Objective:To investigate the clinical efficacy of autologous adipose-derived stem cell gel (SVF-gel) grafting in the treatment of depressed acne scars.Methods:A retrospective analysis was conducted on data collected from 28 patients who underwent SVF-gel grafting treatment for depressed acne scars in the Department of Dermatology, Xijing Hospital, Air Force Medical University from October 2018 to May 2021. There were 17 males and 11 females, aged 17 - 38 (26 ± 4.86) years. As for clinical types, 8 patients were diagnosed with boxcar acne scars, 14 with rolling acne scars, and 6 with acne scars with characteristics of the two types. The clinical acne scar weighted scale (ECCA scale) was used to evaluate the appearance improvement after the treatment, and patients′ subjective satisfaction scores and incidence of adverse reactions were recorded.Results:After the SVF-gel grafting, the facial appearance of patients with depressed acne scars significantly improved, and the ECCA scores significantly decreased 6 months after surgery (before surgery: 52.5 ± 15.8 points; 6 months after surgery: 23.8 ± 10.2 points; t = 11.68, P < 0.001). The subjective satisfaction rate of patients was 82.14% (23/28), the incidence rate of adverse reactions was 17.86% (5/28), and 5 patients experienced mild inflammatory reactions after surgery, including 2 with subcutaneous nodules. The secondary grafting rate was 67.86% (19/28) . Conclusion:The SVF-gel grafting was markedly effective for the treatment of depressed acne scars, which is worthy of clinical promotion and application.

Objective To explore the value of MRI subtraction technique(ST)for evaluating the efficacy of systemic therapy for advanced hepatocellular carcinoma(HCC)and predicting prognosis after combining with surgery.Methods Totally 35 patients with 39 HCC lesions who received systemic therapy+radical resection were retrospectively collected.Based on preoperative MRI,tumor activity ratio(recorded as tumor activityST)was obtained with ST,while tumor activity value(recorded as tumor activitypathology)was obtained through postoperative pathology,and their correlation was analyzed.The patients were regularly followed up after surgery,and the survival data were recorded.Receiver operating characteristic(ROC)curve was drawn to evaluate the efficacy of tumor activityST for predicting patients'survival status.Then the patients were divided into survival benefit group and no survival benefit group according to the cut-off value,and survival analysis was conducted.Results Tumor activityST was positively correlated with tumor activitypathology(r=0.900,P＜0.001).The median follow-up time was 32.93 months,during which 8 patients died,and the median survival time was 29.9 months.The area under the curve(AUC)of tumor activityST for predicting patients'survival status was 0.67,and the cut-off value was 0.36.Thirty patients with tumor activityST＜0.36 were enrolled in survival benefit group,while 5 patients≥0.36 were collected in no survival benefit group.The overall survival in survival benefit group was longer than that in no survival benefit group(P＜0.001).Conclusion MRI ST could be used to non-invasively evaluate the efficacy of systemic therapy for advanced HCC and predict prognosis after combining with surgery.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]

Objective A new occipital bone removal technology was applied to improve the success rate of brain removal.Methods The skull was sawed based on the traditional brain removal technology,and part of the occipital bone was removed downward centered in external occipital protuberance to the foramen magnum,then exposed the telencephalon,cerebellum and posterior medulla oblongata.After that,removed the tentorium cerebelli and cut down the medulla oblongata and the related cranial nerves at the skull base,then removed the brain tissues.Results The removed brain tissues had structurally intact telencephalon,cerebellum and brain stem,clear vessels in the cerebral sulci,and relatively intact optic chiasm,olfactory tracts and vertebro-basilar arteries.Conclusion Brain removal through a fenestration on the external occipital protuberance can effectively preserve the integrity of brain specimens,and improve the success rate of brain removal,which is of great significance for central nervous system teaching and improvement of human brain tissue repositories.

Aim To evaluate the role of the glucose transporter protein 1(GLUT1)-dependent glycolytic in the attenuation of oxygen-glucose deprivation-reoxygen-ation(OGD/R)injury in HK-2 cells by dexmedetomi-dine(Dex).Methods C57/BL6 mice were random-ly divided into three groups(n=6),namely,sham operation group(Sham group),renal ischemia reper-fusion group(I/R group)and Dex group(I/R+Dex group).Serum creatinine(Cr)and urea nitrogen(BUN)were measured,while the levels of key glyco-lytic enzymes HK2,PFKFB3 and GLUT1 were meas-ured.HK-2 cells were cultured and randomised into seven groups(n=6),which was treated with OGD/R,overexpression or interference with GLUT1,Dex and glycolysis inhibitor 2-DG.CCK-8 and LDH activi-ty were used to detect cellular damage.Glycolysis lev-els were detected by lactate and ECAR.The inflamma-tory level was reflected by qRT-PCR for IL-6 and TNF-α.qRT-PCR and Western blot were performed to de-tect the levels of GLUT1,HK2,and PFKFB3.Results Dex significantly ameliorated kidney injury and HK-2 cell injury(P＜0.05).Dex inhibited the OGD/R-induced rise in lactate and extracellular acidification rate(ECAR),as evidenced by suppression of the ex-pression of GLUT1,HK2 and PFKFB3(P＜0.05).In vitro experiments showed that GLUT1 knockdown sig-nificantly improved OGD/R-induced cellular damage.Lactate,ECAR,glycolysis-related mRNAs and pro-teins were inhibited by GLUT1 knockdown(P＜0.05).Significantly,there were no significant differ-ences in above indexes after Dex treatment based on GLUT1 knockdown.Overexpression of GLUT1 abroga-ted the protective effects of Dex,while reversing the inhibitory effects of Dex on the expression of GLUT1,HK2,and PFKFB3(P＜0.05).Conclusions Dexmedetomidine attenuates OGD/R induced injury in HK-2 cells by inhibiting GLUT1-dependent glycolysis.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

Objective To explore the value of MRI subtraction technique(ST)for evaluating the efficacy of systemic therapy for advanced hepatocellular carcinoma(HCC)and predicting prognosis after combining with surgery.Methods Totally 35 patients with 39 HCC lesions who received systemic therapy+radical resection were retrospectively collected.Based on preoperative MRI,tumor activity ratio(recorded as tumor activityST)was obtained with ST,while tumor activity value(recorded as tumor activitypathology)was obtained through postoperative pathology,and their correlation was analyzed.The patients were regularly followed up after surgery,and the survival data were recorded.Receiver operating characteristic(ROC)curve was drawn to evaluate the efficacy of tumor activityST for predicting patients'survival status.Then the patients were divided into survival benefit group and no survival benefit group according to the cut-off value,and survival analysis was conducted.Results Tumor activityST was positively correlated with tumor activitypathology(r=0.900,P＜0.001).The median follow-up time was 32.93 months,during which 8 patients died,and the median survival time was 29.9 months.The area under the curve(AUC)of tumor activityST for predicting patients'survival status was 0.67,and the cut-off value was 0.36.Thirty patients with tumor activityST＜0.36 were enrolled in survival benefit group,while 5 patients≥0.36 were collected in no survival benefit group.The overall survival in survival benefit group was longer than that in no survival benefit group(P＜0.001).Conclusion MRI ST could be used to non-invasively evaluate the efficacy of systemic therapy for advanced HCC and predict prognosis after combining with surgery.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]