Discovering medication patterns for high-complexity drug-using diseases through electronic medical records

An Electronic Medical Record (EMR) is a professional document that contains all data generated during the treatment process. The EMR can utilize various data formats, such as numerical data, text, and images. Mining the information and knowledge hidden in the huge amount of EMR data is an essential requirement for clinical decision support, such as clinical pathway formulation and evidence-based medical research. In this paper, we propose a machine-learning-based framework to mine the hidden medication patterns in EMR text. The framework systematically integrates the Jaccard similarity evaluation, spectral clustering, the modified Latent Dirichlet Allocation and cross-matching among multiple features to find the residuals that describe additional knowledge and clusters hidden in multiple perspectives of highly complex medication patterns. These methods work together, step by step to reveal the underlying medication pattern. We evaluated the method by using real data from EMR text (patients with cirrhotic ascites) from a large hospital in China. The proposed framework outperforms other approaches for medication pattern discovery, especially for this disease with subtle medication treatment variances. The results also revealed little overlap among the discovered patterns; thus, the distinct features of each pattern are well studied through the proposed framework

An \u3cem\u3eIL1RL1\u3c/em\u3e genetic variant lowers soluble ST2 levels and the risk effects of \u3cem\u3eAPOE\u3c/em\u3e-ε4 in female patients with Alzheimer’s disease

Changes in the levels of circulating proteins are associated with Alzheimer’s disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33–ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR–Cas9 genome editing identified rs1921622, a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622, demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622/sST2 regulates amyloid-beta (Aβ) pathology through the modulation of microglial activation and Aβ clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD

An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer’s disease

Changes in the levels of circulating proteins are associated with Alzheimer’s disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33–ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR–Cas9 genome editing identified rs1921622, a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622, demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622/sST2 regulates amyloid-beta (Aβ) pathology through the modulation of microglial activation and Aβ clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD

An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer’s disease

Changes in the levels of circulating proteins are associated with Alzheimer’s disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33–ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR–Cas9 genome editing identified rs1921622, a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622, demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622/sST2 regulates amyloid-beta (Aβ) pathology through the modulation of microglial activation and Aβ clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD

Defining the causes of sporadic Parkinson's disease in the global Parkinson's genetics program (GP2)

The Global Parkinson’s Genetics Program (GP2) will genotype over 150,000 participants from around the world, and integrate genetic and clinical data for use in large-scale analyses to dramatically expand our understanding of the genetic architecture of PD. This report details the workflow for cohort integration into the complex arm of GP2, and together with our outline of the monogenic hub in a companion paper, provides a generalizable blueprint for establishing large scale collaborative research consortia

Multi-ancestry genome-wide association meta-analysis of Parkinson?s disease

Although over 90 independent risk variants have been identified for Parkinson’s disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson’s disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations

Exploration and mitigation of protrusion behavior in Ga-ion doped h-BN memristors

Using hexagonal boron nitride (h-BN) to prepare resistive switching devices is a promising strategy. Various doping methods have aroused great interest in the semiconductor field in recent years, but many researchers have overlooked the various repetitive anomalies that occur during the testing process. In this study, the basic electrical properties and additive protrusion behavior of Ga-ion-doped h-BN memristors at micro–nanoscale during the voltage scanning process are investigated via AFM and energy dispersive spectroscopy. The additive protrusion behavior is subjected to exploratory research, and it is concluded that it is caused by anodic oxidation. An approach is proposed that involves filling the AFM chamber with nitrogen gas to improve the stability of memristor testing, and this method provides a solution for enhanced testing stability of memristors

Why do patients follow physicians’ advice? The influence of patients’ regulatory focus on adherence: an empirical study in China

Abstract Background In general, medical regimens and treatments are more likely to be effective if patients follow their physicians’ advice. However, limited studies have focused on the relationship between regulatory focus and patient adherence. This study explores the antecedents of patient adherence employing regulatory focus theory. Methods This study established a research model consisting of two independent variables, two mediators, one dependent variable, two moderators, three control variables, and six hypotheses. An online survey involving 336 valid responses was conducted to collect data in China. We used structural equation modelling and confirmatory factor analysis to test the hypotheses and to develop the research model. Results The reliability and validity of the measures were accepted. In terms of control variables, age had a positive effect on conservative treatment-related health information seeking behaviour, and patients with different resident statuses held different attitudes towards seeking conservative treatment-related health information. However, educational level did not have any effect on the variables of the research model. The hypothesis testing results corroborate that promotion focus had a positive impact on patients’ emerging treatment-related health information seeking behaviour; prevention focus had a positive impact on patients’ conservative treatment-related health information seeking behaviour, which had a positive impact on patient adherence. In addition, media campaigns had a positive impact on the relationship between promotion focus and emerging treatment-related health information seeking behaviour, and website reputation had a positive impact on the relationship between prevention focus and conservative treatment-related health information seeking behaviour. Conclusions Individuals can be encouraged to seek health information and share health-related knowledge through mass media, such as the Internet, when the quality of information, especially information from online sources, is guaranteed. In addition, physicians need to improve their professionalism and expand their knowledge of conservative healthcare. As a further application of our work, an Internet information recommendation system can be designed to recommend different types of health information for users according to their regulatory focus

Mature or Emerging? The Impact of Treatment-Related Internet Health Information Seeking on Patients’ Trust in Physicians

Years of clinical trials have proven the maturity and safety of certain treatments, however, some of these mature treatments may not be highly effective. Several treatments have emerged through technological innovations, but their long-term safety, efficacy, and adverse effects remain unknown. At present, many patients seek information related to their treatments on the Internet, which may impact their attitudes towards different treatments and their trust in physicians. In this study, a research model was developed to examine how patients’ trust in their physicians is influenced by related online information on mature or emerging treatments. The hypotheses were tested using confirmatory factor analysis (CFA) and structural equation modelling (SEM). A total of 336 valid responses were collected through an online survey. Mature treatments related health information was found to significantly improve patients’ trust. Thus, physicians should pay more attention to mature treatments, and encourage their patients to seek related information online. Moreover, the quality of online information should be developed further to increase patients’ satisfaction. Physicians should also consider their patients’ psychological safety in communication with patients to strengthen their trust