Pelvic floor muscle strength and influencing factors based on vaginal manometry among healthy women at different life stages: A multicentre cross-sectional study.

OBJECTIVE: To assess pelvic floor muscle (PFM) strength and influencing factors among healthy women at different life stages. DESIGN: Multicentre cross-sectional study. SETTING: Fourteen hospitals in China. POPULATION: A total of 5040 healthy women allocated to the following groups (with 1680 women per group): premenopausal nulliparous, premenopausal parous and postmenopausal. METHODS: The PFM strength was evaluated by vaginal manometry. Multivariate logistic regression was used to determine the influencing factors for low PFM strength. MAIN OUTCOME MEASURES: Maximum voluntary contraction pressure (MVCP). RESULTS: The median MVCP values were 36, 35 and 35 cmH2O in premenopausal nulliparous (aged 19-51 years), premenopausal parous (aged 22-61 years), and postmenopausal (aged 40-86 years) women, respectively. In the premenopausal nulliparous group, physical work (odds ratio, OR 2.05) was the risk factor for low PFM strength, which may be related to the chronic increased abdominal pressure caused by physical work. In the premenopausal parous group, the number of vaginal deliveries (OR 1.28) and diabetes (OR 2.70) were risk factors for low PFM strength, whereas sexual intercourse (<2 times per week vs. none, OR 0.55; ≥2 times per week vs. none, OR 0.56) and PFM exercise (OR 0.50) may have protective effects. In the postmenopausal group, the number of vaginal deliveries (OR 1.32) and family history of pelvic organ prolapse (POP) (OR 1.83) were risk factors for low PFM strength. CONCLUSIONS: Physical work, vaginal delivery, diabetes and a family history of POP are all risk factors for low PFM strength, whereas PFM exercises and sexual life can have a protective effect. The importance of these factors varies at different stages of a woman's life.

The role of peroxisome proliferator-activated receptors in the tumor microenvironment, tumor cell metabolism, and anticancer therapy.

Peroxisome proliferator-activated receptors (PPARs) have been extensively studied for over 3 decades and consist of three isotypes, including PPARα, γ, and ß/δ, that were originally considered key metabolic regulators controlling energy homeostasis in the body. Cancer has become a leading cause of human mortality worldwide, and the role of peroxisome proliferator-activated receptors in cancer is increasingly being investigated, especially the deep molecular mechanisms and effective cancer therapies. Peroxisome proliferator-activated receptors are an important class of lipid sensors and are involved in the regulation of multiple metabolic pathways and cell fate. They can regulate cancer progression in different tissues by activating endogenous or synthetic compounds. This review emphasizes the significance and knowledge of peroxisome proliferator-activated receptors in the tumor microenvironment, tumor cell metabolism, and anti-cancer treatment by summarizing recent research on peroxisome proliferator-activated receptors. In general, peroxisome proliferator-activated receptors either promote or suppress cancer in different types of tumor microenvironments. The emergence of this difference depends on various factors, including peroxisome proliferator-activated receptor type, cancer type, and tumor stage. Simultaneously, the effect of anti-cancer therapy based on drug-targeted PPARs differs or even opposes among the three peroxisome proliferator-activated receptor homotypes and different cancer types. Therefore, the current status and challenges of the use of peroxisome proliferator-activated receptors agonists and antagonists in cancer treatment are further explored in this review.

Anti-inflammatory and immunomodulatory effects of polysaccharide extracted from Wuguchong (maggot) on 2,4-dinitrochlorobenzene-induced atopic dermatitis in mice.

Atopic dermatitis (AD) is an inflammatory, heterogeneous, chronic skin disorder characterized by recurrent eczematous lesions and intense pruritus, and the pathophysiology mechanism of AD is known for immune dysregulation and inflammatory responses. Wuguchong (maggot) has been widely used in the wound field and found with pharmacological properties of the anti-inflammatory and immunomodulatory function. Recently, some polysaccharides were proven to have beneficial effects on AD skin lesions in mice and humans. However, the effect of the polysaccharide extracted from Wuguchong (PEW) on AD remains to be investigated. In the present study, we examined the anti-inflammatory and immunomodulatory effects of PEW on AD and explored the potential mechanisms. Balb/c mice were orally administrated with PEW to evaluate the therapeutic effect of PEW on 2,4-dinitrochlorobenzene (DNCB)-induced AD. Oral PEW administration significantly ameliorated the lesions and symptoms in AD mice, such as the ear thickness and ear swelling degree, epidermal and dermal thickness, and the infiltration of mast cells. In addition, PEW treatment decreased the levels of serum IgE and histamine, the frequencies of Th1 and Th17 cells, as well as the mRNA expression levels of Th1 and Th17 cytokines and nuclear transcript factors (IFN-γ, T-bet, IL-17A, and ROR-rt). Furthermore, the activation of the NF-κB pathway and the phosphorylation of MAPKs (p38, ERK, and JNK) were significantly suppressed by PEW treatment. Taken together, our study suggests that PEW exerts anti-inflammatory and immunomodulatory effects through inhibition of Th1 and Th17 responses and downregulation of NF-κB and MAPK pathways, PEW would be developed as a promising immune therapy for AD.

Identification of ferroptosis-related molecular clusters and genes for diabetic osteoporosis based on the machine learning.

Background: Diabetic osteoporosis exhibits heterogeneity at the molecular level. Ferroptosis, a controlled form of cell death brought on by a buildup of lipid peroxidation, contributes to the onset and development of several illnesses. The aim was to explore the molecular subtypes associated with ferroptosis in diabetic osteoporosis at the molecular level and to further elucidate the potential molecular mechanisms. Methods: Integrating the CTD, GeneCards, FerrDb databases, and the microarray data of GSE35958, we identified ferroptosis-related genes (FRGs) associated with diabetic osteoporosis. We applied unsupervised cluster analysis to divide the 42 osteoporosis samples from the GSE56814 microarray data into different subclusters based on FRGs. Subsequently, FRGs associated with two ferroptosis subclusters were obtained by combining database genes, module-related genes of WGCNA, and differentially expressed genes (DEGs). Eventually, the key genes from FRGs associated with diabetic osteoporosis were identified using the least absolute shrinkage and selection operator (LASSO), Boruta, support vector machine recursive feature elimination (SVM - RFE), and extreme gradient boosting (XGBoost) machine learning algorithms. Based on ROC curves of external datasets (GSE56815), the model's efficiency was examined. Results: We identified 15 differentially expressed FRGs associated with diabetic osteoporosis. In osteoporosis, two distinct molecular clusters related to ferroptosis were found. The expression results and GSVA analysis indicated that 15 FRGs exhibited significantly different biological functions and pathway activities in the two ferroptosis subclusters. Therefore, we further identified 17 FRGs associated with diabetic osteoporosis between the two subclusters. The results of the comprehensive analysis of 17 FRGs demonstrated that these genes were heterogeneous and had a specific interaction between the two subclusters. Ultimately, the prediction model had a strong foundation and excellent AUC values (0.84 for LASSO, 0.84 for SVM - RFE, 0.82 for Boruta, and 0.81 for XGBoost). IDH1 is a common gene to all four algorithms thus being identified as a key gene with a high AUC value (AUC = 0.698). Conclusions: As a ferroptosis regulator, IDH1 is able to distinguish between distinct molecular subtypes of diabetic osteoporosis, which may offer fresh perspectives on the pathogenesis of the disease's clinical symptoms and prognostic heterogeneity.

Revealing the novel ferroptosis-related therapeutic targets for diabetic foot ulcer based on the machine learning.

Objectives: DFU is a serious chronic disease with high disability and fatality rates, yet there is no completely effective therapy. While ferroptosis is integrated to inflammation and infection, its involvement in DFU is still unclear. The study aimed to identify ferroptosis-related genes in DFU, providing potential therapeutic targets. Methods: In the GEO database, two DFU microarray datasets (GSE147890 and GSE80178) were collected. WGCNA was conducted to identify the modular genes most involved in DFU. Subsequently, enrichment analysis and PPI analysis were performed. To yield the DFU-associated ferroposis genes, the ferroposis genes were retrieved from the FerrDb database and overlapped with the modular genes. Eventually, an optimal DFU prediction model was created by combining multiple machine learning algorithms (LASSO, SVM-RFE, Boruta, and XGBoost) to detect ferroposis genes most closely associated with DFU. The accuracy of the model was verified by utilizing external datasets (GSE7014) based on ROC curves. Results: WGCNA yielded seven modules in all, and 1223 DFU-related modular genes were identified. GO analysis revealed that inflammatory response, decidualization, and protein binding were the most highly enriched terms. These module genes were also enriched in the ErbB signaling, IL-17 signaling, MAPK signaling, growth hormone synthesis, secretion and action, and tight junction KEGG pathways. Twenty-five DFU-associated ferroposis genes were obtained by cross-linking with modular genes, which could distinguish DFU patients from controls. Ultimately, the prediction model based on machine learning algorithms was well established, with high AUC values (0.79 of LASSO, 0.80 of SVM, 0.75 of Boruta, 0.70 of XGBoost). MAFG and MAPK3 were identified by the prediction model as the most highly associated ferroposis-genes in DFU. Furthermore, the external dataset (GSE29221) validation revealed that MAPK3 (AUC = 0.81) had superior AUC values than MAFG (AUC = 0.62). Conclusion: As the most related ferroptosis-genes with DFU, MAFG and MAPK3 may be employed as potential therapeutic targets for DFU patients. Moreover, MAPK3, with higher accuracy, could be the more potential ferroptosis-related biomarker for further experimental validation.

JQ1 inhibits high glucose-induced migration of retinal microglial cells by regulating the PI3K/AKT signaling pathway.

Diabetic retinopathy (DR) is one of the main leading causes of visual impairment worldwide. The current study elucidates the role of JQ1 in DR. A diabetic model was constructed by STZ injection and a high-fat diet. After establishment of the diabetic model, rats were assigned to treatment groups: 1) control, 2) diabetic model, and 3) diabetic+JQ1 model. In vitro Transwell and wound-healing assays were used to measure BV2 cell viability by stimulation with low glucose and high glucose with or without JQ1 and 740Y-P. Pathological methods were used to analyze DR, and Western blotting was used to analyze protein expression. Identification of enriched pathways in DR was performed by bioinformatics. Histopathological examination demonstrated that JQ1 rescued the loss of retinal cells and increased the thickness of retinal layers in diabetic rats. JQ1 attenuated high glucose-stimulated BV2 microglial motility and migration. The bioinformatics analysis implied that the Pl3K-Akt signaling pathway was enriched in DR. JQ1 decreased the phosphorylation of PI3K and AKT as well as the immunostaining of PI3K in BV2 cells. 740Y-P (a PI3K agonist) significantly reversed the decrease in p-PI3K and p-AK in BV2 cells. Additionally, JQ1 decreased the protein expression of p-PI3K, p-AKT, and MMP2/9 and immunostaining of PI3K in retinal tissues of rats. JQ1 suppresses the PI3K/Akt cascade by targeting MMP expression, thus decreasing the viability and invasion capacity of retinal microglia, suggesting an interesting treatment target for DR.

Protective effect of homogeneous polysaccharides of Wuguchong (HPW) on intestinal mucositis induced by 5-fluorouracil in mice.

BACKGROUND: In hospitalized patients, drug side effects usually trigger intestinal mucositis (IM), which in turn damages intestinal absorption and reduces the efficacy of treatment. It has been discovered that natural polysaccharides can relieve IM. In this study, we extracted and purified homogenous polysaccharides of Wuguchong (HPW), a traditional Chinese medicine, and explored the protective effect of HPW on 5-fluorouracil (5-FU)-induced IM. METHODS AND RESULTS: First, we identified the physical and chemical properties of the extracted homogeneous polysaccharides. The molecular weight of HPW was 616 kDa, and it was composed of 14 monosaccharides. Then, a model of small IM induced by 5-FU (50 mg/kg) was established in mice to explore the effect and mechanism of HPW. The results showed that HPW effectively increased histological indicators such as villus height, crypt depth and goblet cell count. Moreover, HPW relieved intestinal barrier indicators such as D-Lac and diamine oxidase (DAO). Subsequently, western blotting was used to measure the expression of Claudin-1, Occludin, proliferating cell nuclear antigen, and inflammatory proteins such as NF-κB (P65), tumour necrosis factor-α (TNF-α), and COX-2. The results also indicated that HPW could reduce inflammation and protect the barrier at the molecular level. Finally, we investigated the influence of HPW on the levels of short-chain fatty acids, a metabolite of intestinal flora, in the faeces of mice. CONCLUSIONS: HPW, which is a bioactive polysaccharide derived from insects, has protective effects on the intestinal mucosa, can relieve intestinal inflammation caused by drug side effects, and deserves further development and research.

Are Entrepreneurs More Likely to Be Obese?

BACKGROUND: Entrepreneurs not only promote a nation's economic growth but also increase employment. The risk of obesity among entrepreneurs may bring heavy economic burdens not only to the entrepreneurs but also to the national health care system. We aimed to examine the association between entrepreneurship and the risk of obesity. METHODS: We utilized data from the 2015 Harmonized China Health and Retirement Longitudinal Survey, including 2,802 individuals aged between 45 and 65 with complete data. This study used BMI (Body Mass Index) (kg/m2) as an indicator of obesity risk. Entrepreneurs were defined as those respondents who run their own businesses as main jobs. We used multivariate OLS regression models and Bayesian Markov Chain Monte Carlo (MCMC) method to examine the link of entrepreneurship and obesity risk. RESULTS: The multivariate OLS regression results showed that entrepreneurship was positively associated with BMI (P<0.01). The Bayesian MCMC results indicated that the posterior mean was (0.597, 90% HPD CI: 0.319, 0.897), demonstrating that entrepreneurship was indeed significantly positively associated with the risk of obesity. CONCLUSION: Being an entrepreneur is positively associated with the risk of obesity. As obesity can cause diseases such as hypertension, diabetes, coronary heart disease and stroke, the health departments should take necessary health interventions to prevent entrepreneurs from being obese in order to increase their entrepreneurial success.

Iron, Zinc and Copper from Cereal Food Sources and Cognitive Performance in Older Adults in China.

Background: We aimed to determine the risk factors associated with cognitive performance in older adults in China. Methods: A longitudinal study was conducted in a group of 1,898 adults aged 60 yr and over in China, Cognitive score was determined by a modified Telephone Interview for Cognitive Status (TICSM). The dietary intake of iron (Fe), zinc (Zn) and copper (Cu) from cereal source foods (CSF) were calculated by using Food Frequency Questionnaire (FFQ) and Chinese Food Composition Tables. Descriptive statistics and multivariate mixed regression models were utilized to explore the association between the intake of these elements and cognitive function. Results: The mean dietary intakes of Fe, Zn and Cu from CSF were 12.01, 6.90 and 1.30 mg/d respectively. Compared with participants in the high-cognitive group, those in the low-cognitive group had lower total dietary intakes of Fe, Zn and Cu. However, with respect to ratios of CSF-Zn, CSF-Fe and CSF-Cu to their respective total values, participants in the low-cognitive group had significantly higher ratios than those in the high-cognitive group. The results of multivariate mixed regression model revealed that although total dietary Zn intake was positively linked with cognitive function, the CSF-Zn/Zn ratio was negatively associated with cognitive performance. Conclusion: Excessive intake of Zn from a specific food source, such as CSF, was found to be negatively associated with cognitive status. Avoiding over-intake of Zn from CSF foods and diversifying intake of Zn from different food sources seemed to protect individuals from cognitive decline.

Comparison of the 1-year survival rate in infants with congenital heart disease diagnosed by prenatal and postnatal ultrasound: A retrospective study.

ABSTRACT: The impact of prenatal diagnosis on the survival outcome of infants with congenital heart disease (CHD) is still unclear. This study aimed to compare the 1-year survival rate between the prenatally and postnatally diagnosed infants with CHDs.A single-center population-based retrospective cohort study was performed on data from all infants diagnosed with CHD born between January 1998 and December 2017. Among infants with isolated CHDs, the 1-year Kaplan-Meier survival probabilities for prenatal and postnatal diagnosis were estimated. Cox proportional hazard ratios were adjusted for critical CHD (CCHD) status and gestational age.A total of 424 (40 prenatally and 384 postnatally) diagnosed infants with CHDs were analyzed. Compared with non-CCHDs, infants with CCHDs were more likely to be prenatally diagnosed (55.0% vs 18.0%; P < .001). Among the 312 infants with isolated CHDs, the 1-year survival rate for the prenatally diagnosed was significantly lower than postnatally diagnosed (77.1% vs 96.1%; P < .001). For isolated CCHDs, the 1-year survival rate for the prenatally diagnosed was significantly lower than postnatally diagnosed (73.4% vs 90.0%; P < .001). The 1-year survival rate was increased with the increase of age at diagnosis. Among infants with isolated CHDs and CCHDs, the adjusted hazard ratios for 1-year mortality rates for the prenatally versus postnatally diagnosed were 2.554 (95% confidence interval [CI], 1.790, 3.654; P < .001) and 2.538 (95% CI: 1.796, 3.699; P < .001), respectively.Prenatal diagnosis is associated with lower 1-year survival rate for infants with isolated CCHDs. This could probably due to variation in the disease severity among the CCHD subtypes.

Clinical analysis of prenatal ultrasound diagnosis of fetal cardiovascular malformations in the first and second trimesters of pregnancy: A CARE-compliant article.

Fetal cardiovascular malformations is widely focused and screened, but the accuracy of screening is not satisfactory. In this study, we compared the types of congenital heart malformation, accompanying diseases and fetal outcomes in the first and second trimesters of pregnancy to clarify the advantage of early screening.From January 2013 to June 2018, 230 fetuses were diagnosed with congenital heart malformations using ultrasound method in Qilu Hospital of Shandong University, and divided into 2 groups:the first trimester fetuses (group A) and the second trimester fetuses (group B). In addition, we collected and organized medical data of 347 cases diagnosed with congenital heart disease during 1998 to 2005 (group C). We compared the spectrum of congenital heart disease, associated comorbidities and outcome of fetuses diagnosed with congenital heart disease.There were differences in the types and incidence of cardiac malformations between the first and second trimesters of pregnancy. The number of cases of non-cardiac malformation, congenital heart disease with single ventricular circulation, fetal intrauterine death and premature pregnancy termination was significantly lower in the late stage (group A and group B) than that in the early stage (group C). More patients were screened for trisomy 21, 18, 13 syndromes and Turner syndrome in group A than group B (P <.001). More fetuses with a 22q11 deletion were screened in group B than group C.Early pregnancy screening using ultrasound diagnosis is very important for fetuses with congenital heart disease.

Double-Stranded DNA in Exosomes of Malignant Pleural Effusions as a Novel DNA Source for EGFR Mutation Detection in Lung Adenocarcinoma.

Background: Exosomes are cell-derived vesicles and bear a specific set of nucleic acids including DNA (exoDNA). Thus, this study is to explore whether exoDNA in malignant pleural effusions (MPEs) could be a novel DNA source for mutation detection of epidermal growth factor receptor (EGFR). Methods: In this study, 52 lung adenocarcinoma patients were enrolled, and EGFR mutation status was detected with tumor tissues as well as cell blocks and exosomes in MPEs. The sensitivity, specificity and consistency of EGFR detection using exosomes were evaluated, compared with gene detection using tumor tissues and cell blocks. And the clinical response of patients who were detected as EGFR mutation in exosomes and treated with EGFR tyrosine kinase inhibitor (EGFR-TKI) was explored. Results: Gene detection using exosomes showed sensitivity of 100%, specificity of 96.55% and coincidence rate of 98.08% (Kappa = 0.961, P < 0.001), compared with detection using tumor tissues and cell blocks. After EGFR-TKI treatment, patients detected as EGFR mutation by exosomes showed efficacy rate of 83% and disease control rate of 100%. And patients who were detected as wild type in tumor tissues or cell blocks but EGFR mutation in exosomes turned up as PR or SD. Conclusions: These results demonstrated that exoDNA in MPEs could be used as a DNA source for EGFR detection in lung adenocarcinoma.

New model for predicting preterm delivery during the second trimester of pregnancy.

In this study, a new model for predicting preterm delivery (PD) was proposed. The primary model was constructed using ten selected variables, as previously defined in seventeen different studies. The ability of the model to predict PD was evaluated using the combined measurement from these variables. Therefore, a prospective investigation was performed by enrolling 130 pregnant patients whose gestational ages varied from 17+0 to 28+6 weeks. The patients underwent epidemiological surveys and ultrasonographic measurements of their cervixes, and cervicovaginal fluid and serum were collected during a routine speculum examination performed by the managing gynecologist. The results showed eight significant variables were included in the present analysis, and combination of the positive variables indicated an increased probability of PD in pregnant patients. The accuracy for predicting PD were as follows: one positive - 42.9%; two positives - 75.0%; three positives - 81.8% and four positives - 100.0%. In particular, the combination of ≥2× positives had the best predictive value, with a relatively high sensitivity (82.6%), specificity (88.1%) and accuracy rate (79.2%), and was considered the cut-off point for predicting PD. In conclusion, the new model provides a useful reference for evaluating the risk of PD in clinical cases.

Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data.

Gastric cancer (GC) is often diagnosed in the advanced stages and is associated with a poor prognosis. Obtaining an in depth understanding of the molecular mechanisms of GC has lagged behind compared with other cancers. This study aimed to identify candidate biomarkers for GC. An integrated analysis of microarray datasets was performed to identify differentially expressed genes (DEGs) between GC and normal tissues. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then performed to identify the functions of the DEGs. Furthermore, a protein-protein interaction (PPI) network of the DEGs was constructed. The expression levels of the DEGs were validated in human GC tissues using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A set of 689 DEGs were identified in GC tissues, as compared with normal tissues, including 202 upregulated DEGs and 487 downregulated DEGs. The KEGG pathway analysis suggested that various pathways may play important roles in the pathology of GC, including pathways related to protein digestion and absorption, extracellular matrix-receptor interaction, and the metabolism of xenobiotics by cytochrome P450. The PPI network analysis indicated that the significant hub proteins consisted of SPP1, TOP2A and ARPC1B. RT-qPCR validation indicated that the expression levels of the top 10 most significantly dysexpressed genes were consistent with the illustration of the integrated analysis. The present study yielded a reference list of reliable DEGs, which represents a robust pool of candidates for further evaluation of GC pathogenesis and treatment.

A transcriptome profile in hepatocellular carcinomas based on integrated analysis of microarray studies.

BACKGROUND: Despite new treatment options for hepatocellular carcinomas (HCC) recently, 5-year survival remains poor, ranging from 50 to 70%, which may attribute to the lack of early diagnostic biomarkers. Thus, developing new biomarkers for early diagnosis of HCC, is extremely urgent, aiming to decrease HCC-related deaths. METHODS: In the study, we conducted a comprehensive characterization of gene expression data of HCC based on a bioinformatics method. The results were confirmed by real time polymerase chain reaction (RT-PCR) and TCGA database to prove the credibility of this integrated analysis. RESULTS: After integrating analysis of seven HCC gene expression datasets, 1167 differential expressed genes (DEGs) were identified. These genes mainly participated in the process of cell cycle, oocyte meiosis, and oocyte maturation mediated by progesterone. The results of experiments and TCGA database validation in 10 genes was in full accordance with findings in integrated analysis, indicating the high credibility of our integrated analysis of different gene expression datasets. ASPM, CCT3, and NEK2 was showed to be significantly associated with overall survival of HCC patients in TCGA database. CONCLUSION: This method of integrated analysis may be a useful tool to minish the heterogeneity of individual microarray, hopefully outputs more accurate HCC transcriptome profiles based on large sample size, and explores some potential biomarkers and therapy targets for HCC.

Evaluation of anti-bacterial and wound healing activity of the fruits of Amorpha fruticosa L.

As the traditional Chinese medicine, the fresh fruits of Amorpha fruticosa L. were applied for the treatment of carbuncle, eczema and burn (Das et al., 2007). However, little is known about the functional roles of the fruits of Amorpha fruticosa L. during wound healing progress. In the present study, we evaluated both antimicrobial potential against a wide range of microorganisms and wound healing activity of the seven compounds isolated from the fruits of Amorpha fruticosa L in vitro and in vivo. Our results showed that compounds I (6a,12a-dehydroamorphin), V (dehydrosermundone) and VI (tephrosin) isolated from the fruits of Amorpha fruticosa L. performed dominant antimicrobial potential against microorganisms. Moreover, these compounds significantly enhanced fibroblasts proliferation and migration, leading to promotion of wound healing. Thus, it could be possible for the therapeutic utilization of Amorpha fruticosa L. for wound healing in the future.