Understanding the Development of Legitimate Teacher Authority through the Teacher-Student Relationship: A Qualitative Study

Focusing on the relational elements of care, respect, and trust, this sequential qualitative study examined teacher authority development through the development of the teacher-student relationship. Teacher effectiveness was also investigated in relation to legitimate teacher authority and laissez-faire teacher authority. A model was produced which illustrates how teacher effectiveness is gained through the development of legitimate teacher authority via the teacher-student relationship. The model, which was originally based on current theory from the literature, was supported by the findings of the study. Study participants, who were from the same school district, included 20 anonymous high school English students and 15 teachers from across the district. Among the teachers were 13 females and two males whose ages ranged from 24 to 59 years; all were Caucasian. Data included essays on effective and ineffective teachers collected from the students, and observations and semi-structured interviews conducted with the teachers. Student essays were used to create a teacher observation form which identified effective and ineffective teacher behaviors; this form was used to analyze the teacher observations and identify the most and least effective teachers. Observational and interview data were used to classify each teacher as either a legitimate or laissez-faire authority; these data were then analyzed to describe how legitimate teacher authority develops and how authority affects teacher effectiveness in the classroom. Based on authority type, the teacher observation and interview data were analyzed to describe how those teachers classified as legitimate authorities develop authority as they interact with their students. Using multiple forms of consistent care and respect via their teacher-student relationships, these teachers develop trust with their students; trust which is embodied as student cooperation in the classroom. By cooperating with the teacher, students allow the teacher to have authority and legitimize it through continued cooperation. Teacher care included learning about students as individuals and meeting students’ needs. Teacher respect included: treating students as individuals, recognizing their worth, allowing them to have autonomy, and fairness in the treatment of students in relation to each other. Based on both teacher effectiveness and teacher authority type, the teacher observation and interview data were analyzed to describe how teacher authority type affects teacher effectiveness in the classroom. The most effective teachers were found to be strong legitimate authorities while the least effective teachers were found to have either weak legitimate authority or laissez-faire authority. Students of the most effective teachers were the most cooperative and appeared to be self-regulated in the classroom. Students of the least effective teachers were the least cooperative; they regularly ignored or argued with the teacher, requiring the least effective teachers to exert their authority many times during their observations to gain student cooperation. This study holds many theoretical implications. It provides a model describing the development of legitimate teacher authority and teacher effectiveness through the teacher-student relationship, adds to the literature on teacher socialization of students, and describes major differences between effective and ineffective teachers. This study holds practical implications for the training and evaluation of preservice and in-service teachers. It also holds practical implications for parenting in that it describes the development of legitimate authority from the perspectives of teens and adults

Final Report for the DARPA/NSF Interdisciplinary Study on Human–Robot Interaction

As part of a Defense Advanced Research Projects Agency/National Science Foundation study on human–robot interaction (HRI), over sixty representatives from academia, government, and industry participated in an interdisciplinary workshop, which allowed roboticists to interact with psychologists, sociologists, cognitive scientists, communication experts and human–computer interaction specialists to discuss common interests in the field of HRI, and to establish a dialogue across the disciplines for future collaborations. We include initial work that was done in preparation for the workshop, links to keynote and other presentations, and a summary of the findings, outcomes, and recommendations that were generated by the participants. Findings of the study include— the need for more extensive interdisciplinary interaction, identification of basic taxonomies and research issues, social informatics, establishment of a small number of common application domains, and field experience for members of the HRI community. An overall conclusion of the workshop was expressed as the following— HRI is a cross-disciplinary area, which poses barriers to meaningful research, synthesis, and technology transfer. The vocabularies, experiences, methodologies, and metrics of the communities are sufficiently different that cross-disciplinary research is unlikely to happen without sustained funding and an infrastructure to establish a new HRI community

Trends in E-Cigarette and Tobacco Cigarette Purchasing Behaviors by Youth in the United States, Canada, and England, 2017–2022

Objectives: This paper describes trends in youth e-cigarette (EC) and tobacco cigarette (TC) purchasing behaviors in Canada, England, and the United States (US) in relationship to changing minimum legal age (MLA) laws.Methods: Data are from eight cross-sectional online surveys among national samples of 16- to 19-year-olds in Canada, England, and the US conducted from 2017 to 2022 (N = 104,467). Average wave percentage change in EC and TC purchasing prevalence and purchase locations were estimated using Joinpoint regressions.Results: EC purchasing increased between 2017 and 2022, although the pattern of change differed by country. EC purchasing plateaued in 2019 for the US and in 2020 for Canada, while increasing through 2022 for England. TC purchasing declined sharply in the US, with purchasing from traditional retail locations declining, while purchasing from social sources increased. Vape shops were the most common location for EC purchasing, although declining in England and the US.Conclusion: Trends in EC and TC purchasing trends in the US are consistent with the expected impact of the federal MLA law increasing the legal age to 21 years in December 2019

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

TMEM107 recruits ciliopathy proteins to subdomains of the ciliary transition zone and causes Joubert syndrome

The transition zone (TZ) ciliary subcompartment is thought to control cilium composition and signalling by facilitating a protein diffusion barrier at the ciliary base. TZ defects cause ciliopathies such as Meckel–Gruber syndrome (MKS), nephronophthisis (NPHP) and Joubert syndrome1 (JBTS). However, the molecular composition and mechanisms underpinning TZ organization and barrier regulation are poorly understood. To uncover candidate TZ genes, we employed bioinformatics (coexpression and co-evolution) and identified TMEM107 as a TZ protein mutated in oral–facial–digital syndrome and JBTS patients. Mechanistic studies in Caenorhabditis elegans showed that TMEM-107 controls ciliary composition and functions redundantly with NPHP-4 to regulate cilium integrity, TZ docking and assembly of membrane to microtubule Y-link connectors. Furthermore, nematode TMEM-107 occupies an intermediate layer of the TZ-localized MKS module by organizing recruitment of the ciliopathy proteins MKS-1, TMEM-231 (JBTS20) and JBTS-14 (TMEM237). Finally, MKS module membrane proteins are immobile and super-resolution microscopy in worms and mammalian cells reveals periodic localizations within the TZ. This work expands the MKS module of ciliopathy-causing TZ proteins associated with diffusion barrier formation and provides insight into TZ subdomain architecture

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions