Objective To analyze the characteristics of viral hepatitis mortality and life loss among residents in Pudong New Area from 2003 to 2023, and to provide a basis for related prevention and control work. Methods Viral hepatitis mortality data were obtained from the Pudong New Area mortality monitoring system. The crude mortality rate (CMR), standardized mortality rate (SMR), potential years of life lost (PYLL), average years of life lost (AYLL), and standardized potential years of life lost (SPYLL) were calculated to analyze viral hepatitis deaths. The average annual change (AAPC) and annual percentage change (APC) of the mortality rate were calculated by Joinpoint regression analysis to analyze the trend of mortality. Results The CMR and SMR of viral hepatitis among residents in Pudong New Area from 2003 to 2023 were 3.89/100000 and 1.98/100000, respectively. Both CMR and SMR of viral hepatitis showed a decreasing trend over time (CMR:APC=-5.476, t=-13.581, P<0.001; SMR:APC=- 7.624, t= -21.253, P<0.001). The CMR for males was 4.75/100000 and the SMR for males was 2.65/100000; the CMR for females was 3.04/100000 and the SMR for females was 1.32/100000, with a higher mortality rate for males than for females（Z_CME=12.094，P<0.001; Z_SMR=-14.718，P<0.001). Deaths were concentrated in the age groups of 45-64 years old and 65 years old and above, accounting for 91.62% of the total deaths. The PYLL of deaths due to viral hepatitis among residents in Pudong New Area from 2003 to 2023 was 26912 person-years, with a PYLLR of 0.45% and an AYLL of 8.88 years per person. Conclusion The mortality rate of viral hepatitis among the residents of Pudong New Area in 2003-2023 shows a decreasing trend over time. The mortality rate of males is higher than that of females, and the deaths of middle-aged and elderly people account for a large proportion of the total deaths. Chronic hepatitis B is the main cause of death.

ObjectiveThis paper aims to investigate the traditional Chinese medicine syndrome types in patients with chronic hepatitis B （CHB） complicated by metabolic dysfunction-associated fatty liver disease （MAFLD） and explore the correlations between these syndrome types and clinical indicators， as well as ocular manifestation characteristics， thereby providing a reference for syndrome differentiation and treatment strategies in traditional Chinese medicine. MethodsGeneral data， information from the four diagnostic methods of traditional Chinese medicine， clinical indicators， and ocular manifestation data were collected from 506 patients with CHB complicated by MAFLD enrolled at the Public Health Clinical Center of Chengdu between June 2024 and December 2024. Cluster analysis， principal component analysis， and complex network models were employed to identify the distribution patterns of traditional Chinese medicine syndromes. Correlations between different syndrome types and clinical indicators， as well as ocular manifestation characteristics， were further analyzed. ResultsThe predominant syndromes identified in patients with CHB complicated by MAFLD were dampness and heat accumulation （51.58%）， liver depression with spleen deficiency （31.62%）， blood stasis obstructing collaterals （8.89%）， and Qi-Yin deficiency （7.91%）. No statistically significant differences were found among the four syndrome types in routine blood tests and liver function indicators. However， patients with the dampness and heat accumulation type exhibited significantly higher levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， liver stiffness measurement （LSM）， controlled attenuation parameter （CAP）， and alpha-fetoprotein （AFP）， along with lower levels of high-density lipoprotein cholesterol （HDL-C）， compared with those with other syndrome types. Regarding ocular manifestations， the incidence of moon halo signs was significantly higher in patients with the blood stasis obstructing collaterals type than in those with other syndrome types. Additionally， the incidence in scleral zone 3 （corresponding to the large intestine） was higher in patients with the damp and heat accumulation type. ConclusionDampness and heat accumulation is the core syndrome type in patients with CHB complicated by MAFLD， commonly accompanied by spleen deficiency， liver depression， blood stasis， and Yin deficiency. A complex syndrome pattern characterized by a predominance of dampness and heat， along with a mixture of deficiency and excess， is formed. Different traditional Chinese medicine syndrome types are associated with distinct clinical indicators and ocular manifestation characteristics. Among them， patients with the dampness and heat accumulation type exhibit more pronounced metabolic disturbances and liver injury， whereas those with the blood stasis type show a higher incidence of moon halo signs. Abnormalities in scleral zone 3 are also more prevalent in patients with dampness and heat type.

The digitization of traditional Chinese medicine (TCM) has generated vast amounts of data. However, these data are characterized by significant heterogeneity and complex semantic structures, posing substantial challenges for systematic integration and intelligent analysis, and limiting its potential for modern clinical and computational research. To address the challenges posed by the high heterogeneity and complex structure in TCM data, we designed and developed the TCM Data Hub platform, which is powered by the YiYuan large language models (LLMs). This platform aims to enhance intelligent data processing capabilities and unlock the potential for clinical application of TCM data through systematic integration and efficient utilization, thereby bridging the gap between traditional knowledge and modern computational research. This study first analyzed the heterogeneity and complexity of TCM information with respect to data types, structures, and semantics. A standardized data framework was constructed to enhance data integration and interoperability. Based on the TCM Intelligent Computing Platform of the China Academy of Chinese Medical Sciences, we trained the YiYuan LLMs to acquire domain-specific semantic understanding of TCM, thereby improving the platform’s comprehension of specialized terminology and knowledge systems. Leveraging the natural language processing capabilities of the LLMs, we developed a human-in-the-loop data processing system to enable efficient extraction, cleansing, and structured organization of TCM data. In addition, utilizing Vue and Java technologies, we developed multiple LLM-powered intelligent agents and systems, including a human-in-the-loop data processing system, as well as automated prescription mining and network pharmacology analysis agents. Task-specific agents tailored to TCM data processing were developed to enhance the model’s effectiveness in clinical knowledge discovery. System functionality and platform infrastructure were implemented using Java and Vue technologies.The TCM Data Hub platform has completed system construction and core functionality implementation. It supported integrated management and efficient access to 8 key types of TCM data: prescriptions, materia medica, ingredients, targets, diseases (Western medicine), diseases (TCM), syndromes, and therapeutic methods. The human-in-the-loop data processing system achieved an accuracy of 95.34% in structuring TCM data and supported annotation for data requiring manual labeling. The intelligent agent-driven big-data analytics module enabled 1-click, end-to-end workflows for TCM prescription mining, herb-syndrome association analysis, network pharmacology, and molecular biology research, completing a full data mining task in approximately 30 minutes. Users can interact with and manipulate data through a visual front-end interface. The system demonstrated stable performance, strong scalability, and a user-friendly experience. Empowered by the YiYuan LLMs, the TCM Data Hub platform significantly improves the accessibility, usability, and intelligence of TCM data. It effectively bridges traditional TCM knowledge with modern intelligent technologies, providing robust data support and intelligent tools for TCM research and clinical applications.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

OBJECTIVE: To evaluate the effect of palliative care on drug use, medical service utilization and medical expenditure of patients with advanced cancer. METHODS: A cohort of patients including pal-liative care and standard care was constructed using the medical records of the patients in Peking University Cancer Hospital from 2018 to 2020, and coarsened exact matching was used to match the two groups of patients. The average monthly opioid consumption, hospitalization rate, intensive care unit (ICU) rate and operation rate, and the average monthly total cost were selected to evaluate drug use, medical service utilization and medical expenditure. Chi-square test and Wilcoxon signed rank test were used to compare the differences between the two groups before and after exposure and the change in the palliative care group. The net impact of palliative care on the patients was calculated using the difference-in-differences analysis. RESULTS: In this study, 180 patients in the palliative care group and 3 101 patients in the stan-dard care group were finally included in the matching, and the matching effect of the two groups was good (L₁ < 0.1). Before and after exposure, the average monthly opioid consumption in the palliative care group was significantly higher than that in the standard care group (Before exposure: 0.3 DDD/person-month vs. 0.1 DDD/person-month, P < 0.01; After exposure: 0.7 DDD/person-month vs. 0.1 DDD/person-month, P < 0.01; DDD refers to defined daily dose), palliative care significantly increased the average monthly opioid consumption in the patients (0.3 DDD/person-month, P < 0.01). The hospitalization rate (48.9% vs. 74.3%, P < 0.01) and operation rate (3.9% vs. 8.8%, P < 0.01) of the patients in palliative care group were significantly lower than those in standard care group, and the ICU rate became similar between the two groups (1.1% vs. 1.6%, P=0.634). Palliative care significantly reduced the patients ' hospitalization rate (-25.6%, P < 0.01), ICU rate (-4.9%, P < 0.01) and operation rate (-14.5%, P < 0.01). Before and after exposure, the average monthly total costs of pal-liative care group were slightly higher than those of standard care group (Before exposure: 20 092.3 yuan vs. 19 132.8 yuan, P=0.725; After exposure: 9 719.8 yuan vs. 8 818.8 yuan, P=0.165). Palliative care increased the average monthly total cost by 2 208.8 yuan, but it was not statistically significant (P=0.316). CONCLUSION Palliative care can increase the opioid consumption in advanced cancer patients, reduce the rates of hospitalization, ICU and surgery, but has no significant effect on medical expenditure.
Humans ; Palliative Care/economics* ; Neoplasms/drug therapy* ; Analgesics, Opioid/economics* ; Male ; Female ; Middle Aged ; Aged ; Hospitalization/economics* ; Intensive Care Units/statistics & numerical data* ; Health Expenditures/statistics & numerical data* ; Adult ; Drug Utilization/statistics & numerical data* ; Patient Acceptance of Health Care/statistics & numerical data*

Gut microbial communities are likely remodeled in tandem with accumulated physiological decline during aging, yet there is limited understanding of gut microbiome variation in advanced age. Here, we performed a metagenomics-based enterotype analysis in a geographically homogeneous cohort of 367 enrolled Chinese individuals between the ages of 60 and 94 years, with the goal of characterizing the gut microbiome of elderly individuals and identifying factors linked to enterotype variations. In addition to two adult-like enterotypes dominated by Bacteroides (ET-Bacteroides) and Prevotella (ET-Prevotella), we identified a novel enterotype dominated by Escherichia (ET-Escherichia), whose prevalence increased in advanced age. Our data demonstrated that age explained more of the variance in the gut microbiome than previously identified factors such as type 2 diabetes mellitus (T2DM) or diet. We characterized the distinct taxonomic and functional profiles of ET-Escherichia, and found the strongest cohesion and highest robustness of the microbial co-occurrence network in this enterotype, as well as the lowest species diversity. In addition, we carried out a series of correlation analyses and co-abundance network analyses, which showed that several factors were likely linked to the overabundance of Escherichia members, including advanced age, vegetable intake, and fruit intake. Overall, our data revealed an enterotype variation characterized by Escherichia enrichment in the elderly population. Considering the different age distribution of each enterotype, these findings provide new insights into the changes that occur in the gut microbiome with age and highlight the importance of microbiome-based stratification of elderly individuals.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Bacteroides ; China ; Diabetes Mellitus, Type 2/microbiology* ; Escherichia coli/classification* ; Gastrointestinal Microbiome/genetics* ; Metagenomics ; East Asian People

Natural products (NPs) have historically been a fundamental source for drug discovery. Yet the complex nature of NPs presents substantial challenges in pinpointing bioactive constituents, and corresponding targets. In the present study, an innovative natural product virtual screening-interaction-phenotype (NP-VIP) strategy that integrates virtual screening, chemical proteomics, and metabolomics to identify and validate the bioactive targets of NPs. This approach reduces false positive results and enhances the efficiency of target identification. Salvia miltiorrhiza (SM), a herb with recognized therapeutic potential against ischemic stroke (IS), was used to illustrate the workflow. Utilizing virtual screening, chemical proteomics, and metabolomics, potential therapeutic targets for SM in the IS treatment were identified, totaling 29, 100, and 78, respectively. Further analysis via the NP-VIP strategy highlighted five high-confidence targets, including poly [ADP-ribose] polymerase 1 (PARP1), signal transducer and activator of transcription 3 (STAT3), amyloid precursor protein (APP), glutamate-ammonia ligase (GLUL), and glutamate decarboxylase 67 (GAD67). These targets were subsequently validated and found to play critical roles in the neuroprotective effects of SM. The study not only underscores the importance of SM in treating IS but also sets a precedent for NP research, proposing a comprehensive approach that could be adapted for broader pharmacological explorations.

Objective:To prepare pullulan-spermine (PS)-poly (lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) conjugated with CD3 antibody, and to investigate their effects on T cell proliferation and cytokine secretion.Methods:Purulan polysaccharide was sperminized to synthesize PS, hydrophobically modified, and then grafted with PLGA to synthesize PS-PLGA. Infrared spectroscopy and nuclear magnetic resonance hydrogen spectrum were used to characterize the structure of PS-PLGA. PS-PLGA NPs were prepared by ultrasonic dialysis method and then coupled with CD3 antibody to prepare PS-PLGA-CD3 NPs. The morphological features of PS-PLGA-CD3 NPs were observed by the transmission electron microscope. The particle sizes, Zeta potential and dispersive coefficient of the NPs were measured using the dynamic laser particle size analyzer. The amount of coupled CD3 antibody on the surface of the NPs was determined using quantitative fluorescence analysis method. The effects of 1, 10, 50, 100, and 200 μg/ml PS-PLGA-CD3 NPs on T-cell proliferation were determined using cell counting kit-8 method. The effects of 1, 10, 50, 100, 200 μg/ml PS-PLGA-CD3 NPs on secretion of interferon-γ (IFN-γ), interleukin-2 (IL-2), and tumor necrosis factor-β (TNF-β) by T cell were determined by enzyme-linked immunosorbent assay. Comparisons were made using independent sample t-test or one-factor analysis of variance. Results:Pullulan and PS showed strong absorption at 2 939 cm ?1, and PS had a weaker absorption peak at 3 384 cm ?1 than pullulan. The proton peaks of spermine appeared at chemical shifts of 1.25 to 1.50, 1.63, and 2.25 to 2.75. The characteristic peaks of PLGA appeared at chemical shifts of 1.50, 3.40, and 4.80 to 5.30. Compared to pullulan, the characteristic peaks of both PS and PLGA appeared in the corresponding intervals for PS-PLGA. The morphology of PS-PLGA-CD3 NPs with spermine substitution at 9.7% was all regular and circular, with a mean particle size of (173.3±24.5) nm, a Zeta potential of (?12.78±3.68) mV, the dispersive coefficient of 0.254±0.101, and the CD3 antibody mass fraction of (52.1±9.4) μg/mg. The differences in cell survival were statistically significant for PS-PLGA-CD3 NPs and PS-PLGA NPs, respectively, after co-incubation with T cell after 24, 48, and 72 h at concentrations of 50, 100, and 200 μg/ml, respectively (all P<0.05). The results of the three concentration comparisons after 24 h of co-incubation were [(129.8±23.1)% vs (95.5±8.9)%, (137.5±22.7)% vs (95.1±15.8)%, and (142.3±25.6)% vs (93.2±9.2)%]; and the results after 48 h were [(145.9±23.7)% vs (95.8±10.6)%, (149.3±23.5)% vs (94.9±16.3)%, and (161.2±26.9)% vs (91.5±8.3)%]; and the results after 72 h were [(147.6±20.1)% vs (95.9±17.8)%, (152.4±22.3)% vs (92.7±16.5)%, and (167.7±25.4)% vs (90.8±17.4)%]. The differences in the levels of IFN-γ, IL-2 and TNF-β were statistically significant (all P<0.05 or 0.01) at 50, 100 and 200 μg/ml concentrations for PS-PLGA-CD3 NPs and PS-PLGA NPs, respectively. For IFN-γ, the results of the comparison of the three concentrations were [(35.7±3.1) ng/ml vs (16.4±6.9) ng/ml, (67.3±5.2) ng/ml vs (19.6±2.8) ng/ml, and (79.0±4.2) ng/ml vs (19.3±2.3) ng/ml]; and for IL-2, the results were [(43.5±8.2) ng/ml vs (12.6±1.9) ng/ml, (53.5±7.8) ng/ml vs (15.8±3.3) ng/ml, and (64.0±8.2) ng/ml vs (17.4±3.8) ng/ml]; and for TNF-β, the results were [(108.4±18.9) pg/ml vs (40.8±1.3) pg/ml, (152.3±28.3) pg/ml vs (56.4±3.7) pg/ml and (185.0±33.6) pg/ml vs (81.6±10.2) pg/ml]. Conclusions:PS-PLGA-CD3 NPs are successfully prepared, which have the function of effectively promoting T cell proliferation and cytokine sectetion.