***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Diagnosis of psychiatric disorders based on brain imaging data is highly desirable in clinical applications . However , a common problem in applying machine learning algorithms is that the number of imaging data dimensions often greatly exceeds the number of available training sample s. Furthermore , interpretability of the learned classifier with respect to brain function and anatomy is an important , but non-trivial issue . We propose the use of logistic regression with a least absolute shrinkage and selection operator ( LASSO ) to capture the most critical input features . In particular , we consider application of group LASSO to select brain areas relevant to diagnosis . An additional advantage of LASSO is its probabilistic output , which allows evaluation of diagnosis certainty . To verify our approach , we obtained semantic and phonological verbal fluency fMRI data from 31 depression patients and 31 control subjects , and compared the performances of group LASSO ( gLASSO ) , and sparse group LASSO ( sgLASSO ) to those of st and ard LASSO ( sLASSO ) , Support Vector Machine ( SVM ) , and R and om Forest . Over 90 % classification accuracy was achieved with gLASSO , sgLASSO , as well as SVM ; however , in contrast to SVM , LASSO approaches allow for identification of the most discriminative weights and estimation of prediction reliability . Semantic task data revealed contributions to the classification from left precuneus , left pre central gyrus , left inferior frontal cortex ( pars triangularis ) , and left cerebellum ( c rus1 ) . Weights for the phonological task indicated contributions from left inferior frontal operculum , left post central gyrus , left insula , left middle frontal cortex , bilateral middle temporal cortices , bilateral precuneus , left inferior frontal cortex ( pars triangularis ) , and left pre central gyrus . The distribution of normalized odds ratios further showed , that predictions with absolute odds ratios higher than 0.2 could be regarded as certain Major depressive disorder ( MDD ) is the most common neuropsychiatric disease and despite extensive research , its genetic substrate is still not sufficiently understood . The common polymorphism rs6295 of the serotonin-1A receptor gene ( HTR1A ) is affecting the transcriptional regulation of the 5-HT1A receptor and has been closely linked to MDD . Here , we used positron emission tomography ( PET ) exploiting advances in data mining and statistics by using machine learning in 62 healthy subjects and 19 patients with MDD , which were scanned with PET using the radiolig and [carbonyl-11C]WAY-100635 . All the subjects were genotyped for rs6295 and genotype was grouped in GG vs C allele carriers . Mixed model was applied in a ROI-based ( region of interest ) approach . ROI binding potential ( BPND ) was divided by dorsal raphe BPND as a specific measure to highlight rs6295 effects ( BPDiv ) . Mixed model produced an interaction effect of ROI and genotype in the patients ’ group but no effects in healthy controls . Differences of BPDiv was demonstrated in seven ROIs ; parahippocampus , hippocampus , fusiform gyrus , gyrus rectus , supplementary motor area , inferior frontal occipital gyrus and lingual gyrus . For classification of genotype , ‘ R and omForest ’ and Support Vector Machines were used , however , no model with sufficient predictive capability could be computed . Our results are in line with pre clinical data , mouse model knockout studies as well as previous clinical analyses , demonstrating the two-pronged effect of the G allele on 5-HT1A BPND for , we believe , the first time . Future endeavors should address epigenetic effects and allosteric heteroreceptor complexes . Replication in larger sample s of MDD patients is necessary to substantiate our findings OBJECTIVE The study aims were 1 ) to describe the proportions of individuals who met criteria for melancholic , atypical , and anxious depressive subtypes , as well as subtype combinations , in a large sample of depressed out patients , and 2 ) to compare subtype profiles on remission and change in depressive symptoms after acute treatment with one of three antidepressant medications . METHOD Participants 18 - 65 years of age ( N=1,008 ) who met criteria for major depressive disorder were r and omly assigned to 8 weeks of treatment with escitalopram , sertraline , or extended-release venlafaxine . Participants were classified by subtype . Those who met criteria for no subtype or multiple subtypes were classified separately , result ing in eight mutually exclusive groups . A mixed-effects model using the intent-to-treat sample compared the groups ' symptom score trajectories , and logistic regression compared likelihood of remission ( defined as a score ≤5 on the 16-item Quick Inventory of Depressive Symptomatology-Self-Report ) . RESULTS Thirty-nine percent of participants exhibited a pure-form subtype , 36 % met criteria for more than one subtype , and 25 % did not meet criteria for any subtype . All subtype groups exhibited a similar significant trajectory of symptom reduction across the trial . Likelihood of remission did not differ significantly between subtype groups , and depression subtype was not a moderator of treatment effect . CONCLUSIONS There was substantial overlap of the three depressive subtypes , and individuals in all subtype groups responded similarly to the three antidepressants . The consistency of these findings with those of the Sequenced Treatment Alternatives to Relieve Depression trial suggests that subtypes may be of minimal value in antidepressant selection UNLABELLED Remission rates for Major Depressive Disorder ( MDD ) are low and unpredictable for any given antidepressant . No biological or clinical marker has demonstrated sufficient ability to match individuals to efficacious treatment . Biosignatures developed from the systematic exploration of multiple biological markers , which optimize treatment selection for individuals ( moderators ) and provide early indication of ultimate treatment response ( mediators ) are needed . The rationale and design of a multi-site , placebo-controlled r and omized clinical trial of sertraline examining moderators and mediators of treatment response is described . The target sample is 300 participants with early onset ( ≤30 years ) recurrent MDD . Non-responders to an 8-week trial are switched double blind to either bupropion ( for sertraline non-responders ) or sertraline ( for placebo non-responders ) for an additional 8 weeks . Clinical moderators include anxious depression , early trauma , gender , melancholic and atypical depression , anger attacks , Axis II disorder , hypersomnia/fatigue , and chronicity of depression . Biological moderator and mediators include cerebral cortical thickness , task-based fMRI ( reward and emotion conflict ) , resting connectivity , diffusion tensor imaging ( DTI ) , arterial spin labeling ( ASL ) , electroencephalograpy ( EEG ) , cortical evoked potentials , and behavioral/cognitive tasks evaluated at baseline and week 1 , except DTI , assessed only at baseline . The study is design ed to st and ardize assessment of biomarkers across multiple sites as well as institute replicable quality control methods , and to use advanced data analytic methods to integrate these markers . A Differential Depression Treatment Response Index ( DTRI ) will be developed . The data , including biological sample s ( DNA , RNA , and plasma collected before and during treatment ) , will become available in a public scientific repository . CLINICAL TRIAL REGISTRATION Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression ( EMBARC ) . Identifier : NCT01407094 . URL : http:// clinical trials.gov/show/NCT01407094 Background : Magnetic resonance imaging studies have provided evidence of structural modifications in cortical-limbic regions in major depressive disorder . To date , however , few studies have tracked structural changes in patients during treatment . This prospect i ve , longitudinal imaging study investigated associations between brain structure and clinical responsiveness in a sample of patients with treatment-resistant major depressive disorder during an approximate 1-year follow-up period . Methods : FreeSurfer software was used to extract volume or cortical thickness values from 6 regions of interest ( hippocampus , rostral middle frontal gyrus , orbitofrontal cortex , rostral and caudal anterior cingulate cortices , and inferior temporal gyrus ) in patients ( n = 26 ) and matched healthy controls ( n = 28 ) . Regions of interest were selected based on previous evidence of potential associations between morphometric characteristics in these regions and treatment response or remission . Analyses were conducted to compare volume and cortical thickness in patients and controls at baseline imaging , determine whether patients ’ brain structure at treatment initiation was associated with response over follow-up , and compare longitudinal changes in volume and cortical thickness in patients who achieved sustained 6-month remission ( Montgomery-Åsberg Depression Rating Scale Score ≤12 ) with nonremitters . Results : Patients and controls showed no structural differences at baseline . Among patients , thicker right caudal anterior cingulate cortex at baseline was associated with greater symptom improvement over follow-up . Remitters and nonremitters showed subtle changes in volume and thickness over time in opposing directions , with increased hippocampal volume and cortical thickness in the rostral middle frontal gyrus , orbitofrontal cortex , and inferior temporal gyrus in remitters , and decreased volume or thickness in these regions in nonremitters . Conclusions : The results suggest that longitudinal structural trajectories may differ in major depressive disorder patients according to their clinical response to treatment Antidepressant medications are commonly used to treat depression , but only about 30 % of patients reach remission with any single first-step antidepressant . If the first-step treatment fails , response and remission rates at subsequent steps are even more limited . The literature on biomarkers for treatment response is largely based on secondary analyses of studies design ed to answer primary questions of efficacy , rather than on a planned systematic evaluation of biomarkers for treatment decision . The lack of evidence -based knowledge to guide treatment decisions for patients with depression has lead to the recognition that specially design ed studies with the primary objective being to discover biosignatures for optimizing treatment decisions are necessary . Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care ( EMBARC ) is one such discovery study . Stage 1 of EMBARC is a r and omized placebo controlled clinical trial of 8 week duration . A wide array of patient characteristics is collected at baseline , including assessment s of brain structure , function and connectivity along with electrophysiological , biological , behavioral and clinical features . This paper reports on the data analytic strategy for discovering biosignatures for treatment response based on Stage 1 of EMBARC CONTEXT AND OBJECTIVE Major depressive disorder ( MDD ) is a common psychiatric condition , mostly treated with antidepressant drugs , which are limited due to refractoriness and adverse effects . We describe the study rationale and design of ELECT-TDCS ( Escitalopram versus Electric Current Therapy for Treating Depression Clinical Study ) , which is investigating a non-pharmacological treatment known as transcranial direct current stimulation ( tDCS ) . DESIGN AND SETTING Phase-III , r and omized , non-inferiority , triple-arm , placebo-controlled study , ongoing in São Paulo , Brazil . METHODS ELECT-TDCS compares the efficacy of active tDCS/placebo pill , sham tDCS/escitalopram 20 mg/day and sham tDCS/placebo pill , for ten weeks , r and omizing 240 patients in a 3:3:2 ratio , respectively . Our primary aim is to show that tDCS is not inferior to escitalopram  with a non-inferiority margin of at least 50 % of the escitalopram effect , in relation to placebo . As secondary aims , we investigate several biomarkers such as genetic polymorphisms , neurotrophin serum markers , motor cortical excitability , heart rate variability and neuroimaging . RESULTS Proving that tDCS is similarly effective to antidepressants would have a tremendous impact on clinical psychiatry , since tDCS is virtually devoid of adverse effects . Its ease of use , portability and low price are further compelling characteristics for its use in primary and secondary healthcare . Multimodal investigation of biomarkers will also contribute towards underst and ing the antidepressant mechanisms of action of tDCS . CONCLUSION Our results have the potential to introduce a novel technique to the therapeutic arsenal of treatments for depression Electroconvulsive therapy ( ECT ) is a treatment of choice for severe and therapy resistant forms of major depressive episodes ( MDE ) . Temporal brain volume alterations in MDE have been described for more than two decades . In our prospect i ve study we aim ed to investigate individual pre-post ECT treatment whole brain gray matter ( GM ) volume changes ( quantified with voxel-based morphometry ) in a sample of 18 patients with MDE . In addition , we studied the effect of ECT on voxel-based cortical thickness in cortical brain regions . The most prominent longitudinal GM increases ( significant at a whole brain corrected level ) occurred in temporal lobe regions . Within specific region of interest analyses we detected highly significant increases of GM in the hippocampus and the amygdala and to a lesser extent in the habenula ( left p=0.003 , right p=0.032 ) . A voxel based cortical thickness analysis revealed an increase in cortical temporal regions ( basically temporal pole and insula ) further corroborating our cortical voxel-based morphometry results . Neither GM decreases or white matter increases nor correlations of GM changes with basic psychopathological parameters were detected . We corroborate earlier findings of hippocampal and amygdala GM volume increase following an acute ECT series in patients with MDE . Temporal GM volume increase was significant on a whole brain level and further corroborated by a cortical thickness analysis . Our data widely exclude white matter loss as an indirect cause of GM growth . Our data add further evidence to the hypothesis that E 
    Output:
    
These results support other imaging modalities that report disruptions in various frontal and temporal areas in MDD and identify additional areas in all major cerebral lobes likely to be significant when parsing for biomarkers of treatment or relapse .
Recent neuroimaging studies found differences in cortical thickness between groups .