OBJECTIVE To investigate the effect of pharmaceutical services guided by root cause analysis （RCA） in a problem-oriented manner combined with knowledge-attitude-practice （KAP） theory on reducing the incidence of protocol violations of investigational medicinal products in pediatric clinical trials. METHODS A total of 617 participants from 69 drug clinical trial projects conducted in our hospital from January 2016 to December 2020 were selected as the control group， and 868 participants from 72 drug clinical trial projects from January 2022 to December 2025 as the observation group. RCA was performed on the protocol violations of investigational medicinal product in the control group to identify the types and underlying causes. The control group received routine pharmaceutical services for drug clinical trials， while the observation group was provided with precision pharmaceutical services from the three dimensions of knowledge， attitude and practice on the basis of routine pharmaceutical services， according to the root causes identified by RCA. The occurrence of investigational medicinal products protocol violations was compared between the two groups. RESULTS The total incidence of protocol violations of investigational medicinal products， as well as the incidences of minor and major protocol violations， were all significantly lower in the observation group than in the control group （ P ＜0.001）. The main types of protocol violations in both groups included missed/under-/over-dosing of medications， non-adherence to administration time， failure to adjust dosage as required， and combined medication/vaccination in violation of the protocol. Regarding the responsible subjects of protocol violations， the incidences of protocol violations attributed to participants and their guardians as well as investigators and accidental factors were significantly lower in the observation group than in the control group （ P ＜0.001， P ＜0.001， P ＝0.025）. However， there were no statistically significant differences in the incidences of protocol violations caused by sponsor-related reasons between the two groups （ P ＞0.05）. CONCLUSIONS Pharmaceutical services led by pharmacists， based on problem-oriented RCA and combined with KAP theory， can effectively reduce the protocol violations of investigational medicinal products rate in pediatric clinical trials， thereby safeguarding the safety and rights of study participants.

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.

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.

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.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

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.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

From the theoretical perspective of "body fluids and blood stasis mixing"， environmental microplastics （MPs） are conceptualized as a "novel turbid-toxin". This study aims to elucidate the complete pathogenic pathway through which MPs act as a key driving force （the "crucible" of pathogenesis） in the initiation and progression of atherosclerosis （AS）. By tracing the classical theories in the Chapter The Occurrence of All Diseases of Miraculous Pivot （Ling Shu）， this paper clarifies the core connotations of "body fluids"-it not only refers to endogenous pathological fluids and lipid turbidity but also provides a theoretical basis for incorporating "exogenous turbid fluids"， thereby laying a logical foundation for conceptualizing MPs as a "novel turbid-toxin". Meanwhile， the implications of "blood" （encompassing both blood quality abnormalities and blood stasis） and the dynamic process of "mixing" are elucidated. Drawing upon modern toxicological evidence， this paper demonstrates the high homology between MPs and "exogenous turbid-fluids" from three aspects： Morphology， toxicity， and invasion routes. The micro/nano-scale particle morphology of MPs enables mobility within the bloodstream. The multiple exposure pathways of MPs correspond to the traditional Chinese medicine understanding of pathogens invading through the mouth， nose， and skin. The characteristics of accumulating in vivo while inducing oxidative stress and inflammatory responses of MPs fully embody the pathogenic features-adhesion， binding， and vessel damage-of "turbid-toxin". On this basis， the dynamic pathogenesis of MP-induced AS is systematically interpreted. Initially， MPs with the "turbid-toxin" nature impair nutrient-defense harmony and cause endothelial dysfunction. Subsequently， as the core of "mixing"， they interact with blood lipids and immune cells， generating heat and phlegm to form a major pathological hub of chronic inflammation. Ultimately， this process drives the coalescence of phlegm， stasis， and turbid-toxin into tangible plaques， evolving from stable lesions to vulnerable masses and accumulations. By integrating classical pathogenic model with contemporary environmental medicine， this study establishes an analytical framework that bridges macro-theory and micro-mechanisms for understanding the cardiovascular risks of MPs through an integrative Chinese-Western medicine lens.

ObjectiveTo systematically analyze the epidemiological characteristics and cause-of-death distribution among death cases with hepatitis C in Hongkou District of Shanghai, and to provide a scientific basis for optimizing healthcare resources allocation and targeted hepatitis C prevention and control measures. MethodsA retrospective cross-sectional study was conducted by integrating historical surveillance data from China Information System of Disease Prevention and Control and Shanghai Hongkou District Death Medical Registration System. Data on demographic characteristics, hepatitis C-related clinical and management records, and underlying causes of death for cases with hepatitis C between 2012 and 2024 in Hongkou District of Shanghai, were collected. Descriptive analyses were performed to analyze the epidemiological characteristics and cause-of-death distribution of death cases, and comparative analyses were conducted across different subgroups. ResultsA total of 204 hepatitis C-related deaths were identified in Hongkou District, Shanghai, from 2012 to 2024. The average age at death was (69.49±12.75) years The majority decedents were males (71.57%) and retired (73.53%). The top three underlying causes of death were malignant tumors (45.10%), cerebrovascular diseases (15.20%) and cardiovascular diseases (12.25%), collectively accounting for 72.55% of all deaths. Deaths attributed to hepatitis C accounted for 9.80% (20/204), with a mean age at death of (63.41±11.81) years. No statistically significant differences were observed in the proportion of hepatitis C-attributed deaths across different subgroups (all P>0.05). The proportion of premature deaths was 55.88% (114/204), with a mean age at death of (60.02±6.89) years. The proportion of premature deaths was higher among males (60.27%), laboratory-diagnosed patients (62.69%), patients with other liver diseases (72.06%), and those non-compliant with follow-up (70.97%) compared to their respective counterparts (all P<0.05). Additionally, homemakers /unemployed patients (100.00%) and employed patients (88.89%) had a significantly higher proportion of premature deaths compared to retired patients (42.67%) (P<0.001). There was a statistically significant difference in the distribution of causes of death between the premature death group and the non-premature death group (χ²=14.93， P=0.048). The top three causes of premature deaths were malignant tumors (50.00%), hepatitis C (12.28%) and cerebrovascular diseases (10.53%). Regarding the proportion of deaths occuring prematurely, other viral hepatitis had the highest percentage (75.00%), followed by diabetes mellitus (71.43%) and hepatitis C (70.00%). ConclusionThe majority of death cases with hepatitis C were males and retirees in Hongkou District, Shanghai. The leading cause of death was malignant tumors, while hepatitis C ranked as the fourth underlying cause, as well as served as the second leading cause of premature death following malignant tumors. Premature death was closely associated with gender, occupation, diagnostic classification, presence of other liver diseases, and follow-up compliance, highlighting the importance of enhanced health management and targeted interventions among high-risk groups.