Low anterior resection syndrome （LARS） is a common complication of sphincter-preserving rectal cancer surgery， and its manifestations change dynamically at different stages. By analyzing and summarizing the clinical symptoms and pathomechanism evolution of LARS across different stages， this paper proposes a staged prevention and treatment strategy using acupuncture. During perioperative stage， the main principle is activating the transport function of the body， supplemented by regulating the mind， with the use of dredging the bowels as needed. During the stoma reversal stage， treatment focuses primarily on fortifying the spleen， with draining dampness as a supplementary method， to help consolidate the intestines. During the radiotherapy or chemotherapy stage， the main focus is reinfor-cing healthy qi， with reducing toxin as an adjunct， to achieve the effect of activating the transport of the pivot. During the survival management stage， treatment primarily focuses on tonifying the kidneys and secondarily on fortifying the spleen， with regulating the corporeal soul as the therapeutic emphasis. Acupoints are selected and combined in accordance with the treatment principles at each stage， and different stimulation methods such as electroacupuncture and moxibustion are applied. An analysis of the mechanisms underlying acupuncture for LARS is also provided， offering a theoretical basis and practical approach for the prevention and treatment of LARS with acupuncture.

Based on the theory of diseased collaterals and the progression pattern of diabetic kidney disease （DKD）， this paper proposes a staged treatment system based on the "three states of kidney collaterals" including collateral distention， collateral bi （痹） and collateral accumulation. In the collateral distention stage， the primary pathogenesis is heat damaging the kidney collaterals and collateral vessel dilation， corresponding to the early state of DKD characterized by hyperfiltration and microalbuminuria； the clearing method is suggested， and Shenling Jiangtang Formula （参苓降糖方） can be used to promote the remission of proteinuria by ameliorating insulin resistance and regulating intestinal microecology. In the collateral bi stage， the core pathogenesis lies in the binding of phlegm and stasis， and the formation of concretions and conglomerations in the kidney collaterals， corresponding to massive proteinuria and the decline of renal function， for which the unblocking method should be taken， using Jinchan Yishen Tongluo Formula （金蝉益肾通络方） and Qingre Xiaozheng Formula （清热消癥方） to alleviate renal pathological damage by regulating the autophagy-lysosome pathway and repairing mitochondrial energy metabolism. The collateral accumulation stage is characterized by the internal retention of turbid toxins and accumulations of concretions in the kidney collaterals， corresponding to renal fibrosis and end-stage renal disease （ESRD）； the dispersion method is suggested， and Yiqi Tongluo Xiezhuo Formula （益气通络泄浊方） and Shenyan Fangshuai Fluid （肾炎防衰液） can be used to inhibit extracellular matrix accumulation and delay the progressive loss of renal function. Collateral deficiency runs through the entire course of the disease and is closely related to cellular senescence and the imbalance of the ubiquitin-proteasome/autophagy system. The concept of the "three states of kidney collaterals" integrates the evolution of traditional Chinese medicine pathogenesis with modern pathological staging， forming a whole-course intervention system of "staging-syndrome differentiation-target-formula"， thereby providing novel insights for prevention and treatment of DKD using integrated traditional Chinese and western medicine.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Endometriosis is an estrogen-dependent chronic inflammatory disease that affects 5%to 10%of women of reproductive age worldwide.Its typical symptoms include dysmenorrhea,infertility,and chronic pelvic pain,which seriously affect quality of life.The tradi-tional diagnostic methods include ultrasonography,magnetic resonance imaging,and laparoscopy.Among these,laparoscopy is considered the gold standard for diagnosis.However,its invasive nature limits its widespread application.Recently,artificial intelligence has rapidly advanced in the diagnosis of endometriosis,significantly improving the accuracy and efficiency of early diagnosis by integrating imaging,clinical data,and biomarkers.This article summarizes the limitations of traditional diagnostic methods for endometriosis and the advance-ments in the application of artificial intelligence in the diagnosis of endometriosis,while exploring the potential of artificial intelligence using practical case studies.

In recent years, generative artificial intelligence (AI) technologies have achieved remarkable progress in the early screening, risk prediction, disease progression assessment, and clinical trial design of glaucoma.Using advanced algorithms, such as generative adversarial networks, variational autoencoders, and diffusion models, researchers have synthesized high-quality structural images of the optic disc, macular region, and retinal nerve fiber layer, which effectively alleviates the limitations of scarce clinical imaging data and label imbalance.These methods have substantially improved the accuracy and generalization of deep learning models in visual field defect prediction, structure-function mapping, and longitudinal disease progression simulation.Meanwhile, multimodal generative approaches that integrate imaging data, visual field tests, and clinical features have facilitated individualized prediction of glaucoma progression.In addition, large language models have shown preliminary potential in ophthalmic image interpretation, clinical text information extraction, and decision support, providing new insights into intelligent ophthalmic diagnosis and treatment.However, the clinical implementation of generative AI in glaucoma faces challenges.The pathological authenticity and cross-device consistency of generated images require further validation, which may affect the reliability of early glaucoma detection.The heterogeneous characteristics of different glaucoma subtypes, such as open-angle and angle-closure glaucoma, also limit the generalization of synthetic data.Moreover, issues related to model interpretability (" black-box" nature), artifact generation, data privacy, and ethical governance remain key barriers to clinical translation.In the future, it is expected that establishing large-scale training frameworks that incorporate multicenter, multimodal, and multiethnic datasets will enhance model robustness and clinical applicability.Furthermore, generative AI may contribute to remote ophthalmic care and personalized precision therapy by enhancing low-quality image, reconstructing missing data, and simulating dynamic disease courses.This article reviews the current applications, core technologies, and challenges of generative AI in glaucoma diagnosis and management, and discusses its future directions and translational potential in clinical ophthalmology.

BACKGROUND:Traditional total knee arthroplasty has limited preoperative preparation. We propose a digital precision total knee arthroplasty based oncomputer simulation and 3D printing technology,aiming to enhance surgical outcomes through comprehensive preoperative planning. OBJECTIVE:To establish a digital precision total knee arthroplasty using computer simulation and personalized surgical guides,and to compare the clinicaloutcomes between the new and traditional approaches.METHODS:A retrospective analysis was conducted on 97 patients who underwent total knee arthroplasty. Patients were divided into two groups based on the surgical method they received. The control group (n=48) underwent total knee arthroplasty using traditional methods and used conventional film templates. The observation group (n=49) underwent surgery using the digital precision total knee arthroplasty and utilized computer-assisted technology to select prosthetic sizes. Surgical time,intraoperative blood loss,preoperative and postoperative Hospital for Special Surgery knee joint function scores,as well as the differences in femoral alignment,knee joint line angle and tibial slope,and hip-knee-ankle angle compared to standard angles were compared between the two groups.RESULTS AND CONCLUSION:(1) There were no significant differences in gender,age,body mass index,Hospital for Special Surgery knee scores,as well as the differences in tibial slope,femoral alignment,knee joint line angle,hip-knee-ankle angle compared to standard angles between the two groups (P>0.05). (2) Compared to the control group,the observation group showed shorter surgical time,reduced blood loss,and significant increases in knee joint Hospital for Special Surgery knee scores at 3 months postoperatively compared to preoperative scores (P>0.05). Additionally,the postoperative Hospital for Special Surgery knee scores were higher in the observation group than in the control group (P>0.05). (3) The differences in tibial slope,femoral alignment,knee joint line angle,and hip-knee-ankle angle compared to standard angles were significantly different between the two groups;the observation group was better than the control group (P<0.05). (4) The accuracy of predicting femoral implant size was 94％ in the observation group and 58％ in the control group,while the accuracy of predicting tibial implant size was 96％ in the observation group and 62％ in the control group. (5) It is indicated that digital precision total knee arthroplasty results in shorter surgical time,reduced blood loss,and better postoperative knee joint function scores and alignment compared to traditional total knee arthroplasty. It demonstrates favorable clinical outcomes.

Objective:To analyze the endoscopic and clinicopathological characteristics of Helicobacter pylori ( HP)-negative early gastric cancer (EGC). Methods:A retrospective study was conducted on data of patients who were diagnosed as having EGC at the Affiliated Hospital of Qingdao University between June 2013 and March 2024. Cases meeting the diagnostic criteria for HP-negative status were included. Endoscopic findings and histopathological features of HP-negative EGC were systematically analyzed. Results:Among 698 EGC patients, 29 (4.2%) were identified as HP-negative. The age at diagnosis was 59.9±10.0 years, with marked female predominance (69.0%, 20/29 VS 31.0% males, 9/29). A body mass index ≥24 kg/m 2 was observed in 69.0% (20/29). Regarding therapeutic approaches, endoscopic submucosal dissection was performed in 89.7% (26/29). Among the 29 patients with a total of 30 lesions, the majority were localized to the middle third of the stomach (40.0%, 12/30), or the upper third (36.7%, 11/30). Differentiated-type accounted for 73.3% (22/30) among the histological types, including 13 oxyntic gland adenoma (OGA) / gastric adenocarcinoma of fundic-gland type (GA-FG) (upper third: 7; middle third: 6), and 2 gastric adenocarcinomas of fundic-gland mucosa type (GA-FGM) (both upper third). White-light endoscopy revealed polypoid or small submucosal tumor-like protrusions with whitish or erythematous discoloration and characteristic branching dilated vessels on the surface. Among the OGA/GA-FG lesions, 8 exhibited indistinct demarcation lines (DL). Additionally, both GA-FGM lesions demonstrated poorly defined DL. Three gastric adenocarcinomas of foveolar-type (GA-FV) were identified (upper/middle/lower third: 1 each), with 2 presenting as erythematous elevated masses. Five signet ring cell carcinomas (upper/middle/lower third: 1/3/1) exhibited flat or shallow depressed morphology with whitish or erythematous discoloration under white-light endoscopy; 3 exhibited well-demarcated borders. Four pyloric gland adenocarcinomas and three poorly differentiated tubular adenocarcinomas showed no significant differences in endoscopic features on white-light and narrow-band imaging compared to HP-positive EGC. No intestinal-type adenocarcinomas were identified. Conclusion:HP-negative EGC exhibit distinct endoscopic and clinicopathological characteristics, including female predominance and frequent differentiated histology, and upper/middle-third localization of elevated lesions, primarily OGA/GA-FG.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Endometriosis is an estrogen-dependent chronic inflammatory disease that affects 5%to 10%of women of reproductive age worldwide.Its typical symptoms include dysmenorrhea,infertility,and chronic pelvic pain,which seriously affect quality of life.The tradi-tional diagnostic methods include ultrasonography,magnetic resonance imaging,and laparoscopy.Among these,laparoscopy is considered the gold standard for diagnosis.However,its invasive nature limits its widespread application.Recently,artificial intelligence has rapidly advanced in the diagnosis of endometriosis,significantly improving the accuracy and efficiency of early diagnosis by integrating imaging,clinical data,and biomarkers.This article summarizes the limitations of traditional diagnostic methods for endometriosis and the advance-ments in the application of artificial intelligence in the diagnosis of endometriosis,while exploring the potential of artificial intelligence using practical case studies.

Objective:This study analyzes the clinicopathological features and prognostic factors of early-stage gastric mixed adenoneuroendocrine carcinoma (G-MANEC), which is an exceedingly rare malignancy, in an effort to provide evidence-based insights for clinical decision-making.Methods:A retrospective observational study was conducted using the clinical data of 36 patients with early-stage G-MANEC who underwent surgical resection at Zhongshan Hospital, Fudan University, from July 2014 to May 2022. The observed indicators included clinicopathological data and follow-up information on recurrence, metastasis, and overall survival (OS).Results:Among the 36 patients there were 21 males and 15 females, aged 32-84 (65±11) years. The most common initial symptoms were abdominal pain and distension (19/36, 52.8%), followed by incidental findings during physical examinations (7/36, 19.4%). Tumors were located in the proximal stomach in 13 cases (36.1%), the middle stomach in 4 cases (11.1%), and the distal stomach in 19 cases (52.8%). Average tumor diameter was (2.48±1.18) cm. Gross morphology included elevated type in 12 cases (33.3%), flat type in 20 cases (55.6%), and depressed type in 4 cases (11.1%). Ulceration was present in 12 cases (33.3%). There were 11 cases (30.6%) at T1a stage and 25 cases (69.4%) at T1b stage. Lymph node metastasis was positive in 10 cases (27.8%), and the differentiation grades of the adenocarcinoma component were Grade I, II, and III in 3 (8.3%), 10 (27.8%), and 23 (63.9%) cases, respectively. Furthermore, the proportion of neuroendocrine carcinoma component was ≥50% in 18 cases (50.0%) and <50% in 18 cases (50.0%). Lymphovascular or perineural invasion was present in 18 cases (50.0%). Lauren classification included mixed type in 10 cases (27.8%), intestinal type in 19 cases (52.8%), and diffuse type in 7 cases (19.4%), and chromogranin A (CgA) positivity was found in 20 cases (55.6%). Additionally, the Ki-67 index positivity was found in 26 cases (72.2%). Total gastrectomy was performed in 12 cases (33.3%) and partial gastrectomy in 24 cases (66.7%), with a median follow-up duration of 77.5 months. The 3-year and 5-year OS rates were 88.89% and 79.67%, respectively. Univariate analysis revealed that age, gross morphology, ulceration, proportion of neuroendocrine carcinoma component, lymphovascular or perineural invasion, and chromogranin A (CgA) positivity showed statistical significance in their association with OS ( P<0.10). Multivariate Cox regression analysis further identified ulceration (HR=7.74, 95%CI: 1.24-48.30, P=0.028) and CgA positivity (HR=21.76, 95%CI: 1.86-53.97, P=0.014) as independent risk factors of OS. Conclusions:Patients with early-stage G-MANEC are typically asymptomatic, and those with ulceration or positive CgA immunohistochemical staining tend to have a poor prognosis.