scholarly journals Fibroblasts of skin fragments as a tool for the investigation of genetic diseases: technical recommendations

2000 ◽  
Vol 23 (2) ◽  
pp. 269-271 ◽  
Author(s):  
Janice Carneiro Coelho ◽  
Roberto Giugliani
Keyword(s):  
Diagnostic Tool ◽  
Present Report ◽  
Genetic Disorders ◽  
Genetic Disorder ◽  
Genetic Diseases ◽  
Patient Discomfort ◽  
General Rules ◽  
Probability Of Success ◽  
Skin Biopsies ◽  
Technical Recommendations

Skin biopsies are frequently indicated for investigation and/or confirmation of genetic disorders. Although relatively simple and noninvasive, these procedures require care in order to increase probability of success and to avoid patient discomfort and unnecessary repeated analyses and associated laboratory fees. The present report highlights the importance of skin biopsies in genetic disorder diagnosis and presents general rules for collecting, storing, transporting and processing samples. We recommend its reading to professionals intending to use this important and sometimes fundamental diagnostic tool.

scholarly journals Role of Signal Transduction Pathways and Transcription Factors in Cartilage and Joint Diseases

2020 ◽  
Author(s):  
Riko Nishimura ◽  
Kenji Hata ◽  
Yoshifumi Takahata ◽  
Tomohiko Murakami ◽  
Eriko Nakamura ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Transcription Factors ◽  
Genetic Disorders ◽  
Genetic Disorder ◽  
Genetic Diseases ◽  
Mtor Inhibitors ◽  
Joint Diseases ◽  
Ectopic Ossification ◽  
Proliferation And Differentiation ◽  
Clinical Benefits

Osteoarthritis and rheumatoid arthritis are common cartilage and joint diseases that globally affect more than 200 and 20 million people, respectively. Several transcription factors have been implicated in the onset and progression of osteoarthritis, including Runx2, C/EBPβ, HIF2α, Sox4, and Sox11. IL-1β also leads to osteoarthritis through NF-ĸB, IκBζ, and Zn2+-ZIP8-MTF1 axis. IL-1, IL-6, and TNFα play a major pathological role in rheumatoid arthritis through NF-ĸB and JAK/STAT pathways. Indeed, inhibitory reagents for IL-1, IL-6, and TNFα provide clinical benefits for rheumatoid arthritis patients. Several growth factors, such as BMP, FGF, PTHrP, and Indian hedgehog, play roles regulating chondrocyte proliferation and differentiation. Disruption and excess of these signaling cause genetic disorders in cartilage and skeletal tissues. FOP, an autosomal genetic disorder characterized by ectopic ossification, is induced by mutant ACVR1. mTOR inhibitors were found to prevent ectopic ossification by ACVR1 mutations. ACH and related diseases are autosomal genetic diseases, which manifest severe dwarfism. CNP is currently the most promising therapy for ACH. In these ways, investigation of cartilage and chondrocyte diseases at molecular and cellular levels sheds light on the development of effective therapies. Thus, identification of signaling pathways and transcription factors implicated in these diseases is important.

scholarly journals DNA Classification using Machine Learning for Detecting Genetic Disorders

2020 ◽  
Vol 9 (4) ◽  
pp. 1287-1291
Keyword(s):  
Machine Learning ◽  
Dna Sequences ◽  
Genetic Disorders ◽  
Genetic Disorder ◽  
Median Filter ◽  
Genetic Diseases ◽  
Minimal Amount ◽  
Base Pairs ◽  
Canny Edge ◽  
Dna Pattern

Deoxyribonucleic acid is a double- helical molecule composed of two chains that contains genetic instructions. Genetic diseases are caused by changes in pre-existing genes. A genetic abnormality results from the alteration in chromosomes. DNA classification helps to identify genetic disorders in organisms. DNA pattern recognition is a major issue in bioinformatics. DNA is classified into several categories on the basis of Structure, Location, Number of base pairs etc. Traditionally the DNA Molecule is studied by extracting it from the blood sample and is then manually analysed to find out the abnormalities. To increase the accuracy, a machine learning based DNA classification is done which helps in studying the extracted DNA image using various techniques. This consumes minimal amount of time and is more efficient. The image is preprocessed using median filter and canny edge detection. DNA sequences can be recognized correctly and effectively without any uncertainties with the help of Neural Network.The network successfully classifies an image given as input when it is trained with patterns. Thus, we can analyse if a person has a genetic disorder.

Surgical Management of Atresia Ani in a Crossbred Calf

2019 ◽  
Vol 15 (02) ◽  
pp. 81-82
Author(s):  
Madan Pal ◽  
Kashi Ram ◽  
Chander Pal Garhwal ◽  
Virender .
Keyword(s):  
Body Weight ◽  
Weight Gain ◽  
Body Weight Gain ◽  
Present Report ◽  
Genetic Disorders ◽  
Economic Loss ◽  
Intestinal Atresia ◽  
Congenital Defect ◽  
Surgical Correction ◽  
Anal Opening

Atresia ani is a congenital defect that describes the absence of a normal anal opening. It is fatal unless a surgical correction is carried out to provide an anal opening. In female, the rectum may break through the vagina, forming a rectovaginal fistula permitting defecation via the vulva. Surgical treatment of atresia ani is indicated to save the animal’s life and to improve body weight gain. Intestinal atresia has been reported as a congenital defect in all species of domestic animals (Gass and Tibboel, 1980). Atresia ani may be caused by genetic disorders (chromosomes or transgenesis), environmental factors, or a combination of both (Cassini et al., 2005). Monsang et al. (2011) reported a case of double vulva with atresia ani in a crossbred calf. Atresia ani should be treated by a surgical operation to solve the problem, improve body weight gain, and reduce economic loss. The present report records a case of atresia ani in a crossbred cow-calf and its successful surgical correction.

scholarly journals The Importance of Early Detection of Genetic Diseases

2021 ◽  
Vol 4 (2) ◽  
pp. 133-141
Author(s):  
Suma Elcy Varghese ◽  
Rana Hassan Mohammad El Otol ◽  
Fatma Sultan Al Olama ◽  
Salah Ahmad Mohamed Elbadawi
Keyword(s):  
Early Detection ◽  
Newborn Screening ◽  
Health Authority ◽  
Genetic Screening ◽  
Screening Program ◽  
Genetic Disorders ◽  
Genetic Diseases ◽  
Inborn Errors ◽  
The Usa ◽  
Premarital Screening

<b><i>Background:</i></b> Early detection of diseases in newborn may help in early intervention and treatment, which may either cure the disease or improve the outcome of the patient. Dubai’s Health Authority has a newborn screening program which includes screening for metabolic and genetic conditions, for hearing and vision, and for congenital heart disease. <b><i>Objectives:</i></b> The objectives of this study are to assess the outcome of the newborn genetic screening program, to correlate the association between the outcome of the program and demographic variables and to find out the percentage of the number of infants who were confirmed to have the genetic disease (by confirmatory tests) out of the total infants who had positive screening test results. <b><i>Methods:</i></b> During the period of the study from January 2018 to December 2018, a total of 7,027 newborns were tested in Dubai Health Authority facilities by the newborn genetic screening program (known as the “Step One Screening”). Blood samples were collected by heel prick on a collection paper. All samples were transported to PerkinElmer Genomics in the USA where the tests were done. The genetic disorders identified were correlated with different variables like gender and nationality. The data were entered in an excel sheet and analyzed by using SPSS software. All infants aged 0–3 months who have done newborn genetic screening at Dubai Health Authority facilities between January and December 2018 were included. <b><i>Results:</i></b> The incidence of screened disorders was 1:7,027 for congenital adrenal hyperplasia, 1:1,757 for congenital hypothyroidism, 1:1,757 for inborn errors of metabolism, 1:2,342 for biotinidase deficiency, 1:1,171 for hemoglobinopathies, 1:12 for hemoglobinopathy traits, and 1:10 for different genetic mutations of G6PD deficiency. <b><i>Conclusions:</i></b> There is a high incidence of different genetic diseases detected by newborn screening. These results justify unifying the program in the UAE and preventive programs like premarital screening and genetic counseling.

scholarly journals Role of Signal Transduction Pathways and Transcription Factors in Cartilage and Joint Diseases

2020 ◽  
Vol 21 (4) ◽  
pp. 1340 ◽  
Author(s):  
Riko Nishimura ◽  
Kenji Hata ◽  
Yoshifumi Takahata ◽  
Tomohiko Murakami ◽  
Eriko Nakamura ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Transcription Factors ◽  
Signaling Pathways ◽  
Genetic Disorder ◽  
Interleukin 1 ◽  
Genetic Diseases ◽  
Mtor Inhibitors ◽  
Joint Diseases ◽  
Ectopic Ossification ◽  
Parathyroid Hormone Related Protein

Osteoarthritis and rheumatoid arthritis are common cartilage and joint diseases that globally affect more than 200 million and 20 million people, respectively. Several transcription factors have been implicated in the onset and progression of osteoarthritis, including Runx2, C/EBPβ, HIF2α, Sox4, and Sox11. Interleukin-1 β (IL-1β) leads to osteoarthritis through NF-ĸB, IκBζ, and the Zn2+-ZIP8-MTF1 axis. IL-1, IL-6, and tumor necrosis factor α (TNFα) play a major pathological role in rheumatoid arthritis through NF-ĸB and JAK/STAT pathways. Indeed, inhibitory reagents for IL-1, IL-6, and TNFα provide clinical benefits for rheumatoid arthritis patients. Several growth factors, such as bone morphogenetic protein (BMP), fibroblast growth factor (FGF), parathyroid hormone-related protein (PTHrP), and Indian hedgehog, play roles in regulating chondrocyte proliferation and differentiation. Disruption and excess of these signaling pathways cause genetic disorders in cartilage and skeletal tissues. Fibrodysplasia ossificans progressive, an autosomal genetic disorder characterized by ectopic ossification, is induced by mutant ACVR1. Mechanistic target of rapamycin kinase (mTOR) inhibitors can prevent ectopic ossification induced by ACVR1 mutations. C-type natriuretic peptide is currently the most promising therapy for achondroplasia and related autosomal genetic diseases that manifest severe dwarfism. In these ways, investigation of cartilage and chondrocyte diseases at molecular and cellular levels has enlightened the development of effective therapies. Thus, identification of signaling pathways and transcription factors implicated in these diseases is important.

GENETIC DISORDER OF THE ENDOCRINE GLANDS, by David L. Rimoin, M.D., Ph.D., R. Neil Schimke, M.D. St. Louis: The C. V. Mosby Company, 1971, 383 pp., $32.50

PEDIATRICS ◽  
1972 ◽  
Vol 49 (5) ◽  
pp. 798-798
Author(s):  
S. Douglas Frasier
Keyword(s):  
Genetic Disorders ◽  
Genetic Disorder ◽  
Endocrine Glands

The authors present this book as an attempt to catalogue the known genetic disorders of the endocrine glands. They have succeeded admirably. Each chapter begins with a brief description of the embryology and physiology of the gland under discussion. If there are weaknesses in this presentation, they are excusable in the light of the authors' main purpose. Embryology and physiology are followed by a catalogue of genetic disorders which are associated with altered function of that gland.

Genetic Disorders, Genotyping Techniques and the Emerging Role of Tetra-ARMS-PCR as a Diagnostic Tool

Resonance ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 1229-1240
Author(s):  
Motiur Rahaman ◽  
Mandrita Mukherjee ◽  
Nishant Chakravorty
Keyword(s):  
Diagnostic Tool ◽  
Genetic Disorders ◽  
Arms Pcr

scholarly journals CNV-P: a machine-learning framework for predicting high confident copy number variations

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12564
Author(s):  
Taifu Wang ◽  
Jinghua Sun ◽  
Xiuqing Zhang ◽  
Wen-Jing Wang ◽  
Qing Zhou
Keyword(s):  
Machine Learning ◽  
False Positive ◽  
Copy Number ◽  
Genetic Disorders ◽  
Genetic Diseases ◽  
Basic Research ◽  
Read Depth ◽  
Copy Number Variations ◽  
Sequencing Data ◽  
Learning Framework

Background Copy-number variants (CNVs) have been recognized as one of the major causes of genetic disorders. Reliable detection of CNVs from genome sequencing data has been a strong demand for disease research. However, current software for detecting CNVs has high false-positive rates, which needs further improvement. Methods Here, we proposed a novel and post-processing approach for CNVs prediction (CNV-P), a machine-learning framework that could efficiently remove false-positive fragments from results of CNVs detecting tools. A series of CNVs signals such as read depth (RD), split reads (SR) and read pair (RP) around the putative CNV fragments were defined as features to train a classifier. Results The prediction results on several real biological datasets showed that our models could accurately classify the CNVs at over 90% precision rate and 85% recall rate, which greatly improves the performance of state-of-the-art algorithms. Furthermore, our results indicate that CNV-P is robust to different sizes of CNVs and the platforms of sequencing. Conclusions Our framework for classifying high-confident CNVs could improve both basic research and clinical diagnosis of genetic diseases.

Genetic Disorders and Major Extracardiac Anomalies Associated With the Hypoplastic Left Heart Syndrome

PEDIATRICS ◽  
1988 ◽  
Vol 82 (5) ◽  
pp. 698-706 ◽  
Author(s):  
Marvin Natowicz ◽  
Jane Chatten ◽  
Robert Clancy ◽  
Katrina Conard ◽  
Tracy Glauser ◽  
...  
Keyword(s):  
Hypoplastic Left Heart Syndrome ◽  
Chromosomal Abnormalities ◽  
Genetic Disorders ◽  
Genetic Disorder ◽  
Single Gene ◽  
Left Heart ◽  
Hypoplastic Left Heart ◽  
Gene Defects ◽  
Insulin Dependent Diabetic ◽  
Left Heart Syndrome

All pediatric autopsies of patients with hypoplastic left heart syndrome seen during an 11-year interval were reviewed to determine the frequency of underlying chromosomal and single-gene defects and idiopathic major extracardiac anomalies associated with this common, lethal congenital heart abnormality. Of 83 patients identified, nine had underlying chromosomal abnormalities, four had single-gene defects, ten had one or more major extracardiac anomalies without an identifiable chromosomal or mendelian disorder, and two were infants of insulin-dependent diabetic mothers. Overall, 23 patients (28%) had a genetic disorder and/or major extracardiac anomaly. The substantial prevalence of genetic causes of and major extracardiac anomalies associated with hypoplastic left heart syndrome underscores the need for a detailed genetic evaluation for all patients with hypoplastic left heart syndrome.

Automatic Computerized Diagnostic Tool for Down Syndrome Detection in Fetus

2019 ◽  
pp. 226-243
Author(s):  
Michael Dinesh Simon ◽  
Kavitha A. R.
Keyword(s):  
Down Syndrome ◽  
Diagnostic Tool ◽  
Chromosome Abnormality ◽  
Genetic Disorder ◽  
Nasal Bone ◽  
Training Phase ◽  
Phase Detection ◽  
Femur Length ◽  
Testing Phase ◽  
Two Phases

Down syndrome is a genetic disorder and the chromosome abnormality observed in humans that can cause physical and mental abnormalities. It can never be cured or rectified. Instead it has to be identified in the fetus and prevented from being born. Many ultrasonographic markers like nuchal fold, nasal bone hypoplasia, femur length, and EIF are considered to be the symptoms of Down syndrome in the fetus. This chapter deals with the creation of automatic and computerized diagnostic tool for Down syndrome detection based on EIF. The proposed system consists of two phases: 1) training phase and 2) testing phase. In training phase, the fetal images with EIF and Down syndrome is analyzed and characteristics of EIF are collected. In testing phase, detection of Down syndrome is performed on the fetal image with EIF based on the knowledge cluster obtained using ESOM. The performance of the proposed system is analyzed in terms of sensitivity, accuracy, and specificity.

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