CLADSI: Deep Continual Learning for Alzheimer's Disease Stage Identification Using Accelerometer Data.

Alzheimer's disease (AD) is a neurodegenerative disorder that can cause a significant impairment in physical and cognitive functions. Gait disturbances are also reported as a symptom of AD. Previous works have used Convolutional Neural Networks (CNNs) to analyze data provided by motion sensors that monitor Alzheimer's patients.

Alternative approaches for creating a wealth index: the case of Mozambique.

Introduction: The wealth index is widely used as a proxy for a household's socioeconomic position (SEP) and living standard. This work constructs a wealth index for the Mopeia district in Mozambique using data collected in year 2021 under the BOHEMIA (Broad One Health Endectocide-based Malaria Intervention in Africa) project.

Methods: We evaluate the performance of three alternative approaches against the Demographic and Health Survey (DHS) method based wealth index: feature selection principal components analysis (PCA), sparse PCA and robust PCA.

Burden and risk factors of snakebite in Mopeia, Mozambique: Leveraging larger malaria trials to generate data of this neglected tropical disease.

Background: Snakebite is a neglected disease that disproportionally affects the rural poor. There is a dearth of evidence regarding incidence and risk factors in snakebite-endemic countries. Without this basic data, it will be impossible to achieve the target of a 50% reduction of snakebite morbidity and mortality by 2030 as set by the World Health Organization.

Detecting temporal and spatial malaria patterns from first antenatal care visits.

Pregnant women attending first antenatal care (ANC) visits represent a promising malaria surveillance target in Sub-Saharan Africa. We assessed the spatio-temporal relationship between malaria trends at ANC (n = 6471) and in children in the community (n = 3933) and at health facilities (n = 15,467) in southern Mozambique (2016-2019). ANC P.

BOHEMIA a cluster randomized trial to assess the impact of an endectocide-based one health approach to malaria in Mozambique: baseline demographics and key malaria indicators.

Background: Many geographical areas of sub-Saharan Africa, especially in rural settings, lack complete and up-to-date demographic data, posing a challenge for implementation and evaluation of public health interventions and carrying out large-scale health research. A demographic survey was completed in Mopeia district, located in the Zambezia province in Mozambique, to inform the Broad One Health Endectocide-based Malaria Intervention in Africa (BOHEMIA) cluster randomized clinical trial, which tested ivermectin mass drug administration to humans and/or livestock as a potential novel strategy to decrease malaria transmission.

Methods: The demographic survey was a prospective descriptive study, which collected data of all the households in the district that accepted to participate.

LIN28 and histone H3K4 methylase induce TLR4 to generate tumor-initiating stem-like cells.

Chemoresistance and plasticity of tumor-initiating stem-like cells (TICs) promote tumor recurrence and metastasis. The gut-originating endotoxin-TLR4-NANOG oncogenic axis is responsible for the genesis of TICs. This study investigated mechanisms as to how TICs arise through transcriptional, epigenetic, and post-transcriptional activation of oncogenic TLR4 pathways.

Seroprevalence and socioeconomic impact of the first SARS-CoV-2 infection wave in a small town in Navarre, Spain.

The characterization of the antibody response to SARS-CoV-2 and its determinants are key for the understanding of COVID-19. The identification of vulnerable populations to the infection and to its socioeconomic impact is indispensable for inclusive policies. We conducted an age-stratified cross-sectional community-based seroprevalence survey between June 12th and 19th 2020-during the easing of lockdown-in Cizur, Spain.

BOHEMIA: Broad One Health Endectocide-based Malaria Intervention in Africa-a phase III cluster-randomized, open-label, clinical trial to study the safety and efficacy of ivermectin mass drug administration to reduce malaria transmission in two African settings.

Background: Residual malaria transmission is the result of adaptive mosquito behavior that allows malaria vectors to thrive and sustain transmission in the presence of good access to bed nets or insecticide residual spraying. These behaviors include crepuscular and outdoor feeding as well as intermittent feeding upon livestock. Ivermectin is a broadly used antiparasitic drug that kills mosquitoes feeding on a treated subject for a dose-dependent period.

The HIV epidemic in Colombia: spatial and temporal trends analysis.

Background: Colombia has the fourth highest incidence rate of HIV/AIDS among all Latin American countries and it has been increasing since the 1980s. However, the number of studies that addresses this trend is limited. Here, we employed spatial and temporal trend analyses to study the behaviour of the epidemic in the Colombian territory.

Digital Interventions for Psychological Comorbidities in Chronic Diseases-A Systematic Review.

Chronic diseases represent one of the main causes of death worldwide. The integration of digital solutions in clinical interventions is broadly diffused today; however, evidence on their efficacy in addressing psychological comorbidities of chronic diseases is sparse. This systematic review analyzes and synthesizes the evidence about the efficacy of digital interventions on psychological comorbidities outcomes of specific chronic diseases.

An agenda for research and action toward diverse and just futures for life on Earth.

Decades of research and policy interventions on biodiversity have insufficiently addressed the dual issues of biodiversity degradation and social justice. New approaches are therefore needed. We devised a research and action agenda that calls for a collective task of revisiting biodiversity toward the goal of sustaining diverse and just futures for life on Earth.

A multiphase program for malaria elimination in southern Mozambique (the Magude project): A before-after study.

Background: Malaria eradication remains the long-term vision of the World Health Organization (WHO). However, whether malaria elimination is feasible in areas of stable transmission in sub-Saharan Africa with currently available tools remains a subject of debate. This study aimed to evaluate a multiphased malaria elimination project to interrupt Plasmodium falciparum malaria transmission in a rural district of southern Mozambique.

Alzheimer's Disease stage identification using deep learning models.

Objective: The aim of this research is to identify the stage of Alzheimer's Disease (AD) patients through the use of mobility data and deep learning models. This process facilitates the monitoring of the disease and allows actions to be taken in order to provide the optimal treatment and the prevention of complications.

Materials And Methods: We employed data from 35 patients with AD collected by smartphones for a week in a daycare center.

Moving towards malaria elimination in southern Mozambique: Cost and cost-effectiveness of mass drug administration combined with intensified malaria control.

Background: As new combinations of interventions aiming at interrupting malaria transmission are under evaluation, understanding the associated economic costs and benefits is critical for decision-making. This study assessed the economic cost and cost-effectiveness of the Magude project, a malaria elimination initiative implemented in a district in southern Mozambique (i.e.

The Role of Engagement in Teleneurorehabilitation: A Systematic Review.

The growing understanding of the importance of involving patients with neurological diseases in their healthcare routine either for at-home management of their chronic conditions or after the hospitalization period has opened the research for new rehabilitation strategies to enhance patient engagement in neurorehabilitation. In addition, the use of new digital technologies in the neurorehabilitation field enables the implementation of telerehabilitation systems such as virtual reality interventions, video games, web-based interventions, mobile applications, web-based or telephonic telecoach programs, in order to facilitate the relationship between clinicians and patients, and to motivate and activate patients to continue with the rehabilitation process at home. Here we present a systematic review that aims at reviewing the effectiveness of different engagement strategies and the different engagement assessments while using telerehabilitation systems in patients with neurological disorders.

The Benefits of emotion Regulation Interventions in Virtual Reality for the Improvement of Wellbeing in Adults and Older Adults: A Systematic Review.

The impact of emotion regulation interventions on wellbeing has been extensively documented in literature, although only in recent years virtual reality (VR) technologies have been incorporated in the design of such interventions, in both clinical and non-clinical settings. A systematic search, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, was therefore carried out to explore the state of the art in emotion regulation interventions for wellbeing using virtual reality. The literature on this topic was queried, 414 papers were screened, and 11 studies were included, covering adults and older adults.

Neurorehabilitation of Spatial Memory Using Virtual Environments: A Systematic Review.

In recent years, virtual reality (VR) technologies have become widely used in clinical settings because they offer impressive opportunities for neurorehabilitation of different cognitive deficits. Specifically, virtual environments (VEs) have ideal characteristics for navigational training aimed at rehabilitating spatial memory. A systematic search, following PRISMA guidelines, was carried out to explore the current scenario in neurorehabilitation of spatial memory using virtual reality.

Biotransformation of phenolic compounds by Bacillus aryabhattai.

Phenolic compounds could pose environmental problems if they are in excess, although they could be a renewable resource of substances with industrial interest. The novel strain Bacillus aryabhattai BA03 is able to produce high-added value metabolites from different phenolic compounds such as vanillin, 4-vinylguaiacol and 4-vinylphenol while inducing ligninolytic enzymes such as laccases (Lac) and lignin peroxidases (LiP). In comparison with the medium without inducers, the presence of 500 mg/L caffeic acid improved 9.

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique.

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals.

Classification of Alzheimer's Patients through Ubiquitous Computing.

Functional data analysis and artificial neural networks are the building blocks of the proposed methodology that distinguishes the movement patterns among c's patients on different stages of the disease and classifies new patients to their appropriate stage of the disease. The movement patterns are obtained by the accelerometer device of android smartphones that the patients carry while moving freely. The proposed methodology is relevant in that it is flexible on the type of data to which it is applied.

User Interaction Modeling and Profile Extraction in Interactive Systems: A Groupware Application Case Study.

A relevant goal in human-computer interaction is to produce applications that are easy to use and well-adjusted to their users' needs. To address this problem it is important to know how users interact with the system. This work constitutes a methodological contribution capable of identifying the context of use in which users perform interactions with a groupware application (synchronous or asynchronous) and provides, using machine learning techniques, generative models of how users behave.

Mining lipolytic enzymes in community DNA from high Andean soils using a targeted approach.

Microbial enrichments cultures are a useful strategy to speed up the search for enzymes that can be employed in industrial processes. Lipases have gained special attention because they show unique properties such as: broad substrate specificity, enantio- and regio-selectivity and stability in organic solvents. A major goal is to identify novel lipolytic enzymes from microorganisms living in cold extreme environments such as high Andean soils, of relevance to our study being their capability be used in industrial processes.