Until vaccines and effective therapeutics become available, the practical solution to transit safely out of the current coronavirus disease 19 (CoVID-19) lockdown may include the implementation of an effective testing, tracing and tracking system. However, this requires a reliable and clinically validated diagnostic platform for the sensitive and specific identification of SARS-CoV-2. Here, we report on the development of a de novo, high-resolution and comparative genomics guided reverse-transcribed loop-mediated isothermal amplification (LAMP) assay. To further enhance the assay performance and to remove any subjectivity associated with operator interpretation of results, we engineered a novel hand-held smart diagnostic device. The robust diagnostic device was further furnished with automated image acquisition and processing algorithms and the collated data was processed through artificial intelligence (AI) pipelines to further reduce the assay run time and the subjectivity of the colorimetric LAMP detection. This advanced AI algorithm-implemented LAMP (ai-LAMP) assay, targeting the RNA-dependent RNA polymerase gene, showed high analytical sensitivity and specificity for SARS-CoV-2. A total of ~200 coronavirus disease (CoVID-19)-suspected NHS patient samples were tested using the platform and it was shown to be reliable, highly specific and significantly more sensitive than the current gold standard qRT-PCR. Therefore, this system could provide an efficient and cost-effective platform to detect SARS-CoV-2 in resource-limited laboratories.

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OBJECTIVE: Studies show partial improvements in some core symptoms of Autism Spectrum Disorders (ASD) in time. However, the predictive factors (e.g. pretreatment IQ, comorbid psychiatric disorders, adaptive, and language skills, etc.) for a better the outcome was not studied with machine learning methods. We aimed to examine the predictors of outcome with machine learning methods, which are novel computational methods including statistical estimation, information theories and mathematical learning automatically discovering useful patterns in large amounts of data. METHOD: The study the group comprised 433 children (mean age: 72.3 ± 45.9 months) with ASD diagnosis. The ASD symptoms were assessed by the Autism Behavior Checklist, Aberrant Behavior Checklist, Clinical Global Impression scales at baseline (T0) and 12th (T1), 24th (T2), and 36th (T3) months. We tested the performance of for machine learning algorithms (Naive Bayes, Generalized Linear Model, Logistic Regression, Decision Tree) on our data, including the 254 items in the baseline forms. Patients with ≤2 CGI points in ASD symptoms at in 36 months were accepted as the group who has "better outcome" as the prediction class. RESULTS: The significant proportion of the cases showed significant improvement in ASD symptoms (39.7% in T1, 60.7% in T2; 77.8% in T3). Our machine learning model in T3 showed that diagnosis group affected the prognosis. In the autism group, older father and mother age; in PDD-NOS group, MR comorbidity, less birth weight and older age at diagnosis have a worse outcome. In Asperger's Disorder age at diagnosis, age at first evaluation and developmental cornerstones has affected prognosis. CONCLUSION: In accordance with other studies we found early age diagnosis, early start rehabilitation, the severity of ASD symptoms at baseline assessment predicted outcome. Also, we found comorbid psychiatric diagnoses are affecting the outcome of ASD symptoms in clinical observation. The machine learning models reveal several others are more significant (e.g. parental age, birth weight, sociodemographic variables, etc.) in terms of prognostic information and also planning treatment of children with ASD.

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The purpose of this study is to examine the relationship between high school students’ social support, career adaptability and subjective well-being that are perceived from their family, teachers and friends. The study group consisted of 325 students (193 girls, 132 males) in three secondary schools located in Cukurova and Yuregir districts of Adana city. The data were collected through Career Adaptability Scale, Life Satisfaction Scale, Positive and Negative Affect Schedule and Perceived Social Support Scale and Personal Information Form developed by the researchers to reach the demographic information of the participants. A path analysis was conducted within the framework of structural equation modeling to investigate the relationship between social support, career adaptability and subjective well-being that the students perceived. Data analysis was done through SPSS and AMOS package programs. Correlation coefficients of arithmetic mean, standard deviation, pearson moment analysis were calculated, and path analysis was performed based on the observed variables. The research findings show that there is a significant relationship between subjective well-being, career adaptability and perceived social support. The perceived social support from family, teachers and friends are variables that predict the career adaptability of high school students. Career adaptability has also been found to be a significant predictor of subjective well-being.

Until vaccines and effective therapeutics become available, the practical way to transit safely out of the current lockdown may include the implementation of an effective testing, tracing and tracking system. However, this requires a reliable and clinically validated diagnostic platform for the sensitive and specific identification of SARS-CoV-2. Here, we report on the development of a de novo, high-resolution and comparative genomics guided reverse-transcribed loop-mediated isothermal amplification (LAMP) assay. To further enhance the assay performance and to remove any subjectivity associated with operator interpretation of result, we engineered a novel hand-held smart diagnostic device. The robust diagnostic device was further furnished with automated image acquisition and processing algorithms, and the collated data was processed through artificial intelligence (AI) pipelines to further reduce the assay run time and the subjectivity of the colorimetric LAMP detection. This advanced AI algorithm-implemented LAMP (ai-LAMP) assay, targeting the RNA-dependent RNA polymerase gene, showed high analytical sensitivity and specificity for SARS-CoV-2. A total of ~200 coronavirus disease (CoVID-19)-suspected patient samples were tested using the platform and it was shown to be reliable, highly specific and significantly more sensitive than the current gold standard qRT-PCR. The system could provide an efficient and cost-effective platform to detect SARS-CoV-2 in resource-limited laboratories.

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ÖZ Genç yetişkinlik, romantik ilişkilerin ön planda olduğu bir gelişimsel dönemdir ve bu dönemde sağlıklı romantik ilişkiler kurma konusunda genç yetişkinler çeşitli problemler yaşayabilmektedir. Bu araştırmada, genç yetişkin bireylere yönelik geliştirilen romantik ilişki becerileri psikoeğitim programının etkinliğinin sınanması hedeflenmiştir. Psikoeğitim programının etkinliğinin sınanması nicel ve nitel yolla gerçekleştirilmeye çalışılmıştır. Araştırmada ön test-son test kontrol gruplu yarı deneysel desen kullanılmıştır. Psikoeğitim programının etkinliğini nicel olarak test etmek için karma desen iki yönlü ANOVA testi kullanılmıştır. Ayrıca programın uzun süreli etkinliğini nitel olarak sınamak için müdahale sonrasında katılımcılarla odak grup görüşmesi gerçekleştirilmiştir. Çalışma grubu, Akdeniz bölgesinde yer alan bir üniversitede öğrenim gören ve en az altı aydır devam eden bir romantik ilişkisi olan 24 (deney grubunda 12, kontrol grubunda 12) üniversite öğrencisinden oluşmaktadır. Psikoeğitim programının etkinliğini nicel olarak sınamak için katılımcıların ilişki doyumları incelenmiş ve bunun için ön test ve son test ölçümlerinde İlişki İstikrarı Ölçeği'nin ilişki doyumu alt ölçeği kullanılmıştır. Deney ve kontrol gruplarının tekrarlı ölçümlerinden elde edilen ilişki doyumu düzeylerine ilişkin toplam puanları arasında anlamlı bir fark olmadığı ancak gruplar içi ön test ve son test ilişki doyumu düzeylerine ilişkin puanlar arasında anlamlı bir fark olduğu belirlenmiştir. Ayrıca, farklı işlem gruplarında olmak ile tekrarlı ölçümler faktörlerinin ilişki doyumu üzerindeki ortak etkilerinin anlamlı olduğu belirlenmiştir. Buna göre deney grubundaki katılımcıların, kontrol grubunda olup bu eğitimi almayan katılımcılara göre ilişki doyumu düzeylerinde anlamlı bir artış olduğunu belirlenmiştir. Odak grup görüşmesinden elde edilen bulgulara göre, psikoeğitim programından sonra katılımcıların ilişki doyumlarındaki olumlu gelişimin devam ettiği görülmüştür. Ayrıca katılımcılar iletişim, ilişki inançları, hedefe ulaşma ve beklentiler gibi konularda kazandıkları bilgi, beceri ve farkındalıkların ilişkilerini olumlu yönde etkilediğini ifade etmişlerdir. Araştırma sonucunda elde edilen hem nicel hem de nitel bulgular psikoeğitim programının amacına ulaştığını göstermiştir.