This study aimed to evaluate the link between health problems, demographic factors, and the indoor environment quality of residents in Indonesia. We conducted a cross-sectional design study through a questionnaire survey with 443 respondents aged between 12 and 81 years. The questionnaire was concerned with previous health problem occurrences associated with thermal discomfort experiences, indoor environments, economic conditions, and basic anthropometric factors. Logistic regression with the odds ratio (OR) was applied to evaluate the tendency of different respondent groups to suffer from certain health problems, when compared to reference groups. Furthermore, structural equation modelling (SEM) was used to incorporate certain factors (economic conditions, thermal discomfort experiences, and perceived indoor environments) into a single model to understand their direct and indirect effects on health conditions. The results indicate that economic conditions are the most significantly associated with health problems. Furthermore, we found that the low-income group was the most vulnerable to health problems, including coughing, puking, diarrhoea, odynophagia, headaches, fatigue, rheumatism, fidgeting, skin rashes, muscle cramps, and insomnia (OR: 1.94C6.04, p <0.05). Additionally, the SEM suggested that the respondents economic conditions and thermal discomfort experiences had significant direct effects on their health problems with standardized estimates of -0.29 and 0.55, respectively. Additionally, perceived indoor environment quality, which is possible to cause thermal discomfort experience, indirectly affect health problems. These findings contribute an insightful and intuitive knowledge base which can aid health assessments associated with demographic and physical environments in developing sustainable and healthy environment strategies for the future.

Twenty-seven strains of avian infectious bronchitis virus (IBV) were isolated from dead or diseased chickens at different chicken farms in South China during 2004C2008, of which the S1 gene was sequenced. Phylogenetic analysis of the S1 gene sequences of the isolated 27 strains together with 29 strains published in Genbank revealed that all IBV strains except for one isolated and one published were clustered into six distinct genotypes I-VI. 26 isolated strains belong to genotypes I, II, and III, forming a big phylogenetic branch without new predominant strains, whereas all five vaccine strains belong to genotype V that is evolutionarily distant from genotypes I, II, and III. The study of the protease cleavage motif within the S1 protein found 12 different cleavage motifs, of which 3 motifs are shared by both isolated and published strains, 2 motifs unique to isolated strains, and 7 motifs unique to published strains, further bolstering the notion of no new predominant strains. Alignment analysis of the S1 amino acid sequences indicated that the amino acid substitutions, insertions, and deletions are polymorphic and diverse, showing no sign of predominant genetic changes among the isolated strains. Taken together, there was no predominant new strain circulating in South China during 2004C2008. Nonetheless, circulating IBV strains have been continuously evolving with genetic compositions distant from vaccine strains; this explains why there have been constant but infrequent outbreaks in commercial flocks in South China during 2004C2008. Furthermore, in order to safe guard against the sudden emergence of new predominant strains, continuing surveillance of IBV strains circulating in the field is of extreme importance.

Efforts to contain the spread of SARS-CoV-2 have spurred the need for reliable, rapid, and cost-effective diagnostic methods which can easily be applied to large numbers of people. However, current standard protocols for the detection of viral nucleic acids while sensitive, require a high level of automation, sophisticated laboratory equipment and trained personnel to achieve throughputs that allow whole communities to be tested on a regular basis. Here we present Cap-iLAMP (capture and improved loop-mediated isothermal amplification). This method combines a hybridization capture-based RNA extraction of non-invasive gargle lavage samples to concentrate samples and remove inhibitors with an improved colorimetric RT-LAMP assay and smartphone-based color scoring. Cap-iLAMP is compatible with point-of-care testing and enables the detection of SARS-CoV-2 positive samples in less than one hour. In contrast to direct addition of the sample to improved LAMP (iLAMP), Cap-iLAMP does not result in false positives and single infected samples can be detected in a pool among 25 uninfected samples, thus reducing the technical cost per test to ~1 Euro per individual.

The VOC of SARS-CoV-2, Omicron (BA.1, BA.1.1, BA.2, or BA.3), is associated with an increased risk of reinfection. BA.2 has become the next dominant variant worldwide. Although BA.2 infection has been shown to be mild illness, its high transmissibility will result in high numbers of cases. In response to the surge of Omicron BA.1 cases, booster vaccination was initiated in many countries. But there is limited evidence regarding the effectiveness of a booster vaccination against BA.2. We collected blood samples from 84 physicians at Kobe University Hospital, Japan, in January 2022 [~]7 months after they had received two BNT162b2 vaccinations and [~]2 weeks after their booster vaccination. We performed a serum neutralizing assay against BA.2 using authentic virus. Although most of the participants had no or a very low titer of neutralizing antibody against BA.2 at 7 months after two BNT162b2 vaccinations, the titer increased significantly at 2 weeks after the booster vaccination.

Limitation of direct physical interaction related to the Covid-19 pandemic has an impact on the education sector, where all learning activities are carried out online to limit physical interactions. Online learning methods are considered more flexible to do when compared to direct learning methods. This research was conducted to determine how much difference the mental load felt by final year students in online learning and direct learning. Measurement of a mental load was carried out using the National Aeronautics and Space Administration Task Load Index (NASA-TLX) method by distributing questionnaires containing six subscales of mental load measurement to final year students of four different study programs, including Management, Accounting, Informatics Engineering, and English. The six subscales used include Mental Demands, Physical Demands, Temporal Demands, Own Performance, Effort, and Frustration. Based on the results of the average calculation of the four sample groups, it shows that the mental load of online learning is 0.4% greater than direct learning, 81.3% and 80.9%, respectively.

Purpose: The COVID-19 pandemic and the resulting social distancing and lockdown measures are having a substantial impact on daily life and medical management of people with breast cancer. We evaluated to what extent these changes have affected quality of life and physical, and psychosocial wellbeing of people (being) treated for breast cancer. Methods: This study was conducted within the prospective Utrecht cohort for Multiple BREast cancer intervention studies and Long-term evaluation (UMBRELLA). Shortly after the implementation of COVID-19 measures, extra questionnaires were sent to 1595 cohort participants, including standard UMBRELLA quality of life (EORTC) questionnaires. Patient-reported outcomes (PROs) were compared to the most recent PROs collected within UMBRELLA before COVID-19. The impact of COVID-19 on PROs was evaluated using mixed models analysis. Results: In total, 1051 patients (66%) completed the questionnaires. One third (n = 327, 31%) reported a higher threshold to contact their general practitioner due to COVID-19. A significant deterioration in emotional functioning was observed (82.6 to 77.9, p < 0.001) and 505 (48%, 95% CI 45-51) patients reported moderate to severe loneliness. Small significant improvements were observed in QoL, physical-, social- and role functioning scores. In the subgroup of 51 patients under active treatment, there was a strong deterioration in social functioning (69.8 to 5.0, p = 0.03). Conclusion: Due to COVID-19, patients (being) treated for breast cancer are less likely to contact physicians, and experience a deterioration in emotional functioning. Patients undergoing active treatment report a strong drop in social functioning. One in two patients reports (severe) loneliness. Online applications facilitating peer contact and e-mental health interventions could support mental health and social interaction times of total lockdown or social distancing.

The present study aims to highlight how women perceive and adapt to infertility difficulties. To better understand the difficulties that women diagnosed with infertility are experiencing, the study explores this concept in correlation with anxiety and coping. 240 women with fertility problems from various parts of Romania completed the State-Trait Anxiety Inventory (STAI-Form Y), Brief COPE and the scale Difficulties With Infertility and Its Treatment. Statistical analyzes showed that women who were at the beginning of treatment obtained higher scores on the anxiety [F(2,237) = 4.76, p = 0.009] and on the difficulties scale [F(2,237) = 3.53, p = 0.031], compared to participants who resorted to repeated fertilization procedures. It is important to emphasize that there is a significant positive correlation between the perception of infertility difficulties and coping, and also between difficulties and state anxiety. Regarding the relationship between state anxiety and coping, there were significant positive associations between maladaptive coping strategies and state anxiety, while adaptive strategies were negatively associated with state anxiety. In addition, regarding coping strategies, venting and self-blame occurred predominantly in women who know that the cause of infertility is female-related. These findings draws attention to the fact that infertile women live this experience at very high levels of anxiety, using quite a few adaptive coping mechanisms. These results highlight the need to investigate ways to reduce anxiety and optimizing adaptive coping strategies.

On 3 March 2020, the first case of COVID-19 was confirmed in Chile Since then, the Ministry of Health has imposed mobility restrictions, a global policy implemented to mitigate the propagation of the virus The national seismic network operating throughout Chile provides an opportunity to monitor the ambient seismic noise (ASN) and determine the effectiveness of public policies imposed to reduce urban mobility in the major cities Herein, we analyse temporal variations in high-frequency ASN recorded by broadband and strong-motion instruments deployed throughout the main cities of Chile We focus on the capital, Santiago, a city with more than 7 million inhabitants because it is seismically well instrumented and has high levels of urban mobility due to worker commutes inside the region We observed strong similarities between anthropogenic seismic noise and human mobility indicators, as shown in the difference between urban and rural amplitudes, long-term variations, and variability due to the COVID-19 outbreak The same results are observed in other cities such as Iquique, La Serena, and Concepcin Our findings suggest that the initially implemented public health policies and the early end to confinement in mid-April 2020 in the metropolitan region caused an increase in mobility and virus transmission, where the peak in anthropogenic seismic noise coincides with the peak of the effective reproductive number from confirmed positive cases of COVID-19 These results confirm that seismic networks are capable of recording the urban mobility of population within cities, and we show that continuous monitoring of ASN can quantify urban mobility Finally, we suggest that real-time changes in ASN amplitudes should be considered part of public health policy in further protocols in Santiago and other high-density cities of the world, as has been useful during the recent pandemic

The recent availability of electronic health records (EHRs) have provided enormous opportunities to develop artificial intelligence (AI) algorithms. However, patient privacy has become a major concern that limits data sharing across hospital settings and subsequently hinders the advances in AI. \textit{Synthetic data}, which benefits from the development and proliferation of generative models, has served as a promising substitute for real patient EHR data. However, the current generative models are limited as they only generate \textit{single type} of clinical data, i.e., either continuous-valued or discrete-valued. In this paper, we propose a generative adversarial network (GAN) entitled EHR-M-GAN which synthesizes \textit{mixed-type} timeseries EHR data. EHR-M-GAN is capable of capturing the multidimensional, heterogeneous, and correlated temporal dynamics in patient trajectories. We have validated EHR-M-GAN on three publicly-available intensive care unit databases with records from a total of 141,488 unique patients, and performed privacy risk evaluation of the proposed model. EHR-M-GAN has demonstrated its superiority in performance over state-of-the-art benchmarks for synthesizing clinical timeseries with high fidelity. Notably, prediction models for outcomes of intensive care performed significantly better when training data was augmented with the addition of EHR-M-GAN-generated timeseries. EHR-M-GAN may have use in developing AI algorithms in resource-limited settings, lowering the barrier for data acquisition while preserving patient privacy.

This commentary proposes a shift in the current diagnostic workflow for patients with metastatic cancer to incorporate the use of liquid biopsy. This proposal, born in the time of a severe crisis for the health care system, might also be applied when the severe acute respiratory syndrome coronavirus 2 outbreak ends and thereby reduce the turnaround time for results from molecular testing for patients with cancer and increase the number of patients potentially benefiting from highly effective targeted therapies.

This study compares university students' approaches to learning and experiences with the teaching-learning environment in general and during online studying as a result of the COVID-19 pandemic. It examines students' learning profiles and how students with different learning profiles experienced the teaching-learning environment during COVID-19 as well as their approaches to learning and study-related burnout in general. The participants were 665 first- and second-year students. The profiles were examined using K-means cluster analyses and the differences in learning profiles using one-way ANOVA and the Tuckey Test. The results show changes in students' approaches to learning and their experiences with the teaching-learning environment and study-related burnout within the different profiles when comparing a normal situation to the COVID-19 pandemic. We suggest that changes in study-related burnout can be different among different study profiles. The results imply that students with a fragmented knowledge base and difficulties in managing time and effort would require special attention in online teaching situations.

The COVID-19 pandemic exacerbates existing health inequities, including gender disparities, and we must learn from previous global public health threats to build a gender-responsive, intersectional approach to address immediate and long-term consequences. While a narrow gender focus alone can reinforce binary and competing understandings of disease burden by gender, an intersectionality approach encourages understanding of the dimensions of power, historical structural inequalities, and the role of social determinants and lived experience to inform a multidimensional, gender-informed response to this and future emerging infectious diseases. We provide specific, actionable recommendations for critical healthcare, public health, and policy to use an intersectional approach to COVID-19 pandemic preparedness, response and resiliency.

All at once, the U.S. found itself embattled with the threat of COVID-19, the new normal of social distancing, and the perennial scourge of racial injustice. While simultaneously battling those ills, the class of 2020 law graduates found themselves also contending with inflexible bar licensing policies that placed at risk their health, safety, and careers. During a global health pandemic, bar licensing authorities made the bar exam a moving target riddled with uncertainty and last-minute cancellations. This costly and unsettling uncertainty surrounding the bar exam administration was unnecessary because multiple alternatives were available to safely license new attorneys. A ball was dropped, and bar examiners at the state and national levels failed epically at an opportunity to be adaptive, decisive, and transparent, to the detriment of a class new lawyers and the public they will serve. The dogged insistence on status quo that led to the bar exam chaos of 2020, has placed the method and purpose of bar examination under national scrutiny. This Article offers a critical analysis of the systemic failure of bar licensure authorities to respond adaptively to crisis;explores alternative processes to measure minimal competency;and offers insight about the institutional mindset that has dominated our perception of the bar exam. An entire class of bar takers was held captive to conventional thinking at a time that called for compassion and innovation. Any failures on this bar exam are ours, not theirs.

The COronaVIrus Disease 2019 (COVID-19) pandemic is unfortunately highly transmissible across the people. In order to detect and track the suspected COVID-19 infected people and consequently limit the pandemic spread, this paper entails a framework integrating the machine learning (ML), cloud, fog, and Internet of Things (IoT) technologies to propose a novel smart COVID-19 disease monitoring and prognosis system. The proposal leverages the IoT devices that collect streaming data from both medical (e.g., X-ray machine, lung ultrasound machine, etc.) and non-medical (e.g., bracelet, smartwatch, etc.) devices. Moreover, the proposed hybrid fog-cloud framework provides two kinds of federated ML as a service (federated MLaaS); (i) the distributed batch MLaaS that is implemented on the cloud environment for a long-term decision-making, and (ii) the distributed stream MLaaS, which is installed into a hybrid fog-cloud environment for a short-term decision-making. The stream MLaaS uses a shared federated prediction model stored into the cloud, whereas the real-time symptom data processing and COVID-19 prediction are done into the fog. The federated ML models are determined after evaluating a set of both batch and stream ML algorithms from the Pythons libraries. The evaluation considers both the quantitative (i.e., performance in terms of accuracy, precision, root mean squared error, and F1 score) and qualitative (i.e., quality of service in terms of server latency, response time, and network latency) metrics to assess these algorithms. This evaluation shows that the stream ML algorithms have the potential to be integrated into the COVID-19 prognosis allowing the early predictions of the suspected COVID-19 cases.

BACKGROUND: Medicine is an incredibly demanding career that appears to leave many medical students at risk of fatigue, anxiety, depression and burnout. Since adaptation and lifestyle changes are important, quality of life (QOL) of students during medical school could be impaired. Personality traits and emotional intelligence (EI) facets may be both linked to medical students QOL. To our knowledge, no studies have been done on the concurrent and prospective relationship between QOL-related personality traits and EI in Lebanese medical students. This study aimed to investigate the role of EI as a mediator between personality traits and QOL among a sample of Lebanese medical students. METHODS: This research is a descriptive cross-sectional survey study involving 293 Lebanese medical students recruited from all 7 Faculties of Medicine in Lebanon (JuneCDecember 2019). Structural equation modeling (SEM) was performed using SPSS AMOS v.24 to examine the structural relationship between each personality trait taken as independent variables, QOL as the dependent variable, and emotional intelligence as the mediator, among university students. The relative Chi-square ((2)/df), root mean square error of approximation (RMSEA) statistic, Tucker Lewis Index (TFI) and the comparative fit index (CFI) were used to evaluate the goodness-of-fit of the model. RESULTS: Higher conscientiousness was significantly associated with more EI (Beta = 0.38; p < 0.001) and lower QOL (Beta = ? 0.14; p = 0.025). The indirect relationships between conscientiousness, EI and QOL showed that EI mediated the association between conscientiousness and QOL (Beta = 0.17; 95% CI ? 0.73 to ? 0.004; p = 0.037). The fit indices of this model were adequate for (2)/df, RMSEA and CFI but not TLI. Higher openness to experience was significantly associated with more EI (Beta = 0.48; p < 0.001) and lower QOL (Beta = ? 0.38; p < 0.001). The indirect relationships between openness to experience, EI and QOL showed that EI mediated the association between openness to experience and QOL (Beta = 0.30; 95% CI ? 1.11 to ? 0.03; p = 0.04). The fit indices were adequate for (2)/df and CFI but not RMSEA and TLI. EI did not mediate the association between the other three personality traits (extroversion, agreeableness and neuroticism) and QOL. CONCLUSION: This current research has shed considerable light on the nexus of associations between EI, personality traits and well-being, nonetheless, led to the creation of more puzzling questions. On the whole, it seems that EI and its components can be used as an evaluation instrument in relates with Lebanese medical students personality profile as a means of future training to improve quality of life during medical education.

The diffusion of minimally invasive techniques for renal surgery has prompted a renewed interest in nephropexy which is indicated to prevent nephroptosis in symptomatic patients and to mobilize the upper ureter downward in order to bridge a ureteral defect. Recent publications have been reviewed to present the state of the art of the diagnosis and management of these two challenging conditions and to try to foresee the next steps. The evaluation of patients with mobile kidney can be made relying on diagnostic criteria such as ultrasound with color Doppler and measurement of resistive index, conventional upright X-ray frames after a supine uro-computerized tomography scan and both static and dynamic nuclear medicine scans, always with evaluation in the sitting or erect position. Laparoscopic nephropexy emerges as the current treatment option combining both objectively controlled repositioning of the kidney and resolution of symptoms with minimal invasiveness, low morbidity, and short hospital stay. The use of robotics is presently limited by its higher cost, but may increase in the future. Downward renal mobilization and nephropexy is a safe and versatile technique which has been adopted as a unique strategy or more often in combination with other surgical maneuvers in order to cope with complex ureteral reconstruction.

The aim of this study was to describe oral lesions in a group of patients with COVID-19. We recruited 55 patients, 25 women (45.5%) and 30 men (54.5%), aged between 1 and 89 years with confirmed COVID-19 at different stages of severity. After obtaining informed consent, we examined their mouths and recorded clinical findings. Forty percent of the patients had at least 1 oral lesion. The most common lesions were candidiasis and ulcers (7 patients each); 2 patients had enanthems. Geographic tongue and caviar tongue were also observed. Altered taste, dry mouth, and painful/burning mouth were noted in 60%, 27.3%, and 36.4% of patients, respectively. Oral mucosal alterations and lesions were prevalent in this series of COVID-19 patients. Altered taste and a painful/burning mouth were common symptoms.

The coronavirus disease 2019 (COVID-19) pandemic is disturbing and overwhelming a regular medical care in the world. We evaluated the clinical characteristics of patients with primary rhegmatogenous retinal detachment (RRD) during the state of emergency for COVID-19 pandemic in Japan. We also reviewed measures against the COVID-19 pandemic in our institute with a focus on RRD treatment. Retrospectively, patients who underwent initial RRD surgery during the state of emergency between April 7, 2020 and May 25, 2020 were included. For comparison, we recruited patients who underwent surgery for initial RRD during the same period in the last 2 years (2018 and 2019). Data related to the number of surgeries, age, gender, macular detachment, proliferative vitreoretinopathy (PVR), preoperative visual acuity, surgical techniques, the time between the onset and hospitalization and/or surgery of the 2020 cohort were analyzed and compared with those of the 2018 and 2019 cohorts. Furthermore, we reviewed measures taken against COVID-19 in our institute. The number of RRD patients during the state of emergency tended to be lower than that within the last 2 years. Relatively lesser female (vs. male) patients were observed in the 2020 cohort than in the last 2 years (P = 0.084). In contrast, among all cohorts, no significant differences were observed in the incidence of macula-off and PVR, preoperative visual acuity, and the time period between symptom onset and hospitalization and/or surgery. This is the first report to show the clinical patterns of RRD during COVID-19 pandemic in Japan. Despite the state of emergency for the COVID-19 pandemic, no delay in the patients initial visit to the hospital and surgery was observed. Further studies, including multicenter researches, are important for investigating the influence of COVID-19 on urgent ocular diseases.

The coronavirus disease 2019 pandemic has made deployment of an effective vaccine a global health priority. We evaluated the protective activity of a chimpanzee adenovirus-vectored vaccine encoding a prefusion stabilized spike protein (ChAd-SARS-CoV-2-S) in challenge studies with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and mice expressing the human angiotensin-converting enzyme 2 receptor. Intramuscular dosing of ChAd-SARS-CoV-2-S induces robust systemic humoral and cell-mediated immune responses and protects against lung infection, inflammation, and pathology but does not confer sterilizing immunity, as evidenced by detection of viral RNA and induction of anti-nucleoprotein antibodies after SARS-CoV-2 challenge. In contrast, a single intranasal dose of ChAd-SARS-CoV-2-S induces high levels of neutralizing antibodies, promotes systemic and mucosal immunoglobulin A (IgA) and T cell responses, and almost entirely prevents SARS-CoV-2 infection in both the upper and lower respiratory tracts. Intranasal administration of ChAd-SARS-CoV-2-S is a candidate for preventing SARS-CoV-2 infection and transmission and curtailing pandemic spread.

We use two cohorts from the National Longitudinal Surveys (NLSY79 and NLSY97), which are large, nationally representative samples of U.S. adults, to investigate consumption of sugar-sweetened beverages (SSB) by SES, using nine surveys fielded between 2008 and 2016. Previous studies used income and education to measure SES, the NLS enables us to include wealth as well. Previous studies also used cross-sectional data, whereas the NLS allows us to examine whether changes in income and wealth correlate with changes in SSB intake. The results indicate an inverse gradient in SSB consumption with respect to both income and wealth, controlling for education. However, we do not find evidence that changes in income and wealth correlate with changes in SSB intake. This finding suggests that SES influences the development of SSB consumption patterns, but changes in income and wealth generally do not alter them in adulthood.