"Señor buscamos tu rostro": IX Jornadas Patrimonio cultural CONFER
Bibliographic record
Abstract
Schizophrenia is a debilitating psychiatric illness that remains poorly understood. While the bulk of symptomatology has classically been associated with disrupted brain functioning, accumulating evidence demonstrates that schizophrenia is characterized by systemic inflammation and disturbances in metabolism. Indeed, metabolic disease is a major determinant of the high mortality rate associated with schizophrenia. Antipsychotic drugs (APDs) have revolutionized management of psychosis, making it possible to rapidly control psychotic symptoms. This has ultimately reduced relapse rates of psychotic episodes and improved overall quality of life for people with schizophrenia. However, long-term APD use has also been associated with significant metabolic disturbances including weight gain, dysglycemia, and worsening of the underlying cardiometabolic disease intrinsic to schizophrenia. While the mechanisms for these intrinsic and medication-induced metabolic effects remain unclear, inflammation appears to play a key role. Here, we review the evidence for roles of inflammatory mechanisms in the disease features of schizophrenia and how these mechanisms interact with APD treatment. We also discuss the effects of common inflammatory mediators on metabolic disease. Then, we review the evidence of intrinsic and APD-mediated effects on systemic inflammation in schizophrenia. Finally, we speculate about possible treatment strategies. Developing an improved understanding of inflammatory processes in schizophrenia may therefore introduce new, more effective options for treating not only schizophrenia but also primary metabolic disorders.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".