Background: In advanced diabetes mellitus, serum levels of the most hormones are altered due to several interplaying mechanisms. Objective: To assess the relation of serum leptin and lipid profile in type 2 diabetic nephropathy. Patients and Method: Serum leptin levels and its relation to lipid profile were estimated in 62 patients with type 2 diabetic nephropathy attending the National Diabetes Center in Al- Mustansiriya University, and (26) healthy individuals considered as control group. The diabetic patients were classified into three groups, (24) pathients with normoalbuminuria (21) patients with microalbuminuria and (17) patients with macroalbuminuria. Fasting plasma glucose, serum creatinine, Hb A1c %, lipid profile (Total cholesterol, LDL- Cholesterol, HDL- Cholesterol and Triglyceride) and urinary albumin, were measured to establish the possibility of using these biomarkers as a supplementary to serum leptin to be a diagnostic test for type 2 diabetic nephropathy. Results: Serum leptin levels showed a significant elevation in microalbuminuria (20.08± 4.50 ng/ml) and macroalbuminuria groups (22.35± 6.89 ng/ml) as compared to nondiabetic normal control group (10.64 ± 3.17 ng/ml). There was no significant differences observed in serum leptin levels between the normoalbuminuria group (13.96 ± 5.73 ng/ml) and healthy controls, but a significant positive differences were noticed in the levels of fasting plasma glucose, serum creatinine, Hb A1c% and lipid profile in the three patient groups in comparison with the control group. While no significant correlation was observed between these biomarkers levels and serum leptin values. Conclusion: It might be concluded that serum leptin levels were elevated in type 2 diabetic patients with microalbuminuria and macroalbuminuria, suggesting that renal leptin degradation is impaired in early stage of kidney damage and this impairment increase with the progression of this disease. Leptin hormone may consider according to these results as a risk factor for progression of kidney disease in diabetic patients.
HTH Ahmed Dheyaa Al-Obaidi,", Ali Tarik Abdulwahid', Mustafa Najah Al-Obaidi", Abeer Mundher Ali', eNeurologicalSci, 2023
In 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 MoreThis study includes synthesis of some nitrogenous heterocyclic compounds linked to amino acid esters or heterocyclic amines that may have a potential activity as antimicrobial and/or cytotoxic. Quinolines are an important group of organic compounds that possess useful biological activity as antibacterial, antifungal and antitumor .8-Hydroxyquinoline (8-HQ) and numerous of its derivatives exhibit potent activities against fungi and bacteria which make them good candidates for the treatment of many parasitic and microbial infection diseases.
These pharmacological properties of quinolones aroused our interest in synthesizing several new compounds featuring heterocyclic rings of the quinoline derivatives linke
... Show MoreThis research study experimentally the effect of air flow rate on humidification process
parameters. Experimental data are obtained from air conditioning study unit T110D. Results obtained
from experimental test, calculations and psychometrics software are discussed. The effect of air flow rate
on steam humidification process parameters as a part of air-conditioning processes can be explained
according to obtained results. Results of the steam humidification processes (1,2) with and without
preheating with 5A and 7.5A shows decreasing in dry bulb temperature, humidity ratio, and heat add to
moist air with increasing air flow rate, but humidification load, and total energy of moist air increase with
increasing air flo
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
Employing phase-change materials (PCM) is considered a very efficient and cost-effective option for addressing the mismatch between the energy supply and the demand. The high storage density, little temperature degradation, and ease of material processing register the PCM as a key candidate for the thermal energy storage system. However, the sluggish response rates during their melting and solidification processes limit their applications and consequently require the inclusion of heat transfer enhancers. This research aims to investigate the potential enhancement of circular fins on intensifying the PCM thermal response in a vertical triple-tube casing. Fin arrays of non-uniform dimensions and distinct distribution patterns were des
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