Association of Plasma Ghrelin Levels with Insulin Resistance in Type 2 Diabetes Mellitus among Saudi Subjects

Ali Ahmed Al Qarni,Faris Elbahi Joatar,Nagalla Das,Mohamed Awad,Mona Eltayeb,Ahmed Gasim Al-Zubair,Muhalab E. Ali,Abdulaziz Al Masaud,Abdirashid M. Shire,Khalid Gumaa,Hayder A. Giha 대한내분비학회 2017 Endocrinology and metabolism Vol.32 No.2

Background: Although the exact mechanism of insulin resistance (IR) has not yet been established, IR is the hallmark characteristic of type 2 diabetes mellitus (T2DM). The aim of this study was to examine the relationship between plasma ghrelin levels and IR in Saudi subjects with T2DM. Methods: Patients with T2DM (n=107, cases) and non-diabetic apparently healthy subjects (n=101, controls) from Saudi Arabia were included in this study. The biochemical profiles and plasma insulin levels of all subjects were analyzed, and IR was estimated using the homeostatic model assessment of insulin resistance (HOMA-IR) index. Active ghrelin levels in plasma were measured using the radioimmunoassay technique. Results: Only 46.7% (50 of 107) of the T2DM subjects had IR, including 26% (28 of 107) with severe IR (HOMA-IR ≥5), while 5.9% (six of 101) of the controls had moderate IR (3≤ HOMA-IR <5). HOMA-IR values were not associated with age, disease duration, or gender. Importantly, T2DM itself and the co-occurrence of IR with T2DM were significantly associated with low plasma ghrelin levels. However, ghrelin levels were inversely correlated with the HOMA-IR index, body weight, and fasting plasma insulin levels, mainly in the control subjects, which was indicative of the breakdown of metabolic homeostasis in T2DM. Conclusion: The prevalence of IR was relatively low, and IR may be inversely associated with plasma ghrelin levels among Saudi patients with T2DM.

Facial Skin Texture as a Source of Biometric Information

Garsah Farhan Al-Qarni,Farzin Deravi 보안공학연구지원센터(IJSIP) 2012 International Journal of Signal Processing, Image Vol.5 No.4

In Vitro Apoptosis Triggering in the BT-474 Human Breast Cancer Cell Line by Lyophilised Camel's Milk

Hasson, Sidgi S.A.A,Al-Busaidi, Juma Zaid,Al-Qarni, Zahra A.M.,Rajapakse, S.,Al-Bahlani, Shadia,Idris, Mohamed Ahmed,Sallam, Talal A. Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.15

Breast cancer is a global health concern and is a major cause of death among women. In Oman, it is the most common cancer in women, with an incidence rate of 15.6 per 100,000 Omani females. Various anticancer remedies have been discovered from natural products in the past and the search is continuing for additional examples. Cytotoxic natural compounds may have a major role in cancer therapy either in potentiating the effect of chemotherapy or reducing its harmful effects. Recently, a few studies have reported advantages of using crude camel milk in treating some forms of cancer. However, no adequate data are available on the lyophilised camel's milk responsibility for triggering apoptosis and oxidative stress associated with human breast cancer. The present study aimed to address the role of the lyophilised camel's milk in inducing proliferation repression of BT-474 and HEp-2 cells compared with the non-cancer HCC1937 BL cell line. Lyophilized camel's milk fundamentally repressed BT-474 cells growth and proliferation through the initiation of either the intrinsic and extrinsic apoptotic pathways as indicated by both caspase-3 mRNA and its action level, and induction of death receptors in BT-474 but not the HEp-2 cell line. In addition, lyophilised camel's milk enhanced the expression of oxidative stress markers, heme-oxygenase-1 and reactive oxygen species production in BT-474 cells. Increase in caspase-3 mRNA levels by the lyophilised camel's milk was completely prevented by the actinomycin D, a transcriptional inhibitor. This suggests that lyophilized camel's milk increased newly synthesized RNA. Interestingly,it significantly (p<0.003) repressed the growth of HEp-2 cells and BT-474 cells after treatment for 72 hours while 24 hours treatment repressed BT-474 cells alone. This finding suggests that the lyophilised camel's milk might instigate apoptosis through initiation of an alternative apoptotic pathway.

Impact of ZrO₂ nanoparticles addition on flexural properties of denture base resin with different thickness

Albasarah, Sara,Al Abdulghani, Hanan,Alaseef, Nawarah,al-Qarni, Faisal D.,Akhtar, Sultan,Khan, Soban Q.,Ateeq, Ijlal Shahrukh,Gad, Mohammed M. The Korean Academy of Prosthodonitics 2021 The Journal of Advanced Prosthodontics Vol.13 No.4

PURPOSE. This study aimed to evaluate the effect of incorporating zirconium oxide nanoparticles (nano-ZrO₂) in polymethylmethacrylate (PMMA) denture base resin on flexural properties at different material thicknesses. MATERIALS AND METHODS. Heat polymerized acrylic resin specimens (N = 120) were fabricated and divided into 4 groups according to denture base thickness (2.5 mm, 2.0 mm, 1.5 mm, 1.0 mm). Each group was subdivided into 3 subgroups (n = 10) according to nano-ZrO₂ concentration (0%, 2.5%, and 5%). Flexural strength and elastic modulus were evaluated using a three-point bending test. One-way ANOVA, Tukey's post hoc, and two-way ANOVA were used for data analysis (α = .05). Scanning electron microscopy (SEM) was used for fracture surface analysis and nanoparticles distributions. RESULTS. Groups with 0% nano-ZrO₂ showed no significant difference in the flexural strength as thickness decreased (P = .153). The addition of nano-zirconia significantly increased the flexural strength (P < .001). The highest value was with 5% nano-ZrO₂ and 2 mm-thickness (125.4 ± 18.3 MPa), followed by 5% nano-ZrO₂ and 1.5 mm-thickness (110.3 ± 8.5 MPa). Moreover, the effect of various concentration levels on elastic modulus was statistically significant for 2 mm thickness (P = .001), but the combined effect of thickness and concentration on elastic modulus was insignificant (P = .10). CONCLUSION. Reinforcement of denture base material with nano-ZrO₂ significantly increased flexural strength and modulus of elasticity. Reducing material thickness did not decrease flexural strength when nano-ZrO₂ was incorporated. In clinical practice, when low thickness of denture base material is indicated, PMMA/nano-ZrO₂ could be used with minimum acceptable thickness of 1.5 mm.

Leu72Met and Other Intronic Polymorphisms in the GHRL and GHSR Genes Are Not Associated with Type 2 Diabetes Mellitus, Insulin Resistance, or Serum Ghrelin Levels in a Saudi Population

Faris Elbahi Joatar,Ali Ahmed Al Qarni,Muhalab E. Ali,Abdulaziz Al Masaud,Abdirashid M. Shire,Nagalla Das,Khalid Gumaa,Hayder Ahmed Giha 대한내분비학회 2017 Endocrinology and metabolism Vol.32 No.3

Background: Ghrelin (GHRL), a gastric peptide encoded by the GHRL gene, is known to be involved in energy homeostasis via its G protein receptor, encoded by the growth hormone secretagogue receptor (GHSR) gene. Some studies have shown associations between plasma GHRL levels and GHRL single-nucleotide polymorphisms (SNPs), namely the Leu72Met polymorphism (rs696217 TG), with type 2 diabetes mellitus (T2DM) and insulin resistance (IR), while others have not. The controversies in these associations raise the issue of ‘which SNPs in which populations.’ The aim of this study was to investigate whether SNPs in GHRL and/or GHSR genes were associated with T2DM, IR, or plasma GHRL levels among Arab Saudis. Methods: Blood was collected from 208 Saudi subjects with (n=107) and without (n=101) T2DM. DNA samples from these subjects were analyzed by real-time polymerase chain reaction to genotype five intronic SNPs in the GHRL (rs696217 TG, rs27647 CT, rs2075356 CT, and rs4684677 AT) and GHSR (rs509030 GC) genes. In addition, plasma GHRL levels were measured by a radioimmunoassay. Results: None of the SNPs were associated with T2DM, IR, or plasma GHRL levels. The frequencies of the alleles, genotypes, and haplotypes of the five SNPs were comparable between the T2DM patients and the non-diabetic subjects. A large number of the GHRL haplotypes indicates the molecular heterogeneity of the preproghrelin gene in this region. Conclusion: Neither the Leu72Met polymorphism nor the other intronic GHRL and GHSR SNPs were associated with T2DM, IR, or GHRL levels. Further investigations should be carried out to explain the molecular basis of the association of the GHRL peptide with T2DM and IR.

Exploring the Feasibility of Neural Networks for Criminal Propensity Detection through Facial Features Analysis

Amal Alshahrani,Sumayyah Albarakati,Reyouf Wasil,Hanan Farouquee,Maryam Alobthani,Someah Al-Qarni International Journal of Computer ScienceNetwork S 2024 International journal of computer science and netw Vol.24 No.5

While artificial neural networks are adept at identifying patterns, they can struggle to distinguish between actual correlations and false associations between extracted facial features and criminal behavior within the training data. These associations may not indicate causal connections. Socioeconomic factors, ethnicity, or even chance occurrences in the data can influence both facial features and criminal activity. Consequently, the artificial neural network might identify linked features without understanding the underlying cause. This raises concerns about incorrect linkages and potential misclassification of individuals based on features unrelated to criminal tendencies. To address this challenge, we propose a novel region-based training approach for artificial neural networks focused on criminal propensity detection. Instead of solely relying on overall facial recognition, the network would systematically analyze each facial feature in isolation. This fine-grained approach would enable the network to identify which specific features hold the strongest correlations with criminal activity within the training data. By focusing on these key features, the network can be optimized for more accurate and reliable criminal propensity prediction. This study examines the effectiveness of various algorithms for criminal propensity classification. We evaluate YOLO versions YOLOv5 and YOLOv8 alongside VGG-16. Our findings indicate that YOLO achieved the highest accuracy 0.93 in classifying criminal and non-criminal facial features. While these results are promising, we acknowledge the need for further research on bias and misclassification in criminal justice applications