Objective:To investigate the predictive value of transabdominal uterine electromyography for pre-term labor after tocolysis in women with threatened preterm labor.Methods:A total of 48 pregnant women at 28-34 weeks of gestation diagnosed with threatened preterm labor and admitted to The Fourth Affiliated Hospital of Soo-chow University from January to September 2023 were included.According to the response to tocolysis and whether the pregnancy was prolonged for at least 48 h,women were divided into two groups:non-preterm birth within 48 h(n=35)and preterm birth within 48 h(n=13).Uterine electromyography parameters and difference were compared before and after tocolytic therapy in two groups.Univariate Logistic regression was performed to predict the related factors of preterm birth within 48 h after the using of tocolysis in pregnant women with threat-ened preterm birth by uterine electromyography,and receiver operating characteristic(ROC)curve was per-formed to evaluate their performance.Results:Compared to before treatment with tocolysis,after therapy,in the non-preterm birth within 48 h group,significant reductions in contraction frequency,area,duration and amplitude were observed(P<0.05).In the preterm birth within 48 h group,only contraction frequency decreased significant-ly(P<0.05).Univariate Logistic regression indicated that contraction frequency,contraction duration,and contrac-tion area were predictive factors for premature birth within 48 h after tocolysis(P<0.05).When the duration of u-terine contractions lasting for 104.55 s or more the sensitivity and specificity of predicting premature birth within 48 h are 92.3％and 68.6％,respectively.Conclusions:Uterine electromyography may predict the premature birth within 48 h after tocolytic treatment in preterm labor,which may provide reference for subsequent corticosteroid therapy or transfer of high-risk pregnant patients.

Objective:To investigate the predictive value of transabdominal uterine electromyography for pre-term labor after tocolysis in women with threatened preterm labor.Methods:A total of 48 pregnant women at 28-34 weeks of gestation diagnosed with threatened preterm labor and admitted to The Fourth Affiliated Hospital of Soo-chow University from January to September 2023 were included.According to the response to tocolysis and whether the pregnancy was prolonged for at least 48 h,women were divided into two groups:non-preterm birth within 48 h(n=35)and preterm birth within 48 h(n=13).Uterine electromyography parameters and difference were compared before and after tocolytic therapy in two groups.Univariate Logistic regression was performed to predict the related factors of preterm birth within 48 h after the using of tocolysis in pregnant women with threat-ened preterm birth by uterine electromyography,and receiver operating characteristic(ROC)curve was per-formed to evaluate their performance.Results:Compared to before treatment with tocolysis,after therapy,in the non-preterm birth within 48 h group,significant reductions in contraction frequency,area,duration and amplitude were observed(P<0.05).In the preterm birth within 48 h group,only contraction frequency decreased significant-ly(P<0.05).Univariate Logistic regression indicated that contraction frequency,contraction duration,and contrac-tion area were predictive factors for premature birth within 48 h after tocolysis(P<0.05).When the duration of u-terine contractions lasting for 104.55 s or more the sensitivity and specificity of predicting premature birth within 48 h are 92.3％and 68.6％,respectively.Conclusions:Uterine electromyography may predict the premature birth within 48 h after tocolytic treatment in preterm labor,which may provide reference for subsequent corticosteroid therapy or transfer of high-risk pregnant patients.

Objective:To evaluate the diagnostic performance of artificial intelligence-assisted diagnostic systems in cervical cytopathological examination.Methods:Cervical cytology slide data were retrospectively collected from four hospitals for the external validation of the developed artificial intelligence-assisted diagnostic system. Subsequently, prospective data collection was conducted for human-machine assisted studies.Results:In the retrospective study, a total of 3 162 valid samples were collected as external validation data. The system showed an area under the curve (AUC) of 0.890 (95% CI: 0.878-0.902), accuracy of 0.885 (95% CI: 0.873-0.896), sensitivity of 0.928 (95% CI: 0.914-0.941), and specificity of 0.852 (95% CI: 0.834-0.867). In the prospective study, 212 valid samples were collected, and five junior cytologists participated in the human-machine assisted study. Without artificial intelligence assistance, the average AUC for the five cytologists was 0.686 (95% CI: 0.650-0.722), the accuracy was 0.699 (95% CI: 0.671-0.727), the sensitivity was 0.653 (95% CI: 0.599-0.703), the specificity was 0.719 (95% CI: 0.685-0.750), the Fleiss κ value was 0.510, and the reading time was 223 seconds. With artificial intelligence assistance, the AUC, accuracy, sensitivity, and specificity increased by 0.166, 0.143, 0.225, and 0.107, respectively. Additionally, Fleiss κ was 0.730 and the reading time decreased by 188 seconds. All differences were statistically significant (all P<0.001). Conclusions:Artificial intelligence-assisted diagnosis system shows excellent performance and good generalizability, significantly improving the diagnostic accuracy, consistency, and efficiency of junior cytologists. It can be an effective auxiliary tool for junior cytologists in clinical practice.

HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.

Objective: To understand the epidemiological and etiological characteristics of food poisoning event occurred in a school in Hangzhou, Zhejiang, so as to provide reference for the scientific management of related emergencies. Methods: By determining the nature of the event through epidemiological investigation, a case control study was carried out to spot suspicious food in May 2024. The hygienic investigation was conducted to find out possible pollution links and factors, patients and canteen practitioners anal swab, canteen retention samples, catering link daub and other specimens were collected ,for rapid pathogen screening. And the suspected pathogen Clostridium perfringens (CP) were isolated and identified according to the screening results, and toxin gene detection and whole genome sequencing and cluster analysis of CP isolated strains were carried out. Results: The incident resulted in 45 people experiencing gastrointestinal symptoms, such as diarrhea and abdominal pain. The suspicious food was tomato scrambled eggs and corn ribs provided by the student canteen for lunch on May 29. A hygiene investigation found that there was a risk of contamination in the food processing, preparation and storage. A total of 46 anal swabs and 10 canteen retention samples were positive for CP 16 S, 59 strains of CP were isolated from 27 samples, 10 cases and 1 practitioner isolate were positive for CPE ( cpe ) (F mode), and their whole genome evolution analysis was conducted based on the same source. Conclusions The food poisoning event is caused by CP infection carrying CPE ( cpe ) (F mode), and the possible sources of outbreak are the carriers of the CP by employees. It is recommended that cafeteria staff strengthen training on common foodborne diseases and conduct regular monitoring of pathogens.

Objective To investigate the genetic characteristics of the VP1 region of Coxsackievirus A10 (CVA10) in Yunnan Province. Methods Fecal samples of suspected hand, foot and mouth disease (HFMD) were subjected to real-time fluorescent quantitative PCR for detection of enterovirus CVA10. Positive samples were subjected to VP1 gene sequence amplification and Sanger sequencing. Sequence splicing was performed with DNAstar7.1 Seqman software, and nucleotide sequence and amino acid site analysis were performed using Mega 6.0 software. Results The sequencing of VP1 gene of CVA10 obtained a sequence of 894 nucleotides, encoding 298 amino acids. Compared with the original strain, there were mainly three active amino acid mutation regions, 13-33, 141-142, and 283-285. The nucleotide difference rate between the Yunnan isolates and the reference strain ranged from 16.92% to 30.90%, and the amino acid difference rate ranged from 2.58% to 4.00%. C1 and C2 group nucleotide difference was 10.58%, and the amino acid difference rate was 1.80%. The VP1 150-176 region exhibited highly conserved characteristics. Six CVA10 strains and Sichuan strain MW178898 belonged to the C1 group of the C genotype. The other 14 CVA10 strains belonged to the C2 group. Conclusion VP1 gene mutation is active and CVA10 is an important pathogen of HFMD in Yunnan. C2 genotype of CVA10 is dominant in this study, and C1 and C2 have co-circulated in Yunnan. It is necessary to strengthen monitoring and develop multivalent vaccines containing CVA10 epidemic genotype.

Objective:To evaluate the diagnostic performance of artificial intelligence-assisted diagnostic systems in cervical cytopathological examination.Methods:Cervical cytology slide data were retrospectively collected from four hospitals for the external validation of the developed artificial intelligence-assisted diagnostic system. Subsequently, prospective data collection was conducted for human-machine assisted studies.Results:In the retrospective study, a total of 3 162 valid samples were collected as external validation data. The system showed an area under the curve (AUC) of 0.890 (95% CI: 0.878-0.902), accuracy of 0.885 (95% CI: 0.873-0.896), sensitivity of 0.928 (95% CI: 0.914-0.941), and specificity of 0.852 (95% CI: 0.834-0.867). In the prospective study, 212 valid samples were collected, and five junior cytologists participated in the human-machine assisted study. Without artificial intelligence assistance, the average AUC for the five cytologists was 0.686 (95% CI: 0.650-0.722), the accuracy was 0.699 (95% CI: 0.671-0.727), the sensitivity was 0.653 (95% CI: 0.599-0.703), the specificity was 0.719 (95% CI: 0.685-0.750), the Fleiss κ value was 0.510, and the reading time was 223 seconds. With artificial intelligence assistance, the AUC, accuracy, sensitivity, and specificity increased by 0.166, 0.143, 0.225, and 0.107, respectively. Additionally, Fleiss κ was 0.730 and the reading time decreased by 188 seconds. All differences were statistically significant (all P<0.001). Conclusions:Artificial intelligence-assisted diagnosis system shows excellent performance and good generalizability, significantly improving the diagnostic accuracy, consistency, and efficiency of junior cytologists. It can be an effective auxiliary tool for junior cytologists in clinical practice.

Objective:To investigate the potential value of cerebral glucose metabolism characteristics in anti-leucine-rich glioma-inactivated protein 1 (LGI1) antibody-related encephalitic patients during acute phase as the clinical indicator of disease outcomes.Methods:From October 2019 to December 2023, 28 patients (18 males, 10 females; age (56.6±11.9) year) with anti-LGI1 antibody-related encephalitis diagnosed at Huashan Hospital, Fudan University were prospectively enrolled. All patients received baseline brain 18F-FDG PET imaging and were divided into different subgroups according to the prognosis (good prognosis and poor prognosis groups) and recurrence (recurrence and non-recurrence groups) after follow-up. The difference of Montreal Cognitive Assessment (MoCA) score between the two groups was compared by Mann-Whitney U test. Statistical parametric mapping (SPM) analysis was used to analyze the PET images of different groups by independent-sample t test, and the characteristics of cerebral glucose metabolism of patients with different outcomes were obtained. Results:MoCA scores between the recurrence group ( n=6) and the non-recurrence group ( n=22; 14.0(9.8, 20.5) vs 22.0(18.0, 24.0); Z=2.17, P=0.030), and between the poor prognosis group ( n=13) and the good prognosis group ( n=15; 14.0(10.0, 22.0) vs 22.0(19.8, 25.3); Z=2.47, P=0.013) were significantly different. Compared with the good prognosis group, the cerebral glucose metabolism in the poor prognosis group was decreased in the bilateral frontal lobe, lateral temporal lobe, inferior parietal lobule and cingulate gyrus, but increased in the brainstem, bilateral lentiform nucleus and bilateral paracentral lobule/postcentral gyrus (all t=1.71, all P<0.05). Compared with the non-recurrence group, the metabolism of bilateral medial frontal gyrus, anterior cingulate gyrus, bilateral insula, superior temporal gyrus and thalamus decreased in the recurrence group, while the metabolism of bilateral precentral gyrus, inferior frontal gyrus and bilateral lentiform nucleus increased (all t=1.71, all P<0.05). Conclusion:18F-FDG PET imaging reveals the differences in brain metabolism of anti-LGI1 antibody-related encephalitic patients at baseline with different outcomes (prognosis, recurrence or not), which can provide a new perspective for the clinical evaluation of the disease at baseline.

Retinopathy of prematurity (ROP) is a vision-threatening disorder that leads to pathological growth of the retinal vasculature due to hypoxia. Here, we investigated the potential effects of alamandine, a novel heptapeptide in the renin-angiotensin system (RAS), on hypoxia-induced retinal neovascularization and its underlying mechanisms. In vivo, the C57BL/6J mice with oxygen-induced retinopathy (OIR) were injected intravitreally with alamandine (1.0 μmol/kg per eye). In vitro, human retinal microvascular endothelial cells (HRMECs) were utilized to investigate the effects of alamandine (10 μg/mL) on proliferation, apoptosis, migration, and tubular formation under vascular endothelial growth factor (VEGF) stimulation. Single-cell RNA sequencing (scRNA-seq) matrix data from the Gene Expression Omnibus (GEO) database and RAS-related genes from the Molecular Signatures Database (MSigDB) were sourced for subsequent analyses. By integrating scRNA-seq data across multiple species, we identified that RAS-associated endothelial cell populations were highly related to retinal neovascularization. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis revealed a significant decrease in alamandine levels in both the serum and retina of OIR mice compared to those in the control group. Next, alamandine ameliorated hypoxia-induced retinal pathological neovascularization and physiologic revascularization in OIR mice. In vitro, alamandine effectively mitigated VEGF-induced proliferation, scratch wound healing, and tube formation of HRMECs primarily by inhibiting the hypoxia-inducible factor-1α (HIF-1α)/VEGF pathway. Further, coincubation with D-Pro⁷ (Mas-related G protein-coupled receptor D (MrgD) antagonist) hindered the beneficial impacts of alamandine on hypoxia-induced pathological angiogenesis both in vivo and in vitro. Our findings suggested that alamandine could mitigate retinal neovascularization by targeting the MrgD-mediated HIF-1α/VEGF pathway, providing a potential therapeutic agent for OIR prevention and treatment.
Animals ; Retinal Neovascularization/prevention & control* ; Mice, Inbred C57BL ; Vascular Endothelial Growth Factor A/metabolism* ; Humans ; Mice ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Oligopeptides/therapeutic use* ; Signal Transduction/drug effects* ; Cell Proliferation/drug effects* ; Endothelial Cells/drug effects* ; Retinopathy of Prematurity/drug therapy* ; Apoptosis/drug effects* ; Cell Movement/drug effects* ; Renin-Angiotensin System/drug effects* ; Cells, Cultured

Objective:To investigate the potential value of cerebral glucose metabolism characteristics in anti-leucine-rich glioma-inactivated protein 1 (LGI1) antibody-related encephalitic patients during acute phase as the clinical indicator of disease outcomes.Methods:From October 2019 to December 2023, 28 patients (18 males, 10 females; age (56.6±11.9) year) with anti-LGI1 antibody-related encephalitis diagnosed at Huashan Hospital, Fudan University were prospectively enrolled. All patients received baseline brain 18F-FDG PET imaging and were divided into different subgroups according to the prognosis (good prognosis and poor prognosis groups) and recurrence (recurrence and non-recurrence groups) after follow-up. The difference of Montreal Cognitive Assessment (MoCA) score between the two groups was compared by Mann-Whitney U test. Statistical parametric mapping (SPM) analysis was used to analyze the PET images of different groups by independent-sample t test, and the characteristics of cerebral glucose metabolism of patients with different outcomes were obtained. Results:MoCA scores between the recurrence group ( n=6) and the non-recurrence group ( n=22; 14.0(9.8, 20.5) vs 22.0(18.0, 24.0); Z=2.17, P=0.030), and between the poor prognosis group ( n=13) and the good prognosis group ( n=15; 14.0(10.0, 22.0) vs 22.0(19.8, 25.3); Z=2.47, P=0.013) were significantly different. Compared with the good prognosis group, the cerebral glucose metabolism in the poor prognosis group was decreased in the bilateral frontal lobe, lateral temporal lobe, inferior parietal lobule and cingulate gyrus, but increased in the brainstem, bilateral lentiform nucleus and bilateral paracentral lobule/postcentral gyrus (all t=1.71, all P<0.05). Compared with the non-recurrence group, the metabolism of bilateral medial frontal gyrus, anterior cingulate gyrus, bilateral insula, superior temporal gyrus and thalamus decreased in the recurrence group, while the metabolism of bilateral precentral gyrus, inferior frontal gyrus and bilateral lentiform nucleus increased (all t=1.71, all P<0.05). Conclusion:18F-FDG PET imaging reveals the differences in brain metabolism of anti-LGI1 antibody-related encephalitic patients at baseline with different outcomes (prognosis, recurrence or not), which can provide a new perspective for the clinical evaluation of the disease at baseline.