Aim To explore the possible mechanism of "component-target-pathway" of Radix Hedysari against target organ damage caused by radiotherapy and chemotherapy, and to verify the " dose-effect" relationship of the main active components. Methods TCMSP, Uniprot, Swiss Target Prediction, GeneCards, Cytoscape, Omicshare and other platforms were used for network pharmacology analysis. Autodock, Pymol and Ligplot were used for molecular docking. The water extract of Radix Hedysari was used for animal experiment verification. The contents of eight main components were determined by HPLC. Results Four active components, eight key targets and four key pathways of Radix Hedysari were identified to resist the damage of target organs caused by radiotherapy and chemotherapy. Molecular docking showed that formononetin and quercetin had good binding activity with HSP90AA1, naringenin and MAPK3, and ursolic acid and TP53. Animal experiments showed that gastrointestinal factors MTL and VIP increased significantly, liver and kidney factors Cr, BUN, AST and ALT decreased significantly, inflammatory factor IL-10 increased significantly and TNF-a decreased significantly. The content of ononm was the highest (2 . 884 8 µg • g "

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective:To study the longitudinal trends and spatial clustering characteristics of healthcare service efficiency in China and in North,Northeast,East,Central,South,Southwest,and Northwest China.Methods:The Malmquist index model is used to measure China's healthcare service efficiency from 2012 to 2021,the Dagum Gini coefficient as well as the decomposition method are used to measure the magnitude and source of regional gaps in healthcare service efficiency,and the Kernel density estimation is used to study the longitudinal trend of change and spatial agglomeration characteristics of China's healthcare service efficiency.Results:China's overall healthcare service efficiency is growing,and the inter-regional gap is gradually narrowing,characterized by a concentration trend;the gap in the level of healthcare service efficiency between regions did not widen during the period under examination,but it was found that the gap within some regions was still significant.Conclusion:The national health service efficiency is growing slightly,and the regional gap is generally decreasing,but the Gini coefficient shows that the inter-regional contribution is still the main source of the gap.National health service efficiency is generally concentrated,but some regions are less efficient,with significant internal disparities.

Objective: To explore the efficacy of chemotherapy re-challenge in the third-line setting for patients with metastatic colorectal cancer (mCRC) in the real world. Methods: The clinicopathological data, treatment information, recent treatment efficacy, adverse events and survival data of mCRC patients who had disease progression after treatment with oxaliplatin-based and/or irinotecan-based chemotherapy and received third-line chemotherapy re-challenge from January 2013 to December 2020 at Tianjin Medical University Cancer Institute and Hospital were retrospectively collected. Survival curves were plotted with the Kaplan-Meier method, and the Cox proportional hazard model was used to analyze the prognostic factors. Results: A total of 95 mCRC patients were included. Among them, 32 patients (33.7%) received chemotherapy alone and 63 patients (66.3%) received chemotherapy combined with targeted drugs. Eighty-three patients were treated with dual-drug chemotherapy (87.4%), including oxaliplatin re-challenge in 35 patients and irinotecan re-challenge in 48 patients. The remaining 12 patients were treated with triplet chemotherapy regimens (12.6%). Among them, as 5 patients had sequential application of oxaliplatin and irinotecan in front-line treatments, their third-line therapy re-challenged both oxaliplatin and irinotecan; 7 patients only had oxaliplatin prescription before, and these patients re-challenged oxaliplatin in the third-line treatment. The overall response rate (ORR) and disease control rate (DCR) reached 8.6% (8/93) and 61.3% (57/93), respectively. The median progression free survival (mPFS) and median overall survival (mOS) were 4.9 months and 13.0 months, respectively. The most common adverse events were leukopenia (34.7%) and neutropenia (34.7%), followed by gastrointestinal adverse reactions such as nausea (32.6%) and vomiting (31.6%). Grade 3-4 adverse events were mostly hematological toxicity. Cox multivariate analysis showed that gender (HR=1.609, 95% CI: 1.016-2.548) and the PFS of front-line treatments (HR=0.598, 95% CI: 0.378-0.947) were independent prognostic factors. Conclusion: The results suggested that it is safe and effective for mCRC patients to choose third-line chemotherapy re-challenge, especially for patients with a PFS of more than one year in front-line treatments.
Humans ; Irinotecan/therapeutic use* ; Oxaliplatin/therapeutic use* ; Colorectal Neoplasms/pathology* ; Retrospective Studies ; Fluorouracil ; Colonic Neoplasms/chemically induced* ; Rectal Neoplasms/drug therapy* ; Antineoplastic Combined Chemotherapy Protocols/adverse effects* ; Camptothecin/adverse effects*