M2 isoform of pyruvate kinase rewires glucose metabolism during radiation therapy to promote an antioxidant response and glioblastoma radioresistance.

Background: Resistance to existing therapies is a significant challenge in improving outcomes for glioblastoma (GBM) patients. Metabolic plasticity has emerged as an important contributor to therapy resistance, including radiation therapy (RT). Here, we investigated how GBM cells reprogram their glucose metabolism in response to RT to promote radiation resistance.

A Suite of Mouse Reagents for Studying Amelogenesis.

Amelogenesis, the formation of dental enamel, is driven by specialized epithelial cells called ameloblasts, which undergo successive stages of differentiation. Ameloblasts secrete enamel matrix proteins (EMPs), proteases, calcium, and phosphate ions in a stage-specific manner to form mature tooth enamel. Developmental defects in tooth enamel are common in humans, and they can greatly impact the well-being of affected individuals.

Radiosensitizing Pancreatic Cancer via Effective Autophagy Inhibition.

Despite aggressive treatments, pancreatic ductal adenocarcinoma (PDAC) remains an intractable disease, largely because it is refractory to therapeutic interventions. To overcome its nutrient-poor microenvironment, PDAC heavily relies on autophagy for metabolic needs to promote tumor growth and survival. Here, we explore autophagy inhibition as a method to enhance the effects of radiotherapy on PDAC tumors.

1-[(4-Nitrophenyl)sulfonyl]-4-phenylpiperazine treatment after brain irradiation preserves cognitive function in mice.

Background: Normal tissue toxicity is an inevitable consequence of primary or secondary brain tumor radiotherapy. Cranial irradiation commonly leads to neurocognitive deficits that manifest months or years after treatment. Mechanistically, radiation-induced loss of neural stem/progenitor cells, neuroinflammation, and demyelination are contributing factors that lead to progressive cognitive decline.

Development and verification of prediction models for preventing cardiovascular diseases.

Objectives: Cardiovascular disease (CVD) is one of the major causes of death worldwide. For improved accuracy of CVD prediction, risk classification was performed using national time-series health examination data. The data offers an opportunity to access deep learning (RNN-LSTM), which is widely known as an outstanding algorithm for analyzing time-series datasets.

Cox Proportional Hazard Regression Versus a Deep Learning Algorithm in the Prediction of Dementia: An Analysis Based on Periodic Health Examination.

Background: With the increase in the world's aging population, there is a growing need to prevent and predict dementia among the general population. The availability of national time-series health examination data in South Korea provides an opportunity to use deep learning algorithm, an artificial intelligence technology, to expedite the analysis of mass and sequential data.

Objective: This study aimed to compare the discriminative accuracy between a time-series deep learning algorithm and conventional statistical methods to predict all-cause dementia and Alzheimer dementia using periodic health examination data.

PK-M2-mediated metabolic changes in breast cancer cells induced by ionizing radiation.

Purpose: Radiotherapy (RT) constitutes an important part of breast cancer treatment. However, triple negative breast cancers (TNBC) exhibit remarkable resistance to most therapies, including RT. Developing new ways to radiosensitize TNBC cells could result in improved patient outcomes.

Osteoprogenitor cells from bone marrow and cortical bone: understanding how the environment affects their fate.

Bone is a dynamic organ where skeletal progenitors and hematopoietic cells share and compete for space. Presumptive mesenchymal stem cells (MSC) have been identified and harvested from the bone marrow (BM-MSC) and cortical bone fragments (CBF-MSC). In this study, we demonstrate that despite the cells sharing a common ancestor, the differences in the structural properties of the resident tissues affect cell behavior and prime them to react differently to stimuli.

Serotonin (5-HT) excites rat masticatory muscle afferent fibers through activation of peripheral 5-HT3 receptors.

In the present study, we combined immunohistochemical experiments with in vivo single unit recordings to examine whether 5-HT(3) receptors are expressed by masticatory (masseter and temporalis) sensory ganglion neurons and to investigate the effects of intramuscular injection of 5-HT on the excitability and mechanical threshold of rat masticatory muscle afferent fibers. The expression of 5-HT(3) receptors by masticatory ganglion neurons was examined using immunohistochemical techniques. In vivo extracellular single unit recording techniques were used to assess changes in the excitability of individual masticatory muscle afferent fibers.