Dynamical behavior of a stochastic multigroup staged-progression HIV model with saturated incidence rate and higher-order perturbations

In this paper,we analyze a higher-order stochastically perturbed multigroup staged-progression model for the transmission of HlV with saturated incidence rate.We obtainsufficient conditions for the existence and uniqueness of an ergodic stationary distribu-tion of positive solutions to the system by establishing a suitable stochastic Lyapunovfunction.In addition,we make up adequate conditions for complete eradication and wip-ing out the infectious disease.In a biological interpretation,the existence of a stationarydistribution implies that the disease will prevail and persist in the long term.Finally,examples and numerical simulations are introduced to validate our theoretical results.

Diagnosing phenotypes of single-sample individuals by edge biomarkers

Network or edge biomarkers area reliable form to characterize phenotypes or diseases.However,obtaining edges orcorrelations between molecules for an individual requires measurement ofmultiple samples of that individual,which are generally unavailable in clinical practice.Thus,it is strongly demanded to diagnose a disease by edge or network biomarkers in one-sample-for-one-individual context.Here,we developed a new computational framework,EdgeBiomarker,to integrate edge and node biomarkers to diagnose phenotype of each single test sample.By applying the method to datasets of lung and breast cancer,it reveals new marker genes/gene-pairs and related sub-networks for distinguishing earlier and advanced cancer stages.Our method shows advantages over traditional methods:(i)edge biomarkers extracted from non-differentially expressed genes achieve better cross-validation accuracy of diagnosis than molecule or node biomarkers from differentially expressed genes,suggesting that certain pathogenic information is only present at the level of network and under-estimated by traditional methods;(ii)edge biomarkers categorize patients into low/high survival rate in a more reliablemanner;(iii)edge biomarkers are significantly enriched in relevant biological functions or pathways,implying that the association changes ina network,rather than expression changes in individual molecules,tendtobe causally related to cancer development.The new frameworkof edgebiomarkers paves theway for diagnosing diseases and analyzing the irmolecular mechanisms by edges or networks in one-sample-for-one-individual basis.This also provides a powerful tool for precision medicine or big-data medicine.

Considerations on the role of environmental toxins in idiopathic Parkinson’s disease pathophysiology

Neurodegenerative diseases are characterized by a progressive dysfunction of the nervous system.Often associated with atrophy of the affected central or peripheral nervous structures,they include diseases such as Parkinson’s Disease(PD),Alzheimer’s Disease and other dementias,Genetic Brain Disorders,Amyotrophic Lateral Sclerosis(ALS or Lou Gehrig’s Disease),Huntington’s Disease,Prion Diseases,and others.The prevalence of neurodegenerative diseases has increased over the last years.This has had a major impact both on patients and their families and has exponentially increased the medical bill by hundreds of billions of Euros.Therefore,understanding the role of environmental and genetic factors in the pathogenesis of PD is crucial to develop preventive strategies.While some authors believe that PD is mainly genetic and that the aging of the society is the principal cause for this increase,different studies suggest that PD may be due to an increased exposure to environmental toxins.In this article we review epidemiological,sociological and experimental studies to determine which hypothesis is more plausible.Our conclusion is that,at least in idiopathic PD(iPD),the exposure to toxic environmental substances could play an important role in its aetiology.