An intelligent system for prognosis of noncommunicable diseases’ risk factors

Antinociceptive, anti-inflammatory and hypoglycemic activities of the ethanolic Turnera subulata Sm. flower extract in adult zebrafish (Danio rerio)

Turnera subulata Sm. belongs to the family Turneraceae and is found in Brazil. The present study evaluated the antinociceptive, anti-inflammatory, and hypoglycemic potential of T. subulata flower extract (EtFloTsu) in zebrafish (Danio rerio). The total phenol and flavonoid contents of EtFloTsu were determined and identified using the Folin Ciocalteu reagent and aluminum chloride (AlCl₃), respectively. The constituents of the extract were identified by HPLC-DAD, and the in vitro antioxidant activity (DPPH) was determined, toxicity in brine shrimp, and acute toxicity of 96 h in adult zebrafish. In addition, adult zebrafish (n = 6/fish) were treated orally with EtFloTsu (4, 20, or 40 mg/kg; vo) and subjected to formalin-induced nociception tests (with its possible mechanism of action with camphor), carrageenan-induced inflammation, and D-glucose-induced hyperglycemia (111 mM). Oxidative stress in the liver and brain tissues was assessed. EtFloTsu showed high levels of phenolic and flavonoid compounds with antioxidant activity. The phytochemicals chlorogenic acid, luteolin-7-o-glucoside, vitexin, and apigenin-7-o-glucoside were also identified in EtFloTsu. The synergism between these constituents was possibly responsible for the antinociceptive (via TRPA1), anti-inflammatory, and hypoglycemic effects of EtFloTsu in adult zebrafish, without causing toxicity in animals. Therefore, T. subulata flowers have therapeutic agents that could treat pain, inflammation, diabetes, and related complications.Communicated by Ramaswamy H. Sarma.

Machine Learning and IoT Applied to Cardiovascular Diseases Identification through Heart Sounds: A Literature Review

This article presents a systematic mapping study dedicated to conduct a literature review on machine learning and IoT applied in the identification of diseases through heart sounds. This research was conducted between January 2010 and July 2021, considering IEEE Xplore, PubMed Central, ACM Digital Library, JMIR—Journal of Medical Internet Research, Springer Library, and Science Direct. The initial search resulted in 4372 papers, and after applying the inclusion and exclusion criteria, 58 papers were selected for full reading to answer the research questions. The main results are: of the 58 articles selected, 46 (79.31%) mention heart rate observation methods with wearable sensors and digital stethoscopes, and 34 (58.62%) mention care with machine learning algorithms. The analysis of the studies based on the bibliometric network generated by the VOSviewer showed in 13 studies (22.41%) a trend related to the use of intelligent services in the prediction of diagnoses related to cardiovascular disorders.

Ambient Intelligence Based on IoT for Assisting People with Alzheimer’s Disease Through Context Histories

New Internet of Things (IoT) applications are enabling the development of projects that help with monitoring people with different diseases in their daily lives. Alzheimer’s is a disease that affects neurological functions and needs support to maintain maximum independence and security of patients during this stage of life, as the cure and reversal of symptoms have not yet been discovered. The IoT-based monitoring system provides the caregivers’ support in monitoring people with Alzheimer’s disease (AD). This paper presents an ontology-based computational model that receives physiological data from external IoT applications, allowing identification of potentially dangerous behaviors for patients with AD. The main scientific contribution of this work is the specification of a model focusing on Alzheimer’s disease using the analysis of context histories and context prediction, which, considering the state of the art, is the only one that uses analysis of context histories to perform predictions. In this research, we also propose a simulator to generate activities of the daily life of patients, allowing the creation of data sets. These data sets were used to evaluate the contributions of the model and were generated according to the standardization of the ontology. The simulator generated 1026 scenarios applied to guide the predictions, which achieved average accurary of 97.44%. The experiments also allowed the learning of 20 relevant lessons on technological, medical, and methodological aspects that are recorded in this article.

Anti-inflammatory, hypoglycemic, hypolipidemic, and analgesic activities of Plinia cauliflora (Mart.) Kausel (Brazilian grape) epicarp

ETHNOPHARMACOLOGICAL RELEVANCE

Plinia cauliflora (Mart.) Kausel, known in Brazil as jabuticaba or jaboticaba has been used by Brazilian native populations for medicinal purposes, including those related to inflammatory conditions, such as asthma, diarrhea, disorders in female genitourinary tract, and tonsillitis. Inflammation has emerged as a main factor for the oxidative stress, hyperglycemia, and dyslipidemia present in chronic noncommunicable diseases (NCDs). Such disturbances have been a leading cause of death worldwide for decades, despite significant efforts in developing new therapies. Therefore, strengthening the relevance of ethnobotanic approaches, as P. cauliflora has the potential to become a natural, native, and traditional product to prevent and treat inflammation-associated diseases more effectively for more people.

AIM OF THE STUDY

Evaluate anti-inflammatory, hypoglycemic, hypolipidemic, and analgesic properties of hydroethanolic extract of P. cauliflora epicarps (PcE).

MATERIALS AND METHODS

Phytochemical compound from the PcE were identified through HPLC-DAD-ESI-MSⁿ analysis. Antioxidant activity was determined by measuring 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging. The anti-inflammatory potential was investigated by carrageenan-induced paw edema and peritonitis in mice. Analgesic effect was assessed, in mice, though hot plate test and acetic acid-induced abdominal writhing. Antidiabetic and hypolipidemic potential were evaluated using alloxan-induced diabetic mice.

RESULTS

Tannins, phenolic acids, and their derivatives were the predominant phytochemicals found. Overall, PcE showed different properties related to the treatment of clinical conditions associated with chronic diseases as a potent antioxidant activity, demonstrating a radical scavenging action similar to gallic acid. PcE oral administration also significantly reduced inflammation induced by paw edema and partially blocked leukocyte migration. Moreover, PcE produced peripheral and central analgesic effects, as evaluated in the writhing model and hot plate tests. Treatment with PcE significantly improved glucose levels and lipid markers in diabetic mice.

CONCLUSIONS

P. cauliflora fruits are rich sources of secondary metabolites, mainly tannins and phenolic acids with high biological potential, which can effectively contribute to the approach of preventing and controlling chronic NCDs.

Applied Computing to Education on Noncommunicable Chronic Diseases: A Systematic Mapping Study

Background: The number of deaths from noncommunicable chronic diseases (NCDs) has increased worldwide. These deaths would be partly avoidable if prevention and follow-up measures were applied to reduce risk factors. Computing can help educate individuals, improving their knowledge about NCDs. This article presents a systematic mapping of studies that apply computing to education on NCDs. The results allow a general view of the literature and the identification of research opportunities. Materials and Methods: The methodology followed three steps: (1) definition of search databases from computer science and health sciences, (2) selection of keywords for search string composition, and (3) application of inclusion and exclusion criteria to filter the results. The survey occurred from January 2008 to April 2018. Results: The initial search resulted in 19,675 papers, of which 38 were selected after applying the filter criteria. The use of mobile computing stood out in 25 papers. The education modalities were self-management and educational content for diabetes (10 papers), asthma (1), cardiovascular disease (1) and chronic diseases (1), self-management of diabetes and games (1), educational content (15), games (6), personalized content (2), and virtual community (1). The percentage of papers on diabetes was 65%. Most solutions (55%) do not use data from individuals to provide information considering their health condition. In addition, 19 papers produced outcome measures by means of experiments. Conclusions: Mobile computing was the most used technology in the papers. In addition, self-management, educational content, and games were the most used mechanisms. A research opportunity consists of personalized assistance. In this sense, ubiquitous learning can provide a continuous and contextualized education.