Objective:To develop and assess a deep learning-based model for automatic segmentation of organs at risk (OARs) in postoperative brachytherapy for endometrial carcinoma (EC).Methods:A retrospective study was conducted on the computed tomography (CT) images of 108 EC patients who received high-dose-rate (HDR) 192Ir intracavitary vaginal-cuff brachytherapy (VCB) at the Peking University Third Hospital from November 2021 to October 2022. Then, the rectum, colon, small intestine, and bladder in these images were manually segmented. These patients were randomly divided into two groups using a random number table: 90 cases for training the 3D no-new-U-Net (nnU-Net) segmentation model and 18 cases for model testing. The precision and clinical applicability of the automatic segmentation model were assessed using geometric indexes including Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD), as well as dose-volume parameters (DVPs) including the minimum dose to 0.1, 1.0, and 2.0 cm 3 of OARs that received the highest irradiation doses ( D0.1 cm 3, D1.0 cm 3, and D2.0 cm 3). Results:The 3D nnU-Net model yielded mean DSC values of 0.90, 0.85, 0.88, and 0.95, respectively for the segmentations of the rectum, colon, small bowel, and bladder, all of which were better than those of the 3D U-Net and V-Net models. The differences among the three models were statistically significant ( F = 21.78, 24.33, 36.00, 20.11, P < 0.001). The 3D nnU-Net exhibited statistically significant differences in HD values for the colon, small intestine, and bladder segmentations among the three method ( F = 17.33, 24.11, 6.33, P < 0.05). The 3D nnU-Net model yielded lower MSD values for the segmentations of all organs compared to the control model, with statistically significant differences ( F = 29.78, 27.11, 27.11, 14.78, P < 0.001). No statistically significant difference was found in all DVPs between the 3D nnU-Net model-based and manual segmentations ( P > 0.05). Bland-Altman analysis demonstrated great consistency between the 3D nnU-Net and manual segmentations. Conclusions:The 3D nnU-Net-based model exhibits high geometric accuracy and dosimetric consistency with manual segmentation of OARs in brachytherapy, holding potential to improve clinical efficiency.

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.

AIM To study the chemical constituents from ethyl acetate fraction of Balanophora harlandii Hook.f.and their tyrosinase inhibitory activity.METHODS Separation and purification were performed using silica gel,MCI,ODS,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The monophenolase inhibitory activity was determined by the tyrosinase-catalyzed oxidation of L-tyrosine.RESULTS Twenty-four compounds were isolated and identified as sesamin(1),methyl caffeate(2),quercetin(3),5,7-dihydroxychromanone(4),methyl 3,4-dihydroxybenzoate(5),esculetin(6),kaempferol(7),naringenin(8),pyrogallic acid(9),pinosylvin(10),methyl propionate(11),caffeic acid(12),saccharinol(13),ferulic acid(14),trans-p-hydroxycinnamic acid(15),cinnamic acid(16),vanillic acid(17),vanillin(18),4-hydroxyacetophenone(19),4-hydroxybenzaldehyde(20),apigenin(21),(-)-isolariciresinol(22),(-)-secoisolariciresinol(23)and meso-2,3-di(3′,4′-methylenedioxybenzyl)butane-1,4-diol(24).The IC50 values of compounds 3,5,7,8,19,and 20 ranged from(0.246 5±0.028 3)to(1.278 2±0.021 3)mmol/L.CONCLUSION Compounds 1-9、11、15、17-21、24 are isolated from this plant for the first time,and 1,6,9,17-19,24 are first isolated from genus Balanophora.Compounds 3、5、7、8、19 and 20 have tyrosinase inhibitory activity.

AIM To study the chemical constituents from salt-processed Litchi Semen and their antioxidant activities.METHODS The 85％ethanol extract from salt-processed Litchi Semen was isolated and purified by silica gel,Sephadex LH-20,MCI,ODS and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.DPPH and ABTS+free radical scavenging method were used to evaluate their antioxidant activities.RESULTS Fifteen compounds were isolated and identified as dehydrocostuslactone(1),ananosmoside A(2),funingensin A(3),(2S)-pinocembrin-7-O-(6-O-α-L-rhamnopyranosyl-β-D-glucopyranoside)(4),liquiritienin(5),quercetin(6),rutin(7),isorhamnetin-3-O-β-rutinoside(8),procyanidin A2(9),procyanidin A1(10),ethyl protocatechuate(11),5-hydroxymethylfurfural(12),di(2-ethyl-hexyl)phthalate(13),nicotinamide(14),(10E,15Z)-9,12,13-trihydroxyoctadeca-10,15-dienoic acid(15).Compounds 6-7,9-10 exhibited scavenging activities against DPPH radicals with IC50 values of(12.929±1.232),(14.104±0.946),(10.417±1.736),(6.944±0.030)μmol/L,respectively.Compounds 6-10 exhibited scavenging activities against ABTS+radicals with IC50 values of(21.952±0.577),(25.683±0.625),(22.970±1.336),(20.210±1.435),(18.725±0.324)μmol/L,respectively.CONCLUSION Compounds 1,5,14-15 are isolated from Litchi genus for the first time.Compounds 6-7,9-10 have strong in vitro antioxidant activities.

Hypothermia is a clinical syndrome characterized by core body temperature<35℃,caused by significant heat loss from body surface in cold environment.As a systemic cold injury,it can be lethal if treatment is delayed.Emergent diagnosis and treatment of hypothermia are expected to improve the prognosis of patients.In 2005,the U.S.Army Research Institute of Environmental Medicine(USARIEM)issued guidelines for the prevention and management of cold injuries,but there has been no corresponding standard in China.Therefore,Emergency Branch of Chinese Medical Rescue Association,Emergency Medical Equipment Society of China Association of Medical Equipment,Integrated Rehabilitation Medical Branch of Chinese Medical Rescue Association,and Pre-Hospital Emergency Care Working Committee of Chinese Aging Well Association jointly developed the Chinese Expert Consensus on Emergent Treatment of Hypothermia(2025 edition).The consensus covers the pathophysiology,etiology and epidemiology,diagnosis and severity grading,prehospital treatment,and in-hospital treatment of hypothermia,including 15 recommendations in total,aiming to provide guidance for the relevant clinical rescue work.

AIM To study the chemical constituents from salt-processed Litchi Semen and their antioxidant activities.METHODS The 85％ethanol extract from salt-processed Litchi Semen was isolated and purified by silica gel,Sephadex LH-20,MCI,ODS and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.DPPH and ABTS+free radical scavenging method were used to evaluate their antioxidant activities.RESULTS Fifteen compounds were isolated and identified as dehydrocostuslactone(1),ananosmoside A(2),funingensin A(3),(2S)-pinocembrin-7-O-(6-O-α-L-rhamnopyranosyl-β-D-glucopyranoside)(4),liquiritienin(5),quercetin(6),rutin(7),isorhamnetin-3-O-β-rutinoside(8),procyanidin A2(9),procyanidin A1(10),ethyl protocatechuate(11),5-hydroxymethylfurfural(12),di(2-ethyl-hexyl)phthalate(13),nicotinamide(14),(10E,15Z)-9,12,13-trihydroxyoctadeca-10,15-dienoic acid(15).Compounds 6-7,9-10 exhibited scavenging activities against DPPH radicals with IC50 values of(12.929±1.232),(14.104±0.946),(10.417±1.736),(6.944±0.030)μmol/L,respectively.Compounds 6-10 exhibited scavenging activities against ABTS+radicals with IC50 values of(21.952±0.577),(25.683±0.625),(22.970±1.336),(20.210±1.435),(18.725±0.324)μmol/L,respectively.CONCLUSION Compounds 1,5,14-15 are isolated from Litchi genus for the first time.Compounds 6-7,9-10 have strong in vitro antioxidant activities.

Objective:To observe the effect of modified autologous skull defect repair in patients with traumatic brain injury and its influence on neurological function and living ability.Methods:104 patients with traumatic brain injury who were admitted to our hospital from March 2022 to August 2024 were included,they were divided into Group A[37 cases,poly ether ether ketone(PEEK)skull defect repair],Group B(35 cases,traditional titanium mesh skull defect repair),and Group C(32 cases,modified autologous skull defect repair).Perioperative indicators,neurological function,activity of daily living,quality of life,satisfaction,and incidence of postoperative complications were compared among three groups.Results:There were no differences in the operation time,operation blood loss and postoperative hospital stay among the three groups(P＞0.05).The hospitalization costs of Group A,Group B and Group C decreased successively(P＜0.05).Activity of Daily Living(ADL)scores at 3 and 6 months after surgery increased among three groups,while National Institutes of Health Stroke Scale(NIHSS)scores decreased(P＜0.05).There was no significant difference in physiological function,social function,psychological function,and material life among the three groups at 6 months after surgery(P＞0.05).The overall satisfaction rate in Group C was higher than that of Group A and Group B(P＜0.05).The overall incidence of complications in Group C was lower than that in Group A and Group B(P＜0.05).Conclusion:PEEK,traditional titanium mesh,and modified autologous skull are used in skull defect repair,operation time,operation blood loss and postoperative hospital stay are comparable,they can also reduce neurological function damage,improve living ability,and enhance the quality of life of patients,however,PEEK is relatively expensive,the satisfaction of traditional titanium mesh is low,andincidence of postoperative complications are relatively high.

Antibiotics are widely used in clinical treatment of bacterial infection diseases and in the breeding of livestock,poultry and aquatic products.However,the irrational and excessive use of antibiotics not only leads to the emergence of drug-resistant superbugs,but also the antibiotics discharged into the environment pose a significant threat to the environment and human health.Antibiotics have been included in the list of key new pollutants to be controlled.Therefore,the detection of residual antibiotics in environmental media and food is of vital importance for protecting the environment and public health.Among various antibiotic detection methods,electrochemical sensors have attracted extensive attention due to their high sensitivity,low cost,simplicity and rapidity.Appropriate modification of the electrode surface can enhance the sensitivity of electrochemical sensors,reduce interference and expand the detection range.Metal-organic frameworks(MOFs)materials have the advantages of rich types,adjustable structure and activity,high specific surface area and high porosity,and show great application potential in the field of electrochemical sensing.This paper first introduces the synthesis methods of MOFs,reviews the research progress of MOFs-modified electrodes for detection of common antibiotics by electrochemical sensors,and finally looks forward to their future development trends in the field of rapid antibiotic detection.

Objective To construct a model combining with traditional Chinese medicine(TCM)syndrome for predicting the risk of disease progression in patients with idiopathic membranous nephropathy(IMN)by machine learning methods,thus to quantitatively evaluating the value of TCM syndrome in the prediction of the risk of disease progression in IMN.Methods Monofactor analysis,recursive feature elimination(RFE)and multivariate binary Logistic regression analysis were used to screen the independent related factors affecting the risk of disease progression of IMN,and then a risk prediction model was constructed.A total of 102 patients with IMN were randomly assigned to the training set and the test set in a ratio of 65∶35,and then the comparison was conducted in the performance indicators of accuracy,sensitivity,specificity,F1 value,and area under the receiver operating characteristic(ROC)area under the curve(AUC)of the risk prediction model with or without the inclusion of the TCM syndrome information.Results Before the inclusion of TCM syndrome information,12 clinical characteristic variables for patients with MN were obtained after monofactor analysis combined with RFE screening,and they were age,hemoglobin quantification,urinary occult blood,24-hour urine protein quantification,urine protein-creatinine ratio,estimated glomerular filtration rate(eGFR),creatinine,uric acid,alanine transaminase,anti-phospholipase A2 receptor antibody(PLA2R-Ab),total cholesterol,and low-density lipoprotein cholesterd.A risk cholesterol prediction model containing the above variables was constructed.The multivariate binary Logistic regression analysis showed that the differences of the clinical variables mentioned above between the training-set group and test-set group were statistically significant,and the risk prediction model presented good sensitivity and predictability.Monofactor analysis combined with RFE screening was performed again after the inclusion of TCM syndrome information,and then 14 variables were obtained,which included blood stasis syndrome and dampness obstruction syndrome.The sensitivity and specificity of the model with the inclusion of the TCM syndrome information were significantly improved when compared with those without the inclusion of TCM syndrome information.Conclusion The results of the study initially indicate that TCM syndrome can be used as an important supplementary variable for predicting the risk of disease progression in IMN,and will provide a reference for intelligent diagnosis through the integration of traditional Chinese and western medicine information,and will supply the guidance for the treatment of IMN with TCM.

Objective:To develop and assess a deep learning-based model for automatic segmentation of organs at risk (OARs) in postoperative brachytherapy for endometrial carcinoma (EC).Methods:A retrospective study was conducted on the computed tomography (CT) images of 108 EC patients who received high-dose-rate (HDR) 192Ir intracavitary vaginal-cuff brachytherapy (VCB) at the Peking University Third Hospital from November 2021 to October 2022. Then, the rectum, colon, small intestine, and bladder in these images were manually segmented. These patients were randomly divided into two groups using a random number table: 90 cases for training the 3D no-new-U-Net (nnU-Net) segmentation model and 18 cases for model testing. The precision and clinical applicability of the automatic segmentation model were assessed using geometric indexes including Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD), as well as dose-volume parameters (DVPs) including the minimum dose to 0.1, 1.0, and 2.0 cm 3 of OARs that received the highest irradiation doses ( D0.1 cm 3, D1.0 cm 3, and D2.0 cm 3). Results:The 3D nnU-Net model yielded mean DSC values of 0.90, 0.85, 0.88, and 0.95, respectively for the segmentations of the rectum, colon, small bowel, and bladder, all of which were better than those of the 3D U-Net and V-Net models. The differences among the three models were statistically significant ( F = 21.78, 24.33, 36.00, 20.11, P < 0.001). The 3D nnU-Net exhibited statistically significant differences in HD values for the colon, small intestine, and bladder segmentations among the three method ( F = 17.33, 24.11, 6.33, P < 0.05). The 3D nnU-Net model yielded lower MSD values for the segmentations of all organs compared to the control model, with statistically significant differences ( F = 29.78, 27.11, 27.11, 14.78, P < 0.001). No statistically significant difference was found in all DVPs between the 3D nnU-Net model-based and manual segmentations ( P > 0.05). Bland-Altman analysis demonstrated great consistency between the 3D nnU-Net and manual segmentations. Conclusions:The 3D nnU-Net-based model exhibits high geometric accuracy and dosimetric consistency with manual segmentation of OARs in brachytherapy, holding potential to improve clinical efficiency.