Karpal Tünel Sendromu Dekompresyon Cerrahisi Geçiren Hastaların Geç Dönem Memnuniyet Düzeylerini Değerlendirmede Elektromiyografi ve Hasta Değerlendirme Ölçümünün Geçerliliği

Objective: This study investigated whether electromyelography (EMG) evaluation is helpful in the late phase after surgical treatment of carpal tunnel syndrome (CTS). Methods: This retrospective study included 35 patients who underwent mini-open decompression therapy between 2008 and 2011 with CTS diagnosis. Patients were assessed electrophysiologically and clinically with Patient Evaluation Measurement (PEM) scoring and handgrip, palmar grip, lateral grip, and fingertip grip strength. Additionally, patients' clinical scores and strength values were compared with electrophysiologic values from preoperative and postoperative 4-year controls. Results: According to the Padua classification, EMG data were classified before and after surgery. One patient had extreme grade, four patients had severe grade, 26 patients had moderate grade, and four had a mild grade before surgery. At the postoperative 4th year EMG follow-up, six patients were classified as minimal and 29 as negative. According to the PEM scale, the mean score before surgery was 58.77±7.89, and in the controls at the 4th year after surgery, the mean score was 13.48±4.01. The strength of the operated hand was significantly weaker than that of the contralateral healthy hand before surgery. However, in the controls at the 4th year after surgery, the strength of the operated hand was significantly increased compared with the preoperative period, and there was no significant difference from the contralateral hand. Conclusion: Electrophysiological assessment (EMG) in the late phase after surgical treatment of CTS has positive parallels with clinical assessment and strength assessment. Therefore, we conclude that EMG helps follow late surgical outcomes. © Copyright 2022 by Medical Journal of Bakırköy published by Galenos Yayınev

Bioactive (3Z,5E)-11,20-Epoxybriara-3,5-dien-7,18-olide Diterpenoids from the South China Sea Gorgonian Dichotella gemmacea

Six new (3Z,5E)-11,20-epoxybriara-3,5-dien-7,18-olide diterpenoids, gemmacolides N–S (1–6), were isolated together with four known analogues, juncenolide D, and juncins R, S and U (7–10), from the South China Sea gorgonian Dichotella gemmacea. The structures of the new compounds were elucidated by the detailed analysis of spectroscopic data in combination with the comparison with reported data. The absolute configuration of 1 was determined by a TDDFT calculation of its solution ECD spectrum, affording the determination of absolute configuration of other analogues by simply comparing their ECD spectra with that of 1. The cytotoxic and antimicrobial activities of these compounds were evaluated. In preliminary in vitro bioassays, compounds 4, 5, 6, 8 and 9 showed cytotoxicity against A549 and MG63, while compounds 1, 2, 4, 7–10 showed antimicrobial activity against the fungus Septoria tritici and the bacterium Escherichia coli

Introducing organic metallic salts to enhance capacitive energy storage of carbon nanofibers

A suitable form of precursor carbon is a great importance for electrochemical performance of carbon materials for supercapacitor applications. Herein, we investigate the addition of organic bimetallic salts to polymer precursor for the fabrication of carbon nanofiber (CNF). The presence of additional pore structures is beneficial for transfer of electrolytes by providing more active sites and improving electrochemical performance. Compared with the samples without any metallic salts, the activated electrode shows a high specific surface area of 420 m(2) g(-1) and outstanding specific capacitance of 460 F g(-1) at 1 A g(-1). The capacitance retention shows that it retains 95.6% of initial capacitance up to 1000 cycles and 76.5% even after 9000 cycles. A high specific energy of 16 Wh kg(-1) at 250 W kg(-1) is also obtained. This strategy holds a great promise for use in energy-related applications

Assisting humans in privacy management: an agent-based approach

Image sharing is a service offered by many online social networks. In order to preserve privacy of images, users need to think through and specify a privacy setting for each image that they upload. This is difficult for two main reasons: first, research shows that many times users do not know their own privacy preferences, but only become aware of them over time. Second, even when users know their privacy preferences, editing these privacy settings is cumbersome and requires too much effort, interfering with the quick sharing behavior expected on an online social network. Accordingly, this paper proposes a privacy recommendation model for images using tags and an agent that implements this, namely pelte. Each user agent makes use of the privacy settings that its user have set for previous images to predict automatically the privacy setting for an image that is uploaded to be shared. When in doubt, the agent analyzes the sharing behavior of other users in the user’s network to be able to recommend to its user about what should be considered as private. Contrary to existing approaches that assume all the images are available to a centralized model, pelte is compatible to distributed environments since each agent accesses only the privacy settings of the images that the agent owner has shared or those that have been shared with the user. Our simulations on a real-life dataset shows that pelte can accurately predict privacy settings even when a user has shared a few images with others, the images have only a few tags or the user’s friends have varying privacy preferences