OBJECTIVE To systematically evaluate the efficacy and safety of different chemotherapy combination regimens for first-line treatment of metastatic colorectal cancer （mCRC）. METHODS PubMed， Cochrane Library， Embase and Web of Science were electronically searched to collect randomized controlled clinical trial （RCT） on first-line treatment for mCRC from January 1， 2000 to February 16， 2025. Two reviewers independently screened literature， extracted data and assessed the risk of bias of the included studies. Network meta-analysis was performed by using R4.4.3 and Stata 17.0 software. RESULTS A total of 28 RCTs， involving 16 intervention measures， were included. In terms of prolonging progression-free survival （PFS） and overall survival （OS）， FOLFOX （5-fluorouracil+oxaliplatin+calcium folinate regimen）+cetuximab had the highest probability of ranking first. In terms of improving objective response rate （ORR）， FOLFOXIRI （5-fluorouracil+oxaliplatin+irinotecan+calcium folinate regimen）+ bevacizumab and FOLFOX+bevacizumab+nivolumab had the highest probability of ranking first； in terms of the incidence of grade 3 or higher adverse reactions， FOLFOXIRI+panitumumab had the highest probability of ranking first； in subgroup analysis of KRAS wild-type patients， FOLFIRI （5-fluorouracil+irinotecan+calcium folinate regimen）+panitumumab and FOLFIRI+bevacizumab had the highest probability of ranking first in terms of prolonging PFS and OS， respectively； in terms of ORR， FOLFOXIRI+ cetuximab had the highest probability of ranking first. CONCLUSIONS In first-line treatment for mCRC， FOLFOX combined with targeted therapy has advantages in terms of efficacy and safety. However， individualized treatment strategies should be formulated based on the KRAS gene status and tumor location of patients.

Background Existing studies have confirmed that fine particulate matter (PM_2.5)is one of the important factors inducing pulmonary fibrosis. Pulmonary fibrosis is the terminal stage of a major category of lung diseases characterized by the destruction of tissue structure, and eventually leading lung ventilation and ventilation dysfunction. No effective pulmonary fibrosis treatment is available yet. Objective To investigate the protective effect of salidroside on pulmonary fibrosis induced by the exposure of PM_2.5 and its molecular mechanism. Methods Seventy 7-week-old male C57BL/6 mice were randomly divided into four groups: control group (intratracheal instillation of normal saline + saline by gavage, n=25), Sal group (intratracheal instillation of normal saline + Sal 60 mg·kg⁻¹ by gavage, n=10), PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ + saline by gavage, n=10), and Sal + PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ +Sal 60 mg·kg⁻¹ by gavage, n=10). The mice were administered by gavage once daily, intratracheal instillation once every 3 d, and every 3 d constituted an experimental cycle. At the end of the 26-30th cycles, 3 mice in the control group and 3 mice in the PM_2.5 group were randomly sacrificed, and the lung tissues were collected for Masson staining to verify whether the pulmonary fibrosis model was successfully established. After 30 cycles, the model was successfully constructed. After 1 week of continuous observation, the mice were sacrificed, and the blood and lung tissues of the mice were collected to make lung tissue sections. Assay kits were correspondingly employed to detect oxidative stress indicators such as serum malondialdehyde (MDA) and superoxide dismutase (SOD). Western blotting was used to detect the expression of fibrosis-related proteins (Collagen-III, α-SMA), mitochondrial dynamics-related proteins (MFN1, Drp1), and mitophagy-related proteins (PINK1, Parkin, and LC3). Results Compared with the control group, the weight gain rate of the PM_2.5 group was slowed down (P<0.05), which was alleviated by the Sal intervention (P<0.05). The lung coefficient increased after the PM_2.5 exposure (P<0.05), which was alleviated by Sal intervention. Compared with the control group, the PM_2.5 group showed severe alveolar structure damage, inflammatory cell infiltration, and blue collagen deposition, and significantly increased the lung injury score, collagen volume fraction (CVF), Szapiel score, and Ashcroft score (P<0.05), as well as serum oxidative stress levels (P<0.05). The protein expression levels of Collagen-III, α-SMA, Drp1, PINK1, Parkin, and LC3 II/I were increased (P<0.05), and the expression of MFN1 was decreased (P<0.05). Compared with the PM_2.5 group, the Sal intervention alleviated lung injury, reduced inflammatory cell infiltration and collagen deposition, showing decreased lung injury score, CVF, Szapiel score, and Ashcroft score (P<0.05), and decreased serum oxidative stress levels (P<0.05); the protein expression levels of Collagen-III, α-SMA, PINK1, Parkin, and LC3 II/I were decreased (P<0.05), the expression level of Drp1 was decreased, and the expression level of MFN1 was increased. Conclusion In the process of pulmonary fibrosis induced by PM_2.5 exposure in mice, Sal may affect mitochondrial autophagy through PINK1/Parkin pathway and play a protective role. The specific mechanism needs to be further verified.

BACKGROUND: The role of inflammation in the development of gestational diabetes mellitus (GDM) has recently become a focus of research. The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), novel indices, reflect the body's chronic immune-inflammatory state. This study aimed to investigate the associations between the SII or SIRI and GDM. METHODS: A prospective birth cohort study was conducted at Beijing Obstetrics and Gynecology Hospital from February 2018 to December 2020, recruiting participants in their first trimester of pregnancy. Baseline SII and SIRI values were derived from routine clinical blood results, calculated as follows: SII = neutrophil (Neut) count × platelet (PLT) count/lymphocyte (Lymph) count, SIRI = Neut count × monocyte (Mono) count/Lymph count, with participants being grouped by quartiles of their SII or SIRI values. Participants were followed up for GDM with a 75-g, 2-h oral glucose tolerance test (OGTT) at 24-28 weeks of gestation using the glucose thresholds of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). Logistic regression was used to analyze the odds ratios (ORs) (95% confidence intervals [CIs]) for the the associations between SII, SIRI, and the risk of GDM. RESULTS: Among the 28,124 women included in the study, the average age was 31.8 ± 3.8 years, and 15.76% (4432/28,124) developed GDM. Higher SII and SIRI quartiles were correlated with increased GDM rates, with rates ranging from 12.26% (862/7031) in the lowest quartile to 20.10% (1413/7031) in the highest quartile for the SII ( Ptrend <0.001) and 11.92-19.31% for the SIRI ( Ptrend <0.001). The ORs (95% CIs) of the second, third, and fourth SII quartiles were 1.09 (0.98-1.21), 1.21 (1.09-1.34), and 1.39 (1.26-1.54), respectively. The SIRI findings paralleled the SII outcomes. For the second through fourth quartiles, the ORs (95% CIs) were 1.24 (1.12-1.38), 1.41 (1.27-1.57), and 1.64 (1.48-1.82), respectively. These associations were maintained in subgroup and sensitivity analyses. CONCLUSION The SII and SIRI are potential independent risk factors contributing to the onset of GDM.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/immunology* ; Prospective Studies ; Adult ; Inflammation/immunology* ; Glucose Tolerance Test ; Birth Cohort

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

This report describes two cases of severe immune-mediated thrombocytopenia after allogeneic hematopoietic stem cell transplantation (HSCT) who were treated with umbilical cord mesenchymal stem cells (UC-MSCs). Case 1 was a child with severe aplastic anemia who underwent haploidentical bone marrow and peripheral blood HSCT, with a chimerism rate of 99.8% on day +25 and severe immune-mediated thrombocytopenia on day +60. After intravenous immunoglobulin (IVIG) pulse therapy, platelet count increased temporarily but then decreased, while cyclosporine, methylprednisolone, and rituximab had a poor therapeutic effect. Case 2 was a child with Gaucher's disease who underwent unrelated umbilical cord blood HSCT, with a chimerism rate of 96.35% on day +41 and severe immune-mediated thrombocytopenia on day +153. After three sessions of IVIG pulse therapy, the platelet count increased initially but subsequently decreased. Therapies with dexamethasone, prednisone, cyclosporine, and recombinant human thrombopoietin also yielded a poor response. Both children received three sessions of UC-MSCs infusion, and platelet counts increased and were subsequently maintained within the normal range. Case 1 has been followed up for 10 years and remains in disease-free survival. UC-MSCs infusion may be effective for severe immune-mediated thrombocytopenia that is unresponsive to first- and second-line therapies after HSCT and could potentially improve the quality of life and disease-free survival rate.
Child ; Humans ; Hematopoietic Stem Cell Transplantation/adverse effects* ; Mesenchymal Stem Cell Transplantation ; Purpura, Thrombocytopenic, Idiopathic/etiology* ; Thrombocytopenia/therapy* ; Transplantation, Homologous ; Umbilical Cord/cytology*

OBJECTIVE: To analyze the efficacy and safety of decitabine-based myeloablative preconditioning regimen for allogeneic hematopoietic stem cell transplantation (allo-HSCT) in patients with acute myeloid leukemia (AML). METHODS: The clinical characteristics and efficacy of 115 AML patients who underwent allo-HSCT at the First Medical Center of Chinese PLA General Hospital from August 2018 to August 2022 were retrospectively analyzed, including 37 patients treated with decitabine conditioning regimen (decitabine group) and 78 patients without decitabine conditioning regimen (non-decitabine group). The cumulative incidence of relapse (CIR), overall survival (OS), leukemia-free survival (LFS), non-relapse mortality (NRM) and graft versus host disease (GVHD) were analyzed. RESULTS: For the patients in first complete remission (CR1) state before allo-HSCT, the 1-year relapse rates of decitabine group(22 cases) and non-decitabine group(69 cases) were 9.1% and 29.6%, respectively, the difference was statistically significant(P =0.042). The 1-year cumulative incidence of acute graft-versus-host disease (aGVHD) in decitabine group and non-decitabine group was 62.2% and 70.5%, respectively, and the 1-year cumulative incidence of chronic inhibitor-versus-host disease (cGVHD) was 18.9% and 14.1%, respectively, there were no significant differences in the incidence of aGVHD and cGVHD between the two groups (P >0.05). Of the 115 patients, there were no significantly differences in the 1-year CIR(21.7% vs 28.8%, P =0.866), NRM(10.9% vs 3.9%, P =0.203), OS(75.2% vs 83.8%, P =0.131) and LFS(74.6% vs 69.1%, P =0.912) between the decitabine group(37 cases) and the non-decitabine group(78 cases). CONCLUSION Decitabine-based conditioning regimen could reduce the relapse rate of AML CR1 patients with good safety.
Humans ; Leukemia, Myeloid, Acute/therapy* ; Hematopoietic Stem Cell Transplantation/methods* ; Decitabine/therapeutic use* ; Transplantation Conditioning/methods* ; Retrospective Studies ; Graft vs Host Disease ; Transplantation, Homologous ; Male ; Female ; Adult ; Middle Aged ; Adolescent ; Young Adult

Traditional Chinese medicine formula (TCMF) represents a fundamental component of Chinese medical practice, incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities, while providing comprehensive insights into health and disease. The foundation of TCMF lies in its holistic approach, manifested through herbal compatibility theory, which has emerged from extensive clinical experience and evolved into a highly refined knowledge system. Within this framework, Chinese herbal medicines exhibit intricated characteristics, including multi-component interactions, diverse target sites, and varied biological pathways. These complexities pose significant challenges for understanding their molecular mechanisms. Contemporary advances in artificial intelligence (AI) are reshaping research in traditional Chinese medicine (TCM), offering immense potential to transform our understanding of the molecular mechanisms underlying TCMFs. This review explores the application of AI in uncovering these mechanisms, highlighting its role in compound absorption, distribution, metabolism, and excretion (ADME) prediction, molecular target identification, compound and target synergy recognition, pharmacological mechanisms exploration, and herbal formula optimization. Furthermore, the review discusses the challenges and opportunities in AI-assisted research on TCMF molecular mechanisms, promoting the modernization and globalization of TCM.
Artificial Intelligence ; Drugs, Chinese Herbal/pharmacokinetics* ; Humans ; Medicine, Chinese Traditional ; Animals

Artificial intelligence (AI) has emerged as a transformative technology in accelerating drug discovery and development within natural medicines research. Natural medicines, characterized by their complex chemical compositions and multifaceted pharmacological mechanisms, demonstrate widespread application in treating diverse diseases. However, research and development face significant challenges, including component complexity, extraction difficulties, and efficacy validation. AI technology, particularly through deep learning (DL) and machine learning (ML) approaches, enables efficient analysis of extensive datasets, facilitating drug screening, component analysis, and pharmacological mechanism elucidation. The implementation of AI technology demonstrates considerable potential in virtual screening, compound optimization, and synthetic pathway design, thereby enhancing natural medicines' bioavailability and safety profiles. Nevertheless, current applications encounter limitations regarding data quality, model interpretability, and ethical considerations. As AI technologies continue to evolve, natural medicines research and development will achieve greater efficiency and precision, advancing both personalized medicine and contemporary drug development approaches.
Biological Products/pharmacology* ; Artificial Intelligence ; Humans ; Drug Discovery/methods* ; Machine Learning ; Deep Learning

Human carboxylesterase 2A (hCES2A) plays pivotal roles in prodrug activation and hydrolytic metabolism of ester-bearing chemicals. Targeted inhibition of intestinal hCES2A represents a feasible strategy to mitigate irinotecan-triggered gut toxicity (ITGT), but the orally active, selective, and efficacious hCES2A inhibitors are rarely reported. Here, a novel drug-like hCES2A inhibitor was developed via three rounds of structure-based drug design (SBDD) and structural optimization. Initially, donepezil was identified as a moderate hCES2A inhibitor from 2000 US Food and Drug Administration (FDA)-approved drugs. Following two rounds of SBDD and structural optimization, a donepezil derivative (B7) was identified as a strong reversible hCES2A inhibitor. Subsequently, nine B7 carbamates were rationally designed, synthesized and biologically assayed. Among all synthesized carbamates, C3 showed the most potent time-dependent inhibition on hCES2A (IC₅₀ = 0.56 nmol/L), excellent specificity and favorable drug-like properties. C3 could covalently modify the catalytic serine of hCES2A with high selectivity, while this agent also showed favorable safety profiles, high intestinal exposure, and impressive effects for ameliorating ITGT in both human intestinal organoids and tumor-bearing mice. Collectively, this study showcases a rational strategy for developing drug-like and serine-targeting covalent inhibitors against target serine hydrolase(s), while C3 emerges as a promising orally active drug candidate for ameliorating ITGT.

OBJECTIVES: To explore the value of serum cystatin C (CysC) levels in evaluating renal prognosis in IgA nephropathy (IgAN) patients. METHODS: We retrospectively collected the clinical data of IgAN patients diagnosed by renal biopsy at Guangdong Provincial People's Hospital from January, 2014 to December, 2018. Based on baseline serum CysC levels, the patients were divided into high serum CysC (>1.03 mg/L) group and normal serum CysC (≤1.03 mg/L) group. The composite endpoint for poor renal prognosis was defined as ≥50% decline in estimated glomerular filtration rate (eGFR) and/or progression to end-stage renal disease (ESRD). Lasso regression, multivariate Cox regression and Kaplan-Meier survival analysis were used to identify the risk factors and compare renal survival rates between the two groups. Smooth curves fitting and threshold effect analysis were used to explore the relationship between serum CysC levels and the outcomes. A nomogram model was constructed and its predictive performance was evaluated using concordance index, calibration curve, receiver operating characteristic (ROC) curve and the area under curve (AUC). RESULTS: A total of 356 IgAN patients were enrolled, who were followed up for 4.65±0.93 years. The composite endpoint occurred in 74 patients. High serum CysC was identified as an independent risk factor for poor renal prognosis in IgAN (HR=2.142, 95% CI 1.222 to 3.755), and the patients with high serum CysC levels had a lower renal survival rate (Log-rank χ²=47.970, P<0.001). In patients with serum CysC below 2.12 mg/L, a higher CysC level was associated with an increased risk of poor renal prognosis (β=3.487, 95% CI: 2.561-4.413, P<0.001), while above this level, the increase of the risk was not significant (β=0.676, 95% CI: -0.642-1.995, P=0.315). The nomogram model based on serum CysC and 3 other independent risk factors demonstrated good internal validity with a concordance index of 0.873 (95% CI: 0.839-0.907) and an AUC of 0.909 (95% CI: 0.873-0.945). CONCLUSIONS Serum CysC levels are associated with renal prognosis in IgAN patients, and high serum CysC an independent risk factor for poor renal prognosis.
Humans ; Glomerulonephritis, IGA/diagnosis* ; Cystatin C/blood* ; Prognosis ; Risk Factors ; Retrospective Studies ; Glomerular Filtration Rate ; Kidney Failure, Chronic ; Male ; Female ; Adult ; Nomograms ; Middle Aged