Importance of Balanced Attention Toward Coronavirus Disease 2019 and Neglected Tropical Diseases.

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has been spreading since 2019, causing a worldwide pandemic. Amid the COVID-19 pandemic, tuberculosis, AIDS, and malaria have adversely affected the quality of life of patients and killed millions of people. In addition, COVID-19 continues to impede the delivery of health services, including those for the control of neglected tropical diseases (NTDs). Furthermore, NTDs have been reported as possible co-pathogens among patients infected with COVID-19. However, studies regarding parasitic co-infection among these patients have been limited. This review aimed to explore and describe the cases and reports of parasitic infections in the backdrop of COVID-19 to provide comprehensive knowledge regarding this aspect. We reviewed seven cases of patients who had parasitic co-infection and tested positive for COVID-19, and summarized the literature on the importance of controlling parasitic diseases. In addition, we identified recommendations for the control of parasitic diseases under possible difficulties, such as declining funding for parasitic diseases in 2020. This review highlights the growing burden of NTDs under COVID-19 that may be caused by the deficiency of healthcare infrastructure and human resources as the main reasons. Clinicians should remain vigilant for possible co-infections with parasites in COVID-19 patients, while policymakers are urged to reinforce a balanced and long-term health strategy that addresses both NTDs and COVID-19.

Online Contingent Attention Training (OCAT): transfer effects to cognitive biases, rumination, and anxiety symptoms from two proof-of-principle studies.

The aim of the present research was to develop and test the efficacy of a novel online contingent attention training (i.e., OCAT) to modify attention and interpretation biases, improve emotion regulation, and reduce emotional symptom levels in the face of major stressors. Two proof-of-principle studies were carried out. In study 1, 64 undergraduates who were about to start a major stressful period (i.e., final exams) were randomized to undergo 10 days of active OCAT or a sham-control training. Emotion regulation (habitual use of rumination and reappraisal) and symptom levels (depression and anxiety) were assessed before and after the intervention. In study 2, the same 2 × 2 mixed design was used with 58 individuals from the general population undergoing a major stressful situation (the lockdown period at the beginning of the COVID-19 pandemic in 2020). In both studies, the OCAT group showed significant improvements on attention towards negative information and interpretation biases in comparison to the sham-control group. Additionally, changes in cognitive biases transferred to reductions of participants' use of rumination and anxiety symptom levels. These results show preliminary evidence regarding the efficacy of the OCAT to target attention and interpretation biases as well as to improve emotion regulation processes and to buffer against the effects of major stressors.

AIGAN: Attention-encoding Integrated Generative Adversarial Network for the reconstruction of low-dose CT and low-dose PET images.

X-ray computed tomography (CT) and positron emission tomography (PET) are two of the most commonly used medical imaging technologies for the evaluation of many diseases. Full-dose imaging for CT and PET ensures the image quality but usually raises concerns about the potential health risks of radiation exposure. The contradiction between reducing the radiation exposure and remaining diagnostic performance can be addressed effectively by reconstructing the low-dose CT (L-CT) and low-dose PET (L-PET) images to the same high-quality ones as full-dose (F-CT and F-PET). In this paper, we propose an Attention-encoding Integrated Generative Adversarial Network (AIGAN) to achieve efficient and universal full-dose reconstruction for L-CT and L-PET images. AIGAN consists of three modules: the cascade generator, the dual-scale discriminator and the multi-scale spatial fusion module (MSFM). A sequence of consecutive L-CT (L-PET) slices is first fed into the cascade generator that integrates with a generation-encoding-generation pipeline. The generator plays the zero-sum game with the dual-scale discriminator for two stages: the coarse and fine stages. In both stages, the generator generates the estimated F-CT (F-PET) images as like the original F-CT (F-PET) images as possible. After the fine stage, the estimated fine full-dose images are then fed into the MSFM, which fully explores the inter- and intra-slice structural information, to output the final generated full-dose images. Experimental results show that the proposed AIGAN achieves the state-of-the-art performances on commonly used metrics and satisfies the reconstruction needs for clinical standards.

Investigation of the Effect of Students' Nodding on Their Arousal Levels in On-Demand Lectures.

Due to COVID-19, various lecture styles are being explored. On-demand lectures are attracting increasing attention due to advantages such as being able to watch without restrictions due to location and time. In contrast, on-demand lectures have disadvantages, such as no interaction with the lecturer, so the quality of on-demand lectures should be improved. Our previous study showed that when participants nod without showing their faces in a real-time remote lecture, their heart rate state changes to arousal and nodding can increase arousal. In this paper, we hypothesize that nodding during on-demand lectures increases participants' arousal levels, and we investigate the relationship between natural and forced nodding and the level of arousal based on heart rate information. Students taking on-demand lectures rarely nod naturally, so we used entrainment to encourage nodding by showing a video of another participant nodding, and by forcing the participants to nod when the other participant nodded in the video. The results showed that only participants who nodded spontaneously changed the value of pNN50, an index of the arousal level, which reflected a state of high arousal after one minute. Thus, participants' nodding in on-demand lectures can increase their arousal levels; however, the nodding must be spontaneous, not forced.

Social Distancing and Shopping Behaviour: The Role of Anxiety, Attention, and Awareness on Safety Preferences while Queuing during the COVID-19 Pandemic.

The COVID-19 pandemic increased global anxiety, and many people shopped less frequently. This study quantifies customer preferences in where to shop while following social distancing regulations, specifically focusing on customers' anxiety. Collecting data online from 450 UK participants, we measured trait anxiety, COVID-19 anxiety, queue awareness, and queue safety preferences. Confirmatory factor analyses were used to develop novel queue awareness and queue safety preference variables from new items. Path analyses tested the hypothesised relationships between them. Queue awareness and COVID-19 anxiety were positive predictors of queue safety preference, with queue awareness partially mediating the effect of COVID-19 anxiety. These results suggest that customers' preferences for shopping at one business and not another may depend on safe queueing and waiting conditions, especially in those more anxious about COVID-19 transmission. Interventions that target highly aware customers are suggested. Limitations are acknowledged and areas for future development are outlined.

Procrastination and Stress: A Conceptual Review of Why Context Matters.

Research over the past two decades has continued to highlight the robust associations between procrastination and stress across multiple populations and contexts. Despite this burgeoning evidence base and theory linking procrastination to higher levels of stress, as well as the reverse, the role of context in this potentially dynamic association has received relatively little attention. In this conceptual review I argue that from a mood regulation perspective of procrastination, stressful contexts necessarily increase risk for procrastination because they deplete coping resources and lower the threshold for tolerating negative emotions. Drawing on insights from coping and emotion regulation theory, the new stress context vulnerability model of procrastination proposes that the risk for procrastination increases in stressful contexts primarily because procrastination is a low-resource means of avoiding aversive and difficult task-related emotions. The new model is then applied to evidence on the primary and secondary sources of stress during the COVID-19 pandemic and how they may have increased vulnerability for procrastination. After discussing potential applications of the new model for understanding how and why risk for procrastination may increase in other stressful contexts, approaches that might mitigate vulnerability for procrastination in high-stress contexts are discussed. Overall, this new stress context vulnerability model underscores the need for taking a more compassionate view of the antecedents and factors that may increase the risk for procrastination.

Head turning is an effective cue for gaze following: Evidence from newly sighted individuals, school children and adults.

In referential communication, gaze is often interpreted as a social cue that facilitates comprehension and enables word learning. Here we investigated the degree to which head turning facilitates gaze following. We presented participants with static pictures of a man looking at a target object in a first and third block of trials (pre- and post-intervention), while they saw short videos of the same man turning towards the target in the second block of trials (intervention). In Experiment 1, newly sighted individuals (treated for congenital cataracts; N = 8) benefited from the motion cues, both when comparing their initial performance with static gaze cues to their performance with dynamic head turning, and their performance with static cues before and after the videos. In Experiment 2, neurotypical school children (ages 5-10 years; N = 90) and adults (N = 30) also revealed improved performance with motion cues, although most participants had started to follow the static gaze cues before they saw the videos. Our results confirm that head turning is an effective social cue when interpreting new words, offering new insights for a pathways approach to development.

Emotional, hyperactivity and inattention problems in adolescents with immunocompromising chronic diseases during the COVID-19 pandemic.

OBJECTIVE: To assess factors associated with emotional changes and Hyperactivity/Inattention (HI) motivated by COVID-19 quarantine in adolescents with immunocompromising diseases. METHODS: A cross-sectional study included 343 adolescents with immunocompromising diseases and 108 healthy adolescents. Online questionnaires were answered including socio-demographic data and self-rated healthcare routine during COVID-19 quarantine and validated surveys: Strengths and Difficulties Questionnaire (SDQ), Pittsburgh Sleep Quality Index (PSQI), Pediatric Quality of Life Inventory 4.0 (PedsQL4.0). RESULTS: The frequencies of abnormal emotional SDQ scores from adolescents with chronic diseases were similar to those of healthy subjects (110/343 [32%] vs. 38/108 [35%], p = 0.548), as well as abnormal hyperactivity/inattention SDQ scores (79/343 [23%] vs. 29/108 [27%], p = 0.417). Logistic regression analysis of independent variables associated with abnormal emotional scores from adolescents with chronic diseases showed: female sex (Odds Ratio [OR = 3.76]; 95% Confidence Interval (95% CI) 2.00‒7.05; p < 0.001), poor sleep quality (OR = 2.05; 95% CI 1.08‒3.88; p = 0.028) and intrafamilial violence during pandemic (OR = 2.17; 95% CI 1.12‒4.19; p = 0.021) as independently associated with abnormal emotional scores, whereas total PedsQL score was inversely associated with abnormal emotional scores (OR = 0.95; 95% CI 0.93‒0.96; p < 0.0001). Logistic regression analysis associated with abnormal HI scores from patients evidenced that total PedsQL score (OR = 0.97; 95% CI 0.95‒0.99; p = 0.010], changes in medical appointments during the pandemic (OR = 0.39; 95% CI 0.19-0.79; p = 0.021), and reliable COVID-19 information (OR = 0.35; 95% CI 0.16‒0.77; p = 0.026) remained inversely associated with abnormal HI scores. CONCLUSION: The present study showed emotional and HI disturbances in adolescents with chronic immunosuppressive diseases during the COVID-19 pandemic. It reinforces the need to promptly implement a longitudinal program to protect the mental health of adolescents with and without chronic illnesses during future pandemics.

Attention and memory after COVID-19 as measured by neuropsychological tests: Systematic review and meta-analysis.

COVID-19 is associated with a range of sequelae, including cognitive dysfunctions as long-standing symptoms. Considering that the number of people infected worldwide keeps growing, it is important to understand specific domains of impairments to further organize appropriate rehabilitation procedures. In this study we conducted a meta-analysis to investigate specific cognitive functions impacted by COVID-19. A literature search was conducted in Web of Science, Scopus, PubMed, Academic Search Premier, Health Source: Nursing/Academic Edition, and preprint databases (OSF and PsyArXiv via OSF Preprints, medRxiv, bioRxiv, Research Square). We included the studies that compared cognitive functioning in COVID-19 reconvalescents and healthy controls, and used at least one validated neuropsychological test. Our findings show that short-term memory in the verbal domain, and possibly, visual short-term memory and attention, are at risk in COVID-19 reconvalescents. The impact of COVID-19 on cognitive functioning has yet to be studied in detail. In the future more controlled studies with validated computerized tests might help deepen our understanding of the issue. PSYCINFO CLASSIFICATION: 3360 Health Psychology & Medicine.

Lapses in the Person Radar: ADHD Symptoms Predict Difficulty in Interpersonal Distancing.

OBJECTIVE: Across contexts, from social cognition to the COVID-19 pandemic response, individual variation in the regulation of interpersonal distance has typically been viewed as a voluntary choice. Here we examine the frequency of unintentional lapses in interpersonal distancing, and their relationship with childhood ADHD symptoms. METHOD: We administered a novel measure of difficulty with interpersonal distancing across three undergraduate samples (total N = 1,225), in addition to measures of recalled childhood ADHD symptoms, mind wandering, and hyperfocus. RESULTS: Almost all (>97%) participants reported unintentional lapses in maintaining interpersonal distance, with 16% experiencing such lapses frequently. Thirty percent of the variance in these reports was accounted for by attentional traits: Inattentive and hyperactive/impulsive ADHD symptoms jointly predicted difficulties with interpersonal distancing, with the former relationship fully mediated by hyperfocus and spontaneous mind wandering. CONCLUSION: Both inattentive and hyperactive/impulsive ADHD symptoms confer vulnerability to frequent unintentional lapses in interpersonal distancing.

An Attention towards the Prophylactic and Therapeutic Options of Phytochemicals for SARS-CoV-2: A Molecular Insight.

The novel pathogenic virus was discovered in Wuhan, China (December 2019), and quickly spread throughout the world. Further analysis revealed that the pathogenic strain of virus was corona but it was distinct from other coronavirus strains, and thus it was renamed 2019-nCoV or SARS-CoV-2. This coronavirus shares many characteristics with other coronaviruses, including SARS-CoV and MERS-CoV. The clinical manifestations raised in the form of a cytokine storm trigger a complicated spectrum of pathophysiological changes that include cardiovascular, kidney, and liver problems. The lack of an effective treatment strategy has imposed a health and socio-economic burden. Even though the mortality rate of patients with this disease is lower, since it is judged to be the most contagious, it is considered more lethal. Globally, the researchers are continuously engaged to develop and identify possible preventive and therapeutic regimens for the management of disease. Notably, to combat SARS-CoV-2, various vaccine types have been developed and are currently being tested in clinical trials; these have also been used as a health emergency during a pandemic. Despite this, many old antiviral and other drugs (such as chloroquine/hydroxychloroquine, corticosteroids, and so on) are still used in various countries as emergency medicine. Plant-based products have been reported to be safe as alternative options for several infectious and non-infectious diseases, as many of them showed chemopreventive and chemotherapeutic effects in the case of tuberculosis, cancer, malaria, diabetes, cardiac problems, and others. Therefore, plant-derived products may play crucial roles in improving health for a variety of ailments by providing a variety of effective cures. Due to current therapeutic repurposing efforts against this newly discovered virus, we attempted to outline many plant-based compounds in this review to aid in the fight against SARS-CoV-2.

Development of criteria for cognitive dysfunction in post-COVID syndrome: the IC-CoDi-COVID approach.

BACKGROUND: We aimed to develop objective criteria for cognitive dysfunction associated with the post-COVID syndrome. METHODS: Four hundred and four patients with post-COVID syndrome from two centers were evaluated with comprehensive neuropsychological batteries. The International Classification for Cognitive Disorders in Epilepsy (IC-CoDE) framework was adapted and implemented. A healthy control group of 145 participants and a complementary data-driven approach based on unsupervised machine-learning clustering algorithms were also used to evaluate the optimal classification and cutoff points. RESULTS: According to the developed criteria, 41.2% and 17.3% of the sample were classified as having at least one cognitive domain impaired using -1 and -1.5 standard deviations as cutoff points. Attention/processing speed was the most frequently impaired domain. There were no differences in base rates of cognitive impairment between the two centers. Clustering analysis revealed two clusters, although with an important overlap (silhouette index 0.18-0.19). Cognitive impairment was associated with younger age and lower education levels, but not hospitalization. CONCLUSIONS: We propose a harmonization of the criteria to define and classify cognitive impairment in the post-COVID syndrome. These criteria may be extrapolated to other neuropsychological batteries and settings, contributing to the diagnosis of cognitive deficits after COVID-19 and facilitating multicenter studies to guide biomarker investigation and therapies.

[Cognitive consequences of COVID-19]. / Kognitivnaya disfunktsiya pri COVID-19.

An analysis of foreign publications illustrates changes in ideas about the etiology, pathogenesis, target organs, leading pathophysiological syndromes and clinical manifestations of nervous system damage in COVID-19 over 2.5 years of the pandemic. It has been demonstrated that, according to modern concepts, COVID-19 is considered as a pathology with a tendency to multiple organ damage, where the symptoms of damage to the nervous system not only determine the severity of the course of the disease, but also indirectly affect the development of severe somatic manifestations, such as distress syndrome. Particular attention is paid to the analysis of publications summarizing the available data on the frequency of cognitive deficit in the acute period of COVID-19 and in the post-COVID period, risk factors, recovery prospects. Putative mechanisms underlying cognitive deficit in COVID-19 are considered. Despite a significant number of observations and publications, many mechanisms of nervous system damage in COVID-19 and the selectivity of the cognitive deficit pattern remain unexplored. In modern publications, there is no information and long term forecast of the cognitive state dynamics, which is an important argument in favor of the need to continue research.

Task-unrelated thought increases after consumption of COVID-19 and general news.

Task-unrelated thoughts (TUTs) are frequent distractions from our everyday tasks, which can reduce productivity and safety during task performance. This necessitates the examination of factors that modulate TUT occurrence in daily life. One factor that has previously been implicated as a source of TUT is personally salient concerns. External factors such as news media serve as cues for these concerns, potentially increasing TUT occurrence. However, this has not been thoroughly examined in everyday life settings. We thus utilized Ecological Momentary Assessment to survey participants throughout the day for ten days, on their TUTs and news consumption in two separate studies. Study 1 focused on the impact of news related to the Coronavirus Disease (COVID-19) pandemic, as a common and global concern. We found that TUT occurrence was significantly predicted by COVID-19 news consumption, such that TUT occurrence increased with COVID-19 news consumption. To extend these findings, we implemented Study 2 using similar methods, but focusing on the consumption of news media in general. TUT occurrence was predicted by general news consumption, with an increase in reports of TUT following consumption of news media in general. We thus extended the association found between TUT and COVID-19-related news in Study 1, to any news topic in Study 2. We speculate that the increase in TUTs was due to heightened salience of current concerns, cued by the news. These findings highlight the importance of considering when we choose to consume news media and the value of examining contextual factors when studying TUTs in daily life.

Crosslink-Net: Double-Branch Encoder Network via Fusing Vertical and Horizontal Convolutions for Medical Image Segmentation.

Accurate image segmentation plays a crucial role in medical image analysis, yet it faces great challenges caused by various shapes, diverse sizes, and blurry boundaries. To address these difficulties, square kernel-based encoder-decoder architectures have been proposed and widely used, but their performance remains unsatisfactory. To further address these challenges, we present a novel double-branch encoder architecture. Our architecture is inspired by two observations. (1) Since the discrimination of the features learned via square convolutional kernels needs to be further improved, we propose utilizing nonsquare vertical and horizontal convolutional kernels in a double-branch encoder so that the features learned by both branches can be expected to complement each other. (2) Considering that spatial attention can help models to better focus on the target region in a large-sized image, we develop an attention loss to further emphasize the segmentation of small-sized targets. With the above two schemes, we develop a novel double-branch encoder-based segmentation framework for medical image segmentation, namely, Crosslink-Net, and validate its effectiveness on five datasets with experiments. The code is released at https://github.com/Qianyu1226/Crosslink-Net.

Immunogenicity and immune-persistence of the CoronaVac or Covilo inactivated COVID-19 Vaccine: a 6-month population-based cohort study.

Background: Owing to the coronavirus disease 2019 (COVID-19) pandemic and the emergency use of different types of COVID-19 vaccines, there is an urgent need to consider the effectiveness and persistence of different COVID-19 vaccines. Methods: We investigated the immunogenicity of CoronaVac and Covilo, two inactivated vaccines against COVID-19 that each contain inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The levels of neutralizing antibodies to live SARS-CoV-2 and the inhibition rates of neutralizing antibodies to pseudovirus, as well as the immunoglobulin (Ig)G and IgM responses towards the spike (S) and nucleocapsid (N) protein of SARS-CoV-2 at 180 days after two-dose vaccination were detected. Results: The CoronaVac and Covilo vaccines induced similar antibody responses. Regarding neutralizing antibodies to live SARS-CoV-2, 77.9% of the CoronaVac vaccine recipients and 78.3% of the Covilo vaccine recipients (aged 18-59 years) seroconverted by 28 days after the second vaccine dose. Regarding SARS-CoV-2-specific antibodies, 97.1% of the CoronaVac vaccine recipients and 95.7% of the Covilo vaccine recipients seroconverted by 28 days after the second vaccine dose. The inhibition rates of neutralizing antibody against a pseudovirus of the SARS-CoV-2 Delta variant were significantly lower compared with those against a pseudovirus of wildtype SARS-CoV-2. Associated with participant characteristics and antibody levels, persons in the older age group and with basic disease, especially a chronic respiratory disease, tended to have lower anti-SARS-CoV-2 antibody seroconversion rates. Conclusion: Antibodies that were elicited by these two inactivated COVID-19 vaccines appeared to wane following their peak after the second vaccine dose, but they persisted at detectable levels through 6 months after the second vaccine dose, and the effectiveness of these antibodies against the Delta variant of SARS-CoV-2 was lower than their effectiveness against wildtype SARS-CoV-2, which suggests that attention must be paid to the protective effectiveness, and its persistence, of COVID-19 vaccines on SARS-CoV-2 variants.

Dynamic Classification of Imageless Bioelectrical Impedance Tomography Features with Attention-Driven Spatial Transformer Neural Network.

Point-of-Care monitoring devices have proven to be pivotal in the timely screening and intervention of critical care patients. The urgent demands for their deployment in the COVID-19 pandemic era has translated into the escalation of rapid, reliable, and low-cost monitoring systems research and development. Electrical Impedance Tomography (EIT) is a highly promising modality in providing deep tissue imaging that aids in patient bedside diagnosis and treatment. Motivated to bring forth an accurate and intelligent EIT screening system, we bypassed the complexity and challenges typically associated with its image reconstruction and feature identification processes by solely focusing on the raw data output to extract the embedded knowledge. We developed a novel machine learning architecture based on an attention-driven spatial transformer neural network to specifically accommodate for the patterns and dependencies within EIT raw data. Through elaborate precision-mapped phantom experiments, we validated the reproduction and recognition of features with systemically controlled changes. We demonstrated over 95% accuracy via state-of-the-art machine learning models, and an enhanced performance using our adapted transformer pipeline with shorter training time and greater computational efficiency. Our approach of using imageless EIT driven by a novel attention-focused feature learning algorithm is highly promising in revolutionizing conventional EIT operations and augmenting its practical usage in medicine and beyond.