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Abstract Natural disaster management approach establishes stages of prevention, preparation, response, and recovery. With the Internet of Things (IoT), Bigdata, Business Intelligence, and other Information Communication Technologies, data can be gathered to support decisions in stages of the response to natural disaster events. In biological natural disasters, the ICTs can also support efforts to promote social distancing, public health, and economic monitoring to face the threads. São Paulo state used IoT in scenarios to face COVID‐19, such as monitoring vehicular interurban mobility, social distancing, and economic activity. Frameworks, strategies, data views, and use cases are presented to support the decision‐making process to face this biological natural disaster. The data‐driven approach supports several purposes, including the communication of social distancing indices, economic recovery, the progression of contagion, and deaths. It also played a pivotal role in fostering transparency initiatives for society and supporting the crisis committee by facilitating situational analyses, and this approach became standard practice for pandemic response. Studies and innovative visualisation perspectives have produced positive outcomes, guiding the decision‐making process through data analysis. Noteworthy use cases were interurban traffic fence monitoring; mapping of virus spreading; tracking the economic impact concerning recovery plans; and, evaluating the effectiveness of public policies.

The past decade witnessed substantial discoveries related to the psychosis spectrum. Many of these discoveries resulted from pursuits of objective and quantifiable biomarkers in tandem with the application of analytical tools such as machine learning. These approaches provided exciting new insights that significantly helped improve precision in diagnosis, prognosis, and treatment. This article provides an overview of how machine learning has been employed in recent biomarker discovery research in the psychosis spectrum, which includes schizophrenia, schizoaffective disorders, bipolar disorder with psychosis, first episode psychosis, and clinical high risk for psychosis. It highlights both human and animal model studies and explores a varying range of the most impactful biomarkers including cognition, neuroimaging, electrophysiology, and digital markers. We specifically highlight new applications and opportunities for machine learning to impact noninvasive symptom monitoring, prediction of future diagnosis and treatment outcomes, integration of new methods with traditional clinical research and practice, and personalized medicine approaches.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is linked to high mortality, primarily through an intense inflammatory response. Diacerein has emerged as a potential therapy for COVID-19 due to its potential impact in decreasing the inflammasome activation and coronavirus replication. This study aims to explore diacerein’s influence in inhibiting both viral replication and the inflammatory response after SARS-CoV-2 infection.MethodsHuman peripheral blood mononuclear cells (PBMCs) were obtained from healthy volunteers and infected in vitro with SARS-CoV-2. Additionally, we carried out a pilot randomized, double-blind, placebo-controlled study with 14 participants allocated to diacerein (n = 7) or placebo (n = 7) therapies every 12 h for 10 days. The primary endpoint was change in plasma markers of inflammasome activation (NLRP3, caspase-1, and gasdermin-D).ResultsIn vitro protocols have shown that rhein, diacerein’s primary metabolite, decreased IL-1β secretion caused by SARS-CoV-2 infection in human PBMCs (p < 0.05), and suppressed viral replication when administered either before or after the virus incubation (p < 0.05). This later effect was, at least partially, attributed to its inhibitory effect on 3-chymotrypsin-like protease (SARS-CoV-2 3CLpro) and papain-like protease in the SARS-CoV-2 (SARS-CoV-2 PLpro) virus and in the phosphorylation of proteins related cytoskeleton network (p < 0.05). Diacerein-treated COVID-19 patients presented a smaller area under the curve for NLRP3, caspase-1 and GSDM-D measured on days 2, 5, and 10 after hospitalization compared to those receiving a placebo (p < 0.05).ConclusionThe indicated mechanisms of action of diacerein/rhein can reduce viral replication and mitigate the inflammatory response related to SARS-CoV-2. These findings are preliminary and require confirmation in clinical trials.

Abstract Background There are no robust population-based Australian data on prevalence and attributed burden of migraine and medication-overuse headache (MOH) data. In this pilot cross-sectional study, we aimed to capture the participation rate, preferred response method, and acceptability of self-report questionnaires to inform the conduct of a future nationwide migraine/MOH epidemiological study. Methods We developed a self-report questionnaire, available in hard-copy and online, including modules from the Headache-Attributed Restriction, Disability, Social Handicap and Impaired Participation (HARDSHIP) questionnaire, the Eq. 5D (quality of life), and enquiry into treatment gaps. Study invitations were mailed to 20,000 randomly selected households across Australia’s two most populous states. The household member who most recently had a birthday and was aged ≥ 18 years was invited to participate, and could do so by returning a hard-copy questionnaire via reply-paid mail, or by entering responses directly into an online platform. Results The participation rate was 5.0% (N = 1,000). Participants’ median age was 60 years (IQR 44–71 years), and 64.7% (n = 647) were female. Significantly more responses were received from areas with relatively older populations and middle-level socioeconomic status. Hard copy was the more commonly chosen response method (n = 736). Females and younger respondents were significantly more likely to respond online than via hard-copy. Conclusions This pilot study indicates that alternative methodology is needed to achieve satisfactory engagement in a future nationwide migraine/MOH epidemiological study, for example through inclusion of migraine screening questions in well-resourced, interview-based national health surveys that are conducted regularly by government agencies. Meanwhile, additional future research directions include defining and addressing treatment gaps to improve migraine awareness, and minimise under-diagnosis and under-treatment.

Background: Many conditions we now call body-focused repetitive behaviors (BFRBs) have been subject to research for several decades, most notably trichotillomania and skin picking. However, the American Psychiatric Association did not combine these conditions into a single category, body-focused repetitive behavior disorders (BFRBDs), until the fifth edition of the DSM (2013). Several aspects of the disorder remain uncertain and controversial. For example, ongoing debate surrounds which specific conditions fall under this diagnostic category and how to best differentiate BFRBs from conditions such as nonsuicidal self-injury (NSSI). The current article presents results from a survey of experts' opinions on diagnostic criteria, with the goal of refining the diagnostic criteria. Method: We contacted experts on BFRB via various sources and invited them to complete an online survey on the phenomenology, classification, and differential diagnosis of BFRB. We also inquired about possible alternative syndrome labels (e.g., body-focused habit). Results: Data from the final sample of 50 experts demonstrates that most experts agree with the present classification of BFRB/BFRBD as an obsessive-compulsive and related disorder and recommend retaining the labels BFRB or BFRBD. The experts considered the following conditions BFRB, with an agreement of over 60%: trichotillomania, skin picking, dermatophagia, nail biting, and lip-cheek biting. Mixed results emerged for awake bruxism and thumb sucking in adults. Only a minority regarded night bruxism and knuckle cracking as BFRB. To differentiate BFRB from NSSI, the experts noted that the motive behind the urge (self-harm/injury versus release of tension) should be considered. Analyses of a sub-sample of experts with at least six years of clinical and/or research experience yielded results compatible with those of the entire sample. Discussion: The survey supports the usefulness of the BFRBD diagnostic entity. However, some criteria require further refinement. Future editions of the DSM should more explicitly delineate which conditions qualify as BFRB. Furthermore, it is important to give more attention to the primary motivation behind BFRB to distinguish it from NSSI and potentially from stereotypic movement behavior.

Abstract The COVID-19 pandemic was initiated by the rapid spread of a SARS-CoV-2 strain. Though mainly classified as a respiratory disease, SARS-CoV-2 infects multiple tissues throughout the human body, leading to a wide range of symptoms in patients. To better understand how SARS-CoV-2 affects the proteome from cells with different ontologies, this work generated an infectome atlas of 9 cell models, including cells from brain, blood, digestive system, and adipocyte tissue. Our data shows that SARS-CoV-2 infection mainly trigger dysregulations on proteins related to cellular structure and energy metabolism. Despite these pivotal processes, heterogeneity of infection was also observed, highlighting many proteins and pathways uniquely dysregulated in one cell type or ontological group. These data have been made searchable online via a tool that will permit future submissions of proteomic data ( https://reisdeoliveira.shinyapps.io/Infectome_App/ ) to enrich and expand this knowledgebase.

In this two-part article we discuss the difference between a continuous and a discrete approach to trap modeling in the simulation of 3-D NAND Flash memories with polysilicon channel. In Part I we focus on threshold voltage $({\mathrm { V}}_{\mathrm { T}})$ fluctuations induced by traps and show that lower values for the average and rms ${\mathrm { V}}_{\mathrm { T}}$ arise when the discrete nature of traps is accounted for. We explain such differences in terms of a stronger percolation that leads to a lower number of filled traps in the discrete-trap case, and investigate such differences as a function of cell parameters and temperature. Finally, we compare the two approaches showing that a continuous trap model cannot reproduce the correct dependences resulting from a discrete treatment.

In Part II of this article we discuss the impact of a discrete treatment of traps on 3-D NAND Flash random telegraph noise (RTN). A higher RTN results when discrete traps are taken into account, that can only be explained by a stronger influence of the discrete charged traps on the current conduction, leading to more percolation. The effects are then investigated as a function of the cell parameters, showing that a continuous model for traps cannot reproduce the correct dependence.

Dimethyl fumarate (DMF, Tecfidera) is an oral drug utilized to treat relapsing-remitting multiple sclerosis (MS). DMF treatment reduces disease activity in MS. Gastrointestinal discomfort is a common adverse effect of the treatment with DMF. This study aimed to investigate the effect of DMF administration in the gut draining lymph nodes cells of C57BL6/J female mice with experimental autoimmune encephalomyelitis (EAE), an animal model of MS. We have demonstrated that the treatment with DMF (7.5 mg/kg) significantly reduces the severity of EAE. This reduction of the severity is accompanied by the increase of both proinflammatory and anti-inflammatory mechanisms at the beginning of the treatment. As the treatment progressed, we observed an increasing number of regulatory Foxp3 negative CD4 T cells (Tr1), and anti-inflammatory cytokines such as IL-27, as well as the reduction of PGE2 level in the mesenteric lymph nodes of mice with EAE. We provide evidence that DMF induces a gradual anti-inflammatory response in the gut draining lymph nodes, which might contribute to the reduction of both intestinal discomfort and the inflammatory response of EAE. These findings indicate that the gut is the first microenvironment of action of DMF, which may contribute to its effects of reducing disease severity in MS patients.

BackgroundIndividuals with Tourette Syndrome and Persistent Tic Disorders (collectively TS) often experience premonitory urges-aversive physical sensations that precede tics and are temporarily relieved by tic expression. The relationship between tics and premonitory urges plays a key role in the neurobehavioral treatment model of TS, which underlies first-line treatments such as the Comprehensive Behavioral Intervention for Tics (CBIT). Despite the efficacy of CBIT and related behavioral therapies, less than 40% of adults with TS respond to these treatments. Further examination of the relationship between premonitory urges, tic severity, and tic impairment can provide new insights into therapeutic targets to optimize behavioral treatment outcomes. This study examined whether urge intolerance-difficulty tolerating premonitory urges-predicted tic severity and tic-related impairment among adults with TS.MethodsParticipants were 80 adults with TS. Assessments characterized premonitory urge, distress tolerance, tic severity, and tic impairment. We used structural equation modeling (SEM) to examine the construct of urge intolerance-comprised of premonitory urge ratings and distress tolerance ratings. We first evaluated a measurement model of urge intolerance through bifactor modeling, including tests of the incremental value of subfactors that reflect premonitory urge severity and distress tolerance within the model. We then evaluated a structural model where we predicted clinician-rated tic severity and tic impairment by the latent variable of urge intolerance established in our measurement model.ResultsAnalyses supported a bifactor measurement model of urge intolerance among adults with TS. Consistent with theoretical models, higher levels of urge intolerance predicted greater levels of clinician-rated tic severity and tic impairment.ConclusionThis investigation supports the construct of urge intolerance among adults with TS and distinguishes it from subcomponents of urge severity and distress tolerance. Given its predictive relationship with tic severity and tic impairment, urge intolerance represents a promising treatment target to improve therapeutic outcomes in adults with TS.

Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive-compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi-site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA-OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA.

Background: Acute kidney injury (AKI) after transcatheter aortic valve implantation (TAVI) is a frequent complication associated with adverse outcomes and mortality. Various scores have been developed to predict this complication in the coronary setting. However, none have ever been tested in a large TAVI population. This study aimed to evaluate the power of four different scores in predicting AKI after TAVI. Methods: Overall, 1535 consecutive TAVI patients from the observational multicentric “Magna Graecia” TAVI registry were included in the analysis. Of the study population, 235 (15.31%) developed AKI early. The Mehran, William Beaumont Hospital, CR4EATME3AD3, and ACEF scores were calculated retrospectively. Results: The patients who developed TAVI-related AKI had significantly higher absolute values of all risk scores than those who did not. The receiver-operating characteristic analysis also showed a significant correlation between these four scores and AKI, but without a significant difference among all of them (p value = 0.176). Nevertheless, based on their area under the curve values (≤0.604 for all), none had adequate diagnostic accuracy in predicting TAVI-related AKI. Importantly, multivariate analysis identified myocardial revascularization close to the TAVI procedure and implantation of self-expanding prostheses, as well as atrial fibrillation, low-osmolar contrast media administration, corrected contrast medium volume, and any transfusion (p value

In this paper, we present a detailed experimental investigation of high-temperature data retention in 3D floating-gate NAND Flash memory arrays. Data reveal that charge detrapping from the cell tunnel oxide and depassivation of traps in the string polysilicon channel are the physical mechanisms resulting in the most relevant long-term reliability issues for the memory array. On one hand, the two mechanisms give rise to threshold-voltage $(\mathbf {V_{T}})$ instabilities with similar activation energy and comparable magnitude on fresh devices. On the other hand, polysilicon trap depassivation displays a negligible strengthening with cycling and a more marked dependence on the cell $\mathbf {V_{T}}$ level during data retention with respect to charge detrapping. Results must be carefully considered in the reliability assessment of all state-of-the-art and future 3D NAND Flash technology nodes.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the agent of a major global outbreak of respiratory tract disease known as Coronavirus Disease 2019 (COVID-19). SARS-CoV-2 infects mainly lungs and may cause several immune-related complications, such as lymphocytopenia and cytokine storm, which are associated with the severity of the disease and predict mortality. The mechanism by which SARS-CoV-2 infection may result in immune system dysfunction is still not fully understood. Here, we show that SARS-CoV-2 infects human CD4+ T helper cells, but not CD8+ T cells, and is present in blood and bronchoalveolar lavage T helper cells of severe COVID-19 patients. We demonstrated that SARS-CoV-2 spike glycoprotein (S) directly binds to the CD4 molecule, which in turn mediates the entry of SARS- CoV-2 in T helper cells. This leads to impaired CD4 T cell function and may cause cell death. SARS-CoV-2-infected T helper cells express higher levels of IL-10, which is associated with viral persistence and disease severity. Thus, CD4-mediated SARS-CoV-2 infection of T helper cells may contribute to a poor immune response in COVID-19 patients.

Visceral adiposity is a risk factor for severe COVID-19, and infection of adipose tissue by SARS-CoV-2 has been reported. Here the authors confirm that human adipose tissue is a possible site for SARS-CoV-2 infection, but the degree of adipose tissue infection and the way adipocytes respond to the virus depend on the adipose tissue depot and the viral strain.

This paper examines national gaps and trends in geography achievement in eighth grade from 1994 to 2018. Statistical models comprising student- and school-level variables were developed to predict achievement using data provided by the National Assessment of Educational Progress (NAEP). Although there were statistically significant relationships between achievement and school-level attributes such as geographic region and school sector, the magnitudes of the coefficients were relatively minor and inconsistent over time compared with student-level characteristics such as gender, race, ethnicity, and parental education. The results inform current policy directions and efforts to foster educational equity in K-12 geography.

Background: While standard clinical assessments provide great value for people with multiple sclerosis (PwMS), they are limited in their ability to characterize patient perspectives and individual-level symptom heterogeneity. Objectives: To identify PwMS subgroups based on patient-reported outcomes (PROs) of physical, cognitive, and emotional symptoms. We also sought to connect PRO-based subgroups with demographic variables, functional impairment, hypertension and smoking status, traditional qualitative multiple sclerosis (MS) symptom groupings, and neuroperformance measurements. Methods: Using a cross-sectional design, we applied latent profile analysis (LPA) to a large database of PROs; analytic sample N = 6619). Results: We identified nine distinct MS subtypes based on PRO patterns. The subtypes were primarily categorized into low, moderate, and high mobility impairment clusters. Approximately 70% of participants were classified in a low mobility impairment group, 10% in a moderate mobility impairment group, and 20% in a high mobility impairment group. Within these subgroups, several unexpected patterns were observed, such as high mobility impairment clusters reporting low non-mobility impairment. Conclusions: The present study highlights an opportunity to advance precision medicine approaches in MS. Combining PROs with data-driven methodology allows for a cost-effective and personalized characterization of symptom presentations. that can inform clinical practice and future research designs. [ABSTRACT FROM AUTHOR]

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is linked to high mortality, primarily through an intense inflammatory response. Diacerein has emerged as a potential therapy for COVID-19 due to its potential impact in decreasing the inflammasome activation and coronavirus replication. This study aims to explore diacerein's influence in inhibiting both viral replication and the inflammatory response after SARS-CoV-2 infection. Methods: Human peripheral blood mononuclear cells (PBMCs) were obtained from healthy volunteers and infected in vitro with SARS-CoV-2. Additionally, we carried out a pilot randomized, double-blind, placebo-controlled study with 14 participants allocated to diacerein (n = 7) or placebo (n = 7) therapies every 12 h for 10 days. The primary endpoint was change in plasma markers of inflammasome activation (NLRP3, caspase-1, and gasdermin-D). Results: In vitro protocols have shown that rhein, diacerein's primary metabolite, decreased IL-1ß secretion caused by SARS-CoV-2 infection in human PBMCs (p < 0.05), and suppressed viral replication when administered either before or after the virus incubation (p < 0.05). This later effect was, at least partially, attributed to its inhibitory effect on 3-chymotrypsin-like protease (SARS-CoV-2 3CLpro) and papain-like protease in the SARS-CoV-2 (SARS-CoV-2 PLpro) virus and in the phosphorylation of proteins related cytoskeleton network (p < 0.05). Diacereintreated COVID-19 patients presented a smaller area under the curve for NLRP3, caspase-1 and GSDM-D measured on days 2, 5, and 10 after hospitalization compared to those receiving a placebo (p < 0.05). Conclusion: The indicated mechanisms of action of diacerein/rhein can reduce viral replication and mitigate the inflammatory response related to SARS-CoV-2. These findings are preliminary and require confirmation in clinical trials. [ABSTRACT FROM AUTHOR]

Background: Loss of mobility is common in persons with multiple sclerosis (PwMS), but little is known about this impairment from the patient's perspective. Objective: The aim is to model longitudinal variation in a mobility patient-reported outcome (PRO) and compare trajectories to those observed for Timed 25-Foot Walk (T25FW) in a retrospective cohort. Methods: Latent-class growth analysis was applied to 47,508 measures of Performance Scales© Mobility PRO (PS-Mobility) over ~4 years for 8524 PwMS. For 7347 PwMS, there were 41,988 T25FW measures during this period. Repeated measures correlation and concordance of trajectory assignment were evaluated. Results: At the group level, PS-Mobility and T25FW linearly worsened and repeated-measures correlation was moderate. Eight latent classes with varying shapes that worsened described PS-Mobility variation, compared to six latent classes for T25FW that differed by intercept. The agreement between PS-Mobility and T25FW cluster assignment was modest. A higher proportion of individuals who were Black/African American, older, Medicaid beneficiaries, living in deprived neighborhoods, had longer disease duration, had progressive disease, and ever smokers were assigned to more impaired clusters. Discussion: Cross-sectionally, PS-Mobility and T25FW were highly correlated, but longitudinally correlation was modest to moderate, underscoring the importance of considering both objective and subjective perspectives in evaluating mobility changes in PwMS. [ABSTRACT FROM AUTHOR]

Abstract Obsessive-compulsive disorder (OCD) is highly heterogeneous. Although perseverative negative thinking (PT) is a feature of OCD, little is known about its neural mechanisms or relationship to clinical heterogeneity in the disorder. In a sample of 85 OCD patients, we investigated the relationships between self-reported PT, clinical symptom subtypes, and resting-state functional connectivity measures of local and global connectivity. Results indicated that PT scores were highly variable within the OCD sample, with greater PT relating to higher severity of the “unacceptable thoughts” symptom dimension. PT was positively related to local connectivity in subgenual anterior cingulate cortex (ACC), pregenual ACC, and the temporal poles—areas that are part of, or closely linked to, the default mode network (DMN)—and negatively related to local connectivity in sensorimotor cortex. While the majority of patients showed higher local connectivity strengths in sensorimotor compared to DMN regions, OCD patients with higher PT scores had less of an imbalance between sensorimotor and DMN connectivity than those with lower PT scores, with healthy controls exhibiting an intermediate pattern. Clinically, this imbalance was related to both the “unacceptable thoughts” and “symmetry/not-just-right-experiences” symptom dimensions, but in opposite directions. These effects remained significant after accounting for variance related to psychiatric comorbidity and medication use in the OCD sample, and no significant relationships were found between PT and global connectivity. These data indicate that PT is related to symptom and neural variability in OCD. Future work may wish to target this circuity when developing personalized interventions for patients with these symptoms.