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Electroacupuncture (EA) can effectively modulate pain perception and pain-related negative affect; however, we do not know whether the effect of EA on sensation and affect is parallel, or dissociated, interactional. In this study, we observed the effects of the anterior cingulate cortex (ACC) lesion and the primary somatosensory cortex (S1) activation on pain perception, pain-related affection, and neural oscillation in S1. ACC lesions did not affect pain perception but relieved pain-paired aversion. S1 activation increased pain perception and anxious behavior. EA can mitigate pain perception regardless of whether there is an ACC lesion. Chronic pain may increase the delta and theta band oscillatory activity in the S1 brain region and decrease the oscillatory activity in the alpha, beta, and gamma bands. EA intervention may inhibit the oscillatory activity of the alpha and beta bands. These results suggest that EA may mitigate chronic pain by relieving pain perception and reducing pain-related affection through different mechanisms. This evidence builds upon findings from previous studies of chronic pain and EA treatment.

Intestinal sensitivity to mechanical stimuli has been studied intensively in visceral pain studies. The ability to sense different stimuli in the gut and translate these to physiological outcomes relies on the mechanosensory and transductive capacity of intrinsic intestinal nerves. However, the nature of the mechanosensitive channels and principal mechanical stimulus for mechanosensitive receptors are unknown. To be able to characterize intestinal mechanoelectrical transduction, that is, the molecular basis of mechanosensation, comprehensive mathematical models to predict responses of the sensory neurons to controlled mechanical stimuli are needed. This study aims to develop a biophysically based mathematical model of the myenteric neuron with the parameters constrained by learning from existing experimental data.

. The conductance-based single-compartment model was selected. The parameters in the model were optimized by using a combination of hand tuning and automated estimation. Using the optimized parameters, the model successfully predicted the electrophysiological features of the myenteric neurons with and without mechanical stimulation.

The model provides a method to predict features and levels of detail of the underlying physiological system in generating myenteric neuron responses. The model could be used as building blocks in future large-scale network simulations of intrinsic primary afferent neurons and their network.

The model provides a method to predict features and levels of detail of the underlying physiological system in generating myenteric neuron responses. The model could be used as building blocks in future large-scale network simulations of intrinsic primary afferent neurons and their network.The recommendation system in the online medical consultation website is a system to assist patients to find appropriate doctors. Based on the analysis of the current situation of the development of an online medical community (Haodf.com) in China, this paper puts forward recommendation suggestions of finding the right hospital and doctor to promote the rapid integration of Internet technology and traditional medical services. A new recommendation model called Probabilistic Matrix Factorization integrated with Convolutional Neural Network (PMF-CNN) is proposed in the paper. Doctors' data in Haodf.com were used to evaluate the performance of our system. The model improves the performance of medical consultation recommendations by fusing review text and doctor information based on CNN (Convolutional Neural Network). Specifically, CNN is used to learn the feature representation of the review text and the doctors' information. RVX-000222 Furthermore, the extended matrix factorization model is exploited to fuse the review information feature and the initial value of the doctors' information for recommendation. As is shown in the experimental results on Haodf.com datasets, the proposed PMF-CNN achieves better recommendation performances than the other state-of-the-art recommendation algorithms. And the recommendation system in an online medical website improves the utilization efficiency of doctors and the balance of public health resources allocation.Potassium (K) is essential for regulating plant growth and mediating abiotic stress responses. Elucidating the biological mechanism underlying plant responses to K-deficiency is crucial for breeding new cultivars with improved K uptake and K utilization efficiency. In this study, we evaluated the extent of the genetic variation among 543 wheat accessions differing in K-deficiency tolerance at the seedling and adult plant stages. Two accessions, KN9204 and BN207, were identified as extremely tolerant and sensitive to K-deficiency, respectively. The accessions were exposed to normal and K-deficient conditions, after which their roots underwent ionomic, transcriptomic, and metabolomic analyses. Under K-deficient conditions, KN9204 exhibited stronger root growth and maintained higher K concentrations than BN207. Moreover, 19,440 transcripts and 162 metabolites were differentially abundant in the roots of both accessions according to transcriptomic and metabolomic analyses. An integrated analysis of gene expression and metabolite profiles revealed that substantially more genes, including those related to ion homeostasis, cellular reactive oxygen species homeostasis, and the glutamate metabolic pathway, were up-regulated in KN9204 than in BN207 in response to low-K stress. Accordingly, these candidate genes have unique regulatory roles affecting plant K-starvation tolerance. These findings may be useful for further clarifying the molecular changes underlying wheat root adaptations to K deprivation.Adventitious root (AR) formation is a complex developmental process controlled by a plethora of endogenous and environmental factors. Based on fossil evidence and genomic phylogeny, AR formation might be considered the default state of plant roots, which likely evolved independently several times. The application of next-generation sequencing techniques and bioinformatics analyses to non-model plants provide novel approaches to identify genes putatively involved in AR formation in multiple species. Recent results uncovered that the regulation of shoot-borne AR formation in monocots is an adaptive response to nutrient and water deficiency that enhances topsoil foraging and improves plant performance. A hierarchy of transcription factors required for AR initiation has been identified from genetic studies, and recent results highlighted the key involvement of additional regulation through microRNAs. Here, we discuss our current understanding of AR formation in response to specific environmental stresses, such as nutrient deficiency, drought or waterlogging, aimed at providing evidence for the integration of the hormone crosstalk required for the activation of root competent cells within adult tissues from which the ARs develop.

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