Vagus nerve stimulation (VNS), targeting the imbalanced autonomic nervous system, is a promising therapeutic approach for chronic heart failure (HF). Moreover, calcium cycling is an important part of cardiac excitation-contraction coupling (ECC), which also participates in the antiarrhythmic effects of VNS. We hypothesized that low-level VNS (LL-VNS) could improve cardiac function by regulation of intracellular calcium handling properties. The experimental HF model was established by ligation of the left anterior descending coronary artery (LAD). Thirty-two male Sprague-Dawley rats were divided into 3 groups as follows; control group (sham operated without coronary ligation, n = 10), HF-VNS group (HF rats with VNS, n = 12), and HF-SS group (HF rats with sham nerve stimulation, n = 10). After 8 weeks of treatment, LL-VNS significantly improved left ventricular ejection fraction (LVEF) and attenuated myocardial interstitial fibrosis in the HF-VNS group compared with the HF-SS group. Elevated plasma norepinephrine and dopamine, but not epinephrine, were partially reduced by LL-VNS. Additionally, LL-VNS restored the protein and mRNA levels of sarcoplasmic reticulum Ca2+ ATPase (SERCA2a), Na+–Ca2+ exchanger 1 (NCX1), and phospholamban (PLB) whereas the expression of ryanodine receptor 2 (RyR2) as well as mRNA level was unaffected. Thus, our study results suggest that the improvement of cardiac performance by LL-VNS is accompanied by the reversal of dysfunctional calcium handling properties including SERCA2a, NCX1, and PLB which may be a potential molecular mechanism of VNS for HF.
Intensive monocular perceptual learning can improve visual acuity, contrast sensitivity, and vernier acuity in the amblyopic eye in adults with amblyopia. It is however not clear how much monocular training can enhance binocular visual functions. In the current study, we aimed to evaluate effects of monocular training on a variety of binocular functions. Nineteen anisometropic amblyopes (18.5±1.26yrs, mean±s.e.) were trained in a grating contrast detection task near each individual's cutoff spatial frequency for 6-10days (630 trials/day). Visual acuity, stereoacuity, monocular and binocular contrast sensitivity functions (CSF), binocular phase combination and binocular rivalry were tested before and after training. Although monocular training can improve visual acuity and contrast sensitivity and eye dominance of the amblyopic eye, the magnitudes of improvements did not correlate with each other; the impact of monocular training on binocular phase combination was not significant. The results strongly suggest that structured monocular and binocular training is needed to fully recover deficient visual functions in anisometropic amblyopia.
Optical coherence tomography (OCT) technology has significant potential value in the application of early gastrointestinal tumor screening and intraoperative guidance. In the application of diagnosing gastrointestinal diseases, a key step of OCT image intelligent analysis system is to segment the tissues and layers accurately. In this paper, we propose a new encoder-decoder network named PDTANet, which contains a global context-guided PDFF module and a lightweight attention-aware triplet attention (TA) mechanism. Moreover, during the model training stage, we adopt a region-aware and boundary-aware hybrid loss function to learn and update model parameters. The proposed PDTANet model has been applied for automatic tumor segmentation of guinea pig colorectal OCT images. The experimental results show that our proposed PDTANet model has the ability to focus on and connect global context and important feature information for OCT images. Compared with the prediction results of the model trained by the traditional Unet model and Dice loss function, the PDTANet model and a combination of dice and boundary related loss function proposed as the hybrid loss function proposed in this paper have significantly improved the accuracy of the segmentation of tissue boundaries, especially the surface Dice metric, which is improved by about 3%.
Postoperative pain poses a significant challenge to the healthcare system and patient satisfaction and is associated with chronic pain and long-term narcotic use. However, systemic assessment of the quality of postoperative pain management in China remains unavailable.In this cross-sectional study, we analyzed data collected from a nationwide registry, China Acute Postoperative Pain Study (CAPOPS), between September 2019 and August 2021. Patients aged 18 years or above were required to complete a self-reported pain outcome questionnaire on the first postoperative day (POD1). Perioperative pain management and pain-related outcomes, including the severity of pain, adverse events caused by pain or pain management, and perception of care and satisfaction with pain management were analyzed.A total of 26,193 adult patients were enrolled. There were 48.7% of patients who had moderate-to-severe pain on the first day after surgery, and pain severity was associated with poor recovery and patient satisfaction. The systemic opioid use was 68% on the first day after surgery, and 89% of them were used with intravenous patient-controlled analgesia, while the rate of postoperative nerve blocks was low.Currently, almost half of patients still suffer from moderate-to-severe pain after surgery in China. The relatively high rate of systemic opioid use and low rate of nerve blocks used after surgery suggests that more effort is needed to improve the management of acute postoperative pain in China.National Key Research and Development Program of China (No. 2018YFC2001905).
The olivocerebellar circuitry is important to convey both motor and non-motor information from the inferior olive (IO) to the cerebellar cortex. Several methods are currently established to observe the dynamics of the olivocerebellar circuitry, largely by recording the complex spike activity of cerebellar Purkinje cells; however, these techniques can be technically challenging to apply in vivo and are not always possible in freely behaving animals. Here, we developed a method for the direct, accessible, and robust recording of climbing fiber (CF) Ca2+ signals based on optical fiber photometry. We first verified the IO stereotactic coordinates and the organization of contralateral CF projections using tracing techniques and then injected Ca2+ indicators optimized for axonal labeling, followed by optical fiber-based recordings. We demonstrated this method by recording CF Ca2+ signals in lobule IV/V of the cerebellar vermis, comparing the resulting signals in freely moving mice. We found various movement-evoked CF Ca2+ signals, but the onset of exploratory-like behaviors, including rearing and tiptoe standing, was highly synchronous with recorded CF activity. Thus, we have successfully established a robust and accessible method to record the CF Ca2+ signals in freely behaving mice, which will extend the toolbox for studying cerebellar function and related disorders.
The sensory neocortex has been suggested to be a substrate for long-term memory storage, yet which exact single cells could be specific candidates underlying such long-term memory storage remained neither known nor visible for over a century. Here, using a combination of day-by-day two-photon Ca2+ imaging and targeted single-cell loose-patch recording in an auditory associative learning paradigm with composite sounds in male mice, we reveal sparsely distributed neurons in layer 2/3 of auditory cortex emerged step-wise from quiescence into bursting mode, which then invariably expressed holistic information of the learned composite sounds, referred to as holistic bursting (HB) cells. Notably, it was not shuffled populations but the same sparse HB cells that embodied the behavioral relevance of the learned composite sounds, pinpointing HB cells as physiologically-defined single-cell candidates of an engram underlying long-term memory storage in auditory cortex.
In this work, we investigate the statistical computation of the Boltzmann entropy of statistical samples. For this purpose, we use both histogram and kernel function to estimate the probability density function of statistical samples. We find that, due to coarse-graining, the entropy is a monotonic increasing function of the bin width for histogram or bandwidth for kernel estimation, which seems to be difficult to select an optimal bin width/bandwidth for computing the entropy. Fortunately, we notice that there exists a minimum of the first derivative of entropy for both histogram and kernel estimation, and this minimum point of the first derivative asymptotically points to the optimal bin width or bandwidth. We have verified these findings by large amounts of numerical experiments. Hence, we suggest that the minimum of the first derivative of entropy be used as a selector for the optimal bin width or bandwidth of density estimation. Moreover, the optimal bandwidth selected by the minimum of the first derivative of entropy is purely data-based, independent of the unknown underlying probability density distribution, which is obviously superior to the existing estimators. Our results are not restricted to one-dimensional, but can also be extended to multivariate cases. It should be emphasized, however, that we do not provide a robust mathematical proof of these findings, and we leave these issues with those who are interested in them.
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