Methods: We studied the soleus muscle and tibia from intact r

\n\nMethods: We studied the soleus muscle and tibia from intact rats (SHAM), orchidectomized buy Lonafarnib rats treated for 3 months with vehicle (ORX), nandrolone decanoate (NAN) or dihydrotestosterone (DHT).\n\nResults: Orchidectomy had very little effect on the soleus muscle. However, maximal force production by soleus muscle (+69%) and fatigue resistance (+35%) in NAN rats were both increased when compared with ORX rats.

In contrast, DHT treatment did not improve muscle function. The relative number of muscle fibres expressing slow myosin heavy chain and citrate synthase activity were not different in NAN and ORX rats. Moreover, NAN and DHT treatments did not modify muscle weights and cross-sectional area of muscle fibres. Furthermore, phosphorylation levels of downstream SU5402 datasheet targets of the Akt/mTOR signalling pathway, Akt, ribosomal protein S6 and eukaryotic initiation factor 4E-binding protein

1 were similar in muscles of NAN, DHT and ORX rats. In addition, trabecular tibia from NAN and DHT rats displayed higher bone mineral density and bone volume when compared with ORX rats. Only in NAN rats was this associated with increased bone resistance to fracture.\n\nConclusion: Physiological doses of androgens are beneficial to muscle performance in orchidectomized rats without relationship to muscle and fibre hypertrophy and activation

of the Akt/mTOR signalling pathway. Taken together our data clearly indicate that the activity of androgens on muscle and bone could participate in the global improvement of musculoskeletal status in the context of androgen deprivation induced by ageing.”
“PythDock is a heuristic docking program that uses Python programming language with a simple scoring function and a population based search engine. The scoring function considers electrostatic and dispersion/repulsion 4SC-202 research buy terms. The search engine utilizes a particle swarm optimization algorithm. A grid potential map is generated using the shape information of a bound ligand within the active site. Therefore, the searching area is more relevant to the ligand binding. To evaluate the docking performance of PythDock, two well-known docking programs (AutoDock and DOCK) were also used with the same data. The accuracy of docked results were measured by the difference of the ligand structure between x-ray structure, and docked pose, i.e., average root mean squared deviation values of the bound ligand were compared for fourteen protein-ligand complexes. Since the number of ligands’ rotational flexibility is an important factor affecting the accuracy of a docking, the data set was chosen to have various degrees of flexibility.

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