A retrospective study of the effects of uterine manipulators on prognosis in patients with cervical cancer.

OBJECTIVE: This retrospective study investigated the effects of uterine manipulator use during minimally invasive radical hysterectomy on prognosis in patients with cervical cancer. METHODS: We collected clinical data on 762 patients with stage IA2 to IIB cervical cancer who underwent radical hysterectomy and pelvic lymphadenectomy in Chinese PLA General Hospital from 2009 to 2019. Kaplan-Meier analysis and log-rank tests were used to compare the 5-year overall survival rates between patients treated with and without a uterine manipulator. RESULTS: Patient demographics did not differ between the two groups. In addition, the incidence of lymphovascular space invasion, tumor size, pathologic types, the International Federation of Gynecology and Obstetrics stage, the histologic grade, and the rate of lymphatic metastases did not differ between the groups. Meanwhile, perioperative clinical indicators were similar in the groups. Furthermore, no significant differences in 5-year survival rates and survival curves were recorded between the groups among both all patients (84.5% vs. 85.6%) and early-stage patients (89.1% vs. 89.2%). CONCLUSIONS: The use of uterine manipulators during minimally invasive radical hysterectomy for cervical cancer did not affect clinicopathological markers or increase the risk of death.

DNA methylation profiling identifies epigenetic signatures of early gastric cancer.

Research on the DNA methylation status of gastric cancer (GC) has primarily focused on identifying invasive GC to develop biomarkers for diagnostic. However, DNA methylation in noninvasive GC remains unclear. We conducted a comprehensive DNA methylation profiling study of differentiated-type intramucosal GCs (IMCs). Illumina 850K microarrays were utilized to assess the DNA methylation profiles of formalin-fixed paraffin-embedded tissues from eight patients who were Epstein-Barr virus-negative and DNA mismatch repair proficient, including IMCs and paired adjacent nontumor mucosa. Gene expression profiling microarray data from the GEO database were analyzed via bioinformatics to identify candidate methylation genes. The final validation was conducted using quantitative real-time PCR, the TCGA methylation database, and single-sample gene set enrichment analysis (GSEA). Genome-wide DNA methylation profiling revealed a global decrease in methylation in IMCs compared with nontumor tissues. Differential methylation analysis between IMCs and nontumor tissues identified 449 differentially methylated probes, with a majority of sites showing hypomethylation in IMCs compared with nontumor tissues (66.1% vs 33.9%). Integrating two RNA-seq microarray datasets, we found one hypomethylation-upregulated gene: eEF1A2, overlapped with our DNA methylation data. The mRNA expression of eEF1A2 was higher in twenty-four IMC tissues than in their paired adjacent nontumor tissues. GSEA indicated that the functions of eEF1A2 were associated with the development of IMCs. Furthermore, TCGA data indicated that eEF1A2 is hypomethylated in advanced GC. Our study illustrates the implications of DNA methylation alterations in IMCs and suggests that aberrant hypomethylation and high mRNA expression of eEF1A2 might play a role in IMCs development.

Discovering different acupoint combinations of manual or electro-acupuncture to treat chemotherapy-induced nausea and vomiting based on the complex networks analysis.

OBJECTIVES: The aim of this research was to find the acupoint combinations of manual and electro-acupuncture to treat chemotherapy-induced nausea and vomiting via the complex networks analysis. METHODS: We conducted searches using PubMed, ScienceDirect, MEDLINE, Ovid, spring, Wiley, EMBASE, the Chinese biomedicine database, VIP information network, and China National Knowledge Infrastructure from the establishment of the databases to the August, 2023. Information about titles, journals, interventions, and main acupoints was extracted using the self-established "acupoint for prevention CINV data base" powered by EpiData. According to the level of literature evidence and sample size, the clinical trials and weights of the outcome indicators including nausea/vomiting efficiency were combined. After identifying articles, literature processing and complex network analysis were conducted. The degree distribution of each node, the probability distribution of node degree, the node clustering coefficient, and the distance matrix are calculated by software. RESULTS: Of the 4001 screened publications, 489 were eligible after careful selection. Our result showed the acupoints ST36 and PC6 were the most common combination acupoints in both electro and manual acupuncture. In terms of efficiency, ST36, PC6, and CV12 are significantly effective acupoints for manual acupuncture, and the PC6 and ST36 are effective acupoint for electro-acupuncture. CONCLUSIONS: We found that the near-far collocation method has been commonly used for different types of acupuncture treatment in CINV. Zhongwan, Shangwan, and Liangmen have been mainly used as local acupoints, while Neiguan, Hegu, Quchi, Zusanli, Gongsun, TaiChong, and Neiguan have been mainly used as distal acupoints. From the effect analysis, acupuncture treatment of nausea manual acupuncture effect is better; acupuncture treatment of vomiting or electro-acupuncture effect is better.

Human leukocyte antigen-G in gynaecological tumours.

Gynaecological tumours that threaten the health of women, especially when advanced and recurrent, have remained mostly intractable to existing treatments. Therefore, new therapeutic targets are urgently needed. Human leukocyte antigen-G (HLA-G) is a nonclassical major histocompatibility complex class I molecule typically expressed in foetuses for protection against destruction by the maternal immune system. HLA-G is also expressed under pathological conditions, such as in solid tumours, and may participate in tumour development and serve as a novel immune checkpoint in cancer. Furthermore, it is expressed in most gynaecological tumours. Therefore, inhibiting HLA-G and its receptors to block the immune escape pathway could represent a new strategy in cancer immunotherapy. To the best of our knowledge, this review is the first to summarize recent research findings on HLA-G in gynaecological oncology. We highlight the fact that HLA-G is expressed in gynaecological tumour tissues, wherein it inactivates immune effectors involved in tumour progression. Further studies on HLA-G in gynaecological oncology are needed to incorporate HLA-G into the design and evaluation of immunotherapy for malignant gynaecological diseases.

Global research status and trends in orthopaedic surgical robotics: a bibliometric and visualisation analysis study.

This study aimed to investigate and summarise the current state of research and trends in orthopaedic surgical robots. Data on publicly available publications related to orthopaedic surgical robots were extracted by abstract searches of the Web of Science Core Collection database. A bibliometric analysis and detailed reading of the publications were then carried out and the information was visualised using co-authorship analysis, coupling analysis, co-citation analysis and co-occurrence analysis in VOSviewer. With 436 publications included in the study from 1993 to 2022, the overall contribution of publications to the world showed an increasing trend year by year, with a particularly pronounced after 2017, and a geographical trend of predominantly East Asia, North America, and Western Europe. Of these, China was the largest contributor (n = 128). Overall, the UK affiliates and their scholars were leaders in the field, with a high number of publications, total citations, average citations per article and H-index. The most published institutions and authors were Imperial College London (n = 21) and Professor Fares Sahi Haddad of University College London (n = 12), respectively. Journals with a high overall impact on robotic orthopaedic surgery were the Journal of Arthroplasty, Bone Joint Journal, International Journal of Medical Robotics and Computer Assisted Surgery. Keyword co-occurrence network analysis revealed four main clusters: robot-assisted knee, hip arthroplasty, spine surgery, and robotic technology research and development. The top three most common sites for robot-assisted surgery use were the knee, hip and spine. The most used robot types were the knee and spine, with Mako and Arobot being the most used robots for the knee and TiRobot for the spine. This study comprehensively reveals the current status and trends of global research on orthopaedic surgical robots, covering countries, institutions, authors, journals, research hotspots, robot types and surgical sites, providing directional guidance and research ideas for further research on the technological development and clinical evaluation of orthopaedic surgical robots.

Transcriptomic analysis of mid-secretory endometrium reveals essential immune factors associated with pregnancy after single euploid blastocyst transfer.

PURPOSE: Implantation is a limiting factor for treatment success in assisted reproduction. Both embryonic and endometrial factors contribute to implantation. Embryonic factors have often been ignored in previous studies about the role of endometrium in implantation. In this study, we sought to identify the endometrial genes associated with negative pregnancy outcomes following the transfer of a single euploid blastocyst. METHODS: Computational analyses of the transcriptomes of mid-secretory endometria from nine pregnant and seven non-pregnant patients in a cycle preceding the transfer of a single euploid blastocyst in a vitrified-warmed cycle were performed. RESULTS: Principal component analysis of two reported endometrial receptivity gene sets showed close clustering of the pregnant and non-pregnant samples. Differential gene expression analysis and co-expression module analysis identified 131 genes associated with the pregnancy status. The endometrial signatures identified highlight the importance of immune and metabolic regulation in pregnancy outcome. Network analysis identified 20 hub genes that could predict pregnancy outcomes with 88.9% sensitivity and 85.7% specificity. Single-cell gene expression analysis highlighted the regulation of endometrial natural killer (NK) cells, T cells, and macrophages during embryo implantation. Immune cell abundance analysis supported the dysregulation of cytotoxic immune cells in the endometria of non-pregnant women. CONCLUSIONS: We reported the first endometrial gene signature associated with pregnancy after elimination of embryo aneuploidy and highlighted the importance of the endometrial immune microenvironment and metabolic status in pregnancy outcomes.

Outcomes associated with different surgical approaches to radical hysterectomy: A systematic review and network meta-analysis.

OBJECTIVE: To evaluate the efficacy and safety of five different approaches to cervical cancer surgery. METHODS: We conducted a systematic search for comparative studies on different radical hysterectomy types for cervical cancer in PubMed, Embase, the Cochrane Library, and Web of Science databases. All included observational studies used survival analyses to compare clinical outcomes of patients undergoing different radical hysterectomy types. All studies were assessed by the Newcastle-Ottawa Scale with scores of at least seven points. We extracted the relevant data and conducted a network meta-analysis to compare clinical outcomes among five surgical approaches. RESULTS: Thirty studies (n = 11 353) were included. Robotic surgery had the lowest blood loss volume and hospitalization duration; open surgery had the shortest operative time. Vaginal assisted laparoscopic surgery was associated with the highest number of resected lymph nodes and lowest rate of perioperative complications. Survival outcomes and tumor recurrence outcomes were similar among the approaches. CONCLUSION: The current approaches to cervical cancer surgery have comparable efficacies.

Maternal preterm birth prediction in the United States: a case-control database study.

BACKGROUND: Preterm birth is serious public health worldwide, and early prediction of preterm birth in pregnant women may provide assistance for timely intervention and reduction of preterm birth. This study aimed to develop a preterm birth prediction model that is readily available and convenient for clinical application. METHODS: Data used in this case-control study were extracted from the National Vital Statistics System (NVSS) database between 2018 and 2019. Univariate and multivariate logistic regression analyses were utilized to find factors associated with preterm birth. Odds ratio (OR) and 95% confidence interval (CI) were used as effect measures. The area under the curve (AUC), accuracy, sensitivity, and specificity were utilized as model performance evaluation metrics. RESULTS: Data from 3,006,989 pregnant women in 2019 and 3,039,922 pregnant women in 2018 were used for the model establishment and external validation, respectively. Of these 3,006,989 pregnant women, 324,700 (10.8%) had a preterm birth. Higher education level of pregnant women [bachelor (OR = 0.82; 95%CI, 0.81-0.84); master or above (OR = 0.82; 95%CI, 0.81-0.83)], pre-pregnancy overweight (OR = 0.96; 95%CI, 0.95-0.98) and obesity (OR = 0.94; 95%CI, 0.93-0.96), and prenatal care (OR = 0.48; 95%CI, 0.47-0.50) were associated with a reduced risk of preterm birth, while age ≥ 35 years (OR = 1.27; 95%CI, 1.26-1.29), black race (OR = 1.26; 95%CI, 1.23-1.29), pre-pregnancy underweight (OR = 1.26; 95%CI, 1.22-1.30), pregnancy smoking (OR = 1.27; 95%CI, 1.24-1.30), pre-pregnancy diabetes (OR = 2.08; 95%CI, 1.99-2.16), pre-pregnancy hypertension (OR = 2.22; 95%CI, 2.16-2.29), previous preterm birth (OR = 2.95; 95%CI, 2.88-3.01), and plurality (OR = 12.99; 95%CI, 12.73-13.24) were related to an increased risk of preterm birth. The AUC and accuracy of the prediction model in the testing set were 0.688 (95%CI, 0.686-0.689) and 0.762 (95%CI, 0.762-0.763), respectively. In addition, a nomogram based on information on pregnant women and their spouses was established to predict the risk of preterm birth in pregnant women. CONCLUSIONS: The nomogram for predicting the risk of preterm birth in pregnant women had a good performance and the relevant predictors are readily available clinically, which may provide a simple tool for the prediction of preterm birth.

Single-cell Sequencing Reveals Clearance of Blastula Chromosomal Mosaicism in In Vitro Fertilization Babies.

Although chromosomal mosaic embryos detected by trophectoderm (TE) biopsy offer healthy embryos available for transfer, high-resolution postnatal karyotyping and chromosome testing of the transferred embryos are insufficient. Here, we applied single-cell multi-omics sequencing for seven infants with blastula chromosomal mosaicism detected by TE biopsy. The chromosome ploidy was examined by single-cell genome analysis, with the cellular identity being identified by single-cell transcriptome analysis. A total of 1616 peripheral leukocytes from seven infants with embryonic chromosomal mosaicism and three control ones with euploid TE biopsy were analyzed. A small number of blood cells showed copy number alterations (CNAs) on seemingly random locations at a frequency of 0%-2.5% per infant. However, none of the cells showed CNAs that were the same as those of the corresponding TE biopsies. The blastula chromosomal mosaicism may be fully self-corrected, probably through the selective loss of the aneuploid cells during development, and the transferred embryos can be born as euploid infants without mosaic CNAs corresponding to the TE biopsies. The results provide a new reference for the evaluations of transferring chromosomal mosaic embryos in certain situations.

Lifestyle Behaviors and Depressive Symptoms in Chinese Adolescents Using Regression and fsQCA Models.

The study was to compare the performance of the regression models and fuzzy set qualitative comparative analysis (fsQCA) models in analyzing the possible effects of sociodemographic variables (age and sex) and lifestyle behaviors (physical activity, sedentary time, sleep duration, physical education class and screen time) on depressive symptoms in adolescents. This cross-sectional surgery was conducted among 726 adolescents in Jilin Province of China, selected by random cluster sampling. The regression model showed that age, physical education (PE) class and sleep duration were associated with depressive symptoms. Meanwhile, the fsQCA models showed that shorter physical activity, PE class and sleep duration as well as longer sedentary and screen time were related to higher levels of depressive symptoms. Both regression and fsQCA models indicated that promoting lifestyle behaviors could affect depressive symptoms. Considering the differences between the two methods, they are not superior to the other method, but complementary and should be used in other studies at the same time.

Deep learning for automatic diagnosis of gastric dysplasia using whole-slide histopathology images in endoscopic specimens.

BACKGROUND: Distinguishing gastric epithelial regeneration change from dysplasia and histopathological diagnosis of dysplasia is subject to interobserver disagreement in endoscopic specimens. In this study, we developed a method to distinguish gastric epithelial regeneration change from dysplasia and further subclassify dysplasia. Meanwhile, optimized the cross-hospital diagnosis using domain adaption (DA). METHODS: 897 whole slide images (WSIs) of endoscopic specimens from two hospitals were divided into training, internal validation, and external validation cohorts. We developed a deep learning (DL) with DA (DLDA) model to classify gastric dysplasia and epithelial regeneration change into three categories: negative for dysplasia (NFD), low-grade dysplasia (LGD), and high-grade dysplasia (HGD)/intramucosal invasion neoplasia (IMN). The diagnosis based on the DLDA model was compared to 12 pathologists using 100 gastric biopsy cases. RESULTS: In the internal validation cohort, the diagnostic performance measured by the macro-averaged area under the receiver operating characteristic curve (AUC) was 0.97. In the independent external validation cohort, our DLDA models increased macro-averaged AUC from 0.67 to 0.82. In terms of the NFD and HGD cases, our model's diagnostic sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were significantly higher than junior and senior pathologists. Our model's diagnostic sensitivity, NPV, was higher than specialist pathologists. CONCLUSIONS: We demonstrated that our DLDA model could distinguish gastric epithelial regeneration change from dysplasia and further subclassify dysplasia in endoscopic specimens. Meanwhile, achieved significant improvement of diagnosis cross-hospital.

Combined legumain- and integrin-targeted nanobubbles for molecular ultrasound imaging of breast cancer.

Molecular ultrasound imaging is a promising strategy for non-invasive and precise cancer diagnosis. Previously reported ultrasound contrast agents (UCAs) are mostly microbubbles or nanobubbles (NBs) larger than 200 nm, leading to less efficient tumor delivery. Here we synthesized NBs with a small size (~49 nm) and modified the NB surface with alanine-alanine-asparagine (NB-A) or arginine-glycine-aspartic acid peptide (NB-R) for concurrent active targeting towards legumain in tumor cells and integrin in tumor neovasculature. In vitro, the NB-A and NB-R presented echogenicity comparable with SonoVue MBs and showed specific binding with tumors cells and endothelial cells, respectively. In vivo, the combined NB-A/NB-R accumulated in tumor tissues selectively and provided ultrasound signals with prolonged duration and that were significantly stronger than non-targeted NBs, single-targeted NBs and SonoVue MBs. Overall, the dual targeted NBs served as efficient UCAs for specific imaging of breast cancer, and hold great potential for general cancer diagnosis/monitoring in the future.

Asparagine endopeptidase-targeted Ultrasound-responsive Nanobubbles Alleviate Tau Cleavage and Amyloid-ß Deposition in an Alzheimer's Disease Model.

Inhibition of asparagine endopeptidase (AEP) has been implied to be effective for treating tau- and amyloid-beta-mediated neurodegenerative diseases, although a method for targeted intracerebral delivery of AEP inhibitors has not yet been achieved. Here, we fabricated ultrasound-responsive nanobubbles (NBs) to load AEP inhibitor RR-11a, and modified the NB surface with either AEP recognizable peptide AAN or pro-transendothelial transversal motif RGD, i.e. NB(11a)-A and NB(11a)-R, for AEP-targeted treatment of Alzheimer's disease (AD). The developed NBs were uniform, small in size (50.1 ± 1.5 nm), with strong echogenicity and high drug loading efficiency (∼91.97%). When intravenously co-injected in the APP/PS1 mouse model, NB(11a)-R could adhere to endothelial cells and enhance transient opening of the blood-brain barrier (BBB) upon focused ultrasound oscillations, allowing the rest NBs/localized released RR-11a molecules to enter the brain, and then NB(11a)-A could selectively bind with the impaired neurons and deposit RR-11a molecules at the AD lesion. As a result, co-administration of NB(11a)-A and NB(11a)-R significantly promoted accumulation of RR-11a in the mouse brain, and substantially alleviated both tau cleavage and amyloid plaques deposition in the hippocampus. Most strikingly, the cognitive ability of the AD model mice was dramatically improved, achieving a level close to the normal mice. Overall, this unique AEP-targeted nanobubble design provides an efficient intracerebral drug delivery strategy and significantly enhances treatment efficacy of AD. STATEMENT OF SIGNIFICANCE: Asparagine endopeptidase (AEP) is an innovative therapeutic target simultaneously involved in Aß and tau-mediated Alzheimer's disease (AD) pathology, but targeted delivery of AEP inhibitors has not been achieved yet. Here we developed an efficient strategy to deliver AEP inhibitor RR-11a towards impaired neurons. We fabricated RR-11a-loaded ultrasound-responsive nanobubbles (NBs) and modified the NB surface with RGD peptide to promote BBB crossing upon focused ultrasound oscillations, or with AAN peptide to increase binding of NBs on the neurons. Our results indicated that, co-administration of the NB(11a)-A and NB(11a)-R significantly enhanced accumulation of RR-11a molecules at the AD lesion, alleviated both tau cleavage and amyloid plaques deposition in the hippocampus, and consequently restored cognitive function of the AD model mice.

[Application and Progress of Convolutional Neural Network-based Pathological Diagnosis of Gastric Cancer].

The incidence of gastric cancer is the highest among all kinds of malignant tumors in China. Because gastric cancer is very hard to identify in its early stage, the early diagnosis rate of gastric cancer in China is relatively low. At present, the pathological diagnosis of gastric cancer mainly depends on the diagnosis of pathologists. However, the gradual improvement of people's living standards and the growing demand for medical and health care have exacerbated the shortage of medical resources, which has become a even more serious problem. Therefore, there is an urgent need for new technologies to help deal with this challenge. In recent years, with the rapid development of artificial intelligence (AI) and digital pathology, AI-aided pathological diagnosis based on convolutional neural network (CNN) as the core technology is showing promises for improving the diagnostic efficiency of gastric cancer. It is also of great significance for the early diagnosis and treatment of the disease and the reduction of its high incidence and mortality. We herein summarize the application and progress of deep-learning CNN in pathological diagnosis of gastric cancer, as well as the existing problems and prospects of future development.