Comprehensive analysis of immune-related lncRNAs in AML patients uncovers potential therapeutic targets and prognostic biomarkers.

Purpose: The objective of this study was to provide theoretically feasible strategies by understanding the relationship between the immune microenvironment and the diagnosis and prognosis of AML patients. To this end, we built a ceRNA network with lncRNAs as the core and analyzed the related lncRNAs in the immune microenvironment by bioinformatics analysis. Methods: AML transcriptome expression data and immune-related gene sets were obtained from TCGA and ImmPort. Utilizing Pearson correlation analysis, differentially expressed immune-related lncRNAs were identified. Then, the LASSO-Cox regression analysis was performed to generate a risk signature consisting immune-related lncRNAs. Accuracy of signature in predicting patient survival was evaluated using univariate and multivariate analysis. Next, GO and KEGG gene enrichment and ssGSEA were carried out for pathway enrichment analysis of 183 differentially expressed genes, followed by drug sensitivity and immune infiltration analysis with pRRophetic and CIBERSORT, respectively. Cytoscape was used to construct the ceRNA network for these lncRNAs. Results: 816 common lncRNAs were selected to acquire the components related to prognosis. The final risk signature established by multivariate Cox and stepwise regression analysis contained 12 lncRNAs engaged in tumor apoptotic and metastatic processes: LINC02595, HCP5, AC020934.2, AC008770.3, LINC01770, AC092718.4, AL589863.1, AC131097.4, AC012368.1, C1RL-AS1, STARD4-AS1, and AC243960.1. Based on this predictive model, high-risk patients exhibited lower overall survival rates than low-risk patients. Signature lncRNAs showed significant correlation with tumor-infiltrating immune cells. In addition, significant differences in PD-1/PD-L1 expression and bleomycin/paclitaxel sensitivity were observed between risk groups. Conclusion: LncRNAs related to immune microenvironment were prospective prognostic and therapeutic options for AML.

Polygenic risk-stratified screening for nasopharyngeal carcinoma in high-risk endemic areas of China: a cost-effectiveness study.

Background: Nasopharyngeal carcinoma (NPC) has an extremely high incidence rate in Southern China, resulting in a severe disease burden for the local population. Current EBV serologic screening is limited by false positives, and there is opportunity to integrate polygenic risk scores for personalized screening which may enhance cost-effectiveness and resource utilization. Methods: A Markov model was developed based on epidemiological and genetic data specific to endemic areas of China, and further compared polygenic risk-stratified screening [subjects with a 10-year absolute risk (AR) greater than a threshold risk underwent EBV serological screening] to age-based screening (EBV serological screening for all subjects). For each initial screening age (30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, and 65-69 years), a modeled cohort of 100,000 participants was screened until age 69, and then followed until age 79. Results: Among subjects aged 30 to 54 years, polygenic risk-stratified screening strategies were more cost-effective than age-based screening strategies, and almost comprised the cost-effectiveness efficiency frontier. For men, screening strategies with a 1-year frequency and a 10-year absolute risk (AR) threshold of 0.7% or higher were cost-effective, with an incremental cost-effectiveness ratio (ICER) below the willingness to pay (¥203,810, twice the local per capita GDP). Specifically, the strategies with a 10-year AR threshold of 0.7% or 0.8% are the most cost-effective strategies, with an ICER ranging from ¥159,752 to ¥201,738 compared to lower-cost non-dominated strategies on the cost-effectiveness frontiers. The optimal strategies have a higher probability (29.4-35.8%) of being cost-effective compared to other strategies on the frontier. Additionally, they reduce the need for nasopharyngoscopies by 5.1-27.7% compared to optimal age-based strategies. Likewise, for women aged 30-54 years, the optimal strategy with a 0.3% threshold showed similar results. Among subjects aged 55 to 69 years, age-based screening strategies were more cost-effective for men, while no screening may be preferred for women. Conclusion: Our economic evaluation found that the polygenic risk-stratified screening could improve the cost-effectiveness among individuals aged 30-54, providing valuable guidance for NPC prevention and control policies in endemic areas of China.

Probucol mitigates high-fat diet-induced cognitive and social impairments by regulating brain redox and insulin resistance.

Probucol has been utilized as a cholesterol-lowering drug with antioxidative properties. However, the impact and fundamental mechanisms of probucol in obesity-related cognitive decline are unclear. In this study, male C57BL/6J mice were allocated to a normal chow diet (NCD) group or a high-fat diet (HFD) group, followed by administration of probucol to half of the mice on the HFD regimen. Subsequently, the mice were subjected to a series of behavioral assessments, alongside the measurement of metabolic and redox parameters. Notably, probucol treatment effectively alleviates cognitive and social impairments induced by HFD in mice, while exhibiting no discernible influence on mood-related behaviors. Notably, the beneficial effects of probucol arise independently of rectifying obesity or restoring systemic glucose and lipid homeostasis, as evidenced by the lack of changes in body weight, serum cholesterol levels, blood glucose, hyperinsulinemia, systemic insulin resistance, and oxidative stress. Instead, probucol could regulate the levels of nitric oxide and superoxide-generating proteins, and it could specifically alleviate HFD-induced hippocampal insulin resistance. These findings shed light on the potential role of probucol in modulating obesity-related cognitive decline and urge reevaluation of the underlying mechanisms by which probucol exerts its beneficial effects.

A comprehensive meta-analysis on the association of SGLT2is and GLP-1RAs with vascular diseases, digestive diseases and fractures.

AIM: Sodium-glucose cotransporter-2 inhibitors (SGLT2is) and glucagon-like peptide 1 receptor agonists (GLP-1RAs) are two new classes of antidiabetic agents. We aimed to evaluate the association between these two drug classes and risk of various vascular diseases, digestive diseases and fractures. METHODS: Large randomized trials of SGLT2is and GLP-1RAs were included. Outcomes of interest were the various serious adverse events related to vascular diseases, digestive diseases and fractures. We performed meta-analyses using synthesize risk ratio (RR) and 95% confidence interval (CI) as effect size. RESULTS: We included 27 large trials. SGLT2is had significant association with less hypertension (RR 0.70, 95% CI 0.54-0.91), hypertensive crisis (RR 0.63, 95% CI 0.47-0.84), varicose vein (RR 0.34, 95% CI 0.13-0.92), and vomiting (RR 0.55, 95% CI 0.31-0.97); but more spinal compression fracture (RR 1.73, 95% CI 1.02-2.92) and tibia fracture. GLP-1RAs had significant association with more deep vein thrombosis (RR 1.92, 95% CI 1.23-3.00), pancreatitis (RR 1.54, 95% CI 1.07-2.22), and cholecystitis acute (RR 1.51, 95% CI 1.08-2.09); but less rib fracture (RR 0.59, 95% CI 0.35-0.97). Sensitivity analyses suggested that our findings were robust. CONCLUSIONS: SGLT2is may have protective effects against specific vascular and digestive diseases, whereas they may increase the incidence of site-specific fractures (e.g., spinal compression fracture). GLP-1RAs may have protective effects against site-specific fractures (i.e., rib fracture), whereas they may increase the incidence of specific vascular and digestive diseases. These findings may help to make a choice between SGLT2is and GLP-1RAs in clinical practice.

The burden and predictors of 30-day unplanned readmission in patients with acute liver failure: a national representative database study.

BACKGROUND: Liver diseases were significant source of early readmission burden. This study aimed to evaluate the 30-day unplanned readmission rates, causes of readmissions, readmission costs, and predictors of readmission in patients with acute liver failure (ALF). METHODS: Patients admitted for ALF from 2019 National Readmission Database were enrolled. Weighted multivariable logistic regression models were applied and based on Directed Acyclic Graphs. Incidence, causes, cost, and predictors of 30-day unplanned readmissions were identified. RESULTS: A total of 3,281 patients with ALF were enrolled, of whom 600 (18.3%) were readmitted within 30 days. The mean time from discharge to early readmission was 12.6 days. The average hospital cost and charge of readmission were $19,629 and $86,228, respectively. The readmissions were mainly due to liver-related events (26.6%), followed by infection (20.9%). The predictive factors independently associated with readmissions were age, male sex (OR 1.227, 95% CI 1.023-1.472; P = 0.028), renal failure (OR 1.401, 95% CI 1.139-1.723; P = 0.001), diabetes with chronic complications (OR 1.327, 95% CI 1.053-1.672; P = 0.017), complicated hypertension (OR 1.436, 95% CI 1.111-1.857; P = 0.006), peritoneal drainage (OR 1.600, 95% CI 1.092-2.345; P = 0.016), etc. CONCLUSIONS: Patients with ALF are at relatively high risk of early readmission, which imposes a heavy medical and economic burden on society. We need to increase the emphasis placed on early readmission of patients with ALF and establish clinical strategies for their management.

Comparison of different nutritional screening tools in nutritional screening of patients with cirrhosis: A cross-sectional observational study.

Aims: The Royal Free Hospital Nutritional Prioritizing Tool (RFH-NPT), the Liver Disease Undernutrition Screening Tool (LDUST) and Nutritional Risk Screening 2002 (NRS2002) were used by nurses to screen, compare, and analyze the nutritional status of patients with liver cirrhosis. The application value of different screening tools was summarized in the nutritional screening of patients with liver cirrhosis. Methods: In this study, LDUST, RFH-NPT, and NRS2002 were used by nurses to screen the nutritional status of hospitalized patients with liver cirrhosis within 24-48 h after admission. The study calculated validity indicators such as sensitivity, specificity, the area under the receiver operating curve (AUC), and reliability indicators such as the Kappa coefficient. The efficacy of these screening tools in the nutritional screening of patients with liver cirrhosis was compared. Results: Among the 207 patients, LDUST and NRS2002 identified 72.9 % and 23.7 % as undernourished, respectively. The sensitivity of LDUST and NRS2002 were 92.1 % and 30.0 %, respectively. The Kappa value of LDUST and RFH-NPT was 0.620, and the Kappa value of LDUST compared with NRS2002 was 0.144. Conclusion: This study shows that the Liver Disease Undernutrition Screening Tool, a special screening tool for patients with liver cirrhosis, has a more reliable screening effect and higher sensitivity than NRS2002. The Liver Disease Undernutrition Screening Tool is recommended for nutritional screening in patients with liver cirrhosis.

DDLA: a double deep latent autoencoder for diabetic retinopathy diagnose based on continuous glucose sensors.

The current diagnosis of diabetic retinopathy is based on fundus images and clinical experience. However, considering the ineffectiveness and non-portability of medical devices, we aimed to develop a diagnostic model for diabetic retinopathy based on glucose series data from the wearable continuous glucose monitoring system. Therefore, this study developed a novel method, i.e., double deep latent autoencoder, for exploring glycemic variability influence from multi-day glucose data for diabetic retinopathy. Specifically, the model proposed in this research could encode continuous glucose sensor data with non-continuous and variable length via the integration of a data reorganization module and a novel encoding module with fragmented-missing-wise objective function. Additionally, the model implements a double deep autoencoder, which integrated convolutional neural network, long short-term memory, to jointly capturing the inter-day and intra-day glucose latent features from glucose series. The effectiveness of the proposed model is evaluated through a cross-validation method to clinical datasets of 765 type 2 diabetes patients. The proposed method achieves the highest accuracy value (0.89), precision value (0.88), and F1 score (0.73). The results suggest that our model can be used to remotely diagnose and screen for diabetic retinopathy by learning potential features of glucose series data collected by wearable continuous glucose monitoring systems.

Identification of disease-specific genes related to immune infiltration in nonalcoholic steatohepatitis using machine learning algorithms.

To identify disease signature genes associated with immune infiltration in nonalcoholic steatohepatitis (NASH), we downloaded 2 publicly available gene expression profiles, GSE164760 and GSE37031, from the gene expression omnibus database. These profiles represent human NASH and control samples and were used for differential genes (DEGs) expression screening. Two machine learning methods, the Least Absolute Shrinkage and Selection Operator regression model and Support Vector Machine Recursive Feature Elimination, were used to identify candidate disease signature genes. The CIBERSORT deconvolution algorithm was employed to analyze the infiltration of 22 immune cell types in NASH. Additionally, we constructed a NASH cell model using HepG2 cells treated with oleic acid and free fatty acids. The construction of the cell model was verified using oil red O staining, and Western blotting was used to detect the protein expression of the disease signature genes in both control and model groups. As a result, a total of 262 DEGs were identified. These DEGs were primarily associated with metal ion transmembrane transporter activity, sodium ion transmembrane transporter protein activity, calcium ion, and neuroactive ligand-receptor interactions. FOS, IGFBP2, dual-specificity phosphatase 1 (DUSP1), and IKZF3 were identified as disease signature genes of NASH by the least absolute shrinkage and selection operator and Support Vector Machine Recursive Feature Elimination algorithms for DEGs analysis. The receiver operating characteristic curves showed that FOS, IGFBP2, DUSP1, and IKZF3 had good diagnostic value (area under receiver operating characteristic curve > 0.8). These findings were validated in the GSE89632 dataset and through cellular assays. Immunocyte infiltration analysis revealed that NASH was associated with CD8 T cells, CD4 T cells, follicular helper T cells, resting NK cells, eosinophils, regulatory T cells, and γδ T cells. The FOS, IGFBP2, DUSP1, and IKZF3 genes were specifically associated with follicular helper T cells. Lipid droplet aggregation significantly increased in HepG2 cells treated with oleic acid and free fatty acids, indicating successful construction of the cell model. In this model, the expression of FOS, IGFBP2, and DUSP1 was significantly decreased, while that of IKZF3 was significantly elevated (P < .01, P < .001) compared with the control group. Therefore, FOS, IGFBP2, DUSP1, and IKZF3 can be considered as disease signature genes associated with immune infiltration in NASH.

Deep learning-based differentiation of ventricular septal defect from tetralogy of Fallot in fetal echocardiography images.

BACKGROUND: Congenital heart disease (CHD) seriously affects children's health and quality of life, and early detection of CHD can reduce its impact on children's health. Tetralogy of Fallot (TOF) and ventricular septal defect (VSD) are two types of CHD that have similarities in echocardiography. However, TOF has worse diagnosis and higher morality than VSD. Accurate differentiation between VSD and TOF is highly important for administrative property treatment and improving affected factors' diagnoses. OBJECTIVE: TOF and VSD were differentiated using convolutional neural network (CNN) models that classified fetal echocardiography images. METHODS: We collected 105 fetal echocardiography images of TOF and 96 images of VSD. Four CNN models, namely, VGG19, ResNet50, NTS-Net, and the weakly supervised data augmentation network (WSDAN), were used to differentiate the two congenital heart diseases. The performance of these four models was compared based on sensitivity, accuracy, specificity, and AUC. RESULTS: VGG19 and ResNet50 performed similarly, with AUCs of 0.799 and 0.802, respectively. A superior performance was observed with NTS-Net and WSDAN specific for fine-grained image categorization tasks, with AUCs of 0.823 and 0.873, respectively. WSDAN had the best performance among all models tested. CONCLUSIONS: WSDAN exhibited the best performance in differentiating between TOF and VSD and is worthy of further clinical popularization.

An elastic single crystal composed of one-dimensional chiral coordination polymers.

A single crystal composed of one-dimensional coordinated polymers, [CdCl2(1-methyl-2-pyridone)]n, has been synthesized and characterized. This compound exhibits outstanding elastic bending due to the molecular spring nature of the CdCl2 coordination framework and weak intermolecular interactions between the coordination chains. Owing to the helical arrangement of organic ligands surrounding the coordination structure, the compound crystallizes in a chiral space group. As a result, it displays compelling circular dichroism spectra and second harmonic generation properties.

Discordant results between Xpert MTB/RIF assay and Bactec MGIT 960 culture system regarding the detection of rifampin-resistant Mycobacterium tuberculosis isolates in Wenzhou, China.

This study aimed to assess the possible causes of discordant results between Xpert MTB/RIF (Xpert) and Bactec MGIT 960 Culture System (MGIT960) regarding rifampicin (RIF) susceptibility in Mycobacterium tuberculosis. Patients with previous RIF-resistant tuberculosis who were admitted to Wenzhou Central Hospital from January 2020 to December 2022 were enrolled. The isolates obtained from these patients were subjected to RIF susceptibility tests using Xpert and MGIT960, and the minimum inhibitory concentration (MIC) of RIF was determined by the MYCOTB MIC plate test. Additionally, molecular docking and molecular dynamics (MD) simulations were performed to evaluate the binding efficacy of rpoB and RIF based on rpoB mutations detected in the isolates with discordant RIF susceptibility results. A total of 28 isolates with discordant RIF susceptibility test results were detected, 15 of them were RIF susceptible with MICs ≤ 0.5 µg/mL. Twelve out of 15 isolates contained borderline RIF resistance-associated mutations [L430P (n = 6), H445N (n = 6)], 1 isolate had D435Y and Q429H double mutation, and the remaining 2 isolates had a silent (Q432Q) mutation. Compared with the affinity of RIF toward the wild type (WT) (-45.83 kcal/mol) by MD, its affinity toward L452P (-55.52 kcal/mol), D435Y (-47.39 kcal/mol), L430P (approximately -69.72 kcal/mol), H445N (-49.53 kcal/mol), and Q429H (-55.67 kcal/mol) increased. Borderline RIF resistance-associated mutations were the main cause for the discordant RIF susceptibility results between Xpert and MGIT960, and the mechanisms of the resistance need further investigated.IMPORTANCEThis study is aimed at assessing discordant results between Xpert MTB/RIF (Xpert) assay and Bactec MGIT 960 Culture System (MGIT960) regarding the detection of rifampicin (RIF)-resistant Mycobacterium tuberculosis isolates in Wenzhou, China. The discordant results of RIF between these two assays were mainly caused by borderline RIF resistance-associated mutations, subsequently by silent mutations of rpoB. Borderline RIF resistance- associated mutations detected in our study were demonstrated to not be affected by the affinity of rpoB and RIF by molecular dynamics, and the mechanism of resistance was needed to be clarified. For the discordant results of RIF by Xpert and MGIT960 that occurred, rpoB DNA sequencing was recommended to investigate its association with resistance to RIF.

Effect of Orem's self-care model on discharge readiness of patients undergoing enterostomy: A randomized controlled trial.

OBJECTIVE: To evaluate the effectiveness of Orem's self-care model in preparing hospitals for the discharge of patients with colorectal cancer who undergo enterostomy. METHODS: 92 patients with enterostomy were recruited between February 2022 and February 2023 from a general tertiary hospital. The participants were assigned to either the intervention group or the control group randomly. The intervention group received Orem's self-care program and a three-month follow-up, whereas the control group received only routine care and a three-month follow-up. Discharge readiness, self-care ability, and stoma-quality-of-life data were collected at hospital discharge (T1), 30 days (T2), and 90 days (T3) after discharge. RESULTS: The intervention group had substantially higher discharge readiness (knowledge, p < 0.001; coping ability, p = 0.006; personal status, p = 0.001; expected support, p = 0.021; total score, p < 0.001), better self-care ability at T1 (self-care knowledge, p < 0.001; self-care skills, p = 0.010), better total quality of life (QoL) at T1, T2, and T3 (p < 0.001; p = 0.006; p = 0.014); better stoma management and daily routine at T1 (p = 0.004; p < 0.001); and better daily routine at T2 (p = 0.009) than the control group. CONCLUSIONS: The designed discharge readiness program based on Orem's self-care could promote effective patient discharge readiness, self-care knowledge, self-care skills, and QoL. TRIAL REGISTRATION: The trial number ChiCTR2200056302 registered on ClinicalTrials.gov.

iDNA-OpenPrompt: OpenPrompt learning model for identifying DNA methylation.

Introduction: DNA methylation is a critical epigenetic modification involving the addition of a methyl group to the DNA molecule, playing a key role in regulating gene expression without changing the DNA sequence. The main difficulty in identifying DNA methylation sites lies in the subtle and complex nature of methylation patterns, which may vary across different tissues, developmental stages, and environmental conditions. Traditional methods for methylation site identification, such as bisulfite sequencing, are typically labor-intensive, costly, and require large amounts of DNA, hindering high-throughput analysis. Moreover, these methods may not always provide the resolution needed to detect methylation at specific sites, especially in genomic regions that are rich in repetitive sequences or have low levels of methylation. Furthermore, current deep learning approaches generally lack sufficient accuracy. Methods: This study introduces the iDNA-OpenPrompt model, leveraging the novel OpenPrompt learning framework. The model combines a prompt template, prompt verbalizer, and Pre-trained Language Model (PLM) to construct the prompt-learning framework for DNA methylation sequences. Moreover, a DNA vocabulary library, BERT tokenizer, and specific label words are also introduced into the model to enable accurate identification of DNA methylation sites. Results and Discussion: An extensive analysis is conducted to evaluate the predictive, reliability, and consistency capabilities of the iDNA-OpenPrompt model. The experimental outcomes, covering 17 benchmark datasets that include various species and three DNA methylation modifications (4mC, 5hmC, 6mA), consistently indicate that our model surpasses outstanding performance and robustness approaches.

Clinical application value of pre-pregnancy carrier screening in Chinese Han childbearing population.

BACKGROUND: To explore the clinical application value of pre-conception expanded carrier screening (PECS) in the Chinese Han ethnicity population of childbearing age. METHODS: The results of genetic testing of infertile parents who underwent PECS in the Reproductive Medicine Center of the Second Affiliated Hospital of Zhengzhou University, China, from September 2019 to December 2021, were retrospectively analyzed. The carrier rate of single gene disease, the detection rate of high-risk parents, and the clinical outcome of high-risk parents were statistically analyzed. RESULTS: A total of 1372 Chinese Han ethnicity patients underwent PECS, among which 458 patients underwent the extended 108-gene test, their overall carrier rate was 31.7%, and the detection rate of high-risk parents was 0.3%. The highest carrier rates were SLC22A (2.4%), ATP7B (2.4%), MMACHC (2.2%), PAH (1.8%), GALC (1.8%), MLC1 (1.3%), UNC13D (1.1%), CAPN3 (1.1%), and PKHD1 (1.1%). There were 488 women with fragile X syndrome-FMR1 gene detection, and 6 patients (1.2%) had FMR1 gene mutation. A total of 426 patients were screened for spinal muscular atrophy-SMN1, and the carrier rate was 3.5%, and the detection rate of parents' co-carrier was 0.5%. CONCLUSION: Monogenic recessive hereditary diseases had a high carrier rate in the population. Pre-pregnancy screening could provide good prenatal and postnatal care guidance for patients and preimplantation genetic testing for monogenic/single gene disorders (PGT-M) and prenatal diagnosis could provide more precise reproductive choices for high-risk parents.

Efficacy of catheter ablation in ganglionated plexus for malignant vasovagal syncope children.

AIM: Malignant vasovagal syncope in children seriously affects their physical and mental health. Our study aimed to explore the efficacy of catheter ablation in ganglionated plexus with malignant vasovagal syncope children. CONCLUSION: Catheter ablation of ganglionated plexus was safe and effective in children with malignant vasovagal syncope and can be used as a treatment option for these children. METHODS: A total of 20 children diagnosed with malignant vasovagal syncope were enrolled in Beijing Children's Hospital, affiliated with Capital Medical University. All underwent catheter ablation treatment of ganglionated plexus. Ganglionated plexuses of the left atrium were identified by high-frequency stimulation and/or anatomic landmarks being targeted by radiofrequency catheter ablation. The efficacy of the treatment was evaluated by comparing the remission rate of post-operative syncopal symptoms and the rate of negative head-up tilt results. Safety and adverse events were evaluated. RESULTS: After follow-up for 2.5 (0.6-5) years, the syncope symptom scores were decreased significantly compared with before treatment [3 (2-4) versus 5 (3-8) scores, P < 0.01]. Eighty-five per cent (17/20) children no longer experienced syncope, whilst 80% (16/20) children showed negative head-up tilt test after treatment. No adverse effects such as cardiac arrhythmia occurred in the children.

Monitoring hepatocellular carcinoma using tumor content in circulating cell-free DNA.

PURPOSE: To evaluate the utility of tumor content in circulating cell-free DNA (ccfDNA) for monitoring hepatocellular carcinoma (HCC) throughout its natural history. METHODS: We included 67 hepatitis B virus (HBV)-related HCC patients, of whom 17 had paired pre- and post-treatment samples, and 90 controls. Additionally, in a prospective cohort with HBV surface antigen-positive participants recruited in 2012 and followed up biannually with blood sample collections until 2019, we included 270 repeated samples before diagnosis from 63 participants who later developed HCC (pre-HCC samples). Shallow whole-genome sequencing and the ichorCNA method were used to analyze genome-wide copy number and tumor content in ccfDNA. RESULTS: High tumor content was associated with advanced tumor stage (P < 0.001) and a poor survival after HCC diagnosis (HR=12.35; 95% confidence interval [CI]=1.413-107.9; P = 0.023). Tumor content turned negative after surgery (P = 0.027), while remained positive after transarterial chemoembolization treatment (P = 0.578). In non-HCC samples, the mean tumor content (±SD) was 0.011 (±0.007) and had a specificity of 97.8% (95%CI=92.2%-99.7%). In pre-HCC samples, tumor content increased from 0.014 in 4 years before diagnosis to 0.026 in 1 year before diagnosis. The sensitivity of tumor content in detecting HCC increased from 22.7% (95%CI=11.5%-37.8%) within one year before diagnosis to 30.4% (95%CI=13.2%-52.9%) at BCLC stage 0/A, 81.8% (95%CI=59.7%-94.8%) at stage B, and 95.5% (95%CI=77.2%-99.9%) at stage C. CONCLUSIONS: The tumor content in ccfDNA is correlated with tumor burden and may help in monitoring HCC one year earlier than clinical diagnosis and in predicting patient prognosis.

Application of interpretable machine learning algorithms to predict distant metastasis in ovarian clear cell carcinoma.

BACKGROUND: Ovarian clear cell carcinoma (OCCC) represents a subtype of ovarian epithelial carcinoma (OEC) known for its limited responsiveness to chemotherapy, and the onset of distant metastasis significantly impacts patient prognoses. This study aimed to identify potential risk factors contributing to the occurrence of distant metastasis in OCCC. METHODS: Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, we identified patients diagnosed with OCCC between 2004 and 2015. The most influential factors were selected through the application of Gaussian Naive Bayes (GNB) and Adaboost machine learning algorithms, employing a Venn test for further refinement. Subsequently, six machine learning (ML) techniques, namely XGBoost, LightGBM, Random Forest (RF), Adaptive Boosting (Adaboost), Support Vector Machine (SVM), and Multilayer Perceptron (MLP), were employed to construct predictive models for distant metastasis. Shapley Additive Interpretation (SHAP) analysis facilitated a visual interpretation for individual patient. Model validity was assessed using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and the area under the receiver operating characteristic curve (AUC). RESULTS: In the realm of predicting distant metastasis, the Random Forest (RF) model outperformed the other five machine learning algorithms. The RF model demonstrated accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and AUC (95% CI) values of 0.792 (0.762-0.823), 0.904 (0.835-0.973), 0.759 (0.731-0.787), 0.221 (0.186-0.256), 0.974 (0.967-0.982), 0.353 (0.306-0.399), and 0.834 (0.696-0.967), respectively, surpassing the performance of other models. Additionally, the calibration curve's Brier Score (95%) for the RF model reached the minimum value of 0.06256 (0.05753-0.06759). SHAP analysis provided independent explanations, reaffirming the critical clinical factors associated with the risk of metastasis in OCCC patients. CONCLUSIONS: This study successfully established a precise predictive model for OCCC patient metastasis using machine learning techniques, offering valuable support to clinicians in making informed clinical decisions.

Unraveling intestinal microbiota's dominance in polycystic ovary syndrome pathogenesis over vaginal microbiota.

Background: Polycystic ovary syndrome (PCOS) is a prevalent endocrine disease in women, intricately linked to hormonal imbalances. The microbiota composition plays a pivotal role in influencing hormonal levels within the body. In this study, we utilized a murine model to investigate how intestinal and vaginal microbiota interact with hormones in the development of PCOS. Methods: Twenty female mice were randomly assigned to the normal group (N) and the model group (P), where the latter received daily subcutaneous injections of 0.1 mL DHEA (6 mg/100 g). Throughout the experiment, we evaluated the PCOS mouse model by estrus cycle, serum total testosterone (T), prolactin (PRL) and luteinizing hormone (LH) levels, and ovarian pathological morphology. The microbial composition in both intestinal content and vaginal microbiota were studied by 16S rRNA gene high-throughput sequencing. Results: Compared with the N group, the P group showed significant increases in body weight, T, and PRL, with significant decrease in LH. Ovaries exhibited polycystic changes, and the estrous cycle was disrupted. The intestinal microbiota result shows that Chao1, ACE, Shannon and Simpson indexes were decreased, Desulfobacterota and Acidobacteriota were increased, and Muribaculaceae, Limosilactobacillus and Lactobacillus were decreased in the P group. T was significantly positively correlated with Enterorhabdus, and LH was significantly positively correlated with Lactobacillus. The analysis of vaginal microbiota revealed no significant changes in Chao1, ACE, Shannon, and Simpson indices. However, there were increased in Firmicutes, Bacteroidota, Actinobacteriota, Streptococcus, and Muribaculaceae. Particularly, Rodentibacter displayed a robust negative correlation with other components of the vaginal microbiota. Conclusion: Therefore, the response of the intestinal microbiota to PCOS is more significant than that of the vaginal microbiota. The intestinal microbiota is likely involved in the development of PCOS through its participation in hormonal regulation.

Idiopathic mesenteric phlebosclerosis missed by a radiologist at initial diagnosis: A case report.

BACKGROUND: Idiopathic mesenteric phlebosclerosis (IMP) is a rare type of ischemic colitis characterized by thickening of the wall of the right hemicolon and calcification, sclerosis, and fibrosis of mesenteric veins. The diagnosis of IMP is based on typical clinical features and imaging findings. We report a case of IMP that was initially missed by the radiologist. CASE SUMMARY: A 77-year-old woman was admitted to the hospital due to chronic diarrhea for over 2 months. She had been consuming Chinese patent medicines (CPM) containing fructus gardeniae for more than 15 years. Colonoscopy revealed an edematous mucosa, bluish-purple discoloration, erosions, and ulcerations throughout the colorectal area. Abdominal computed tomography (CT) showed diffuse mural thickening of the entire colorectum, with tortuous thread-like calcifications in the right hemicolon, left hemicolon, and rectum. Most of the calcifications were located in the mesenteric vein. The diagnosis of IMP was established based on medical history, colonoscopy, CT findings, and histopathological examination. The patient was treated conservatively with papaverine and rifaximin, and CPM was stopped. Her diarrhea symptoms improved, indicating the effectiveness of the treatment. Over the next several years, she took opium alkaloids for an extended period and did not require hospitalization for the aforementioned gastrointestinal disorder. CONCLUSION: IMP is a rare gastrointestinal disease affecting Asian populations, possibly related to long-term herbal medicine intake. Accurate imaging analysis is crucial for diagnosis, but insufficient understanding of the disease can lead to misdiagnosis or missed diagnosis. Treatment strategies should be personalized.

[Retracted] Upregulation of microRNA­181b inhibits CCL18­induced breast cancer cell metastasis and invasion via the NF­κB signaling pathway.

[This retracts the article DOI: 10.3892/ol.2016.5230.].