieving a predictive R of 0.9841. For wogonoside, modeling was also conducted after 1stD preprocessing of the UV-Vis spectra, yielding a predictive R of 0.9929. For liquiritin, a high-level fusion strategy combining UV-based feature extraction via the random frog (RF) algorithm and NIR-based feature extraction via competitive adaptive reweighted sampling (CARS) was used, achieving an R of 0.9406 in the validation set. For glycyrrhizic acid, the optimal approach involved a combination of UV-CARS feature extraction and NIR-RF feature extraction, coupled with high-level data fusion, resulting in an R of 0.9859 in the validation set. For saikosaponin B , the optimal scheme utilized UV-RF feature extraction combined with NIR-CARS feature extraction and high-level fusion (R = 0.7702 in the validation set). Conclusion: The integration of process analytical technologies and data fusion strategies enabled the successful establishment of online quantitative models for 6 indicators during the extraction process of Xiaochaihu capsules. Overall, the established online quantitative models effectively captured and reflected the dynamic changes of these indicators throughout the extraction process.

Objective To explore the application value of computed tomography (CT) three-dimensional reconstruction in total knee arthroplasty (TKA). Methods A total of 102 patients who underwent TKA in our hospital between April 2022 and April 2025 were enrolled and divided using a random number table into a traditional group (51 cases, routine preoperative evaluation) and a study group (51 cases, CT three-dimensional reconstruction-assisted surgery). The therapeutic efficacy at 3 months postoperatively and perioperative indicators were compared between the two groups. The hip-knee-ankle (HKA) angle was measured preoperatively and at 3 months postoperatively. The Hospital for Special Surgery (HSS) knee score and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score were recorded preoperatively and at 3 and 6 months postoperatively. Complications were documented. Results The excellent/good rate in the study group (92.16%) was higher than that in the traditional group (74.51%) (P<0.05). The operation time, intraoperative blood loss, postoperative drainage volume, and hospital stay in the study group were (69.52 ± 7.11) min, (102.69 ± 8.54) mL, (167.33 ± 12.35) mL, and (10.93 ± 2.37) days, respectively, which were shorter than those in the traditional group [(78.45 ± 5.98) min, (108.36 ± 10.02) mL, (175.96 ± 14.93) mL, and (12.04 ± 1.95) days] (P<0.05). At 3 months postoperatively, the HKA angle was 178.02° ± 1.05° in the study group and 177.45° ± 1.34° in the traditional group, both were significantly improved compared with those before operation, with the study group showing better improvement (P<0.05). The HSS knee and WOMAC scores in both groups at 3 and 6 months postoperatively were improved compared with preoperative scores (P<0.05). At 3 and 6 months postoperatively, the study group showed higher HSS knee score and lower WOMAC score than the traditional group (P<0.05). The incidence of complications in the study group (3.92%) was lower than that in the traditional group (17.65%) (P<0.05). Conclusion TKA guided by CT three-dimensional reconstruction improved the excellent/good rate, optimized HKA angle and knee function, shortened operation time and hospital stay, reduced intraoperative blood loss and postoperative drainage volume, and decreased the incidence of complications.

Objective To explore the application value of computed tomography (CT) three-dimensional reconstruction in total knee arthroplasty (TKA). Methods A total of 102 patients who underwent TKA in our hospital between April 2022 and April 2025 were enrolled and divided using a random number table into a traditional group (51 cases, routine preoperative evaluation) and a study group (51 cases, CT three-dimensional reconstruction-assisted surgery). The therapeutic efficacy at 3 months postoperatively and perioperative indicators were compared between the two groups. The hip-knee-ankle (HKA) angle was measured preoperatively and at 3 months postoperatively. The Hospital for Special Surgery (HSS) knee score and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score were recorded preoperatively and at 3 and 6 months postoperatively. Complications were documented. Results The excellent/good rate in the study group (92.16%) was higher than that in the traditional group (74.51%) (P<0.05). The operation time, intraoperative blood loss, postoperative drainage volume, and hospital stay in the study group were (69.52 ± 7.11) min, (102.69 ± 8.54) mL, (167.33 ± 12.35) mL, and (10.93 ± 2.37) days, respectively, which were shorter than those in the traditional group [(78.45 ± 5.98) min, (108.36 ± 10.02) mL, (175.96 ± 14.93) mL, and (12.04 ± 1.95) days] (P<0.05). At 3 months postoperatively, the HKA angle was 178.02° ± 1.05° in the study group and 177.45° ± 1.34° in the traditional group, both were significantly improved compared with those before operation, with the study group showing better improvement (P<0.05). The HSS knee and WOMAC scores in both groups at 3 and 6 months postoperatively were improved compared with preoperative scores (P<0.05). At 3 and 6 months postoperatively, the study group showed higher HSS knee score and lower WOMAC score than the traditional group (P<0.05). The incidence of complications in the study group (3.92%) was lower than that in the traditional group (17.65%) (P<0.05). Conclusion TKA guided by CT three-dimensional reconstruction improved the excellent/good rate, optimized HKA angle and knee function, shortened operation time and hospital stay, reduced intraoperative blood loss and postoperative drainage volume, and decreased the incidence of complications.

Objective To explore the application value of computed tomography (CT) three-dimensional reconstruction in total knee arthroplasty (TKA). Methods A total of 102 patients who underwent TKA in our hospital between April 2022 and April 2025 were enrolled and divided using a random number table into a traditional group (51 cases, routine preoperative evaluation) and a study group (51 cases, CT three-dimensional reconstruction-assisted surgery). The therapeutic efficacy at 3 months postoperatively and perioperative indicators were compared between the two groups. The hip-knee-ankle (HKA) angle was measured preoperatively and at 3 months postoperatively. The Hospital for Special Surgery (HSS) knee score and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score were recorded preoperatively and at 3 and 6 months postoperatively. Complications were documented. Results The excellent/good rate in the study group (92.16%) was higher than that in the traditional group (74.51%) (P<0.05). The operation time, intraoperative blood loss, postoperative drainage volume, and hospital stay in the study group were (69.52 ± 7.11) min, (102.69 ± 8.54) mL, (167.33 ± 12.35) mL, and (10.93 ± 2.37) days, respectively, which were shorter than those in the traditional group [(78.45 ± 5.98) min, (108.36 ± 10.02) mL, (175.96 ± 14.93) mL, and (12.04 ± 1.95) days] (P<0.05). At 3 months postoperatively, the HKA angle was 178.02° ± 1.05° in the study group and 177.45° ± 1.34° in the traditional group, both were significantly improved compared with those before operation, with the study group showing better improvement (P<0.05). The HSS knee and WOMAC scores in both groups at 3 and 6 months postoperatively were improved compared with preoperative scores (P<0.05). At 3 and 6 months postoperatively, the study group showed higher HSS knee score and lower WOMAC score than the traditional group (P<0.05). The incidence of complications in the study group (3.92%) was lower than that in the traditional group (17.65%) (P<0.05). Conclusion TKA guided by CT three-dimensional reconstruction improved the excellent/good rate, optimized HKA angle and knee function, shortened operation time and hospital stay, reduced intraoperative blood loss and postoperative drainage volume, and decreased the incidence of complications.

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

ObjectiveTo investigate the therapeutic effects of direct-acting antiviral agents (DAAs) combined regimens for hepatitis C virus (HCV) patients in Dehong Prefecture, Yunnan Province from 2022 to 2024, to analyze the characteristics of treatment failure patients, so as to provide a basis for discovering more effective treatment regimens in the future. MethodsData on HCV prevention and treatment in Dehong Prefecture was extracted from the China Disease Control and Prevention Information System. A total of 617 patients with HCV antiviral therapy were included, and the differences in variable characteristics among patients with different genotypes were analyzed using comparative statistical tests, including basic socio-demographic characteristics, biochemical testing indicators, and information on previous treatment and current treatment. In addition, the cure rate of HCV patients with diverse characteristics was compared, and the potential causes of treatment failure were explored simultaneously. ResultsThe cure rate of HCV was 96.8%, and statistically significant differences were observed in aspartate transaminase (AST) and alanine transaminase (ALT) levels, previous antiviral therapy history and initial treatment regimens among patients with different HCV genotypes (all P<0.05). Among the multi-type combination regimens, the cure rate of sofosbuvir (SOF)-containing regimens was 97.00%, that of velpatasvir (VEL)-containing regimens was 95.45%, and the cure rate of other treatment regimens, including the regimens with ribavirin (RIB) intervention, was 93.10%. Among the patients with treatment failure, 45.00% had genotype 3, 40.00% had abnormal abdominal ultrasound results, and all presented with elevated baseline AST test levels. ConclusionThe clinical treatment of HCV patients should consider the differences in genotype and biochemical test results. DAAs combined regimens for HCV have achieved a high cure rate in Dehong Prefecture and are applicable to HCV patients with diverse clinical characteristics, providing research evidence for wider application.