ObjectiveTo delineate the species composition structure and seasonal density fluctuations of mosquito populations in Yangpu District, Shanghai, and to provide scientific insights for the prevention and control of vector-borne diseases. MethodsA total of 12 monitoring sites from different habitats were selected to conduct adult mosquito monitoring using the CO₂ trap light method during 2019‒2023, elucidating the temporal and spatial distribution and change patterns of mosquito populations and densities in Yangpu District. ResultsFrom 2019 to 2023, a total of 1 321 female mosquitoes was captured, with an overall density of 0.16 case·(lamp·h)^-1. The species identified were predominantly Culex pipiens pallens (87.28%), followed by Aedes albopictus (12.64%), and Culex tritaeniorhynchus (0.08%). Seasonal distribution showed a typical single-peak pattern, with June‒August being the peak period. In terms of habitat distribution, the highest mosquito population density was found in residential areas [0.18 case·(lamp·h)^-1], followed by hospitals [0.13 case·(lamp·h)^-1] and parks [0.11 case·(lamp·h)^-1]. Culex pipiens pallens was the dominant species in all habitats, with a density of [0.14 case·(lamp·h)^-1]. Notably, there was a statistically significant difference in the composition of Culex pipiens pallens and Aedes albopictus among the three habitats mentioned(χ²=38.396, P<0.001; χ²=36.790, P<0.001). The mosquito density of the 12 streets from high to low is Changhai Road, Pingliang, Yinhang, Xinjiangwan City, Yanji, Daqiao, Wujiaochang, Kongjiang, Changbai New Village, Jiangpu, Siping and Dinghai.The distribution of mosquito density was relatively balanced across different communities (H=1.559, P=1.000). ConclusionThe results of CO₂ trap light monitoring reveals a relatively low density of adult mosquitoes in Yangpu District, with Culex pipiens pallens as the predominant species, and summer being the peak season for mosquitoes. In light of the threat of mosquito-borne diseases such as dengue fever, more effective and evidence-based mosquito control strategies, aligning with the distribution and behavioral patterns of mosquitoes, should be developed.

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

Amino acid metabolism plays a critical role in the progression and development of breast cancer. Cancer cells, including those in breast cancer, reprogram amino acid metabolism to meet the demands of rapid proliferation, survival, and immune evasion. This includes alterations in the uptake and utilization of amino acids, such as glutamine, serine, glycine, and arginine, which provide essential building blocks for biosynthesis, energy production, and redox homeostasis. Notably, the metabolic phenotypes of breast cancer cells vary across molecular subtypes and disease stages, emphasizing the need for patient stratification and personalized therapeutic strategies. Advances in multi-level diagnostics, including phenotyping and predictive tools, such as AI-based analysis and body fluid profiling, have highlighted the potential for tailoring treatments to individual metabolic profiles. Enzymes, such as glutaminase and serine hydroxymethyltransferase, often upregulated in breast cancer, represent promising therapeutic targets. Understanding the interplay between amino acid metabolism and breast cancer biology, alongside the integration of personalized medicine approaches, can uncover novel insights into tumor progression and guide the development of precision therapies. This review explores the metabolic pathways of amino acids in breast cancer, with a focus on their implications for personalized treatment strategies.
Humans ; Breast Neoplasms/therapy* ; Female ; Amino Acids/metabolism*

Accurate prediction of drug responses in cancer cell lines (CCLs) and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine. Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response (CDR) prediction, challenges remain regarding the generalization of new drugs that are unseen in the training set. Herein, we propose a multimodal fusion deep learning (DL) model called drug-target and single-cell language based CDR (DTLCDR) to predict preclinical and clinical CDRs. The model integrates chemical descriptors, molecular graph representations, predicted protein target profiles of drugs, and cell line expression profiles with general knowledge from single cells. Among these features, a well-trained drug-target interaction (DTI) prediction model is used to generate target profiles of drugs, and a pretrained single-cell language model is integrated to provide general genomic knowledge. Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods. Further ablation studies verified the effectiveness of each component of our model, highlighting the significant contribution of target information to generalizability. Subsequently, the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments, demonstrating its potential for real-world applications. Moreover, DTLCDR was transferred to the clinical datasets, demonstrating satisfactory performance in the clinical data, regardless of whether the drugs were included in the cell line dataset. Overall, our results suggest that the DTLCDR is a promising tool for personalized drug discovery.

OBJECTIVE: To construct a longitudinal trajectory model of arterial oxygen tension (PaO₂) within 24 hours after cardiac arrest (CA). METHODS: A retrospective cohort study was conducted. CA patients admitted to the ICU from 2014 to 2015 were selected from the eICU Collaborative Research Database (eICU-CRD). Data about patients' demographic characteristics, history of comorbidities, laboratory test indicators within 24 hours of intensive care unit (ICU) admission [including all PaO₂ data and arterial carbon dioxide tension (PaCO₂)], vasopressor use, and clinical outcomes were extracted from the database. The primary outcome variable was all-cause in-hospital mortality. Group-based trajectory model (GBTM) were built based on the changes in PaO₂ within 24 hours of ICU admission, and patients were grouped according to their initial static PaO₂ values upon ICU admission. Multivariable adjusted Poisson regression analysis was used to compare the in-hospital mortality risk among patients in different PaO₂ dynamic trajectory groups. Sensitivity analyses were performed using multivariable logistic regression and multivariable adjusted Poisson regression without imputation of missing values. RESULTS: A total of 3 866 CA patients were included. Three GBTM trajectory groups were identified based on PaO₂ changes within 24 hours of ICU admission: Group-1 (low level first increased then decreased, 148 cases), Group-2 (sustained low level, 3 040 cases), and Group-3 (first high level then decreased, 678 cases). Significant differences were found among the three groups in age, body weight, maximum serum potassium, maximum PaCO₂, minimum hemoglobin (Hb), vasopressor use, total hospitalization time, ICU stay, and hospital mortality. After incorporating variables with significant differences into the multivariable adjusted Poisson regression model, results showed that compared to Group-2 patients, patients in Group-1 and Group-3 had an increased risk of all-cause in-hospital mortality [Group-1 adjusted relative risk (aRR) = 1.20, 95% confidence interval (95%CI) was 1.02-1.41; Group-3 aRR = 1.11, 95%CI was 1.01-1.24]. Based on initial static PaO₂ values at ICU admission, patients were divided into four groups: PaO₂ < 100 mmHg (1 mmHg = 0.133 kPa; 1 217 cases), PaO₂ 100-200 mmHg (569 cases), PaO₂ 201-300 mmHg (547 cases), and PaO₂ > 300 mmHg (1 082 cases). Multivariable adjusted Poisson regression analysis indicated a significant upward trend in aRR for the latter three groups compared to the PaO₂ < 100 mmHg group. Sensitivity analyses revealed that compared to Group-2, patients in Group-1 and Group-3 had a significantly increased risk of all-cause in-hospital mortality (both P < 0.05). CONCLUSIONS Within 24 hours after return of spontaneous circulation in CA patients, PaO₂ exhibits different dynamic trajectories, and patients with hyperoxia have an increased risk of in-hospital mortality.
Humans ; Retrospective Studies ; Hospital Mortality ; Heart Arrest/blood* ; Prognosis ; Oxygen/blood* ; Intensive Care Units ; Cardiopulmonary Resuscitation ; Male ; Female ; Middle Aged

OBJECTIVE: Huachansu injection (HCSI), a promising anti-cancer Chinese medicine injection, has been reported to have the potential for reducing the toxicity of chemotherapy and improving the quality of life for colorectal cancer (CRC) patients. The objective of this study is to explore the synergistic and detoxifying effects of HCSI when used in combination with irinotecan (CPT-11). METHODS: To investigate the effect of HCSI on anti-CRC efficacy and intestinal toxicity of CPT-11, we measured changes in the biological behavior of LoVo cells in vitro, and anti-tumor effects in LoVo cell xenograft nude mice models in vivo. Meanwhile, the effect of HCSI on intestinal toxicity and the uridine diphosphate-glucuronosyltransferase 1A1 (UGT1A1) expression was investigated in the CPT-11-induced colitis mouse model. Subsequently, we measured the effect of HCSI and its 13 constituent bufadienolides on the expression of UGT1A1 and organic anion transporting polypeptides 1B3 (OATP1B3) in HepG2 cells. RESULTS: The combination index (CI) results showed that the combination of HCSI and CPT-11 exhibited a synergistic effect (CI < 1), which significantly suppressing the LoVo cell migration, enhancing G2/M and S phase arrest, and inhibiting tumor growth in vivo. Additionally, the damage to intestinal tissues was attenuated by HCSI in CPT-11-induced colitis model, while the increased expression of UGT1A1 in HepG2 cells and in mouse was observed. CONCLUSION The co-therapy with HCSI alleviated the intestinal toxicity induced by CPT-11 and exerted an enhanced anti-CRC effect. The detoxifying mechanism may be related to the increased expression of UGT1A1 and OATP1B3 by HCSI and its bufadienolides components. The findings of this study may serve as a theoretical insights and strategies to improve CRC patient outcomes. Please cite this article as: Jiang B, Meng ZY, Hu YJ, Chen JJ, Zong L, Xu LY, Zhang XQ, Zhang JX, Han YL. Huachansu injection enhances anti-colorectal cancer efficacy of irinotecan and alleviates its induced intestinal toxicity through upregulating UGT1A1-OATP1B3 expression in vitro and in vivo. J Integr Med. 2025; 23(5):576-590.
Irinotecan/therapeutic use* ; Animals ; Glucuronosyltransferase/genetics* ; Humans ; Colorectal Neoplasms/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Mice, Nude ; Mice ; Up-Regulation/drug effects* ; Male ; Xenograft Model Antitumor Assays ; Mice, Inbred BALB C ; Hep G2 Cells ; Cell Line, Tumor ; Intestines/drug effects* ; Amphibian Venoms

Radiation mainly comes from medical radiation,industrial radiation,nuclear waste and atmospheric ultraviolet radiation,etc.,radiation is divided into ionizing radiation and non-ionizing radiation.Studying the effects of ionizing and non-ionizing radiation on drug metabolism,understanding the absorption and distribution of drugs in the body after radiation and the speed of elimination under radiation conditions can provide reasonable guidance for clinical medication.This article reviews the effects of radiation on the pharmacokinetics of different drugs,elaborates the changes of different pharmacokinetics under radiation state,and discusses the reasons for the changes.

Lipopolysaccharides (LPS) are major outer membrane components of Gram-negative bacteria. Unlike most Gram-negative bacteria, Acinetobacter baumannii can still survive and acquire polymyxin resistance after complete loss of LPS. Previous studies of LPS-deficient Acinetobacter baumannii mostly focused on LPS-deficient strains induced by polymyxin, whose background was complex and unstable. To investigate LPS loss-mediated polymyxin resistant-Acinetobacter baumannii, this study constructed a stable and clear background LPS-deficient strain by knocking out lpxC gene in Acinetobacter baumannii ATCC 19606 with CIRSPR/Cas9, and then studied the phenotypic changes of the lpxC-deficient strain including morphology, growth rate, antibiotic susceptibility, virulence, membrane permeability, and membrane potential. Animal experiments were approved by the Animal Care and Welfare Committee Institute of Medicinal Biotechnology, CAMS and PUMC (approval number: IMB-20240119D₉). The results indicated that the lpxC gene of Acinetobacter baumannii ATCC 19606 was successfully knocked out. After losing the lpxC, the strain underwent the morphological change from rod-shaped to spherical. Furthermore, it leads to reduced growth rate, enhanced membrane permeability, decreased membrane potential, lower virulence, and increased antibiotic susceptibility to β-lactams, quinolones, aminoglycosides, macrolides, glycopeptides. The lpxC deletion results in significant changes in membrane homeostasis and adaptability of Acinetobacter baumannii. Understanding the phenotypic changes of colistin-resistant Acinetobacter baumannii mediated by LPS loss is useful for exploring the resistance mechanism of Acinetobacter baumannii and developing new therapeutic strategies.

Aim To investigate the mechanism of treatment of hepatolenticular degeneration with Garde-nia and Rhubarb decoction based on network pharma-cology and animal experiments.Methods The chemi-cal components and target sites of Gardenia and Rhu-barb decoction were retrieved using the Traditional Chi-nese Medicine System Pharmacology Analysis Platform(TCMSP).The disease targets were obtained by searching the databases of DisGeNET,GeneCards.The PPI network of active compound target sites was constructed using the STRING database.GO function and KEGG pathway enrichment analysis were per-formed using the DAVID database to predict the action pathway.A copper-loaded WD rat model was estab-lished by intragastric administration of copper sulfate pentahydrate.A total of 36 rats were randomly divided into the normal group,model group,penicillamine group and the low,medium and high dose groups of gardenia rhubarb.The relevant indicators and patho-logical changes of liver tissue were detected in WD rats.Results Network pharmacology screening identi-fied 68 potential active components of Gardenia and Rhubarb Decoction,30 intersection targets of diseases and drugs,involving key targets such as TNF,IL10,IGF1,IL1B,TP53,CASP3,PPARG,IL6,CXCL8,IL1A,TGFB1,mainly related to signal pathways such as MAPK,AGE-RAGE signaling pathway in diabetic complications.In the animal experiments,compared with the normal group,the urine copper,liver copper,blood copper,liver coefficient,serum and liver ALT,AST,TNF-α,CASP3,P53 levels in the model group rats significantly increased(P＜0.05);hepatocyte swelling,cytoplasm loose reticular appearance,feath-er-like degeneration and reticular necrosis were ob-served in liver tissue pathology;compared with the model group,the urine copper,liver copper,blood copper,liver coefficient,serum and liver ALT,AST,TNF-α,CASP3,P53 levels in the penicillamine group and Gardenia and Rhubarb decoction groups were sig-nificantly reduced(P＜0.05),and the degree of re-ticular necrosis in the rat liver cells in the penicilla-mine group and the Gardenia and Rhubarb decoction group was significantly reduced.Conclusions Garde-nia and Rhubarb decoction has the effect of regulating copper metabolism and reducing liver injury.The mechanism of action may be related to reversing apop-tosis and downregulating protein expression of TNF-α,CASP3,P53 in MAPK signaling pathway.