Role of Infection in Neurologic and Psychiatric Diseases
Bibliographic record
Abstract
What makes CNS injury by pathogens different from other CNS afflictions such as stroke or Alzheimer's Disease is well illustrated in the manuscripts of this volume. We will see that viral, bacterial, or prion-induced injuries are dynamic and varied. No two infection cases are the same due to host or agent factors. We will encounter pathogens that are shared with other species and some that range across the globe. We will also find robust examples of gene x age x environment interactions as determinants of nervous system disease, which can be incorporated into understanding many neurobiological processes. The role of infection in neurologic and psychiatric diseases is predicated on clinical and research observations, which have been expanded into the domains of neurobiology by hypotheses from several perspectives. Our collected papers come from perspectives of epidemiology, protein biochemistry, immunology, genetics, molecular biology, pathology, behavioral sciences, psychology, neuropharmacology, and human and veterinary medicine. These articles are comprehensive reviews, topical summaries, or original research papers. We hope that this collection of manuscripts provides a greater understanding of both familiar and unfamiliar pathogens, prompts new ideas on disease mechanisms and treatments, and stimulates further cooperative work on infection in neurologic and psychiatric diseases. We thank our contributors from around the world. When it comes to transmissible diseases, the world is a small place. Although we did not specifically solicit for public health topics, we note that cross-species transfers, emerging diseases, epidemics and pandemics, are developed as key discussions in several of our manuscripts. For this reason we dedicate this special issue to the One Health Initiative, whose work is defined by the Mission Statement on their website: www.onehealthinitiative.com/mission.php “Recognizing that human and animal health and mental health.... are inextricably linked, One Health seeks to promote, improve, and defend the health and well-being of all species by enhancing cooperation and collaboration between physicians, veterinarians, and other scientific professionals....” We express our sincere gratitude to all authors and reviewers for their time and effort, to Betsy Foxman, Editor-in-Chief for the invitation, and the staff at Hindawi Publishing for their assistance and support. Marylou V. Solbrig Guey Chuen Perng
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.005 |
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 source (direct Gemma or distilled Codex), 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".