Tet (ten-eleven translocation) proteins belong to α-ketoglutaric acid (α-KG or 2-OG) and Fe2+ dependent dioxygenases. Tets are found to be involved in the unique mammalian DNA active demethylation process by specifically oxidizing the methyl group of 5-methylcytosine (5mC) in mammalian genome, and play critical roles in gene regulation in early embryonic development and stem cell differentiation via regulating the dynamic balance distribution of 5mC. Abnormal expression and function of Tets are closely associated with various hematological malignances, including myelodysplastic syndrome, chronic myelomonocytic leukemia, and acute lymphoblastic leukemia, as well as solid tumors. Hence, Tets and Tets-mediated DNA demethylation are novel anti-tumor drug targets. Investigation of biological function and catalytic mechanism of Tets is helpful for further understanding mechanisms of tumor incidence and development relevant to DNA demethylation pathway and can provide reference for developing new anti-tumor targeted drugs.

Objective: To explore whether the pro-inflammatory effect of endoplasmic reticulum stress in placental tissues involves in the genesis of gestational diabetes mellitus (GDM). Methods: Forty gravidas who underwent regular prenatal examinations and delivered at Tongji Hospital were recruited from January to December, 2016. Among them, 20 were GDM women (GDM group), and the remaining twenty were served as the control, which were selected from those without GDM and matched for age and gestational weeks to the GDM group. Placental tissues were collected from the two groups. The ultrastructure of endoplasmic reticulum in trophoblast cells was observed under transmission electron microscope. The expression of glucose-regulated protein-78 (GRP-78), a marker protein for endoplasmic reticulum stress, and C/EBP homologous protein (CHOP) were detected using Western blotting. Five placental tissue samples were collected from normal gravidas for explant culture. Three subgroups were set up according to different culturing methods including culturing with IL-1β (5 ng/ml) for 20 h (IL-1β model group), 30 μmol/L thapsigargin (TG, an endoplasmic reticulum stress agonist) for 2 h after treating with IL-1β (5 ng/ml) for 18 h (IL-1β+TG intervention group) or with no stimulation (blank control group). Western blotting was used to detect the expressions of GRP-78, CHOP and glucose transporter 4 (GLUT4) in placenta explants. The mRNA expressions of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) were determined by real-time fluorescence quantitative polymerase chain reaction (RT-PCR). Statistical analysis was performed using one-way analysis of variance, LSD and t test. Results: (1) In the GDM group, increased number and size of endoplasmic reticulum cisternae were observed in trophoblast cells. Moreover, obviously dilated endoplasmic reticulum and different size of fragments and vesicles were also seen under electron microscope. While the endoplasmic reticulum in the placental tissues of the control group showed no obvious swelling. (2) The expression of GRP-78 and CHOP protein in the GDM group were higher than those in the control group (0.90±0.17 vs 0.48±0.08, t=2.24; 0.85±0.13 vs 0.46±0.12, t=2.10; both P<0.05). (3) Compared with the blank control group, the expression of GRP-78 and CHOP protein in the IL-1β model group increased significantly (0.87±0.18 vs 0.36±0.07, t=2.67; 1.14±0.09 vs 0.78±0.06, t=3.20; both P<0.05); but the expression of GLUT4 protein significantly decreased (1.00±0.14 vs 2.21±0.49, t=2.40, P<0.05); the expressions of IL-6 and TNF-α mRNA significantly increased (0.89±0.23 vs 0.30±0.06, t=2.31; 0.62±0.16 vs 0.17±0.09, t=2.29; both P<0.05). Compared with the IL-1β model group, the expression of GRP-78 and CHOP protein significantly increased in IL-1β+TG group (2.02±0.32 vs 0.87±0.18, t=3.11; 2.18±0.31 vs 1.14±0.09, t=3.16; both P<0.05); the expression of GLUT4 protein significantly decreased (0.39±0.19 vs 1.00±0.14, t=2.66, P<0.05); the expression of IL-6 and TNF-α mRNA increased significantly (1.67±0.25 vs 0.89±0.23, t=2.26; 1.42±0.27 vs 0.62±0.16, t=2.51; both P<0.05). Conclusions Endoplasmic reticulum stress may be associated with increased release of pro-inflammatory cytokines in placental tissues of some GDM women and involved in the onset and development of GDM.

Objective:To investigate the effect of sarcopenia on the perioperative clinical outcomes of esophageal squamous cell carcinoma (ESCC).Methods:The retrospective case-control study was conducted. The clinicopathological data of 1 148 ESCC patients who were admitted to the Affiliated Huaian No.1 People′s Hospital of Nanjing Medical University from January 2020 to December 2021 were collected. There were 789 males and 359 females, aged (67±7)years. All patients under-went thoracoscopic and laparoscopic radical esophagectomy for esophageal cancer. Observation indicators: (1) incidence of sarcopenia in patients with ESCC; (2) comparison of general data between ESCC patients complicated with sarcopenia and those without sarcopenia; (3) comparison of clinical outcomes between ESCC patients complicated with sarcopenia and those without sarcopenia; (4) analysis of influencing factors for sarcopenia in ESCC patients. Measurement data of normal distri-bution were represented by Mean± SD, and comparison between groups was conducted using the t test. Count data were represented as absolute numbers, and comparison between groups was conducted using the chi-square test. Ordinal data was analyzed using the Mann-Whitney U test. Logistic regression analysis was used to conduct univariate analysis. Logistic backward stepwise regression model was used to conduct multivariate analysis. Results:(1) Incidence of sarcopenia in patients with ESCC. Among 1 148 ESCC patients, 469 cases were complicated with sarcopenia, 679 were without sarcopenia. The incidence of sarcopenia was 40.854%(469/1 148). Among the 469 patients with sarcopenia, there were 313 males and 156 females. There were 125 cases <65 years old, 145 cases ≥65 years old but <70 years old, 106 cases ≥70 years old but<75 years old, 93 cases ≥75 years old, respectively. (2) Comparison of general data between patients with ESCC complicated with sarco-penia and those without sarcopenia. The age, tumor diameter, body mass index, cases in stage T1, T2, T3, preoperative albumin, preoperative serum prealbumin, psoas muscle index, psoas muscle density were (68±7)years, (3.3±1.5)cm, (22.4±2.9)kg/m 2, 100, 105, 264, (43±4)g/L, (193±38)mg/dL, (3.9±0.8)cm 2/m 2, (48±8)HU of 469 ESCC patients complicated with sarcopenia, versus (66±7)years, (3.2±1.4)cm, (23.8±3.0)kg/m 2, 173, 170, 336, (44±4)g/L, (206±37)mg/dL, (6.0±2.2)cm 2/m 2, (50±7)HU of 679 ESCC patients without sarcopenia, showing significant differences between the two groups ( t=5.74, 2.11, 7.57, Z=-2.93, t=2.25, 5.52,20.36, 4.18, P<0.05). (3) Comparison of clinical outcomes between patients with ESCC complicated with sarcopenia and those without sarcopenia. The duration of postoperative hospital stay, cases with postoperative hospital stay>30 days, pneumonia, acute respiratory failure, anastomotic fistula, and abnormal heart rhythm were (17±9)days, 32, 158, 39, 33, and 103 of 469 ESCC patients complicated with sarcopenia, respectively, versus (15±6)days, 15, 102, 18, 19, and 85 of 679 ESCC patients without sarcopenia, showing significant differences between the two groups ( t=4.89, χ2=15.04, 55.17, 18.86, 11.52, 18.06, P<0.05). (4) Analysis of influencing factors for sarcopenia in ESCC patients. Results of multivariate analysis showed that age ≥65 years was an independent risk factor for sarcopenia in ESCC patients ( odds ratio=1.64, 95% confidence interval as 1.26-2.14, P<0.05). Preoperative serum prealbumin ≥200 mg/dL, psoas muscle density ≥48 HU and body mass index >24 kg/m 2 were independent protective factors for sarcopenia in ESCC patients ( odds ratio=0.64, 0.72, 0.53, 95% confidence interval as 0.50-0.82, 0.56-0.92, 0.41-0.69, P<0.05). Conclusions:Age ≥65 years is an independent risk factor for sarcopenia in ESCC patients. Preoperative serum prealbumin ≥200 mg/dL, psoas muscle density ≥48 HU and body mass index >24 kg/m 2 are independent protective factors for sarcopenia in ESCC patients. Compared with patients without sarcopenia, ESCC patients with sarcopenia are more prone to postoperative compli-cations such as pneumonia, acute respiratory failure, anastomotic fistula, and arrhythmia, and have a longer postoperative hospital stay.

Objective To investigate the recognition efficiency of AI model based on deep learning for cardiac conduction system(CCS).Methods HE staining sections of cardiac muscle and CCS of 17 cases of non-sudden death were selected,and the gold standard was unanimous recognition by 2 forensic pathologists with more than 20 years of CCS diagnosis experience.Inception V3 algorithm was used to establish AI model and complete CCS identification training and testing.Confusion matrix,accuracy,precision,recall,F1 score,ROC curve and AUC value were used to evaluate the effectiveness of AI model,and accuracy,sensitivity and specificity were used to evaluate the efficiency of manual independent and AI-assisted manual recognition for CCS.Results The accuracy of AI model was 87.3%,the precision was 91.9%,the recall was 81.9%,the F1 score was 86.6%,and the AUC value was 95.3%.The accuracy of AI model was higher than that of senior forensic pathologists.There was no statistical significance in the accuracy of AI-assisted senior forensic pathologists in identifying CCS compared with manual independent detection(P>0.05),while the accuracy of AI-assisted intermediate and junior forensic pathologists in identifying CCS was increased by 8%and 14.33%,respectively,with statistical significance(P<0.05).The accuracy rate of AI-assisted junior forensic pathologists to identify CCS was higher than that of intermediate forensic pathologists in self-diagnosis.Conclusion The AI model could be used for the automatic recognition of CCS,and could improve the diagnostic efficiency of CCS and narrow the gap between the forensic pathologists with low experience and that with high experience.

Objective The diagnosis of nasal fractures poses challenges in forensic clinical evaluation.This study aims to develop and enhance an artificial intelligence-based model for nasal fracture recognition,evaluate its performance,and provide assistance and support for forensic clinical identification.Methods Multi-center nasal CT images were selected and screened according to the consensus standards set by Chinese experts in nasal CT examination and diagnosis.A recognition model was constructed,followed by external verification and evaluation.Additionally,the diagnostic capabilities of qualified appraisers/doctors with different professional titles(primary,intermediate,and senior)were compared with the performance of the intelligent recognition model.The accuracy,sensitivity,specificity),and negative predictive value(NP)of the intelligent recognition model were comprehensively evaluated.Results The intelligent recognition model exhibited high diagnostic efficiency and stability.It improved the diagnostic accuracy of radiologists and appraisers in detecting nasal fractures while effectively bridging the gap between inexperienced doctors/appraisers and experienced ones.Conclusion The intelligent recognition model for nasal fractures can assist appraisers in enhancing their ability to locate such fractures on CT images and improve work efficiency while enhancing appraisal opinions'accuracy and scientificity.

Objective To conduct a comprehensive visual analysis of the application of Artificial Intelligence(AI)in forensic medicine using bibliometric tools so as to create knowledge maps of cooperation network,research hotspots,important findings,and potential future trends in this field.Methods The Web of Science(WoSCC)was utilized as the primary data source,search formula incorporating AI and forensic medicine as core subject words was constructed,resulting in a dataset comprising 2 287 literature records.Vosviewer,Citespace,and Bibliometrix were employed for analyzing various aspects such as cooperation network,keyword co-occurrence networks,clustering dynamics,clusters,centrality degree and thematic strategic coordinate charts.These analyses facilitated the creation of corresponding visual maps.Results The collaboration among authors still requires further strengthening;however significant groups have emerged among institutions and countries.Research hotspots and important findings predominantly revolve around algorithmic applications.Furthermore,"identification"related research appears to become a prominent future research trend.Conclusion By employing bibliometric analysis techniques on the application of artificial intelligence in forensic medicine domain,this study successfully elucidats cooperation networks,research hotspots,important findings,future research directions,and provides objective support through empirical evidence for related studies.

Melatonin receptor 1B (MT2, encoded by the MTNR1B gene), a high-affinity receptor for melatonin, is associated with glucose homeostasis including glucose uptake and transport. The rs10830963 variant in the MTNR1B gene is linked to glucose metabolism disorders including gestational diabetes mellitus (GDM); however, the relationship between MT2-mediated melatonin signaling and a high birth weight of GDM infants from maternal glucose abnormality remains poorly understood. This article aims to investigate the relationship between rs10830963 variants and GDM development, as well as the effects of MT2 receptor on glucose uptake and transport in trophoblasts. TaqMan-MGB (minor groove binder) probe quantitative real-time polymerase chain reaction (qPCR) assays were used for rs10930963 genotyping. MT2 expression in the placenta of GDM and normal pregnant women was detected by immunofluorescence, western blot, and qPCR. The relationship between MT2 and glucose transporters (GLUTs) or peroxisome proliferator-activated receptor γ (PPARγ) was established by western blot, and glucose consumption of trophoblasts was measured by a glucose assay kit. The results showed that the genotype and allele frequencies of rs10830963 were significantly different between GDM and normal pregnant women (P<0.05). The fasting, 1-h and 2-h plasma glucose levels of G-allele carriers were significantly higher than those of C-allele carriers (P<0.05). Besides, the protein and messenger RNA (mRNA) expression of MT2 in the placenta of GDM was significantly higher than that of normal pregnant women (P<0.05). Melatonin could stimulate glucose uptake and GLUT4 and PPARγ protein expression in trophoblasts, which could be attenuated by MT2 receptor knockdown. In conclusion, the rs10830963 variant was associated with an increased risk of GDM. The MT2 receptor is essential for melatonin to raise glucose uptake and transport, which may be mediated by PPARγ.
Female ; Humans ; Pregnancy ; Blood Glucose/metabolism* ; Diabetes, Gestational/metabolism* ; Glucose/metabolism* ; Melatonin/metabolism* ; Polymorphism, Genetic ; PPAR gamma ; Receptor, Melatonin, MT2/genetics*