Does Domain-General Auditory Processing Uniquely Explain the Outcomes of Second Language Speech Acquisition, Even Once Cognitive and Demographic Variables are Accounted For?

Extending the paradigm in L1 acquisition, scholars have begun to investigate whether participants’ domain-general ability to represent, encode, and integrate spectral and temporal dimensions of sounds (i.e., auditory processing) could be a potential determinant of the outcomes of post-pubertal L2 speech learning. The current study set out to test the hypothesis that auditory processing makes a unique contribution to L2 speech acquisition for 70 Japanese classroom learners of English with different levels of L2 proficiency when biographical backgrounds (length of instruction and immersion) and memory abilities (working, declarative, and procedural memory) are controlled for. Auditory processing loaded onto modality-general capacities to represent and incorporate anchor stimuli (relative to target stimuli) into long-term memory in an implicit fashion, but dissociated from explicit abilities to remember, associate, and elaborate sensory information. Auditory processing explained a small-to-medium amount of variance in L2 speech learning, even after the other potentially confounding variables were statistically factored out

Detection of COVID-19 epidemic outbreak using machine learning

BackgroundThe coronavirus disease (COVID-19) pandemic has spread rapidly across the world, creating an urgent need for predictive models that can help healthcare providers prepare and respond to outbreaks more quickly and effectively, and ultimately improve patient care. Early detection and warning systems are crucial for preventing and controlling epidemic spread.ObjectiveIn this study, we aimed to propose a machine learning-based method to predict the transmission trend of COVID-19 and a new approach to detect the start time of new outbreaks by analyzing epidemiological data.MethodsWe developed a risk index to measure the change in the transmission trend. We applied machine learning (ML) techniques to predict COVID-19 transmission trends, categorized into three labels: decrease (L0), maintain (L1), and increase (L2). We used Support Vector Machine (SVM), Random Forest (RF), and XGBoost (XGB) as ML models. We employed grid search methods to determine the optimal hyperparameters for these three models. We proposed a new method to detect the start time of new outbreaks based on label 2, which was sustained for at least 14 days (i.e., the duration of maintenance). We compared the performance of different ML models to identify the most accurate approach for outbreak detection. We conducted sensitivity analysis for the duration of maintenance between 7 days and 28 days.ResultsML methods demonstrated high accuracy (over 94%) in estimating the classification of the transmission trends. Our proposed method successfully predicted the start time of new outbreaks, enabling us to detect a total of seven estimated outbreaks, while there were five reported outbreaks between March 2020 and October 2022 in Korea. It means that our method could detect minor outbreaks. Among the ML models, the RF and XGB classifiers exhibited the highest accuracy in outbreak detection.ConclusionThe study highlights the strength of our method in accurately predicting the timing of an outbreak using an interpretable and explainable approach. It could provide a standard for predicting the start time of new outbreaks and detecting future transmission trends. This method can contribute to the development of targeted prevention and control measures and enhance resource management during the pandemic

Effects of time-compressed speech training on multiple functional and structural neural mechanisms involving the left superior temporal gyrus

Time-compressed speech is an artificial form of rapidly presented speech. Training with time-compressed speech (TCSSL) in a second language leads to adaptation toward TCSSL. Here, we newly investigated the effects of 4 weeks of training with TCSSL on diverse cognitive functions and neural systems using the fractional amplitude of spontaneous low-frequency fluctuations (fALFF), resting-state functional connectivity (RSFC) with the left superior temporal gyrus (STG), fractional anisotropy (FA), and regional gray matter volume (rGMV) of young adults by magnetic resonance imaging. There were no significant differences in change of performance of measures of cognitive functions or second language skills after training with TCSSL compared with that of the active control group. However, compared with the active control group, training with TCSSL was associated with increased fALFF, RSFC, and FA and decreased rGMV involving areas in the left STG. These results lacked evidence of a far transfer effect of time-compressed speech training on a wide range of cognitive functions and second language skills in young adults. However, these results demonstrated effects of time-compressed speech training on gray and white matter structures as well as on resting-state intrinsic activity and connectivity involving the left STG, which plays a key role in listening comprehension

Effects of time-compressed speech training on multiple functional and structural neural mechanisms involving the left superior temporal gyrus

Time-compressed speech is an artificial form of rapidly presented speech. Training with time compressed speech in a second language leads to adaptation toward time-compressed speech in a second language and toward time compressed speech in different languages. However, the effects of training with time-compressed speech of a second language (TCSSL) on diverse cognitive functions and neural mechanisms beyond time compressed speech-related activation are unknown. We investigated the effects of 4 weeks of training with TCSSL on the fractional amplitude of spontaneous low-frequency fluctuations (fALFF) of 0.01–0.08 Hz, resting-state functional connectivity (RSFC) with the left superior temporal gyrus (STG), fractional anisotropy (FA), and regional gray matter volume (rGMV) of young adults by magnetic resonance imaging. There were no significant differences in change of performance of measures of cognitive functions or second language skills after training with TCSSL compared with that of the active control group. However, compared with the active control group, training with TCSSL was associated with increased fALFF, RSFC, and FA and decreased rGMV involving areas in the left STG. These results lacked evidence of a far transfer effect of time compressed speech training on a wide range of cognitive functions and second language skills in young adults. However, these results demonstrated effects of time compressed speech training on gray and white matter structures as well as on resting-state intrinsic activity and connectivity involving the left STG, which plays a key role in listening comprehension

Lenticular nucleus correlates of general self-efficacy in young adults

General self-efficacy (GSE) is an important factor in education, social participation, and medical treatment. However, the only study that has investigated the direct association between GSE and a neural correlate did not identify specific brain regions, rather only assessed brain structures, and included older adult subjects. GSE is related to motivation, physical activity, learning, the willingness to initiate behaviour and expend effort, and adjustment. Thus, it was hypothesized in the present study that the neural correlates of GSE might be related to changes in the basal ganglia, which is a region related to the abovementioned self-efficacy factors. This study aimed to identify the brain structures associated with GSE in healthy young adults (n = 1204, 691 males and 513 females, age 20.7 ± 1.8 years) using regional grey matter density and volume (rGMD and rGMV), fractional anisotropy (FA) and mean diffusivity (MD) analyses of magnetic resonance imaging (MRI) data. The findings showed that scores on the GSE Scale (GSES) were associated with a lower MD value in regions from the right putamen to the globus pallidum; however, there were no significant association between GSES scores and regional brain structures using the other analyses (rGMD, rGMV, and FA). Thus, the present findings indicated that the lenticular nucleus is a neural correlate of GSE

GSK3B induces autophagy by phosphorylating ULK1

Unc-51-like autophagy activating kinase 1 (ULK1), a mammalian homolog of the yeast kinase Atg1, has an essential role in autophagy induction. In nutrient and growth factor signaling, ULK1 activity is regulated by various posttranslational modifications, including phosphorylation, acetylation, and ubiquitination. We previously identified glycogen synthase kinase 3 beta (GSK3B) as an upstream regulator of insulin withdrawal-induced autophagy in adult hippocampal neural stem cells. Here, we report that following insulin withdrawal, GSK3B directly interacted with and activated ULK1 via phosphorylation of S405 and S415 within the GABARAP-interacting region. Phosphorylation of these residues facilitated the interaction of ULK1 with MAP1LC3B and GABARAPL1, while phosphorylation-defective mutants of ULK1 failed to do so and could not induce autophagy flux. Furthermore, high phosphorylation levels of ULK1 at S405 and S415 were observed in human pancreatic cancer cell lines, all of which are known to exhibit high levels of autophagy. Our results reveal the importance of GSK3B-mediated phosphorylation for ULK1 regulation and autophagy induction and potentially for tumorigenesis. © 2021, The Author(s).1

Autophagy as a decisive process for cell death

Cell death: cell component recycling in health and disease A natural cellular recycling process could be harnessed or targeted for the treatment of multiple diseases including cancer and psychological disorders. Autophagy is a process that occurs within cells, whereby damaged, toxic, or obsolete cellular components are degraded and recycled to release energy and maintain balance. However, scientists now recognize that autophagy can trigger cell death under certain conditions. Seong-Woon Yu and co-workers at the Daegu Gyeongbuk Institute of Science and Technology, South Korea, reviewed recent research into the mechanisms and role of autophagy in health and disease. Autophagic cell death is implicated in the suppression of tumor development; for example, inducing autophagy led to the death of precancerous cells in mice. Autophagy may also regulate immune cell populations, and play a role in the death of brain cells during chronic stress-related disorders

Ru(II)-Catalyzed Site-Selective Hydroxylation of Flavone and Chromone Derivatives: The Importance of the 5-Hydroxyl Motif for the Inhibition of Aurora Kinases

An efficient protocol for Ru(II)-catalyzed direct C-H oxygenation of a broad range of flavone and chromone substrates was developed. This convenient and powerful synthetic tool allows for the rapid installation of the hydroxyl group into the flavone, chromone, and other related scaffolds and opens the way for analog synthesis of highly potent Aurora kinase inhibitors. The molecular docking simulations indicate that the formation of bidentate H-bonding patterns in the hinge regions between the 5-hydroxyflavonoids and Ala213 was the significant binding force, which is consistent with experimental and computational findings. © 2015 American Chemical Society. (Chemical Presented)114141sciescopu