The study aimed to establish the association of miR-153-3p expression with treatment response to IM in CML patients. Sixty CML patients were included and divided into two groups consistent with their response to treatment whether sensitive or resistant to IM. Ten healthy normal participants were enrolled as control group. RNA was extracted from serum to work out miR-153-3p expression utilizing real-time quantitative reverse transcription polymerase chain reaction. The primers were supplied by Macrogen Inc. Twenty seven patients were sensitive to imatinib and 33 were resistant to imatinib. The ratio of male to female was 1.14:1. The bulk (58%) of patients were within the age range of 41-60 years. Weight and gender did not significantly diffe

ackground An autoimmune and inflammatory illness called rheumatoid arthritis (RA) occurs when your immune system mistakenly attacks normal cells in your body. Interleukin-35 is a brand-new cytokine that belongs to the immunosuppressive and anti-inflammatory IL-12 family. β -herpesvirus that produces inflammation and stays dormant in its host for life is the human cytomegalovirus. Human herpesvirus (HCMV) has been at the core of several RA-related theories. Objective The current study looked at the association between RA and serum IL-35 levels as well as the association between RA and CMV. Patients and methods Blood samples were taken in the Baghdad Teaching Hospital and Typical Rheumatology Unit from January 2022 to Mars 2022 for the curre

Vitiligo is an acquired idiopathic skin disorder characterized by depigmented macules due to loss of cutaneous melanocytes. A potential role of the immune dysfunction has been suggested in vitiligo, so to test this hypothesis, certain cytokines (IL-17A and TNF-?) and immunoglobulins (IgM, IgG, IgA and total IgE) were investigated in all participants. The study included: 60 patients with age range between (6-55) year; 30(11 males and 19 females) were untreated and 30(12 males and 18 females) were treated with Narrow Band Ultraviolet-B (NB-UVB) and 30 (14 males and 16 females) apparently healthy control. Serum was separated and cytokines (IL-17A and TNF-?) and total immunoglobulin E (IgE) were detected by using Enzyme Linked Immunosorbent Ass

In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15