Conjugated linoleic acid attenuates neuropathic pain induced by sciatic nerve in mice

Purpose: Conjugated linoleic acid (CLA) has been suggested to be necessary for human health, but there is limited research regarding its effect on neuropathic pain (NP). Here, we aim to investigate the potential effect of CLA administration on NP development and nerve recovery. Methods: Forty mice were divided into four equal groups randomly. The mice in control group underwent a sham operation to achieve a unilateral sciatic nerve cut. Other groups were subjected to partial sciatic nerve ligation (PSNL) surgery followed by 4 weeks of CLA treatment. Behavioral tests were performed shortly before mice were sacrificed. Blood, sciatic nerve and spinal cord tissues were collected after sacrifice. Electron microscopy was performed to determine myelin thickness and calculate myelin thickness/axon diameter ratio. Results: Mice that received daily oral CLA treatment for 4 weeks after PSNL surgery showed less mechanical and thermal allodynia than mice in PSNL surgery alone group. Behavioral tests showed that CLA treatment was associated with marked increases in both nerve conduction velocity (NCV) and force of gastrocnemius contraction. In addition, CLA reduced the levels of interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α), sciatic myeloperoxidase (MPO) activity, and activating transcription factor-3 (ATF-3) expression. CLA also restored mitochondrial manganese superoxide dismutase (MnSOD) activity which was decreased in the sciatic nerves and spinal cords of the PSNL surgery group. Regeneration of myelins and axons in nerve fibers in CLA group was faster and more complete than that in the vehicle group. Conclusion: The current study demonstrates that CLA effectively attenuates NP and significantly inhibits neuro-inflammation and oxidative stress. This treatment improves sciatic nerve form and function after injury, suggesting that it can attenuate NP

Early results of quality of life for curatively treated rectal cancers in Chinese patients with EORTC QLQ-CR29

<p>Abstract</p> <p>Purpose</p> <p>To assess the quality of life in curatively treated patients with rectal cancer in a prospectively collected cohort.</p> <p>Methods</p> <p>Patients with stage I-III rectal cancer who were treated curatively in a single institution were accrued prospectively. Quality of life was assessed by use of the European Organization for Research and Treatment of Cancer questionnaire module for all cancer patients (QLQ-C30) and for colorectal cancer patients (QLQ-CR29). Quality of life among different treatment modalities and between stoma and nonstoma patients was evaluated in all patients.</p> <p>Results</p> <p>A total of 154 patients were assessed. The median time of completion for the questionnaires was 10 months after all the treatments. For patients with different treatment modalities, faecal incontinence and diarrhea were significantly higher in radiation group (p = 0.002 and p = 0.001, respectively), and no difference in male or female sexual function was found between radiation group and non-radiation group. For stoma and nonstoma patients, the QLQ-CR29 module found the symptoms of Defaecation and Embarrassment with Bowel Movement were more prominent in stoma patients, while no difference was detected in scales QLQ-C30 module.</p> <p>Conclusions</p> <p>Our study provided additional information in evaluating QoL of Chinese rectal cancer patients with currently widely used QoL questionnaires. As a supplement to the QLQ-C30, EORTC QLQ-CR29 is a useful questionnaire in evaluating curatively treated patients with rectal cancer. Bowel dysfunction (diarrhea and faecal incontinence) was still the major problem compromising QoL in patients with either pre- or postoperative chemoradiotherapy.</p

Immunohistochemical localization of mu opioid receptor in the marginal division with comparison to patches in the neostriatum of the rat brain

<p>Abstract</p> <p>Background</p> <p>Mu opioid receptor (MOR), which plays key roles in analgesia and also has effects on learning and memory, was reported to distribute abundantly in the patches of the neostriatum. The marginal division (MrD) of the neostriatum, which located at the caudomedial border of the neostriatum, was found to stain for enkephalin and substance P immunoreactivities and this region was found to be involved in learning and memory in our previous study. However, whether MOR also exists in the MrD has not yet been determined.</p> <p>Methods</p> <p>In this study, we used western blot analysis and immunoperoxidase histochemical methods with glucose oxidase-DAB-nickel staining to investigate the expression of MOR in the MrD by comparison to the patches in the neostriatum.</p> <p>Results</p> <p>The results from western blot analyses revealed that the antibody to MOR detected a 53 kDa protein band, which corresponded directly to the molecular weight of MOR. Immunohistochemical results showed that punctate MOR-immunoreacted fibers were observed in the "patch" areas in the rostrodorsal part of the neostriatum but these previous studies showed neither labelled neuronal cell bodies, nor were they shown in the caudal part of the neostriatum. Dorsoventrally oriented dark MOR-immunoreactive nerve fibers with individual labelled fusiform cell bodies were firstly observed in the band at the caudomedial border, the MrD, of the neostriatum. The location of the MOR-immunoreactivity was in the caudomedial border of the neostriatum. The morphology of the labelled fusiform neuronal somatas and the dorsoventrally oriented MOR-immunoreacted fibers in the MrD was distinct from the punctate MOR-immunoreactive diffuse mosaic-patterned patches in the neostriatum.</p> <p>Conclusions</p> <p>The results indicated that MOR was expressed in the MrD as well as in patches in the neostriatum of the rat brain, but with different morphological characteristics. The punctate MOR-immunoreactive and diffuse mosaic-patterned patches were located in the rostrodorsal part of the neostriatum. By contrast, in the MrD, the dorsoventrally parallel oriented MOR-immunoreactive fibers with individual labelled fusiform neuronal somatas were densely packed in the caudomedial border of the neostriatum. The morphological difference in MOR immunoreactivity between the MrD and the patches indicated potential functional differences between them. The MOR most likely plays a role in learning and memory associated functions of the MrD.</p

1H NMR-based metabolomics of paired tissue, serum and urine samples reveals an optimized panel of biofluids metabolic biomarkers for esophageal cancer

IntroductionThe goal of this study was to establish an optimized metabolic panel by combining serum and urine biomarkers that could reflect the malignancy of cancer tissues to improve the non-invasive diagnosis of esophageal squamous cell cancer (ESCC).MethodsUrine and serum specimens representing the healthy and ESCC individuals, together with the paralleled ESCC cancer tissues and corresponding distant non-cancerous tissues were investigated in this study using the high-resolution 600 MHz 1H-NMR technique.ResultsWe identified distinct 1H NMR-based serum and urine metabolic signatures respectively, which were linked to the metabolic profiles of esophageal-cancerous tissues. Creatine and glycine in both serum and urine were selected as the optimal biofluids biomarker panel for ESCC detection, as they were the overlapping discriminative metabolites across serum, urine and cancer tissues in ESCC patients. Also, the were the major metabolites involved in the perturbation of “glycine, serine, and threonine metabolism”, the significant pathway alteration associated with ESCC progression. Then a visual predictive nomogram was constructed by combining creatine and glycine in both serum and urine, which exhibited superior diagnostic efficiency (with an AUC of 0.930) than any diagnostic model constructed by a single urine or serum metabolic biomarkers.DiscussionOverall, this study highlighted that NMR-based biofluids metabolomics fingerprinting, as a non-invasive predictor, has the potential utility for ESCC detection. Further studies based on a lager number size and in combination with other omics or molecular biological approaches are needed to validate the metabolic pathway disturbances in ESCC patients

Benefits and risks of drug combination therapy for diabetes mellitus and its complications: a comprehensive review

Diabetes is a chronic metabolic disease, and its therapeutic goals focus on the effective management of blood glucose and various complications. Drug combination therapy has emerged as a comprehensive treatment approach for diabetes. An increasing number of studies have shown that, compared with monotherapy, combination therapy can bring significant clinical benefits while controlling blood glucose, weight, and blood pressure, as well as mitigating damage from certain complications and delaying their progression in diabetes, including both type 1 diabetes (T1D), type 2 diabetes (T2D) and related complications. This evidence provides strong support for the recommendation of combination therapy for diabetes and highlights the importance of combined treatment. In this review, we first provided a brief overview of the phenotype and pathogenesis of diabetes and discussed several conventional anti-diabetic medications currently used for the treatment of diabetes. We then reviewed several clinical trials and pre-clinical animal experiments on T1D, T2D, and their common complications to evaluate the efficacy and safety of different classes of drug combinations. In general, combination therapy plays a pivotal role in the management of diabetes. Integrating the effectiveness of multiple drugs enables more comprehensive and effective control of blood glucose without increasing the risk of hypoglycemia or other serious adverse events. However, specific treatment regimens should be tailored to individual patients and implemented under the guidance of healthcare professionals

Simultaneous Audio Encryption and Compression Using Parallel Compressive Sensing and Modified Toeplitz Measurement Matrix

With the explosive growth of voice information interaction, there is an urgent need for safe and effective compression transmission methods. In this paper, compressive sensing is used to realize the compression and encryption of speech signals. Firstly, the scheme of linear feedback shift register combined with inner product to generate measurement matrix is proposed. Secondly, we adopt a new parallel compressive sensing technique to tremendously improve the processing efficiency. Further, the two parties in the communication adopt public key cryptosystem to safely share the key and select a different measurement matrix for each frame of the voice signal to ensure the security. This scheme greatly reduces the difficulty of generating measurement matrix in hardware and improves the processing efficiency. Compared with the existing scheme by Moreno-Alvarado et al., our scheme has reduced the execution time by approximately 8%, and the mean square error (MSE) has also been reduced by approximately 5%

Short-Term Load Forecasting Based on Deep Learning Bidirectional LSTM Neural Network

Accurate load forecasting guarantees the stable and economic operation of power systems. With the increasing integration of distributed generations and electrical vehicles, the variability and randomness characteristics of individual loads and the distributed generation has increased the complexity of power loads in power systems. Hence, accurate and robust load forecasting results are becoming increasingly important in modern power systems. The paper presents a multi-layer stacked bidirectional long short-term memory (LSTM)-based short-term load forecasting framework; the method includes neural network architecture, model training, and bootstrapping. In the proposed method, reverse computing is combined with forward computing, and a feedback calculation mechanism is designed to solve the coupling of before and after time-series information of the power load. In order to improve the convergence of the algorithm, deep learning training is introduced to mine the correlation between historical loads, and the multi-layer stacked style of the network is established to manage the power load information. Finally, actual data are applied to test the proposed method, and a comparison of the results of the proposed method with different methods shows that the proposed method can extract dynamic features from the data as well as make accurate predictions, and the availability of the proposed method is verified with real operational data

General Dynamic Equivalent Modeling of Microgrid Based on Physical Background

Microgrid is a new power system concept consisting of small-scale distributed energy resources; storage devices and loads. It is necessary to employ a simplified model of microgrid in the simulation of a distribution network integrating large-scale microgrids. Based on the detailed model of the components, an equivalent model of microgrid is proposed in this paper. The equivalent model comprises two parts: namely, equivalent machine component and equivalent static component. Equivalent machine component describes the dynamics of synchronous generator, asynchronous wind turbine and induction motor, equivalent static component describes the dynamics of photovoltaic, storage and static load. The trajectory sensitivities of the equivalent model parameters with respect to the output variables are analyzed. The key parameters that play important roles in the dynamics of the output variables of the equivalent model are identified and included in further parameter estimation. Particle Swarm Optimization (PSO) is improved for the parameter estimation of the equivalent model. Simulations are performed in different microgrid operation conditions to evaluate the effectiveness of the equivalent model of microgrid