Ulcerative C2 neurocutaneous dysesthesia (trigeminal trophic syndrome in an alternative distribution)

Trigeminal trophic syndrome is an uncommon condition characterized by paresthesia, itch, and self-inflicted wounds following the trigeminal dermatome(s). Similar processes adhering to cervical nerve distributions have been reported, calling into question the specificity of trigeminal trophic syndrome for the trigeminal network. Herein, we report patient with trigeminal trophic syndrome adhering to the C2 dermatome, a previously unreported distribution

Social anxiety in learning: Stages of change in a sample of UK undergraduates

© 2014 UCU. Social anxiety in learning is prevalent amongst traditional-age students and has a marked effect on their engagement with higher education. It receives little attention from academic or support services and there is a presumption that students will manage their anxieties. Yet it is unclear what psychosocial resources they might bring to this task and how these may develop through the undergraduate years. This study sought to identify possible change processes in student social anxiety by analysing qualitative responses obtained from Level 2 undergraduate students (n=39) in relation to their experience of learning situations such as lectures, seminars and group presentations. Thematic analysis suggested a four-stage developmental progression for students in terms of their experience and orientation to coping with social anxiety. Implications for staff development and student support are outlined

Hydrogen bonding in acrylamide and its role in the scattering behavior of acrylamide-based block copolymers

Hydrogen bonding plays a role in the microphase separation behavior of many block copolymers, such as those used in lithography, where the stronger interactions due to H-bonding can lead to a smaller period for the self-assembled structures, allowing the production of higher resolution templates. However, current statistical thermodynamic models used in descriptions of microphase separation, such as the Flory-Huggins approach, do not take into account some important properties of hydrogen bonding, such as site specificity and cooperativity. In this combined theoretical and experimental study, a step is taken toward the development of a more complete theory of hydrogen bonding in polymers, using polyacrylamide as a model system. We begin by developing a set of association models to describe hydrogen bonding in amides. Both models with one association constant and two association constants are considered. This theory is used to fit IR spectroscopy data from acrylamide solutions in chloroform, thereby determining the model parameters. These parameters are then employed to calculate the scattering function of the disordered state of a diblock copolymer with one polyacrylamide block and one non-hydrogen-bonding block in the random phase approximation. It is then shown that the expression for the inverse scattering function with hydrogen bonding is the same as that without hydrogen bonding, but with the Flory-Huggins parameter χ replaced by an effective value χeff=χ+δχHB(f), where the hydrogen-bonding contribution δχHB depends on the volume fraction f of the hydrogen-bonding block. We find that models with two constants give better predictions of bond energy in the acrylamide dimer and more realistic asymptotic behavior of the association constants and δχHB in the limit of high temperatures

AI and student feedback

AI has the potential to have a transformative effect on teaching, learning, and assessment. This paper reviews recent literature on AI Education (AIEd). The paper makes recommendations for the development of edtech learning platforms using AI. This paper reviews recent literature on AI Education (AIEd). The review was conducted in three stages: the first and second were systematic reviews conducted in 2023; the third stage provides a narrative review of emerging issues since Chat GPT has been part of debates about AIEd. The literature reflects positive progress regarding personalised learning journeys, AI-enhanced grading and evaluation, conversational agents for speaking and listening practice, and early interventions for struggling students. The review extends to the incorporation of AI within educational administration, encompassing learning analytics and predictive capabilities. The originality of this study arises from the paucity of studies on AI in the context of bricks and mortar school classrooms. The rigour of the study is the result of the systematic selection of current, targeted peerreviewed studies. Emerging studies each make their own contributions to knowledge in areas such as learning design, adaptive learning, modelling, and knowledge mapping. There were concerns about privacy, biased input leading to stereotypical judgments, and ethics and privacy. Furthermore, the study acknowledges the need for ongoing research into AI Ed

Digital Single-Cell Analysis of Plant Organ Development Using 3DCellAtlas

Diverse molecular networks underlying plant growth and development are rapidly being uncovered. Integrating these data into the spatial and temporal context of dynamic organ growth remains a technical challenge. We developed 3DCellAtlas, an integrative computational pipeline that semiautomatically identifies cell types and quantifies both 3D cellular anisotropy and reporter abundance at single-cell resolution across whole plant organs. Cell identification is no less than 97.8% accurate and does not require transgenic lineage markers or reference atlases. Cell positions within organs are defined using an internal indexing system generating cellular level organ atlases where data from multiple samples can be integrated. Using this approach, we quantified the organ-wide cell-type-specific 3D cellular anisotropy driving Arabidopsis thaliana hypocotyl elongation. The impact ethylene has on hypocotyl 3D cell anisotropy identified the preferential growth of endodermis in response to this hormone. The spatiotemporal dynamics of the endogenous DELLA protein RGA, expansin gene EXPA3, and cell expansion was quantified within distinct cell types of Arabidopsis roots. A significant regulatory relationship between RGA, EXPA3, and growth was present in the epidermis and endodermis. The use of single-cell analyses of plant development enables the dynamics of diverse regulatory networks to be integrated with 3D organ growth

Interaction and engagement with an anxiety management app: Analysis using large-Scale behavioral data

© Paul Matthews, Phil Topham, Praminda Caleb-Solly. Background: SAM (Self-help for Anxiety Management) is a mobile phone app that provides self-help for anxiety management. Launched in 2013, the app has achieved over one million downloads on the iOS and Android platform app stores. Key features of the app are anxiety monitoring, self-help techniques, and social support via a mobile forum (“the Social Cloud”). This paper presents unique insights into eMental health app usage patterns and explores user behaviors and usage of self-help techniques. Objective: The objective of our study was to investigate behavioral engagement and to establish discernible usage patterns of the app linked to the features of anxiety monitoring, ratings of self-help techniques, and social participation. Methods: We use data mining techniques on aggregate data obtained from 105,380 registered users of the app’s cloud services. Results: Engagement generally conformed to common mobile participation patterns with an inverted pyramid or “funnel” of engagement of increasing intensity. We further identified 4 distinct groups of behavioral engagement differentiated by levels of activity in anxiety monitoring and social feature usage. Anxiety levels among all monitoring users were markedly reduced in the first few days of usage with some bounce back effect thereafter. A small group of users demonstrated long-term anxiety reduction (using a robust measure), typically monitored for 12-110 days, with 10-30 discrete updates and showed low levels of social participation. Conclusions: The data supported our expectation of different usage patterns, given flexible user journeys, and varying commitment in an unstructured mobile phone usage setting. We nevertheless show an aggregate trend of reduction in self-reported anxiety across all minimally-engaged users, while noting that due to the anonymized dataset, we did not have information on users also enrolled in therapy or other intervention while using the app. We find several commonalities between these app-based behavioral patterns and traditional therapy engagement