Bruno Aguiar

Bio: Bruno Aguiar is an academic researcher from Federal University of Piauí. The author has contributed to research in topics: Valosin-containing protein & Population. The author has an hindex of 8, co-authored 19 publications receiving 254 citations. Previous affiliations of Bruno Aguiar include Instituto de Biologia Molecular e Celular & University of Porto.

Accelerometer-based fall detection for smartphones

Abstract: Falls are considered the main cause of fear and loss of independence among the elderly population and are also a major cause of morbidity, disability and health care utilization. In the majority of fall events external support is imperative in order to avoid major consequences. Therefore, the ability to automatically detect these fall events could help reducing the response time and significantly improve the prognosis of fall victims. This paper presents a unobtrusive smartphone based fall detection system that uses a combination of information derived from machine learning classification applied in a state machine algorithm. The data from the smartphone built-in accelerometer is continuously screened when the phone is in the user's belt or pocket. Upon the detection of a fall event, the user location is tracked and SMS and email notifications are sent to a set of contacts. The accuracy of the fall detection algorithm here proposed is near 97.5% for both the pocket and belt usage. In conclusion, the proposed solution can reliably detect fall events without disturbing the users with excessive false alarms, presenting also the advantage of not changing the user's routines, since no additional external sensors are required.

DDX3 DEAD-box RNA helicase plays a central role in mitochondrial protein quality control in Leishmania

Abstract: DDX3 is a highly conserved member of ATP-dependent DEAD-box RNA helicases with multiple functions in RNA metabolism and cellular signaling. Here, we describe a novel function for DDX3 in regulating the mitochondrial stress response in the parasitic protozoan Leishmania. We show that genetic inactivation of DDX3 leads to the accumulation of mitochondrial reactive oxygen species (ROS) associated with a defect in hydrogen peroxide detoxification. Upon stress, ROS production is greatly enhanced, causing mitochondrial membrane potential loss, mitochondrial fragmentation, and cell death. Importantly, this phenotype is exacerbated upon oxidative stress in parasites forced to use the mitochondrial oxidative respiratory machinery. Furthermore, we show that in the absence of DDX3, levels of major components of the unfolded protein response as well as of polyubiquitinated proteins increase in the parasite, particularly in the mitochondrion, as an indicator of mitochondrial protein damage. Consistent with these findings, immunoprecipitation and mass-spectrometry studies revealed potential interactions of DDX3 with key components of the cellular stress response, particularly the antioxidant response, the unfolded protein response, and the AAA-ATPase p97/VCP/Cdc48, which is essential in mitochondrial protein quality control by driving proteosomal degradation of polyubiquitinated proteins. Complementation studies using DDX3 deletion mutants lacking conserved motifs within the helicase core support that binding of DDX3 to ATP is essential for DDX3's function in mitochondrial proteostasis. As a result of the inability of DDX3-depleted Leishmania to recover from ROS damage and to survive various stresses in the host macrophage, parasite intracellular development was impaired. Collectively, these observations support a central role for the Leishmania DDX3 homolog in preventing ROS-mediated damage and in maintaining mitochondrial protein quality control.

Monitoring physical activity and energy expenditure with smartphones

Abstract: Monitoring physical activity and energy expenditure is important for maintaining adequate activity levels with an impact in health and well-being. This paper presents a smartphone based method for classification of inactive postures and physical activities including the calculation of energy expenditure. The implemented solution considers two different positions for the smartphone, the user's pocket or belt. The signal from the accelerometer embedded in the smartphone is used to classify the activities resorting to a decision tree classifier. The average accuracy of the classification task for all activities is 99.5% for the pocket usage and 99.4% when the phone is used in the belt. Using the output of the activity classifier we also compute an estimation of the energy expended by the user. The proposed solution is a trustworthy smartphone based activity monitor, classifying the activities of daily living throughout the entire day and allowing to assess the associated energy expenditure without causing any change in user's routines.

A comparative study of the short term cold resistance response in distantly related Drosophila species: the role of regucalcin and frost.

Abstract: The molecular basis of short term cold resistance (indexed as chill-coma recovery time) has been mostly addressed in D. melanogaster, where candidate genes (Dca (also known as smp-30) and Frost (Fst)) have been identified. Nevertheless, in Drosophila, the ability to tolerate short term exposure to low temperatures evolved several times independently. Therefore, it is unclear whether variation in the same candidate genes is also responsible for short term cold resistance in distantly related Drosophila species. It should be noted that Dca is a candidate gene for cold resistance in the Sophophora subgenus only, since there is no orthologous gene copy in the Drosophila subgenus. Here we show that, in D. americana (Drosophila subgenus), there is a north-south gradient for a variant at the 5′ non-coding region of regucalcin (a Dca-like gene; in D. melanogaster the proteins encoded by the two genes share 71.9% amino acid identities) but in our D. americana F2 association experiment there is no association between this polymorphism and chill-coma recovery times. Moreover, we found no convincing evidence that this gene is up-regulated after cold shock in both D. americana and D. melanogaster. Size variation in the Fst PEST domain (putatively involved in rapid protein degradation) is observed when comparing distantly related Drosophila species, and is associated with short term cold resistance differences in D. americana. Nevertheless, this effect is likely through body size variation. Moreover, we show that, even at two hours after cold shock, when up-regulation of this gene is maximal in D. melanogaster (about 48 fold expression change), in D. americana this gene is only moderately up-regulated (about 3 fold expression change). Our work thus shows that there are important differences regarding the molecular basis of cold resistance in distantly related Drosophila species.

Inferences on specificity recognition at the Malus×domestica gametophytic self-incompatibility system

Abstract: In Malus × domestica (Rosaceae) the product of each SFBB gene (the pollen component of the gametophytic self-incompatibility (GSI) system) of a S-haplotype (the combination of pistil and pollen genes that are linked) interacts with a sub-set of non-self S-RNases (the pistil component), but not with the self S-RNase. To understand how the Malus GSI system works, we identified 24 SFBB genes expressed in anthers, and determined their gene sequence in nine M. domestica cultivars. Expression of these SFBBs was not detected in the petal, sepal, filament, receptacle, style, stigma, ovary or young leaf. For all SFBBs (except SFBB15), identical sequences were obtained only in cultivars having the same S-RNase. Linkage with a particular S-RNase was further established using the progeny of three crosses. Such data is needed to understand how other genes not involved in GSI are affected by the S-locus region. To classify SFBBs specificity, the amino acids under positive selection obtained when performing intra-haplotypic analyses were used. Using this information and the previously identified S-RNase positively selected amino acid sites, inferences are made on the S-RNase amino acid properties (hydrophobicity, aromatic, aliphatic, polarity, and size), at these positions, that are critical features for GSI specificity determination.

“Bioinformatics” 특집을 내면서

Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

The mitochondrial pathways of apoptosis

Abstract: Mitochondria are the bioenergetics and metabolic center of eucaryotic cells that carry out many important functions to sustain life. Recent biochemical studies revealed another aspect of mitochondrial function: inducing apoptosis by triggering specific biochemical reactions that lead to rapid disposal of damaged cells. In response to a variety of apoptotic stimuli, mitochondria release many apoptogenic proteins that normally reside in the intermembrane space of mitochondria. These studies suggest that mitochondria are dynamic responsive structures engaged incessantly in controlling metabolic and genetic interaction with other cellular organelles. Consequently, when cellular milieu is no longer conducive to maintaining homeostasis, either due to injury or developmental cues, mitochondria initiate apoptotic programs that efficiently demise the cell.

Tracking the Evolution of Smartphone Sensing for Monitoring Human Movement.

Abstract: Advances in mobile technology have led to the emergence of the “smartphone”, a new class of device with more advanced connectivity features that have quickly made it a constant presence in our lives. Smartphones are equipped with comparatively advanced computing capabilities, a global positioning system (GPS) receivers, and sensing capabilities (i.e., an inertial measurement unit (IMU) and more recently magnetometer and barometer) which can be found in wearable ambulatory monitors (WAMs). As a result, algorithms initially developed for WAMs that “count” steps (i.e., pedometers); gauge physical activity levels; indirectly estimate energy expenditure and monitor human movement can be utilised on the smartphone. These algorithms may enable clinicians to “close the loop” by prescribing timely interventions to improve or maintain wellbeing in populations who are at risk of falling or suffer from a chronic disease whose progression is linked to a reduction in movement and mobility. The ubiquitous nature of smartphone technology makes it the ideal platform from which human movement can be remotely monitored without the expense of purchasing, and inconvenience of using, a dedicated WAM. In this paper, an overview of the sensors that can be found in the smartphone are presented, followed by a summary of the developments in this field with an emphasis on the evolution of algorithms used to classify human movement. The limitations identified in the literature will be discussed, as well as suggestions about future research directions.

New Advances and Challenges of Fall Detection Systems: A Survey

Abstract: Falling, as one of the main harm threats to the elderly, has drawn researchers’ attentions and has always been one of the most valuable research topics in the daily health-care for the elderly in last two decades. Before 2014, several researchers reviewed the development of fall detection, presented issues and challenges, and navigated the direction for the study in the future. With smart sensors and Internet of Things (IoT) developing rapidly, this field has made great progress. However, there is a lack of a review and discussion on novel sensors, technologies and algorithms introduced and employed from 2014, as well as the emerging challenges and new issues. To bridge this gap, we present an overview of fall detection research and discuss the core research questions on this topic. A total of 6830 related documents were collected and analyzed based on the key words. Among these documents, the twenty most influential and highly cited articles are selected and discussed profoundly from three perspectives: sensors, algorithms and performance. The findings would assist researchers in understanding current developments and barriers in the systems of fall detection. Although researchers achieve fruitful work and progress, this research domain still confronts challenges on theories and practice. In the near future, the new solutions based on advanced IoT will sustainably urge the development to prevent falling injuries.