Hematological and renoprotective effects of folic acid and lentil extract in diclofenac sodium exposed rats

Excessive intake of non-steroidal anti-inflammatory drugs such as, diclofenac sodium (DS) may lead to toxicity in the rats. In this work, we aimed to examine the protective impact of lentil extract (LE) and folic acid (FA) on the hematological markers, the kidney tissue oxidative stress and the renal function against diclofenac sodium (DS) in male albino rats. The rats (120-150 g) were divided into four equal groups randomly, the first group kept as the untreated control. The second group was administrated with DS (11.6 mg/kg b.wt. orally once/day). The third group was received DS+FA (11.6 mg/kg b.wt.+76.9 microgram/kg b.wt.) orally once/day. The fourth group was treated with DS+LE (11.6 mg/kg b.wt.+500 mg/kg b.wt.) orally once/day. After four weeks, the results revealed that DS produced a significant decrease in the values of red blood cells (RBCs), hemoglobin concentration (Hb), hematocrit (HCT) and white blood cells (WBCs). On the other hand, there was a significant increase in the platelets count. Also, DS induced a renal deterioration; this was evidenced by the significant increase in the serum levels of urea, creatinine, uric acid, Na, Ca, Mg as well as the nitric oxide (NO) level in the kidney tissue. Also, there were a significant reduction in the serum levels of potassium (K) and reduced glutathione (GSH) in the kidney homogenates. Moreover, the findings in the rats treated by DS+LE or DS+FA showed a potential protection on the hematological markers, oxidative stress in the kidney tissue and the renal function disturbed by DS. LE and FA could play a potent role for the prevention the adverse hematological, the kidney tissue oxidative stress and the renal dysfunction caused by DS via their anti-oxidative and bioactive phytochemicals.

Application of a Machine Learning Technology in the Definition of Metabolically Healthy and Unhealthy Status: A Retrospective Study of 2567 Subjects Suffering from Obesity with or without Metabolic Syndrome

The key factors playing a role in the pathogenesis of metabolic alterations observed in many patients with obesity have not been fully characterized. Their identification is crucial, and it would represent a fundamental step towards better management of this urgent public health issue. This aim could be accomplished by exploiting the potential of machine learning (ML) technology. In a single-centre study (n = 2567), we used an ML analysis to cluster patients with metabolically healthy (MHO) or metabolically unhealthy (MUO) obesity, based on several clinical and biochemical variables. The first model provided by ML was able to predict the presence/absence of MHO with an accuracy of 66.67% and 72.15%, respectively, and included the following parameters: HOMA-IR, upper body fat/lower body fat, glycosylated haemoglobin, red blood cells, age, alanine aminotransferase, uric acid, white blood cells, insulin-like growth factor 1 (IGF-1) and gamma-glutamyl transferase. For each of these parameters, ML provided threshold values identifying either MUO or MHO. A second model including IGF-1 zSDS, a surrogate marker of IGF-1 normalized by age and sex, was even more accurate with a 71.84% and 72.3% precision, respectively. Our results demonstrated high IGF-1 levels in MHO patients, thus highlighting a possible role of IGF-1 as a novel metabolic health parameter to effectively predict the development of MUO using ML technology.

Lung protective effect of Punicalagin on LPS-induced acute lung injury in mice

Background: Punicalagin (Pun) is one of the main bioactive compounds in pomegranate peel, it possesses many properties, including antioxidant, anti-inflammation, and immunosuppressive activities. The study was aimed to investigate the protective effect and mechanisms of Pun on lipopolysaccharide (LPS) induced acute lung injury (ALI) in mice. Methods and Results: Forty-eight BALB/c male mice were used to establish ALI by intratracheal-instilled 2.4 mg/kg LPS, the mice were randomly divided into model and Pun (10, 20, 40 mg/kg) groups. The other twelve mice were intratracheal-instilled same volume of water as control. After 2 h of receiving LPS, mice were administrated drug through intraperitoneal injection. Lung index, histopathological changes, white blood cells and biomarkers in bronchoalveolar lavage fluid (BALF) were analyzed. The protein expression of total and phosphor p65, IκBα, ERK1/2, JNK and p38 in lung tissue was detected. The result showed that Pun could reduce the lung index and wet/dry weight ratio, improve lung histopathological injury. In addition, Pun decreased the inflammation cells and regulated the biomarkers in BALF. Furthermore, Pun dose-dependently reduced the phosphor protein levels of p65, IκBα, ERK1/2, JNK and p38 in lung tissue, which exhibited that the effect of Pun related to MAPKs pathway. More importantly, there is no toxicity was observed in the acute toxicity study of Pun. Conclusion: Pun improves LPS-induced ALI mainly through its anti-inflammatory properties, which is associated with NF-κB and MAPKs signaling pathways. The study implied that Pun maybe a potent agent against ALI in future clinic.

Circulating levels of hypoxia-inducible factor-1α and miR-210 are associated with photosensitivity in systemic lupus erythematosus patients

Background: miR-210, a key HypoxamiR, regulates the hypoxia and inflammation-linked hypoxia. Systemic lupus erythematosus (SLE), a chronic autoimmune disease, responsible for many pathological disorders, including photosensitivity. Objective: Finding the correlation between the circulating miR-210/HIF-1α levels and photosensitivity in SLE patients and other SLE-associated pathological complications, in a single-center case control study. Methods: Study population of 104 SLE Egyptian patients with photosensitivity, 32 SLE patients without photosensitivity, and 32 healthy subjects. SLE activity was assessed for all patients by SLE Disease Activity Index (SLEDAI). The clinical complications/manifestations and the hematological/serological analyses were recorded. HIF-α concentration was investigated by ELISA and miR-210 expression was analyzed by qRT-PCR. Results: The results revealed that circulating miR-210 was significantly increased in SLE/photosensitivity than SLE and controls. The additional occurrence of malar rash, oral ulcers, renal disorders or hypertension resulted in a higher expression of miR-210. SLEDAI activity status showed no effect on miR-210. Erythrocyte sedimentation rate, white blood cells, hemoglobin, platelets, the patients age and the disease duration were positively correlated with circulatory miR-210. HIF-α concentration was significantly induced in SLE/photosensitivity than SLE and controls. In SLE/photosensitivity, presence of renal disorders and hypertension resulted in highest HIF-α concentrations. A strong positive correlation was recorded between HIF-α concentration and circulatory miR-210 in SLE/photosensitivity patients (r = 0.886). Conclusion:: The dysregulation of circulating miR-210/ HIF-1α levels in SLE/photosensitivity‎ patients is controlled by the presence of additional pathological complications and supposed that hypoxia pathway might interact positively with the pathogenesis and illness progress of SLE.

Computational Intelligence Method for Detection of White Blood Cells Using Hybrid of Convolutional Deep Learning and SIFT

Infection diseases are among the top global issues with negative impacts on health, economy, and society as a whole. One of the most effective ways to detect these diseases is done by analysing the microscopic images of blood cells. Artificial intelligence (AI) techniques are now widely used to detect these blood cells and explore their structures. In recent years, deep learning architectures have been utilized as they are powerful tools for big data analysis. In this work, we are presenting a deep neural network for processing of microscopic images of blood cells. Processing these images is particularly important as white blood cells and their structures are being used to diagnose different diseases. In this research, we design and implement a reliable processing system for blood samples and classify five different types of white blood cells in microscopic images. We use the Gram-Schmidt algorithm for segmentation purposes. For the classification of different types of white blood cells, we combine Scale-Invariant Feature Transform (SIFT) feature detection technique with a deep convolutional neural network. To evaluate our work, we tested our method on LISC and WBCis databases. We achieved 95.84% and 97.33% accuracy of segmentation for these data sets, respectively. Our work illustrates that deep learning models can be promising in designing and developing a reliable system for microscopic image processing.

Deep Learning Model for the Automatic Classification of White Blood Cells

Blood cell count is highly useful in identifying the occurrence of a particular disease or ailment. To successfully measure the blood cell count, sophisticated equipment that makes use of invasive methods to acquire the blood cell slides or images is utilized. These blood cell images are subjected to various data analyzing techniques that count and classify the different types of blood cells. Nowadays, deep learning-based methods are in practice to analyze the data. These methods are less time-consuming and require less sophisticated equipment. This paper implements a deep learning (D.L) model that uses the DenseNet121 model to classify the different types of white blood cells (WBC). The DenseNet121 model is optimized with the preprocessing techniques of normalization and data augmentation. This model yielded an accuracy of 98.84%, a precision of 99.33%, a sensitivity of 98.85%, and a specificity of 99.61%. The proposed model is simulated with four batch sizes (BS) along with the Adam optimizer and 10 epochs. It is concluded from the results that the DenseNet121 model has outperformed with batch size 8 as compared to other batch sizes. The dataset has been taken from the Kaggle having 12,444 images with the images of 3120 eosinophils, 3103 lymphocytes, 3098 monocytes, and 3123 neutrophils. With such results, these models could be utilized for developing clinically useful solutions that are able to detect WBC in blood cell images.

Evaluating the blood toxicity of functionalized graphene-arginine with anticancer drug ginsenoside Rh2 in balb/c mouse model with breast cancer

Background: Gensenoside Rh2 is an anticancer drug with low toxicity and stability in the body. The aim of this study was to evaluate the blood toxicity of functionalized graphene-arginine with anticancer drug ginsenoside Rh2 in balb/c mouse model with breast cancer. Materials and Methods: Graphene-Arginine (G-Arg) and Graphene-Arginine-ginsenoside Rh2 (G-Arg-Rh2) were synthesized using microwave method. For evaluation of blood toxicity, 32 mice with breast tumors were randomly divided into 4 groups: control (3mg/kg 6 mg / kg PBS sterile), group 1 (6 mg / kg ginsenoside), group 2 (3 mg / kg G-Arg), and group 3 (3 mg / kg G-Arg-Rh2). Treatment was done intravenously once every three days for 32 days. Finally, blood factors were also examined by sampling from the heart. Results: Complete functionalization was proven by FTIR and Raman. Examination of blood factors showed that white blood cells had a very small increase. Anova test showed significant difference among four groups in term of WBC count (p=0.016). Pair sample T test showed that there was significant difference between control and group 1(p=0.036) and control and group 2 (p=0.036). There was no significant difference between control and group 3 (p=0.051). Other blood factors had no significant difference among examined groups (p>0.05). Conclusion: Based on results, after treatment with all designed nanostructures, only white blood cells had a very small increase and inflammatory reactions were statistically similar in all groups. This indicates the high efficiency of designed drug.

Hematologic Involvement as a Predictor of Mortality in COVID-19 Patients in a Safety Net Hospital

Introduction. COVID-19 affects the hematologic system. We evaluate the impact of hematologic involvement of different blood cell line parameters of white blood cells including absolute neutrophil count (ANC), hemoglobin, and platelets in COVID-19 patients and their association with hospital mortality and length of stay (LOS). Methods. This is a retrospective study of 475 patients with confirmed positive COVID-19 infection and hematologic abnormalities in the metropolitan New York City area. Results. Increased (ANC) (OR:1.20; 95% CI:1.02-1.42, p<0.05) increased days to hematologic involvement (OR:4.44, 95% CI:1.42-13.90; p<0.05), and persistence of hematologic involvement at discharge (OR:2.87, 95% CI:1.20, 6.90, p<0.05) were associated with higher mortality. Higher hemoglobin at admission (OR:0.77, 95% CI:0.60-0.98, p<0.001) and platelets peak (OR:0.995, 95% CI 95%:0.992-0.997, p<0.001) were associated with decreased mortality. Patients with higher white blood cell peak (B=0.46, SE=0.07, p<0.001) and higher hemoglobin at admission (B=0.05, SE=0.01, p<0.001) were associated with higher LOS. Those with higher hemoglobin nadir (B=-0.06, SE=0.01, p<0.001), higher platelets nadir (B=-0.001, SE=<0.001, p<0.001), and hematologic involvement at discharge/death (B=-0.06, SE=0.03, p<0.05) were associated with lower LOS. Conclusions. These findings can be used by clinicians to better risk-stratify patients with hematologic involvement in COVID-19 and tailor therapies to potentially improve patient outcomes.

EFFICACY OF IVERMACTIN AGANIST SOME NATURALLY ACQUIRED GASTRO-INTESTINAL PARASITIC INFECTION IN MULES

The activity of a single subcutaneous injection of ivermectin at dose of 200 mcg/kg of body weight was evaluated against naturally acquired gastro-intestinal parasites in mules. Faecal samples were examined at the time of treatment and weekly thereafter up to 4 weeks. Results indicated that invrmectin was highly effective (100%) against Oxyuries equi, Strongyloides westeri, Tristostronglus axei, Trichhonema spp., and Strongylus spp. as judged one week after ivermectin administration. Complete elimination of Parascaris equorum eggs occurred two weeks after treatment. In contrast, ivermectin was not effective against the tape worms, Anoplocephala spp.. Infected animals had low levels of haemoglobin and red blood cells counts and an elevated packed cell volume, white blood cells and erythrocyte sedimentation rate. These values returned to normal values 21 days post treatment. No adverse reaction was recorded in the treated animals.

Total Protein–Chloride Ratio in Pleural Fluid Independently Predicts Overall Survival in Malignant Pleural Effusion at the First Diagnosis

ObjectivePre-treatment biomarkers to estimate overall survival (OS) for malignant pleural effusion (MPE) are unidentified, especially those in pleural fluid. We evaluated the relationship between OS and total protein–chloride ratio in malignant pleural effusion (PE TPClR).Materials and MethodsA retrospective study was undertaken to identify patients from 2006 to 2018 who had pathologically or cytologically confirmed MPE and received no tumor-targeted therapy. We recorded the pre-treatment clinicopathologic characteristics and follow-up status. OS was estimated by the Kaplan–Meier method, and the association between variables and OS was evaluated by Cox proportional hazards models.ResultsWe screened 214 patients who met the eligibility criteria. The optimal cutoff value for the PE TPClR was set at 0.53. The univariate analysis showed that there was a significant correlation between PE TPClR and OS (P &lt; 0.001). The multivariate analysis between OS and the variables selected from the univariate analysis showed that the levels of neutrophil, alkaline phosphatase, neuron-specific enolase, platelets, albumin in peripheral blood, and white blood cells in pleural effusion were also independent predictors of OS.ConclusionIn patients with MPE, pre-treatment PE TPClR independently predicts OS. Although further research is necessary to generalize our results, this information will help clinicians and patients to determine the most appropriate treatment for MPE patients.