Biology subjects

Yamada, L.

Publications and source records attributed to Yamada, L..

3 recordsLinked to original sources

bioRxiv2026

Compression Detects Changes in Spiking Neural Data from Cortical Lesions

1ObjectiveThe complexity of neural data changes as the brain processes information during events. Universal lossless compression algorithms, which are broadly applicable and grounded in information theory, identify and exploit redundancies in data in order to compress it to essentially-optimal sizes regardless of underlying statistics. These algorithms may be used to conveniently and efficiently estimate a given signals Shannon entropy rate, a biologically relevant measure of the complexity of a signal. It is therefore natural to explore their effectiveness in the analysis of spiking neural data. ApproachThis work focuses on using compression to analyze recordings (96-channel Utah arrays) taken from motor cortex of animals performing reaching tasks for three days before and three days after administering electrolytic lesions (Subject U: 4 lesions, H: 3). In particular, we use the inverse compression ratio (ICR), which compares the sizes of compressed and uncompressed data to estimate the amount of statistically unique information. We calculate ICR with temporally-independent lossless compression (gzip) and temporally-dependent lossy compression (H.264, MPEG-2). Compression-based ICR was compared to single-neuron measures used to understand spiking data, such as average firing rates and Fano factor. Compression is also compared to common dimensionality reduction techniques, principal component analysis (PCA) and factor analysis (FA). Main ResultsStatistical tests on aggregate data comparing each metric before and after lesioning reveal that ICR is able to significantly (Mann-Whitney U test, p < 0.01) detect lesions with higher accuracy than single-neuron metrics, but not dimensionality reduction (ICR methods: 85.7%, single-neuron methods: 78.6%, dimensionality reduction: 100%). Additionally, statistical results on the same data show that ICR metrics remain more stable than single-neuron methods after lesion. The bitrate parameter of lossy compression algorithms is swept to better understand the effect of information rates and "optimal" compression on lesion detection performance. Our conclusions are confirmed by the same analyses performed on several different simulated neural datasets. SignificanceThese results suggest that compression algorithms may be a useful tool to detect and better understand perturbations to the underlying structure of neural data. Information-theoretic analyses may complement techniques like dimensionality reduction and firing rate tuning as a convenient and useful tool to characterize neural data.

neuroscience↗

bioRxiv2026

Senescence-inhibitory Δ133p53α counteracts accelerated ageing and mortality

Research on progeria not only contributes to treatments for the disease but also enhances our understanding of physiological ageing1. Mouse models of progeria recapitulate pathological ageing phenotypes seen in patients, including cardiovascular defects, increased cellular senescence, systemic inflammation, DNA damage accumulation, and shortened lifespan2. In cultured cells from Hutchinson-Gilford progeria syndrome (HGPS) patients, the human p53 isoform {Delta}133p53 was previously shown to inhibit p53-mediated cellular senescence, proinflammatory IL-6 production, and DNA damage accumulation, and to extend cellular replicative lifespan3. Here we show that, in a heterozygous HGPS mouse model4, transgenic expression of {Delta}133p53 reproduces these in vitro-observed effects across multiple organs in vivo and extends median lifespan by 11% (387 versus 349 days, P = 0.0379). In the aorta and skin, {Delta}133p53 abrogates progeria-characteristic pathological changes and preserves tissue integrity. Our data further suggest that {Delta}133p53 may promote a broad spectrum of ageing-counteracting mechanisms, including bone homeostasis, metabolic fitness, antioxidant defense, youthful epigenome, and tissue stemness. Together with the anti-inflammatory and tissue-preserving effects of {Delta}133p53 in naturally aged mice and its age-associated downregulation in human tissues, this study suggests that {Delta}133p53-based therapeutic strategies may be applicable not only to HGPS but also as broader interventions for preventing or delaying ageing.

physiology↗

bioRxiv2025

SRSF3 knockdown-induced cellular senescence as a possible therapeutic strategy for non-small cell lung cancer

Tyrosine kinase (TK) inhibitors improve clinical outcomes in non-small cell lung cancer (NSCLC) with targetable mutations. However, such NSCLC cases only consist of about 50% in the western populations. This study, for the first time in NSCLC cells including those without a targetable TK mutation, explores a tumor-suppressive activity of siRNA knockdown of a splicing factor SRSF3, which was reportedly effective in other cancer cell types. The knockdown of SRSF3 increased cellular senescence, indicated by senescence-associated {beta}-galactosidase activity and reduced cell proliferation, in all NSCLC cell lines examined, including A549 (no TK mutation; TP53 wild-type), NCI-H1975 (EGFR L858R/T790M; TP53 R273H mutant), NCI-H322 (no TK mutation; TP53 R248L mutant) and NCI-H596 (no TK mutation; TP53 G245C mutant). An increase in apoptotic cleavage of caspase-3 and poly(ADP-ribose) polymerase was also observed in A549 cells. p53{beta}, a tumor-suppressive p53 isoform generated via alternative mRNA splicing, was upregulated by SRSF3 knockdown, as previously reported in normal fibroblasts. However, neither cellular senescence nor apoptosis was increased by overexpression of p53{beta}, suggesting no or minimum contribution of this p53 isoform to the tumor-suppressive activity of SRSF3 knockdown in NSCLC cells. Our gene expression assay indicated that the SRSF3 knockdown-induced senescence in NSCLC cells may be mediated by downregulation of TOP2A, UBE2C or ASPM, which are known to be oncogenic and are associated with poor patient prognosis. We also generated SRSF3 siRNA-encapsulating lipid nanoparticles as a future therapeutic tool. This study suggests a therapeutic strategy for NSCLC irrespective of the mutation status of TP53 and TK-encoding genes. SummaryKnockdown of a splicing factor SRSF3 increases cellular senescence in NSCLC cells including those with no targetable mutation of tyrosine kinases and thus may represent a novel therapeutic strategy for a hard-to-treat group of NSCLC.

cancer biology↗