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The combined addition of branched-chain volatile fatty acids (BCVFAs) and folic acid (FA) could improve growth performance and nutrient utilization by stimulating ruminal microbial growth and enzyme activity. This study was conducted to evaluate the effects of BCVFA and FA addition on growth performance, ruminal fermentation, nutrient digestibility, microbial enzyme activity, microflora and excretion of urinary purine derivatives (PDs) in calves. Thirty-six Chinese Holstein weaned calves (60 ± 5.4 days of age and 107 ± 4.7 kg of BW) were assigned to one of four groups in a randomized block design. Treatments were control (without additives), FA (with 10 mg FA/kg dietary DM), BCVFA (with 5 g BCVFA/kg dietary DM) and the combined addition of FA and BCVFA (10 mg/kg DM of FA and 5 g/kg DM of BCVFA). Supplements were hand-mixed into the top one-third of total mixed ration. Dietary concentrate to maize silage ratio was 50 : 50 on a DM basis. Dietary BCVFA or FA addition did not affect dry matter intake but increased average daily gain (ADG) and feed conversion efficiency. Ruminal pH and ammonia N were lower, and total volatile fatty acids (VFAs) concentration was higher for BCVFA or FA addition than for control. Dietary BCVFA or FA addition did not affect acetate proportion but decreased propionate proportion and increased acetate to propionate ratio. Total tract digestibility of DM, organic matter, CP and NDF was higher for BCVFA or FA addition than for control. Dietary BCVFA or FA addition increased activity of carboxymethyl cellulase and cellobiase, population of total bacteria, fungi, Ruminococcus albus, R. flavefaciens, Fibrobacter succinogenes and Prevotella ruminicola as well as total PD excretion. Ruminal xylanase, pectinase and protease activity and Butyrivibrio fibrisolvens population were increased by BCVFA addition, whereas population of protozoa and methanogens was increased by FA addition. The BCVFA × FA interaction was significant for acetate to propionate ratio, cellobiase activity and total PD excretion, and these variables increased more with FA addition in diet without BCVFA than in diet with BCVFA. The data indicated that supplementation with BCVFA or FA increased ADG, nutrient digestibility, ruminal total VFA concentration and microbial protein synthesis by stimulating ruminal microbial growth and enzyme activity in calves. [ABSTRACT FROM AUTHOR]

Abstract: Both μ- and δ-opioid agonists selectively inhibit nociception but have little effect on other sensory modalities. Voltage-activated Ca2+ channels in the primary sensory neurons are important for the regulation of nociceptive transmission. In this study, we determined the effect of δ-opioid agonists on voltage-activated Ca2+ channel currents (ICa) in small-diameter rat dorsal root ganglion (DRG) neurons that do and do not bind isolectin B4 (IB4). The δ-opioid agonists [d-Pen2,d-Pen5]-enkephalin (DPDPE) and deltorphin II produced a greater inhibition of high voltage–activated ICa in IB4-negative than IB4-positive neurons. Furthermore, DPDPE produced a greater inhibition of N-, P/Q-, and L-type ICa in IB4-negative than IB4-positive neurons. However, DPDPE had no significant effect on the R-type ICa in either type of cells. We were surprised to find that DPDPE failed to inhibit either the T-type or high voltage–activated ICa in all the DRG neurons with T-type ICa. Double immunofluorescence labeling showed that the majority of the δ-opioid receptor-immunoreactive DRG neurons had IB4 labeling, while all DRG neurons immunoreactive to δ-opioid receptors exhibited Cav3.2 immunoreactivity. Additionally, DPDPE significantly inhibited high voltage–activated ICa in Tyrode''s or N-methyl-d-glucamine solution but not in tetraethylammonium solution. This study provides new information that δ-opioid agonists have a distinct effect on voltage-activated Ca2+ channels in different phenotypes of primary sensory neurons. High voltage–activated Ca2+ channels are more sensitive to inhibition by δ-opioid agonists in IB4-negative than IB4-positive neurons, and this opioid effect is restricted to DRG neurons devoid of functional T-type Ca2+ currents. [Copyright &y& Elsevier]

Abstract: Olvanil ((N-vanillyl)-9-oleamide), a non-pungent transient receptor potential vanilloid type 1 agonist, desensitizes nociceptors and alleviates pain. But its molecular targets and signaling mechanisms are little known. Calcium influx through voltage-activated Ca2+ channels plays an important role in neurotransmitter release and synaptic transmission. Here we determined the effect of olvanil on voltage-activated Ca2+ channel currents and the signaling pathways in primary sensory neurons. Whole-cell voltage-clamp recordings were performed in acutely isolated rat dorsal root ganglion neurons. Olvanil (1 μM) elicited a delayed but sustained inward current, and caused a profound inhibition (∼60%) of N-, P/Q-, L-, and R-type voltage-activated Ca2+ channel current. Pretreatment with a specific transient receptor potential vanilloid type 1 antagonist or intracellular application of 1,2-bis(2-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid abolished the inhibitory effect of olvanil on voltage-activated Ca2+ channel current. Calmodulin antagonists (ophiobolin-A and calmodulin inhibitory peptide) largely blocked the effect of olvanil and capsaicin on voltage-activated Ca2+ channel current. Furthermore, calcineurin (protein phosphatase 2B) inhibitors (deltamethrin and FK-506) eliminated the effect of olvanil on voltage-activated Ca2+ channel current. Notably, 1,2-bis(2-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid, calmodulin antagonists, and calcineurin inhibitors each alone significantly increased the amplitude of voltage-activated Ca2+ channel current. In addition, double immunofluorescence labeling revealed that olvanil induced a rapid internalization of CaV2.2 immunoreactivity from the membrane surface of dorsal root ganglion neurons. Collectively, this study suggests that stimulation of non-pungent transient receptor potential vanilloid type 1 inhibits voltage-activated Ca2+ channels through a biochemical pathway involving intracellular Ca2+-calmodulin and calcineurin in nociceptive neurons. This new information is important for our understanding of the signaling mechanisms of desensitization of nociceptors by transient receptor potential vanilloid type 1 analogues and the feedback regulation of intracellular Ca2+ and voltage-activated Ca2+ channels in nociceptive sensory neurons. [Copyright &y& Elsevier]

Aim: To investigate the performance of a deep-learning approach termed lesion-aware convolutional neural network (LACNN) to identify 14 different thoracic diseases on chest X-rays (CXRs).Materials and Methods: In total, 10,738 CXRs of 3,526 patients were collected retrospectively. Of these, 1,937 CXRs of 598 patients were selected for training and optimising the lesion-detection network (LDN) of LACNN. The remaining 8,801 CXRs from 2,928 patients were used to train and test the classification network of LACNN. The discriminative performance of the deep-learning approach was compared with that obtained by the radiologists. In addition, its generalisation was validated on the independent public dataset, ChestX-ray14. The decision-making process of the model was visualised by occlusion testing, and the effect of the integration of CXRs and non-image data on model performance was also investigated. In a systematic evaluation, F1 score, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) metrics were calculated.Results: The model generated statistically significantly higher AUC performance compared with radiologists on atelectasis, mass, and nodule, with AUC values of 0.831 (95% confidence interval [CI]: 0.807-0.855), 0.959 (95% CI: 0.944-0.974), and 0.928 (95% CI: 0.906-0.950), respectively. For the other 11 pathologies, there were no statistically significant differences. The average time to complete each CXR classification in the testing dataset was substantially longer for the radiologists (∼35 seconds) than for the LACNN (∼0.197 seconds). In the ChestX-ray14 dataset, the present model also showed competitive performance in comparison with other state-of-the-art deep-learning approaches. Model performance was slightly improved when introducing non-image data.Conclusion: The proposed LACNN achieved radiologist-level performance in identifying thoracic diseases on CXRs, and could potentially expand patient access to CXR diagnostics. [ABSTRACT FROM AUTHOR]