The CONSORT-EHEALTH checklist is intended for authors of randomized trials evaluating web-based and Internet-based applications/interventions, including mobile interventions, electronic games (incl multiplayer games), social media, certain telehealth applications, and other interactive and/or networked electronic applications. Some of the items (e.g. all subitems under item 5 -description of the intervention) may also be applicable for other study designs.The goal of the CONSORT EHEALTH checklist and guideline is to be a) a guide for reporting for authors of RCTs, b) to form a basis for appraisal of an ehealth trial (in terms of validity) CONSORT-EHEALTH items/subitems are MANDATORY reporting items for studies published in the Journal of Medical Internet Research and other journals / scientific societies endorsing the checklist.Items numbered 1., 2., 3., 4a., 4b etc are original CONSORT or CONSORT-NPT (nonpharmacologic treatment) items. Items with Roman numerals (i., ii, iii, iv etc.) are CONSORT-EHEALTH extensions/clarifications.As the CONSORT-EHEALTH checklist is still considered in a formative stage, we would ask that you also RATE ON A SCALE OF 1-5 how important/useful you feel each item is FOR THE PURPOSE OF THE CHECKLIST and reporting guideline (optional).Mandatory reporting items are marked with a red *.

Background The gut microbiome and microbiome-gut-brain (MGB) axis have been receiving increasing attention for their role in the regulation of mental behavior and possible biological basis of psychiatric disorders. With the advance of next-generation sequencing technology, characterization of the gut microbiota in schizophrenia (SZ) patients can provide rich clues for the diagnosis and prevention of SZ. Methods In this study, we compared the differences in the fecal microbiota between 82 SZ patients and 80 demographically matched normal controls (NCs) by 16S rRNA sequencing and analyzed the correlations between altered gut microbiota and symptom severity. Results The alpha diversity showed no significant differences between the NC and SZ groups, but the beta diversity revealed significant community-level separation in microbiome composition between the two groups (pseudo-F =3.337, p < 0.001, uncorrected). At the phylum level, relatively more Actinobacteria and less Firmicutes (p < 0.05, FDR corrected) were found in the SZ group. At the genus level, the relative abundances of Collinsella, Lactobacillus, Succinivibrio, Mogibacterium, Corynebacterium, undefined Ruminococcus and undefined Eubacterium were significantly increased, whereas the abundances of Adlercreutzia, Anaerostipes, Ruminococcus and Faecalibacterium were decreased in the SZ group compared to the NC group (p < 0.05, FDR corrected). We performed PICRUSt analysis and found that several metabolic pathways differed significantly between the two groups, including the Polyketide sugar unit biosynthesis, Valine, Leucine and Isoleucine biosynthesis, Pantothenate and CoA biosynthesis, C5-Branched dibasic acid metabolism, Phenylpropanoid biosynthesis, Ascorbate and aldarate metabolism, Nucleotide metabolism and Propanoate metabolism pathways (p < 0.05, FDR corrected). Among the SZ group, the abundance of Succinivibrio was positively correlated with the total Positive and Negative Syndrome Scale (PANSS) scores (r = 0.24, p < 0.05, uncorrected) as well as the general PANSS scores (r = 0.22, p < 0.05, uncorrected); Corynebacterium was negatively related to the negative scores of PANSS (r = 0.22, p < 0.05, uncorrected). Conclusions Our findings provided evidence of altered gut microbial composition in SZ group. In addition, we found that Succinvibrio and Corynebacterium were associated with the severity of symptoms for the first time, which may provide some new biomarkers for the diagnosis of SZ.

Background: Anxiety has been a common mental state during the epidemic of Coronavirus Disease 2019 (COVID-19) and is usually closely related to somatization. However, no study on somatization in anxiety and its relationship with insomnia has been conducted. Therefore, this study aimed to identify the prevalence of anxiety, somatization and insomnia and explore the relationships between different psychological states in the general population during the COVID-19 outbreak. Methods: A total of 1,172 respondents were recruited from 125 cities in mainland China by an online questionnaire survey. All subjects were evaluated with the 7-item Generalized Anxiety Disorder (GAD-7) scale, the somatization subscale of the Symptom Checklist 90-Revised (SCL-90-R), and the 7-item Insomnia Severity Index (ISI). Results: The percentages of anxiety, somatization, and insomnia were 33.02%, 7.59%, and 24.66%, respectively. The prevalence of somatization was 19.38% in participants with anxiety. Compared to the anxiety without somatization group, the anxiety with somatization group had a significantly higher percentage of patients with a history of physical disease and insomnia, as well as higher GAD-7 scores and SCL-90 somatization subscores (all p < 0.001). The SCL-90 somatization subscores were positively correlated with age, history of physical disease, GAD-7 scores, and ISI scores (all p < 0.001). Furthermore, multivariate logistic regression showed that GAD-7 score, ISI score, and age were risk factors for somatization in the anxious population.

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The overlapping clinical features of Alzheimer's disease (AD) and Dementia with Lewy bodies (DLB) make differentiation difficult in the clinical environment. Evaluating the CSF levels of biomarkers in AD and DLB patients could facilitate clinical diagnosis. CSF Visinin-like protein-1 (VILIP-1), a calciummediated neuronal injury biomarker, has been described as a novel biomarker for AD. The aim of this study was to investigate the diagnostic utility of CSF VILIP-1 and VILIP-1/ Ab 1-42 ratio to distinguish AD from DLB. Levels of CSF VILIP-1, t-tau, p-tau 181P , Ab 1-42 , and a-synuclein were measured in 61 AD patients, 32 DLB patients, and 40 normal controls using commercial ELISA kits. The results showed that the CSF VILIP-1 level had significantly increased in AD patients compared with both normal controls and DLB patients. The CSF VILIP-1 and VILIP-1/Ab 1-42 levels had enough diagnostic accuracy to allow the detection and differential diagnosis of AD. Additionally, CSF VILIP-1 levels were positively correlated with t-tau and p-tau 181P within each group and with a-synuclein in the AD and control groups. We conclude that CSF VILIP-1 could be a diagnostic marker for AD, differentiating it from DLB. The analysis of biomarkers, representing different neuropathologies, is an important approach reflecting the heterogeneous features of AD and DLB.