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1.
Cureus ; 16(2): e54914, 2024 Feb.
Article in English | MEDLINE | ID: mdl-38544644

ABSTRACT

INTRODUCTION: The study determined the damage caused by formaldehyde (FA) exposure in blood and liver samples using biochemical markers. Histopathological analysis was performed using the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) method and measurement of CD68 cell density. To what extent the antioxidant molecules thymoquinone (TQ) and ozone (O3) reversed the damage caused by FA exposure was investigated, both when used alone and combined. METHODS: Fifty-six Sprague-Dawley male rats of eight to ten weeks of age were used in the experiment. The rats were divided into eight groups, with seven rats in each group: the untreated control group, the group treated with TQ (10 mg/kg/day), the group treated with O3 (150 µg/kg/day), the group treated with TQ+O3, the group exposed to FA (10 ppm 8 h/day), the group receiving FA+TQ, the group receiving FA+O3, and the group receiving FA+TQ+O3. Serum aspartate transaminase (AST), alanine transaminase (ALT), total antioxidant (TAS, U/mL), and total oxidant (TOS, nmol/mL) levels were analyzed. TAS and TOS levels, CD68 cell density, and apoptotic cells were determined in liver tissues. RESULTS: FA exposure caused an increase in serum AST and ALT levels of (p<0.05) experimental animals, a decrease in TAS levels in serum (p=0.03) and liver (p>0.05) and an increase in TOS levels (p>0.05), TUNEL positivity (p<0.001), and CD68 cell density (p=0.004). Administration of TQ and O3 as antioxidants significantly reversed biochemical and histopathological alterations in the serum and liver. CONCLUSION: TQ and ozone therapy suppressed oxidative stress caused by FA exposure and reversed the emerging histopathological deteriorations. Ozone therapy did not suppress the effects of TQ. Therefore, ozone therapy can be given as a supportive therapy along with the main therapeutic agents. We think TQ and ozone therapy may be useful to protect individuals exposed to FA.

2.
Biotech Histochem ; 99(1): 21-32, 2024 Nov.
Article in English | MEDLINE | ID: mdl-37933453

ABSTRACT

Metabolic syndrome (MetS) is a prevalent public health problem. Uric acid (UA) is increased by MetS. We investigated whether administration of UA and 10% fructose (F) would accelerate MetS formation and we also determined the effects of irisin and exercise. We used seven groups of rats. Group 1 (control); group 2 (sham); group 3 (10% F); group 4 (1% UA); group 5 (2% UA); group 6 (10% F + 1% UA); and Group 7, (10% F + 2% UA). After induction of MetS (groups 3 -7), Group 3 was divided into three subgroups: 3A, no further treatment; 3B, irisin treatment; 3C, irisin treatment + exercise. Group 4, 1% UA, which was divided into three subgroups: 4A, no further treatment; 4B, irisin treatment; 4C, Irisin treatment + exercise. Group 5, 2% UA, which was divided into three subgroups: 5A, no further treatment; 5B, irisin treatment; 5C, irisin treatment + exercise. Group 6, 10% F + 1% UA, which was divided into three subgroups: 6A, no further treatment; 6B, irisin treatment; 6C, irisin treatment + exercise. Group 7, 10% F + 2% UA, which was divided into three subgroups: 7A, no further treatment; 7B, irisin treatment; 7C, irisin treatment + exercise., Irisin was administered 10 ng/kg irisin intraperitoneally on Monday, Wednesday, Friday, Sunday each week for 1 month. The exercise animals (in addition to irisin treatment) also were run on a treadmill for 45 min on Monday, Wednesday, Friday, Sunday each week for 1 month. The rats were sacrificed and samples of liver, heart, kidney, pancreas, skeletal muscles and blood were obtained. The amounts of adropin (ADR) and betatrophin in the tissue supernatant and blood were measured using an ELISA method. Immunohistochemistry was used to detect ADR and betatrophin expression in situ in tissue samples. The duration of these experiments varied from 3 and 10 weeks. The order of development of MetS was: group 7, 3 weeks; group 6, 4 weeks; group 5, 6 weeks; group 4, 7 weeks; group 3, 10 weeks. Kidney, liver, heart, pancreas and skeletal muscle tissues are sources of adropin and betatrophin. In these tissues and in the circulation, adropin was decreased significantly, while betatrophin was increased significantly due to MetS; irisin + exercise reversed this situation. We found that the best method for creating a MetS model was F + UA2 supplementation. Our method is rapid and simple. Irisin + exercise was best for preventing MetS.


Subject(s)
Fibronectins , Metabolic Syndrome , Rats , Animals , Fibronectins/pharmacology , Fibronectins/metabolism , Metabolic Syndrome/therapy , Angiopoietin-Like Protein 8 , Heart
3.
Healthcare (Basel) ; 11(20)2023 Oct 22.
Article in English | MEDLINE | ID: mdl-37893868

ABSTRACT

Cancer is a devastating disease that has significant psychological and biological impacts. Generally, lung cancer primarily affects men while breast cancer primarily affects women. Thus, this study aimed to investigate the levels of anxiety and depression in patients with these prevalent cancer types, as well as their perceptions of the illness and any potential connections between them. The study included a total of 252 participants, consisting of 110 breast cancer patients, 112 lung cancer patients, and 30 healthy individuals as controls. The Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) were administered to assess mood, while the Illness Perception Questionnaire (IPQ) was used to evaluate cancer perceptions. Results revealed that both breast cancer and lung cancer patients had significantly higher BDI and BAI scores compared to the control group. Furthermore, the BDI and BAI scores were lower in breast cancer patients compared to lung cancer patients. The IPQ causal representation-immunity score was significantly higher in lung cancer patients than in breast cancer patients (p = 0.01). Positive correlations were found between BDI scores and BAI scores, as well as between BDI scores and certain subscale scores of the IPQ related to illness representation and causal representation. Additionally, a positive correlation was observed between BAI scores and the IPQ illness representation-timeline acute/chronic subscale, while a negative correlation was found between BAI scores and the IPQ causal representation-accident or chance scores. Overall, the study findings demonstrated that breast and lung cancer patients possess negative perceptions of their disease and experience high levels of anxiety and depression. To enhance the quality of life and promote resilience in these patients, it is recommended to incorporate psychological interventions that consider anxiety, depression, and disease perception.

4.
Biotech Histochem ; 98(4): 243-254, 2023 May.
Article in English | MEDLINE | ID: mdl-36825397

ABSTRACT

We investigated the presence of asprosin (ASP), betatrophin, elabela (ELA), glucagon and subfatin (SUB) in the milk of mothers with gestational diabetes mellitus (GDM) and compared their levels with blood levels. We also investigated whether these peptides are synthesized by the breast. We investigated 12 volunteer mothers with GDM and 14 pregnant non-GDM control mothers. The peptides were measured using ELISA and their tissue localization was determined using immunohistochemistry. Breast milk contains ASP, betatrophin, ELA, glucagon and SUB. The amount of the peptides ranged from highest to the lowest in colostrum, transitional milk and mature milk. The amount of peptides in the milk was greater than for blood. The peptides, except for ELA, were increased in milk and blood by GDM. Betatrophin and ELA are synthesized in the connective tissue of the breast. ASP, glucagon and SUB are synthesized in the alveolar tissue of the breast. These peptides in breast milk may contribute to the development of the gastrointestinal tract of newborns and infants.


Subject(s)
Diabetes, Gestational , Female , Humans , Infant , Infant, Newborn , Pregnancy , Angiopoietin-Like Protein 8 , Glucagon , Milk, Human , Peptides
5.
Comput Biol Med ; 147: 105725, 2022 08.
Article in English | MEDLINE | ID: mdl-35716434

ABSTRACT

Nasal polyps are edematous polypoid masses covered by smooth, gray, shiny, soft and gelatinous mucosa. They often pose a threat for the patients to result in allergic rhinitis, sinus infections and asthma. The aim of this paper is to design a reliable rhinology assistance system for recognizing the nasal polyps in endoscopic videos. We introduce NP-80, a novel dataset that contains high-quality endoscopy video-frames of 80 participants with and without nasal polyps (NP). We benchmark vanilla machine learning and deep learning-based classifiers on the proposed dataset with respect to robustness and accuracy. We conduct a series of classification experiments and an exhaustive empirical comparison on handcrafted features (texture features -Local Binary Patterns (LBP) and shape features- Histogram of Oriented Gradients (HOG) and Convolutional Neural Network (CNN) features for recognizing nasal polyps automatically. The classification experiments are carried out by K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Random Forest (RF), Decision Tree (DT) and CNN classifiers. The best obtained precision, recall, and accuracy rates are 99%, 98%, and 98.3%, respectively. The classifier methods built with handcrafted features have shown poor recognition performance (best accuracy of %96.3) from the proposed CNN classifier (best accuracy of %98.3). The empirical results of the proposed learning techniques on NP-80 dataset are promising to support clinical decision systems. We make our dataset publicly available to encourage further research on rhinology experiments. The major research objective accomplished in this study is the creation of a high-accuracy deep learning based nasal polyps classification model using easily obtainable portable rhino fiberoscope images to be integrated into an otolaryngologist decision support system. We conclude from the research that using appropriate image processing techniques along with suitable deep learning networks allow researchers to obtain high accuracy recommendations in identifying nasal polyps. Furthermore, the results from the study encourages us to develop deep learning models for various other medical conditions.


Subject(s)
Nasal Polyps , Endoscopy , Humans , Image Processing, Computer-Assisted/methods , Nasal Polyps/diagnostic imaging , Neural Networks, Computer , Support Vector Machine
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