Complex dynamics on the one-dimensional quantum droplets via time piecewise PINNs

The dynamics of one-dimensional quantum droplets and the landing applications of deep learning are recent research hotspots. In this work, we propose a novel time piecewise physics-informed neural networks (PINNs) to study complex dynamics on the one-dimensional quantum droplets by solving the corresponding amended Gross-Pitaevskii equation. The training effect of this network model in the long time domain is far better than that of the conventional PINNs, and each of its subnetworks is independent and highly adjustable. By using time piecewise PINNs with scarce training points, we not only study intrinsic modulation of single droplet and collision between two droplets, but also excite the breathers on droplet background. Intriguingly, we obtain an interference pattern from training result of collision between two droplets, which is a significant feature of the interplay of coherent matter waves. The numerical results showcase that different parameters may lead to completely different dynamic behaviors under the same initial condition in a nonlinear non-integrable system. Our results provide the significant guidance for intrinsic modulation of single droplet, droplet collision and breathers excitation via deep learning technology

Post-stroke cognitive impairment: exploring molecular mechanisms and omics biomarkers for early identification and intervention

Post-stroke cognitive impairment (PSCI) is a major stroke consequence that has a severe impact on patients’ quality of life and survival rate. For this reason, it is especially crucial to identify and intervene early in high-risk groups during the acute phase of stroke. Currently, there are no reliable and efficient techniques for the early diagnosis, appropriate evaluation, or prognostication of PSCI. Instead, plenty of biomarkers in stroke patients have progressively been linked to cognitive impairment in recent years. High-throughput omics techniques that generate large amounts of data and process it to a high quality have been used to screen and identify biomarkers of PSCI in order to investigate the molecular mechanisms of the disease. These techniques include metabolomics, which explores dynamic changes in the organism, gut microbiomics, which studies host–microbe interactions, genomics, which elucidates deeper disease mechanisms, transcriptomics and proteomics, which describe gene expression and regulation. We looked through electronic databases like PubMed, the Cochrane Library, Embase, Web of Science, and common databases for each omics to find biomarkers that might be connected to the pathophysiology of PSCI. As all, we found 34 studies: 14 in the field of metabolomics, 5 in the field of gut microbiomics, 5 in the field of genomics, 4 in the field of transcriptomics, and 7 in the field of proteomics. We discovered that neuroinflammation, oxidative stress, and atherosclerosis may be the primary causes of PSCI development, and that metabolomics may play a role in the molecular mechanisms of PSCI. In this study, we summarized the existing issues across omics technologies and discuss the latest discoveries of PSCI biomarkers in the context of omics, with the goal of investigating the molecular causes of post-stroke cognitive impairment. We also discuss the potential therapeutic utility of omics platforms for PSCI mechanisms, diagnosis, and intervention in order to promote the area’s advancement towards precision PSCI treatment

Comparative efficacy and acceptability of antidepressants, psychological interventions, and their combination for depressive disorder in children and adolescents:protocol for a network meta-analysis

Introduction Depressive disorder is common in children and adolescents, with important consequences and serious impairments in terms of personal and social functioning. While both pharmacological and psychological interventions have been shown to be effective, there is still uncertainty about the balance between these and what treatment strategy should be preferred in clinical practice. Therefore, we aim to compare and rank in a network meta-analysis (NMA) the commonly used psychological, pharmacological and combined interventions for depressive disorder in children and adolescents. Methods and analysis We will update the literature search of two previous NMAs for the identification of trials of antidepressant and psychotherapy alone for depressive disorder in children and adolescents. For identification of trials of combination interventions, seven databases (PubMed, EMBASE, CENTRAL (Cochrane Central Register of Controlled Trials), Web of Science, PsycINFO, CINAHL, LiLACS) will be searched from date of inception. We will also search ClinicalTrials.gov, the WHO International Clinical Trials Registry Platform and check relevant reports on the US Food and Drug Administration website for unpublished data. Building on our previous findings in the field, we will include any commonly prescribed oral antidepressants and any manualised or structured psychotherapies, as well as their combinations. Randomised controlled trials assessing any active intervention against active comparator or pill placebo/psychological controls in acute treatment for depressive disorder in children and adolescents will be included. The primary outcomes will be efficacy (mean change in depressive symptoms), and acceptability of treatment (dropout rate due to any cause). The secondary outcomes will be remission rate, tolerability of treatment (dropouts for adverse events), as well as suicide-related outcomes (suicidal behaviour or ideation). We will perform Bayesian NMAs for all relative outcome measures. Subgroup analyses and sensitivity analyses will be conducted to assess the robustness of the findings. Dissemination This NMA will provide the most up to date and clinically useful information about the comparative efficacy and acceptability of antidepressants, psychological intervention and their combination in the acute treatment of children and adolescents with depressive disorder. This is the newest NMA and therefore these results are very important in terms of evidence-based medicine. The results will be disseminated through peer-reviewed publication. Protocol registration PROSPERO CRD42015020841

Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression

The first brain-wide voxel-level resting state functional-connectivity neuroimaging analysis of depression is reported, with 421 patients with major depressive disorder and 488 controls. Resting state functional connectivity between different voxels reflects correlations of activity between those voxels and is a fundamental tool in helping to understand the brain regions with altered connectivity and function in depression. One major circuit with altered functional connectivity involved the medial orbitofrontal cortex BA 13, which is implicated in reward, and which had reduced functional connectivity in depression with memory systems in the parahippocampal gyrus and medial temporal lobe, especially involving the perirhinal cortex BA 36 and entorhinal cortex BA 28. The Hamilton Depression Rating Scale scores were correlated with weakened functional connectivity of the medial orbitofrontal cortex BA 13. Thus in depression there is decreased reward-related and memory system functional connectivity, and this is related to the depressed symptoms. The lateral orbitofrontal cortex BA 47/12, involved in non-reward and punishing events, did not have this reduced functional connectivity with memory systems. Second, the lateral orbitofrontal cortex BA 47/12 had increased functional connectivity with the precuneus, the angular gyrus, and the temporal visual cortex BA 21. This enhanced functional connectivity of the non-reward/punishment system (BA 47/12) with the precuneus (involved in the sense of self and agency), and the angular gyrus (involved in language) is thus related to the explicit affectively negative sense of the self, and of self-esteem, in depression. A comparison of the functional connectivity in 185 depressed patients not receiving medication and 182 patients receiving medication showed that the functional connectivity of the lateral orbitofrontal cortex BA 47/12 with these three brain areas was lower in the medicated than the unmedicated patients. This is consistent with the hypothesis that the increased functional connectivity of the lateral orbitofrontal cortex BA 47/12 is related to depression. Relating the changes in cortical connectivity to our understanding of the functions of different parts of the orbitofrontal cortex in emotion helps to provide new insight into the brain changes related to depression, which are considered in the Discussion

Antidepressants for depressive disorder in children and adolescents: a database of randomised controlled trials

Abstract Background In recent years, whether, when and how to use antidepressants to treat depressive disorder in children and adolescents has been hotly debated. Relevant evidence on this topic has increased rapidly. In this paper, we present the construction and content of a database of randomised controlled trials of antidepressants to treat depressive disorder in children and adolescents. This database can be freely accessed via our website and will be regularly updated. Description Major bibliographic databases (PubMed, the Cochrane Library, Web of Science, Embase, CINAHL, PsycINFO and LiLACS), international trial registers and regulatory agencies’ websites were systematically searched for published and unpublished studies up to April 30, 2017. We included randomised controlled trials in which the efficacy or tolerability of any oral antidepressant was compared with that of a control group or any other treatment. In total, 7377 citations from bibliographical databases and 3289 from international trial registers and regulatory agencies’ websites were identified. Of these, 53 trials were eligible for inclusion in the final database. Selected data were extracted from each study, including characteristics of the participants (the study population, setting, diagnostic criteria, type of depression, age, sex, and comorbidity), characteristics of the treatment conditions (the treatment conditions, general information, and detail of pharmacotherapy and psychotherapy) and study characteristics (the sponsor, country, number of sites, blinding method, sample size, treatment duration, depression scales, other scales, and primary outcome measure used, and side-effect monitoring method). Moreover, the risk of bias for each trial were assessed. Conclusion This database provides information on nearly all randomised controlled trials of antidepressants in children and adolescents. By using this database, researchers can improve research efficiency, avoid inadvertent errors and easily focus on the targeted subgroups in which they are interested. For authors of subsequent reviews, they could only use this database to insure that they have completed a comprehensive review, rather than relied solely on the data from this database. We expect this database could help to promote research on evidence-based practice in the treatment of depressive disorder in children and adolescents. The database could be freely accessed in our website: http://xiepengteam.cn/research/evidence-based-medicine

Comparative efficacy and tolerability of new-generation antidepressants for major depressive disorder in children and adolescents: protocol of an individual patient data meta-analysis.

INTRODUCTION Although previous conventional meta-analyses and network meta-analyses have provided some important findings about pharmacological treatments for children and adolescents with depressive disorders in the past decades, several questions still remain unsolved by the aggregate data from those meta-analyses. Individual participant data meta-analysis (IPD-MA) enables exploration of the impacts of individual characteristics on treatment effects, allowing matching of treatments to specific subgroups of patients. We will perform an IPD-MA to assess the efficacy and tolerability of new-generation antidepressants for major depressive disorder in children and adolescents. METHODS AND ANALYSIS We will systematically search for all double-blind randomised controlled trials (RCTs) that have compared any new-generation antidepressant with placebo for the acute treatment of major depressive disorder in children and adolescents, in the following databases: PubMed, EMBASE, the Cochrane Library, PsycINFO, Web of Science, CINAHL, LILACS and ProQuest Dissertations. We will contact all corresponding authors of included RCTs and ask for their cooperation in this project by providing individual participant data from the original trials. The primary outcomes will include efficacy, measured as the mean change of depression symptoms by Children's Depression Rating Scale Revised (CDRS-R), and tolerability, measured as the proportion of patients who withdrew from the trials early due to adverse effects. The secondary outcomes will include response rates, remission rates, deterioration rate, all-cause discontinuation, suicidal-related outcomes and global functioning outcome. Using the raw de-identified study data, we will use mixed-effects logistic and linear regression models to perform the IPD-MAs. The risk of bias of included studies will be assessed using the Cochrane risk of bias tool. We will also detect the publication bias and effects of non-participation of eligible studies. DISSEMINATION Ethical approval is not required given that informed consent has already been obtained from the patients by the trial investigators before the included trials were conducted. This study may have considerable implications for practice and help improve patient care. PROSPERO REGISTRATION NUMBER CRD42016051657