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Protein-protein interaction in depression

2018· other· en· W6958679285 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2018
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthMajor depressive disorderDepression (economics)MoodAnxietyDistressSadnessDepressed mood

Abstract

fetched live from OpenAlex

Depression is a mental health disorder that affects an individual's mood, where they consistently and persistently feel sadness and lack of interest, thus referred to as a mood disorder. Officially called Major Depressive Disorder (MDD), it can embody the individual suffering from MDD to the point where it affects how you think, feel, and ultimately behave. MDD affects the daily lives of the individuals suffering from it, taking away their interests, and at times eliciting suicidal thoughts and behaviours. Symptoms of MDD include sadness, emptiness, and hopelessness, which also come with a loss of interest in activities that were once joyful, and sometimes a loss of interest in any and all activities. Sleep is also negatively affected, contributing to the individuals lack of energy and loss of appetite and weight loss. However, MDD can also be associated with food cravings and weight gain. Individuals suffering from MDD commonly develop anxiety disorders as well, and experience suicidal thoughts and behaviours, as well as other medical conditions that come with a compromised immune system. Depression is sometimes difficult to diagnose because many other medical conditions embody some depressive symptoms, and thus must be ruled out first. According to the Center for Addiction and Mental Health (CAMH), 14% of high-school students indicate high levels of psychological distress that points to depression, and 40% of Canadians can be depressed but have never sought medical help. Mood disorders, namely depression, continue to be the most common type of mental disorder experienced by Canadians. Mental health is a leading contributor to health crises in Canada and the rest of the world, however it continues to be neglected in modern healthcare settings. While it is increasingly acknowledged and researched in recent times, there is still much work to be done on the social and biological aspects of depression and other mental health disorders. Although there tends to be a debate between the biological and social contributors, healthcare officials agree that both are significant contributors. Thus, it is important to consider their interaction, and screen for potential biomarkers that may indicate an increased susceptibility to depression in order to decrease the prevalence of this debilitating mental disorder.Depression can be treated in many ways that ultimately depend on the individual’s particular symptoms and circumstances. Psychotherapy is a common way to treat depression, and there are many types of psychotherapy that work. For example, interpersonal psychotherapy focuses on communication and relationships, while cognitive behavioural therapy focuses on helping people find and understand their cognitive distortions that amplify depressive thoughts and feelings, as well as mindfulness. Other types of psychotherapy are social skills therapy, psychodynamic therapy, supportive counseling, behavioural activation, and problem-solving therapy. When depression affects others, family and couples therapy may be utilized as well. If a patient becomes a danger to themselves or others, hospitalization may be necessary. With regards to medication, tricyclic antidepressants (TCA), Monoamine oxidase inhibitors (MAOI), and Selective serotonin reuptake inhibitors (SSRI), are the more common medications used to treat depression.There are many organizations around the world that are very dedicated to helping individuals deal with mental health issues, including depression. The Mood Disorder Society of Canada (and the respective provinces), the Canadian Mental Health Association (CMHA), and the Centre for Addiction and Mental Health (CAMH) are the three most widely used and funded organizations that provide a wide range of assistance.<br>Works CitedChen, J., Huang, C., Song, Y., Shi, H., Wu, D., Yang, Y., ... &amp; Cheng, K. (2015). Comparative proteomic analysis of plasma from bipolar depression and depressive disorder: identification of proteins associated with immune regulatory. <i>Protein &amp; cell</i>, <i>6</i>(12), 908-911.Gao, L. J., Zhao, X., Li, J. G., Xu, Y., &amp; Zhang, Y. (2018). Bioinformatics analysis of genes related to pathogenesis of major depression disorder. <i>Sheng li xue bao:[Acta physiologica Sinica]</i>, <i>70</i>(4), 361-368.김은영. (2016). <i>Discovery of Peripheral Biomarkers for Major Depressive Disorder Using Proteomics and Heart Rate Variability Analysis</i> (Doctoral dissertation, 서울대학교 대학원).Martins-de-Souza, D. (2014). Proteomics, metabolomics, and protein interactomics in the characterization of the molecular features of major depressive disorder. <i>Dialogues in clinical neuroscience</i>, <i>16</i>(1), 63.<br> <br>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.435
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.4460.011

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.239
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2018
Admission routes1
Has abstractyes

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