scholarly journals Molecular Analysis of PKU-Associated PAH Mutations: A Fast and Simple Genotyping Test

2018 ◽  
Vol 1 (3) ◽  
pp. 30
Author(s):  
Manuela Tolve ◽  
Cristiana Artiola ◽  
Amelia Pasquali ◽  
Teresa Giovanniello ◽  
Sirio D’Amici ◽  
...  
Keyword(s):  
Neonatal Screening ◽  
Detection Rate ◽  
Phenylalanine Hydroxylase ◽  
Dried Blood Spots ◽  
Italian Population ◽  
High Detection Rate ◽  
New Variant ◽  
Frequent Mutations ◽  
Second Tier ◽  
The 1960S

Neonatal screening for phenylketonuria (PKU, OMIM: 261600) was introduced at the end of the 1960s. We developed a rapid and simple molecular test for the most frequent phenylalanine hydroxylase (PAH, Gene ID: 5053) mutations. Using this method to detect the 18 most frequent mutations, it is possible to achieve a 75% detection rate in Italian population. The variants selected also reach a high detection rate in other populations, for example, 70% in southern Germany, 68% in western Germany, 76% in Denmark, 68% in Sweden, 63% in Poland, and 60% in Bulgaria. We successfully applied this confirmation test in neonatal screening for hyperphenylalaninemias using dried blood spots and obtained the genotype in approximately 48 h. The method was found to be suitable as second tier test in neonatal screening for hyperphenylalaninemias in neonates with a positive screening test. This test can also be useful for carrier screening because it can bypass the entire coding sequence and intron–exon boundaries sequencing, thereby overcoming the questions that this approach implies, such as new variant interpretations.

scholarly journals Security of Things Intrusion Detection System for Smart Healthcare

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1375
Author(s):  
Celestine Iwendi ◽  
Joseph Henry Anajemba ◽  
Cresantus Biamba ◽  
Desire Ngabo
Keyword(s):  
Genetic Algorithm ◽  
Intrusion Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Detection Rate ◽  
Web Security ◽  
Intrusion Detection Systems ◽  
High Detection Rate ◽  
Detection Systems ◽  
Smart Healthcare

Web security plays a very crucial role in the Security of Things (SoT) paradigm for smart healthcare and will continue to be impactful in medical infrastructures in the near future. This paper addressed a key component of security-intrusion detection systems due to the number of web security attacks, which have increased dramatically in recent years in healthcare, as well as the privacy issues. Various intrusion-detection systems have been proposed in different works to detect cyber threats in smart healthcare and to identify network-based attacks and privacy violations. This study was carried out as a result of the limitations of the intrusion detection systems in responding to attacks and challenges and in implementing privacy control and attacks in the smart healthcare industry. The research proposed a machine learning support system that combined a Random Forest (RF) and a genetic algorithm: a feature optimization method that built new intrusion detection systems with a high detection rate and a more accurate false alarm rate. To optimize the functionality of our approach, a weighted genetic algorithm and RF were combined to generate the best subset of functionality that achieved a high detection rate and a low false alarm rate. This study used the NSL-KDD dataset to simultaneously classify RF, Naive Bayes (NB) and logistic regression classifiers for machine learning. The results confirmed the importance of optimizing functionality, which gave better results in terms of the false alarm rate, precision, detection rate, recall and F1 metrics. The combination of our genetic algorithm and RF models achieved a detection rate of 98.81% and a false alarm rate of 0.8%. This research raised awareness of privacy and authentication in the smart healthcare domain, wireless communications and privacy control and developed the necessary intelligent and efficient web system. Furthermore, the proposed algorithm was applied to examine the F1-score and precisionperformance as compared to the NSL-KDD and CSE-CIC-IDS2018 datasets using different scaling factors. The results showed that the proposed GA was greatly optimized, for which the average precision was optimized by 5.65% and the average F1-score by 8.2%.

scholarly journals Neonatal screening and genotype-phenotype correlation of hyperphenylalaninemia in the Chinese population

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Xin Wang ◽  
Yanyun Wang ◽  
Dingyuan Ma ◽  
Zhilei Zhang ◽  
Yahong Li ◽  
...  
Keyword(s):  
Neonatal Screening ◽  
Phenylalanine Hydroxylase ◽  
Laboratory Data ◽  
Molecular Characteristics ◽  
Phenotype Correlation ◽  
Common Amino Acid ◽  
Appropriate Treatment ◽  
Clinical Presentations ◽  
Average Current

Abstract Background Hyperphenylalaninemia (HPA) is the most common amino acid metabolic disease involving phenylalanine hydroxylase (PAH, OMIM*612,349) deficiency or coenzyme tetrahydrobiopterin (BH4) deficiency. Patients with severe HPA often have a difficult life. Early diagnosis of HPA before the development of symptoms is possible via neonatal screening, facilitating appropriate treatment and reducing mortality and disability rates. This study revealed the prevalence, mutational and phenotypic spectrum, and prognosis of HPA by neonatal screening from January 2001 to September 2020 in Nanjing, Jiangsu Province, China. Methods Through a retrospective analysis of the information available in the neonatal screening database, the clinical presentations, laboratory data, molecular characteristics and treatment follow-up data of HPA patients detected by neonatal screening were evaluated. Results We diagnosed 181 patients with HPA from 1 to 957 newborns, giving an incidence of 1:6873. Among these patients, 177 were identified as PAH deficient and four patients were BH4 deficient. The average current age of the patients was 6.38 years old. The most common mutations of PAH were c.728 C > A/ p.Arg243Gln (13.83 %), c.158G > A/ p.Arg53His (9.57 %), c.611 A > G/ p.Tyr204Cys (7.44 %), and c.721 C > T/ p.Arg241Cys (6.38 %). Conclusions This study revealed the prevalence, phenotype-genotype, and prognosis of HPA in China and contributes to the updating of PAHD data for China and worldwide. Our study not only expanded the spectrum of phenotypes and genotype but also provided a valuable tool for improved genetic counseling and management of future cases.

scholarly journals Wildlife Monitoring Using a Multi-UAV System with Optimal Transport Theory

2021 ◽  
Vol 11 (9) ◽  
pp. 4070
Author(s):  
Rabiul Hasan Kabir ◽  
Kooktae Lee
Keyword(s):  
Detection Rate ◽  
Transport Theory ◽  
Optimal Transport ◽  
Position Estimation ◽  
Wildlife Monitoring ◽  
High Detection Rate ◽  
Monitoring Strategies ◽  
Spatio Temporal ◽  
Optimal Transport Theory ◽  
Multi Uav

This paper addresses a wildlife monitoring problem using a team of unmanned aerial vehicles (UAVs) with the optimal transport theory. The state-of-the-art technology using UAVs has been an increasingly popular tool to monitor wildlife compared to the traditional methods such as satellite imagery-based sensing or GPS trackers. However, there still exist unsolved problems as to how the UAVs need to cover a spacious domain to detect animals as many as possible. In this paper, we propose the optimal transport-based wildlife monitoring strategy for a multi-UAV system, to prioritize monitoring areas while incorporating complementary information such as GPS trackers and satellite-based sensing. Through the proposed scheme, the UAVs can explore the large-size domain effectively and collaboratively with a given priority. The time-varying nature of wildlife due to their movements is modeled as a stochastic process, which is included in the proposed work to reflect the spatio-temporal evolution of their position estimation. In this way, the proposed monitoring plan can lead to wildlife monitoring with a high detection rate. Various simulation results including statistical data are provided to validate the proposed work. In all different simulations, it is shown that the proposed scheme significantly outperforms other UAV-based wildlife monitoring strategies in terms of the target detection rate up to 3.6 times.

Neonatal screening for cystic fibrosis, using immunoreactive trypsin assay in dried blood spots

1981 ◽  
Vol 113 (2) ◽  
pp. 111-121 ◽  
Author(s):  
Jeanette R. Crossley ◽  
Patricia A. Smith ◽  
Brian W. Edgar ◽  
Peter D. Gluckman ◽  
Robert B. Elliott
Keyword(s):  
Cystic Fibrosis ◽  
Neonatal Screening ◽  
Dried Blood Spots ◽  
Immunoreactive Trypsin ◽  
Blood Spots

Clinical and Genetic Characteristics of Phenylketonuria in Ryazan Region

2021 ◽  
Vol 29 (1) ◽  
pp. 5-12
Author(s):  
Grigorii I. Yakubovskii ◽  
Olga B. Serebriakova ◽  
Alina G. Yakubovskaya ◽  
Nadezhda V. Ruban ◽  
Angelina A. Lyakhovets
Keyword(s):  
Blood Level ◽  
Phenylalanine Hydroxylase ◽  
Clinical Course ◽  
Molecular Genetic ◽  
Residual Activity ◽  
Speech Development ◽  
Genetic Characteristics ◽  
Frequent Mutations ◽  
R408w Mutation ◽  
Pah Gene

Aim. This investigation seeks to determine the incidence of phenylketonuria in the Ryazan region, assess the spectrum of mutations in the PAH gene (phenylalanine hydroxylase), investigate the interrelationship between the diseases clinical course, the phenylalanine blood level, and the patients genotype. Materials and Methods. The incidence of phenylketonuria was studied based on the data of massive neonatal screening for the period from 2000 to 2019. Molecular genetic examination of mutations was conducted in 39 patients using the allele-specific multiplex ligation method. The interrelationship between the phenylalanine blood level on the fifth day of life and retest, the diseases clinical course, and the patients genotype was assessed according to the medical record data of 33 patients under dispensary observation in a medico-genetic clinic. The patients were divided into two groups. The first group (n=21) had two severe mutations (residual activity of phenylalanine hydroxylase 10%). The second group (n=12) had one severe and one mild mutation (the residual activity of the enzyme 10%). Results. The incidence of phenylketonuria in the Ryazan region was one in 5054 newborns, exceeding the Russian Federations average parameters. Eighteen mutations were discovered in the PAH gene. The most frequent was the R408W mutation (56.4% alleles). The second most frequent mutations were the IVS10-11GA (6.4%) and P281L (5.1%). The R158Q and Y418C mutations occurred with a frequency of 4.1% and Е280К mutation of 2.7%. All the rest of the mutations occurred as single cases. Investigation of the interrelationship between the phenylalanine blood level, the diseases clinical course, and the patients genotype revealed a reliably higher content of amino acid in the first group on retest (32.11.7 mg/% vs. 17.71.5 mg/% in the second group, р0.001) and predomination of more severe forms of phenylketonuria (90.5% vs. 41.7%, respectively, р0.001). Disorders in neuropsychic and speech development were present in 28.6% of patients in the first group but were absent in the second group. Conclusion. By conducting the study, the incidence of phenylketonuria was determined in the Ryazan region. The spectrum of mutations in the PAH gene was defined. The interrelationship between the diseases clinical portrait, the phenylalanine blood level, and the patients PAH genotype was revealed.

scholarly journals High Reliability of Neonatal Screening for Congenital Adrenal Hyperplasia in Switzerland

2002 ◽  
Vol 87 (9) ◽  
pp. 4106-4110 ◽  
Author(s):  
Michael Steigert ◽  
Eugen J. Schoenle ◽  
Anna Biason-Lauber ◽  
Toni Torresani
Keyword(s):  
Positive Predictive Value ◽  
Congenital Adrenal Hyperplasia ◽  
Predictive Value ◽  
Neonatal Screening ◽  
Screening Program ◽  
High Reliability ◽  
Dried Blood Spots ◽  
Recall Rate ◽  
Adrenal Hyperplasia ◽  
Salt Wasting

Newborn screening for congenital adrenal hyperplasia (CAH) is justified by the sometimes difficult clinical diagnosis and the risks associated with missed diagnosis, particularly the life-threatening salt-wasting crisis. In Switzerland, nationwide screening for CAH by measuring 17-hydroxyprogesterone levels in dried blood spots was introduced in 1992. At the Zurich University Children’s Hospital, 50% of the population of Switzerland is screened. The aim of the study was to evaluate the efficiency of the Zurich screening program. Between January 1, 1993, and May 31, 2001, 333,221 newborns were screened for CAH. Thirty-one newborns had CAH (incidence, 1 in 10,749); 30 were detected through screening (sensitivity, 97%). A recall for suspected CAH was performed in only 60 cases, corresponding to a very low recall rate (0.0018%). In 30 recalls CAH was confirmed (positive predictive value, 50%; specificity, 99.99%). Fifteen of 31 patients profited from screening, as CAH had not been recognized clinically. The timely availability of screening results made therapy possible within the first week of life in most cases and helped in preventing salt-wasting crisis in all patients. With a sensitivity of 97%, a specificity of 99.99%, and a positive predictive value of 50%, the Zurich neonatal screening program for CAH can be considered highly reliable.

scholarly journals Network Anomaly Detection System with Optimized DS Evidence Theory

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Yuan Liu ◽  
Xiaofeng Wang ◽  
Kaiyu Liu
Keyword(s):  
Anomaly Detection ◽  
Detection Rate ◽  
Computer Network ◽  
Detection System ◽  
Evidence Theory ◽  
Optimization Methods ◽  
High Detection Rate ◽  
Detection Model ◽  
Network Anomaly Detection ◽  
Anomaly Detection System

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor’s regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.

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