Correction to: a novel biallelic lck variant resulting in profound t-cell ımmune deficiency and review of the literature

Lymphocyte-specific protein tyrosine kinase (LCK) is an SRC-family kinase critical for initiation and propagation of T-cell antigen receptor (TCR) signaling through phosphorylation of TCR-associated CD3 chains and recruited downstream molecules. Until now, only one case of profound T-cell immune deficiency with complete LCK deficiency [1] caused by a biallelic missense mutation (c.1022T>C, p.L341P) and three cases of incomplete LCK deficiency [2] caused by a biallelic splice site mutation (c.188-2A>G) have been described. Additionally, deregulated LCK expression has been associated with genetically undefined immune deficiencies and hematological malignancies. Here, we describe the second case of complete LCK deficiency in a 6-month-old girl born to consanguineous parents presenting with profound T-cell immune deficiency. Whole exome sequencing (WES) revealed a novel pathogenic biallelic missense mutation in LCK (c.1393T>C, p.C465R), which led to the absence of LCK protein expression and phosphorylation, and a consecutive decrease in proximal TCR signaling. Loss of conventional CD4+ and CD8+ αβT-cells and homeostatic T-cell expansion was accompanied by increased γδT-cell and Treg percentages. Surface CD4 and CD8 co-receptor expression was reduced in the patient T-cells, while the heterozygous mother had impaired CD4 and CD8 surface expression to a lesser extent. We conclude that complete LCK deficiency is characterized by profound T-cell immune deficiency, reduced CD4 and CD8 surface expression, and a characteristic TCR signaling disorder. CD4 and CD8 surface expression may be of value for early detection of mono- and/or biallelic LCK deficiency. © 2023, The Author(s)

Hope, childhood experiences, and achievement motivation in high school students: A mixed methods study

The aim of the study is to examine the role of childhood experiences and achievement motivation in high school students' hope levels. The quantitative (N = 686, 43.9% females and 56.1% males, aged between 13 and 19; Mage = 16.02, standard deviation = 1.23) and qualitative data of the study, in which enriched design was used, were collected from high school students studying in the Southeast of Turkey. Hierarchical regression was used in the quantitative part of the study and content analysis was carried out in the qualitative part. It is seen that the results in the qualitative analysis part largely coincide with the results in the quantitative part. The results denote that high school students have high hope levels. Also, according to the results, there is a negative, low-level, and significant relationship between childhood experiences and hope, and a positive and moderately significant relationship between hope and achievement motivation. Although childhood experiences and achievement motivation significantly predict the level of hope, it is concluded that achievement motivation contributes more to the hope-related variance which is explained. The findings reveal the value of achievement motivation and childhood experiences in understanding adolescents' hope multidimensionally. © 2024 Wiley Periodicals LLC

Adaptation of the computational thinking skills assessment tool (techcheck-k) in early childhood

In the early years, it has become essential to support the acquisition of computational thinking, which is seen as a 21st-century skill and new literacy. A valid and reliable measurement tool is needed to develop and evaluate educational practices related to these skills. TechCheck is a validated unplugged assessment of computational thinking skills for young children. (Relkin & Bers in IEEE Global Engineering Education Conference (EDUCON) in 2021 (pp. 1696–1702), 2021; Relkin et al. in Journal of Science Education and Technology 29(4):482–498, 2020). This study aims to adapt and characterize a Turkish version of TechCheck-K for children aged 5–6. Validity and reliability of the Turkish version were established through classical test theory and item response theory, as had been done for the original English language version. Based on classical test theory, the confirmatory factor analysis used A tetrachoric weighted matrix to test the instrument’s structure. The one-dimensional structure of the instrument was verified. The KR-20 reliability coefficient for the scale consisting of one dimension and 15 items was.87, which is considered an acceptable level of reliability. Rasch and 2PL models were compared with M2 statistics to determine the item and test parameters based on item response theory (IRT). The 2PL model was chosen as the best fit. Mean TechCheck scores differed based on gender, socio-economic status, past exposure to computers, and coding experience. These results indicate that the Turkish version of TechCheck-K has acceptable psychometric properties for measuring computational thinking skills in children between 5 and 6 years of age. © 2024, The Author(s), under exclusive licence to Springer Nature B.V

Psychometric testing of the newborn skin assessment attitude scale in neonatal ıcu nurses

OBJECTIVE To develop a Newborn Skin Assessment Attitude Scale (NSAAS) for neonatal ICU (NICU) RNs. METHODS The study was conducted with 326 nurses working in NICUs in three cities in Turkey. The researchers evaluated the content and construct validity and reliability of the scale with item-Total score correlation analysis, the test-retest method, and calculating the Cronbach α reliability coefficient. RESULTS The content validity index of the scale ranged between 0.87 and 1.00. Prior to exploratory factor analysis and confirmatory factor analysis, the Kaiser-Meyer-Olkin coefficient of the NSAAS was 0.976, and the Bartlett test of sphericity result was χ2 = 15,337.052 (P [removed].05). CONCLUSIONS The NSAAS can be reliably used for measuring NICU nurses' attitudes toward newborn skin assessment. © Wolters Kluwer Health, Inc. All rights reserved

Highly efficient family of two-step simultaneous method for all polynomial roots

In this article, we constructed a derivative-free family of iterative techniques for extracting simultaneously all the distinct roots of a non-linear polynomial equation. Convergence analysis is discussed to show that the proposed family of iterative method has fifth order convergence. Nonlinear test models including fractional conversion, predator-prey, chemical reactor and beam designing models are included. Also many other interesting results concerning symmetric problems with application of group symmetry are also described. The simultaneous iterative scheme is applied starting with the initial estimates to get the exact roots within the given tolerance. The proposed iterative scheme requires less function evaluations and computation time as compared to existing classical methods. Dynamical planes are exhibited in CAS-MATLAB (R2011B) to show how the simultaneous iterative approach outperforms single roots finding methods that might confine the divergence zone in terms of global convergence. Furthermore, convergence domains, namely basins of attraction that are symmetrical through fractal-like edges, are analyzed using the graphical tool. Numerical results and residual graphs are presented in detail for the simultaneous iterative method. An extensive study has been made for the newly developed simultaneous iterative scheme, which is found to be efficient, robust and authentic in its domain. © 2023 the Author(s), licensee AIMS Press

A novel molecularly imprinted electrochemical sensor based on graphitic carbon nitride nanosheets decorated bovine serum albumin@MnO2 nanocomposite for zearalenone detection

Zearalenone (ZEA), as a carcinogenic mycotoxin, is widely found in a wide variety of food products such as grains and its carcinogenicity, neurotoxicity, and estrogenic effects on humans were reported. In this report, a novel electrochemical sensor based on graphitic carbon nitride nanosheets decorated bovine serum albumin@MnO2 (g-C3N4NS/BSA@MnO2) nanocomposite and molecularly imprinted polymers (MIPs) was developed and applied to rice samples for ZEA determination. Firstly, the synthesis of bulk g-C3N4 by thermal poly-condensation method was completed. After the ultra-sonication treatment of bulk g-C3N4 providing graphitic carbon nitride nanosheets, the nanocomposite was successfully produced via electrostatic forces between g-C3N4NS and BSA@MnO2. Then, a novel MIP-based electrochemical electrode including g-C3N4NS/BSA@MnO2 was prepared in the presence of ZEA as target analyte and pyrrole (Py) monomer by cyclic voltammetry (CV). The formed electrochemical sensor exhibited a linearity of 1.0 – 10.0 ng L−1 with a detection limit (LOD) of 0.25 ng L−1. Furthermore, the high selectivity, reproducibility and stability of the prepared MIPebased electrochemical sensor exhibited that it could be used in real sample analysis such as rice. © 2023 Elsevier Inc

A meta-analysis of applied behavior analysis-based ınterventions for ındividuals with autism spectrum disorders (asd) in Turkey

Interventions based on the principles of applied behavior analysis (ABA) have been determined to be evidenced-based practices and are widely used with individuals with autism spectrum disorders (ASD) across the world. Originally developed in the USA, implementation of these interventions has become widespread in the last decade in Turkey. Given the significance of culture in guiding ABA practices, this meta-analysis investigated the prevalence and the magnitude effects of ABA-based interventions and whether specific participant and intervention characteristics moderated such effects in Turkey. Seventy-one ABA-based intervention studies were assessed based on What Works Clearinghouse (WWC, Kratochwill et al., Remedial and Special Education, 34(1), 26–38, 2013) design standards (DSs) including (a) systematic manipulation of independent variables, (b) interrater reliability, (c) three demonstrations of the intervention effect, and (d) adequate number of data points collected for each condition. Forty-three studies that met WWC (Kratochwill et al., Remedial and Special Education, 34(1), 26–38, 2013) DSs were analyzed and calculated with baseline-corrected tau (Tarlow, Behavior Modification, 41(4), 427–467, 2017). Furthermore, performance-criteria-based effect size values (PCES; Aydin and Tanious, Journal of Applied Behavior Analysis, 2021) were calculated for 27 studies that had mastery criteria. While the overall tau appeared to be large 0.71 (p = 0.072, se = 0.254), the overall effect size for PCES revealed a small effect of 0.73. The comparisons of all sub-categories’ effect sizes of moderator variables were not statistically significant based on Kruskal Wallis or Mann Whitney U tests. Additionally, findings revealed that studies were predominantly implemented by highly trained researchers in segregated one-on-one settings, and did not include adults with ASD nor challenging behavior. Overall, there has been significant growth in ABA-based interventions in Turkey that show promise in improving the lives of individuals with ASD. However, further research and cultural considerations are essential for a comprehensive understanding of their impact in the Turkish context. Findings from two different effect size analyses and recommendations for future studies are discussed. © 2024, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply

Deep eutectic solvent liquid phase microextraction, powered by ultrasonic system, for determination of β-carotene in food samples

The research work is mainly concerned with the extraction of beta-carotene, which is a terpenoid compound, from food and fruit samples using deep eutectic solvent based liquid phase extraction. Deep eutectic solvent liquid phase microextraction method, powered by ultrasonic mixing, (DES-UP-LPME) was carried out with deep eutectic solvent (DES) consisting of tetrabutylammoniumbromide (TBAB) and decanoic acid (DA). Key parameters such as pH, sample volume, tetrahydrofuran (THF) volume, DES type and volume, matrix effect, ultra-sonication/centrifugation time were optimized to increase the extraction efficiency of beta-carotene. Quantitative recoveries were obtained when pH, TBAB:DA ratio and sample volume were 3, 1:3 and 30, respectively. The limit of detection (LOD) and limit of quantification (LOQ) were found to be 0.005 mu g/mL and 0.015 mu g/mL, respectively. Various food samples were analyzed spectrophotometrically by using the developed DES-UP-LPME at 450 nm. The addition/recovery studies were also performed on water samples to evaluate the accuracy of the method

Machine learning models for early prediction of mortality risk in patients with burns: A single center experience

Mortality rate is considered as the most important outcome measure for assessing the severity of burn injury. A scale or model that accurately predicts burn mortality can be useful to determine the clinical course of burn injuries, discuss treatment options and rehabilitation with patients and their families, and evaluate novel, innovative interventions for the injuries. This study aimed to use machine learning models to predict the mortality risk of patients with burns after their first admission to the center and to compare the performances of these models. Overall, 1064 patients hospitalized in burn intensive care and burn service units between 2016 and 2022 were included in the study. In total, 40 parameters, including demographic characteristics and biochemical parameters of all patients, were analyzed in the study. Furthermore, the dataset was randomly divided into two clusters with 70% of the data used for artificial neural networks (ANNs) training and 30% for model success testing. The ANN model proposed in this study showed high success across all machine learning methods tried in different variants, with an accuracy of 95.92% in the test set. Machine learning models can be used to predict the mortality risk of patients with burns. This study may help validate the use of machine learning models for applications in clinical practice. Conducting multicenter studies will further contribute to the literature. © 2023 British Association of Plastic, Reconstructive and Aesthetic Surgeon

Modeling natural resources for ecological sustainability

While natural resource consumption is critical for almost all production processes, the overdependence on and poor governance of those resources might result not only in natural resource depletion but also in ecological unsustainability. Against this background, the present research explores the novel perspective on how financial inclusivity moderates the effects of decentralized governance systems and natural resource reliance on ecological sustainability in the presence of research and development (R&D) expenditures. This research employs a novel method of moments quantile regression on data from eight selected OECD countries during 1995–2020. It is found that decentralized governance systems deteriorate ecological sustainability across all quantiles, with a more substantial impact for higher quantiles of ecological intensity. Natural resource reliance also hinders ecological sustainability, with the degree of effects decreasing from lower to higher quantiles of ecological intensity. Financial inclusion directly mitigates ecological unsustainability, manifesting a more powerful influence in ecologically more intensive countries. Concerning moderation, financial inclusivity negatively moderates the influence of decentralized governance systems and natural resource reliance on ecological intensity, showing stronger relationships in ecologically more intensive countries. Taking the other covariates into account, the EKC curve is uncovered to exist for all levels of ecological sustainability. Moreover, the labor force participation rate exerts ecological pressures, especially for countries with low ecological sustainability. Besides, R&D expenditures are negatively associated with ecological intensity and are responsible for the betterment of the OECD's ecological sustainability. The baseline findings are robust to those of additional models employing ecological footprint as an alternative dependent variable. Findings implicate that subnational governments should promote (i) green microfinancing to resource-efficient investments, (ii) funding to small businesses extending sustainable business solutions, (iii) green finance thinking among the general public, and (iv) financing to localized sustainability projects. © 2023 International Association for Gondwana Researc