OBJECTIVES: The application of photodynamic therapy in solid tumors has attracted increasing attention in recent years, and the efficiency of photosensitizers is a crucial determinant of therapeutic efficacy. This study aims to evaluate the cytotoxic effects of a novel photosensitizer, PEG-MTPABZ-PyC, in photodynamic therapy against gastric cancer cells. METHODS: Gastric cancer MKN45 cells were treated with PEG-MTPABZ-PyC. A high-content live-cell imaging system was used to assess the cellular uptake kinetics and subcellular localization of the photosensitizer. The cytotoxic effects of PEG-MTPABZ-PyC-mediated photodynamic therapy were examined using the cell counting kit-8 (CCK-8) assay and flow cytometry, while the intrinsic cytotoxicity of the photosensitizer alone was verified by the CCK-8 assay. Intracellular reactive oxygen species (ROS) generation after photodynamic therapy was detected using 2'-7'-dichlorodihydrofluorescein diacetate (DCFH-DA). RESULTS: PEG-MTPABZ-PyC alone exhibited no cytotoxicity toward MKN45 cells, indicating excellent cytocompatibility. The compound efficiently entered cells within 6 hours and localized predominantly in lysosomes. Upon light irradiation, PEG-MTPABZ-PyC-mediated photodynamic therapy induced significant cytotoxicity compared with the control group (P<0.05) and generated abundant intracellular ROS. CONCLUSIONS The novel photosensitizer PEG-MTPABZ-PyC demonstrates potent photodynamic cytotoxicity against gastric cancer cells, showing promising potential for further development in gastric cancer photodynamic therapy.
Humans ; Stomach Neoplasms/drug therapy* ; Photochemotherapy/methods* ; Photosensitizing Agents/pharmacology* ; Cell Line, Tumor ; Polyethylene Glycols/chemistry* ; Reactive Oxygen Species/metabolism* ; Mesoporphyrins/pharmacology*

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in (a) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expert-driven tool PROFEAT, (b) implementing a hybrid deep neural network architecture that integrates convolutional neural network (CNN), fully connected (FC) layer, and bidirectional long short-term memory (BiLSTM) blocks, and (c) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools. The web server is freely accessible at https://idrblab.org/LocPro/.

Objective:To investigate the effect of blood lipids and statins use on the outcome of acute ischemic stroke (AIS) patients with cerebral microbleeds (CMBs).Methods:Consecutive AIS patients with CMBs hospitalized at the First People's Hospital of Taicang, Jiangsu Province from July 2023 to June 2024 were included retrospectively. At 3 months after onset, the modified Rankin Scale was used for outcome assessment. 0-2 was defined as good outcome and >2 was defined as poor outcome. Multivariate logistic regression analysis was used to identify independent influencing factors for poor outcome. Results:A total of 110 AIS patients with CMBs were enrolled, including 72 males (65.5%), aged 68.04±3.12 years. Thirty patients (27.3%) had poor outcome. Univariate analysis showed that age, baseline National Institutes of Health Stroke Scale (NIHSS) score, total cholesterol, triglycerides, low-density lipoprotein cholesterol, and the proportion of patients with hypertension and diabetes in poor outcome group were significantly higher than those in good outcome group, while baseline high-density lipoprotein cholesterol and the proportion of patients using statins before onset were significantly lower than those in good outcome group ( P<0.05). Multivariate logistic regression analysis showed that age (odds ratio [ OR] 1.309, 95% confidence interval [ CI] 1.007-1.702; P=0.044), the baseline NIHSS score ( OR 1.541, 95% CI 1.143-2.078; P=0.005) and high triglycerides ( OR 5.150, 95% CI 2.150-8.717; P=0.023) were the independent risk factors for poor outcome, while high high-density lipoprotein cholesterol ( OR 0.001, 95% CI 0.001-0.034; P<0.001) and statins use ( OR 0.231, 95% CI 0.046-0.558; P=0.019) were the independent protective factors for good outcome. Conclusions:Blood lipid and statins use are independent influencing factors for the outcome of AIS patients with CMBs. The use of statins before onset is associated with a lower risk of poor outcome in AIS patients with CMBs.

Drug development encompasses multiple processes,wherein protein subcellular localization is essential.It promotes target identification,treatment development,and the design of drug delivery systems.In this research,a deep learning framework called LocPro is presented for predicting protein subcellular localization.Specifically,LocPro is unique in(a)combining protein representations from the pre-trained large language model(LLM)ESM2 and the expert-driven tool PROFEAT,(b)implementing a hybrid deep neural network architecture that integrates convolutional neural network(CNN),fully connected(FC)layer,and bidirectional long short-term memory(BiLSTM)blocks,and(c)developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels.Additionally,a dataset was curated and divided using a homology-based strategy for training and validation.Compar-ative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction.The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization.All in all,LocPro serves as a valuable complement to existing protein localization prediction tools.The web server is freely accessible at https://idrblab.org/LocPro/.

Advancements in artificial intelligence(AI)and emerging technologies are rapidly expanding the exploration of chemical space,facilitating innovative drug discovery.However,the transformation of novel compounds into safe and effective drugs remains a lengthy,high-risk,and costly process.Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development.Despite this need,no comprehensive tool currently supports systematic evaluation and efficient screening.Here,we present druglikeFilter,a deep learning-based framework designed to assess drug-likeness across four critical dimensions:1)physicochemical rule evaluated by systematic determination,2)toxicity alert investigated from multiple perspectives,3)binding affinity measured by dual-path analysis,and 4)compound synthesizability assessed by retro-route prediction.By enabling automated,multidimensional filtering of compound libraries,druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates,which can be freely accessed at https://idrblab.org/drugfilter/.

OBJECTIVE To explore the mechanism of action of Fushao Diqin Decoction in the treatment of colorectal cancer.METHODS In vitro cell experiments were conducted using Fushao Diqin Decoction to treat colorectal cancer CT-26 cells,and the cell proliferation and migration abilities were detected.Flow cytometry was used to detect the levels of reactive oxygen species(ROS)in colorectal cancer CT-26 cells,as well as the levels of iron ions(Fe2+),malondialdehyde(MDA),and the activity of su-peroxide dismutase(SOD).PCR Array and Western blot methods were used to analyze and verify the differential gene expression of ferroptosis.Balb/c mice were randomly divided into a blank control group,a model group,an oxaliplatin group(1.5 mg·kg-1·d-1),a low-dose group of Fushao Diqin Decoction(4.49 g·kg-1·d-1),a medium dose group of Fushao Diqin Decoction(8.97 g·kg-1·d-1),and a high-dose group of Fushao Diqin Decoction(17.94 g·kg-1·d-1)for in vivo animal experi-ments.The effects of Fushao Diqin Decoction on Fe2+,ROS,MDA levels,SOD activity,and Nrf2,Keap1,SLC7A11 and GPX4 ex-pression levels in mouse tumor tissues were tested.RESULTS In vitro cell experiments showed that compared with the blank control group,Fushao Diqin Decoction significantly inhibited the proliferation and migration of colorectal cancer CT-26 cells in a dose-de-pendent manner.Fushao Diqin Decoction could increase the Fe2+content(P＜0.05)and ROS level(P＜0.01)in colorectal cancer CT-26 cells,increase the MDA level in CT-26 cells of colorectal cancer(P＜0.01)and significantly reduce SOD activity(P＜0.01).Iron death PCR array analysis found that compared with the blank control group,after intervention with Fushao Diqin Decoc-tion,the expression of genes GPX4 and SLC7A11 was significantly downregulated,while the expression of GSTA1,HMOX1,Ca9,Chac1,Keap1,Sqstm1,NOX1,FTH1,Tfr1,SAT2,Pparg,and Hamp was significantly upregulated.Western blot analysis revealed that after intervention with Fushao Diqin Decoction,the expression of Keap1 protein was upregulated(P＜0.01),while the expression of Nrf2,SLC7A11,and GPX4 proteins was downregulated(P＜0.01)in colorectal cancer CT-26 cells.The results of in vivo animal experiments showed that Fushao Diqin Decoction significantly inhibited the growth of subcutaneous transplanted tumors in mice(P＜0.05),increased the degree of tumor tissue necrosis,and levels of Fe2+,ROS,and MDA(P＜0.05,P＜0.01),decreased SOD ac-tivity(P＜0.01)and upregulated Keap1 protein expression(P＜0.01),while downregulated Nrf2,SLC7A11,and GPX4 protein ex-pression(P＜0.01).CONCLUSION Fushao Diqin Decoction has an anti-colorectal cancer effect and may promote ferroptosis in colorectal cancer cells by inhibiting the Nrf2/SLC7A11/GPX4 signaling pathway to exert its anti-colorectal cancer effect.

Professor Qiu Maoliang,in his clinical practice and experience summary of acupuncture-moxibustion in the treatment of febrile diseases,proposes four acupuncture-moxibustion antipyretic methods,namely,releasing the exterior and reducing fever,clear-ing the interior and purging the heat,nourishing the yin and purging the heat,and assisting the yang and reducing fever,which respec-tively correspond to the exterior heat syndrome,interior heat syndrome,yin deficiency fever syndrome,and yang deficiency fever syn-drome.The academic connotation of Professor Qiu Maoliang's acupuncture-moxibustion for fever can be summarized as examining the syndrome and seeking the cause,and classifying fever;coordinating the four methods of acupuncture-moxibustion and operation tech-niques,which reflect Professor Qiu Maoliang's academic characteristics,such as the convergence of Chinese and Western medicine,mutual learning of acupuncture-moxibustion and medicine,and the connection of effect mechanism and theory.Professor Qiu Ma-oliang's academic thought of acupuncture-moxibustion antipyretic method not only helps to provide basis for further application of acu-puncture-moxibustion in contemporary clinical practice,but also enriches the modern biological connotation of acupuncture-moxibus-tion medicine.

Objective To summarize the medication law of TCM in the treatment of chronic bronchitis;To provide reference for clinical medication.Methods Medical records of patients with chronic bronchitis who were hospitalized in the Respiratory Department of the First Affiliated Hospital of Henan University of Chinese Medicine from January 1,2016 to December 31,2021 were extracted based on HIS electronic medical record data.After screening,the TCM prescriptions used by patients with chronic bronchitis were input into Excel 2019 to establish a database.Based on the software Lantern 5.0,the latent structure model was learned,hidden variables and explicit variables were obtained,and the model was interpreted.SPSS Modeler 18.0 was used to establish model points with Apriori algorithm for Chinese materia medica with a frequency greater than 6%,to obtain the association rules between drugs,and to analyze the medication law of TCM in treating chronic bronchitis.Results A total of 3 410 cases were included,involving 423 kinds of Chinese materia medica,with a cumulative frequency of 82 766 times.Among them,109 kinds of Chinese materia medica with a frequency of>6 % had a cumulative frequency of 69 845 times.The top five commonly used medicines were Fritillariae Cirrhosae Bulbus,Poria,Atractyodis Macrocephalae Rhizoma,Asteris Radix et Rhizoma,Citri Reticulatae Pericarpium,mainly with medicines of reducing cough and phlegm,antiasthmatic medicine,tonifying deficiency,clearing heat,relieving superficies,promoting blood circulation and removing blood stasis.The medicinal properties were warming,cold and mild,and the main tastes were bitter,sweet and pungent,and the meridians were mainly lung,spleen,liver and stomach meridians.Through analysis of latent structure,49 hidden variables and 149 hidden classes were obtained.Combined with professional knowledge,10 comprehensive clustering models and 21 core formulas were deduced,such as Sangbaipi Decoction,Xuefu Zhuyu Decoction,Xiaoqinglong Decoction,Erchen Decoction,Shashen Maidong Decoction,Liuwei Dihuang Pills,Yinqiao Powder,Zhisou Powder,Yupingfeng Powder,Xuefu Zhuyu Decoction combined with Daotan Decoction,etc.It was concluded that the chronic bronchitis syndrome included phlegm-heat stagnation lung syndrome,qi stagnation blood stasis syndrome,cold fluid attacking lung syndrome,phlegm-dampness accumulation lung syndrome,lung qi and yin deficiency syndrome,kidney yin deficiency syndrome,wind heat attacking lung syndrome,wind cold attacking lung syndrome,lung qi and spleen deficiency syndrome,phlegm stasis interjunction syndrome.A total of 41 strong association rules were screened in the analysis of association rules,including 5 strong association rules for two and 36 strong association rules for three.The high confidence rules were Saposheikovize Radix + Angelicae Sinensis Radix →Atractyodis Macrocephalae Rhizoma,Saposheikovize Radix + Codonopsis Radix → Atractyodis Macrocephalae Rhizoma,Codonopsis Radix + Citri Reticulatae Pericarpium → Atractyodis Macrocephalae Rhizoma;the higher degree of improvement were Bupleuri Radix + Mori Cortex → Scutellariae Radix,Perillae Fructus + Belamcandae Rhizoma → Fritillariae Cirrhosae Bulbus,Armeniacae Semen Amarum + Pinelliae Rhizoma → Citri Reticulatae Pericarpium,etc.Conclusion In the treatment of chronic bronchitis,TCM is mainly used to reduce phlegm,relieve cough and asthma,and the method of promoting blood circulation and removing blood stasis is commonly used to help eliminate phlegm.In addition,TCM pays attention to the application of methods such as tonifying lung and securing the exterior,invigorating spleen and benefiting qi.