Synaptic modulation of glutamate in striatum of the YAC128 mouse model of Huntington disease.

Background: Altered balance between striatal direct and indirect pathways contributes to early motor, cognitive and psychiatric symptoms in Huntington disease (HD). While degeneration of striatal D2-type dopamine receptor (D2)-expressing indirect pathway medium spiny neurons (iMSNs) occurs prior to that of D1-type dopamine receptor (D1)-expressing direct pathway neurons, altered corticostriatal synaptic function precedes degeneration. D2-mediated signaling on iMSNs reduces their excitability and promotes endocannabinoid (eCB) synthesis, suppressing glutamate release from cortical afferents.

Evolutionary potential and constraints in an aposematic species: Genetic correlations between warning coloration and fitness components in wood tiger moths.

Variability in warning signals is common but remains puzzling since deviations from the most common form should result in a higher number of predator attacks. One explanation may lie in constraints due to genetic correlations between warning colour and other traits under selection. To explore the relationship between variation in warning colour and different life-history traits, we used an extensive data set comprising 64,741 individuals from a Finnish and an Estonian population of the wood tiger moths, Arctia plantaginis, that have been maintained in captivity over 25 generations.

Charting the shared genetic architecture of Alzheimer's disease, cognition, and educational attainment, and associations with brain development.

The observation that the risk of developing Alzheimer's disease is reduced in individuals with high premorbid cognitive functioning, higher educational attainment, and occupational status has led to the 'cognitive reserve' hypothesis. This hypothesis suggests that individuals with greater cognitive reserve can tolerate a more significant burden of neuropathological changes before the onset of cognitive decline. The underpinnings of cognitive reserve remain poorly understood, although a shared genetic basis between measures of cognitive reserve and Alzheimer's disease has been suggested.

Applying clustered artificial neural networks to enhance contaminant diffusion prediction in geotechnical engineering.

This paper introduces a novel approach using Clustered Artificial Neural Networks (CLANN) to address the challenge of developing predictive models for multimodal dataset with extreme parameter values. The CLANN method strategically decomposes the dataset, derived from Finite Element Analysis (FEA), into clusters, each representing distinct diffusion behaviors, and applies specialized neural networks within these clusters. The CLANN model was rigorously evaluated and demonstrated superior accuracy and consistency compared to traditional methods such as the Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy expert systems.

No clinically relevant relationship between different quantitative measurement methods of the lateral femoral condyle morphology on lateral radiographs in anterior cruciate ligament-injured patients.

Purpose: To clarify whether different methods of quantifying lateral femoral condyle (LFC) bone morphology as risk factors for anterior cruciate ligament (ACL) injury on lateral radiographs should be considered as individual risk factors and to assess inter- and intraobserver reliability.

Methods: We retrospectively reviewed 487 patients undergoing primary ACL reconstruction at our institution. Routine lateral radiographs of the injured knees were utilized to measure the following parameters: LFC ratio (LFCR), height of LFC to anteroposterior diameter ratio (HAPR), femur tibia size ratio (FTSR), tibia to posterior femoral condyle ratio (TPFCR) and Porto ratios (XY/AB; B/AB; B/XY).