Going Too Far Is the Same as Falling Short†: Kinesin-3 Family Members in Hereditary Spastic Paraplegia
Bibliographic record
Abstract
Proper intracellular trafficking is essential for neuronal development and function, and when any aspect of this process is dysregulated, the resulting "transportopathy" causes neurological disorders. Hereditary spastic paraplegias (HSPs) are a family of such diseases attributed to over 80 spastic gait genes (SPG), specifically characterized by lower extremity spasticity and weakness. Multiple genes in the trafficking pathway such as those relating to microtubule structure and function and organelle biogenesis are representative disease loci. Microtubule motor proteins, or kinesins, are also causal in HSP, specifically mutations in Kinesin-I/KIF5A (SPG10) and two kinesin-3 family members; KIF1A (SPG30) and KIF1C (SPG58). KIF1A is a motor enriched in neurons, and involved in the anterograde transport of a variety of vesicles that contribute to pre- and post-synaptic assembly, autophagic processes, and neuron survival. KIF1C is ubiquitously expressed and, in addition to anterograde cargo transport, also functions in retrograde transport between the Golgi and the endoplasmic reticulum. Only a handful of KIF1C cargos have been identified; however, many have crucial roles such as neuronal differentiation, outgrowth, plasticity and survival. HSP-related kinesin-3 mutants are characterized mainly as loss-of-function resulting in deficits in motility, regulation, and cargo binding. Gain-of-function mutants are also seen, and are characterized by increased microtubule-on rates and hypermotility. Both sets of mutations ultimately result in misdelivery of critical cargos within the neuron. This likely leads to deleterious cell biological cascades that likely underlie or contribute to HSP clinical pathology and ultimately, symptomology. Due to the paucity of histopathological or cell biological data assessing perturbations in cargo localization, it has been difficult to positively link these mutations to the outcomes seen in HSPs. Ultimately, the goal of this review is to encourage future academic and clinical efforts to focus on "transportopathies" through a cargo-centric lens.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".