Learning gene regulatory networks using gaussian process emulator and graphical LASSO.

Large amounts of research efforts have been focused on learning gene regulatory networks (GRNs) based on gene expression data to understand the functional basis of a living organism. Under the assumption that the joint distribution of the gene expressions of interest is a multivariate normal distribution, such networks can be constructed by assessing the nonzero elements of the inverse covariance matrix, the so-called precision matrix or concentration matrix. This may not reflect the true connectivity between genes by considering just pairwise linear correlations. To relax this limitative constraint, we employ Gaussian process (GP) model which is well known as computationally efficient non-parametric Bayesian machine learning technique. GPs are among a class of methods known as kernel machines which can be used to approximate complex problems by tuning their hyperparameters. In fact, GP creates the ability to use the capacity and potential of different kernels in constructing precision matrix and GRNs. In this paper, in the first step, we choose the GP with appropriate kernel to learn the considered GRNs from the observed genetic data, and then we estimate kernel hyperparameters using rule-of-thumb technique. Using these hyperparameters, we can also control the degree of sparseness in the precision matrix. Then we obtain kernel-based precision matrix similar to GLASSO to construct kernel-based GRN. The findings of our research are used to construct GRNs with high performance, for different species of Drosophila fly rather than simply using the assumption of multivariate normal distribution, and the GPs, despite the use of the kernels capacity, have a much better performance than the multivariate Gaussian distribution assumption.

Barriers to Adherence to Medical Care Programs in Liver Transplant Recipients: A Qualitative Study.

BACKGROUND: Non-adherence to medical care programs in transplant recipients is considered one of the life-threatening factors in transplant recipients, which can prevent achieving the desired levels of health care. OBJECTIVE: To determine perceptions of liver transplant recipients about the barriers to their adherence to medical care programs. METHODS: This study was conducted based on a qualitative content analysis method using semi-structured interviews with 23 liver transplant recipients, their families, and the transplant teams. A purposive sampling method was used in liver transplant clinics affiliated to Tehran University of Medical Sciences, Tehran, Iran, from May to November 2017. RESULTS: Three main categories including factors related to therapeutic problems (educational problems and medication challenges), personal factors (self-management disability), as well as social problems (cultural conditions and passive family) were identified as the barriers to adherence to medical care programs. CONCLUSION: Paying attention to barriers to adherence to medical care and planning for moderating them in a collaborative effort between transplant recipients and health care providers could increase the likelihood of survival and quality of life in these patients.

Unhealthy lifestyles and ischaemic electrocardiographic abnormalities: the Persian Gulf Healthy Heart Study.

We assessed prevalence of cardiovascular risk factors, ischaemic heart disease (IHD) and unhealthy lifestyles in 3723 participants aged > or = 25 years in the northern Persian Gulf region; 96.0% had > or = 1 cardiovascular risk factor. Over 60% had unhealthy body weight, only 8.3% ate the recommended amount of fruits and vegetables, 70.6% were physically inactive and 19.0% were current smokers. Prevalence of electrocardiogram (ECG) with evidence of IHD was 12.7%. Present or past smoking and truncal obesity were independently associated with IHD ECGs in men, and past or present smoking and obesity in women. Hypertension and diabetes were independently associated with increased risk of IHD ECG.

Unhealthy lifestyles and ischaemic electrocardiographic abnormalities: the Persian Gulf Healthy Heart Study

We assessed prevalence of cardiovascular risk factors, ischaemic heart disease [IHD] and unhealthy lifestyles in 3723 participants aged >/= 25 years in the northern Persian Gulf region; 96.0% had >/= 1 cardiovascular risk factor. Over 60% had unhealthy body weight, only 8.3% ate the recommended amount of fruits and vegetables, 70.6% were physically inactive and 19.0% were current smokers. Prevalence of electrocardiogram [ECG] with evidence of IHD was 12.7%. Present or past smoking and truncal obesity were independently associated with IHD ECGs in men, and past or present smoking and obesity in women. Hypertension and diabetes were independently associated with increased risk of IHD ECG