Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To investigate the clinical efficacy of pancreatic cancer surgery with arterial resection.Methods:The clinicopathological and follow-up data of 135 patients undergoing pancreatectomies with arterial resection in Pancreas Center, the First Affiliated Hospital of Nanjing Medical University from Sep 2013 to Dec 2023 were retrospectively analyzed.Results:There were 77 males and 58 females, with age [ M( IQR)] of 63 (14) years old. Among the 135 patients, 122 (90.4%) were distal pancreatectomies, 8 (5.9%) were pancreaticoduodenectomies, 4 (3.0%) were total pancreatectomies and 1 (0.7%) was resection for local recurrence after distal pancreatectomy. There were 120 (88.9%) celiac axis resections, 11 (8.1%) hepatic artery resections, 1 (0.7%) superior mesenteric artery resection and 3 (2.2%) other artery resections. Simultaneous portal vein-superior mesenteric vein or organ resection accounted for 26.7% (36/135) and 29.6% (40/135),respectively. The median blood loss was 300 (300) ml and the median operation time was 275 (105) minutes. The 90-day mortality rate was 7.4% (10/135). The overall morbidity rate was 70.4% (95/135) while the major morbidity rate was 18.5% (25/135). Postoperative hemorrhage occurred in 8.9% (12/135), clinically relevant postoperative pancreatic fistula in 57.0% (77/135), bile leak in 0.74% (1/135), delayed gastric emptying in 9.6% (13/135), liver failure in 3.7% (5/135) and transient liver enzyme elevation in 44.4% (60/135). All of the 135 cases were confirmed as pancreatic cancer histologically, including 54.6% (71/130) moderately differentiated, 45.4% (59/130) poorly differentiated and no for well differentiated. The median tumor size was 4.5 (2.3) cm. The median number of harvested lymph nodes was 14 (13) and the percentage of N0, N1 and N2 according to AJCC 8th staging system was 27.1% (36/133), 52.6% (70/133) and 20.3% (27/133), respectively. The R 0 resection was achieved in 40 of 123 cases (32.5%), whose margins of specimens were assessed circumferentially based on the 1mm rule. The median overall survival time (MST) after surgery was 22.5 months, and the median progress-free survival time was 16.1 months. The overall survival rate at 1-, 2- and 5-year was 71.5%, 45.1% and 11.3%, respectively. The MST of patients who received no adjuvant therapy, chemotherapy after surgery was 8.4 months, 25.3 months, respectively. Conclusions:Pancreatectomy with arterial resection is generally safe and feasible. Survival outcome improves significantly when combined with adjuvant chemotherapy.

Objective:To summarize the clinicopathological features, evolving trends in treatment and surgical approaches, and survival outcomes of patients who underwent D2 radical gastrectomy for gastric cancer in Shanxi Provincial Cancer Hospital over the past 11 years with the goal of providing a reference for the clinical practice of gastric cancer in this region.Methods:A retrospective observational study was conducted to analyze the clinicopathological data of patients who underwent D2 radical gastrectomy for pathologically confirmed gastric malignancy at the Department of Gastrointestinal Surgery, Shanxi Provincial Cancer Hospital from January, 2013 to December, 2023. Exclusion criteria consisted of: (1) residual gastric cancer or recurrent gastric cancer after surgery; (2) emergency gastric cancer resection due to bleeding, perforation, obstruction, or other causes; (3) comorbidity with other primary malignant tumors; (4) severe preoperative cardiopulmonary insufficiency or hepatic and renal insufficiency who cannot tolerate radical surgery; and (5) inconsistent main diagnosis information across the medical record system, pathological system, and gastric cancer-specific database. Patients were divided into three groups based on treatment methods: the surgery-only group, the perioperative chemotherapy group, and the adjuvant chemotherapy group. Endpoints included: (1) baseline patient characteristics; (2) trends in tumor location and pathological features; (3) evolution of treatment modalities; and (4) survival outcomes.Results:A total of 15,644 patients were included in the analysis, with 12,591 males and 3,053 females, the male-to-female gender ration was approximately 4∶1; the mean age was (61.2±9.5) years. The tumor sites were mainly concentrated in the esophagogastric junction (EGJ) (57.4%), followed by the antrum (25.9%). The incidence of EGJ cancer initially rose and then declined. However, gastric antrum tumors remained stable, and gastric body tumors showed a slow upward trend after 2020, accounting for 16.7%. In terms of pathological types, poorly differentiated carcinoma was the most prevalent, accounting for 55.9%, followed by moderately differentiated carcinoma (24.2%), mucinous adenocarcinoma (or signet ring cell carcinoma,14.1%), neuroendocrine carcinoma (4.8%), and well-differentiated carcinoma (0.9%). The proportion of poorly differentiated adenocarcinoma showed a significant upward trend overall as well, peaking at 65.6% in 2022 and decreasing to 57.5% in 2023. Mucinous adenocarcinoma (or signet ring cell carcinoma) exhibited fluctuations with a first increase followed by a decrease: it peaked at 17.3% in 2018, dropped sharply to 8.4% in 2022, and rose back to 13.8% in 2023. The proportions of well-differentiated adenocarcinoma, moderately differentiated adenocarcinoma, and neuroendocrine tumors remained stable year by year. In terms of pathological staging, the overall proportions of gastric cancer at Stage 0, Stage I, Stage II, Stage III, and Stage IVa were 0.5%, 17.3%, 25.1%, 54.9%, and 2.3%, respectively. For Stage III, its proportion was 74.6% in 2013, which decreased to 46.4% by 2023. Stages I and II gastric cancer showed an upward trend, with their proportions rising from 10.2% and 12.1% in 2013 to nearly 21.0% and 29.6% in 2023, respectively. Between 2013 and 2023, the proportion of patients who received surgery alone continued to decrease, with this proportion dropping to 34.7% in 2023. In contrast, the number of patients who received adjuvant chemotherapy increased year by year, reaching 54.2% in 2023. Since 2017, the application of perioperative chemotherapy has gradually increased, rising to 11.1% in 2023. Immunotherapy showed an almost synchronous growth trend with perioperative chemotherapy. However, targeted therapy exhibited a downward trend after a period of growth. There were 10,704 cases of open surgery (68.4%), 4,744 cases of laparoscopic surgery (30.3%), and 193 cases of transthoracic surgery (1.2%). Pathological margin positivity was observed in 443 cases (2.8%), and the volume of gastric cancer surgeries gradually increased, peaked in 2021 before subsequently decreasing gradually. However, the volume of laparoscopic surgeries did not decrease; instead, it showed an upward trend. The main resection method for EGJ tumors was total gastrectomy, accounting for 78.5% of the total, followed by proximal gastrectomy, which accounted for 21.5%. After total gastrectomy, esophagojejunal Roux-en-Y anastomosis was the primary anastomotic method, and for proximal gastrectomy, the main anastomotic method was esophagogastric anastomosis, which accounted for 68.0% of the total. For distal gastrectomy, Billroth II anastomosis was the most common anastomotic technique, accounting for 92.7% of these procedures. The overall incidence of postoperative complications was 14.5% (2,264/15,644), among which the incidence of severe complications (grades III-IV) was 4.5% (706/15,644). The entire cohort was followed up with for (47.1±36.8) months, and the 1-year, 3-year, and 5-year overall survival rates were 86.4%, 65.9%, and 58.1%, respectively. For patients with stage 0, I, II, III, and IV gastric adenocarcinoma, the 1-year overall survival rates were 95.7%, 98.0%, 89.4%, 81.0%, and 49.1%, respectively; the 3-year overall survival rates were 92.1%, 94.6%, 81.9%, 51.4%, and 14.7%, respectively; and the 5-year overall survival rates were 89.4%, 91.7%, 75.1%, 41.5%, and 10.0%, respectively. For patients with stage I, II, III, and IV gastric neuroendocrine carcinoma, the 1-year overall survival rates were 96.7%, 91.1%, 73.8%, and 52.6%, respectively; the 3-year overall survival rates were 87.2%, 69.6%, 46.1%, and 32.1%, respectively; and the 5-year overall survival rates were 87.2%, 62.2%, 36.7%, and 32.1%, respectively.Conclusions:Gastric cancer in Shanxi Province is characterized by a male predominance, a high prevalence of tumors at the esophagogastric junction, a large proportion of poorly differentiated adenocarcinoma, and presentation at advanced stages (predominantly Stage III). The detection rate of early gastric cancer has been increasing year by year, the volume of laparoscopic surgeries has been on the rise annually, and the treatment model has shifted from single surgery to comprehensive treatment.