Impact of the Pandemic on the Teaching and Research Staff at a Technological University in Spain: Deepening the Gender Gap.

The alteration of the educational model caused by the COVID-19 pandemic has not affected all university faculty equally. This work explores the academic, digital and gender inequalities caused by the pandemic on the teaching and research staff of a technological university for STEM (Science, Technology, Engineering and Mathematics) disciplines in Spain, the Universitat Politècnica de Catalunya-BarcelonaTech (UPC). The study considers an anonymous survey with a non-probabilistic voluntary sample (n = 355). The results of the survey reveal that, over these months, the teaching and research staff of the university, regardless of gender, has significantly increased its academic activity due especially to the number of hours devoted to virtual teaching compared to its teaching dedication in a situation of normalcy. This study shows that the lockdown has strongly affected women who are more vulnerable to crisis. In particular, the negative impact on research has been higher in female faculty staff from the UPC, who already face disparities regarding promotion and, during lockdown, stated more difficulties with household work reconciliation. From the results of this study, it is possible to conclude that the COVID-19 pandemic has deepened the gender gap in the academic field.

Impact of the Pandemic on the Teaching and Research Staff at a Technological University in Spain: Deepening the Gender Gap

The alteration of the educational model caused by the COVID-19 pandemic has not affected all university faculty equally. This work explores the academic, digital and gender inequalities caused by the pandemic on the teaching and research staff of a technological university for STEM (Science, Technology, Engineering and Mathematics) disciplines in Spain, the Universitat Politècnica de Catalunya-BarcelonaTech (UPC). The study considers an anonymous survey with a non-probabilistic voluntary sample (n = 355). The results of the survey reveal that, over these months, the teaching and research staff of the university, regardless of gender, has significantly increased its academic activity due especially to the number of hours devoted to virtual teaching compared to its teaching dedication in a situation of normalcy. This study shows that the lockdown has strongly affected women who are more vulnerable to crisis. In particular, the negative impact on research has been higher in female faculty staff from the UPC, who already face disparities regarding promotion and, during lockdown, stated more difficulties with household work reconciliation. From the results of this study, it is possible to conclude that the COVID-19 pandemic has deepened the gender gap in the academic field.

Immune Assessment of BNT162b2 m-RNA-Spike Based Vaccine Response in Adults.

Vaccine efficacy is based on clinical data. Currently, the assessment of immune response after SARS-CoV-2 vaccination is scarce. A total of 52 healthcare workers were immunized with the same lot of BNT162b2 vaccine. The immunological response against the vaccine was tested using a T-specific assay based on the expression of CD25 and CD134 after stimulation with anti-N, -S, and -M specific peptides of SARS-CoV-2. Moreover, IgG anti-S2 and -RBD antibodies were detected using ELISA. Furthermore, the cell subsets involved in the response to the vaccine were measured in peripheral blood by flow cytometry. Humoral-specific responses against the vaccine were detected in 94% and 100% after the first and second doses, respectively. Therefore, anti-S T-specific responses were observed in 57% and 90% of the subjects after the first and second doses of the vaccine, respectively. Thirty days after the second dose, significant increases in T helper 1 memory cells (p < 0.001), peripheral memory T follicular helper (pTFH) cells (p < 0.032), and switched memory (p = 0.005) were observed. This study describes the specific humoral and cellular immune responses after vaccination with the new mRNA-based BNT162b2 vaccine. A mobilization of TFH into the circulation occurs, reflecting a specific activation of the immune system.

Innate and Adaptive Immune Assessment at Admission to Predict Clinical Outcome in COVID-19 Patients.

During the COVID-19 pandemic, many studies have been carried out to evaluate different immune system components to search for prognostic biomarkers of the disease. A broad multiparametric antibody panel of cellular and humoral components of the innate and the adaptative immune response in patients with active SARS-CoV-2 infection has been evaluated in this study. A total of 155 patients were studied at admission into our center and were categorized according to the requirement of oxygen therapy as mild or severe (the latter being those with the requirement). The patients with severe disease were older and had high ferritin, D-dimer, C-reactive protein, troponin, interleukin-6 (IL-6) levels, and neutrophilia with lymphopenia at admission. Moreover, the patients with mild symptoms had significantly increased circulating non-classical monocytes, innate lymphoid cells, and regulatory NK cells. In contrast, severe patients had a low frequency of Th1 and regulatory T cells with increased activated and exhausted CD8 phenotype (CD8+CD38+HLADR+ and CD8+CD27-CD28-, respectively). The predictive model included age, ferritin, D-dimer, lymph counts, C4, CD8+CD27-CD28-, and non-classical monocytes in the logistic regression analysis. The model predicted severity with an area under the curve of 78%. Both innate and adaptive immune parameters could be considered potential predictive biomarkers of the prognosis of COVID-19 disease.

Academic and emotional effects of online learning during the COVID-19 pandemic on engineering students.

The unprecedented situation of the COVID-19 pandemic has caused the closure of universities worldwide and has forced the transition to online learning. This exceptional context compels us to understand students' experience with online learning. Previous literature identifies relevant factors that intervene in the online education experience and can affect students' academic development. One of the main concerns is the students' mental health, given the lockdown restrictions under which classes have been conducted. Furthermore, the impact of the prolonged lockdown and the pandemic fatigue on university students and their academic experience is still unclear. This study delves into engineering undergraduate students' online education experience during the COVID-19 pandemic and its emotional impact across time. With this aim, a questionnaire was distributed to second, third, and fourth-year engineering undergraduate students at two time points, approximately six months apart. The results show significant differences in students' connection with other students and teachers, workspace conditions, and boredom between time points. Besides, the findings indicate significant correlations between academic development and quality of online classes, adaptation of the course, workspace conditions, and connection with other students and teachers, and also between students' emotions and connection with other students and teachers. Finally, the study identifies best practices carried out during online teaching that will be of value for future courses and engineering education beyond the pandemic situation, amongst which those related to effective communication with teachers stand out.

Innate and Adaptive Immunity Alterations in Metabolic Associated Fatty Liver Disease and Its Implication in COVID-19 Severity.

The coronavirus infectious disease 2019 (COVID-19) pandemic has hit the world, affecting health, medical care, economies and our society as a whole. Furthermore, COVID-19 pandemic joins the increasing prevalence of metabolic syndrome in western countries. Patients suffering from obesity, type II diabetes mellitus, cardiac involvement and metabolic associated fatty liver disease (MAFLD) have enhanced risk of suffering severe COVID-19 and mortality. Importantly, up to 25% of the population in western countries is susceptible of suffering from both MAFLD and COVID-19, while none approved treatment is currently available for any of them. Moreover, it is well known that exacerbated innate immune responses are key in the development of the most severe stages of MAFLD and COVID-19. In this review, we focus on the role of the immune system in the establishment and progression of MAFLD and discuss its potential implication in the development of severe COVID-19 in MAFLD patients. As a result, we hope to clarify their common pathology, but also uncover new potential therapeutic targets and prognostic biomarkers for further research.

The direct and indirect effects of COVID-19 pandemic in a real-life hematological setting.

BACKGROUND: Clinical outcomes of novel coronavirus 2019 disease (COVID-19) in onco-hematological patients are unknown. When compared to non-immunocompromised patients, onco-hematological patients seem to have higher mortality rates. AIMS: We describe the characteristics and outcomes of a consecutive cohort of 24 onco-hematological patients with COVID-19 during the first month of the pandemic. We also describe variations in healthcare resource utilization within our hematology department. METHODS AND RESULTS: Data from patients between the first month of the pandemic were retrospectively collected. Clinical and logistic data were also collected and compared with the average values from the prior 3 months of activity. Prevalence of COVID-19 in our hematological population was 0.4%. Baseline characteristics were as follows: male sex: 83%, lymphoid diseases: 46%, median age: 69 (22-82) years. Median follow-up in survivors was 14 (9-28) days and inpatient mortality rate was 46%. Average time to moderate/severe respiratory insufficiency and death were 3 (1-10) and 10 (3-18) days, respectively. Only 1 out of every 12 patients who developed moderate to severe respiratory insufficiency recovered. Upon univariate analysis, the following factors were associated with higher mortality: age ≥ 70 years (P = .01) and D-dimer ≥900 mcg/L (P = .04). With respect to indirect effects during the COVID-19 pandemic, and when compared with the prior 3 months of activity, inpatient mortality (excluding patients with COVID-19 included in the study) increased by 56%. This was associated with a more frequent use of vasoactive drugs (+300%) and advanced respiratory support (+133%) in the hematology ward. In the outpatient setting, there was a reduction in initial visits (-55%) and chemotherapy sessions (-19%). A significant increase in phone visits was reported (+581%). CONCLUSION: COVID-19 pandemic is associated with elevated mortality in hematological patients. Negative indirect effects are also evident within this setting.

Loss of Smell and Taste Can Accurately Predict COVID-19 Infection: A Machine-Learning Approach.

The COVID-19 outbreak has spread extensively around the world. Loss of smell and taste have emerged as main predictors for COVID-19. The objective of our study is to develop a comprehensive machine learning (ML) modelling framework to assess the predictive value of smell and taste disorders, along with other symptoms, in COVID-19 infection. A multicenter case-control study was performed, in which suspected cases for COVID-19, who were tested by real-time reverse-transcription polymerase chain reaction (RT-PCR), informed about the presence and severity of their symptoms using visual analog scales (VAS). ML algorithms were applied to the collected data to predict a COVID-19 diagnosis using a 50-fold cross-validation scheme by randomly splitting the patients in training (75%) and testing datasets (25%). A total of 777 patients were included. Loss of smell and taste were found to be the symptoms with higher odds ratios of 6.21 and 2.42 for COVID-19 positivity. The ML algorithms applied reached an average accuracy of 80%, a sensitivity of 82%, and a specificity of 78% when using VAS to predict a COVID-19 diagnosis. This study concludes that smell and taste disorders are accurate predictors, with ML algorithms constituting helpful tools for COVID-19 diagnostic prediction.