Emotional intelligence and resilience in secondary school Physical Education students during the COVID-19 pandemic

Emotional intelligence (EI) and resilience play an important role in the lives of adolescents, and this has been especially so during the coronavirus pandemic, which has affected the mental health of young people. The study objectives were: (i) to analyse the correlations between the EI variables and resilience;(ii) to analyse the differences between the resilience variable and the EI variables according to the sex variable;and (iii) to analyse the predictive relationship between the EI variables and the resilience variable according to sex. A cross-sectional, observational, and descriptive design study was carried out with a convenience sample consisting of 150 students (78 girls;72 boys) between the ages of 12 and 18 years (M=14.83;SD=1.72). The scales administered were: The Emotional Quotient Inventory and the Resilience Scale. The descriptive statistics were calculated -Student's T test was used to check for differences based on the sex variable, and linear regression analysis was performed to check the prediction ratio of the EI subscales on resilience. The results demonstrated positive and significant relationships between the EI variables and resilience, with EI and resilience being higher in boys than in girls -this differs from previous data, perhaps influenced by the Covid-19 pandemic. The results also reflect that EI positively predicts resilience to a greater extent in boys than in girls.

[Impact of hyperglycemia on the prognosis of patients hospitalized for severe pneumonia in COVID-19]

Background: Adequate glycemic control improves the prognosis of patients hospitalized for pneumonia associated with severe COVID-19. Objective: To evaluate the impact of hyperglycemia (HG) on the prognosis of patients hospitalized for severe pneumonia associated with COVID-19 in unvaccinated patients. Material and methods: Prospective cohort study. We included patients hospitalized from August 2020 to February 2021, with severe COVID-19 pneumonia, not vaccinated against SARS-CoV-2. Data was collected from admission to discharge. We used descriptive and analytical statistics according to the data distribution. ROC curves were used to determine the cut-off points with the highest predictive performance for HG and mortality, with the IBM SPSS program, version 25. Results: We included 103 patients, 32% women, 68% men, age 57 +/- 13 years;58% were admitted with HG (191, IQR 152-300 mg/dL) and 42% with normoglycemia (NG < 126 mg/dL). Mortality was higher in HG at admission 34 (56.7%) than in NG 13 (30.2%) (p = 0.008). HG was associated with diabetes mellitus 2 and neutrophilia (p < 0.05). The risk of death increases 1.558 times (95% CI 1.118-2.172) if HG is at admission and 1.43 times (95% CI 1.14-1.79) during hospitalization. Maintaining NG throughout the hospitalization contributed independently to survival (RR = 0.083 [95% CI 0.012-0.571], p = 0.011). Conclusion: HG significantly impacts prognosis by increasing mortality more than 50% during hospitalization for COVID-19. Copyright © 2023 Revista Medica del Instituto Mexicano del Seguro Social.

[The impact of COVID-19 in a cohort of patients with systemic sclerosis]

Background: COVID-19 brought with it unknowns related to systemic sclerosis. Objective: To know the clinical evolution and prognosis of COVID-19 in a cohort of patients with systemic sclerosis. Methods: During the pandemic, we had digital contact with a cohort of 197 patients with SSc. If they had any condition that met the suspected definition of COVID-19, they underwent polymerase chain reaction testing for SARS-CoV-2;they were treated on an outpatient or hospital basis without interfering with their treatment. They followed their evolution every 24 hours until they became asymptomatic or died. Results: Thirteen patients (6.6%), nine diffuse cutaneous (dcSSc), and four limited cutaneous (lcSSc) developed COVID-19 during nine months of follow-up. The immunosuppressants used at the time of the disease were: mycophenolate mofetil, methotrexate, and prednisone, in low doses. Seven patients had interstitial lung disease (ILD). The main symptoms were chest pain, cough, dyspnea, dysgeusia, and anosmia, 1 with mild symptoms without pneumonia, 11 with mild pneumonia, and one with severe pneumonia that required hospital management. Only one (7.7%) presented severe pneumonia, was hospitalized, and died. Conclusions: COVID-19 disease in patients with SSc can be overcome in most cases, even when they are ILD and were using immunosuppressants at the time of infection with the SARS-CoV-2 virus. Copyright © 2023 Revista Medica del Instituto Mexicano del Seguro Social.

Automated ventilator prototype for COVID-19 patient treatment: the design and development of the electronic system

The coronavirus disease 2019 (COVID-19) pandemic has created an urgent global demand for ventilators, respirators and various resuscitation devices. Various research and development organizations, private companies and individual engineers have collaborated and carried out the development of low-cost ventilation prototypes. In turn, doctors and nurses are collapsed due to the exponential increase in COVID-19 cases. This scenario worsens more when the tasks are manual in nature. The article`s objective to describe the electronic system designed, developed and implemented in a functional prototype of an automatic ventilator in order to be evaluated by a team of health professionals to be later used in cases of health emergencies. This system automates the manual ventilation task aided by a few medical resources in a scenario of scarce resources and is a temporary solution when a respirator is not available. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

Stratifying risk outcomes among adult COVID-19 inpatients with high flow oxygen: The R4 score.

BACKGROUND: High flow oxygen therapy (HFO) is a widely used intervention for pulmonary complications. Amid the coronavirus infectious disease 2019 (COVID-19) pandemic, HFO became a popular alternative to conventional oxygen supplementation therapies. Risk stratification tools have been repurposed -and new ones developed- to estimate outcome risks among COVID-19 patients. This study aims to provide a simple risk stratification system to predict invasive mechanical ventilation (IMV) or death among COVID-19 inpatients on HFO. METHODS: Among 529 adult inpatients with COVID-19 pneumonia, we selected unadjusted clinical risk factors for developing the composite endpoint of IMV or death. The risk for the primary outcome by each category was estimated using a Cox proportional hazards model. Bootstrapping was used to validate the results. RESULTS: Age above 62, eGFR under 60 ml/min, room air SpO2 ≤89 % upon admission, history of hypertension, history of diabetes, and any comorbidity (cancer, cardiovascular disease, COPD/ asthma, hypothyroidism, or autoimmune disease) were considered for the score. Each of the six criteria scored 1 point. The score was further simplified into 4 categories: 1) 0 criteria, 2) 1 criterion, 3) 2-3 criteria, and 4) ≥4 criteria. Taking the first category as the reference, risk estimates for the primary endpoint were HR; 2.94 [1.67 - 5.26], 4.08 [2.63 - 7.05], and 6.63 [3.74 - 11.77], respectively. In ROC analysis, the AUC for the model was 0.72. CONCLUSIONS: Our score uses simple criteria to estimate the risk for IMV or death among COVID-19 inpatients with HFO. Higher category reflects consistent increases in risk for the endpoint.

A Usability-focused Method to Design a Cybersecurity MOOC for Children

Teaching cybersecurity to children is not a trivial task due to the complexity of explaining online-threat-related topics such as sexting or cyberbullying. Moreover, most of the courses designed to raise awareness in these controversial subjects has been mainly produced in English. However, during the Covid-19 pandemic, getting access to Spanish-based training for protecting children online became a priority for parents in countries such as Ecuador, which was not prepared to have children studying at home whilst being exposed to such threats. In this paper, we show that it is feasible to design a virtual course (MOOC) to teach cybersecurity to Spanish-speaking children with acceptable usability levels and minor usability issues. Our proposed methodology combines ADDIE, DPIPE and UDL for developing the course, and uses both SUS and Nielsen as methods to assess the MOOC from an usability point of view. For enhancing user engagement, our course uses novel 3D anthropomorphic characters and storyboards to aid the learning process. Regarding usability results, our proposed MOOC has very high and acceptable scores, with around 86/100 using the SUS scale, and less than 3 in the Nielsen score. © 2022 IEEE.

The arise of SARS-CoV-2 Delta variant in Cape Verde

Since March 2020, we have been living in a pandemic caused by the SARS-CoV-2 virus, responsible for COVID-19 disease. The emergence of new variants and strains of SARS-CoV-2 virus, in particular the Delta variant in October 2020, sparked a new alert for the scientific community, given its high efficiency in replication and transmissibility, as well as its relationship to more serious symptoms, which contribute to the increase of hospitalization and mortality rates, particularly in African countries. In this case report, we explored the arrival of the Delta variant in Cape Verde, an African middle-income country, in August 2021, and analyzed its possible effects on increased notification of new cases and mortality rates in the country, as well as the health system's responsiveness to the new variant. This is particularly relevant given the country's lack of infrastructure for the screening and surveillance of new variants, which, therefore, influence the adoption of new mitigation and control measures for COVID-19 prevention, particularly in this period of flexibilization of the most COVID-19 restrictive measures (i.e. social distance), return of tourism and schools activities in the country. © 2023 Multidisciplinary Science Journal. All rights reserved.

Viral and Host Small RNA Response to SARS-CoV-2 Infection

After two years into the pandemic of the coronavirus disease 2019 (COVID-19), it remains unclear how the host RNA interference (RNAi) pathway and host miRNAs regulate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and impact the development of COVID-19. In this study, we profiled small RNAs in SARS-CoV-2-infected human ACE2-expressing HEK293T cells and observed dysregulated host small RNA groups, including specific host miRNAs that are altered in response to SARS-CoV-2 infection. By comparing dysregulated miRNAs in different SARS-CoV-2-infected samples, we identified miRNA-210-3p, miRNA-30-5p, and miR-146a/b as key host miRNAs that may be involved in SARS-CoV-2 infection. Furthermore, by comparing virally derived small RNAs (vsmRNAs) in different SARS-CoV-2-infected samples, we observed multiple hot spots in the viral genome that are prone to generating vsmRNAs, and their biogenesis can be dependent on the antiviral isoform of Dicer. Moreover, we investigated the biogenesis of a recently identified SARS-CoV-2 viral miRNA encoded by ORF7a and found that it is differentially expressed in different infected cell lines or in the same cell line with different viral doses. Our results demonstrate the involvement of both host small RNAs and vsmRNAs in SARS-CoV-2 infection and identify these small RNAs as potential targets for anti-COVID-19 therapeutic development. © 2022 by the authors.

TFM a Dataset for Detection and Recognition of Masked Faces in the Wild

Droplet transmission is one of the leading causes of the spread of respiratory infections, such as coronavirus disease (COVID-19). The proper use of face masks is an effective way to prevent the transmission of such diseases. Nonetheless, different types of masks provide various degrees of protection. Hence, automatic recognition of face mask types may benefit the control access to facilities where a specific protection degree is required. In the last two years, several deep learning models have been proposed for face mask detection and properly wearing mask recognition. However, the current publicly available datasets do not consider the different mask types and occasionally lack real-world elements needed to train robust models. In this paper, we introduce a new dataset named TFM with sufficient size and variety to train and evaluate deep learning models for face mask detection and recognition. This dataset contains more than 135,000 annotated faces from about 100,000 photographs taken in the wild. We consider four mask types (cloth, respirators, surgical and valved) as well as unmasked faces, of which up to six can appear in a single image. The photographs were mined from Twitter within two years since the beginning of the COVID-19 pandemic. Thus, they include diverse scenes with real-world variations in background and illumination. With our dataset, the performance of four state-of-the-art object detection models is evaluated. The experimental results show that YOLOv5 can achieve about 90% of mAP@0.5, demonstrating that the TFM dataset can be used to train robust models and may help the community step forward in detecting and recognizing masked faces in the wild. Our dataset and pre-trained models used in the evaluation will be available upon the publication of this paper. © 2022 ACM.

Cumulative Steroid Dose in Hospitalized Patients and COVID-19 Associated Pulmonary Aspergillosis

Background. Severe COVID-19 elicits a hyperimmune response frequently amenable by high-dose steroids, although treatment may increase the risk for opportunistic infections. Invasive pulmonary aspergillosis (IPA) is a known complication of COVID-19, termed COVID-19 associated pulmonary aspergillosis (CAPA).While steroid use is a known risk factor for CAPA, the role of cumulative steroid dose in the development of CAPA is unclear. This study evaluates the relationship between cumulative steroid dose in hospitalized individuals and the risk for CAPA. Methods. This retrospective cohort study includes 130 hospitalized patients with RT-PCR-confirmed COVID-19 pneumonia at a specialized center in north Mexico. Patients who developed CAPA were matched by age and gender to two patients who did not develop CAPA. CAPA was defined according to 2020 ECMM/ISHAM criteria. Patients with either possible, probable, or proven CAPA were considered positive cases. Steroid dose was converted to dexamethasone equivalents according to potency and duration. Cumulative dose was obtained in every patient from admission until discharge or diagnosis of CAPA. We assessed the risk of CAPA by the continuous cumulative steroid dose using a logistic regression model. Results. A total of 42 patients were diagnosed with possible, probable, or confirmed CAPA and were matched to 88 controls. Mean age was 61 +/- 14 years, 94 (72%) were male, 11 (12%) were smokers, and 55 (50%) were obese. Mean cumulative steroid dose was 66 +/- 75 in patients without CAPA vs 195 +/- 226 in patients with CAPA (P< 0.001) (Figure Panel A). The risk for CAPA was higher as the cumulative dose of steroids increased, in a near-linear relationship (OR 1.008;95% CI 1.003, 1.013, P< 0.001) (Figure Panel B). Conclusion. Patients who develop CAPA have a history of higher cumulative steroid dose during hospitalization. The risk for CAPA increases in a near-linear fashion as the cumulative steroid dose during hospitalization increases. While causality cannot be drawn by this study, caution while prescribing high-dose steroids is warranted among individuals hospitalized with COVID-19 pneumonia. Clinical suspicion of CAPA should increase in individuals with a high cumulative dose of steroids and clinical decline.

Application of Crossed Impacts to Obtain Risk Indices for Stock Management

As a result of COVID 19, companies have presented problems of both excess and shortages in the management of their stocks, since there are often sudden changes in demand as a result of the behavior of the pandemic, these changes occur quickly and the Companies must react in a timely manner to have the least possible losses, in view of this scenario a situational analysis is proposed by exploring events in the business environment that may affect their demand, making an analysis of the probabilities of said events and how these interact and impact each other to obtain the probability of a future scenario consisting of an increase or decrease in demand, taking this probability as a risk index that serves as a basis for decision-making in stock management. The importance of this index lies in reducing the problems of excess or shortage of stocks. © 2022 IEEE.

Impact of the COVID-19 pandemic on hospital admission and clinical evolution

Introduction: The COVID-19 pandemic is considered to be the greatest healthcare challenge that has occurred in the world. Prevention and treatment services for chronic noncommunicable diseases have been severely affected. Objective: To identify the impact of the COVID-19 pandemic on the admission and clinical evolution of patients with cardiovascular pathologies treated in the Coronary Intensive Care Unit of the "Enrique Cabrera Cossío" General Teaching Hospital. Methods: A cross-sectional observational study was carried out. The universe consisted of all patients included in the unit's database (1360);the sample consisted of 213 and 159 patients attended six months prior to the pandemic (September 1 to February 28) and six months after its onset (March 1 to August 31), respectively;regardless of diagnosis. The results of the two periods were compared in terms of the following variables: number of admissions, clinical-epidemiological characteristics, clinical diagnosis on admission, and diagnosis on admission of the deceased. Results: We found a decrease in the number of admissions during the pandemic period of more cases, in the age group between 60 and 79 years. Mortality increased by 40.3%. Admissions for acute myocardial infarction increased (48.8%) and decreased for heart failure (70%) after the onset of the pandemic (p < 0.05);deaths due to acute myocardial infarction doubled and those caused by heart failure were reduced to zero in this same period. Conclusions: The COVID-19 pandemic has had a significant impact on the admission and clinical evolution of patients with cardiovascular pathologies. © 2022, Cuban Society of Cardiology, Cuban Institute of Cardiology and Cardiovascular Surgery. All rights reserved.

Cyber Dating Violence, attachment and relationship satisfaction in young Mexicans during confinement

With the appearance of COVID-19, couple relationships have been modified due to the leading role of ICT in the initiation and preservation of affective bonds, however, the inappropriate use of ICT can lead to Cyber dating violence (CDV). Thus, the objective of this research was to analyze this phenomenon and some associated factors in a sample of 230 young Mexicans, where CDV, attachment style and satisfaction with the relationship were evaluated. Based on the analyzes carried out, it was determined that control behaviors committed and suffered were found in the female sample, a relationship of CDV with avoidant and anxious attachment, as well as with satisfaction with the relationship;Likewise, a positive association was determined between the duration of the relationship and the CDV of control committed and suffered. For their part, the men indicated having suffered and perpetrated direct aggression and control, links were also found between the control committed and suffered, and the aggression committed and suffered. In conclusion, the data obtained suggest that Cyber dating violence is a bidirectional phenomenon, which is related to attachment and satisfaction with the relationship.

Twitter Face Image Mining for Recognition of Different Face Mask Types

In the current pandemic of coronavirus disease (COVID-19), an effective way to prevent the transmission and infection of the virus is the proper use of face masks. However, the different types of masks provide different degrees of protection. For instance, valved masks protect the user but do not help to stop the transmission. Hence, the automatic recognition of face mask types may benefit applications that control access to facilities where a certain facepiece is required. In this paper, we propose a Twitter mining framework to gather a large-scale dataset of masked faces suitable to train deep learning-based models for face mask recognition. We employ a keyword-based selection where non-face images are discarded by an efficient face detector (Retinaface). Finally, we train a state-of-the-art CNN architecture (ConvNeXt) for recognizing the wearing mask. We also present a brief analysis of more than two million image-based tweets acquired over two years since the beginning of the pandemic. The code of the proposed framework and a preliminary dataset of more than 10K faces (manually annotated into unmasked, surgical, cloth, respirators, and valved masks) are available on github.com/GibranBenitez/FaceMask Twitter. © 2022 The authors and IOS Press. All rights reserved.

Differential innate immune response and replication of SARS-CoV-2 in human diabetic corneal epithelial cells

Purpose : Diabetes predisposes an individual to severe COVID-19. Diabetic cornea is also known to have impaired wound healing, increasing the chances of infection. Earlier, we reported the ability of SARS-CoV-2 to infect conjunctival cells, and the presence of viral RNA and proteins was also detected in the corneas of COVID-19 donors. In this study, we evaluated the effect of diabetes on corneal innate immune response during SARS-CoV-2 infection and sought to determine the underlying mechanisms. Methods : Human primary corneolimbal epithelial cells (HCECs) were isolated from the corneas of three diabetic and three non-diabetic donors. In vitro studies were performed by infecting HCECs with SARS-CoV-2-USA-WA1/2020 strain at MOI 0.5. Viral replication was assessed by viral genome copy number. RNAseq analysis was performed to determine genes/pathways altered by diabetic vs non-diabetic HCECs. qPCR was used to assess the expression of innate inflammatory and antiviral genes. Western blot was performed to detect the protein expression of antiviral signaling molecules. Results : The primary HCECs were found permissive to SARS-CoV-2 infection, as evidenced by increased viral replication which peaked at day 3 p.i. along with an induction of pSTAT1. Interestingly, HCECs from diabetic cornea had higher viral RNA on all three days post-infection. SARS-CoV-2 infected HCECs exhibited induced expression of inflammatory genes and their levels were relatively higher in diabetic cells. RNA-seq analysis revealed significant differences in diabetic vs. non-diabetic SARS-CoV-2 infected cells with alteration in genes regulating viral response, inflammation, and injury. The most affected down-regulated genes are related to lipid metabolism, ferroptosis, and oxidative stress. Conclusions : Our study demonstrates increased SARS-CoV-2 replication and differential innate antiviral and inflammatory response in HCECs from diabetic corneas. These results indicate that diabetes is a potential risk for enhanced infectivity of SARS-CoV-2 for the ocular surface.

Millennials and COVID-19

News about this novel virus that was striking China has started roaming around. They said that while it started like the common cold, the virus led to severe respiratory distress and failure. It was taking their health-care system to its limits. We did not know much, but after several weeks, we were talking about this virus been all over China and Europe. The tension started to build, but we were not doing a lot. As the virus reached Seattle and started to spread around the United States, that tension promptly progressed to anxiety. This led to increased efforts in preparation to what seemed inevitable. But by then, it was too late. Even though we were preparing for it, we underestimated the virus capability to spread. © 2022 Elsevier Inc. All rights reserved.

Epidemiology, Management and Risk of Sars-Cov2 Transmission in a Cohort of Newborns Born to Mothers Diagnosed with Covid19 Infection

INTRODUCTION: the impact of maternal SARS-CoV2 infection and its risk of vertical transmission is still not well known. Recommendations from scientific societies seek to provide safety for newborns without compromising the benefits of early contact. The aim of the study is to describe characteristics and evolution of newborns born to mothers with SARS-CoV2 infection, as well as the implemented measures following recommendations from the Sociedad Espanola de Neonatologia. METHODS: observational, prospective and single-center cohort study. A specific circuit was designed for mothers with SARS-CoV2 infection and their newborns. Epidemiological and clinical data were collected. PCR were performed in newborns at delivery and at 14 days of age. RESULTS: 73 mothers and 75 newborns were included in the study. 95.9% of maternal infections were diagnosed during the third trimester of pregnancy, 43.8% were asymptomatic. Median gestational age was 38 weeks (IQR:37-40), 25.9% of newborns required admission to Neonatology. Skin-to-skin mother care was performed in 68% of newborns, 80% received exclusive maternal or donated breast milk during hospital stay. No positive PCR results were observed in newborns at delivery, one case of positive PCR was observed in an asymptomatic neonate at 14 days of age. CONCLUSIONS: Risk of SARS-CoV2 transmission is low when complying to the recommendations issued by Sociedad Espanola de Neonatologia, allowing rooming-in and promoting breastfeeding.

Digital safety and its importance in teacher education. Analysis of children's online behaviour in the Czech and Polish context

Internet use has skyrocketed in recent years, leading to risky behaviour such as online aggression. The aim of this study was to analyse the risks in the online environment of Czech and Polish students, with a special focus on online aggression. A quantitative approach was employed using an online survey. A total of 13657 students from the Czech Republic and Poland, aged 7-17 years (M = 13.75;SD = 3.85), participated in the study. The results revealed the apps most used by children (mostly YouTube, Facebook and Instagram) and online safety issues such as user theft, sexting and cyber-aggression. Finally, the implications of this work are discussed, highlighting the richness of the data obtained in relation to risk behaviours on the Internet during the Covid-19 pandemic. © 2022, AUFOP. All rights reserved.