scholarly journals 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

Nutrients ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 373
Author(s):  
Davide Masi ◽  
Renata Risi ◽  
Filippo Biagi ◽  
Daniel Vasquez Barahona ◽  
Mikiko Watanabe ◽  
...  
Keyword(s):  
Machine Learning ◽  
Body Fat ◽  
Blood Cells ◽  
White Blood Cells ◽  
Surrogate Marker ◽  
Upper Body ◽  
Public Health Issue ◽  
Gamma Glutamyl Transferase ◽  
Metabolically Healthy ◽  
Glutamyl Transferase

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.

scholarly journals Selected haematological and biochemical indices in donkeys in the Czech and Slovak Republics

2016 ◽  
Vol 85 (3) ◽  
pp. 227-230 ◽  
Author(s):  
Markéta Sedlinská ◽  
Dominika Biricová ◽  
Eliška Horáčková ◽  
Miroslava Mráčková
Keyword(s):  
Blood Cells ◽  
White Blood Cells ◽  
Haemoglobin Concentration ◽  
Biochemical Properties ◽  
Gamma Glutamyl Transferase ◽  
Reference Ranges ◽  
Mean Cell Volume ◽  
Glutamyl Transferase ◽  
Biochemical Indices ◽  
Haematological Indices

The aim of this study was to establish normal reference values of biochemical and haematological indices of donkeys in the Czech and Slovak Republics. Blood samples were obtained from 112 clinically healthy donkeys (37 males and 75 females). The haematological indices examined were: red blood cells, white blood cells, haemoglobin concentration, haematocrit, mean cell volume, mean cell haemoglobin, mean cell haemoglobin concentration, platelets, segmented neutrophils, neutrophil bands, lymphocytes, monocytes, eosinophils and basophils. The biochemical properties examined were: total protein, albumin, creatinine, alkaline phosphatase, aspartate aminotransferase, creatine kinase, gamma-glutamyl transferase, lactate dehydrogenase, triacylglycerols, cholesterol, calcium, phosphorus, potassium, sodium, lactate. The results reported in this study could serve as reference ranges for the donkey population in the Czech and Slovak Republics.

scholarly journals Effect of Quercetin on Haematobiochemical and Histological Changes in the Liver of Polychlorined Biphenyls-Induced Adult Male Wistar Rats

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Kandaswamy Selvakumar ◽  
Senthamilselvan Bavithra ◽  
Sekaran Suganya ◽  
Firdous Ahmad Bhat ◽  
Gunasekaran Krishnamoorthy ◽  
...  
Keyword(s):  
Blood Cells ◽  
Hematological Parameters ◽  
White Blood Cells ◽  
Density Lipoprotein ◽  
Protective Role ◽  
Low Density Lipoproteins ◽  
Gamma Glutamyl Transferase ◽  
Low Density ◽  
Very Low Density Lipoproteins ◽  
Glutamyl Transferase

Polychlorinated biphenyls exposure damages the rat liver cells. Hematological parameters such as hemoglobin, packed cell volume, red-blood cells, white-blood cells, neutrophils, platelet counts, and RBC indices were significantly decreased. Polymorphs, eosinophil counts, and erythrocyte sedimentation rate were significantly increased. Serum liver enzymes such as aspartate transaminase, alanine transaminase, alkaline phosphatase, and gamma-glutamyl transferase were increased by PCBs treatment. Serum lipid profiles such as cholesterol, triglycerides, low-density lipoproteins and very-low-density lipoproteins were increased in PCBs-treated rats. High-density lipoprotein, total protein, albumin, globulin levels, and albumin/globulin ratio were also decreased after PCB exposure. Then levels of sodium, potassium, chloride, and bicarbonate were also altered. Serum glucose levels were increased along with total bilirubin after PCBs exposure. Simultaneous quercetin supplementation significantly protected the PCBs-induced changes of hematobiochemical parameters. Thus, quercetin shows a protective role against PCBs-induced alterations in the hematological and biochemical parameters.

Safety evaluation of the aqueous extract of Leonotis leonurus shoots in rats

2008 ◽  
Vol 27 (11) ◽  
pp. 837-843 ◽  
Author(s):  
V Maphosa ◽  
PJ Masika ◽  
AA Adedapo
Keyword(s):  
Acute Toxicity ◽  
Aqueous Extract ◽  
Blood Cells ◽  
Chronic Toxicity ◽  
White Blood Cells ◽  
Female Rats ◽  
Gamma Glutamyl Transferase ◽  
Histopathological Changes ◽  
Glutamyl Transferase ◽  
Leonotis Leonurus

The aqueous extract from Leonotis leonurus (L) R.Br. (Lamiaceae) shoots was evaluated in female rats for its acute, sub acute, and chronic toxicity together with hematological, biochemical, and histopathological changes. In the acute toxicity test, the extract caused death in animals receiving 3200 mg/kg dose. The extract also caused significant ( P < 0.05) changes in red blood cells, packed cell volume, hemoglobin concentration, mean corpuscular volume, platelets, white blood cells and its differentials at doses of 1600 mg/kg in sub-acute toxicity and in as low as 200 mg/kg in chronic toxicity. In biochemical parameters, the extract caused a significant ( P < 0.05) decrease in the levels of urea and creatinine at 1600 mg/kg dose and a significant ( P < 0.05) reduction in urea, total bilirubin, total protein, albumin, globulin, glutamine transference gamma-glutamyl transferase (GGT), and alanine transminase in the 400 mg/kg dose in chronic toxicity. Changes were also noted in body weights, but no significant changes were observed in the levels of electrolytes (sodium, potassium, and chloride). Clinico-pathologically, starry hair coat, respiratory distress, and mortality were recorded. The extract also caused various histopathological changes in the organs. The study concluded that farmers need to exercise caution in the use of the plant for medicinal purposes.

scholarly journals Detection of Blood Cancer Cells Using Microscopic Images

2021 ◽  
Vol 9 (8) ◽  
pp. 995-1003
Author(s):  
Vidyashree M S
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Cancer Cells ◽  
Blood Cells ◽  
White Blood Cells ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Support Vector Machine Algorithm ◽  
Blood Cancer ◽  
Acute Myeloid

Abstract: Blood Cancer cells forming a tissue is called lymphoma. Thus, disease decreases the cells to fight against the infection or cancer blood cells. Blood cancer is also categorized in too many types. The two main categories of blood cancer are Acute Lymphocytic Lymphoma and Acute Myeloid Lymphoma. In this project proposes a approach that robotic detects and segments the nucleolus from white blood cells in the microscopic Blood images. Here in this project, we have used the two Machine learning algorithms that are k-means algorithm, Support vector machine algorithm. K-mean algorithm is use for segmentation and clustering. Support vector machine algorithm is used for classification. Keywords: k-means, Support vector machine, Lymphoma, Acute Lymphocytic Lymphoma, Machine Learning

scholarly journals Evolving liver inflammation in biochemically normal individuals with anti-mitochondria antibodies

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Danielle Cristiane Baldo ◽  
Alessandra Dellavance ◽  
Maria Lucia Gomes Ferraz ◽  
Luis Eduardo C. Andrade
Keyword(s):  
Liver Fibrosis ◽  
Rat Kidney ◽  
Surrogate Marker ◽  
Serum Levels ◽  
Autoimmune Response ◽  
Primary Biliary Cholangitis ◽  
Gamma Glutamyl Transferase ◽  
Normal Individuals ◽  
Glutamyl Transferase

Abstract Background Anti-mitochondria autoantibodies (AMA) occur in > 95% primary biliary cholangitis (PBC) patients. Biochemically normal AMA-positive (BN/AMA+) individuals, occasionally noticed by indirect immunofluorescence (IIF) on HEp-2 cells and confirmed in AMA-specific assays, may represent early stages of PBC. The Enhanced Liver Fibrosis (ELF) score is a surrogate marker for liver fibrosis. This prospective study investigated the ELF score in BN/AMA+ individuals and PBC patients, considering autoantibody avidity and serum levels along the years. Methods 327 samples from 35 PBC and 59 BN/AMA+ were prospectively obtained in average 3.83 (range 0.50–7.40) years apart. Samples were tested by IIF on rat-kidney (IIF-AMA), western-blot for AMA (WB-AMA), and ELISA for antibodies against pyruvate-dehydrogenase (PDC-E2), gp210, sp100 and CENP-A/B. Anti-PDC-E2 avidity was determined by 6 M urea-elution ELISA. Alkaline phosphatase (ALP), gamma glutamyl transferase (ɣGT) and ELF score were measured by automated methods. Results Along the follow-up period BN/AMA+ subjects and PBC patients presented significant increase in serum anti-PDC-E2 (mean 10.45% and 8.86% per year; respectively), anti-PDC-E2 avidity (3.02% and 4.94%/year) and ELF score (3.24% and 2.71%/year). IIF-AMA and ɣGT increased in BN/AMA+ (6.59% and 2.36%) and decreased in PBC (− 4.89%/year and − 3.88%/year). In BN/AMA+ individuals there was positive correlation of ELF with IIF-AMA titer (r = 0.465; p < 0.001) and with anti-PDC-E2 levels (r = 0.239; p < 0.001). Expansion of autoantibody targets along time occurred in 39% BN/AMA+ and 49% PBC patients. The frequency of BN/AMA+ with high probability of having established PBC increased from 7 to 14%. Conclusions BN/AMA+ individuals present an orchestrated increase in ELF score and humoral autoimmune response over time, indicating an opportunity for early therapeutic intervention and prevention in autoimmunity.

scholarly journals Improved White Blood Cells Classification based on Pre-trained Deep Learning Models

2020 ◽  
Vol 16 (1) ◽  
pp. 37-45 ◽  
Author(s):  
Ensaf H. Mohamed ◽  
Wessam H. El-Behaidy ◽  
Ghada Khoriba ◽  
Jie Li
Keyword(s):  
Machine Learning ◽  
Blood Cells ◽  
White Blood Cells ◽  
Evaluation Process ◽  
Cell Detection ◽  
Learning Classifier ◽  
Proposed Model ◽  
Higher Rank ◽  
Fully Connected ◽  
Automated Methods

Leukocytes, or white blood cells (WBCs), are microscopic organisms that fight against infectious disease, bacteria, viruses, and others. The manual method to classify and count WBCs is tedious, time-consuming and may has inaccurate results, whereas the automated methods are costly. The objective of this work is to automatically identify and classify WBCs in a microscopic image into four types with higher accuracy. BCCD is the used dataset in this study, which is a scaled down blood cell detection dataset. BCCD is firstly pre-processed by passing through several processes such as segmentation and augmentation,then it is passed to the proposed model. Our model combines the privilege of deep models in automatically extracting features with the higher classification accuracy of traditional machine learning classifiers.The proposed model consists of two main layers; a shallow tuning pre-trained model and a traditional machine learning classifier on top of it. Here, ten different pretrained models with six different machine learning are used in this study. Moreover, the fully connected network (FCN) of pretrained models is used as a baseline classifier for comparison. The evaluation process shows that the hybrid between MobileNet-224 as feature extractor with logistic regression as classifier has a higher rank-1 accuracy with 97.03%. Besides, the proposed hybrid model outperformed the baseline FCN with 25.78% on average.

scholarly journals (P2-63) An Evaluation of 57 Tick Bite Cases

2011 ◽  
Vol 26 (S1) ◽  
pp. s156-s156
Author(s):  
M. Ortatatli ◽  
R. Gumral ◽  
H. Uckardes ◽  
M. Eroglu ◽  
L. Kenar ◽  
...  
Keyword(s):  
Rural Areas ◽  
Emergency Departments ◽  
White Blood Cells ◽  
Hemorrhagic Fever ◽  
Health Staff ◽  
Gamma Glutamyl Transferase ◽  
Tick Bites ◽  
Number Of Patients ◽  
Glutamyl Transferase

Crimean-Congo Hemorrhagic Fever (CCHF) is a fatal zoonotic viral infection. The agent belongs to the Nairovirus of the Bunyaviridae species. The virus naturally recycles in vector-vertebrate-vector. This study aimed to evaluate cases of tick bites admitted to Infectious Diseases and Emergency Departments in 2008, and to develop management recommendations of such cases. Fifty-seven patients who admitted to a hospital due to tick bites in 2008 were included in the study. A 10-day clinical follow-up was performed to assess for symptoms including fever, fatigue, abdominal pain, headache, nausea/vomiting, diarrhea, disseminated somatic pain, and other hemorrhagic signs. During this period, laboratory analyzes, including white blood cells, thrombocytes, aspartate aminotransferase, alanine aminotransferase, gamma-glutamyl transferase, lactate dehydrogenase, creatinine phosphokinase (CK), and pentylenetetrazol were performed. Personal data of the patients, location of the bite, and the removal of the tick were recorded.ResultsOf the 57 patients, 37% were from the city, and 63% were from rural areas. The tick was removed by health staff in 25 (44%) of the cases. The bites occurred on body areas including the head/neck, trunk, upper extremities, and lower extremities in 14%, 24%, 27%, and 13% of the cases, respectively. During the follow-up period, none of the patients exhibited any of the signs or symptoms listed above. Laboratory tests did not reveal any abnormalities, except for high levels of CK in 15 patients. Thus, 57 cases did not develop CCHF.Discussion and ConclusionSince 2002, CCHF has caused an increased mortality in Turkey, and has resulted in high anxiety and concern among the Turkish public regarding tick bites. This has resulted in a rise in the number of patients admitting to emergency departments with tick bites. Due to CCHF's incubation period, patients with tick bites should be evaluated for 10 days using a multidisciplinary approach involving both clinical and laboratory evaluations in order to prevent the unnecessary administration of ribavirine.

scholarly journals Feline obesity: risk factors and clinical and metabolic findings

2021 ◽  
Vol 42 (6) ◽  
pp. 3305-3320
Author(s):  
Camila Moura de Lima ◽  
◽  
Gustavo Antônio Boff ◽  
Sergiane Baes Pereira ◽  
Alexsander Ferraz ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Environmental Management ◽  
Body Fat ◽  
Body Condition Score ◽  
Serum Biochemistry ◽  
The Body ◽  
Gamma Glutamyl Transferase ◽  
Glutamyl Transferase

Excess body fat can cause a series of metabolic and mechanical effects on the body. Therefore, this study aimed to verify the clinical, metabolic, and risk factors of overweight (OW) cats. For the acceptance of participation in the research, the tutors were asked to answer a questionnaire containing 34 questions and to point out the body condition score (BCS) on a sheet containing nine images of different scores (1 to 9 on a 9-point scale). Thereafter, the body evaluations were performed as a classification of the BCS on a scale from 1 to 9, with an ideal score (IS) of BCS 5 and OW for BCS > 5. Further, the lean mass index and morphometric measurements (thoracic and abdominal circumferences and height and length of the patella to calcaneal tuberosity) were performed to estimate the percentage of body fat. Systolic blood pressure was measured using the non-invasive Doppler method and blood was collected for hemogram and serum biochemistry (creatinine, urea, alanine aminotransferase, alkaline phosphatase, gamma-glutamyl transferase, glucose, triglycerides, and cholesterol). After these analyses, we sought to guide and raise the awareness of the tutors to promote the correct nutritional and environmental management of the animals. Thirty adult cats were divided into two groups, based on the classification of the BCS, with eight having an IS and 22 being OW. The OW group was found to have a low level of physical activity, hypercholesterolemia, and higher values of body characteristics. Additionally, there was a median agreement between the perceptions of the clinician and the tutors. Therefore, it was concluded that the main laboratory alteration found in the obese cats was hypercholesterolemia, which was a critical parameter. It was observed that a low degree of physical activity could cause excess weight gain. It was found that the guardians of the cats with ideal weight underestimated the BCS, which could contribute to the supply of excess food and consequently, obesity. Thus, this study was sought to guide and raise the awareness of tutors, to promote the correct nutritional and environmental management thereby providing welfare and quality of life to the animals.

Diagnosis of inaccessible infections using infrared microscopy of white blood cells and machine learning algorithms

The Analyst ◽  
2020 ◽  
Vol 145 (21) ◽  
pp. 6955-6967
Author(s):  
Adam H. Agbaria ◽  
Guy Beck ◽  
Itshak Lapidot ◽  
Daniel H. Rich ◽  
Joseph Kapelushnik ◽  
...  
Keyword(s):  
Machine Learning ◽  
Ftir Spectroscopy ◽  
Blood Cells ◽  
Learning Algorithms ◽  
White Blood Cells ◽  
Machine Learning Algorithms ◽  
Infrared Microscopy

Rapid and objective diagnosis of the etiology of inaccessible infections by analyzing WBCs spectra, measured by FTIR spectroscopy, using machine-learning.

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