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Article ; Online: Mental health challenges, treatment experiences, and care needs of post-secondary students

Elnaz Moghimi / Callum Stephenson / Gilmar Gutierrez / Jasleen Jagayat / Gina Layzell / Charmy Patel / Amber McCart / Cynthia Gibney / Caryn Langstaff / Oyedeji Ayonrinde / Sarosh Khalid-Khan / Roumen Milev / Erna Snelgrove-Clarke / Claudio Soares / Mohsen Omrani / Nazanin Alavi

BMC Public Health, Vol 23, Iss 1, Pp 1-

a cross-sectional mixed-methods study

2023 Volume 16

Abstract: Abstract Background Post-secondary students frequently experience high rates of mental health challenges. However, they present meagre rates of treatment-seeking behaviours. This elevated prevalence of mental health problems, particularly after the COVID- ...

Abstract	Abstract Background Post-secondary students frequently experience high rates of mental health challenges. However, they present meagre rates of treatment-seeking behaviours. This elevated prevalence of mental health problems, particularly after the COVID-19 pandemic, can lead to distress, poor academic performance, and lower job prospects following the completion of education. To address the needs of this population, it is important to understand students' perceptions of mental health and the barriers preventing or limiting their access to care. Methods A broad-scoping online survey was publicly distributed to post-secondary students, collecting demographic, sociocultural, economic, and educational information while assessing various components of mental health. Results In total, 448 students across post-secondary institutions in Ontario, Canada, responded to the survey. Over a third (n = 170; 38.6%) of respondents reported a formal mental health diagnosis. Depression and generalized anxiety disorder were the most commonly reported diagnoses. Most respondents felt that post-secondary students did not have good mental health (n = 253; 60.5%) and had inadequate coping strategies (n = 261; 62.4%). The most frequently reported barriers to care were financial (n = 214; 50.5%), long wait times (n = 202; 47.6%), insufficient resources (n = 165; 38.9%), time constraints (n = 148; 34.9%), stigma (n = 133; 31.4%), cultural barriers (n = 108; 25.5%), and past negative experiences with mental health care (n = 86; 20.3%). The majority of students felt their post-secondary institution needed to increase awareness (n = 231; 56.5%) and mental health resources (n = 306; 73.2%). Most viewed in-person therapy and online care with a therapist as more helpful than self-guided online care. However, there was uncertainty about the helpfulness and accessibility of different forms of treatment, including online interventions. The qualitative findings highlighted the need for personal strategies, mental health education and awareness, ...
Keywords	Mental health ; Student mental health ; Mental health treatment ; Psychotherapy ; Post-secondary students ; Mental health needs ; Public aspects of medicine ; RA1-1270
Subject code	360
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression

Benjamin Schwartzmann / Lena C. Quilty / Prabhjot Dhami / Rudolf Uher / Timothy A. Allen / Stefan Kloiber / Raymond W. Lam / Benicio N. Frey / Roumen Milev / Daniel J. Müller / Claudio N. Soares / Jane A. Foster / Susan Rotzinger / Sidney H. Kennedy / Faranak Farzan

Scientific Reports, Vol 13, Iss 1, Pp 1-

a Canadian biomarker integration network for depression study

2023 Volume 12

Abstract: Abstract Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which ... ...

Abstract	Abstract Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies. In a Canadian Biomarker Integration Network for Depression (CAN-BIND) study, forty-one adults with depression were recruited to undergo a 16-week course of CBT with thirty having resting-state electroencephalography (EEG) recorded at baseline and week 2 of therapy. Successful clinical response to CBT was defined as a 50% or greater reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to post-treatment completion. EEG relative power spectral measures were analyzed at baseline, week 2, and as early changes from baseline to week 2. At baseline, lower relative delta (0.5–4 Hz) power was observed in responders. This difference was predictive of successful clinical response to CBT. Furthermore, responders exhibited an early increase in relative delta power and a decrease in relative alpha (8–12 Hz) power compared to non-responders. These changes were also found to be good predictors of response to the therapy. These findings showed the potential utility of resting-state EEG in predicting CBT outcomes. They also further reinforce the promise of an EEG-based clinical decision-making tool to support treatment decisions for each patient.
Keywords	Medicine ; R ; Science ; Q
Subject code	150
Language	English
Publishing date	2023-05-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Association of intranasal esketamine, a novel ‘standard of care’ treatment and outcomes in the management of patients with treatment-resistant depression

Peter Giacobbe / Ayal Schaffer / Raymond W Lam / Roumen Milev / Gustavo Vazquez / Gilmar Gutierrez / Joshua Rosenblat / Jennifer Swainson / Ganapathy Karthikeyan / Nisha Ravindran / André Do / Emily Hawken

BMJ Open, Vol 12, Iss

protocol of a prospective cohort observational study of naturalistic clinical practice

2022 Volume 9

Abstract: Introduction Esketamine is the S-enantiomer of racemic ketamine and has been approved by the Food and Drug Administration for the management of treatment resistant depression, demonstrating effective and long-lasting benefits. The objective of this ... ...

Abstract	Introduction Esketamine is the S-enantiomer of racemic ketamine and has been approved by the Food and Drug Administration for the management of treatment resistant depression, demonstrating effective and long-lasting benefits. The objective of this observational study is to elucidate the association of intranasal (IN) esketamine with beneficial and negative outcomes in the management of treatment resistant major depressive disorder.Methods and analysis This is a multicentre prospective cohort observational study of naturalistic clinical practice. We expect to recruit 10 patients per research centre (6 centres, total 60 subjects). After approval to receive IN esketamine as part of their standard of care management of moderate to severe treatment resistant depression, patients will be invited to participate in this study. Association of esketamine treatment with outcomes in the management of depression will be assessed by measuring the severity of depression symptoms using the Montgomery-Åsberg Depression Rating Scale (MADRS), and tolerability by systematically tracking common side effects of ketamine treatment, dissociation using the simplified 6-Item Clinician Administered Dissociative Symptom Scale and potential for abuse using the Likeability and Craving Questionnaire (LCQ). Change in depressive symptoms (MADRS total scores) over time will be evaluated by within-subject repeated measures analysis of variance. We will calculate the relative risk associated with the beneficial (reduction in total scores for depression) outcomes, and the side effect and dropout rates (tolerability) of adding IN esketamine to patients’ current pharmacological treatments. Covariate analysis will assess the impact of site and demographic variables on treatment outcomes.Ethics and dissemination Approval to perform this study was obtained through the Health Sciences Research Ethics Board at Queen’s University. Findings will be shared among collaborators, through departmental meetings, presented on different academic venues and ...
Keywords	Medicine ; R
Subject code	310
Language	English
Publishing date	2022-09-01T00:00:00Z
Publisher	BMJ Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A detailed manual segmentation procedure for the hypothalamus for 3T T1-weighted MRI

Mohammad Ali / Jee Su Suh / Milita Ramonas / Stefanie Hassel / Stephen R. Arnott / Stephen C. Strother / Luciano Minuzzi / Roberto B. Sassi / Raymond W. Lam / Roumen Milev / Daniel J. Müller / Valerie H. Taylor / Sidney H. Kennedy / Benicio N. Frey

MethodsX, Vol 9, Iss , Pp 101864- (2022)

2022

Abstract: The hypothalamus is a small grey matter structure which plays a crucial role in many physiological functions. Some studies have found an association between hypothalamic volume and psychopathology, which stresses the need for a standardized method to ... ...

Abstract	The hypothalamus is a small grey matter structure which plays a crucial role in many physiological functions. Some studies have found an association between hypothalamic volume and psychopathology, which stresses the need for a standardized method to maximize segmentation accuracy. Here, we provide a detailed step-by-step method outlining the procedures to manually segment the hypothalamus using anatomical T1w images from 3T scanners, which many neuroimaging studies collect as a standard anatomical reference image. We compared volumes generated by manual segmentation and those generated by an automatic algorithm, observing a significant difference between automatically and manually segmented hypothalamus volumes on both sides (left: U = 222842, p-value < 2.2e-16; right: U = 218520, p- value < 2.2e-16). • Significant difference exists between existing automatic segmentation methods and the manual segmentation procedure. • We discuss potential drift effects, segmentation quality issues, and suggestions on how to mitigate them. • We demonstrate that the present manual segmentation procedure using standard T1-weighted MRI may be significantly more accurate than automatic segmentation outputs.
Keywords	Manual Segmentation of the Hypothalamus using standard 3T anatomical T1w images ; Science ; Q
Subject code	000
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Effects of electroconvulsive therapy and repetitive transcranial magnetic stimulation on serum brain-derived neurotrophic factor levels in patients with depression

RoumenMilev / LauraGedge / RuzicaJokic

Frontiers in Psychiatry, Vol

2012 Volume 3

Abstract: Objective: Brain-derived neurotrophic factor (BDNF) levels are decreased in individuals with depression and increase following antidepressant treatment. The objective of this study is to compare pre- and post-treatment serum BDNF levels in patients with ... ...

Abstract	Objective: Brain-derived neurotrophic factor (BDNF) levels are decreased in individuals with depression and increase following antidepressant treatment. The objective of this study is to compare pre- and post-treatment serum BDNF levels in patients with drug-resistant major depressive disorder (MDD) who received either electroconvulsive therapy (ECT) or repetitive transcranial magnetic stimulation (rTMS). It is hypothesized that non-pharmacological treatments also increase serum BDNF levels. Methods: This was a prospective, single-blind study comparing pre- and post-treatment serum BDNF levels of twenty-nine patients with drug-resistant MDD who received ECT or rTMS treatment. Serum BDNF levels were measured one week prior to and one week after treatment using the sandwich ELISA technique. Depression severity was measured one week before and one week after treatment using the Hamilton Depression Rating Scale. Two-sided normal distribution paired t-test analysis was used to compare pre- and post-treatment BDNF concentration and illness severity. Bivariate correlations using Pearson's coefficient assessed the relationship between post-treatment BDNF levels and post-treatment depression severity. Results: There was no significant difference in serum BDNF levels before and after ECT, although concentrations tended to increase from a baseline mean of 9.95 ng/ml to 12.29 ng/ml after treatment (p= 0.137). Treatment with rTMS did not significantly alter BDNF concentrations (p= 0.282). Depression severity significantly decreased following both ECT (p= 0.003) and rTMS (p< 0.001). Post-treatment BDNF concentration was not significantly correlated with post-treatment depression severity in patients who received either ECT (r= -0.133, p= 0.697) or rTMS (r= 0.374, p= 0.126). Conclusion: This study suggests that ECT and rTMS may not exert their clinical effects by altering serum BDNF levels. Serum BDNF concentration may not be a biomarker of ECT or rTMS treatment response.
Keywords	Psychiatry ; RC435-571 ; Neurology. Diseases of the nervous system ; RC346-429 ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571 ; Internal medicine ; RC31-1245 ; Medicine ; R
Language	English
Publishing date	2012-02-01T00:00:00Z
Publisher	Frontiers
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Transcranial Magnetic Stimulation of the Supplementary Motor Area in the Treatment of Obsessive-Compulsive Disorder

Emily R. Hawken / Dancho Dilkov / Emil Kaludiev / Selcuk Simek / Felicia Zhang / Roumen Milev

International Journal of Molecular Sciences, Vol 17, Iss 3, p

A Multi-Site Study

2016 Volume 420

Abstract: Recently, strategies beyond pharmacological and psychological treatments have been developed for the management of obsessive-compulsive disorder (OCD). Specifically, repetitive transcranial magnetic stimulation (rTMS) has been employed as an adjunctive ... ...

Abstract	Recently, strategies beyond pharmacological and psychological treatments have been developed for the management of obsessive-compulsive disorder (OCD). Specifically, repetitive transcranial magnetic stimulation (rTMS) has been employed as an adjunctive treatment in cases of treatment-refractory OCD. Here, we investigate six weeks of low frequency rTMS, applied bilaterally and simultaneously over the sensory motor area, in OCD patients in a randomized, double-blind placebo-controlled clinical trial. Twenty-two participants were randomly enrolled into the treatment (ACTIVE = 10) or placebo (SHAM = 12) groups. At each of seven visits (baseline; day 1 and weeks 2, 4, and 6 of treatment; and two and six weeks after treatment) the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) was administered. At the end of the six weeks of rTMS, patients in the ACTIVE group showed a clinically significant decrease in Y-BOCS scores compared to both the baseline and the SHAM group. This effect was maintained six weeks following the end of rTMS treatment. Therefore, in this sample, rTMS appeared to significantly improve the OCD symptoms of the treated patients beyond the treatment window. More studies need to be conducted to determine the generalizability of these findings and to define the duration of rTMS’ clinical effect on the Y-BOCS. Clinical Trial Registration Number (NCT) at www.clinicaltrials.gov: NCT00616486.
Keywords	Yale-Brown obsessive compulsive scale ; sensory motor area ; low-frequency rTMS ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
Subject code	616
Language	English
Publishing date	2016-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Accelerated brain aging in major depressive disorder and antidepressant treatment response

Pedro L. Ballester / Jee Su Suh / Nikita Nogovitsyn / Stefanie Hassel / Stephen C. Strother / Stephen R. Arnott / Luciano Minuzzi / Roberto B. Sassi / Raymond W. Lam / Roumen Milev / Daniel J. Müller / Valerie H. Taylor / Sidney H. Kennedy / Benicio N. Frey

NeuroImage: Clinical, Vol 32, Iss , Pp 102864- (2021)

A CAN-BIND report

2021

Abstract: Objectives: Previous studies suggest that major depressive disorder (MDD) may be associated with volumetric indications of accelerated brain aging. This study investigated neuroanatomical signs of accelerated aging in MDD and evaluated whether a brain ... ...

Abstract	Objectives: Previous studies suggest that major depressive disorder (MDD) may be associated with volumetric indications of accelerated brain aging. This study investigated neuroanatomical signs of accelerated aging in MDD and evaluated whether a brain age gap is associated with antidepressant response. Methods: Individuals in a major depressive episode received escitalopram treatment (10–20 mg/d) for 8 weeks. Depression severity was assessed at baseline and at weeks 8 and 16 using the Montgomery-Asberg Depression Rating Scale (MADRS). Response to treatment was characterized by a significant reduction in the MADRS (≥50%). Nonresponders received adjunctive aripiprazole treatment (2–10 mg/d) for a further 8 weeks. The brain-predicted age difference (brain-PAD) at baseline was determined using machine learning methods trained on 3377 healthy individuals from seven publicly available datasets. The model used features from all brain regions extracted from structural magnetic resonance imaging data. Results: Brain-PAD was significantly higher in older MDD participants compared to younger MDD participants [t(147.35) = -2.35, p < 0.03]. BMI was significantly associated with brain-PAD in the MDD group [r(155) = 0.19, p < 0.03]. Response to treatment was not significantly associated with brain-PAD. Conclusion: We found an elevated brain age gap in older individuals with MDD. Brain-PAD was not associated with overall treatment response to escitalopram monotherapy or escitalopram plus adjunctive aripiprazole.
Keywords	Treatment response ; Major depressive disorder ; Brain age ; Machine learning ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurology. Diseases of the nervous system ; RC346-429
Subject code	150 ; 616
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Replication of machine learning methods to predict treatment outcome with antidepressant medications in patients with major depressive disorder from STAR*D and CAN-BIND-1.

John-Jose Nunez / Teyden T Nguyen / Yihan Zhou / Bo Cao / Raymond T Ng / Jun Chen / Benicio N Frey / Roumen Milev / Daniel J Müller / Susan Rotzinger / Claudio N Soares / Rudolf Uher / Sidney H Kennedy / Raymond W Lam

PLoS ONE, Vol 16, Iss 6, p e

2021 Volume 0253023

Abstract: Objectives Antidepressants are first-line treatments for major depressive disorder (MDD), but 40-60% of patients will not respond, hence, predicting response would be a major clinical advance. Machine learning algorithms hold promise to predict treatment ...

Abstract	Objectives Antidepressants are first-line treatments for major depressive disorder (MDD), but 40-60% of patients will not respond, hence, predicting response would be a major clinical advance. Machine learning algorithms hold promise to predict treatment outcomes based on clinical symptoms and episode features. We sought to independently replicate recent machine learning methodology predicting antidepressant outcomes using the Sequenced Treatment Alternatives to Relieve Depression (STARD) dataset, and then externally validate these methods to train models using data from the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) dataset. Methods We replicated methodology from Nie et al (2018) using common algorithms based on linear regressions and decision trees to predict treatment-resistant depression (TRD, defined as failing to respond to 2 or more antidepressants) in the STARD dataset. We then trained and externally validated models using the clinical features found in both datasets to predict response (≥50% reduction on the Quick Inventory for Depressive Symptomatology, Self-Rated [QIDS-SR]) and remission (endpoint QIDS-SR score ≤5) in the CAN-BIND-1 dataset. We evaluated additional models to investigate how different outcomes and features may affect prediction performance. Results Our replicated models predicted TRD in the STARD dataset with slightly better balanced accuracy than Nie et al (70%-73% versus 64%-71%, respectively). Prediction performance on our external methodology validation on the CAN-BIND-1 dataset varied depending on outcome; performance was worse for response (best balanced accuracy 65%) compared to remission (77%). Using the smaller set of features found in both datasets generally improved prediction performance when evaluated on the STARD dataset. Conclusion We successfully replicated prior work predicting antidepressant treatment outcomes using machine learning methods and clinical data. We found similar prediction performance using these methods on an external ...
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: SNORD90 induces glutamatergic signaling following treatment with monoaminergic antidepressants

Rixing Lin / Aron Kos / Juan Pablo Lopez / Julien Dine / Laura M Fiori / Jennie Yang / Yair Ben-Efraim / Zahia Aouabed / Pascal Ibrahim / Haruka Mitsuhashi / Tak Pan Wong / El Cherif Ibrahim / Catherine Belzung / Pierre Blier / Faranak Farzan / Benicio N Frey / Raymond W Lam / Roumen Milev / Daniel J Muller /

Sagar V Parikh / Claudio Soares / Rudolf Uher / Corina Nagy / Naguib Mechawar / Jane A Foster / Sidney H Kennedy / Alon Chen / Gustavo Turecki

eLife, Vol

2023 Volume 12

Abstract: Pharmacotherapies for the treatment of major depressive disorder were serendipitously discovered almost seven decades ago. From this discovery, scientists pinpointed the monoaminergic system as the primary target associated with symptom alleviation. As a ...

Abstract	Pharmacotherapies for the treatment of major depressive disorder were serendipitously discovered almost seven decades ago. From this discovery, scientists pinpointed the monoaminergic system as the primary target associated with symptom alleviation. As a result, most antidepressants have been engineered to act on the monoaminergic system more selectively, primarily on serotonin, in an effort to increase treatment response and reduce unfavorable side effects. However, slow and inconsistent clinical responses continue to be observed with these available treatments. Recent findings point to the glutamatergic system as a target for rapid acting antidepressants. Investigating different cohorts of depressed individuals treated with serotonergic and other monoaminergic antidepressants, we found that the expression of a small nucleolar RNA, SNORD90, was elevated following treatment response. When we increased Snord90 levels in the mouse anterior cingulate cortex (ACC), a brain region regulating mood responses, we observed antidepressive-like behaviors. We identified neuregulin 3 (NRG3) as one of the targets of SNORD90, which we show is regulated through the accumulation of N6-methyladenosine modifications leading to YTHDF2-mediated RNA decay. We further demonstrate that a decrease in NRG3 expression resulted in increased glutamatergic release in the mouse ACC. These findings support a molecular link between monoaminergic antidepressant treatment and glutamatergic neurotransmission.
Keywords	major depressive disorder ; Antidepressant ; snoRNA ; m6A ; Medicine ; R ; Science ; Q ; Biology (General) ; QH301-705.5
Subject code	616
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	eLife Sciences Publications Ltd
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An investigation of cortical thickness and antidepressant response in major depressive disorder

Jee Su Suh / Luciano Minuzzi / Pradeep Reddy Raamana / Andrew Davis / Geoffrey B. Hall / Jacqueline Harris / Stefanie Hassel / Mojdeh Zamyadi / Stephen R. Arnott / Gésine L. Alders / Roberto B. Sassi / Roumen Milev / Raymond W. Lam / Glenda M. MacQueen / Stephen C. Strother / Sidney H. Kennedy / Benicio N. Frey

NeuroImage: Clinical, Vol 25, Iss , Pp - (2020)

A CAN-BIND study report

2020

Abstract: Major depressive disorder (MDD) is considered a highly heterogeneous clinical and neurobiological mental disorder. We employed a novel layered treatment design to investigate whether cortical thickness features at baseline differentiated treatment ... ...

Abstract	Major depressive disorder (MDD) is considered a highly heterogeneous clinical and neurobiological mental disorder. We employed a novel layered treatment design to investigate whether cortical thickness features at baseline differentiated treatment responders from non-responders after 8 and 16 weeks of a standardized sequential antidepressant treatment. Secondary analyses examined baseline differences between MDD and controls as a replication analysis and longitudinal changes in thickness after 8 weeks of escitalopram treatment. 181 MDD and 95 healthy comparison (HC) participants were studied. After 8 weeks of escitalopram treatment (10–20 mg/d, flexible dosage), responders (>50% decrease in Montgomery-Åsberg Depression Scale score) were continued on escitalopram; non-responders received adjunctive aripiprazole (2–10 mg/d, flexible dosage). MDD participants were classified into subgroups according to their response profiles at weeks 8 and 16. Baseline group differences in cortical thickness were analyzed with FreeSurfer between HC and MDD groups as well as between response groups. Two-stage longitudinal processing was used to investigate 8-week escitalopram treatment-related changes in cortical thickness. Compared to HC, the MDD group exhibited thinner cortex in the left rostral middle frontal cortex [MNI(X,Y,Z=−29,9,54.5,−7.7); CWP=0.0002]. No baseline differences in cortical thickness were observed between responders and non-responders based on week-8 or week-16 response profile. No changes in cortical thickness was observed after 8 weeks of escitalopram monotherapy. In a two-step 16-week sequential clinical trial we found that baseline cortical thickness does not appear to be associated to clinical response to pharmacotherapy at 8 or 16 weeks. Keywords: Major depressive disorder, Cortical thickness, Structural neuroimaging, Antidepressant response, Clinical trial
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurology. Diseases of the nervous system ; RC346-429
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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