Protective effect of Mucuna pruriens (L.) DC. var. pruriens seed extract on apoptotic germ cells in ethanolic male rats.

Thai Mucuna pruriens (L.) DC. var pruriens (T-MP) seed containing levodopa (L-DOPA) and antioxidant capacity has been shown to improve sexual behavior and male reproductive parameters in rats treated with ethanol (Eth). However, its protective effect on testicular apoptotic germ cells has never been reported. This study aimed to investigate the potential effects of T-MP seed extract on expressions of caspase, proliferating cell nuclear antigen (PCNA), and dopamine D2 receptor (D2R) proteins in Eth rats. Thirty-six male Wistar rats were divided into four groups (9 animals/group), including control, Eth, T-MP150+Eth, and T-MP300+Eth, respectively. Control rats received distilled water, and Eth rats received Eth (3g/kg BW; 40%v/v). The T-MP groups were treated with T-MP seed extract at a dose of 150 or 300 mg/kg before Eth administration for 56 consecutive days. The results showed that the seminiferous tubule diameter and epithelial height were significantly increased in both T-MP treated groups compared to the Eth group. Additionally, the caspase-9 and -3, and PCNA expressions were decreased, but D2R expression was markedly increased in T-MP groups. It was concluded that T-MP seed extract could protect testicular apoptosis induced by Eth via changes in caspase, PCNA, and D2R protein expressions.

Towards microstructure-informed material models for human brain tissue.

Emerging evidence suggests that the mechanical behavior of the brain plays a critical role in development, disease, and aging. Recent studies have begun to characterize the mechanical behavior of gray and white matter tissue and to identify sets of material models that best reproduce the stress-strain behavior of different brain regions. Yet, these models are mainly phenomenological in nature, their parameters often lack clear physical interpretation, and they fail to correlate the mechanical behavior to the underlying microstructural composition. Here we make a first attempt towards identifying general relations between microstructure and mechanics with the ultimate goal to develop microstructurally motivated constitutive equations for human brain tissue. Using histological staining, we analyze the microstructure of brain specimens from different anatomical regions, the cortex, basal ganglia, corona radiata, and corpus callosum, and identify the regional stiffness and viscosity under multiple loading conditions, simple shear, compression, and tension. Strikingly, our study reveals a negative correlation between cell count and stiffness, a positive correlation between myelin content and stiffness, and a negative correlation between proteoglycan content and stiffness. Additionally, our analysis shows a positive correlation between lipid and proteoglycan content and viscosity. We demonstrate how understanding the microstructural origin of the macroscopic behavior of the brain can help us design microstructure-informed material models for human brain tissue that inherently capture regional heterogeneities. This study represents an important step towards using brain tissue stiffness and viscosity as early diagnostic markers for clinical conditions including chronic traumatic encephalopathy, Alzheimer's and Parkinson's disease, or multiple sclerosis. STATEMENT OF SIGNIFICANCE: The complex and heterogeneous mechanical properties of brain tissue play a critical role for brain function. To understand and predict how brain tissue properties vary in space and time, it will be key to link the mechanical behavior to the underlying microstructural composition. Here we use histological staining to quantify area fractions of microstructural components of mechanically tested specimens and evaluate their individual contributions to the nonlinear macroscopic mechanical response. We further propose a microstructure-informed material model for human brain tissue that inherently captures regional heterogeneities. The current work provides unprecedented insights into the biomechanics of human brain tissue, which are highly relevant to develop refined computational models for brain tissue behavior or to advance neural tissue engineering.