Lithium Ions as Modulators of Complex Biological Processes: The Conundrum of Multiple Targets, Responsiveness and Non-Responsiveness, and the Potential to Prevent or Correct Dysregulation of Systems during Aging and in Disease
Bibliographic record
Abstract
. Instead, at an early stage of evolution, organisms committed to a range of elements such as sodium, potassium, calcium, magnesium, zinc, and iron to serve essential functions. Such ions serve critical functions in ion channels, as co-factors in enzymes, as a cofactor in oxygen transport, in DNA replication, as a storage molecule in bone and liver, and in a variety of other roles in biological processes. While seemingly excluded from a major essential role in such processes, lithium ions appear to be able to modulate a variety of biological processes and "correct" deviation from normal activity, as a deficiency of lithium can have biological consequences. Lithium salts are found in low levels in many foods and water supplies, but the effectiveness of Li salts to affect biological systems came to recent prominence with the work of Cade, who reported that administrating Li salts calmed guinea pigs and was subsequently effective at relatively high doses to "normalize" a subset of patients with bipolar disorders. Because of its ability to modulate many biological pathways and processes (e.g., cyclic AMP, GSK-3beta, inositol metabolism, NaK ATPases, neuro processes and centers, immune-related events, respectively) both in vitro and in vivo and during development and adult life, Li salts have become both a useful tool to better understand the molecular regulation of such processes and to also provide insights into altered biological processes in vivo during aging and in disease states. While the range of targets for lithium action supports its possible role as a modulator of biological dysregulation, it presents a conundrum for researchers attempting to elucidate its specific primary target in different tissues in vivo. This review will discuss aspects of the state of knowledge regarding some of the systems that can be influenced, focusing on those involving neural and autoimmunity as examples, some of the mechanisms involved, examples of how Li salts can be used to study model systems, as well as suggesting areas where the use of Li salts could lead to additional insights into both disease mechanisms and natural processes at the molecular and cell levels. In addition, caveats regarding lithium doses used, the strengths and weaknesses of rodent models, the background genetics of the strain of mice or rats employed, and the sex of the animals or the cells used, are discussed. Low-dose lithium may have excellent potential, alone or in combination with other interventions to prevent or alleviate aging-associated conditions and disease progression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".