A comparative study on clinical characterizations between acute myelitis onset of neuromyelitis optica spectrum disease and idiopathic transverse myelitis

ABSTRACT

Background/Aims

Both of neuromyelitis optica spectrum disease (NMOSDs) and idiopathic transverse myelitis (ITM) could present as acute transverse myelitis. However, long-term immunological treatment and prognosis are different for high recurrence of NMOSDs. In this study, we summarized clinical differences between acute attack myelitis of NMOSDs and ITM, we further screened serum auto-antibodies to help understand the two distinct clinical entities.     

Serum vitamin D status in type 2 diabetic patients from Gaza Strip

ObjectiveTo assess serum vitamin D status and its relations to other biochemical parameters in type 2 diabetic patients from Gaza Strip.Materials and methodsThis case-control study included 58 type 2 diabetic patients as well as 58 non-diabetic controls. Patients and controls were matched for age and gender. Data were obtained from questionnaire interview, and biochemical analysis of blood samples.ResultsSerum vitamin D was significantly lower in diabetic patients compared to non-diabetic controls (25.9 ± 11.0 versus 34.6 ± 13.8 ng/dl, % difference = 28.8%, P < 0.001). The number of patients having vitamin D deficient, insufficient and sufficient were 6 (10.4%), 35 (60.3%) and 17 (29.3%) compared to controls of 3 (5.2%), 16 (27.6%) and 39 (67.2%), respectively (χ² = 14.672, P < 0.001). Serum glucose, glycated hemoglobin (HbA1c), serum alanine aminotransferase (ALT), aspartate aminotransferase (AST) and triglycerides were significantly higher in patients than in controls whereas serum insulin, high density lipoprotein cholesterol (HDL-C) and calcium were significantly lower in patients. Serum vitamin D showed significant negative correlations with HbA1c (r = ? 0.186, P = 0.046), ALT (r = ? 192, P = 0.040) and AST (r = ? 0.188, P = 0.044) whereas significant positive correlations were found with HDL-C (r = 0.188, P = 0.044) and calcium (r = 0.239, P = 0.010).ConclusionThe significant negative and positive correlations of vitamin D with HbA1c and calcium, respectively suggests that vitamin D supplementation would be of potential therapeutic value in clinical settings for controlling of type 2 diabetes and more importantly its complications. However, a well-designed clinical trials are needed to define the contribution of vitamin D status and therapy in the global diabetes problem.     

Asymmetrically Substituted Poly(diitaconates) Obtained by Reversible Addition‐Fragmentation Chain Transfer (RAFT) Polymerization: Synthesis,Copolymerization Parameters,and Antimicrobial Activity

Asymmetrically substituted poly(diitaconate) copolymers are synthesized from 1‐((N‐tert‐butoxycarbonyl)‐2‐aminoethyl)‐4‐propyl diitaconate (PrIA) and different comonomers (N,N‐dimethyl‐acrylamide, DMAA; acrylic acid; or ((N‐tert‐butoxycarbonyl)‐2‐aminoethyl)methacrylate) by reversible addition–fragmentation chain transfer polymerization (RAFT). The RAFT copolymerization parameters of PrIA and DMAA are r_DMAA = 0.49 and r_PrIA = 0.17, compared to r_DMAA = 0.52 and r_PrIA = 0.54 obtained by free radical copolymerization (FRP). Thus, the RAFT process has a stronger trend to alternating polymerization than the FRP process. The polydispersity index of the RAFT copolymers is around 1.2–1.8, compared to 2.8–2.9 for the corresponding FRP copolymers. After removal of the tert‐butoxycarbonyl protective groups, antimicrobially active synthetic mimics of antimicrobial peptides are obtained. The thus activated poly(PrIA‐co‐DMAA) copolymers (repeat unit ratio 1:1) have an increasing activity against Escherichia coli and Staphylococcus aureus with increasing molar mass. The RAFT copolymers are slightly more active and less toxic than comparable FRP polymers, leading to a higher selectivity for bacteria over mammalian cells. Higher molar fractions of PrIA in poly(PrIA‐co‐DMAA) copolymers (up to 80 mol%) do not increase their antimicrobial activity; reduction of the BuIA content in poly(BuIA‐DMAA) (down to 10 mol%) leads to a loss of activity against both E. coli and S. aureus.     

Intraductal carcinoma of the prostate: What we know and what we do not know

Intraductal carcinoma of the prostate (IDC-P) is a malignant, clonal proliferation of cells growing within the basement membrane-bound structures of the prostate. IDC-P is usually associated with unfavorable clinicopathologic parameters such as large tumor volume, high-grade Gleason score, extra prostatic extension and seminal vesicle invasion. Majority of laboratory and patient data suggest that IDC-P represents intraductal spread of invasive carcinoma, rather than a precursor lesion. Additionally, relationship of IDC-P and adjacent invasive carcinoma has been investigated in a series of molecular studies. The differential diagnosis of IDC-P from other lesions is critical for patient management. In this article, we summarize current literatures regarding what we know about IDC-P, including its pathological morphology, incidence, differential diagnosis, molecular features and clinical significance. In addition, we propose several issues that we currently do not know about IDC-P. Further research is needed to better understand the biological nature of IDC-P.     

Effect of long‐chain triglyceride lipid emulsion on bupivacaine‐induced changes in electrophysiological parameters of rabbit Purkinje cells

Lipid emulsions are used in the reversal of local anesthetic toxicity. The aim of this study was to investigate the cellular electrophysiological effects of long‐chain triglyceride lipid emulsion (LCTE) on cardiac action potential characteristics and conduction disturbances induced by bupivacaine. Purkinje fibers were dissected from the left ventricle of New Zealand white rabbit hearts and superfused with either Tyrode's solution during 30 min (control group), with bupivacaine 10^?6 m , 10^?5 m , and 5.10^?5 m alone, or in the presence of LCTE 0.5%, in addition, LCTE at 0.1%, 0.5%, and 1% was perfused alone. Electrophysiological parameters were recorded using the conventional microelectrode technique (37 °C, 1 Hz frequency). Bupivacaine 5.10^?5 m ‐induced conduction blocks (8/8 preparations): LCTE 0.5% suppressed the bupivacaine 5.10^?5 m ‐induced conduction blocks (1/8 preparations). Exposure to bupivacaine 10^?6 m , 10^?5 m , and 5.10^?5 m resulted in a significant decrease in the maximal rate of depolarization (V_max) (respectively, 25%, 55%, 75%; P < 0.002 vs. control group). In the presence of LCTE 0.5%, bupivacaine 10^?6 m did not significantly decreased V_max (13%; P = 0.10 vs. control group). The decrease in V_max resulting from bupivacaine 10^?5 m alone was significantly less in the presence of LCTE 0.5% (P < 0.01 vs. bupivacaine 10^?5 m alone). Exposure to bupivacaine 10^?6 m , 10^?5 m , and 5.10^?5 m alone or in the presence of LCTE 0.5% resulted in a significant decrease in action potential duration measured at 50% and 90% repolarization (APD₅₀ and APD₉₀; P < 0.01 vs. control group). LCTE inhibited the Purkinje fibers conduction blocks induced by bupivacaine. Moreover, LCTE 0.5% attenuates the decrease in V_max induced by bupivacaine 10^?6 m and 10^?5 m .     

Emotion recognition from physiological signals

Emotion recognition is one of the great challenges in human–human and human–computer interaction. Accurate emotion recognition would allow computers to recognize human emotions and therefore react accordingly. In this paper, an approach for emotion recognition based on physiological signals is proposed. Six basic emotions: joy, sadness, fear, disgust, neutrality and amusement are analysed using physiological signals. These emotions are induced through the presentation of International Affecting Picture System (IAPS) pictures to the subjects. The physiological signals of interest in this analysis are: electromyogram signal (EMG), respiratory volume (RV), skin temperature (SKT), skin conductance (SKC), blood volume pulse (BVP) and heart rate (HR). These are selected to extract characteristic parameters, which will be used for classifying the emotions. The SVM (support vector machine) technique is used for classifying these parameters. The experimental results show that the proposed methodology provides in general a recognition rate of 85% for different emotional states.