Notes

Id involving Circular RNAs Related to Chemoresistance within Digestive tract Cancer.
Pancreatic neuroendocrine tumors (pNETs) in Von Hippel-Lindau (VHL) disease have a relatively good prognosis. However, a subset of pNETs metastasize and significantly contribute to VHL-related mortality. Evidence-based guidelines are needed for timely detection, management and intervention of these tumors. However, the value of several diagnostic tools is controversial, and evidence-based management strategies are lacking. This systematic review aims to update current literature on diagnostic and management strategies of pNETs in VHL and proposes evidence-based recommendations. The databases of PubMed/Medline, Embase and Web of Science were systematically searched to identify relevant studies. Studies were screened independently and cross-checked by two authors to assess eligibility for inclusion. Eighty-four articles were eligible for full text reading, and thirteen were critically appraised using the modified Quality Assessment of Diagnostic Accuracy Studies or modified Quality in Prognostic Studies tool. Six studies assessed the diagnostic value of imaging modalities, five focused on the optimal timing for surgical intervention, and one article studied the growth rate of pNETs. Quality of the available evidence was determined using the Grading of Recommendations, Assessment, Development and Evaluations tool. Studies recommended CT or MRI as the primary screening modalities for pNETs. For detection of metastases, 68Gallium-DOTATATE/TOC PET/CT is advised. For pNETs less then 2 cm a watch-and-wait approach is recommended, while for pNETs ≥2.5 cm surgical resection is advised. Due to limited data, no strong recommendations on surveillance could be proposed.N/A.
Alcohol use disorder (AUD) has been associated with diverse physical and mental morbidities. Among the main consequences of chronic and excessive alcohol use are cognitive and executive deficits. Some of these deficits may be reversed in specific cognitive and executive domains with behavioral approaches consisting of cognitive training. The advent of computer-based interventions may leverage these improvements, but randomized controlled trials (RCTs) of digital interactive-based interventions are still scarce.

The aim of this study is to explore whether a cognitive training approach using VR exercises based on activities of daily living is feasible for improving the cognitive function of patients with AUD undergoing residential treatment, as well as to estimate the effect size for this intervention to power future definitive RCTs.

This study consisted of a two-arm pilot RCT with a sample of 36 individuals recovering from AUD in a therapeutic community; experimental group participants received a therapiand cognitive flexibility of patients recovering from AUD.

ClinicalTrials.gov NCT04505345; https//clinicaltrials.gov/show/NCT04505345.
ClinicalTrials.gov NCT04505345; https//clinicaltrials.gov/show/NCT04505345.
Recent years have witnessed a constant increase in the number of people with chronic conditions requiring ongoing medical support in their everyday lives. However, global health systems are not adequately equipped for this extraordinarily time-consuming and cost-intensive development. Here, conversational agents (CAs) can offer easily scalable and ubiquitous support. Moreover, different aspects of CAs have not yet been sufficiently investigated to fully exploit their potential. One such trait is the interaction style between patients and CAs. In human-to-human settings, the interaction style is an imperative part of the interaction between patients and physicians. Patient-physician interaction is recognized as a critical success factor for patient satisfaction, treatment adherence, and subsequent treatment outcomes. However, so far, it remains effectively unknown how different interaction styles can be implemented into CA interactions and whether these styles are recognizable by users.

The objective of thapproach that is tailored for a medical context to induce a paternalistic and deliberative interaction style into a written interaction between a patient and a CA. We successfully tested and validated the procedure in a web-based experiment involving 88 participants. Future research should implement and test this approach among actual patients with chronic diseases and compare the results in different medical conditions. This approach can further be used as a starting point to develop dynamic CAs that adapt their interaction styles to their users.
Latino men in the United States report low physical activity (PA) levels and related health conditions (eg, diabetes and obesity). Engaging in regular PA can reduce the risk of chronic diseases and yield many health benefits; however, there is a paucity of interventions developed exclusively for Latino men.

To address the need for culturally relevant PA interventions, this study aims to develop and evaluate Hombres Saludables, a 6-month theory-based, tailored web- and text message-based PA intervention in Spanish for Latino men. This protocol paper describes the study design, intervention, and evaluation methods for Hombres Saludables.

Latino men aged 18-65 years were randomized to either the individually tailored PA internet intervention arm or the nutrition and wellness internet control arm. The PA intervention included 2 check-in phone calls; automated SMS text messages; a pedometer; a 6-month gym membership; access to a private Facebook group; and an interactive website with PA tracking, goal settinsis are ongoing.

We developed and tested protocols for a highly accessible, culturally and linguistically relevant, theory-driven PA intervention for Latino men. Hombres Saludables used an innovative, interactive, web- and text message-based intervention for improving PA among Latino men, an underserved population at risk of low PA and related chronic disease. If the intervention demonstrates feasibility, acceptability, and preliminary efficacy, we will refine and evaluate it in a larger randomized control trial.

Clinicaltrials.gov NCT03196570; https//clinicaltrials.gov/ct2/show/NCT03196570.

DERR1-10.2196/23690.
DERR1-10.2196/23690.
International asthma guidelines recommend the monitoring of peak expiratory flow (PEF) as part of asthma self-management in children and adolescents who poorly perceive airflow obstruction, those with a history of severe exacerbations, or those who have difficulty controlling asthma. Measured with a peak flow meter, PEF represents a person's maximum speed of expiration and helps individuals to follow their disease evolution and, ultimately, to prevent asthma exacerbations. However, patient adherence to regular peak flow meter use is poor, particularly in pediatric populations. To address this, we developed an interactive tablet-based game with a portable game controller that can transduce a signal from the user's breath to generate a PEF value.

The purpose of this study was to evaluate the concordance between PEF values obtained with the game controller and various measures derived from conventional pulmonary function tests (ie, spirometry) and to synthesize the participants' feedback.

In this cross-secnal spirometry. Future studies are necessary to evaluate the clinical impact this novel tool might have on asthma management and its potential use in an out-of-hospital setting.
The ability to objectively measure the severity of depression and anxiety disorders in a passive manner could have a profound impact on the way in which these disorders are diagnosed, assessed, and treated. Existing studies have demonstrated links between both depression and anxiety and the linguistic properties of words that people use to communicate. Smartphones offer the ability to passively and continuously detect spoken words to monitor and analyze the linguistic properties of speech produced by the speaker and other sources of ambient speech in their environment. The linguistic properties of automatically detected and recognized speech may be used to build objective severity measures of depression and anxiety.

The aim of this study was to determine if the linguistic properties of words passively detected from environmental audio recorded using a participant's smartphone can be used to find correlates of symptom severity of social anxiety disorder, generalized anxiety disorder, depression, and generaures revealed a strong relationship between the usage rates of death-related words and depressive symptoms (r=0.41, P<.001). There were also interesting correlations between rates of word usage in the categories of reward-related words with depression (r=-0.22, P=.04) and generalized anxiety (r=-0.29, P=.007), and vision-related words with social anxiety (r=0.31, P=.003).

In this study, words automatically recognized from environmental audio were shown to contain a number of potential associations with severity of depression and anxiety. This work suggests that sparsely sampled audio could provide relevant insight into individuals' mental health.
In this study, words automatically recognized from environmental audio were shown to contain a number of potential associations with severity of depression and anxiety. This work suggests that sparsely sampled audio could provide relevant insight into individuals' mental health.
Machine learning (ML) algorithms have been widely introduced to diabetes research including those for the identification of hypoglycemia.

The objective of this meta-analysis is to assess the current ability of ML algorithms to detect hypoglycemia (ie, alert to hypoglycemia coinciding with its symptoms) or predict hypoglycemia (ie, alert to hypoglycemia before its symptoms have occurred).

Electronic literature searches (from January 1, 1950, to September 14, 2020) were conducted using the Dialog platform that covers 96 databases of peer-reviewed literature. Included studies had to train the ML algorithm in order to build a model to detect or predict hypoglycemia and test its performance. The set of 2 × 2 data (ie, number of true positives, false positives, true negatives, and false negatives) was pooled with a hierarchical summary receiver operating characteristic model.

A total of 33 studies (14 studies for detecting hypoglycemia and 19 studies for predicting hypoglycemia) were eligible. Laduviglusib GSK-3 inhibitor For detectionell as the average ability of the ML algorithms. Continued research is required to develop more accurate ML algorithms than those that currently exist and to enhance the feasibility of applying ML in clinical settings.

PROSPERO International Prospective Register of Systematic Reviews CRD42020163682; http//www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020163682.
PROSPERO International Prospective Register of Systematic Reviews CRD42020163682; http//www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020163682.
The COVID-19 pandemic has led to a notable increase in psychological distress, globally. Oman is no exception to this, with several studies indicating high levels of anxiety and depression among the Omani public. There is a need for adaptive and effective interventions that aim to improve the elevated levels of psychological distress due to the COVID-19 pandemic.

This study aimed to comparatively assess the efficacy of therapist-guided online therapy with that of self-help, internet-based therapy focusing on COVID-19-induced symptoms of anxiety and depression among individuals living in Oman during the COVID-19 pandemic.

This was a 6-week-long pragmatic randomized controlled trial involving 60 participants who were recruited from a study sample surveyed for symptoms of anxiety or depression among the Omani public amid the COVID-19 pandemic. Participants in the intervention group were allocated to receive 1 online session per week for 6 weeks from certified psychotherapists in Oman; these sessions were conducted in Arabic or English.
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