Experiencias docentes en tiempo de pandemia

El texto Experiencias docentes en tiempo de pandemia está estructurado en dos partes: 1. Discusiones necesarias sobre la educación superior en tiempo de pandemia. 2. Prácticas docentes en época de pandemia expresadas a través del relato. En la primera parte, se presenta un conjunto de nueve artículos que buscan fundamentar teóricamente la situación actual de la educación conforme a las circunstancias que estamos viviendo, de manera que: Robert Fernando Bolaños Vivas, en su artículo La filosofía de la Educación ante la crisis sanitaria COVID-19, una oportunidad de humanización, considera que la crisis sanitaria de la COVID-19 ha puesto de manifesto la profunda crisis humana que pone a prueba la calidad de los seres humanos, razón por la cual el autor intenta demostrar la deficiente respuesta antropológica a las complejas exigencias y complejidades de la crisis sanitaria provocada por la COVID- 19, en este sentido, en el artículo reflexiona sobre la dimensión de la alteridad, la historicidad y la temporalidad humana

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

A Novel Hyaluronic Acid Matrix Ingredient with Regenerative, Anti-Aging and Antioxidant Capacity

Hyaluronic acid (HA) and proteoglycans (such as dermatan sulphate (DS) and chondroitin sulphate (CS)) are the main components of the extracellular matrix of the skin, along with collagen and elastin. These components decrease with age, which implies a loss of skin moisture causing wrinkles, sagging and aging. Currently, the external and internal administration of effective ingredients that can reach the epidermis and dermis is the main alternative for combating skin aging. The objective of this work was to extract, characterise and evaluate the potential of an HA matrix ingredient to support anti-aging. The HA matrix was isolated and purified from rooster comb and characterised physicochemically and molecularly. In addition, its regenerative, anti-aging and antioxidant potential and intestinal absorption were evaluated. The results show that the HA matrix is composed of 67% HA, with an average molecular weight of 1.3 MDa; 12% sulphated glycosaminoglycans, including DS and CS; 17% protein, including collagen (10.4%); and water. The in vitro evaluation of the HA matrix's biological activity showed regenerative properties in both fibroblasts and keratinocytes, as well as moisturising, anti-aging and antioxidant effects. Furthermore, the results suggest that the HA matrix could be absorbed in the intestine, implying a potential oral as well as topical use for skin care, either as an ingredient in a nutraceutical or a cosmetic product

Yeast-Derived Nucleotides Enhance Fibroblast Migration and Proliferation and Provide Clinical Benefits in Atopic Dermatitis

Nucleotides, glycosaminoglycans, and omega-3 essential fatty acids (O3s) could be used for improving skin health, although their modes of action, alone or in combination, are not yet fully understood. To gain some insight into these mechanisms, we performed two in vitro tests and one in vivo pilot trial. The effects on human dermal fibroblast proliferation and migration were evaluated with the following compounds and combinations: 0.156 mg/mL O3s, 0.0017 mg/mL hyaluronic acid (HA), 0.0004 mg/mL dermatan sulfate (DS), 0.0818 mg/mL nucleotides, and [O3s + HA + DS] and [O3s + HA + DS + nucleotides] at the same concentrations. In both in vitro assays, adding nucleotides to [O3s + HA + DS] provided significant improvements. The resulting combination [O3s + HA + DS + nucleotides] was then tested in vivo in dogs with atopic dermatitis by oral administration of a supplement providing a daily amount of 40 mg/kg nucleotides, 0.9 mg/kg HA, 0.18 mg/kg DS, 53.4 mg/kg EPA, and 7.6 mg/kg DHA. After 30 days, the pruritus visual analog scale (pVAS) score was significantly reduced, and no adverse effects were observed. In conclusion, the combination of nucleotides plus glycosaminoglycans and O3s could serve as a useful therapeutic alternative in skin health applications

Carta de Psicología No. 57

Editorial. Especialización en Psicología Clínica: uno de los mejores programas de la Facultad de Psicología. Comprensión del fenómeno de trata de personas con fines de explotación sexual en Colombia. Procesos de socialización en niños, niñas y adolescentes (NNA) colombianos durante y después de la pandemia. Escala de Medición de la Soledad BATAN. Ciberviolencia, una aproximación desde la cognición extendida y enactiva. Efectos de las prácticas de crianza en el desarrollo de niños y niñas durante la infancia temprana en familias disfuncionales. Influencia de los padres en el uso de estrategias adaptativas y desadaptativas de regulación emocional utilizadas por los niños y niñas durante la infancia intermedia. Exploración acerca de las estrategias de intervención implementadas en los niños, niñas y adolescentes víctimas del conflicto armado en Colombia. Validación por jueces de un instrumento de medición de afectividad y erotismo en trabajadoras sexuales de Bogotá. Efectos del castigo físico como agente de control y disciplina en la crianza de niños y niñas en infancia temprana. Beneficios cognitivos de los videojuegos. Revisión teórica del estilo de crianza democrático. Ser porque hemos sido: La conexión emocional en la reconstrucción del tejido social para la paz. Conexión emocional como estrategia para la construcción del sentido de país. El uso de tecnologías de la información y la comunicación en la medición de procesos psicológicos. Relación entre moda, imagen corporal y conducta alimentaria en Latinoamérica. Niveles de estrés, ansiedad y depresión durante el aislamiento social obligatorio en personas que realizan teletrabajo. Contribuyendo al bienestar y calidad de vida de las comunidades. El rol de los hermanos de niños diagnosticados con trastorno del espectro autista (TEA): desarrollo de interacciones y comunicación, una revisión teórica

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit