A meta-analysis of surgical decompression in the treatment of diabetic peripheral neuropathy.

BACKGROUND: Over the last decade, surgical decompression procedures have been commonly used in the treatment of diabetic peripheral neuropathy (DPN). However, the effectiveness of them remains to be proved. METHODS: A comprehensive literature search of databases including PubMed-Medline, Ovid-Embase, and Cochrane Library was performed to collect the related literatures. The Medical Subject Headings used were "diabetic neuropathy," "surgical decompression," and "outcomes." The methodological index for nonrandomized studies was adopted for assessing the studies included in this review. Analyses were performed with Review Manager (Version 5.3, The Nordic Cochrane Centre, the Cochrane Collaboration, Copenhagen, 2014). RESULTS: A total of 12 literatures (including 8 prospective and 4 retrospective) encompassing 1825 patients with DPN were included in the final analysis. Only 1 literature was identified as a randomized-controlled trial. The remaining 11 literatures were observational studies; 7 of them were classified as upper-extremity nerve decompression group and 4 of them were classified as lower-extremity nerve decompression group. Meta-analysis shows that Boston questionnaire symptom severity and functional status of upper extremities, and distal motor latency and sensory conduction velocity of median nerve of DPN patients are significantly improved after carpal tunnel release. Besides, visual analog scale and 2-point discrimination are considered clinically and statistically significant in lower extremities after operation. CONCLUSIONS: The findings from our review have shown the efficacy of surgical decompression procedures in relieving the neurologic symptoms and restoring the sensory deficits in DPN patients. As there are few high-quality randomized-controlled trials or well-designed prospective studies, more data are needed to elucidate the role of surgical procedures for DPN treatment in the future.

[Evaluation and selection of VOCs treatment technologies in packaging and printing industry].

Volatile organic compounds (VOCs) play an important role in urban air pollution. Activities of industries including the packaging and printing industries are regarded as the major sources. How to select the suitable treating techniques is the major problem for emission control. In this article, based on the VOCs emission characteristics of the packaging and printing industry and the existing treatment technologies, using the analytic hierarchy process (AHP) model, an evaluation system for VOCs selection was established and all the technologies used for treatment were assessed. It showed that the priority selection was in the following order: Carbon Fiber Adsorption-Desorption > Granular Carbon Adsorption-Desorption > Thermal Combustion > Regenerative Combustion > Catalytic combustion > Rotary adsorption-concentration and combustion > Granular Carbon adsorption-concentration and combustion. Carbon Fiber Adsorption-Desorption was selected as the best available technology due to its highest weight among those technologies.

[Preparation by different methods and characterization of desulfurization mixed oxides derived from hydrotalcites].

Hydrotalcite-based MgAl mixed oxides were synthesized by urea hydrolysis and constant-pH coprecipitation methods, and characterized by means of X-ray diffraction (XRD) , thermal gravity analysis-differential thermal gravity (TG-DTG) , scanning electron microscope (SEM), N2-adsorption/desorption and CO2 temperature programmed desorption (CO2-TPD), and their adsorption performances for SO2 were also tested. It was found that MgAl mixed oxides prepared by coprecipitation method would facilitate the catalyst to maintain a high specific area (148. 1 m2.g-1) and more basic sites, which resulted in higher SO2 adsorption capacity and velocity. The SO2 adsorption capacity of the mixed oxides prepared by urea hydrolysis and constant-pH coprecipitation methods were 0.55 g.g-1and 0. 79 gg-1 respectively at 700 degreeC.