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.

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.

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]

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.

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.

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.

OBJECTIVE: To observe the clinical effect and safety of acupuncture in treatment of neck pain due to cervical spondylosis. METHODS: According to the patients' preference and acceptance for the interventions of neck pain induced by cervical spondylosis, an acupuncture group (221 cases) and a non-acupuncture group (251 cases) were divided. After the control of confounding factors with propensity score matching, 218 cases were included in either acupuncture group or non-acupuncture group. In the acupuncture group, acupuncture was applied to Dazhui (GV 14), Baihui (GV 20), ashi points, bilateral neck-Jiaji (EX-B 2), Fengchi (GB 20), Houxi (SI 3), Shenmai (BL 62), etc. The treatment was given once daily, one course of intervention was composed of 5 treatments and 3 courses were included. In the non-acupuncture group, the oral administration of imrecoxib tablets and cobalt tablets was prescribed for 2 weeks. Before and after treatment, the scores of Northwick Park questionnaire (NPQ) and the simplified McGill pain questionnaire (SF-MPQ) were observed, and the safety was assessed in patients of the two groups. RESULTS: After treatment completion, the scores of NPQ and SF-MPQ were all reduced when compared with those before treatment in each group (P<0.001), and the scores of NPQ and SF-MPQ in the acupuncture group were lower than those of the non-acupuncture group (P<0.001). The incidence of adverse reactions was 6.0% (13/218) in the acupuncture group and was 10.1% (22/218) in the non-acupuncture group, without statistical significance in comparison (P>0.05). CONCLUSION Acupuncture is effective and safe in the relief of neck pain and the improvement of comprehensive quality of life in the patients with cervical spondylosis.
Humans ; Neck Pain/therapy* ; Propensity Score ; Quality of Life ; Acupuncture Points ; Acupuncture Therapy ; Spondylosis/therapy* ; Treatment Outcome

Objective: To analyze the incidence of preterm birth based on pre-pregnancy body mass index (BMI) stratification and explore the associated factors of preterm birth among pregnant women at different BMI stratifications. Methods: From February 2018 to December 2020, pregnant women who participated in China Birth Cohort Study (CBCS) and gave birth at Beijing Obstetrics and Gynecology Hospital were enrolled as the study subjects. Electronic Data Capture System and standard structured questionnaires were used to collect data related to pre-pregnancy, pregnancy, and delivery for pregnant women. Pregnant women were divided into the low-weight group, normal-weight group and overweight group based on their pre-pregnancy BMI. A Cox proportional hazards model was used to analyze the associated factors of preterm birth among pregnant women with different BMI before pregnancy. Results: A total of 27 195 singleton pregnant women were included, with a preterm birth rate of 5.08% (1 381/27 195). The preterm birth rates in the low-weight group, normal-weight group and overweight group were 4.29% (138/3 219), 4.63% (852/18 390) and 7.00% (391/5 586) respectively (P<0.001). After adjusting for relevant factors, the Cox proportional hazards model showed that the risk of preterm birth in the overweight group was 1.457 times higher than that in the normal-weight group (95%CI: 1.292-1.643). Preeclampsia-eclampsia (HR=2.701, 95%CI: 1.318-5.537) was the associated factor for preterm birth in the low-weight group. Advanced maternal age (HR=1.232, 95%CI: 1.054-1.441), history of preterm birth (HR=4.647, 95%CI: 3.314-6.515), vaginal bleeding in early pregnancy (HR=1.613, 95%CI: 1.380-1.884), and preeclampsia-eclampsia (HR=3.553, 95%CI: 2.866-4.404) were associated factors for preterm birth in the normal-weight group. Advanced maternal age (HR=1.473, 95%CI: 1.193-1.818), history of preterm birth (HR=3.209, 95%CI: 1.960-5.253), vaginal bleeding in early pregnancy (HR=1.636, 95%CI: 1.301-2.058), preeclampsia-eclampsia (HR=2.873, 95%CI:2.265-3.643), and pre-gestational diabetes mellitus (HR=1.867, 95%CI: 1.283-2.717) were associated factors for preterm birth in the overweight group. Conclusion: Pre-pregnancy overweight is an associated factor for preterm birth, and there are significant differences in the associated factors of preterm birth among pregnant women with different BMI before pregnancy.
Pregnancy ; Infant, Newborn ; Female ; Humans ; Body Mass Index ; Overweight/epidemiology* ; Premature Birth/epidemiology* ; Pre-Eclampsia/epidemiology* ; Cohort Studies ; Eclampsia ; Incidence ; Risk Factors ; Thinness/epidemiology*