UNASSIGNED: The rising incidence of drug abuse among pregnant women has rendered neonatal opioid withdrawal syndrome a significant global health concern.
UNASSIGNED: Databases including PubMed, Web of Science, the Cochrane Library, Embase, Elton B. Stephens. Company (EBSCO), China National Knowledge Infrastructure (CNKI), and Wanfang were searched for comparative studies of the Eat, Sleep, Console model vs. traditional assessment tools for neonatal opioid withdrawal syndrome. Two reviewers conducted literature searches, screened according to the inclusion criteria, extracted data, and independently verified accuracy. All meta-analyses were conducted using Review Manager Version 5.4.
UNASSIGNED: In total, 18 studies involving 4,639 neonates were included in the meta-analysis. The Eat, Sleep, Console model demonstrated superior outcomes in assessing neonatal opioid withdrawal syndrome, significantly reducing the need for pharmacological treatment [risk ratio = 0.44, 95% confidence interval (CI) = 0.34-0.56, P < 0.001], decreasing the length of hospital stay [standard mean difference (SMD) = -2.10, 95% CI = -3.43 to -0.78, P = 0.002], and shortening the duration of opioid treatment (SMD = -1.33, 95% CI = -2.22 to -0.45, P = 0.003) compared to the Finnegan Neonatal Abstinence Scoring System.
UNASSIGNED: The Eat, Sleep, Console model is more effective than the Finnegan Neonatal Abstinence Scoring System in improving the assessment and management of neonatal opioid withdrawal syndrome.

Endocrine-disrupting chemicals (EDCs) are chemicals that can interfere with homeostatic processes. They are a major concern for public health, and they can cause adverse long-term effects such as cancer, intellectual impairment, obesity, diabetes, and male infertility. The endocrine system is a complex machinery, with the estrogen (E), androgen (A), and thyroid hormone (T) modes of action being of major importance. In this context, the availability of in silico models for the rapid detection of hazardous chemicals is an effective contribution to toxicological assessments. We developed Qualitative Gene expression Activity Relationship (QGexAR) models to predict the propensities of chemically induced disruption of EAT modalities. We gathered gene expression profiles from the LINCS database tested on two cell lines, i.e., MCF7 (breast cancer) and A549 (adenocarcinomic human alveolar basal epithelial). We optimized our prediction protocol by testing different feature selection methods and classification algorithms, including CATBoost, XGBoost, Random Forest, SVM, Logistic regression, AutoKeras, TPOT, and deep learning models. For each EAT endpoint, the final prediction was made according to a consensus prediction as a function of the best model obtained for each cell line. With the available data, we were able to develop a predictive model for estrogen receptor and androgen receptor binding and thyroid hormone receptor antagonistic effects with a consensus balanced accuracy on a validation set ranging from 0.725 to 0.840. The importance of each predictive feature was further assessed to identify known genes and suggest new genes potentially involved in the mechanisms of action of EAT perturbation.

UNASSIGNED: Recent studies have shown that epicardial adipose tissue (EAT) is an independent atrial fibrillation (AF) prognostic marker and has influence on the myocardial function. In computed tomography (CT), EAT volume (EATv) and density (EATd) are parameters that are often used to quantify EAT. While increased EATv has been found to correlate with the prevalence and the recurrence of AF after ablation therapy, higher EATd correlates with inflammation due to arrest of lipid maturation and with high risk of plaque presence and plaque progression. Automation of the quantification task diminishes the variability in readings introduced by different observers in manual quantification and results in high reproducibility of studies and less time-consuming analysis. Our objective is to develop a fully automated quantification of EATv and EATd using a deep learning (DL) framework.
UNASSIGNED: We proposed a framework that consists of image classification and segmentation DL models and performs the task of selecting images with EAT from all the CT images acquired for a patient, and the task of segmenting the EAT from the output images of the preceding task. EATv and EATd are estimated using the segmentation masks to define the region of interest. For our experiments, a 300-patient dataset was divided into two subsets, each consisting of 150 patients: Dataset 1 (41,979 CT slices) for training the DL models, and Dataset 2 (36,428 CT slices) for evaluating the quantification of EATv and EATd.
UNASSIGNED: The classification model achieved accuracies of 98% for precision, recall and F 1 scores, and the segmentation model achieved accuracies in terms of mean ( ± std.) and median dice similarity coefficient scores of 0.844 ( ± 0.19) and 0.84, respectively. Using the evaluation set (Dataset 2), our approach resulted in a Pearson correlation coefficient of 0.971 ( R 2 = 0.943) between the label and predicted EATv, and the correlation coefficient of 0.972 ( R 2 = 0.945) between the label and predicted EATd.
UNASSIGNED: We proposed a framework that provides a fast and robust strategy for accurate EAT segmentation, and volume (EATv) and attenuation (EATd) quantification tasks. The framework will be useful to clinicians and other practitioners for carrying out reproducible EAT quantification at patient level or for large cohorts and high-throughput projects.

Traumatic perforation of the tympanic membrane often occurs in Japanese patients who scratch their ears to relieve itching. Traumatic tympanic membrane perforation may close spontaneously, but the perforation may remain. One of the causes of prolonged tympanic membrane perforation closure is dysfunction of the Eustachian tube. In this study, I experienced a case of chronic epipharyngitis causing ear fullness and itching, and a traumatic perforation of the tympanic membrane caused by scratching with an earpick. The patient also had sleep apnea syndrome (SAS). Treatment of chronic epipharyngitis with epipharyngeal abrasive therapy (EAT) shortened the time to perforation closure and improved SAS, suggesting that EAT affected the improvement of Eustachian tube function and airway resistance in the epipharynx.

A case of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) with chronic epipharyngitis was treated with epipharyngeal abrasive therapy (EAT). The symptoms of ME/CFS improved along with the improvement of chronic epipharyngitis. The patient was followed up with endocrine and autonomic function tests. Endocrine function tests included salivary cortisol and salivary α-amylase activity. Salivary α-amylase activity was stimulated by EAT. EAT improved the diurnal variability of salivary cortisol secretion. Autonomic function tests included heart rate variability analysis by orthostatic stress test. EAT normalized parasympathetic and sympathetic reflexes over time and regulated autonomic balance. Based on the improvement of symptoms and test results, EAT was considered effective for ME/CFS. A literature review was conducted on the mechanism of the therapeutic effect of EAT on ME/CFS.

One of the characteristic features of ovarian cancer is its early dissemination. Metastasis and the invasiveness of ovarian cancer are strongly dependent on the phenotypical and molecular determinants of cancer cells. Invasive cancer cells, circulating tumor cells, and cancer stem cells, which are responsible for the metastatic process, may all undergo different modes of transition, giving rise to mesenchymal, amoeboid, and redifferentiated epithelial cells. Such variability is the result of the changing needs of cancer cells, which strive to survive and colonize new organs. This would not be possible if not for the variety of migration modes adopted by the transformed cells. The most common type of metastasis in ovarian cancer is dissemination through the transcoelomic route, but transitions in ovarian cancer cells contribute greatly to hematogenous and lymphatic dissemination. This review aims to outline the transition modes of ovarian cancer cells and discuss the migratory capabilities of those cells in light of the known ovarian cancer metastasis routes.

BACKGROUND: this study aimed to assess the complex relationship between EAT thickness, as measured with echocardiography, and the severity of coronary artery disease (CAD). We investigated whether individuals with higher EAT thickness underwent coronary revascularization. Subsequently, we conducted a three-year follow-up to explore any potential modifications in EAT depots post-angioplasty.
METHODS: we conducted a prospective and retrospective cross-sectional observational study involving 150 patients consecutively referred for acute coronary syndrome, including ST-elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction (NSTEMI), and unstable angina. Upon admission (T0), all patients underwent coronary angiography to assess the number of pathologic coronary vessels. Percutaneous transluminal coronary angioplasty (PTCA) was performed based on angiogram results if indicated. The sample was categorized into two groups: non-revascularized (no-PTCA) and revascularized (PTCA). Transthoracic echocardiograms to measure epicardial fat thickness were conducted at admission (T0) and after a 3-year follow-up (T1).
CONCLUSIONS: findings revealed a positive correlation between EAT thickness and the severity of coronary artery disease (CAD), with patients undergoing PTCA showing decreased EAT thickness after three years. Echocardiography demonstrated reliability in assessing EAT, offering potential for risk stratification. The study introduces a cut-off value of 0.65 cm as a diagnostic tool for cardiovascular risk. Incorporating EAT measurements into clinical practice may lead to more precise risk stratification and tailored treatment strategies, ultimately reducing the burden of cardiovascular disease.

BACKGROUND: Obesity is a major risk factor of many chronic diseases. However, current obesity control policies and actions are not sufficient to halt the pandemic. It has been documented that more than half of all adults are not able to interpret their own weight status, not to mention to practice healthy lifestyles. Social media and interactive websites can reach people on a long-term basis, which may be used as intervention vehicles to build up cognition for weight control and to promote healthy behavior practices.
OBJECTIVE: WAKE.TAIWAN is an ongoing web-based multifaceted healthy lifestyle promotion program with social media and interactive websites as the intervention vehicle. This study aimed to examine whether adults reached by our program would have increased awareness to their own anthropometric measures, correctly judge their body weight status, and practice healthy behaviors over time.
METHODS: This study adopted a quasi-experimental design with web-based questionnaire surveys. The experimental group consisted of WAKE.TAIWAN Facebook group members aged 20-65 years who have used the interactive website health education resources (n=177). The group was further stratified into 2 subgroups based on their duration of participation (E1 group: duration <1 year; E2 group: duration ≥1 year). The control group consisted of other Facebook users (n=545) in the same age range who had not been exposed to the health education materials of this project. A total of 722 people (male: n=267, 37%; and female: n=455, 63%) participated in our survey in 2019. Data were analyzed to evaluate program effectiveness using a generalized linear model.
RESULTS: The proportion of people correctly interpreting their own weight status in the experimental group was greater than that of the control group (control group: 320/545, 58.7%; group E1: 53/88, 60%; and group E2: 64/89, 72%). The E2 experimental group was significantly better than the control group in paying attention to weight-related measures and in correctly interpreting their own weight status (odds ratio 1.73, 95% CI 1.04-2.89; P=.04). With respect to the behavioral stages of practicing healthy eating and active living, both experimental groups, E1 and E2, performed significantly better than the control group (group E1: P=.003 and P=.02; and group E2: P=.004 and P<.001, respectively).
CONCLUSIONS: This study demonstrates that the longer the participants were exposed to our social media-based programs, the higher the proportion of them that would have the correct judgement on their weight status and fall in the higher stages of healthy lifestyle behaviors. A longitudinal follow-up survey is in place to verify these findings.

UNASSIGNED: The opioid epidemic has led to a surge in diagnoses of neonatal opioid withdrawal syndrome (NOWS). Many states track the incidence of NOWS by using the P96.1 International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code for \"neonatal withdrawal symptoms from maternal use of drugs of addiction.\" In October 2018, an ICD-10-CM code for neonatal opioid exposure (P04.14) was introduced. This code can be used when an infant is exposed to opioids in utero but does not have clinically significant withdrawal symptoms. We analyzed the effect of the P04.14 code on the incidence rate of NOWS (P96.1) and \"other\" neonatal drug exposure diagnoses (P04.49).
UNASSIGNED: We used private health insurance data collected for infants in the United States from the first quarter of 2016 through the third quarter of 2021 to describe incidence rates for each code over time and examine absolute and percentage changes before and after the introduction of code P04.14.
UNASSIGNED: The exclusive use of code P96.1 declined from an incidence rate per 1000 births of 1.08 in 2016-2018 to 0.70 in 2019-2021, a -35.7% (95% CI, -47.6% to -23.8%) reduction. Use of code P04.49 only declined from an incidence rate of 2.34 in 2016-2018 to 1.64 in 2019-2021, a -30.0% (95% CI, -36.4% to -23.7%) reduction. Use of multiple codes during the course of treatment increased from an average incidence per 1000 births of 0.56 in 2016-2018 to 0.79 in 2019-2021, a 45.5% (95% CI, 24.8%-66.1%) increase.
UNASSIGNED: The introduction of ICD-10-CM code P04.14 altered the use of other neonatal opioid exposure codes. The use of multiple codes increased, indicating that some ambiguity may exist about which ICD-10-CM code is most appropriate for a given set of symptoms.

UNASSIGNED: In recent years, peri-organ fat has emerged as a diagnostic and therapeutic target in metabolic diseases, including diabetes mellitus. Here, we performed a comprehensive analysis of epicardial adipose tissue (EAT) transcriptome expression differences between diabetic and non-diabetic participants and explored the possible mechanisms using various bioinformatic tools.
UNASSIGNED: RNA-seq datasets GSE108971 and GSE179455 for EAT between diabetic and non-diabetic patients were obtained from the public functional genomics database Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were identified using the R package DESeq2, then Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed. Next, a PPI (protein-protein interaction) network was constructed, and hub genes were mined using STRING and Cytoscape. Additionally, CIBERSORT was used to analyze the immune cell infiltration, and key transcription factors were predicted based on ChEA3.
UNASSIGNED: By comparing EAT samples between diabetic and non-diabetic patients, a total of 238 DEGs were identified, including 161 upregulated genes and 77 downregulated genes. A total of 10 genes (IL-1β, CD274, PDCD1, ITGAX, PRDM1, LAG3, TNFRSF18, CCL20, IL1RN, and SPP1) were selected as hub genes. GO and KEGG analysis showed that DEGs were mainly enriched in the inflammatory response and cytokine activity. Immune cell infiltration analysis indicated that macrophage M2 and T cells CD4 memory resting accounted for the largest proportion of these immune cells. CSRNP1, RELB, NFKB2, SNAI1, and FOSB were detected as potential transcription factors.
UNASSIGNED: Comprehensive bioinformatic analysis was used to compare the difference in EAT between diabetic and non-diabetic patients. Several hub genes, transcription factors, and immune cell infiltration were identified. Diabetic EAT is significantly different in the inflammatory response and cytokine activity. These findings may provide new targets for the diagnosis and treatment of diabetes, as well as reduce potential cardiovascular complications in diabetic patients through EAT modification.