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Background: Digital media consumption is prevalent among pre-schoolers, but its impact on language development remains unclear. Aims and Objectives: This study investigates the effects of different types of digital media on pre-school children’s language outcomes. Materials and Methods: A total of 100 pre-school-aged children (mean age 4.2±0.5 years; 51% male) were observed for 12 months. Digital media exposure was categorized into educational interactive, educational passive, and non-educational content, with average screen time being 1.5±0.45 h daily. Language development was assessed using the Preschool Language Scale-5 (PLS-5) at baseline and 12-month follow-up. Results: At the 12-month follow-up, the study participants exhibited an average Total Language Score (TLS) increase from 100±10 to 107±12. Interactive educational app users showed significant language improvements (TLS: 112±10; P

Background: Amnestic mild cognitive impairment (aMCI), considered as the prodromal stage of Alzheimer's disease, is characterized by isolated memory impairment and cerebral gray matter volume (GMV) alterations. Previous structural MRI studies in aMCI have been mainly based on univariate statistics using voxel-based morphometry. Objective: We investigated structural network differences between aMCI patients and cognitively normal older adults by using source-based morphometry, a multivariate approach that considers the relationship between voxels of various parts of the brain. Methods: Ninety-one aMCI patients and 80 cognitively normal controls underwent structural MRI and neuropsychological assessment. Spatially independent components (ICs) that covaried between participants were estimated and a multivariate analysis of covariance was performed with ICs as dependent variables, diagnosis as independent variable, and age, sex, education level, and site as covariates. Results: aMCI patients exhibited reduced GMV in the precentral, temporo-cerebellar, frontal, and temporal network, and increased GMV in the left superior parietal network compared to controls (pFWER < 0.05, Holm-Bonferroni correction). Moreover, we found that diagnosis, more specifically aMCI, moderated the positive relationship between occipital network and Mini-Mental State Examination scores (pFWER < 0.05, Holm-Bonferroni correction). Conclusions: Our results showed GMV alterations in temporo-fronto-parieto-cerebellar networks in aMCI, extending previous results obtained with univariate approaches. [ABSTRACT FROM AUTHOR]

Complicated urinary tract infections (cUTIs) are difficult to treat, consume substantial resources, and cause increased patient morbidity. Data suggest that cUTI may be caused by polymicrobial and fastidious organisms (PMOs and FOs, respectively); as such, urine culture (UC) may be an unreliable diagnostic tool for detecting cUTIs. We sought to determine the utility of PCR testing for patients presumed to have a cUTI and determine the impact of PCR panel size on organism detection. We reviewed 36,586 specimens from patients with presumptive cUTIs who received both UC and PCR testing. Overall positivity rate for PCR and UC was 52.3% and 33.9%, respectively (p < 0.01). PCR detected more PMO and FO than UC (PMO: 46.2% vs. 3.6%; FO: 31.3% vs. 0.7%, respectively, both p < 0.01). Line-item concordance showed that PCR detected 90.2% of organisms identified by UC whereas UC discovered 31.9% of organisms detected by PCR (p < 0.01). Organism detection increased with expansion in PCR panel size from 5–25 organisms (p < 0.01). Our data show that overall positivity rate and the detection of individual organisms, PMO and FO are significantly with PCR testing and that these advantages are ideally realized with a PCR panel size of 25 or greater.

Golesorkhi et al. use a combination of magnetoencephalography data, machine learning and simulation to investigate intrinsic neural timescales during resting and task states. They provide insight into how the temporal hierarchy of the human cortex converges with its spatial core-periphery hierarchy.

Neural responses to the same stimulus show significant variability over trials, with this variability typically reduced (quenched) after a stimulus is presented. This trial-to-trial variability (TTV) has been much studied, however how this neural variability quenching is influenced by the ongoing dynamics of the prestimulus period is unknown. Utilizing a human intracranial stereo-electroencephalography (sEEG) data set, we investigate how prestimulus dynamics, as operationalized by standard deviation (SD), shapes poststimulus activity through trial-to-trial variability (TTV). We first observed greater poststimulus variability quenching in those real trials exhibiting high prestimulus variability as observed in all frequency bands. Next, we found that the relative effect of the stimulus was higher in the later (300-600ms) than the earlier (0-300ms) poststimulus period. Lastly, we replicate our findings in a separate EEG dataset and extend them by finding that trials with high prestimulus variability in the theta and alpha bands had faster reaction times. Together, our results demonstrate that stimulus-related activity, including its variability, is a blend of two factors: 1) the effects of the external stimulus itself, and 2) the effects of the ongoing dynamics spilling over from the prestimulus period - the state at stimulus onset - with the second dwarfing the influence of the first.