Glycine and D-serine improve the negative symptoms of schizophrenia
Bibliographic record
Abstract
Tuominen HJ, Tiihonen J, Wahlbeck K. Glutamatergic drugs for schizophrenia: a systematic review and meta-analysis. Schizophr Res 2005;72:225–34.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q Are glutamate receptor agonist drugs effective for people with schizophrenia? ### ![Graphic][5]</img>Design: Systematic review with meta-analysis. ### ![Graphic][6]</img>Data sources: Studies were identified using the Cochrane schizophrenia group’s trial register, BIOSIS Inside, CENTRAL, CINAHL, EMBASE, MEDLINE, and PsycINFO plus handsearches and contact with investigators. ### ![Graphic][7]</img>Study selection and analysis: Eligible studies were double blind randomised controlled trials (RCTs) of NMDA, AMPA, or kainate glutamate receptor agonist (glutamatergic) drugs in people with schizophrenia, with a trial duration of more than two weeks. Random and fixed effect models were used to carry out meta-analyses. ### ![Graphic][8]</img>Outcomes: Global response (Clinical Global Impression scale (CGI); Global Assessment Scale (GAS)), negative symptoms (Positive and Negative Syndrome Scale (PANSS); Scale for Assessment of Negative Symptoms), and cognitive deficiencies (PANSS cognitive subscale). Eighteen RCTs met inclusion criteria. The glutamatergic drugs investigated were D-cyloserine (7 RCTs), glycine (7 RCTs), … [1]: {openurl}?query=rft.jtitle%253DSchizophrenia%2Bresearch%26rft.stitle%253DSchizophr%2BRes%26rft.aulast%253DTuominen%26rft.auinit1%253DH.%2BJ.%26rft.volume%253D72%26rft.issue%253D2-3%26rft.spage%253D225%26rft.epage%253D234%26rft.atitle%253DGlutamatergic%2Bdrugs%2Bfor%2Bschizophrenia%253A%2Ba%2Bsystematic%2Breview%2Band%2Bmeta-analysis.%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.schres.2004.05.005%26rft_id%253Dinfo%253Apmid%252F15560967%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1016/j.schres.2004.05.005&link_type=DOI [3]: /lookup/external-ref?access_num=15560967&link_type=MED&atom=%2Febmental%2F8%2F3%2F82.atom [4]: /lookup/external-ref?access_num=000226430200014&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif [8]: /embed/inline-graphic-4.gif
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".