The nature and intensity of the association of myasthenia gravis (MG) with distinct human leukocyte antigen (HLA) haplotypes differ between ethnic populations, so this study determined the association of HLA class II antigens with myasthenia gravis (MG) in Iraq.The study included Iraqi patients diagnosed with MG and two control groups the first of 54 insulin dependent diabetes mellitus patients and the second of 237 subjects as a normal control group. The test used was microlymphocytotoxicity test.The work was done in the Teaching Laboratories/Medical City/Baghdad.Results: positive associations were observed (etiological risk factors) as follows: 1. HLA-DR locus showed one positively associated allele when compared to healthy control and this was HLA-DR3 (RR: 21.05, EF0.73, & P value ? 0.05), While when compared to IDDM control no significant association appeared (since the same allele is positively associated with IDDM). 2. HLA-DQ locus showed only one positively associated allele when compared to healthy control; this was HLA-DQ2 (RR 4.67, EF 0.50, and P value ? 0.05). While no significant association appeared when compared to IDDM control. Other important clinical association were observed; association with age, gender, strong stressful events, thymoma, and other autoimmune disorders. Conclusion: The positively associated antigens which were found as follows HLA-DR3 and HLA-DQ2, while no negative association was detected.
We report a new theranostic device based on lead sulfide quantum dots (PbS QDs) with optical emission in the near infrared wavelength range decorated with affibodies (small 6.5 kDa protein-based antibody replacements) specific to the cancer biomarker human epidermal growth factor receptor 2 (HER2), and zinc(II) protoporphyrin IX (ZnPP) to combine imaging, targeting and therapy within one nanostructure. Colloidal PbS QDs were synthesized in aqueous solution with a nanocrystal diameter of ∼5 nm and photoluminescence emission in the near infrared wavelength range. The ZHER2:432 affibody, mutated through the introduction of two cysteine residues at the C-terminus (
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Proxy-based sliding mode control PSMC is an improved version of PID control that combines the features of PID and sliding mode control SMC with continuously dynamic behaviour. However, the stability of the control architecture maybe not well addressed. Consequently, this work is focused on modification of the original version of the proxy-based sliding mode control PSMC by adding an adaptive approximation compensator AAC term for vibration control of an Euler-Bernoulli beam. The role of the AAC term is to compensate for unmodelled dynamics and make the stability proof more easily. The stability of the proposed control algorithm is systematically proved using Lyapunov theory. Multi-modal equation of motion is derived using the Galerkin metho
... Show MoreIn information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare
... Show MoreRecent studies have revealed some conflicting results about the health effects of caffeine. These studies are inconsistent in terms of design and population and source of consumed caffeine. In the current study, we aimed to evaluate the possible health effects of dietary caffeine intake among overweight and obese individuals.
In this cross-sectional study, 488 apparently healthy individuals with overweight and obesity were participated. Dietary intake was assessed by a Food Frequency Questionnaire (FFQ) and