High-expressed ACAT2 predicted the poor prognosis of platinum-resistant epithelial ovarian cancer.

BACKGROUND: Acetyl-CoA acetyltransferase 2 (ACAT2) is a lipid metabolism enzyme and rarely was researched in epithelial ovarian cancer (EOC). METHODS: ACAT2 expressions were confirmed in two pairs of cell lines (A2780 and A2780/DDP, OVCAR8 and OVCAR8/DDP) from Gene Expression Omnibus database by bioinformatics analysis, and in A2780 and A2780/DDP cell lines by quantitative real-time polymerase chain reaction and western blotting. Tissue samples were stained by immunohistochemistry and scored for ACAT2 expression. The relationships between ACAT2 expression and clinicopathological characteristics were analyzed by χ2 test. The prognosis of ACAT2 was analyzed by the log-rank tests and Cox regression models. RESULTS: ACAT2 was remarkably upregulated in the above drug-resistant cell lines by mRNA (all P < 0.05) and protein expression (P = 0.026) than those in sensitive ones. Patients were classified as ACAT2-high (n = 51) and ACAT2-low (n = 26) according to immunohistochemical score. ACAT2 expression had a significantly inverse correlation with FIGO stage (P = 0.030) and chemo-response (P = 0.041). A marginal statistical significance existed in ACAT2 expression and ascites volume (P = 0.092). Univariate analysis suggested that high-expressed ACAT2 was associated with decreased platinum-free interval (PFI) (8.57 vs. 14.13 months, P = 0.044), progression-free survival (PFS) (14.12 vs. 19.79 months, P = 0.039) and overall survival (OS) (36.89 vs. 52.40 months, P = 0.044). Multivariate analysis demonstrated that ACAT2 expression (hazard ratio = 2.18, 95% confidence interval: 1.15-4.11, P = 0.017) affected OS independently, rather than PFI and PFS. CONCLUSION: The expression of ACAT2 in A2780/DDP and OVCAR8/DDP was higher than the corresponding A2780 and OVCAR8. High-expressed ACAT2 was associated with advanced FIGO stage, chemo-resistance, and decreased PFI, PFS and OS. It was an independent prognostic factor of OS in EOC.

Intelligent classification of cardiotocography based on a support vector machine and convolutional neural network: Multiscene research.

OBJECTIVE: To propose a computerized system utilizing multiscene analysis based on a support vector machine (SVM) and convolutional neural network (CNN) to assess cardiotocography (CTG) intelligently. METHODS: We retrospectively collected 2542 CTG records of singleton pregnancies delivered at the maternity ward of the First Affiliated Hospital of Xi'an Jiaotong University from October 10, 2020, to August 7, 2021. CTG records were divided into five categories (baseline, variability, acceleration, deceleration, and normality). Apart from the category of normality, the other four different categories of abnormal data correspond to four scenes. Each scene was divided into training and testing sets at 9:1 or 7:3. We used three computer algorithms (dynamic threshold, SVM, and CNN) to learn and optimize the system. Accuracy, sensitivity, and specificity were performed to evaluate performance. RESULTS: The global accuracy, sensitivity, and specificity of the system were 93.88%, 93.06%, and 94.33%, respectively. In acceleration and deceleration scenes, when the convolution kernel was 3, the test data set reached the highest performance. CONCLUSION: The multiscene research model using SVM and CNN is a potential effective tool to assist obstetricians in classifying CTG intelligently.

Serum prolactin and gonadal hormones in hemodialysis women: a meta-analysis.

BACKGROUND: A meta-analysis followed by PRISMA 2020 statement was performed aiming to present a whole prolactin and sex hormone profile in hemodialysis women. METHODS: Literatures were searched in PubMed, Cochrane library, Embase, and Web of science before March 11, 2023. Trial sequential analysis (TSA) was performed to test the conclusiveness of this meta-analysis. Egger's test and trim-and-fill analysis was used to test publication bias. We took standardized mean difference (SMD) as pool effect of hormones values including prolactin (PRL), follicle-stimulating hormone (FSH), luteinizing hormone (LH), estradiol (E2) and progesterone (P). This study was registered in PROSPERO and the number was CRD42023394503. RESULTS: Twenty-two articles from 13 countries were analyzed. Combining the results of TSA and meta-analysis, we found that compared with healthy control, hemodialysis women had higher PRL, follicular FSH and LH values and lower P levels (PRL: I2 = 87%, SMD 1.24, 95% CI: 0.79-1.69, p < 0.00001; FSH: I2 = 0%, SMD 0.34, 95% CI: 0.13-0.55, p = 0.002; LH: I2 = 39%, SMD 0.64, 95% CI: 0.34-0.93, p < 0.00001; P: I2 = 30%, SMD - 1.62, 95% CI: -2.04 to -1.20, p < 0.00001). What's more, compared with women after renal transplantation, hemodialysis women had higher PRL levels (I2 = 0%, SMD 0.51, 95% CI: 0.25-0.78, p = 0.0001). There was not enough evidence to draw a conclusion on the comparison of hormones between regular and irregular menses hemodialysis women. Egger's test and trim-and-fill analysis didn't show significant publication bias. CONCLUSIONS: Hemodialysis women had higher serum PRL, follicular phase FSH, LH and lower serum P values compared with healthy control. PRL values of hemodialysis women were also higher than that of women after renal transplantation.

Laser Welding Multimodel Quality Forecast Method Based on Dynamic Geometric Features of the Molten Pool.

Laser welding quality forecast is highly significant during the laser manufacturing process. However, extracting the dynamic characteristics of the molten pool in the short laser welding process makes predicting of the welding quality in real time difficult. Accordingly, this study proposes a multimodel quality forecast (MMQF) method based on dynamic geometric features of molten pool to forecast the welding quality in real time. For extraction of geometric features of molten pool, an improved fully convolutional neural network is proposed to segment the collected dynamic molten pool images during the entire welding process. In addition, several dynamic geometric features of the molten pool are extracted by using the minimum enclosed rectangle algorithm with an evaluation of the performance by several statistical indexes. With regard to forecasting the welding quality, a nonlinear quadratic kernel logistic regression model is proposed by mapping the linear inseparable features to the high dimensional space. Experimental results show that the MMQF method can make an effective and stable forecast of welding quality. It performs well under small data and can satisfy the requirement of real-time forecast.

The sealing effect of magnetic-sealing uterine manipulator in isolated uterus from patients with early-stage cervical cancer: a pre-clinical study.

OBJECTIVE: Traditional uterine manipulator is considered as the main reason for short survival of patients with early-stage cervical cancer during minimally invasive surgery. This study aims to assess the sealing effect of magnetic-sealing uterine manipulators (MUMs) in isolated uteruses. METHODS: The study was performed on isolated uterus from patients with early-stage cervical cancer who underwent open abdominal radical hysterectomy between November 2019 to April 2021. Right-angle forceps closure tests (groups 1 and 3) were defined as control tests. One experimental MUM closure test (group 2) and 2 control tests were respectively carried out in each of the isolated uterus. DNA ploidy analysis system was used to observe exfoliated cells. Statistical analysis was performed using Wilcoxon signed-rank test to assess the sealing effect of MUM. RESULTS: We identified 36 patients. No regional node metastasis was discovered and only one tumor was larger than 4.0 cm in diameter. The mean of exfoliated tumor cells in groups 1, 2, and 3 were 1, 1, and 2, respectively. There was no significant difference in the quantity of exfoliated cells between groups 1 and 3 (p=0.476), so the results of the 2 groups were merged. Subsequently, a significant difference was observed between combined right-angle forceps closure tests and MUM closure tests (p=0.022). CONCLUSION: The sealing effect of MUM was better than that of right-angle forceps. MUM can effectively seal cervical cancer cells in the cup cover, avoiding the dissemination of tumor cells. TRIAL REGISTRATION: Chinese Clinical Trial Register Identifier: ChiCTR1900026012.

Micro-histology combined with cytology improves the diagnostic accuracy of endometrial lesions.

BACKGROUND: In the study, we aimed to evaluate the ability of micro-histology combined with cytology to improve the quality of slides and diagnose endometrial lesions. METHODS: Endometrial specimens were collected from Li Brushes. Every specimen was prepared for micro-histological and cytological slides, using cell block (CB) and liquid-based cytology (LBC) technologies. Semi-quantitative scoring system was used to evaluate the qualities of slides. CB slides were assessed by 5-category scoring system. Diagnostic accuracy was calculated in LBC, CB, and LBC + CB groups based on the histological gold standard. Endometrial atypical hyperplasia, and endometrial cancer were considered positive, whereas others were considered negative. RESULTS: A total of 167 patients were enrolled. CB slides were inferior to LBC slides only in cellularity (p < 0.001), but superior in the other six parameters (all p < 0.001). The satisfaction rate of micro-histology accounted for 92.3%. The accuracy index in the CB group was higher than in the LBC group in terms of sensitivity (85.5% vs. 82.7%) and specificity (98.9% vs. 95.7%). The sensitivity and specificity in the LBC + CB group were increased to 94.2% and 99.0%, respectively. CONCLUSIONS: The quality of micro-histological slides was higher than that of cytological slides. By combining micro-histology with cytology, higher accuracy was achieved for endometrial lesions diagnosis.

Positive Rate of Malignant Cells in Endometrial Cytology Samples of Ovarian Cancer, Fallopian Tube Cancer, and Primary Peritoneal Cancer Patients: A Systematic Review and Meta-Analysis.

To estimate the feasibility of diagnosing ovarian cancer, fallopian tube cancer, and primary peritoneal cancer through endometrial cytology, we performed a systematic review and meta-analysis to calculate the pooled positive rate of malignant cells in endometrial cytology samples. We queried PubMed, EMBASE, Medline, and Cochrane Central Register of Controlled Trails from inception to November 12, 2020 for studies estimating positive rates of malignant cells in endometrial cytology samples from patients with ovarian cancer, fallopian tube cancer, and primary peritoneal cancer. The positive rates of the included studies were calculated as pooled positive rate through meta-analyses of proportion. Subgroup analysis based on different sampling methods was conducted. Seven retrospective studies involving 975 patients were included. Pooled positive rate of malignant cells in endometrial cytology specimens of ovarian cancer, fallopian tube cancer, and primary peritoneal cancer patients was 23% (95% CI: 16% - 34%). Statistical heterogeneity between the included studies was considerable (I2 = 89%, P < 0.01). The pooled positive rates of the group of brushes and the group of aspiration smears were 13% (95% CI: 10% - 17%, I2 = 0, P = 0.45) and 33% (95% CI: 25% - 42%, I2 = 80%, P < 0.01), respectively. Although endometrial cytology is not an ideal diagnostic tool for ovarian cancer, fallopian tube cancer, and primary peritoneal cancer, it is a convenient, painless, and easy-to-implement adjunct to other tools. Sampling method is one of the factors that affect the detection rate.

Clinically Applicable Pathological Diagnosis System for Cell Clumps in Endometrial Cancer Screening via Deep Convolutional Neural Networks.

OBJECTIVES: The soaring demand for endometrial cancer screening has exposed a huge shortage of cytopathologists worldwide. To address this problem, our study set out to establish an artificial intelligence system that automatically recognizes and diagnoses pathological images of endometrial cell clumps (ECCs). METHODS: We used Li Brush to acquire endometrial cells from patients. Liquid-based cytology technology was used to provide slides. The slides were scanned and divided into malignant and benign groups. We proposed two (a U-net segmentation and a DenseNet classification) networks to identify images. Another four classification networks were used for comparison tests. RESULTS: A total of 113 (42 malignant and 71 benign) endometrial samples were collected, and a dataset containing 15,913 images was constructed. A total of 39,000 ECCs patches were obtained by the segmentation network. Then, 26,880 and 11,520 patches were used for training and testing, respectively. On the premise that the training set reached 100%, the testing set gained 93.5% accuracy, 92.2% specificity, and 92.0% sensitivity. The remaining 600 malignant patches were used for verification. CONCLUSIONS: An artificial intelligence system was successfully built to classify malignant and benign ECCs.

Relapsed and refractory yolk sac tumor of the peritoneum (mesentery): A case report and literature review.

Background: Extragonadal yolk sac tumor (YST) of peritoneum is a rare malignancy. Case Description: A 37-year-old Chinese woman was admitted to hospital with a 3-month abdominal pain 4 years ago. Alpha-fetoprotein was 228,499.0 ng/mL. Computed tomography scan revealed a massive mass in the left lower abdomen. Exploratory laparotomy exposed a huge mesenteric mass. Then, mesenteric tumor resection, partial sigmoidectomy, and single-lumen fistula of sigmoid colon were performed. Postoperative pathologic diagnosis reported a stage IV mesenteric YST. After surgery, the patient received 6 courses of BEP (bleomycin, etoposide, and cisplatin) chemotherapy. Seven months later, the patient underwent stoma reversion of sigmoid colon and received another 2 courses of BEP chemotherapy. Three months after the last chemotherapy, liver metastases were diagnosed. She subsequently underwent 3 surgeries, radiotherapy for liver metastases, and multiple tiers of palliative chemotherapies, including TP (docetaxel and carboplatin), VIP (ifosfamide, cisplatin, and etoposide), TIP (paclitaxel, ifosfamide, and cisplatin), and so on. After the third surgery (left hepatic lesion resection and right iliac lymph node resection), she received 4 cyclic chemotherapies of BEP´ (boanmycin, etoposide, and cisplatin) without pulmonary toxic side effects. Conclusion: Postoperative histopathology and immunohistochemistry are gold standards for the diagnosis of peritoneal YST. The standard first-line treatment is surgery plus BEP chemotherapy. Second-line therapy regimens and above, including VIP and TIP, improve the prognosis of recurrent germ cell tumors. This relapsed and refractory patient with peritoneal YST benefits from the secondary BEP´ chemotherapy.

Efficacy and Safety of Placebo During the Maintenance Therapy of Ovarian Cancer in Randomized Controlled Trials: A Systematic Review and Meta-analysis.

Introduction: This meta-analysis evaluated the efficacy and safety of placebo during the maintenance therapy of ovarian cancer (OC) patients in randomized controlled trials (RCTs). Methods: A comprehensive literature review was performed for RCTs published up to and including August 2020 from four electronic databases. We analyzed the efficacy and safety in the control arms of the maintenance therapy in advanced OC patients. Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) of progression-free survival (PFS) and overall survival (OS) were estimated in the placebo arms and the observation arms, respectively, using the Frequency Framework method. We also calculated the incidences of common adverse effects (AEs) in the placebo arms. Results: In total, 41 articles with 20,099 (4,787 in the placebo arms, 3,420 in the observation arms, and 11,892 in the experiment arms) patients were included in this meta-analysis. Compared with observation, placebo did not improve or reduce PFS (HR, 1.02; 95% CI, 0.87-1.20; P = 0.81) and OS (HR, 1.02; 95% CI, 0.89-1.16; P = 0.76) of OC patients, while other treatments, except for radiotherapy, significantly improved PFS and OS (all P < 0.05). The incidences of AEs produced by placebo were 94.03% in all grades and 20.22% in grade ≥3. The incidences of AEs were 29.75% in fatigue, 26.38% in nausea, 24.34% in abdominal pain, 18.92% in constipation, 16.65% in diarrhea, 14.55% in vomiting, 13.89% in hypertension, and 13.14% in headache. Conclusions: Placebo did not improve or reduce the PFS and OS benefits of OC patients in RCTs but increased the incidences of AEs.

Extremely high serum CA19-9 level along with elevated D-dimer in assisting detection of ruptured ovarian endometriosis.

BACKGROUND: To clarify clinical importance of serum CA19-9, CA-125, and plasma D-dimer (D-D) levels in detecting spontaneously ruptured ovarian endometriosis (OE). MATERIALS AND METHODS: We retrospectively examined 173 patients with endometriosis out of 735 cases of OE between 2013 and 2019. Among these, 21 cases were diagnosed as "spontaneously ruptured" after surgery, while the remaining cases were unruptured. Venous blood was collected pre-operatively to detect CA19-9, CA-125, and D-D levels. A receiver operating characteristic curve analysis was applied to test clinical value of each marker. RESULTS: Among the 21 patients with ruptured OE, 16 had a history of pelvic cysts, 19 claimed sudden onsets of lower abdominal pain, and fluid accumulation were detected in cul-de-sac in only six participants by ultrasound. For serological investigation, both CA19-9 and D-D were significantly elevated in the ruptured OE group (343.09 ± 367.67 U/ml vs. 36.84 ± 40.01 U/ml, 3.39 ± 4.90 mg/L vs. 0.43 ± 0.29 mg/L, both p < .0001). The area under curve (AUC) value for the combination of CA19-9 and D-D was 0.975 (95% CI, 0.939 - 0.993), with specificity of 96.69%, and sensitivity of 85.71%. The combination of CA-125, CA19-9 and D-D showed the highest AUC value that up to 0.976 (95% CI, 0.940-0.993), with sensitivity of 95.24%, and specificity of 87.50%. CONCLUSION: The combination of CA19-9 and D-D can be chosen as an effective and economical indicators to identify patients with spontaneously ruptured OE in pre-operation assessment. However, from the perspective of differential diagnosis, the combination of CA-125, CA19-9 and D-D is the best choice. Key messagesTaking into account the economic effect, the combination of CA19-9 and D-D can be chosen as an effective indicators to identify patients with spontaneously ruptured OE in pre-operation assessment.From the perspective of differential diagnosis, the combination of CA-125, CA19-9 and D-D is the best choice to identify patients with spontaneously ruptured OE.

Hypermethylated CDO1 and ZNF454 in Cytological Specimens as Screening Biomarkers for Endometrial Cancer.

We aimed to estimate the diagnostic value of DNA methylation levels in cytological samples of endometrial cancer (EC) and atypical hyperplasia (AH). Two hypermethylated genes, namely, cysteine dioxygenase type 1 (CDO1) and zinc finger protein 454 (ZNF454), in patients with EC were identified from The Cancer Genome Atlas database. In 103 endometrial histological specimens (the training set), the methylation levels of candidate genes were verified by quantitative methylation-specific polymerase chain reaction (qMSP). The methylation levels of another 120 cytological specimens (the testing set) were evaluated. Sensitivity (Se), specificity (Sp), accuracy, and area under the curve (AUC) were determined, with diagnosis verified by histopathological results. CDO1 and ZNF454 verified hypermethylation in histological specimens of patients with EC and AH compared with those with benign and normal endometrium (P < 0.001). In cytological specimens, hypermethylated CDO1 showed 86.36% Se and 90.79% Sp with the cutoff value of 6.0 to distinguish between malignant and benign groups; ZNF454 showed 79.55% Se and 93.42% Sp with the cutoff value of 7.1. When the two genes were combined, Se increased to 90.91% and Sp was 86.84%. AUC reached 0.931 (95% CI: 0.885-0.976). The diagnostic accuracy with cytology had no significant difference with endometrial tissue (P = 0.847 for CDO1, P = 0.108 for ZNF454, and P = 0.665 for their combination). Hypermethylated CDO1 and ZNF454 in endometrial cytology showed high Se, Sp, and AUC to detect EC and AH. Methylation analysis of endometrial cytology is promising biomarker for the screening of EC and AH.

Blood Bacterial 16S rRNA Gene Alterations in Women With Polycystic Ovary Syndrome.

Background: Evidence proved the association between gut microbiome dysbiosis and polycystic ovary syndrome (PCOS) in metabolic disorder, decreased fertility, and hyperandrogenism. However, alterations in blood microbiome of PCOS remained unknown. Objective: This study aims to measure the blood microbiome profile of PCOS patients compared with healthy controls by 16S rRNA sequencing and to investigate its association with PCOS. Methods: In this case-control study, bacterial DNA in blood of 24 PCOS patients and 24 healthy controls was investigated by 16S rRNA gene sequencing using the MiSeq technology. Alpha and beta diversity were used to analyze within-sample biodiversity and similarity of one group to another, respectively. Linear discriminant analysis effect size (LEfSe) was calculated to determine biomarkers between groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional prediction was performed at genera level. Result: Alpha diversity of blood microbiome decreased significantly in women with PCOS, and beta diversity analysis demonstrated a major separation between the two groups. In the PCOS group, the relative abundance of Proteobacteria, Firmicutes, and Bacteroidetes decreased significantly, while Actinobacteria increased significantly. Cladogram demonstrated the microbiome differences between the two groups at various phylogenic levels. Meanwhile, linear discriminant analysis (LDA) presented significant decreases in Burkholderiaceae, Lachnospiraceae, Bacteroidaceae, Ruminococcaceae, and S24-7 and significant increases in Nocardioidaceae and Oxalobacteraceae of the PCOS group. KEGG pathway analysis at genera level suggested that 14 pathways had significant differences between the two groups. Conclusion: Our findings demonstrated that blood microbiome had a significantly lower alpha diversity, different beta diversity, and significant taxonomic variations in PCOS patients compared with healthy controls.

A Computer-Aided Diagnosis System of Fetal Nucleated Red Blood Cells With Convolutional Neural Network.

CONTEXT.­: The rapid recognition of fetal nucleated red blood cells (fNRBCs) presents considerable challenges. OBJECTIVE.­: To establish a computer-aided diagnosis system for rapid recognition of fNRBCs by convolutional neural network. DESIGN.­: We adopted density gradient centrifugation and magnetic-activated cell sorting to extract fNRBCs from umbilical cord blood samples. The cell-block method was used to embed fNRBCs for routine formalin-fixed paraffin sectioning and hematoxylin-eosin staining. Then, we proposed a convolutional neural network-based, computer-aided diagnosis system to automatically discriminate features and recognize fNRBCs. Extracting methods of interested region were used to automatically segment individual cells in cell slices. The discriminant information from cellular-level regions of interest was encoded into a feature vector. Pathologic diagnoses were also provided by the network. RESULTS.­: In total, 4760 pictures of fNRBCs from 260 cell-slides of 4 umbilical cord blood samples were collected. On the premise of 100% accuracy in the training set (3720 pictures), the sensitivity, specificity, and accuracy of cellular intelligent recognition were 96.5%, 100%, and 98.5%, respectively, in the test set (1040 pictures). CONCLUSIONS.­: We established a computer-aided diagnosis system for effective and accurate fNRBC recognition based on a convolutional neural network.

3D Dense Volumetric Network for Accurate Automated Pancreas Segmentation.

Pancreatic cancer poses a great threat to our health with an overall five-year survival rate of 8%. Automatic and accurate segmentation of pancreas plays an important and prerequisite role in computer-assisted diagnosis and treatment. Due to the ambiguous pancreas borders and intertwined surrounding tissues, it is a challenging task. In this paper, we propose a novel 3D Dense Volumetric Network (3D2VNet) to improve the segmentation accuracy of pancreas organ. Firstly, 3D fully convolutional architecture is applied to effectively incorporate the 3D pancreas and geometric cues for volume-to-volume segmentation. Then, dense connectivity is introduced to preserve the maximum information flow between layers and reduce the overfitting on limited training data. In addition, a auxiliary side path is constructed to help the gradient propagation to stabilize the training process. Adequate experiments are conducted on a challenging pancreas dataset in Medical Segmentation Decathlon challenge. The results demonstrate our method can outperform other comparison methods on the task of automated pancreas segmentation using limited data.Clinical relevance-This paper proposes an accurate automated pancreas segmentation method, which can provide assistance to clinicians in the diagnosis and treatment of pancreatic cancer.

Characterization and Functional Prediction of Bacteria in Ovarian Tissues.

The theory of a "sterile" female upper reproductive tract has been encountering increasing opposition due to advancements in bacterial detection. However, whether ovaries contain bacteria has not yet been confirmed yet. Herein, an experiment to detect bacteria in ovarian tissues was introduced. We chose ovarian cancer patients in the cancer group and noncancerous patients in the control group. 16S rRNA gene sequencing was used to differentiate bacteria in ovarian tissues from the cancer and control groups. Furthermore, we predicted the functional composition of the identified bacteria by using BugBase and PICRUSt. This method can also be used in other viscera and tissues since many organs have been proven to harbor bacteria in recent years. The presence of bacteria in viscera and tissues may help scientists evaluate cancerous and normal tissues and may be aid in the treatment of cancer.

A Systematic Review and Meta-Analysis of the Prognostic Impact of Pretreatment Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Parameters in Patients with Locally Advanced Cervical Cancer Treated with Concomitant Chemoradiotherapy.

BACKGROUNDS: The purpose of this paper is to investigate the prognostic value of fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) parameters in patients treated with concurrent chemoradiotherapy (CCRT) for locally advanced cervical cancer (LACC). METHODS: Studies that met the following criteria were retrieved from PubMed and Embase: patients treated with CCRT for LACC; FDG PET/CT scans performed before CCRT treatment; and a detected relationship between the parameters of FDG PET/CT and the prognosis of patients. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were used to estimate the overall survival (OS) or event-free survival (EFS). RESULTS: In total, 14 eligible studies with 1313 patients were included in this meta-analysis. Patients with a high maximum standardized uptake value (SUVmax) have a shorter OS than those with a low SUVmax (HR = 2.582, 95% = CI 1.936-3.443, p < 0.001). Primary tumor SUVmax values (HR = 1.938, 95% CI = 1.203-3.054, p = 0.004) were significantly correlated with EFS, with a relatively high heterogeneity (I2 = 84% and I2 = 69.4%, respectively). Based on the limited data, the combined HR for EFS with the highest primary tumor total lesion glycolysis (TLG) and metabolic tumor volume (MTV) was 1.843 (95% CI = 1.100-3.086, p = 0.02) and 2.06 (95% CI = 1.21-3.51, p = 0.007), respectively. Besides, the combined HR for OS with the highest nodal SUVmax was 2.095 (95% CI = 2.027-2.166, p < 0.001). CONCLUSION: A high primary SUVmax has a significant correlation with the OS and EFS of patients treated with CCRT for LACC and may therefore serve as a prognostic predictor. Due to the limited data, to explore the correlation between survival and TLG, MTV, and nodal SUVmax, further large-scale prospective studies are needed.

Near-Infrared Fluorescent Agent for In Vitro Screening of Endometrial Cancer and Precancerous Lesions.

The lack of cytopathologists delays the advancement of screening for endometrial cancer. It was urgent to develop a new dye for rapid diagnosis. Our study aimed to synthesize a targeted folate receptor-α near-infrared (NIR) fluorescent agent, folic acid-zwitterionic NIR fluorophore (ZW-FA), and explore the feasibility for screening of endometrial cancer and precancerous change. Folic acid was conjugated with zwitterionic NIR fluorophore. The preparation of ZW-FA was validated by 1H NMR, mass spectrometric, ultraviolet spectra and fluorescence spectra. ZW-FA was incubated with endometrial cytology samples obtained from patients who underwent dilation and curettage or total hysterectomy. Diagnostic utility was calculated by applying laser confocal microscope, Image-J and statistical models, such as enumeration, receiver operating characteristic curve, logistic regression, support vector machine and decision tree were used. The purity of ZW-FA was > 95% determined by 1H NMR. ZW-FA had the strongest absorption peak at 633 nm in ultraviolet spectra. Photostability of ZW-FA was over 8 hours. In clinical validation, a total of 92 patients were enrolled. The cut-off value of ZW-FA was 49 in enumeration, which was used to distinguish the type of samples. Indicators about diagnostic utility are as follows: sensitivity 90.77%, specificity 62.96%, false-positive rate 37.04%, false-negative rate 9.23%, positive predictive value 85.51% and negative predictive value 73.91%. The samples processed by ZW-FA did not affect further Hematoxylin-Eosin staining and pathological diagnosis. It was an effective cytologic strategy for in vitro diagnosis of endometrial cancer and precancerous change by using ZW-FA. CLINICAL TRIAL REGISTRATION: http://www.chictr.org.cn/index.aspx, identifier ChiCTR1800020123.

Microwave-assisted rapid synthesis and activation of ultrathin trimetal-organic framework nanosheets for efficient electrocatalytic oxygen evolution.

Ultrathin metal-organic frameworks (MOFs) nanosheets have been considered as one of promising electrocatalysts for oxygen evolution reaction due to their unique structures. However, the preparation process is subject to the low-yield exfoliation and time-consuming synthetic methods. And it still requires to be explored to develop an efficient strategy for regulation of surface electronic states of MOFs to enhance their electrocatalytic activities. Herein, we report a facile microwave-assisted synthesis of NiCoFe-based trimetallic metal-organic framework (MOF) nanosheets, which can achieve simultaneously rapid synthesis and activation of MOF for OER. The as-prepared Ni4Co4Fe2-MOF nanosheets exhibit excellent OER activity and electrochemical stability, which can deliver a current density of 10 mA cm-2 at a low overpotential of 243 mV with a small Tafel slope of 48.1 mV dec-1. This work provides a facile method for the rapid synthesis of MOF nanosheets and also demonstrates an effective approach for regulating the electronic structure of MOFs for electrocatalysis.

Ultrathin Trimetal-Organic Framework Nanosheet Electrocatalysts for the Highly Efficient Oxygen Evolution Reaction.

Synthesis of ultrathin metal-organic framework (MOF) nanosheets for highly efficient oxygen evolution reaction (OER) is prevalent, but still many challenges remain. Herein, a facile and efficient three-layer method is reported for the synthesis of NiCoFe-based trimetallic MOF nanosheets, which can be directly used for the oxygen evolution reaction in alkaline conditions. The physical characterization and morphology of trimetallic MOF nanosheets were characterized by powder X-ray diffraction (PXRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). By optimizing the molar ratio of Ni/Co/Fe atoms, a series of MOFs with different metal proportions were synthesized. Among them, the as-prepared (Ni3Co1)3Fe1-MOF nanosheets can deliver a current density of 10 mA cm-2 at a low overpotential of 245 mV with a small Tafel slope of 50.9 mV dec-1 in an alkaline electrolyte and exhibit excellent stability. More importantly, through the characterization of the intermediates in the OER process, the possible source of the catalytic active species is the electrochemically transformed metal hydroxides and oxyhydroxides.