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BMC Psychology Jun 2024Video games have become a prevalent source of entertainment, especially among children. Furthermore, the amount of time spent playing video games has grown dramatically....
BACKGROUND
Video games have become a prevalent source of entertainment, especially among children. Furthermore, the amount of time spent playing video games has grown dramatically. The purpose of this research was to examine the mediation effects of attention and child memory on the relationship between video games addiction and cognitive and learning abilities in Egyptian children.
METHODS
A cross-sectional research design was used in the current study in two schools affiliated with Dakahlia District, Egypt. The study included 169 children aged 9 to 13 who met the inclusion criteria, and their mothers provided the questionnaire responses. The data collection methods were performed over approximately four months from February to May. Data were collected using different tools: Socio-demographic Interview, Game Addiction Scale for Children (GASC), Children's Memory Questionnaire (CMQ), Clinical Attention Problems Scale, Learning, Executive, and Attention Functioning (LEAF) Scale.
RESULTS
There was a significant indirect effect of video game addiction on cognitive and learning skills through attention, but not child memory. Video game addiction has a significant impact on children's attention and memory. Both attention and memory have a significant impact on a child's cognitive and learning skills.
CONCLUSIONS
These results revealed the significant effect of video game addiction on cognitive and learning abilities in the presence of mediators. It also suggested that attention-focused therapies might play an important role in minimizing the harmful effects of video game addiction on cognitive and learning abilities.
Topics: Humans; Child; Female; Male; Attention; Video Games; Adolescent; Cross-Sectional Studies; Memory; Learning; Cognition; Behavior, Addictive; Egypt; Internet Addiction Disorder; Executive Function
PubMed: 38915089
DOI: 10.1186/s40359-024-01849-9 -
Journal of Cancer Research and Clinical... Jun 2024Pancreatic ductal adenocarcinoma (PDAC) is renowned for its formidable and lethal nature, earning it a notorious reputation among malignant tumors. Due to its...
Identified γ-glutamyl cyclotransferase (GGCT) as a novel regulator in the progression and immunotherapy of pancreatic ductal adenocarcinoma through multi-omics analysis and experiments.
BACKGROUND
Pancreatic ductal adenocarcinoma (PDAC) is renowned for its formidable and lethal nature, earning it a notorious reputation among malignant tumors. Due to its challenging early diagnosis, high malignancy, and resistance to chemotherapy drugs, the treatment of pancreatic cancer has long been exceedingly difficult in the realm of oncology. γ-Glutamyl cyclotransferase (GGCT), a vital enzyme in glutathione metabolism, has been implicated in the proliferation and progression of several tumor types, while the biological function of GGCT in pancreatic ductal adenocarcinoma remains unknown.
METHODS
The expression profile of GGCT was validated through western blotting, immunohistochemistry, and RT-qPCR in both pancreatic cancer tissue samples and cell lines. Functional enrichment analyses including GSVA, ssGSEA, GO, and KEGG were conducted to explore the biological role of GGCT. Additionally, CCK8, Edu, colony formation, migration, and invasion assays were employed to evaluate the impact of GGCT on the proliferation and migration abilities of pancreatic cancer cells. Furthermore, the LASSO machine learning algorithm was utilized to develop a prognostic model associated with GGCT.
RESULTS
Our study revealed heightened expression of GGCT in pancreatic cancer tissues and cells, suggesting an association with poorer patient prognosis. Additionally, we explored the immunomodulatory effects of GGCT in both pan-cancer and pancreatic cancer contexts, found that GGCT may be associated with immunosuppressive regulation in various types of tumors. Specifically, in patients with high expression of GGCT in pancreatic cancer, there is a reduction in the infiltration of various immune cells, leading to poorer responsiveness to immunotherapy and worse survival rates. In vivo and in vitro assays indicate that downregulation of GGCT markedly suppresses the proliferation and metastasis of pancreatic cancer cells. Moreover, this inhibitory effect appears to be linked to the regulation of GGCT on c-Myc. A prognostic model was constructed based on genes derived from GGCT, demonstrating robust predictive ability for favorable survival prognosis and response to immunotherapy.
Topics: Humans; Carcinoma, Pancreatic Ductal; Pancreatic Neoplasms; gamma-Glutamylcyclotransferase; Immunotherapy; Disease Progression; Cell Proliferation; Prognosis; Cell Line, Tumor; Biomarkers, Tumor; Female; Gene Expression Regulation, Neoplastic; Male; Cell Movement; Multiomics
PubMed: 38914714
DOI: 10.1007/s00432-024-05789-0 -
NeuroImage Jun 2024Research into magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) has recently increased, as results from studies in different diseases and populations... (Review)
Review
Research into magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) has recently increased, as results from studies in different diseases and populations are cementing their association with sleep, disease phenotypes, and overall health indicators. With the establishment of worldwide consortia and the availability of large databases, computational methods that allow to automatically process all this wealth of information are becoming increasingly relevant. Several computational approaches have been proposed to assess PVS from MRI, and efforts have been made to summarise and appraise the most widely applied ones. We systematically reviewed and meta-analysed all publications available up to September 2023 describing the development, improvement, or application of computational PVS quantification methods from MRI. We analysed 67 approaches and 60 applications of their implementation, from 112 publications. The two most widely applied were the use of a morphological filter to enhance PVS-like structures, with Frangi being the choice preferred by most, and the use of a U-Net configuration with or without residual connections. Older adults or population studies comprising adults from 18 years old onwards were, overall, more frequent than studies using clinical samples. PVS were mainly assessed from T2-weighted MRI acquired in 1.5T and/or 3T scanners, although combinations using it with T1-weighted and FLAIR images were also abundant. Common associations researched included age, sex, hypertension, diabetes, white matter hyperintensities, sleep and cognition, with occupation-related, ethnicity, and genetic/hereditable traits being also explored. Despite promising improvements to overcome barriers such as noise and differentiation from other confounds, a need for joined efforts for a wider testing and increasing availability of the most promising methods is now paramount.
PubMed: 38914212
DOI: 10.1016/j.neuroimage.2024.120685 -
PloS One 2024With a globally aging population, there is a need to better understand how brain structure relates to function in healthy older and younger adults. (Comparative Study)
Comparative Study
OBJECTIVE
With a globally aging population, there is a need to better understand how brain structure relates to function in healthy older and younger adults.
METHODS
34 healthy participants divided into older (17; Mean = 70.9, SD = 5.4) and younger adults (17; Mean = 28.1, SD = 2.8) underwent diffusion-weighted imaging and neuropsychological assessment, including the California Verbal Learning Test 2nd Edition and the Trail Making Test (TMT-A and TMT-B). Differences in white matter microstructure for older and younger adults and the association between DTI metrics (fractional anisotropy, FA; mean diffusivity, MD) and cognitive performance were analyzed using tract-based spatial statistics (p < 0.05, corrected).
RESULTS
Older adults had significantly lower FA and higher MD than younger adults in widespread brain regions. There was a significant negative correlation between executive function (TMT-B) and MD for older adults in the right superior/anterior corona radiata and the corpus callosum. No significant relationship was detected between DTI metrics and executive function in younger adults or with memory performance in either group.
CONCLUSIONS
The findings underscore the need to examine brain-behaviour relationships as a function of age. Future studies should include comprehensive assessments in larger lifespan samples to better understand the aging brain.
Topics: Humans; White Matter; Aged; Male; Female; Adult; Neuropsychological Tests; Diffusion Tensor Imaging; Aging; Middle Aged; Executive Function; Cognition; Young Adult; Diffusion Magnetic Resonance Imaging; Brain; Aged, 80 and over; Anisotropy
PubMed: 38913655
DOI: 10.1371/journal.pone.0305818 -
Biology Open Jun 2024Changes in mitochondrial distribution are a feature of numerous age-related neurodegenerative diseases. In Drosophila, reducing the activity of Cdk5 causes a...
Changes in mitochondrial distribution are a feature of numerous age-related neurodegenerative diseases. In Drosophila, reducing the activity of Cdk5 causes a neurodegenerative phenotype and is known to affect several mitochondrial properties. Therefore, we investigated whether alterations of mitochondrial distribution are involved in Cdk5-associated neurodegeneration. We find that reducing Cdk5 activity does not alter the balance of mitochondrial localization to the somatodendritic vs. axonal neuronal compartments of the mushroom body, the learning and memory center of the Drosophila brain. We do, however, observe changes in mitochondrial distribution at the axon initial segment (AIS), a neuronal compartment located in the proximal axon involved in neuronal polarization and action potential initiation. Specifically, we observe that mitochondria are partially excluded from the AIS in wild-type neurons, but that this exclusion is lost upon reduction of Cdk5 activity, concomitant with the shrinkage of the AIS domain that is known to occur in this condition. This mitochondrial redistribution into the AIS is not likely due to the shortening of the AIS domain itself but rather due to altered Cdk5 activity. Furthermore, mitochondrial redistribution into the AIS is unlikely to be an early driver of neurodegeneration in the context of reduced Cdk5 activity.
PubMed: 38912559
DOI: 10.1242/bio.060335 -
Heliyon Jun 2024This research examines the function of protein associated with topoisomerase II homolog 1 () in nasal-type natural killer/T-cell lymphoma (NKTCL) and head and neck...
This research examines the function of protein associated with topoisomerase II homolog 1 () in nasal-type natural killer/T-cell lymphoma (NKTCL) and head and neck squamous cell carcinoma (HNSCC). We analyzed bulk RNA-seq data from NKTCL, nasal polyps, and normal nasal mucosa, identifying 439 differentially expressed genes. Machine learning algorithms highlighted as a hub gene. exhibited significant upregulation in NKTCL and HNSCC tumor samples in comparison to normal tissues, showing high diagnostic accuracy (AUC = 1.000) for NKTCL. Further analysis of local hospital data identified as an independent prognostic risk factor for NKTCL. Data analysis of TCGA and GEO datasets revealed that high expression correlated with poorer prognosis in HNSCC patients ( < 0.05). We also constructed a -based nomogram, which emerged as an independent prognostic predictor for HNSCC after addressing missing values. Additionally, we found a strong correlation between and various immune cell infiltrates (e.g., activated.CD4 T cell), and a significant association with the expression of 37 immune checkpoints genes (e.g., , ) and 20 N6-methyladenosine-related genes (e.g., , ) (all < 0.05). Both TCIA and TIDE algorithms suggested that could potentially predict immunotherapy efficacy ( < 0.05). Cellular experiments demonstrated that transfection with a silencing plasmid of significantly inhibited the malignant behaviors of SNK6 and FaDu cell lines( < 0.05). In conclusion, our findings suggest that may serve as a valuable prognostic and predictive biomarker in NKTCL and HNSCC, highlighting its significant role in these cancers.
PubMed: 38912458
DOI: 10.1016/j.heliyon.2024.e32158 -
SSM. Mental Health Jun 2024Depression is a major global health concern especially among mothers of young children in low- and middle-income countries (LMICs). While various risk and protective...
Depression is a major global health concern especially among mothers of young children in low- and middle-income countries (LMICs). While various risk and protective factors have been well-established, the role of fathers in potentially mitigating maternal depression remains understudied. This study aimed to investigate the association between father involvement and maternal depressive symptoms in rural Western Kenya. We used cross-sectional baseline data collected in February-March 2023 from a cluster-randomized controlled trial evaluating the effectiveness of a community-based parenting program for improving early childhood development. Primary caregivers with children 0-18 months of age were enrolled into the trial across 51 villages in Nyamira and Vihiga counties. We analyzed data from 413 mothers who were in a relationship with a male partner (i.e., father of the young child). Maternal depressive symptoms were measured using the CESD-10. Father involvement was reported using a multidimensional measure of men's engagement in childcare activities, household chores, early learning activities, and affection towards their child. We used multilevel regression models to estimate the adjusted associations between father involvement (overall score and by specific domains) and maternal depressive symptoms. We also conducted exploratory subgroup analyses to assess whether this association differed by child age. Overall, greater father involvement was associated with fewer maternal depressive symptoms. Specifically, fathers' engagement in household chores and childcare activities had the strongest protective associations. Exploratory subgroup analyses revealed larger associations for mothers with younger children under 6 months. Our findings suggest that father involvement is a protective factor for maternal mental health. Engaging fathers in early childhood interventions and encouraging men's involvement in caregiving activities may potentially benefit maternal well-being.
PubMed: 38910840
DOI: 10.1016/j.ssmmh.2024.100318 -
Progress in Orthodontics Jun 2024Determining the right time for orthodontic treatment is one of the most important factors affecting the treatment plan and its outcome. The aim of this study is to...
INTRODUCTION
Determining the right time for orthodontic treatment is one of the most important factors affecting the treatment plan and its outcome. The aim of this study is to estimate the mandibular growth stage based on cervical vertebral maturation (CVM) in lateral cephalometric radiographs using artificial intelligence. Unlike previous studies, which use conventional CVM stage naming, our proposed method directly correlates cervical vertebrae with mandibular growth slope.
METHODS AND MATERIALS
To conduct this study, first, information of people achieved in American Association of Orthodontics Foundation (AAOF) growth centers was assessed and after considering the entry and exit criteria, a total of 200 people, 108 women and 92 men, were included in the study. Then, the length of the mandible in the lateral cephalometric radiographs that were taken serially from the patients was calculated. The corresponding graphs were labeled based on the growth rate of the mandible in 3 stages; before the growth peak of puberty (pre-pubertal), during the growth peak of puberty (pubertal) and after the growth peak of puberty (post-pubertal). A total of 663 images were selected for evaluation using artificial intelligence. These images were evaluated with different deep learning-based artificial intelligence models considering the diagnostic measures of sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). We also employed weighted kappa statistics.
RESULTS
In the diagnosis of pre-pubertal stage, the convolutional neural network (CNN) designed for this study has the higher sensitivity and NPV (0.84, 0.91 respectively) compared to ResNet-18 model. The ResNet-18 model had better performance in other diagnostic measures of the pre-pubertal stage and all measures in the pubertal and post-pubertal stages. The highest overall diagnostic accuracy was also obtained using ResNet-18 model with the amount of 87.5% compared to 81% in designed CNN.
CONCLUSION
The artificial intelligence model trained in this study can receive images of cervical vertebrae and predict mandibular growth status by classifying it into one of three groups; before the growth spurt (pre-pubertal), during the growth spurt (pubertal), and after the growth spurt (post-pubertal). The highest accuracy is in post-pubertal stage with the designed networks.
Topics: Humans; Cephalometry; Mandible; Male; Female; Cervical Vertebrae; Artificial Intelligence; Child; Adolescent; Puberty; Deep Learning
PubMed: 38910180
DOI: 10.1186/s40510-024-00527-1 -
BMC Medical Research Methodology Jun 2024Generating synthetic patient data is crucial for medical research, but common approaches build up on black-box models which do not allow for expert verification or...
BACKGROUND
Generating synthetic patient data is crucial for medical research, but common approaches build up on black-box models which do not allow for expert verification or intervention. We propose a highly available method which enables synthetic data generation from real patient records in a privacy preserving and compliant fashion, is interpretable and allows for expert intervention.
METHODS
Our approach ties together two established tools in medical informatics, namely OMOP as a data standard for electronic health records and Synthea as a data synthetization method. For this study, data pipelines were built which extract data from OMOP, convert them into time series format, learn temporal rules by 2 statistical algorithms (Markov chain, TARM) and 3 algorithms of causal discovery (DYNOTEARS, J-PCMCI+, LiNGAM) and map the outputs into Synthea graphs. The graphs are evaluated quantitatively by their individual and relative complexity and qualitatively by medical experts.
RESULTS
The algorithms were found to learn qualitatively and quantitatively different graph representations. Whereas the Markov chain results in extremely large graphs, TARM, DYNOTEARS, and J-PCMCI+ were found to reduce the data dimension during learning. The MultiGroupDirect LiNGAM algorithm was found to not be applicable to the problem statement at hand.
CONCLUSION
Only TARM and DYNOTEARS are practical algorithms for real-world data in this use case. As causal discovery is a method to debias purely statistical relationships, the gradient-based causal discovery algorithm DYNOTEARS was found to be most suitable.
Topics: Humans; Algorithms; Electronic Health Records; Markov Chains; Medical Informatics
PubMed: 38909216
DOI: 10.1186/s12874-024-02257-8 -
Cardiovascular Diabetology Jun 2024Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For... (Comparative Study)
Comparative Study
BACKGROUND
Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as well as anthropometric features. However, there is still no agreement on the most suitable one for predicting CAD.
METHODS
We followed a cohort of 2,000 individuals, ranging in age from 20 to 74, for a duration of 9.9 years. We utilized multivariate Cox proportional hazard models to investigate the association between TyG-index, TyG-BMI, TyG-WC, TG/HDL, plus METS-IR and the occurrence of CAD. The receiver operating curve (ROC) was employed to compare the predictive efficacy of these indices and their corresponding cutoff values for predicting CAD. We also used three distinct embedded feature selection methods: LASSO, Random Forest feature selection, and the Boruta algorithm, to evaluate and compare surrogate markers of insulin resistance in predicting CAD. In addition, we utilized the ceteris paribus profile on the Random Forest model to illustrate how the model's predictive performance is affected by variations in individual surrogate markers, while keeping all other factors consistent in a diagram.
RESULTS
The TyG-index was the only surrogate marker of insulin resistance that demonstrated an association with CAD in fully adjusted model (HR: 2.54, CI: 1.34-4.81). The association was more prominent in females. Moreover, it demonstrated the highest area under the ROC curve (0.67 [0.63-0.7]) in comparison to other surrogate indices for insulin resistance. All feature selection approaches concur that the TyG-index is the most reliable surrogate insulin resistance marker for predicting CAD. Based on the Ceteris paribus profile of Random Forest the predictive ability of the TyG-index increased steadily after 9 with a positive slope, without any decline or leveling off.
CONCLUSION
Due to the simplicity of assessing the TyG-index with routine biochemical assays and given that the TyG-index was the most effective surrogate insulin resistance index for predicting CAD based on our results, it seems suitable for inclusion in future CAD prevention strategies.
Topics: Humans; Insulin Resistance; Coronary Artery Disease; Female; Male; Middle Aged; Predictive Value of Tests; Biomarkers; Machine Learning; Aged; Risk Assessment; Adult; Prognosis; Young Adult; Risk Factors; Time Factors; Insulin; Blood Glucose
PubMed: 38907271
DOI: 10.1186/s12933-024-02306-y