Biology subjects

Teramoto, Y.

Publications and source records attributed to Teramoto, Y..

3 recordsLinked to original sources

bioRxiv2022

TRIAC disrupts cerebral thyroid hormone action via a negative feedback loop and heterogenous distribution among organs

3,3,5-triiodothyroacetic acid (TRIAC) is a metabolite of endogenous thyroid hormones (THs) that can bind to and activate TH receptors. As TRIAC was previously detected in sewage effluent, we aimed to investigate exogenous TRIACs potential for endocrine disruption. We administered either TRIAC or 3,3,5-triiodo-L-thyronine (LT3) to both euthyroid mice and 6-propyl-2-thiouracil-induced hypothyroid mice. In hypothyroid mice, TRIAC alleviated growth retardation, suppressed the hypothalamus-pituitary-thyroid (HPT) axis, and upregulated TH-responsive genes in the pituitary gland, liver, and heart. We observed that, unlike LT3, TRIAC does not upregulate the expression of TH-responsive genes in the cerebrum. Measurement of organ-specific TRIAC levels suggested that TRIAC was not efficiently trafficked into the cerebrum. Furthermore, by analyzing euthyroid mice, we found that cerebral TRIAC levels did not increase despite TRIAC administration at higher concentrations, whereas serum and cerebral TH levels were substantially decreased. Hence, TH-responsive genes in the cerebrum appear to be downregulated by TRIAC. In summary, TRIAC administration decreases circulating TH levels by suppressing the HPT axis, while the consequent attenuation of TH actions was compensated by TRIAC in peripheral tissues but not in the cerebrum due to the relative impermeability of the blood-brain barrier towards TRIAC. We verified that exogenous TRIAC disrupts TH actions in the cerebrum. This disruption is apparently due to the additive effects of circulating endogenous THs being depleted via a negative feedback loop involving the HPT axis and heterogenous distribution of TRIAC among different organs. Our findings indicate that environmental TRIAC poses a potential neurodevelopmental risk.

ecology↗

bioRxiv2020

Targeting Vitamin-D receptor (VDR) by a small molecule antagonist MeTC7 inhibits PD-L1 but controls THMYCN neuroblastoma growth PD-L1 independently

Vitamin-D receptor (VDR) mRNA is enriched in malignant lung, ovarian and pancreatic tissues and showed poor prognoses. Calcitriol and stable or CRISPR-directed VDR upregulation increased PD-L1mRNA and protein expression in cancer cells in-vitro. A ChIP assay showed the binding of VDR with VDREPD-L1. Stattic, a STAT3 phosphorylation inhibitor blocked calcitriol or VDR overexpression induced PD-L1 upregulation. MeTC7, a VDR antagonist developed by us, reduced PD-L1 expression on macrophages, ovarian, lung, breast, and pancreatic cancer cells in-vitro. In radiotherapy inducible PD-L1 model of orthotopic MC38 murine colon cancer, MeTC7 decreased PD-L1 surface expression, suppressed inflammatory monocytes (IMs) population and increased intra-tumoral CD69+PD1+CD8+T-cells. Intriguingly, MeTC7 reduced TH-MYCN transgenic neuroblastoma tumor growth without affecting PD-L1 and tumor immune milieu. In summary, Vitamin-D/VDR drives PD-L1 expression on cancer cells via STAT-3. Inhibiting VDR exhibited anti-checkpoint effects in orthotopic colon tumors, whereas PDL1-independent and anti-VDR/MYCN effects controlled growth of transgenic neuroblastoma and xenografted tumors. SummaryVitamin-D/VDR induces PD-L1 expression on cancer cells via STAT-3; and targeting VDR by a novel small molecule antagonist MeTC7 exhibits both anti-PD-L1 and anti-VDR/MYCN effects in tumor models.

cancer biology↗

bioRxiv2017

Sensory cortex is optimised for prediction of future input

Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimised to represent features in the recent past of sensory input that best predict immediate future inputs. We tested this hypothesis using simple feedforward neural networks, which were trained to predict the next few video or audio frames in clips of natural scenes. The networks developed receptive fields that closely matched those of real cortical neurons, including the oriented spatial tuning of primary visual cortex, the frequency selectivity of primary auditory cortex and, most notably, in their temporal tuning properties. Furthermore, the better a network predicted future inputs the more closely its receptive fields tended to resemble those in the brain. This suggests that sensory processing is optimised to extract those features with the most capacity to predict future input.\n\nImpact statementPrediction of future input explains diverse neural tuning properties in sensory cortex.

neuroscience↗