Genetic and epigenetic targets of natural dietary compounds as anti-Alzheimer's agents

Alzheimer’s disease is a progressive neurodegenerative disorder and the most common cause of dementia that principally affects older adults.Pathogenic factors,such as oxidative stress,an increase in acetylcholinesterase activity,mitochondrial dysfunction,genotoxicity,and neuroinflammation are present in this syndrome,which leads to neurodegeneration.Neurodegenerative pathologies such as Alzheimer’s disease are considered late-onset diseases caused by the complex combination of genetic,epigenetic,and environmental factors.There are two main types of Alzheimer’s disease,known as familial Alzheimer’s disease(onset<65 years)and late-onset or sporadic Alzheimer’s disease(onset≥65 years).Patients with familial Alzheimer’s disease inherit the disease due to rare mutations on the amyloid precursor protein(APP),presenilin 1 and 2(PSEN1 and PSEN2)genes in an autosomaldominantly fashion with closely 100%penetrance.In contrast,a different picture seems to emerge for sporadic Alzheimer’s disease,which exhibits numerous non-Mendelian anomalies suggesting an epigenetic component in its etiology.Importantly,the fundamental pathophysiological mechanisms driving Alzheimer’s disease are interfaced with epigenetic dysregulation.However,the dynamic nature of epigenetics seems to open up new avenues and hope in regenerative neurogenesis to improve brain repair in Alzheimer’s disease or following injury or stroke in humans.In recent years,there has been an increase in interest in using natural products for the treatment of neurodegenerative illnesses such as Alzheimer’s disease.Through epigenetic mechanisms,such as DNA methylation,non-coding RNAs,histone modification,and chromatin conformation regulation,natural compounds appear to exert neuroprotective effects.While we do not purport to cover every in this work,we do attempt to illustrate how various phytochemical compounds regulate the epigenetic effects of a few Alzheimer’s disease-related genes.

Pharmacological treatments of presbyopia:a review of modern perspectives

Introduction:Presbyopia affects people from the 4^(th) decade of life and is characterized by accommodative loss that leads to negative effects on vision-targeted health-related quality of life.A non-invasive pharmacological treatment providing near-lenses independence would be a truly groundbreaking approach in the treatment of presbyopia.The purpose of this review is to analyze the emerging pharmacological solutions proposed to address presbyopia.Results:Several ophthalmic eye drops compounds solutions have been described in peer-reviewed papers or presented in ophthalmological tabloids and congresses.Each topical treatment deals with drug combinations aimed to modify one or more factors involved in the accommodative process and have been proposed to be instilled either monocularly or binocularly.It remains unclear how much each drug in the final combined form is involved in the achievement of the outcome and contributes to it.Conclusion:Despite the lack of a completely well understood mechanism,pharmacological control of presbyopia seems to be a possible and very attractive alternative for presbyopic patients.The studies mentioned in this review are to be considered pilot investigations as they involve either a small number of subjects or are single case series.Complete studies are needed to confirm which will be the more effective pharmacological compound for the treatment of presbyopia.

Sustainable transit vehicle tracking service,using intelligent transportation system services and emerging communication technologies:A review

The most salient problems of transit vehicle service in Latin American intermediate cities include:the high number of passengers involved in traffic accidents;traffic congestion caused by transit vehicles,and pollution generated by these vehicles,which increases in high congestion scenarios.To improve upon this situation,a research was conducted on the transit vehicle tracking service,which is a basic service for implementing mobility solutions for the aforementioned problems,the most relevant characteristics of this service for the context of Latin American intermediate cities were identified,and an implementation was proposed.This paper presents the four stages of the study:(a)a review of the state-of-the-art of services or systems related to vehicle tracking,including wireless communications technologies,implemented sustainability approaches,usage of special algorithms for efficiency improvement,and the intelligent transportation system(ITS)architecture used as a basis;(b)the process of identifying relevant characteristics of the service for a given context;(c)proposal of an ITS architecture for this service in an intermediate city,its requirements and the suggested technologies;and(d)development of experiments for validating usage of the key suggested technologies.The review allowed to identify the main service characteristics,with regard to vehicle positioning technologies,the recommended wireless communication technology(long range,LoRa),energy consumption considerations,and use of artificial intelligence(AI)to calculate waiting time of users at bus stops.Finally,an ITS architecture for the city of Popayan(Colombian city)considering the aforementioned characteristics is proposed,and the experiments related to the use of these technologies are described in detail.

Intelligent collision risk detection in medium-sized cities of developing countries,using naturalistic driving:A review

Traffic accidents are one of the most serious problems worldwide,being one of the leading causes of death and economic loss in the world.Low-and middle-income countries,mainly their medium-sized cities,are among the most affected by this problem.93%of traffic accidents occur in low and middle-income countries,even though these countries have approximately 60%of the world’s vehicles.This occurs mainly because in these types of countries,especially in medium-sized cities(target context),there are no ideal conditions for driving,such as adequate road infrastructure,good condition of vehicles,and rigorous safety policies.Advanced data analysis techniques including machine learning(ML)have increasingly been used to solve this problem.Naturalistic driving(ND)can be applied as a data collection method that provides information on traffic accidents.ND commonly uses a vehicle’s kinematic data to detect high-risk driving behaviors that could cause an accident.The objectives of this document are to present a review of different alternatives that help in data collection and creation of intelligent solutions related to detection of possible traffic accidents,principally using ND;and to propose an intelligent collision risk detection system(ICRDS)for identification of areas with a high probability of TA in the target context.Through the review,it was possible to analyze and evaluate the devices,variables and algorithms that help characterize a risk event in driving,considering the target context.The development of a prototype of an ICRDS for a medium-sized city in a developing country is considered viable,considering the identified components,with the aim of identifying risk events in driving,and areas of high probability of accidents in the city.