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

Objective:To understand the current situation of the quality of life of medical staff in the context of responding to public health emergencies and discuss its influencing factors,so as to scientifically mobilize the enthusiasm and stability of medical staff in response to public health emergencies and promote the new quality productivity of the medical system under public crises. Methods:The convenient sampling and snowball-sampling were used to investigate medical staff with using World Health Organization Quality of Life Brief Scale,the Utrecht Work Engagement Scale and the Practice Environment Scale,and establish decision tree and neural network models to analyze the factors affecting the quality of life of medical staff. Results:Quality of life of medical staff was (62.61±14.99). The practice environment,work engagement,work willingness,educational background had influence on the quality of life of medical staff (P<0.05),and the influence degree was gradually reduced by the results of the neural network model. Conclusion:The quality of life of medical staff is not high. The practice environment,the work engagement,work willingness is the main influencing factor. Two models have their advantages and disadvantages,which combined use makes the results more meaningful.

Objective:To assess the diagnostic efficiency of 18F-FDG PET for Alzheimer′s disease (AD) in patients with memory impairment. Methods:A retrospective analysis was conducted on 96 patients (40 males, 56 females, age: 69.0(62.8, 74.0) years) initially diagnosed with memory impairment in Renji Hospital, School of Medicine, Shanghai Jiao Tong University between August 2019 and September 2023. The amyloid-tau-neurodegeneration (ATN) criteria, based on 18F-AV45+ 18F-PI-2620 PET/CT+ MRI imaging results, were used as the diagnostic standard for AD. Visual analysis (temporoparietal or posterior cingulate cortex (PCC) hypometabolism) and semi-quantitative analysis methods (PET-SCORE and NeuroQ software analysis (SUV ratio, SUVR)) were applied to evaluate the diagnostic efficiency of 18F-FDG PET imaging for AD. Diagnostic efficiencies of visual assessment and semi-quantitative parameters were compared by χ2 test. Additionally, Pearson correlation analysis was performed to examine the relationship between results of PET-SCORE and cognitive scales. Results:Of the 96 patients initially diagnosed with memory impairment, 61 were clinically diagnosed with AD, while 35 were non-AD patients. Visual assessment of temporoparietal hypometabolism showed the highest sensitivity (91.80%, 56/61), which was significantly different from the sensitivities of PET-SCORE (40.98%(25/61); χ2=29.03, P<0.001) and visual assessment of PCC hypometabolism (77.05%(47/61); χ2=5.82, P=0.016). While semi-quantitative assessment using PET-SCORE demonstrated the highest specificity (100%, 35/35), which was significantly different from the specificities of visual assessment methods (temporoparietal hypometabolism: 17.14%(6/35), χ2=27.03, P<0.001; PCC hypometabolism: 54.29%(19/35), χ2=14.06, P<0.001). PET-SCORE exhibited statistically significant correlations with Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Activities of Daily Living (ADL) scores ( r values: -0.38, -0.36, 0.31, all P<0.01). Conclusions:Among patients initially diagnosed with memory impairment, visual assessment in 18F-FDG PET imaging analysis demonstrates higher sensitivity, while semi-quantitative analysis using PET-SCORE exhibits higher specificity. PET-SCORE shows statistically significant correlation with the severity of cognitive decline.

Objective:To evaluate the values of 18F-PI-2620 PET/CT brain imaging with SUV ratio (SUVR) in the assessment of tau protein deposition in the brain of patients with different cognitive disorders and its correlation with cognition. Methods:This was a cross-sectional study. From December 2019 to November 2022, a total of 67 subjects including 54 patients with Alzheimer′s disease (AD; 21 males, 33 females, age (68.6±7.8) years), 7 patients with mild cognitive impairment (MCI; 1 male, 6 females, age (63.1±11.2) years) and 6 healthy controls (HC; 4 males, 2 females, age (69.0±5.8) years) were enrolled retrospectively in Renji Hospital. All participants were examined by 18F-PI-2620 PET/CT. SUVRs of brain regions were obtained, including frontal lobe, temporal lobe, occipital lobe, parietal lobe, insular lobe, whole brain, as well as 10 independent brain ROIs (amygdala, orbitofrontal cortex, cingulate gyrus, superior occipital gyrus, superior parietal gyrus, inferior angular gyrus, precuneus, inferior temporal gyrus, entorhinal cortex and parahippocampal gyrus), with inferior cerebellum cortex as the reference region. All participants were estimated by cognitive scales(mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA)). One-way analysis of variance and the least significant difference t test were used to compare the differences of SUVR in each brain region among HC, MCI and AD groups. ROC curve analysis was used to determine the optimal cut-off values of SUVR in each brain region for the differential diagnosis of AD-MCI and AD-HC. Pearson correlation analysis was employed to examine the correlations of SUVR with cognitive scale scores. Results:The SUVR of whole brain was 1.40±0.31 in AD group, 1.08±0.19 in MCI group, and 1.01±0.12 in HC group. SUVR analysis in the whole brain and each brain region could distinguish AD from HC, AD from MCI ( F values: 1.76-10.09, t values: 2.98-7.47, all P<0.05), but could not distinguish HC from MCI ( t values: 0.17-1.53, all P>0.05). ROC curve analysis showed that the best cut-off value of SUVR was 1.18 for whole brain (AUC=0.89), 1.13 for amygdala (AUC=0.94) and 1.26 for parahippocampal gyrus (AUC=0.94) for differential diagnosis of AD and HC, which was 1.06 for whole brain (AUC=0.82), 1.18 for amygdala (AUC=0.88) and 1.28 (AUC=0.88) for infratemporal gyrus to differential diagnosis of AD and MCI. SUVRs of the whole brain, frontal, occipital, parietal, temporal and insula were significantly negatively correlated with MMSE and MoCA cognitive scale scores ( r values: from -0.64 to -0.40, all P<0.05). Conclusions:SUVR quantitative analysis in 18F-PI-2620 PET imaging can assist the differential diagnosis of AD and HC, AD and MCI. The SUVRs of whole brain and five lobes show negative correlations with MMSE and MoCA scores.

Objective:To understand the current situation of the quality of life of medical staff in the context of responding to public health emergencies and discuss its influencing factors,so as to scientifically mobilize the enthusiasm and stability of medical staff in response to public health emergencies and promote the new quality productivity of the medical system under public crises. Methods:The convenient sampling and snowball-sampling were used to investigate medical staff with using World Health Organization Quality of Life Brief Scale,the Utrecht Work Engagement Scale and the Practice Environment Scale,and establish decision tree and neural network models to analyze the factors affecting the quality of life of medical staff. Results:Quality of life of medical staff was (62.61±14.99). The practice environment,work engagement,work willingness,educational background had influence on the quality of life of medical staff (P<0.05),and the influence degree was gradually reduced by the results of the neural network model. Conclusion:The quality of life of medical staff is not high. The practice environment,the work engagement,work willingness is the main influencing factor. Two models have their advantages and disadvantages,which combined use makes the results more meaningful.

OBJECTIVE: To compare the efficiency and effect of establishing rat peri-implantitis model by traditional cotton thread ligation and local injection of Porphyromonas gingivalis lipopolysaccharide (LPS) around the implant, as well as the combination of the two methods. METHODS: Left side maxillary first molars of 39 male SD rats were extracted, and titanium implants were implanted after four weeks of healing. After 4 weeks of implant osseointegration, 39 rats were randomly divided into 4 groups. Cotton thread ligation (n=12), local injection of LPS around the implant (n=12), and the two methods combined (n=12) were used to induce peri-implantitis, the rest 3 rats were untreated as control group. All procedures were conducted under 5% isoflurane inhalation anesthesia. The rats were sacrificed 2 weeks and 4 weeks after induction through carbon dioxide asphyxiation method. The maxilla of the rats in the test groups were collected and marginal bone loss was observed by micro-CT. The gingival tissues around the implants were collected for further real time quantitative PCR (RT-qPCR) analysis, specifically the expression of tumor necrosis factor-alpha (TNF-α) as well as interleukin-1β (IL-1β). The probing depth (PD), bleeding on probing (BOP) and gingival index (GI) of each rat in the experimental group were recorded before induction of inflammation and before death. RESULTS: After 4 weeks of implantation, the osseointegration of implants were confirmed. All the three test groups showed red and swollen gums, obvious marginal bone loss around implants. After 2 weeks and 4 weeks of inflammation induction, PD, GI and BOP of the three test groups increased compared with those before induction, but only BOP was statistically significant among the three test groups (P < 0.05). At the end of 2 weeks of inflammation induction, marginal bone loss was observed at each site in the cotton thread ligation group and the combined group. At each site, the bone resorption in the combined group was greater than that in the cotton thread ligation group, but the difference was not statistically significant (P > 0.05), bone resorption was observed at some sites of some implants in LPS local injection group. At the end of 4 weeks of inflammation induction, marginal bone loss was observed at all sites in each group. The marginal bone loss in the cotton thread ligation group and the combined group was greater than that in the LPS local injection group, and the difference was statistically significant (P < 0.05). At the end of 2 weeks and 4 weeks of induction, the expression of TNF-α and IL-1β in the test groups were higher than those in the control group (P < 0.05). CONCLUSION Compared with local injection of LPS around the implant, cotton thread ligature and the two methods combined can induce peri-implantitis in rats better and faster.
Animals ; Male ; Rats ; Alveolar Bone Loss/etiology* ; Dental Implants/adverse effects* ; Inflammation ; Lipopolysaccharides ; Peri-Implantitis/pathology* ; Rats, Sprague-Dawley ; Tumor Necrosis Factor-alpha

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*

Objective: To explore the association between coagulation function indicators and placental abruption (PA) in different trimesters of pregnancy among preeclampsia-eclampsia pregnant women. Methods: From February 2018 to December 2020, pregnant women who participated in the China birth cohort study and were diagnosed with preeclampsia, eclampsia and chronic hypertension with superimposed preeclampsia in Beijing Obstetrics and Gynecology Hospital were enrolled in this study. The baseline and follow-up information were collected by questionnaire survey, and the coagulation function indicators in the first and third trimesters were obtained through medical records. The Cox proportional hazards model was used to analyze the association between the coagulation function indicators and PA. A restrictive cubic spline curve was used to draw the dose-response curve between the relevant coagulation function indicators and PA. Results: A total of 1 340 participants were included in this study. The age was (32.50±4.24) and the incidence of PA was 4.4% (59/1 340). After adjusting for relevant factors, Cox proportional hazards model showed that compared with the high-level classification of fibrinogen (FIB), participants within the middle-(HR=3.28, 95%CI: 1.27-8.48) and low-level (HR=3.84, 95%CI: 1.40-10.53) classification during the first trimester and within the low-level classification (HR=4.18, 95%CI: 1.68-10.39) during the third trimester were more likely to experience PA. Compared with the middle-level classification of pro-thrombin time (PT), the risk of PA in the participants within the low-level classification (HR=2.67, 95%CI: 1.48-4.82) was significantly higher in the third trimester. The restrictive cubic spline analysis showed a linear negative association between FIB and PA in the first and third trimesters, while PT and PA showed an approximately L-shaped association . Conclusion: Among pregnant women diagnosed with preeclampsia-eclampsia, the middle-and low-level classification of FIB in the first and third trimesters and the low-level classification of PT in the third trimester could increase the risk of PA.
Pregnancy ; Female ; Humans ; Pre-Eclampsia/diagnosis* ; Abruptio Placentae/epidemiology* ; Pregnant Women ; Eclampsia ; Cohort Studies ; Placenta

With the expansion of mpox virus infection from endemic to a global epidemic in 2022, the WHO declared that the mpox event constituted a Public Health Emergency of International Concern. Due to the high degree of gene sequence similarity among orthopox viruses and cross-reactive antibodies induced by orthoviruses, smallpox vaccination may affect the immune response induced by mpox virus infection. The analysis of the protective effects of smallpox vaccination against mpox virus infection will help define the focus of prevention and control. In this review, we clarify the protection of the smallpox vaccine against mpox virus infection by analyzing the correlation between smallpox vaccination, immune response status, and clinical data and providing evidence for the prevention, control, and strategies of mpox epidemics.
Humans ; Smallpox/epidemiology* ; Monkeypox/drug therapy* ; Smallpox Vaccine/therapeutic use* ; Vaccination ; Immunity

Humans ; Consensus ; Hypersensitivity ; Desensitization, Immunologic/adverse effects* ; Immunotherapy/adverse effects* ; Injections, Subcutaneous ; Allergens