With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

In view of the complex structure of diabetic retinopathy and the large differences in the scales of different lesions,a novel network which integrates deformable convolution and attention mechanism is proposed for automatic diabetic retinopathy multi-lesion segmentation.Specifically,deformable convolution Haar wavelet transform encoder takes place of the original convolutional downsampling encoder to adapt to the irregular shape changes of lesions and extract effective feature information;a dense feature perception and aggregation module is introduced at the bottleneck layer to extract multi-scale features by aggregating multiple receptive fields,thus enhancing deep semantic information;and finally,in order to fully integrate the decoder output and improve the recognition accuracy of edge information,a multi scale adaptive fusion module is used to weight the decoder output of each layer for obtaining the most accurate segmentation feature map.The validation of hard percolation,bleeding point,and soft percolation segmentations on the DDR-RLS dataset reveals that the proposed network shows increases of 0.026 2,0.051 8 and 0.046 5 in IoU coefficient,0.027 1,0.058 1 and 0.050 4 in Dice coefficient,and 0.0423,0.0691 and 0.0734 in AUPR value,as compared with the original Unet.

Paclitaxel (PTX), a valuable natural product derived from Taxus species, exhibits remarkable anti-cancer properties. It penetrates nanopores in microtubule walls, interacting with tubulin on the lumen surface and disrupting microtubule dynamics, thereby inducing cytotoxic effects in cancer cells. PTX and its derivatives have gained approval for treating various diseases due to their low toxicity, high efficiency, and broad-spectrum application. The widespread success and expanding applications of PTX have led to increased demand, raising concerns about accessibility. Consequently, researchers globally have focused on developing alternative production methods and applying nanocarriers in PTX delivery systems to enhance bioavailability. This review examines the challenges and advancements in PTX sourcing, production, physicochemical properties, anti-cancer mechanisms, clinical applications, trials, and chemo-immunotherapy. It aims to provide a comprehensive reference for the rational development and effective utilization of PTX.
Humans ; Paclitaxel/pharmacology* ; Antineoplastic Agents, Phytogenic/pharmacology* ; Neoplasms/drug therapy* ; Animals ; Taxus/chemistry*

A scoping review was performed to systematically search and summarize the clinical research in the treatment of dysmenorrhea with oral Chinese patent medicines. The oral Chinese patent medicines for treating dysmenorrhea in three major drug lists, guidelines, and textbooks were screened, and the relevant clinical trials were retrieved from eight Chinese and English databases. The key information of the included trials was extracted and visually analyzed. A total of 50 Chinese patent medicines were included, among which oral Chinese patent medicines for the dysmenorrhea patients with the syndrome of Qi stagnation and blood stasis accounted for the highest proportion, and the average daily cost varied greatly among Chinese patent medicines. A total of 150 articles were included, involving 22 Chinese patent medicines, among which Guizhi Fuling Capsules/Pills, Sanjie Zhentong Capsules, and Dan'e Fukang Soft Extract were the most frequently studied. These articles mainly reported randomized controlled trial(RCT), which mainly focused on the comparison of the intervention effect between Chinese patent medicines combined with western medicine and western medicine alone, and the sample size was generally 51-100 cases. The high-frequency outcome indicators belonged to nine domains such as effective rate, adverse reactions, and laboratory examinations. This study showed that oral Chinese patent medicines had advantages in the treatment of dysmenorrhea, and the annual number of related clinical trials showed an overall growing trend. However, there were still problems such as insufficient safety information and vague description of traditional Chinese medicine(TCM) syndromes types in the instructions of Chinese patent medicines. The available clinical research had shortcomings such as uneven distribution of Chinese patent medicines, limited research scale, poor methodological rigor, and insufficient standardization of outcome indicators. In the future, it is necessary to deepen the development of high-quality clinical research and improve the contents of the instructions to ensure the effectiveness and safety of the clinical application of oral Chinese patent medicines in the treatment of dysmenorrhea.
Dysmenorrhea/drug therapy* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Administration, Oral ; Nonprescription Drugs/administration & dosage*

This study aims to investigate the mechanism of Qingrun Decoction in alleviating hepatic insulin resistance in type 2 diabetes mellitus(T2DM) rats through the reprogramming of amino acid metabolism. A T2DM rat model was established by inducing insulin resistance through a high-fat diet combined with intraperitoneal injection of streptozotocin. The model rats were randomly divided into five groups: model group, high-, medium-, and low-dose Qingrun Decoction groups, and metformin group. A normal control group was also established. The rats in the normal and model groups received 10 mL·kg~(-1) distilled water daily by gavage. The metformin group received 150 mg·kg~(-1) metformin suspension by gavage, and the Qingrun Decoction groups received 11.2, 5.6, and 2.8 g·kg~(-1) Qingrun Decoction by gavage for 8 weeks. Blood lipid levels were measured in different groups of rats. Pathological damage in rat liver tissue was assessed by hematoxylin-eosin(HE) staining and oil red O staining. Transcriptome sequencing and untargeted metabolomics were performed on rat liver and serum samples, integrated with bioinformatics analyses. Key metabolites(branched-chain amino acids, BCAAs), amino acid transporters, amino acid metabolites, critical enzymes for amino acid metabolism, resistin, adiponectin(ADPN), and mammalian target of rapamycin(mTOR) pathway-related molecules were quantified using quantitative real-time polymerase chain reaction(qRT-PCR), Western blot, and enzyme-linked immunosorbent assay(ELISA). The results showed that compared with the normal group, the model group had significantly increased serum levels of total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), and resistin and significantly decreased ADPN levels. Hepatocytes in the model group exhibited loose arrangement, significant lipid accumulation, fatty degeneration, and pronounced inflammatory cell infiltration. In liver tissue, the mRNA transcriptional levels of solute carrier family 7 member 2(Slc7a2), solute carrier family 38 member 2(Slc38a2), solute carrier family 38 member 4(Slc38a4), and arginase(ARG) were significantly downregulated, while the mRNA transcriptional levels of solute carrier family 1 member 4(Slc1a4), solute carrier family 16 member 1(Slc16a1), and methionine adenosyltransferase(MAT) were upregulated. Furthermore, the mRNA transcription and protein expression levels of branched-chain α-keto acid dehydrogenase E1α(BCKDHA) and DEP domain-containing mTOR-interacting protein(DEPTOR) were downregulated, while mRNA transcription and protein expression levels of mTOR, as well as ribosomal protein S6 kinase 1(S6K1), were upregulated. The levels of BCAAs and S-adenosyl-L-methionine(SAM) were elevated. The serum level of 6-hydroxymelatonin was significantly reduced, while imidazole-4-one-5-propionic acid and N-(5-phospho-D-ribosyl)anthranilic acid levels were significantly increased. Compared with the model group, Qingrun Decoction significantly reduced blood lipid and resistin levels while increasing ADPN levels. Hepatocytes had improved morphology with reduced inflammatory cells, and fatty degeneration and lipid deposition were alleviated. Differentially expressed genes and differential metabolites were mainly enriched in amino acid metabolic pathways. The expression levels of Slc7a2, Slc38a2, Slc38a4, and ARG in the liver tissue were significantly upregulated, while Slc1a4, Slc16a1, and MAT expression levels were significantly downregulated. BCKDHA and DEPTOR expression levels were upregulated, while mTOR and S6K1 expression levels were downregulated. Additionally, the levels of BCAAs and SAM were significantly decreased. The serum level of 6-hydroxymelatonin was increased, while those of imidazole-4-one-5-propionic acid and N-(5-phospho-D-ribosyl)anthranilic acid were decreased. In summary, Qingrun Decoction may improve amino acid metabolism reprogramming, inhibit mTOR pathway activation, alleviate insulin resistance in the liver, and mitigate pathological damage of liver tissue in T2DM rats by downregulating hepatic BCAAs and SAM and regulating key enzymes involved in amino acid metabolism, such as BCKDHA, ARG, and MAT, as well as amino acid metabolites and transporters.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Insulin Resistance ; Diabetes Mellitus, Type 2/genetics* ; Male ; Liver/drug effects* ; Amino Acids/metabolism* ; Rats, Sprague-Dawley ; Humans ; Metabolic Reprogramming

This study aims to systematically review and evaluate the quality of clinical research on the treatment of adenomyosis(AM) with traditional Chinese medicine(TCM) in recent ten years, using evidence graphs. Computer searches were conducted on eight Chinese and English databases, commonly used guideline databases, and guideline-related websites, covering the period from January 1, 2014, to October 1, 2024. Two researchers independently screened, extracted information, and evaluated the quality of the evidence. The distribution and quality of the clinical research evidence were presented using both text and charts. A total of 565 articles were included in the study, comprising 523 intervention studies, 23 observational studies, 18 systematic reviews/Meta-analysis, and 1 guideline. The overall publication volume has shown a downward trend in past two years. The sample sizes of the intervention and observational studies primarily focused on 60 to 120 cases. The intervention schemes mainly involved multi-therapy combinations, including 33 classic prescriptions and 25 Chinese patent medicines. Among these, 48 studies related to 17 classic prescriptions and 45 studies related to 10 types of Chinese patent medicines involved TCM syndrome types. Randomized controlled trial(RCT) tended to focus on overall clinical efficacy and the degree of dysmenorrhea as key outcome measures. Methodological quality issues were found in 97 RCTs related to TCM decoctions and 131 RCTs related to Chinese patent medicines, primarily involving unclear explanations of some information. The AMSTAR scores for the 18 systematic reviews/Meta-analysis ranged from 1 to 8 points, with 16 studies suggesting "evidence of potential therapeutic efficacy". The recommended level for the one included guideline was B-level. TCM shows significant advantages in treating AM. Future clinical research should further standardize study designs, reference relevant reporting guidelines, improve the quality of clinical research, generate higher-level evidence-based results, and promote the high-quality development of clinical research on TCM for treating AM.
Humans ; Adenomyosis/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Female ; Medicine, Chinese Traditional ; Randomized Controlled Trials as Topic

The medicinal materials of Bawei Chenxiang Pills(BCPs) were extracted via three methods: reflux extraction by water, reflux extraction by 70% ethanol, and extraction by pure water following reflux extraction by 70% ethanol, yielding three extracts of ST, CT, and CST. The efficacy of ST(760 mg·kg~(-1)), CT(620 mg·kg~(-1)), and CST(1 040 mg·kg~(-1)) were evaluated by acute myocardial ischemia(AMI) and p-chlorophenylalanine(PCPA)-induced insomnia in mice, respectively. Western blot was further utilized to investigate their hypnosis mechanisms. The main chemical components of different extracts were identified by the UPLC-Q-Exactive-MS technique. The results showed that CT and CST significantly increased the ejection fraction(EF) and fractional shortening(FS) of myocardial infarction mice, reduced left ventricular internal dimension at end-diastole(LVIDd) and left ventricular internal dimension at end-systole(LVIDs). In contrast, ST did not exhibit significant effects on these parameters. In the insomnia model, CT significantly reduced sleep latency and prolonged sleep duration, whereas ST only prolonged sleep duration without shortening sleep latency. CST showed no significant effects on either sleep latency or sleep duration. Additionally, both CT and ST upregulated glutamic acid decarboxylase 67(GAD67) protein expression in brain tissue. A total of 15 main chemical components were identified from CT, including 2-(2-phenylethyl) chromone and 6-methoxy-2-(2-phenylethyl) chromone. Six chemical components including chebulidic acid were identified from ST. The results suggested that chromones and terpenes were potential anti-myocardial ischemia drugs of BCPs, and tannin and phenolic acids were potential hypnosis drugs. This study enriches the pharmacological and chemical research of BCPs, providing a basis and reference for their secondary development, quality standard improvement, and clinical application.
Animals ; Drugs, Chinese Herbal/isolation & purification* ; Mice ; Male ; Sleep Initiation and Maintenance Disorders/physiopathology* ; Humans ; Myocardial Infarction/drug therapy* ; Myocardial Ischemia/drug therapy*

Lymph node metastasis (LNM) is a crucial risk factor influencing an unfavorable prognosis in specific cancers. Fundamental research illuminates our understanding of tumor behavior and identifies valuable therapeutic targets. Nevertheless, the exploration of fundamental theories and the validation of clinical therapies hinge on preclinical experiments. Preclinical models, in this context, serve as the conduit connecting fundamental theories to clinical outcomes. In vivo models established in animals offer a valuable platform for comprehensively observing interactions between tumor cells and organisms. Using various experimental animals, including mice, diverse methods, such as carcinogen-induced tumorigenesis, tumor cell line or human tumor transplantation, genetic engineering, and humanization, have been used effectively to construct numerous models for tumor LNM. Carcinogen-induced models simulate the entire process of tumorigenesis and metastasis. Transplantation models, using human tumor cell lines or patient-derived tumors, offer a research platform closely mirroring the histology and clinical behavior of human tumors. Genetically engineered models have been used to delve into the mechanisms of primary tumorigenesis within an intact microenvironment. Humanized models are used to overcome barriers between human and murine immune systems. Beyond mouse models, various other animal models have unique advantages and limitations, all contributing to exploring LNM. This review summarizes existing in vitro and animal preclinical models, identifies current bottlenecks in preclinical research, and offers an outlook on forthcoming preclinical models.
Animals ; Humans ; Mice ; Lymphatic Metastasis/pathology* ; Disease Models, Animal ; Cell Line, Tumor

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

In view of the complex structure of diabetic retinopathy and the large differences in the scales of different lesions,a novel network which integrates deformable convolution and attention mechanism is proposed for automatic diabetic retinopathy multi-lesion segmentation.Specifically,deformable convolution Haar wavelet transform encoder takes place of the original convolutional downsampling encoder to adapt to the irregular shape changes of lesions and extract effective feature information;a dense feature perception and aggregation module is introduced at the bottleneck layer to extract multi-scale features by aggregating multiple receptive fields,thus enhancing deep semantic information;and finally,in order to fully integrate the decoder output and improve the recognition accuracy of edge information,a multi scale adaptive fusion module is used to weight the decoder output of each layer for obtaining the most accurate segmentation feature map.The validation of hard percolation,bleeding point,and soft percolation segmentations on the DDR-RLS dataset reveals that the proposed network shows increases of 0.026 2,0.051 8 and 0.046 5 in IoU coefficient,0.027 1,0.058 1 and 0.050 4 in Dice coefficient,and 0.0423,0.0691 and 0.0734 in AUPR value,as compared with the original Unet.