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We tested the hypothesis that dorsal cervical epidural electrical stimulation (CEES) increases respiratory activity in male and female anesthetized rats. Respiratory frequency and minute ventilation were significantly increased when CEES was applied dorsally to the C2-C6 region of the cervical spinal cord. By injecting pseudorabies virus into the diaphragm and using c-Fos activity to identify neurons activated during CEES, we found neurons in the dorsal horn of the cervical spinal cord in which c-Fos and pseudorabies were co-localized, and these neurons expressed somatostatin (SST). Using dual viral infection to express the inhibitory Designer Receptors Exclusively Activated by Designer Drugs (DREADD), hM4D(Gi), selectively in SST-positive cells, we inhibited SST-expressing neurons by administering Clozapine N-oxide (CNO). During CNO-mediated inhibition of SST-expressing cervical spinal neurons, the respiratory excitation elicited by CEES was diminished. Thus, dorsal cervical epidural stimulation activated SST-expressing neurons in the cervical spinal cord, likely interneurons, that communicated with the respiratory pattern generating network to effect changes in ventilation.SIGNIFICANCE STATEMENT A network of pontomedullary neurons within the brainstem generates respiratory behaviors that are susceptible to modulation by a variety of inputs; spinal sensory and motor circuits modulate and adapt this output to meet the demands placed on the respiratory system. We explored dorsal cervical epidural electrical stimulation (CEES) excitation of spinal circuits to increase ventilation in rats. We identified dorsal somatostatin (SST)-expressing neurons in the cervical spinal cord that were activated (c-Fos-positive) by CEES. CEES no longer stimulated ventilation during inhibition of SST-expressing spinal neuronal activity, thereby demonstrating that spinal SST neurons participate in the activation of respiratory circuits affected by CEES. This work establishes a mechanistic foundation to repurpose a clinically accessible neuromodulatory therapy to activate respiratory circuits and stimulate ventilation.

Spinal cord stimulation enhanced restoration of motor function following spinal cord injury (SCI) in unblinded studies. To determine whether training combined with transcutaneous electrical spinal cord stimulation (tSCS), with or without systemic serotonergic treatment with buspirone (busp), could improve hand function in individuals with severe hand paralysis following SCI, we assessed ten subjects in a double-blind, sham-controlled, crossover study. All treatments-busp, tSCS, and the busp plus tSCS-reduced muscle tone and spasm frequency. Buspirone did not have any discernible impact on grip force or manual dexterity when administered alone or in combination with tSCS. In contrast, grip force, sinusoidal force generation and grip-release rate improved significantly after 6 weeks of tSCS in 5 out of 10 subjects who had residual grip force within the range of 0.1-1.5 N at the baseline evaluation. Improved hand function was sustained in subjects with residual grip force 2-5 months after the tSCS and buspirone treatment. We conclude that tSCS combined with training improves hand strength and manual dexterity in subjects with SCI who have residual grip strength greater than 0.1 N. Buspirone did not significantly improve the hand function nor add to the effect of stimulation.

Motor deficits are observed in Alzheimer's disease (AD) prior to the appearance of cognitive symptoms. To investigate the role of amyloid proteins in gait disturbances, we characterized locomotion in APP-overexpressing transgenic J20 mice. We used three-dimensional motion capture to characterize quadrupedal locomotion on a treadmill in J20 and wild-type mice. Sixteen J20 mice and fifteen wild-type mice were studied at two ages (4- and 13-month). A random forest (RF) classification algorithm discriminated between the genotypes within each age group using a leave-one-out cross-validation. The balanced accuracy of the RF classification was 92.3 ± 5.2% and 93.3 ± 4.5% as well as False Negative Rate (FNR) of 0.0 ± 0.0% and 0.0 ± 0.0% for the 4-month and 13-month groups, respectively. Feature ranking algorithms identified kinematic features that when considered simultaneously, achieved high genotype classification accuracy. The identified features demonstrated an age-specific kinematic profile of the impact of APP-overexpression. Trunk tilt and unstable hip movement patterns were important in classifying the 4-month J20 mice, whereas patterns of shoulder and iliac crest movement were critical for classifying 13-month J20 mice. Examining multiple kinematic features of gait simultaneously could also be developed to classify motor disorders in humans.

Uncontrollable bleeding is still the main cause of post-traumatic deaths due to the blood loss. Moreover, infectious complication of wound is also still a challenging problem for wound healing. Nevertheless, the currently available hemostasis drugs or materials cannot stanch bleeding well due to single function, slow in effectiveness, adhere to wounds easily, poor gas permeability, etc. Therefore, it is of a great significance to utilize a biomedical hemostatic material that can stop bleeding quickly, preventing from bacterial infections, and with good biocompatibility properties. Herein chitosan (CS) was modified with gallic acid (GA) and thrombin (TB) to prepare an antibacterial hemostatic composite dressing. The CS-based composite hydrogel dressing was obtained by acylation modification, ultraviolet curing crosslinking method and physical mixing. The in vitro results showed that our prepared CS-based composite hydrogel has obvious burst release and good degradation property. Moreover, the in vivo results showed that it has a strong antibacterial property that is much better than single CS, and it can stop bleeding in 1 min which can promote wound healing. Therefore, the findings of this study is expected to contribute to the future designing of biomedical hemostatic materials with improved properties.

In recent years, deep learning has become a promising tool for rotary machinery fault diagnosis, but it works well only when testing samples and training samples are independent and identically distributed. In practice, rotary machinery usually works under variable speed. The change of speed leads to the variation of samples’ distribution, which can significantly decrease the performance of the deep learning model. Scholars try to utilize transfer learning techniques for solving this problem. However, most exiting methods can just work well under target speed instead of all speed, while the target samples are always required in model training. In this article, a deep semisupervised domain generalization network (DSDGN) is proposed for rotary machinery fault diagnosis under variable speed, which can generalize the model to the fault diagnosis task under unseen speed. Under the setting of semisupervised domain generalization, only one fully labeled source (LS) domain data set and one totally unlabeled source (US) domain data set are available during training. To make full use of these data, the proposed method simultaneously utilizes Wasserstein generative adversarial network with gradient penalty (WGAN-GP)-based adversarial learning and pseudolabel-based semisupervised learning for training. The transmission and bearing fault diagnosis cases are utilized for evaluation. The comparative experiments indicate that the proposed method has a better performance than other state-of-the-art methods. [ABSTRACT FROM AUTHOR]