Coping and emotions of global higher education students to the Ukraine war worldwide.

Trauma scientists have raised the alarm about the devastating consequences of the Ukraine war on mental health. We examined how higher education students-as indirect victims-coped with this conflict and how they emotionally reacted during 2022. We involved 2314 students from 16 countries through an online survey. A structural equation model indicated significant relations between war-related worry about military and macroeconomics domains and two coping strategies (opposition, support giving), in turn significantly linked with six emotions. The model was strongly invariant across gender, study field, and geographic area. The most frequent emotions were anger and anxiety, followed by two future-centred emotions (hopelessness and hope). Emotions were more frequent for females and students of the countries geographically close to the war region. Our findings call for evidence-based policy recommendations to be implemented by institutions to combat the negative short and long-term psychological sequelae of being witnesses of armed conflicts.

Prognostic factors of cataract surgery in patients with uveitis.

PURPOSE: To evaluate the long-term visual outcomes of patients with uveitis undergoing cataract surgery and to identify possible factors influencing the visual prognosis and the development of postoperative complications. METHODS: Retrospective study of all patients with uveitis who underwent cataract surgery between January 2015 and February 2020 in our tertiary referral center. RESULTS: A total of 78 eyes from 78 patients were included in the study. The best-corrected visual acuity (BCVA) improved in 86% of patients, and a BCVA of 0.5 or better was achieved in 57 (73%) patients. A significant correlation was shown between the preoperative and postoperative BCVA (Spearman r = 0.521, p < 0.01). Final BCVA differed between diverse anatomical uveitis entities (p = 0.047), and anterior uveitis demonstrated the best outcomes. Chronic uveitis resulted in a worse final BCVA than acute recurrent uveitis (p = 0.001). The presence of CME any time before the surgery and intermediate uveitis were associated with worse visual prognosis, while systemic therapy for uveitis before surgery and iris manipulation during surgery were not related to visual outcomes. Postoperative development of cystoid macular edema (CME) was closely associated with preexisting CME (p < 0.001) and intermediate uveitis (p = 0.01). CONCLUSIONS: Visual results of cataract surgery in patients with uveitis were beneficial, but limited visual outcomes were more frequently observed in patients with chronic uveitis and intermediate uveitis with a history of CME. In consequence, prevention, or adequate treatment of CME, especially in patients with intermediate uveitis, might result in better visual results of their cataract surgery.

Higher education students' achievement emotions and their antecedents in e-learning amid COVID-19 pandemic: A multi-country survey.

The outbreak of the COVID-19 pandemic has had a wide range of negative consequences for higher education students. We explored the generalizability of the control-value theory of achievement emotions for e-learning, focusing on their antecedents. We involved 17019 higher education students from 13 countries, who completed an online survey during the first wave of the pandemic. A structural equation model revealed that proximal antecedents (e-learning self-efficacy, computer self-efficacy) mediated the relation between environmental antecedents (cognitive and motivational quality of the task) and positive and negative achievement emotions, with some exceptions. The model was invariant across country, area of study, and gender. The rates of achievement emotions varied according to these same factors. Beyond their theoretical relevance, these findings could be the basis for policy recommendations to support stakeholders in coping with the challenges of e-learning and the current and future sequelae of the pandemic.

Impacts of the Covid-19 Pandemic on Life of Higher Education Students: Global Survey Dataset from the First Wave.

The Covid-19 pandemic caused by the novel coronavirus SARS-CoV-2 has completely reshaped the lives of people around the world, including higher education students. Beyond serious health consequences for a proportion of those directly affected by the virus, the pandemic holds important implications for the life and work of higher education students, considerably affecting their physical and mental well-being. To capture how students perceived the first wave of the pandemic's impact, one of the most comprehensive and large-scale online surveys across the world was conducted. Carried out between 5 May 2020 and 15 June 2020, the survey came at a time when most countries were experiencing the arduous lockdown restrictions. The online questionnaire was prepared in seven different languages (English, Italian, North Macedonian, Portuguese, Romanian, Spanish, Turkish) and covered various aspects of higher education students' life, including socio-demographic and academic characteristics, academic life, infrastructure and skills for studying from home, social life, emotional life and life circumstances. Using the convenience sampling method, the online questionnaire was distributed to higher education students aged 18 and over and enrolled in a higher education institution. The final dataset consisted of 31,212 responses from 133 countries and 6 continents. The relationships between selected socio-demographic characteristics and elements of student life were tested by using a chi-squared test. The data may prove useful for researchers studying the pandemic's impacts on various aspects of student life. Policymakers can utilize the data to determine the best solutions as they formulate policy recommendations and strategies to support students during this and any future pandemic.

Academic student satisfaction and perceived performance in the e-learning environment during the COVID-19 pandemic: Evidence across ten countries.

The outbreak of the COVID-19 pandemic has dramatically shaped higher education and seen the distinct rise of e-learning as a compulsory element of the modern educational landscape. Accordingly, this study highlights the factors which have influenced how students perceive their academic performance during this emergency changeover to e-learning. The empirical analysis is performed on a sample of 10,092 higher education students from 10 countries across 4 continents during the pandemic's first wave through an online survey. A structural equation model revealed the quality of e-learning was mainly derived from service quality, the teacher's active role in the process of online education, and the overall system quality, while the students' digital competencies and online interactions with their colleagues and teachers were considered to be slightly less important factors. The impact of e-learning quality on the students' performance was strongly mediated by their satisfaction with e-learning. In general, the model gave quite consistent results across countries, gender, study fields, and levels of study. The findings provide a basis for policy recommendations to support decision-makers incorporate e-learning issues in the current and any new similar circumstances.

ACUTE IDIOPATHIC MACULOPATHY: A Proposed Disease Staging Based on Multimodal Imaging.

PURPOSE: To describe the clinical course and the multimodal imaging of acute idiopathic maculopathy. METHODS: Medical records and multimodal imaging including color fundus photography, optical coherence tomography, and fundus autofluorescence were retrospectively reviewed. Recognition of the fundus autofluorescence patterns and their relationship with the disease duration, best-corrected visual acuity, and optical coherence tomography features represented the main outcome measures. RESULTS: Seventeen eyes of 16 patients (7 women; mean age 29.9 years) with a mean follow-up of 23.9 months were included. The mean best-corrected visual acuity at presentation was 0.63 ± 0.54 logarithm of the minimum angle of resolution (Snellen equivalent, 20/85). All but one patient had the best-corrected visual acuity recovery to 20/20. Four sequential patterns of fundus autofluorescence corresponding to 4 proposed stages of disease were observed. Patterns 1 (central hypoautofluorescence with surrounding hyperautofluorescence) and 2 (stippled hyperautofluorescence and hypoautofluorescence) were found at presentation. Patterns 3 (central hyperautofluorescence surrounded by hypoautofluorescence) and 4 (hypoautofluorescence) were observed during the disease course and/or at the last follow-up visit. Duration of the disease was significantly different between patterns at baseline and last visit. Pattern 1 significantly related to the presence of subretinal detachment (Fisher's exact test; P =0.003) on optical coherence tomography in comparison with Pattern 2. Pattern 4 showed unique homogeneously decreased autofluorescence with corresponding attenuation of retinal pigment epithelium and restored outer retinal layers on optical coherence tomography. CONCLUSION: A sequential disease staging based on multimodal imaging for acute idiopathic maculopathy is proposed. The recognition of the observed imaging patterns may help clinicians in the correct diagnosis and patient counseling.

Clinical Features of Acute Anterior Uveitis with Complicated Course in a Slovenian Patient Population.

PURPOSE: To report on patients who needed hospitalization due to acute anterior uveitis (AAU) and within this group to compare clinical features and outcomes of treatment of HLA-B27+ and HLA-B27- AAU in the population of Slovenian patients. METHODS: Retrospective study of hospitalized patients with AAU in the last 39 months at the Eye Hospital in Ljubljana. The data of AAU patients were retroactively studied and compared on the basis of HLA-B27 antigen presence: visual acuity upon admission, visual outcome, the presence of hypopyon, fibrinous reaction, posterior iris synechiae, and complications, such as elevated intraocular pressure, cataract, and cystoid macular edema (CME). We compared the investigations in the diagnostic process, the associated systemic disease, and the treatment administered. Statistical analyses included Student's t-test Fisher's exact test, and the Kolmogorov-Smirnov test. A p value of <0.05 was considered statistically significant. RESULTS: A total of 37 hospitalized patients with AAU were included. HLA-B27 antigen was detected in 73% of patients. In the HLA-B27+ group, women were more commonly affected, while the males were more affected in the HLA-B27- group. The occurrence of fibrin was significantly more common in HLA-B27+ patients, as well as hypopyon and posterior synechiae; only fibrin reached the statistical significance (p < 0.05). The incidence of cataracts, ocular hypertension, and glaucoma did not differ significantly between the two groups. HLA-B27+ AAU was more often associated with systemic diseases, and patients in this group were more frequently treated with systemic immunomodulatory drugs, however, no difference reached the statistical significance. We did not notice any major differences in the final visual acuity in the comparing groups. CONCLUSION: Almost ¾ of AAU patients that required hospitalization were HLA-B27+. In this group, disease was more severe, more frequently associated with ocular complications and systemic disease, but final visual acuity was the same in both groups. HLA-B27 typing has no prognostic value in our group of complicated AAU patients, but it eases the decision about necessary diagnostics and treatment.

Exploring critical factors of the perceived usefulness of blended learning for higher education students.

Performed in a Slovenian higher education institution, the presented research was designed to help investigate which factors influence the ways a student perceives an e-course's usefulness in a blended learning environment. The study is based on an online questionnaire completed by 539 students whose participation in the survey was voluntary. Using structural equation modelling, the students' perceptions of different aspects were investigated, including their attitudes to course topics and technology, learning preferences, teachers' role in course design and managing the teaching process. The empirical results show e-learning is positively perceived to be usefulness when: (1) the teacher is engaged and their activities in an e-course, with the (2) a student's attitude to the subject matter and the lecturer's classroom performance having a direct impact, and (3) technology acceptance having an indirect impact. No major differences were revealed when the model was tested on student subgroups sorted by gender, year of study, and students' weekly spare-time activities.

New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking.

During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.

Computational models reveal genotype-phenotype associations in Saccharomyces cerevisiae.

Genome sequencing is essential to understand individual variation and to study the mechanisms that explain relations between genotype and phenotype. The accumulated knowledge from large-scale genome sequencing projects of Saccharomyces cerevisiae isolates is being used to study the mechanisms that explain such relations. Our objective was to undertake genetic characterization of 172 S. cerevisiae strains from different geographical origins and technological groups, using 11 polymorphic microsatellites, and computationally relate these data with the results of 30 phenotypic tests. Genetic characterization revealed 280 alleles, with the microsatellite ScAAT1 contributing most to intrastrain variability, together with alleles 20, 9 and 16 from the microsatellites ScAAT4, ScAAT5 and ScAAT6. These microsatellite allelic profiles are characteristic for both the phenotype and origin of yeast strains. We confirm the strength of these associations by construction and cross-validation of computational models that can predict the technological application and origin of a strain from the microsatellite allelic profile. Associations between microsatellites and specific phenotypes were scored using information gain ratios, and significant findings were confirmed by permutation tests and estimation of false discovery rates. The phenotypes associated with higher number of alleles were the capacity to resist to sulphur dioxide (tested by the capacity to grow in the presence of potassium bisulphite) and the presence of galactosidase activity. Our study demonstrates the utility of computational modelling to estimate a strain technological group and phenotype from microsatellite allelic combinations as tools for preliminary yeast strain selection.

Computational models for prediction of yeast strain potential for winemaking from phenotypic profiles.

Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40 °C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naïve Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 µg/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection procedures.