OBJECTIVE To set up normal ranges for indexes in embryo-fetal development toxicity studies in Sprague-Dawley(SD)rats and to establish a background database to provide reference for the embryo-fetal development toxicity evaluation of drugs.METHODS The data on embryonic develop-ment and fetal growth from embryo-fetal development toxicity studies(11 items)conducted by our center between 2013 and 2022 was statistically analyzed,involving 205 pregnant rats and 3037 fetuses in total,with the mean and standard deviation,coefficient of variation and 95%confidence interval calculated.The indexes included body mass,body mass gain and food consumption during pregnancy,pregnancy outcomes(pregnancy rate,average corpora lutea,average Implant sites,average live conceptuses,live conceptuse rate,resorption rate and dead conceptuse rate),fetal growth and development(fetal mass,placental mass and sex ratio),appearance abnormality rate,visceral abnormality rate,and skeletal abnormality rate.RESULTS The mass of pregnant rats trended up during gestation,with significant increases in the late period.Food consumption increased along with gestation.Caesarean section was conducted on gestation day 20,and the pregnancy rate was 93.2%.The average corpora lutea,Implant sites and live conceptuses were 18.0±3.2,15.9±2.8 and 14.8±3.0,respectively.The live conceptuse rate was 93.4%while the total dead embryo rate was 6.6%.The average mass of fetuses and placenta were respectively 3.6±0.3 and(0.6±0.3)g,and the fetal sex ratio(male/female)was 0.94.The incidence of fetal appearance abnormalities was about 0.2%,and that of soft tissue abnormalities was approximately 0.8%.The rate of skeletal abnormalities was about 1.2%,with higher incidence of non-ossification and incomplete ossification mostly identified on sternum and hyoid bone.The numbers of ossifications of metacarpal bones,metatarsal bones and sacrococcygeal vertebrae were 7.0±0.7,8.0±0.1 and 7.4±0.5,respectively.The rate of ossification of sternumⅠtoⅣwas higher,with an average of about 98.6%-99.9%.The ossification rates of sternum Ⅴ and Ⅵ were(68.0±28.4)%and(82.8±23.9)%.CONCLUSION The background database of indexes in the embryo-fetal development toxicity study on SD rats is established for our GLP laboratory,which provides reference for reproductive toxicity studies.

The aim of this study was to investigate the impact of overexpressing 70-kD heat shock pro-teins(Hsp70)on glycolysis in C2C12 cells during myogenesis and adipogenesis.Using C2C12 cells as the research material,adenovirus was used to overexpress the Hsp70 gene,and changes in the expression of glycolytic genes were detected using fluorescence quantitative PCR and Western blotting techniques.The study indicated that during C2C12 cell myogenic differentiation,the expression trend of the Hsp70 gene was consistent with that of Gsk3β,Pkm,Prkag3,Pfkm,and Hk-2 genes,suggesting a relationship between Hsp70 and the glycolytic pathway during myogenic differentiation.Overexpression of Hsp70 in the later stages of myogenic differentiation significantly upregulated the expression of Gsk3β,Pkm,Prk-ag3,and Pfkm genes(P＜0.05),with no significant impact on Hk-2 gene expression(P＞0.05).Dur-ing C2C12 cell adipogenic induction,the expression trend of the Hsp70 gene was similar to that of Gsk3β,Pkm,Prkag3,Pfkm,and Hk-2 genes,indicating a relationship between Hsp70 and the glycolytic path-way during adipogenic induction.Following Hsp70 overexpression,in the later stages of adipogenic in-duction,the number of lipid droplets was significantly higher compared to the control group,with a sig-nificant upregulation of Gsk3β,Pkm,Prkag3,and Pfkm gene expression(P＜0.05),while Hk-2 gene expression was not significantly affected(P＞0.05).In conclusion,Hsp70 in C2C12 cells in myogenic and adipogenic states promoted the breakdown of glycogen into 6-phospho-glucose,thereby enhancing the glycolytic pathway,providing insights into the functional role of the Hsp70 gene in glycolysis in C2C12 cells.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective:To investigate the utility of 68Ga-fibroblast activation protein (FAP) inhibitor (FAPI)-04 PET imaging in assessing the therapeutic response in pressure overload-induced heart failure. Methods:Rat models of pressure overload-induced heart failure were established by abdominal aortic constriction (AAC). Thirty rats were categorized into AAC group, 7 days reverse AAC (rAAC) group, and sham operation (sham) group ( n=10 per group) using completely random grouping method. All rats underwent 68Ga-FAPI-04 PET/CT imaging at 4 and 8 weeks after the ACC operation, while echocardiography, pathological examination, and immunohistochemical analysis were performed at 8 weeks postoperation. One-way analysis of variance, independent-sample t test and Pearson correlation analysis were used for data analysis. Results:68Ga-FAPI-04 PET/CT imaging showed that the target-to-background ratios of the heart and liver had significant differences among three groups both at 4 and 8 weeks postoperation ( F values: 2 547.12, 2 041.71, 462.65, 1 210.97, all P<0.001). Echocardiography revealed left ventricular ejection fraction (LVEF), left ventricular internal diameter at end-diastole (LVIDd), and left ventricular internal diameter at end-systole (LVIDs) in three groups at 8 weeks postoperation were significantly different ( F values: 118.92, 9.11, 10.63, all P<0.01). Rats were sacrificed at 8 weeks postoperation, and Masson staining showed that the fibrosis in the heart and liver of the rAAC group was significantly improved compared with that of the AAC group, and immunohistochemical analysis revealed significantly lower FAP levels in the heart and liver of the rAAC group compared with those of the AAC group ( t values: from -11.27 to -4.16, all P<0.01). FAPI uptake in the heart of the AAC group and rAAC group at 8 weeks postoperation were significantly positively correlated with FAPI uptake in the liver, LVIDd and LVIDs, FAPI uptake in the heart was significantly negatively correlated with LVEF, and FAPI uptake in the heart and liver were significantly positively correlated with fibrosis degree and FAP levels of corresponding organs ( r values: -0.89, -0.88, 0.72-0.97, all P<0.05). Conclusions:68Ga-FAPI-04 PET/CT can show the improvement process of cardio-liver fibrosis following the unloading of excessive pressure in heart failure. Myocardial FAPI uptake is closely related to the extent of heart failure improvement.

Objective:To investigate the clinical effect of magnetic stimulation combined with moxibustion on mild to moderate overactive bladder(OAB)and sexual function in women.Methods:We enrolled 80 female patients with mild to moderate OAB in this study and equally randomized them into a control and an experimental group,the former treated by magnetic stimulation and the latter by magnetic stimulation combined with moxibustion,both for 8 weeks.We obtained from the patients their OAB syndrome scores(OABSS),72-hour urination diary(72-h UD)scores,International Consultation on Incontinence Questionnaire-Overactive Bladder(ICIQ-OAB)scores and female sexual function indexes(FSFI),and compared them between the two groups before and after interven-tion.Results:A total of 77 patients completed the study,37 in the control and 40 in the experimental group.There were no statisti-cally significant differences in the baseline data between the two groups(P＞0.05).Compared with the baseline,the experimental group showed significant improvement after treatment in the OABSS(7.54±1.12 vs 4.46±0.96),72-h urine volume([126.40±46.04]vs[216.63±38.26]ml),urination frequency(15.55±3.21 vs 8.03±1.40),ICIQ-OAB score(10.25±1.15 vs 6.32±1.07)and FSFI(20.00±12.40 vs 33.30±21.00)(all P＜0.05),even more significantly than in the control group(OABSS:4.46±0.96 vs 5.59±0.90;72-h urine volume:[216.63±38.26]vs[173.41±15.55]ml;urination frequency:8.03±1.40 vs 9.90±1.49;ICIQ-OAB score:6.32±1.07 vs 7.89±0.77;FSFI:33.30±21.00 vs 30.40±10.40)(all P＜0.01).Conclu-sion:Magnetic stimulation combined with moxibustion can improve the symptoms of mild to moderate overactive bladder and improve sexual function in females.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Traumatic supraorbital fissure syndrome (TSOFS) is a symptom complex caused by nerve entrapment in the supraorbital fissure after skull base trauma. If the compressed cranial nerve in the supraorbital fissure is not decompressed surgically, ptosis, diplopia and eye movement disorder may exist for a long time and seriously affect the patients′ quality of life. Since its overall incidence is not high, it is not familiarized with the majority of neurosurgeons and some TSOFS may be complicated with skull base vascular injury. If the supraorbital fissure surgery is performed without treatment of vascular injury, it may cause massive hemorrhage, and disability and even life-threatening in severe cases. At present, there is no consensus or guideline on the diagnosis and treatment of TSOFS that can be referred to both domestically and internationally. To improve the understanding of TSOFS among clinical physicians and establish standardized diagnosis and treatment plans, the Skull Base Trauma Group of the Neurorepair Professional Committee of the Chinese Medical Doctor Association, Neurotrauma Group of the Neurosurgery Branch of the Chinese Medical Association, Neurotrauma Group of the Traumatology Branch of the Chinese Medical Association, and Editorial Committee of Chinese Journal of Trauma organized relevant experts to formulate Chinese expert consensus on the diagnosis and treatment of traumatic supraorbital fissure syndrome ( version 2024) based on evidence of evidence-based medicine and clinical experience of diagnosis and treatment. This consensus puts forward 12 recommendations on the diagnosis, classification, treatment, efficacy evaluation and follow-up of TSOFS, aiming to provide references for neurosurgeons from hospitals of all levels to standardize the diagnosis and treatment of TSOFS.

Humans ; Aged ; Lung Diseases ; Pneumonia/drug therapy* ; Adrenal Cortex Hormones/therapeutic use* ; Pulmonary Disease, Chronic Obstructive/drug therapy* ; Administration, Inhalation ; Community-Acquired Infections/drug therapy*

ObjectiveBased on knowledge mapping， the studies on prediction models in the field of traditional Chinese medicine （TCM） were visually analyzed， which provided a reference basis for the excavation and evolution of the future research direction by combing the development process and summarizing the research hotspots and dynamic trends. MethodChina National Knowledge Infrastructure and Web of Science Core Collection databases were searched to obtain studies on prediction models in the field of TCM from inception to February 28， 2023. Endnote X20 software was used for document management. Knowledge mapping generated by CiteSpace software and VOSviewer software was used to visually analyze the characteristics of publication， institutional cooperation relationship， author cooperation network， co-citation， and keywords. ResultA total of 264 pieces of Chinese literature and 266 pieces of English literature were included， and the overall number of research publications showed an increasing trend year by year. The cooperation relationship between the issuing institutions showed obvious regional characteristics， with the closest cooperation relationship between the universities of TCM and their affiliated hospitals， as well as secondary units subordinate to scientific research institutions. The number of research teams and team members publishing papers in English was higher， and cooperation between different teams was more frequent. Groundbreaking and/or referential studies were widely cited and referred to. The highly cited literature was mainly published in complementary and alternative medicine journals and pharmaceutical journals. Research hotspots mainly focused on clinical prediction models of TCM， quantitative models of TCM， and specific modeling methods. The application of artificial intelligence technologies such as machine learning and deep learning in the field of TCM will be the most cutting-edge research direction in the future. ConclusionThe field of TCM is paying more and more attention to the studies on prediction models， while the research cooperation mode involving multiple organizations and teams has increasingly become the mainstream. With the continuous development of multi-disciplinary integration， studies on prediction models are closely related to the development and rise of innovative techniques and methods， and any breakthrough in theory or application will induce and guide a new round of research upsurge. Systematic reviews of topic-specific prediction models should be carried out in the future to provide evidence-based evidence.