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.

ObjectiveTo address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

ObjectiveTo explore the application effects of environmentally friendly reagents versus traditional reagents in tissue processing， paraffin sectioning， hematoxylin-eosin （HE） staining， special staining， and immunohistochemistry. MethodsPancreatic， renal， splenic， hepatic， pulmonary， skeletal muscle， and cardiac tissues were collected from mice and New Zealand rabbits， and randomly divided into a traditional group （Group A）， an environmentally friendly reagent I group （Group B）， and an environmentally friendly reagent Ⅱ group （Group C）. The processed tissue sections from all three groups were subjected to paraffin sections， HE staining， phosphotungstic acid-hematoxylin staining， and Mallory trichrome staining. The pancreatic tissue sections were subjected to immunohistochemical detection of insulin protein. Evaluation criteria included tissue morphological integrity， embedding operability， section quality， and staining effects. ResultsNo significant differences were observed among the three groups of samples in terms of fixation efficacy， embedding operations， and section quality. After HE staining， all groups exhibited bright nuclear and cytoplasmic staining with clear contrast， with excellent-and-good rates of 98%， 99%， and 97% for Groups A， B， and C， respectively， showing no statistically significant differences （A vs. B， P=0.561； A vs. C， P=0.651）. In phosphotungstic acid-hematoxylin staining， Groups A and C showed clear structural contrast and bright staining for striated muscle and collagen fibers， whereas Group B exhibited uneven staining. The excellent-and-good rates were 100%， 10%， and 95% for Groups A， B， and C， respectively， with significant differences between Group A and Group B （P＜0.01） but no statistical difference between Group A and Group C （P=0.311）. In Mallory trichrome staining， Groups A and B outperformed Group C. The excellent-and-good rates were 95%， 90%， and 15% for Groups A， B， and C， respectively， with significant differences between Group A and Group C （P＜0.01）， but no statistical difference between Group A and Group B （P=0.548）. Immunohistochemical results showed that Group A had a clean background with no non-specific staining， while Groups B and C exhibited significant non-specific staining， with statistically significant differences in non-specific staining rates between the groups （A vs. B， 5% vs. 100%， P＜0.01； A vs. C， 5% vs.100%， P＜0.01）. ConclusionIn HE staining， environmentally friendly reagents demonstrated effective tissue fixation and staining results comparable to traditional reagents， meeting the teaching requirements. For special staining， Group B and Group C performed better in Mallory trichrome staining and phosphotungstic acid-hematoxylin staining， respectively. However， environmentally friendly reagents exhibited non-specific staining issues in immunohistochemistry， where further optimization is required.