5 research outputs found
Prognostic significance of lymphocyte-to-monocyte ratio in patients with classical Hodgkin lymphoma before and after receiving first-line chemotherapy
No full textINTRODUCTION: Despite the presence of a prognostic risk stratification sco-ring system for Hodgkin lymphoma (HL), the lymphocyte-to-monocyte ratio (LMR) is a simple and low-cost test that has been investigated as a prognostic marker to evaluate the clinical course and survival outcomes. MATERIAL AND METHODS: We prospectively enrolled 92 patients with classical HL (CHL), who were diagnosed and treated in the period from April 2017 to April 2020. Lymphocyte monocyte ratio cut-off values were estimated using receiver operating characteristic curves. RESULTS: We found that patients with LMR 1.4. Patients with increased LMR values after the first 2 cycles of chemotherapy had better PFS and OS; meanwhile, patients who had low LMR after the end of chemotherapy had poorer PFS and OS in comparison to patients who gained higher value after the completion of all cycles of chemotherapy. CONCLUSIONS: A rise of LMR value indicated better outcome and better survival rate, so it can be an independent prognostic factor for survival and to predict outcome in patients with CHL
Effect of superparamagnetic iron oxide nanoparticles on glucose homeostasis on type 2 diabetes experimental model
No full text[Aims]: Evaluation of the anti-diabetic effect of superparamagnetic iron oxide nanoparticles (SPIONs) on Type 2 diabetic rats and compared their effect to metformin treatment.[Main methods]: Diabetic rats were treated with different doses of nanoparticles one time per week for 4 weeks. Fasting blood glucose level was determined for studied groups during the experimental period (30 days). At the end of the experiment, oral glucose tolerance test was carried out, serum samples were collected for biochemical assays. Then animals were sacrificed to obtain tissues for assessment of glucose transporters, insulin receptors and insulin signaling proteins.[Key finding]: SPIONs treatment normalized fasting blood glucose and lowering insulin level in diabetic rats compared to untreated diabetic rats. SPIONs significantly ameliorate the glucose sensing and the active components of insulin signaling pathway. The anti-diabetic effects of SPIONs may be mediated through its effect on (i) hepatic peroxisome proliferator-activated receptor gamma coactivator 1-alpha content, which induced by SPIONs treatment in a dose-dependent manner, (ii) adipocytokines as SPIONs treated diabetic rats showed significantly higher levels of adiponectin and lower retinol binding protein 4 compared to untreated diabetic rats, (iii) lipid profile as SPIONs treatment significantly corrected the lipid profile in a dose-dependent manner and to a similar extent as metformin or even better.[Significance]: To our knowledge, this is the first study that explores the anti-diabetic effects of SPIONs on diabetic model.This work was partially supported by the Spanish Ministry of Science, Innovation and Universities (Grant PGC2018-095795-B-I00) and by the European Union's Horizon 2020 FET Open Programme (Grant no. 801305).Peer reviewe
Assessment of ghrelin serum level and gene polymorphism as a risk factor in progression of chronic viral hepatitis
No full textAbstract Hepatocellular carcinoma (HCC) is a significant health concern, ranking as the fourth most common cancer in Egypt and the sixth globally. Research has identified over 300 single nucleotide polymorphisms (SNPs) in the ghrelin gene, with four of these SNPs being associated with pathogenicity. The current work is a pioneer attempt to evaluate the role of Ghrelin gene polymorphism as a risk factor for progression of chronic viral hepatitis to cirrhosis and hepatocellular carcinoma in Egyptian patients. This study was carried out on 80 cases and were allocated into four groups: Group I: apparently healthy individuals, Group II: patients with chronic viral hepatitis, Group III: patients with post-hepatitic cirrhosis, and Group IV: patients with viral hepatitis-related HCC. Serum Ghrelin was measured by ELISA Kit. Molecular detection of Ghrelin rs34911341 and rs696217 were assessed using DNA sequencing. Outcomes showed that in terms of ghrelin gene polymorphism, every group under study had a GG rs34911341. The frequency of rs696217 genotype CA was statistically significantly higher in controls than in cirrhotic and HCC cases. When cirrhosis and HCC cases were compared to controls and chronic active hepatitis cases, the serum ghrelin level decreased statistically significantly. Taken together, there was no relation of ghrelin gene polymorphism in rs34911341 with progression of chronic active hepatitis. Moreover, the frequency of rs696217 genotype CA was increased in controls compared to patients with chronic viral hepatitis and patients with viral hepatitis-related HCC. Compared to controls, liver disease patients had lower serum Ghrelin levels
Effect of External Electric Field on Tetrel Bonding Interactions in (FTF3FH) Complexes (T = C, Si, Ge, and Sn)
No full textA quantum chemical
study was accomplished on the σ-hole interactions
of the barely explored group IV elements, for the first time, in the
absence and presence of the positively and negatively directed external
electric field (EEF). The analyses of molecular electrostatic potential
addressed the occurrence of the σ-hole on all the inspected
tetrel atoms, confirming their salient versatility to engage in σ-hole
interactions. MP2 energetic findings disclosed the occurrence of favorable
σ-hole interactions within the tetrel bonding complexes. The
tetrel bonding interactions became stronger in the order of C <
Si 3···FH
complexes with the largest interaction energy amounting to −19.43
kcal/mol for the optimized F–Sn–F3···FH
complex under the influence of +0.020 au EEF. The interaction energy
conspicuously evolved by boosting the magnitude of the positively
directed EEF value and declining the negatively directed EEF one.
The decomposition analysis for the interaction energies was also executed
in terms of symmetry-adapted perturbation theory, illuminating the
dominant electrostatic contribution to all the studied complexes’
interactions except carbon-based interactions controlled by dispersion
forces. The outcomes that emerged from the current work reported significantly
how the direction and strength of the EEF affect the tetrel-bonding
interactions, leading to further improvements in the forthcoming studies
of supramolecular chemistry and materials science
A deep learning model to assess and enhance eye fundus image quality
No full textEngineering aims to design, build, and implement solutions that will increase and/or improve the life quality of human beings. Likewise, from medicine, solutions are generated for the same purposes, enabling these two knowledge areas to converge for a common goal. With the thesis work “A Deep Learning Model to Assess and Enhance Eye Fundus Image Quality", a model was proposed and implement a model that allows us to evaluate and enhance the quality of fundus images, which contributes to improving the efficiency and effectiveness of a subsequent diagnosis based on these images. On the one hand, for the evaluation of these images, a model based on a lightweight convolutional neural network architecture was developed, termed as Mobile Fundus Quality Network (MFQ-Net). This model has approximately 90% fewer parameters than those of the latest generation. For its evaluation, the Kaggle public data set was used with two sets of quality annotations, binary (good and bad) and three classes (good, usable and bad) obtaining an accuracy of 0.911 and 0.856 in the binary mode and three classes respectively in the classification of the fundus image quality. On the other hand, a method was developed for eye fundus quality enhancement termed as Pix2Pix Fundus Oculi Quality Enhancement (P2P-FOQE). This method is based on three stages which are; pre-enhancement: for color adjustment, enhancement: with a Pix2Pix network (which is a Conditional Generative Adversarial Network) as the core of the method and post-enhancement: which is a CLAHE adjustment for contrast and detail enhancement. This method was evaluated on a subset of quality annotations for the Kaggle public database which was re-classified for three categories (good, usable, and poor) by a specialist from the Fundación Oftalmolóica Nacional. With this method, the quality of these images for the good class was improved by 72.33%. Likewise, the image quality improved from the bad class to the usable class, and from the bad class to the good class by 56.21% and 29.49% respectively.La ingeniería busca diseñar, construir e implementar soluciones que permitan aumentar y/o mejorar la calidad de vida de los seres humanos. Igualmente, desde la medicina son generadas soluciones con los mismos fines, posibilitando que estas dos áreas del conocimiento convergan por un bien común. Con el trabajo de tesis “A Deep Learning Model to Assess and Enhance Eye Fundus Image Quality”, se propuso e implementó un modelo que permite evaluar y mejorar la calidad de las imágenes de fondo de ojo, lo cual contribuye a mejorar la eficiencia y eficacia de un posterior diagnóstico basado en estas imágenes. Para la evaluación de estás imágenes, se desarrolló un modelo basado en una arquitectura de red neuronal convolucional ligera, la cual fue llamada Mobile Fundus Quality Network (MFQ-Net). Este modelo posee aproximadamente 90% menos parámetros que aquellos de última generación. Para su evaluación se utilizó el conjunto de datos públicos de Kaggle con dos sets de anotaciones de calidad, binario (buena y mala) y tres clases (buena, usable y mala) obteniendo en la tareas de clasificación de la calidad de la imagen de fondo de ojo una exactitud de 0.911 y 0.856 en la modalidad binaria y tres clases respectivamente. Por otra parte, se desarrolló un método el cual realiza una mejora de la calidad de imágenes de fondo de ojo llamado Pix2Pix Fundus Oculi Quality Enhacement (P2P-FOQE). Este método está basado en tres etapas las cuales son; premejora: para ajuste de color, mejora: con una red Pix2Pix (la cual es una Conditional Generative Adversarial Network) como núcleo del método y postmejora: la cual es un ajuste CLAHE para contraste y realce de detalles. Este método fue evaluado en un subconjunto de anotaciones de calidad para la base de datos pública de Kaggle el cual fue re clasificado por un especialista de la Fundación Oftalmológica Nacional para tres categorías (buena, usable y mala). Con este método fue mejorada la calidad de estas imágenes para la clase buena en un 72,33%. Así mismo, la calidad de imagen mejoró de la clase mala a la clase utilizable, y de la clase mala a clase buena en 56.21% y 29.49% respectivamente.Línea de investigación: Visión por computadora para análisis de imágenes médicasMaestrí
