Modifications to the delivery of a gross anatomy course during the COVID-19 pandemic at a Mexican medical school

The Coronavirus disease was declared a pandemic this year, causing an impact on medical education. Following the World Health Organization’s (WHO) recommendations, Universities around the world implemented social distancing and the use of online platforms. Anatomists lead medical students, most of which are part of Generation Z. Different technological tools have been used in the gross anatomy course in combination with face-toface classes, but now are forced to move exclusively online. The Human Anatomy Department in the Medical School of the Universidad Autonoma de Nuevo León (UANL) implemented asynchronous sessions as a short-term resolution, transformed to synchronous sessions as the pandemic progressed. It is important to consider the adaptability of the student, the near-peer teacher, and academic staff, with the creation of innovative ideas to facilitate the learning for the student and to maintain the quality of the course. Their role in this modality should be assessed, as it may change medical education and the way to teach in the future for the new generation of medical students. Professors’ roles are changing and it is necessary to adapt to new situations

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

The Political Economy of Tax Reform in Bangladesh: Political Settlements, Informal Institutions and the Negotiation of Reform

political economy, tax reform, political settlementsThis paper explores the political economy of tax reform in Bangladesh over several decades, shedding light on the complex factors that account for unusually effective and sustained resistance to significant reform. We contend that it is necessary to understand both deep-seated formal and informal institutions and the micro-level incentives that shape the negotiation of short-term reform in order to comprehend tax outcomes. We describe a tax system that is highly informal, largely manual and characterised by high levels of discretion and corruption. However, despite appearing highly dysfunctional on the surface, this system serves the core interests of powerful political, economic and administrative actors. Underpinned by robust informal institutions, the current system delivers low and predictable tax rates to businesses, provides extensive discretion and opportunities for corruption to the tax administration, and acts as an important vehicle for political elites to raise funds and distribute patronage and economic rents. While the tax system has not been without reform, individual reform efforts have been constrained by the parameters of this broader settlement, leaving competing interest groups to pursue strategic gains at the margins while seeking to satisfy external reform demands. This tax bargain reflects Bangladesh’s broader political economy, which is characterised by entrenched informal institutions underpinning the combination of generally weak governance and high levels of economic growth – the so-called ‘paradox of Bangladesh’.DfID, NORA

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

Feasibility and acceptability of CRiSOL: A pilot peer-based intervention to address syndemic health issues afflicting Latino immigrants in the U.S.

Substance use, HIV/AIDS, domestic violence and mental health (SAVAME) are syndemic health issues that disproportionately burden Latinos in the U.S. Yet, there are limited evidence-based interventions to address these interrelated syndemic issues and their shared socio-ecological determinants. This study sought to test the feasibility and acceptability of CRiSOL, a peer-based, resilience-focused intervention to reduce the impact of the SAVAME syndemic on Latino immigrants. Fifteen Latino immigrant community leaders were recruited and trained to serve as health promotion agents in their naturally existing social networks. The training was implemented with high fidelity, received with high satisfaction by the peer leaders, and associated with significant improvements in their knowledge, leadership skills, and social capital. During an 8-month outreach phase, nine leaders remained active in the program and documented 825 one-on-one interactions with community members, during which they provided advice/counseling (52.2% of interactions), health information/education (32.5%), referrals to health and social services (38.5%), food aid (39.9%), and service navigation/assistance (10.2%). While future research must be conducted to establish the effectiveness of CRiSOL, findings from this pilot evaluation indicate the feasibility, acceptability, and high level of reach of this intervention and suggest significant potential to reduce the SAVAME syndemic burden in Latino communities

Anti-carbamylated protein antibodies positivity and disease activity in Hispanic patients with established rheumatoid arthritis: An observational study

Objectives We aimed to determine the prevalence of anti-carbamylated protein (anti-CarP) antibodies in Mexican Hispanics with established rheumatoid arthritis (RA) and to assess their relationship with disease activity. Methods A cohort study was conducted in 278 patients with established RA during an 18-month follow-up. We measured IgG/IgM/IgA rheumatoid factor (RF), IgG anticitrullinated protein antibodies (ACPA) and IgG/IgM/IgA anti-CarP antibodies using enzyme-linked immunosorbent assay (ELISA). For disease activity, we performed the 28-joint disease activity score with erythrocyte sedimentation rate (DAS28-ESR). Repeated measures one-way ANOVA was used to test the association between anti-CarP IgG antibody status and longitudinal DAS28-ESR scores. Patients were evaluated at baseline and at 6, 12, and 18 months during follow-up. Results Anti-CarP IgG antibodies were positive in 47.8% of patients and, accounting for all isotypes, in 9.5% of patients with negative RF and ACPA. Triple antibody positivity was present in 42.6% of patients in our sample. Anti-CarP IgG antibody positivity did not show statistically significant differences in mean DAS28-ESR when compared to anti-CarP IgG antibody negative patients at baseline, 6, 12 or 18 months. Conclusion Anti-CarP IgG antibodies are not associated to a higher disease activity in Hispanic patients with established RA. Our findings suggest that the clinical value of measuring anti-CarP antibodies in RA diminishes over time.Transplantation and autoimmunit