Study of Brain-derived Neurotrophic Factor in Drug-naive Patients with Schizophrenia
Bibliographic record
Abstract
Background and Aim: Brain-derived neurotrophic factor (BDNF) is a widely studied neurotrophin and is said to be involved in the regulation of many neuronal processes, including neurogenesis, neuronal differentiation, maturation, and survival. Over the years, research has shown a significant variation of serum BDNF levels in schizophrenia with no widespread agreement. Herein, we report on serum BDNF levels in drug-naive patients of schizophrenia in comparison to healthy controls (HC) and correlates of BDNF levels in patients of schizophrenia. Materials and Methods: The study sample consisted of 120 participants with 60 drug-naive patients of schizophrenia and 60 HC. The blood sample of the study subjects was collected and processed serum was analyzed using an enzyme-linked immunosorbent assay kit for BDNF levels. Clinical assessment of patients was done using the Positive and Negative Syndrome Scale (PANSS) and Montreal Cognitive Assessment. Results: Serum BDNF levels were significantly lower in drug-naive patients of schizophrenia as compared to age and sex-matched HC ( P – 0.024). The PANSS total score and positive subscale score were negatively correlated with serum BDNF levels which were statistically significant with P = 0.005 and P = 0.001, respectively. Conclusion: The index study found BDNF levels to be reduced in patients of schizophrenia and BDNF was found to correlate with severity of illness, especially positive symptoms. Thus, developing therapeutic strategies that can activate BDNF signaling may prove beneficial in improving the clinical outcome of schizophrenia.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".