OBJECTIVE: To investigate the association between ABO blood types and gestational diabetes mellitus (GDM) risk. METHODS: A prospective birth cohort study was conducted. ABO blood types were determined using the slide method. GDM diagnosis was based on a 75-g, 2-h oral glucose tolerance test (OGTT) according to the criteria of the International Association of Diabetes and Pregnancy Study Groups. Logistic regression was applied to calculate the odds ratios ( ORs) and 95% confidence intervals ( CIs) between ABO blood types and GDM risk. RESULTS: A total of 30,740 pregnant women with a mean age of 31.81 years were enrolled in this study. The ABO blood types distribution was: type O (30.99%), type A (26.58%), type B (32.20%), and type AB (10.23%). GDM was identified in 14.44% of participants. Using blood type O as a reference, GDM risk was not significantly higher for types A ( OR = 1.05) or B ( OR = 1.04). However, women with type AB had a 19% increased risk of GDM ( OR = 1.19, 95% CI = 1.05-1.34; P < 0.05), even after adjusting for various factors. This increased risk for type AB was consistent across subgroup and sensitivity analyses. CONCLUSION The ABO blood types may influence GDM risk, with type AB associated with a higher risk. Incorporating it-either as a single risk factor or in combination with other known factors-could help identify individuals at risk for GDM before or during early pregnancy.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/etiology* ; ABO Blood-Group System ; Adult ; Prospective Studies ; Risk Factors ; Young Adult

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.

Objective To achieve intelligent recognition and segmentation of common craniocerebral inju-ries(hereinafter referred to as"segmentation")by training convolutional neural network DeepLabV3+model based on CT images of blunt craniocerebral injury(BCI),and to explore the value of deep learning in automated diagnosis of BCI in forensic medicine.Methods A total of 5 486 CT images of BCI from living persons were collected as the training set,validation set and test set for model training and performance evaluation.Another 255 CT images of BCI and 156 normal craniocerebral CT images from living persons were collected as the blind test set to evaluate the ability of the model to seg-ment the five types of craniocerebral injuries including scalp hematoma,skull fracture,epidural hema-toma,subdural hematoma,and brain contusion.Another 340 BCI and 120 normal craniocerebral CT images from cadavers were collected as the new blind test set to explore the application value of the model trained by living CT images in the segmentation of BCI in cadavers.The five types CT images of all BCI except the blind test set were manually labeled;then,each dataset was inputted into the model to train the model.The performance of the model was evaluated and optimized based on the loss function and accuracy curves of the training set and validation set,and the generalization ability was evaluated based on the Dice value of the test set.According to the accuracy,precision and F1 value of the blind test set,the segmentation performance of the model for five types of BCI was evaluated.Results After training and optimizing the model,the average Dice values of the final optimal model to scalp hematoma,skull fracture,epidural hematoma,subdural hematoma and brain contusion segmen-tation were 0.766 4,0.812 3,0.938 7,0.782 7 and 0.858 1,respectively,all greater than 0.75,meeting the expected requirements.External validation showed that the F1 values were 93.02%,89.80%,87.80%,92.93%and 86.57%in living CT images,respectively;83.92%,44.90%,76.47%,64.29%and 48.89%in cadaveric CT images,respectively.The above suggested that the model was able to accu-rately segment various types of craniocerebral injury on living CT images,while its segmentation ability was relatively poor on cadaveric CT images,but still able to accurately segment scalp hematoma,epidu-ral hematoma and subdural hematoma.Conclusion Deep learning model trained on CT images can be used for BCI segmentation.However,the direct use of living persons'BCI models for the identifica-tion of cadaveric BCI has some limitations.This study provides a new approach for intelligent segmen-tation of virtual anatomical data for BCI.

From the perspective of the physiological basis of liver and kidney sharing the common source in traditional Chinese medicine(TCM),and by integrating the theory of kidney dominating bone,liver dominating tendon,and meridian sinew of TCM as well as the bone resorption and collapse theory,and non-uniform settlement theory and lower-limb musculoskeletal bowstring structure theory of modern orthopedics,the pathogenesis of osteonecrosis of the femoral head(ONFH)under the system of non-uniform settlement during bone resorption and multidimensional composite bowstring working in coordination with the theory of liver-kidney and muscle-bone was explored.The key to the TCM pathogenesis of ONFH lies in the deficiency of the liver and kidney,and then the imbalance of kidney yin-yang leads to the disruption of the dynamic balance of bone formation and bone resorption mediated by osteoblasts-osteoclasts,which manifests as the elevated level of bone metabolism and the enhancement of focal bone resorption in the femoral head,and then leads to the necrosis and collapse of the femoral head.It is considered that the kidney dominates bone,liver dominates tendon,and the tendon and bone together constitute the muscle-bone-joint dynamic and static system of the hip joint.The appearance of collapse destroys the originally balanced muscle-bone-joint system.Moreover,the failure of liver blood in the nourishment of muscles and tendons further exacerbates the imbalance of the soft tissues around the hip joint,accelerates the collapse of the muscle-bone-joint dynamic and static system,speeds up the process of femoral head collapse,and ultimately results in irreversible outcomes.Based on the above pathogenesis,the systematic integrative treatment of ONFH should be based on the TCM holistic concept,focuses on the focal improvement of internal and external blood circulation of the femoral head by various approaches,so as to rebuild the coordination of joint function.Moreover,attention should be paid to the physical constitution of the patients,and therapy of tonifying the kidney and regulating the liver can be used to restore the balance between osteogenesis and osteoblastogenesis,and to reconstruct the muscle-bone-joint system,so as to effectively delay or even prevent the occurrence of ONFH.

Renal fibrosis is a common pathological manifestation of all chronic kidney diseases.Ferroptosis is closely related to the pathogenesis of renal fibrosis and can influence the onset of renal fibrosis,and it is the most critical step in the development of renal fibrosis.The paper describes the relationship between ferroptosis and renal fibrosis,discusses the research progress of ferroptosis on renal fibrosis,and further summarizes,analyzes,and describes the effective and highly targeted natural active ingredients of traditional Chinese medicines against ferroptosis,and concludes that the reversal of renal fibrosis is achieved through the regulation of the key targets of ferroptosis,with a view to providing a broad new direction for its prospects in the field of renal fibrotic disease prevention and treatment;and to provide a scientific guide for clinical treatment and basis for clinical treatment.

The working principle and development of flexible semiconductor devices based on organic field effect transistor(OFET)technology were introduced.The current research status of OFET-based wearable flexible monitoring devices were reviewed,including biomechanical monitoring devices,tattoo biomonitoring devices and cellular detection devices and etc.The deficiencies of OFET-based wearable flexible monitoring devices were analyzed,and it's pointed out that miniaturization,personalization and diversification were the directions for the development of the future OFET-based wearable flexible moni-toring devices.[Chinese Medical Equipment Journal,2024,45(1):93-100]

Objective To investigate the possible mechanism of Xuebijing injection in regulating abnormal degradation of pulmonary vascular endothelial calyx to improve acute lung injury induced by severe heatstroke.Methods Forty-eight Wistar rats were randomly divided into control group,heatstroke group and Xuebijing group.Before heatstroke induction,rats in Xuebijing group were administrated with Xuebijing injection(2 ml/kg,2 times/d)for 3 days.All rats were exposed to an environment with temperature of(40±2)℃and humidity of 65%±5%for 60 minutes to induce heatstroke.Two hours later,the lung wet/dry weight ratio was recorded;the concentration of proteins in BALF was measured;the pulmonary vascular permeability was measured by Evans blue(EB);HE staining was used to observe the pathological changes of lung tissue;the changes of hyaluronic acid(HA)on the surface of pulmonary vessels were observed by immunofluorescence;Western blotting was used to detect the expression of Syndecan-1,Glypican-1,VE-Cadherin,Occludin,VCAM-1 and E-selectin in lung tissues;Enzyme-linked immunosorbent assay(ELISA)was utilized to quantify the concentration of tumor necrosis factor-α(TNF-α),interleukin-6(IL-6)in serum and heparanase(HPA)in lung tissue.Results Xuebijing could decrease the lung wet/dry weight ratio,reduce protein exudation and improve pulmonary vascular permeability(P<0.01);reduce the histological injury(P<0.01);reduce the degradation of HA,Syndecan-1 and Glypican-1 on the surface of pulmonary vessels(P<0.01);increase the expression of VE-Cadherin and Occludin(P<0.01);regulate the overexpression of VCAM-1 and E-selectin(P<0.01);down-regulate the expression of TNF-α,IL-6 and HPA(P<0.01).Conclusion Xuebijing injection decrease the expression of HPA,improve the disintegration of pulmonary vascular endothelial calyx,repair the integrity of pulmonary vessels,reduce the damage of cell connections,down-regulate the expression of adhesion molecules,inhibit the inflammatory reaction,relieving acute lung injury caused by severe heat stroke.

To investigate the relationship between male semen parameters and sperm DNA fragment index with age. Adopt cross-sectional sampling survey design, 3 203 male patients who visited the Department of Reproductive Andrology in the Third Affiliated Hospital of Zhengzhou University from January 2019 to June 2021 were selected as subjects. Age range is 18-57 years, with the median age of 30 years. Through quartile regression analysis, the correlation between age and different male semen parameters and DNA fragment index (DFI) was presented. The study population was divided into ≤30 years old group and >30 years old group, and the correlation between age and semen volume, sperm concentration, total sperm count, progressive motility, total motility, percentage of normal sperm and DFI level were compared and analyzed. The results showed that there were significant differences in progressive motility, total motility and DFI level among different age groups (χ²=-4.608, -4.604, -7.719,P all <0.05), but there was no significant difference in semen volume, sperm concentration, total sperm count and percentage of normal sperm (χ²=-1.712, -1.203, -0.149, -0.175,P all >0.05). In the>30 years old age group, there was a very weak negative correlation between male age and semen volume, progressive motility and total motility (r=-0.137, -0.101 and -0.056, P all <0.05). There was a very weak positive correlation between male age and sperm concentration and sperm DFI level (r=0.061, 0.190, P all <0.05), while there was no correlation between male age and total sperm count and percentage of normal sperm (r=-0.018, -0.016,P all >0.05). In conclusion, with the increase of age, especially after the age of 30, semen volume, progressive motility and total motility decreased, while sperm concentration and DFI level increased, and semen quality decreased.
Humans ; Male ; Adult ; Adolescent ; Young Adult ; Middle Aged ; Semen ; Semen Analysis ; Cross-Sectional Studies ; Infertility, Male/genetics* ; Sperm Motility ; DNA Fragmentation ; Spermatozoa ; Sperm Count ; DNA

To investigate the relationship between male semen parameters and sperm DNA fragment index with age. Adopt cross-sectional sampling survey design, 3 203 male patients who visited the Department of Reproductive Andrology in the Third Affiliated Hospital of Zhengzhou University from January 2019 to June 2021 were selected as subjects. Age range is 18-57 years, with the median age of 30 years. Through quartile regression analysis, the correlation between age and different male semen parameters and DNA fragment index (DFI) was presented. The study population was divided into ≤30 years old group and >30 years old group, and the correlation between age and semen volume, sperm concentration, total sperm count, progressive motility, total motility, percentage of normal sperm and DFI level were compared and analyzed. The results showed that there were significant differences in progressive motility, total motility and DFI level among different age groups (χ²=-4.608, -4.604, -7.719,P all <0.05), but there was no significant difference in semen volume, sperm concentration, total sperm count and percentage of normal sperm (χ²=-1.712, -1.203, -0.149, -0.175,P all >0.05). In the>30 years old age group, there was a very weak negative correlation between male age and semen volume, progressive motility and total motility (r=-0.137, -0.101 and -0.056, P all <0.05). There was a very weak positive correlation between male age and sperm concentration and sperm DFI level (r=0.061, 0.190, P all <0.05), while there was no correlation between male age and total sperm count and percentage of normal sperm (r=-0.018, -0.016,P all >0.05). In conclusion, with the increase of age, especially after the age of 30, semen volume, progressive motility and total motility decreased, while sperm concentration and DFI level increased, and semen quality decreased.
Humans ; Male ; Adult ; Adolescent ; Young Adult ; Middle Aged ; Semen ; Semen Analysis ; Cross-Sectional Studies ; Infertility, Male/genetics* ; Sperm Motility ; DNA Fragmentation ; Spermatozoa ; Sperm Count ; DNA