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

Gastric cancer is a high-incidence malignancy that poses a serious threat to public health in China, ranking among the top three cancers in both incidence and mortality. The majority of patients are diagnosed at an advanced stage, resulting in limited treatment options and poor prognosis. To address key challenges in gastric cancer diagnosis and treatment, a research team led by Professor Jiafu Ji at Peking University Cancer Hospital has focused on the project "Development and Dissemination of Precision Medicine Approaches in Gastric Cancer Management". Through a series of high-quality multicenter clinical studies, the team established a set of new international standards in perioperative treatment, individua-lized drug selection, intelligent noninvasive diagnostics, and novel immunotherapy strategies. These advances have significantly improved treatment efficacy and reduced surgical trauma, achieving key technological breakthroughs in diagnosis, therapy, and mechanistic understanding, and systematically enhancing outcomes for gastric cancer patients. The project ' s findings had a broad international impact, including hosting China ' s first International Gastric Cancer Congress. Through nationwide dissemination, they have promoted the development of precision diagnosis and treatment of gastric cancer as a discipline, and led the formulation of the National Health Commission's guidelines for gastric cancer diagnosis and treatment. In recognition of its achievements, the project was awarded the First Prize of the 2024 Chinese Medical Science and Technology Award.
Stomach Neoplasms/genetics* ; Humans ; Precision Medicine/methods* ; China ; Immunotherapy/methods*

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.

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.

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.

ObjectiveTo explore the effect and possible mechanism of Shenqi Pills （肾气丸） on cognitive impairment and hippocampal glucose energy metabolism in type 2 diabetes mellitus （T2DM）. MethodsSixty C57BL/6 mice were randomly divided into control group， model group， rosiglitazone group and Shenqi Pills low-， medium- and high-dose groups， with 10 mice in each group. T2DM model was induced by a high-fat diet combined with intraperitoneal injection of streptozotocin in all the groups except for the control group. After successful modeling， the high-， medium-， and low-dose Shenqi Pills groups were given 2.08， 1.04， and 0.52 g/（kg·d） of Shenqi Pills granules by gavage respectively， while the rosiglitazone group was given 3 mg/（kg·d） of rosiglitazone tablets by gavage， and the control group and model group were gavaged with 10 ml/（kg·d） of distilled water， all for 8 consecutive weeks. The body weight and fasting blood glucose （FBG） level were recorded every two weeks. The Morris water maze test was performed on the 8th week of medication. After 8-week medication， oral glucose tolerance test （OGTT） and fasting insulin level were measured， hippocampal glucose energy metabolism-related products were quantitatively detected by liquid chromatography tandem mass spectrometry， and KEGG annotation analysis was performed. ResultsCompared to those measured at the same timepoints in the control group， the body mass on week 6 and 8， as well as the FBG level on week 2， 4， 6 and 8 in the model group increased； the blood glucose level at 0， 30， 60 and 120 minutes of the OGTT test increased， while fasting insulin level after 8-week medication decreased. The escape latency of the model group was significantly prolonged on the 3rd and 4th days， and the escape latency time increased， while the total swimming distance， platform quadrant residence time and the number of platform crossings decreased （P＜0.05 or P＜0.01）. Compared to those measured at the same timepoints in the model group， the body mass on week 6 in the low-dose Shenqi Pills group， on week 6 and 8 in the medium- and high-dose groups， and on week 8 in the rosiglitazone group were significantly reduced； the FBG levels in all the Shenqi Pills groups and rosiglitazone group on week 6 and 8 decreased， while fasting insulin levels increased. In the OGTT test， blood glucose in the medium-dose group of Shenqi Pills at all timepoints decreased； in the Morris water maze test， the escape latency period of the medium- and high-dose Shenqi Pills groups was shortened on the 3rd and 4th days， while the escape latency time was reduced， and the total swimming distance， platform quadrant residence time， and number of platform crossings increased in the medium-dose Shenqi Pills group （P＜0.05 or P＜0.01）.The medium-dose Shenqi Pills showed best effect， therefore it was selected for the targeted quantitative detection of metabolites. The medium-dose Shenqi Pills group could regulate the disorder of glucose metabolism in the hippocampus of T2DM mice， and 13 differential metabolites were found，up-regulating α-ketoglutarate and 3-phosphoglyceric acid， and down-regulating fumaric acid， glutamatic acid， lactatic acid， inosine， malic acid， adenine， fructose 1,6-diphosphate and others. KEGG annotation of differential metabolites suggested that Shenqi Pills was closely related to the regulation of glucose metabolism disorder and insulin resistance in the hippocampus region of T2DM model mice， as well as neurodegenerative diseases and ABC transport， hypoxia-inducible factor 1 （HIF）， forkhead transcription factor （FoXO） and cyclic adenosine monophosphate （cAMP） signaling pathways. ConclusionShenqi Pills can improve learning and memory abilities and cognitive impairment in T2DM mice， and may act its role by regulating glucose energy metabolism in the hippocampus of T2DM.

Protein-protein interaction (PPI) plays an important role in the regulation of life. Most of the PPI interfaces are large and discontinuous, and it is difficult for small molecules to specifically bind to them. Peptides are critical in PPI surface interactions due to their higher affinity and specificity. However, peptides have some defects such as easy hydrolysis by protease and poor membrane permeability. Due to good biocompatibility and chemical diversity, cyclic peptides play an important role in drug discovery. Therefore, the development of efficient cyclic peptide construction methods has become a frontier issue in peptide drug research. In recent years, a series of new progresses have been made in the synthesis strategy and the application of cyclic peptides, providing powerful technical tools for the research and development of cyclic peptide drugs. In this review, the synthesis strategies of cyclic peptides and their application will be reviewed from four aspects: synthesis strategies, property improvement, biological activity and prospect.

Paeonia veitchii and P. lactiflora are both original plants of the famous Chinese medicinal drug Paeoniae Radix Rubra in the Chinese Pharmacopoeia. They have important medicinal value and great potential in the flower market. The selection of stable and reliable reference genes is a necessary prerequisite for molecular research on P. veitchii. In this study, two reference genes, Actin and GAPDH, were selected as candidate genes from the transcriptome data of P. veitchii. The expression levels of the two candidate genes in different tissues(phloem, xylem, stem, leaf, petiole, and ovary) and different growth stages(bud stage, flowering stage, and dormant stage) of P. veitchii were detected using real-time fluorescence quantitative technology(qRT-PCR). Then, the stability of the expression of the two reference genes was comprehensively analyzed using geNorm, NormFinder, BestKeeper, ΔCT, and RefFinder. The results showed that the expression patterns of Actin and GAPDH were stable in different tissues and growth stages of P. veitchii. Furthermore, the expression levels of eight genes(Pv-TPS01, Pv-TPS02, Pv-CYP01, Pv-CYP02, Pv-CYP03, Pv-BAHD01, Pv-UGT01, and Pv-UGT02) in different tissues were further detected based on the transcriptome data of P. veitchii. The results showed that when Actin and GAPDH were used as reference genes, the expression trends of the eight genes in different tissues of P. veitchii were consistent, validating the reliability of Actin and GAPDH as reference genes for P. veitchii. In conclusion, this study finds that Actin and GAPDH can be used as reference genes for studying gene expression levels in different tissues and growth stages of P. veitchii.
Real-Time Polymerase Chain Reaction/methods* ; Paeonia/genetics* ; Actins/genetics* ; Reproducibility of Results ; Transcriptome ; Glyceraldehyde-3-Phosphate Dehydrogenases/genetics* ; Reference Standards ; Gene Expression Profiling/methods*

Objective To establish a method for evaluating the disinfecting effect of positive-pressure protective hoods by testing the disinfecting effect of canine influenza virus(CIV)on the positive-pressure protective hood with 1％Virkon S disinfectant.Methods The neutralizer was selected considering the characteristics of 1％Virkon S disinfectant in accordance with"Disinfection technical specifications"(2002 edition),and the effectiveness of the neutralizer was verified by determining median tissue culture infectious dose(TTCID50)of different samples inoculated with canine renal cells;in the same environment the effects of viral vectors and environment on viral activity were detected by measuring the TCID50 at different time points when CIV acted on the positive pressure protective hood;the optimal disinfection time was determined by establishing a viral vector model and a viral infiltration and sampling method,combining the results of viral recovery rates by real-time quantitative polymerase chain reaction and enzyme-linked immunosorbent assay and viral titer measurements by TCID50 and 50％egg infectious dose(EID50).Results The phosphate buffer solution of 0.1％lecithin,2％Tween 80 and 0.5％sodium thiosulfate could be used as a neutralizer for 1％Virkon S disinfectant;the viral vectors and environment had no effects on CIV activity at different time points;the average recover rate was 96.12％for the samples inoculated with canine renal cells and 95.98％for the chicken eggs,and 1％Virkon S disinfectant behaved the best 4 min after its action on CIV on the positive-pressure protective hood.Conclusion The method proposed for evaluating the disinfection effect of the positive-pressure protective hood is effective in establishing optimal disinfection conditions for the positive-pressure protective hood.[Chinese Medical Equipment Journal,2023,44(9):33-37]