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This paper aims to discuss the Technological Pedagogical Content Knowledge (TPACK) development by mathematics teachers (preservice and inservice) that participated in an online course for developing educational apps and puzzles with GeoGebra. Theoretical foundations are based on the authors Punya Mishra, Matthew J. Koehler et al, regarding TPACK framework and Margaret Niess et al regarding the development of TPACK by mathematics teachers. The research method is qualitative, and to analyze the thoughts and ideas discussed by the participants, we used the Discursive Textual Analysis. In this regard, three representative categories were used to build the following metatexts: instructional approaches, classroom environment management and teacher’s professional development. Through the Discursive Textual Analysis, it was possible to understand the participants concerns in creating different instructional approaches using Information and Communication Technologies, once they realized that dealing with digital natives requires pedagogical innovations, supported by new technologies, and new ways to configure and manage classroom environments permeated by digital resources.

The objective of this study was to estimate the prevalence of diabetes mellitus (DM) and cardiovascular risk factors in a rural population in the province of San Luis, Argentina. Cross-sectional study developed between September and November 2017 with 18-year-old inhabitants and more than four towns in the Juan Martín de Pueyrredón department, San Luis. The participants answered questions by self-report on sociodemographic aspects, habits, psychosocial and risk factors for non-communicable diseases; physical measurements, FINDIRSC questionnaire and blood sample extraction were performed. Univariate estimates stratified by sex with their 95% confidence interval (95%CI) were obtained. We worked with sample expansion factors; crude and adjusted prevalences were calculated. The population consisted of 424 men (52.5%, 95%CI: 46.0-58.9) and 384 women (47.5%, 95%CI: 41.1-54.0). The adjusted prevalences for both sexes (by self-report) were: DM 11.8% (95%CI: 8.2-15.4); arterial hypertension (AHT): 35.5% (95% CI: 31.0-40.1); high cholesterol: 20.3% (CI 16.0-24.7). Males had significantly higher desirable HDL cholesterol and elevated blood pressure than females; women abdominal obesity in greater magnitude. 16.4% (95% CI: 11.0 - 23.6) had a high-very high risk of developing type 2 DM in the next 10 years. The adjusted prevalences of DM, hypertension, and high cholesterol were lower than those of the urban population of the province of San Luis. We highlight the pioneering contribution of this work to the knowledge of the health profile of rural communities in Argentina., (Universidad Nacional de Córdoba)

The COVID-19 pandemic has particularly affected older adults residing in nursing homes, resulting in high rates of hospitalisation and death. Here, we evaluated the longitudinal humoral response and neutralising capacity in plasma samples of volunteers vaccinated with different platforms (Sputnik V, BBIBP-CorV, and AZD1222). A cohort of 851 participants, mean age 83 (60-103 years), from the province of Buenos Aires, Argentina were included. Sequential plasma samples were taken at different time points after vaccination. After completing the vaccination schedule, infection-naïve volunteers who received either Sputnik V or AZD1222 exhibited significantly higher specific anti-Spike IgG titers than those who received BBIBP-CorV. Strong correlation between anti-Spike IgG titers and neutralising activity levels was evidenced at all times studied (rho=0.7 a 0.9). Previous exposure to SARS-CoV-2 and age <80 years were both associated with higher specific antibody levels. No differences in neutralising capacity were observed for the infection-naïve participants in either gender or age group. Similar to anti-Spike IgG titers, neutralising capacity decreased 3 to 9-fold at 6 months after initial vaccination for all platforms. Neutralising capacity against Omicron was between 10-58 fold lower compared to ancestral B.1 for all vaccine platforms at 21 days post dose 2 and 180 days post dose 1. This work provides evidence about the humoral response and neutralising capacity elicited by vaccination of a vulnerable elderly population. This data could be useful for pandemic management in defining public health policies, highlighting the need to apply reinforcements after a complete vaccination schedule., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Rodriguez, Silva, Miglietta, Rall, Pascuale, Ballejo, López Miranda, Ríos, Ramis, Marro, Poncet, Mazzitelli, Salvatori, Ceballos, Gonzalez Lopez Ledesma, Ojeda, Aguirre, Miragaya, Gamarnik, Rossi, Laboratorio SeVa Group and PAMI Group.)

Objective: To establish the magnitude and risk factors for SARS-CoV-2 infection in the General Pueyrredón, Buenos Aires, Argentina: the INECOVID study., Methods: Prospective cohort designed with participants from the District general population. The follow-up period was from June 22nd to December 18th, 2020, with a minimum appointment interval of 21 days. Data were obtained via questionnaires and serum or plasma samples. The primary event was considered as the time to seroconversion (IgG) as evidence of SARS-CoV-2 infection. The accumulated risk of infection was estimated using the Kaplan Meier method. Cox models were built with time-dependent variables., Results: 345 participants were recruited (n=222 women, 64.3%; 123 men, 35.7%), with a median age of 45 years in women (Interquartile range: 19) and 49 in men (Interquartile range: 26). 12.8% of participants (n=44) had evidence of SARS-CoV-2 infection [incidence density of 9.1 cases (women: 11.1, men: 5.1) per 10,000 person-day]. 36.4% of the cases (n=16) were asymptomatic. The following factors were associated to the risk of infection: being in close contact of a confirmed COVID-19 case (HR=5.56; 95%CI 2.85-10.83), being a health worker (HR=2.93; 95%CI 1.55-5.52), living in crowded conditions (HR=2.23; 95%CI 1.13-4.49), and age (HR=0.98; 95%CI 0.95-1.00)., Conclusion: The identified risk factors endorse the protection policies and protocols adopted by the Argentinian sanitary authorities for the general population and the care programs for health workers in the pre-vaccination phase.

Objective: to describe the methodological aspects of the first epidemiological study on the profile of non-communicable diseases (NCDs) in rural areas of Argentina carried out in 2017., Methods: A cross-sectional design was used. The reference population was the inhabitants of 18 years and over from the towns of Beazley, Zanjitas, Alto Pelado and Cazador, Juan M. de Pueyrredón department, San Luis province, Argentina. According to the latest census source, the number of inhabitants of that age group was 808 inhabitants. All homes in each locality were visited; All subjects who met the inclusion criteria were invited to participate. The research consisted of two phases: application of a self-report questionnaire in the home, followed by physical measurements, a FINDIRSC questionnaire (Finnish Diabetes Risk Score) and biochemical determinations. The data were dumped into a database in Epi Info 7. The statistical processing and analysis was performed in R 3.5.2 language., Results: 375 survey records with complete data were obtained, which represented 46.41% of the registered population according to census source; 252 performed laboratory analysis (67.20%) and 250 physical examination (66.67%). Participants in the survey phase exhibited characteristics similar to those who completed all stages of the investigation for most of the characteristics studied., Conclusions: this research was pioneer in generating knowledge about the NCD profile in the rural population of Argentina. It is expected to constitute an input for the planning of prevention policies, taking into account the local particularities., (Universidad Nacional de Córdoba)