University of Vermont

This scoping review aims to update the understanding of AI-driven educational tools for students with autism spectrum disorder (ASD). Following Arksey and O’Malley’s (Int J Soc Res Methodol 8(1):19–32, 2005) five-stage framework, we defined research questions, conducted a comprehensive literature review, selected relevant studies, and qualitatively analyzed the findings. An electronic search in multiple databases using terms related to AI in education and ASD yielded 128 articles. After rigorous screening, 13 studies were selected for data extraction and narrative synthesis. The review highlights the transformative potential of AI in enhancing educational and therapeutic outcomes for students with ASD. AI-driven tools, such as “LIFEisGAME” and “Empower Me,” utilize advanced technologies like facial recognition and augmented reality to improve social and emotional skills. These tools provide real-time feedback, creating interactive and engaging learning environments tailored to individual needs. Additionally, AI applications in speech-generating devices and educational robots like Kaspar and Kiwi have shown promise in developing communication skills and enhancing social interactions. The narrative synthesis revealed key patterns and insights into the effectiveness of AI applications in supporting students with ASD. AI’s ability to analyze behavioral and emotional data provides a holistic understanding of each student, allowing for personalized learning pathways and real-time adaptation of instructional strategies. However, the review also notes significant ethical challenges, including the need for extensive training for educators, data privacy concerns, and potential algorithmic biases. Ensuring the ethical deployment of AI technologies involves addressing these challenges by implementing robust data protection measures, fostering transparency in AI algorithms, and actively mitigating bias. In conclusion, AI has the potential to revolutionize the education and therapy of students with ASD by offering personalized, adaptive, and effective interventions. The implications of this review suggest that to fully harness the potential of AI, future efforts must focus on long-term studies validating AI effectiveness in diverse settings, developing standardized frameworks for ethical AI deployment, and fostering interdisciplinary collaboration. These steps are essential to ensure sustainable, equitable, and impactful integration of AI-driven technologies in educational and therapeutic contexts for students with ASD.

Objective Caregivers play crucial roles in cancer treatment and outcomes. However, little is known regarding how caregivers support patients during cancer clinical trials. The aim of this study was to gain insight into the caregiver experience of rural and urban patients enrolled in cancer clinical trials. Methods As part of a quality improvement study, 21 patient–caregiver dyads were interviewed using closed and open‐ended interview questions. We analyzed quantitative and qualitative data on patient and caregiver perceptions of caregiver contributions and explored differences in the reported caregiving experience between rural and urban participants. Results While patient–caregiver dyads showed significant disagreement in the symptoms/medication management domain, with caregivers tending to acknowledge the contribution while patients did not (χ² (1, 21) = 5.82, p = 0.016), both groups generally showed agreement in their perceptions of caregiver involvement and reported similar levels of involvement across the other six assessed domains. Qualitative analysis revealed three themes: patient independence, invisible support, and accepted forms of support. Despite patients valuing independence, patients benefited from caregivers' unseen support, and providing emotional support and attending appointments were widely accepted forms of support among patients. No meaningful differences in caregiver contributions were found between rural and urban patient–caregiver dyads. Conclusion Our study revealed that caregivers are assisting patients in often unseen and underestimated ways during cancer clinical trials, highlighting their multifaceted role. Cancer clinical trials should implement a family‐centered approach, especially for rural caregivers, to enhance patient retention and outcomes.

Background Plasma p‐tau biomarkers are promising diagnostic tools for widespread clinical use. However, recent studies have raised concerns regarding the effect of common medical comorbidities, such as cardiovascular disease (CVD), on plasma p‐tau specificity. These influences must be better understood to enable appropriate clinical use of p‐tau181. We sought to evaluate the association between p‐tau181 and CVD outcomes in the Framingham Heart Study (FHS), a population‐based prospective cohort with deep‐phenotyping of CVD. Method FHS Offspring and Omni 1 Cohort participants have been followed through quadrennial exams with detailed CVD assessment. Plasma p‐tau181 was measured from samples of 2543 participants collected in 2011‐2014 using Quanterix Simoa, and analyzed as a binary predictor (highest quintile vs remainder). CVD outcomes (binary:yes/no) included overall CVD, congestive heart failure(CHF), coronary heart disease(CHD), stroke/TIA, and peripheral arterial disease(PAD). Multivariate logistic regressions were performed to assess the association between p‐tau181 and each prevalent CVD outcome adjusting for age, sex, cohort in base models, and additionally for eGFR, and BMI in adjusted models. Cox regression models were performed to assess the association between p‐tau181 and incident CVD outcomes adjusting for similar covariates after a median survival time of 7.0 years [5.9‐7.6]). Result Participant characteristics are displayed in Table 1. Elevated p‐tau181 was associated with 74% higher odds of prevalent CHF (OR 1.74; 95%CI[1.02‐2.98], p=0.04) in adjusted models (Table 2). Elevated p‐tau181 was associated with 41% higher risk of incident overall CVD (HR 1.41[1.03‐1.93], p=0.03) and 55% higher risk of incident CHF (1.55[1.03‐2.34], p=0.04) in adjusted models (Table 3). There was no association between p‐tau181 levels and other CVD outcomes in cross‐sectional or longitudinal analyses. Conclusion Elevated plasma p‐tau181 is associated with prevalent and incident CHF and with overall CVD in a community‐based population. This aligns with growing evidence of a possible bidirectional relationship between CHF and AD. P‐tau levels should be interpreted with caution in patients with CHF until the link between p‐tau181 and CHF can be further clarified. Studies to understand systemic diseases that influence plasma AD biomarkers are necessary prior to widespread clinical use, and can reveal new relationships between AD and systemic diseases.

Background Blood‐based biomarkers, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL), show potential for dementia risk stratification. Yet, their predictive performance for incident dementia in heterogeneous older population with multi‐morbidities, is not well tested. This study evaluates their predictive ability for incident dementia accounting for differences in factors affecting health. Method Data from 910 baseline non‐demented participants of the population‐based Age, Gene/Environment Susceptibility‐Reykjavik Study (AGES‐RS) from 2002 to 2015 (average age 76.6 years, 54.2% female, 6.7% incident dementia) were analyzed. Factors (n = 360) (sociodemographic, clinical, sensory, cardiometabolic, musculoskeletal, medical history, and lifestyle) clustered into 34 groups. Incident dementia cases were identified following the baseline exam until December 2015. Logistic regression models, with 5000 bootstraps, evaluated the predictive power of GFAP and NfL for incident dementia. Predictor sets included: biomarker only; plus age and sex; plus basic factors (education, APOE e4, eGFR); and a full model with associated peripheral clusters. An additional model with age and sex served as the reference for assessing performance without biomarker. Model effectiveness was assessed using area under the precision‐recall curve (AUPRC), precision, and sensitivity (recall), suitable for low dementia prevalence contexts. Result Biomarker levels between cases and non‐cases showed significant overlap (Figure 1a). In predictive performance for incident dementia, NfL outperformed GFAP in the biomarker‐only model (AUPRCs, GFAP: 0.17, NfL: 0.20). Integrating peripheral clusters associated with these biomarkers improved the models’ performance, surpassing both biomarker‐only and basic models, especially for NfL (Figure 1b). Precision rates for the final GFAP and NfL models were 0.304 and 0.61, respectively, reflecting approximately 30% and 61% prediction accuracy for incident dementia. The GFAP’s AUPRC improved to 0.339, accurately identifying 5 out of 100 incident dementia cases, while the NfL’s AUPRC was 0.367, predicted 17% of cases. Conclusion Our findings indicate that due to the low prevalence of dementia in the general population, using plasma GFAP and NfL as dementia screening tools is not highly effective. However, the addition of peripheral factor clusters does enhance their predictive performance, with NfL having a slightly better performance over GFAP.

Background As a risk factor for Alzheimer's disease and related dementias (ADRD) in older adults, inflammatory mechanisms underlying physical frailty remain incompletely elucidated. This study aimed to characterize the inflammatory architecture of frailty and explore predictive implications of inflammatory signatures of frailty on ADRD. Method The study included 741 Framingham Heart Study Offspring cohort participants (52% female, mean 60 years range 40 to 85), dementia‐free at Exam 7 (1998‐2001), followed for incident dementia over 15.8 years on average. The sample was randomly split 50/50 into discovery and validation sets. A total of 209 circulating inflammatory markers including peripheral immune cells and inflammatory biomarkers were measured at Exam 7, with Fried frailty index assessed at Exam 8 (2005‐2008). Using frailty and its 5 components as outcomes, LASSO was conducted on inflammatory markers adjusted for covariates in discovery set. Inflammatory signatures were generated by summing the product of regression coefficients and marker levels for each participant. Pairwise associations between 6 signatures and incident dementia/AD were conducted by Cox models in validation set, with FDR ≤0.05 declaring significance. Result A total of 48 inflammatory markers were involved in signatures: 9 protein biomarkers (4E‐BP1, ADA, CCL3, CD40, CDCP1, HGF, IL‐10RB, IL‐12B, and IL‐17C) and 4 immune cells (CD4 T helper cells, CD4+FoxP3+, CD8+FoxP3+, and TREM2+ NCM) contributed to at least two signatures. In the validation set a handgrip‐strength‐specific signature was significantly associated with incident dementia (HR=0.50, 95%CI: (0.32, 0.76), FDR=0.01) and incident AD (HR=0.44, 95%CI: (0.25, 0.76), FDR=0.01), a walking speed‐specific signature was associated with incident dementia (HR=14.30, 95%CI: (3.67, 55.73), FDR=<0.01) and incident AD (HR=13.95, 95%CI: (2.65, 73.49), FDR=0.01). An unintended weight loss‐specific signature was significantly associated with incident dementia (HR=3.45, 95%CI: (1.09, 10.94), FDR=0.05), and exhaustion‐specific signature was associated with incident dementia (HR=4.12, 95%CI: (1.59, 10.69), FDR=0.01) and incident AD (HR=5.73, 95%CI: (1.84, 17.90), FDR=0.01), and overall frailty signature was associated with incident dementia (HR=2.33, 95%CI: (1.13, 4.84), FDR=0.04) and incident AD (HR=2.82, 95%CI: (1.08, 7.37), FDR=0.05). Conclusion Frailty‐implicated signatures unveil inflammatory markers related to the biology of frailty and ADRD. Future replication studies are needed to inform ADRD prediction signatures.

Background The MarkVCID consortium was established to address the paucity of biomarkers for vascular contributions to cognitive impairment and dementia (VCID), a leading cause of dementia. Plasma neurofilament light (NfL), a neuroaxonal injury marker elevated in several neurological and neurodegenerative diseases, was selected as one of the first biomarkers to be examined. We performed comprehensive instrumental and clinical validation of the Quanterix Simoa NfL assay using the first MarkVCID cohort. Method Plasma NfL was measured using HD‐X and HD‐1 Simoa instruments. Samples from the MarkVCID consortium were used to evaluate intra‐ and inter‐plate reliability, test‐retest repeatability, and inter‐site reproducibility. We used linear regression models to assess the association of NfL in MarkVCID with general cognitive function (GCF) as the primary outcome (n=331). In secondary analyses we assessed NfL associations with white matter hyperintensities (WMH). Models were adjusted for potential confounders, including eGFR as renal function influences NfL clearance. We replicated our findings using cohorts from the CHARGE consortium (CARDIA, ARIC, FHS, AGES; n=4,772), the UKY ADRC (n=350), and the UCD ADRC (n=196). Result We found the Quanterix Simoa platform to be reliable with low coefficients of variation (average CV<12%), high inter‐site reproducibility (overall ICC = 0.93) and high repeatability in test‐retest samples drawn within 30 days (ICC=0.968). There was strong consistency across Quanterix instruments (HD‐X and HD‐1; R²≥0.98) and kits (N4PA and single molecule NfL; ICC≥0.81). We observed consistent significant associations between higher NfL concentrations and worse GCF in MarkVCID (β=‐0.23; [95% CI ‐0.41; ‐0.01), CHARGE cohorts (meta‐analysis β=‐0.11; [95% CI ‐0.17; ‐0.06]), the UKY ADRC (β=‐0.16; [95% CI ‐0.27; ‐0.05]) and the UCD ADRC (UCD: β=‐0.28; [95% CI ‐0.48; ‐0.08). Secondary analyses revealed significant associations between elevated NfL concentrations and higher WMH burden in MarkVCID (when controlled for eGFR), CHARGE, and the UCD ADRC. Conclusion We have found that NfL can be reliably measured using the Quanterix platform, making this marker ideal for multi‐site clinical trials. We observed consistent associations for plasma NfL concentrations with cognition and WMH in MarkVCID and across independent samples, providing evidence that it can be a useful biomarker for stratification in VCID trials.

Among a large sample of youth (9–10 years old at baseline) from the Adolescent Brain Cognitive Development (ABCD) Study® (n = 11,661) we modeled trajectories of psychopathology over three years and associated risk and protective factors. Growth mixture modeling characterized latent classes with distinct psychopathology trajectories. Results indicated four different internalizing trajectories: a high-decreasing class, a moderate-decreasing class, a moderate-increasing class, and a low-stable class. There were also four externalizing trajectories: a moderate-decreasing class, a high-decreasing class, a moderate-increasing class, and a low-decreasing class. We used parallel process growth analysis to examine the co-development of internalizing and externalizing symptoms and characterized five trajectory classes with distinct patterns of co-development. These classes were differentially associated with negative life events, neighborhood safety, and parental acceptance. Together, the findings characterize general developmental patterns of psychopathology, quantify the proportion of youth that follow each pattern, and identify key predictors that discriminate these patterns.

Industrial hemp (Cannabis sativa L.) is an ancient crop used throughout history for fiber, oilseed, and therapeutic compounds. Hemp varieties were cultivated across diverse environments in the United States, but knowledge of those agronomic practices along with genetic resources was lost during a period in which cultivation of cannabis was prohibited. Therefore, regional performance evaluations of hemp varieties for crop performance coupled with scientific communication of outcomes to the public are crucial for hemp's development as an agricultural commodity. Objectives for this research were to evaluate relative yields of industrial hemp varieties grown across the United States and link their suitability for commercial production across locations. A national collaboration established variety trials containing seven industrial hemp varieties planted across 14 locations (36°–48° N latitude and 72°–110° W longitude) over a 3‐year period. Crop dry straw yield and seed yield increased from the averages of 1600 and 700 kg ha⁻¹ in Year 1 to 2400 and 1150 kg ha⁻¹ in Year 2, and 3050 and 815 kg ha⁻¹ in Year 3, respectively. The varieties Anka and X‐59 performed best in Vermont and Virginia, where seed yields consistently exceeded 1100 kg ha⁻¹; however, no single variety performed above average across all sites. Overall, this assessment identified two industrial hemp varieties suitable for commercial production in specific sites and highlighted the importance for hemp breeders to investigate variety × location × year interactions when developing improved varieties to best capture site‐specific productivity.

Disasters create and intensify stress for communities, with many factors contributing to how that stress results in mental health outcomes. Guided by the stress process model, this article presents findings from a qualitative investigation of the meaning of stress among community leaders in the context of the water crisis in Flint, Michigan. Semi-structured interviews were conducted with six community leaders in Flint and analyzed using grounded theory techniques. Secondary stressors such as necessary changes to everyday routines, being discredited by government officials, and perceptions of a lack of government action and accountability were perceived to impact the community’s mental health, with potentially more influence than the impact of the primary stressor of contaminated water. Findings indicate that both stressors and coping resources evolve with profound intrapersonal impact, such that proposed social coping resources become stressors when they do not meet individual or community needs or expectations.

Intensifying extreme droughts are altering lentic ecosystems and disrupting services provisioning. Unfortunately, drought research often lacks a holistic and intersectoral consideration of drought impacts, which can limit relevance of the insights for adaptive management. This literature review evaluated the current state of lake and reservoir extreme drought research in relation to biodiversity and three ecosystem services. The study findings demonstrated that few articles linked or discussed drought implications with one or more ecosystem services, instead focusing primarily on biodiversity. Drought effects on biodiversity varied among species and taxonomic groups. In the limited literature that included ecosystem service provisioning, droughts had a general negative effect. Drinking water supply can decrease and become more costly. Decreasing water flow and volume can reduce hydropower generation. Degraded water quality can also impact recreation. Future intersectoral collaborations and research on intensifying droughts should support adaptive management efforts in mitigating drought impacts.

This pilot study evaluated the feasibility of the technology specialist intervention, which assists clients in achieving mental health recovery and well-being goals via existing digital tools in a real-world community mental health setting. Thirteen adult clients with serious mental illness and their providers completed baseline, 3-, and 6-month assessments, including goal setting, self-efficacy, activation, and acceptability measures, along with weekly ecological momentary assessments. Clients selected goals and corresponding tools, used the tools steadily, and showed improvement in activation and self-efficacy. Most participating clients (82%, n = 9) and providers (80%, n = 8) found the intervention acceptable. These preliminary findings show that the technology specialist intervention is promising and warrants further testing.

Introduction H‐index is a widely used metric quantifying a researcher's productivity and impact based on an author's publications and citations. Though convenient to calculate, h‐index fails to incorporate collaborations and interrelationships between physicians into its assessment of academic impact, leading to limited insight into grouped networks. We present social network analysis as a tool to measure relationships between physicians and quantify their academic impact. Methods A bibliometric multicenter analysis was conducted on physician faculty from 129 US ACGME accredited otolaryngology programs who have publications with a physician co‐author in the field. Using web searches, 2494 physician faculty were identified. Scopus IDs, h‐indices, and publication data for these physicians were identified using multiple Elsevier APIs queried in December 2023. Publications with multiple otolaryngology physician co‐authors were included. Network and sub network maps were generated using Gephi and analyzed with custom R scripts. Centrality measures (degree, PageRank, betweenness centralities) quantified collaboration propensity. Non‐parametric correlation analysis between centrality measures and h‐index was conducted. Sankey diagrams were plotted using ggplot2. Results A co‐authorship network of 2259 physicians was constructed. Physicians were visualized as nodes with collaborations as links. Centrality measures correlated strongly with h‐index (h‐index vs. degree centrality: r² = 0.62, h‐index vs. PageRank: r² = 0.55, h‐index vs. betweenness centrality: r² = 0.55; p < .0001). Analysis revealed novel insights into physician network structure, identifying 14 communities primarily populated by single subspecialties with varied node density. Conclusion Social network analysis showed moderate correlation between social connectedness measures and h‐index, supporting its use in measuring academic impact. In otolaryngology, collaborative interactions within the academic community are strongly shaped by sub‐specialty affiliation and academic institution.

CAG/CTG repeats are prone to expansion, causing several inherited human diseases. The initiating sources of DNA damage which lead to inaccurate repair of the repeat tract to cause expansions are not fully understood. Expansion-prone CAG/CTG repeats are actively transcribed and prone to forming stable R-loops with hairpin structures forming on the displaced single-stranded DNA (S-loops). We previously determined that damage by the Saccharomyces cerevisiae cytosine deaminase, Fcy1, was required for both fragility and instability of CAG/CTG tracts engaged in R-loops. To determine whether this mechanism is more universal, we expressed human cytidine deaminases APOBEC3A (A3A), APOBEC3B (A3B), or activation-induced cytidine deaminase (AID) in our yeast system. We show that mutagenic activity of Apolipoprotein B messenger RNA-editing enzyme, catalytic polypeptides causes CAG/CTG fragility and instability, with A3A having the greatest effect followed by A3B and least from AID. A3A-induced repeat fragility was exacerbated by enrichment of R-loops at the repeat site. A3A and A3B-induced instability was dependent on the MutLγ nuclease and to a lesser extent, base excision repair factors. Deaminase activity assays on hairpin substrates containing CTG and GTC triplet sequences revealed that A3A prefers cytidines within the hairpin loop, and bulges in the hairpin stem alter preferred locations. Analysis of RNA expression levels in human cortex samples revealed that A3A is expressed in brain tissue that exhibits CAG/CTG repeat expansions and its expression is elevated in Huntington’s disease (HD) patient samples. These results implicate cytidine deamination by A3A as a potential source of repeat expansions in HD and other CAG/CTG repeat expansion disorders.

Background A lateral extra-articular tenodesis (LET) is increasingly being utilized to augment an anterior cruciate ligament reconstruction because it has been shown to reduce the risk of postreconstruction graft failure or recurrent rotatory instability. Various femoral fixation techniques are available, including the use of an interference screw, staple, or suture anchor. Purpose To determine and compare the biomechanical properties of an LET graft when using an interference screw, staple, or suture anchor for the femoral fixation for a modified Lemaire LET. Study Design Controlled laboratory study. Methods Eighteen fresh-frozen cadaveric knees were obtained and randomly assigned via a random group generator to undergo a modified Lemaire LET using either an interference screw, a staple, or a suture anchor for femoral fixation. The specimen underwent load-to-failure testing at 20 mm/min until graft failure. The maximum failure load, stiffness, and failure mode for each specimen were recorded. Results The mean failure load was highest for the interference screw (252.7 ± 131.2 N), followed by the staple (151.8 ± 34.1 N) and the suture anchor (105.7 ± 16.4 N). There was a significant difference in failure load between the interference screw and the suture anchor ( P = .015). There was no significant difference between the staple and the interference screw ( P = .101) or the suture anchor ( P = .577). There was no significant difference in graft stiffness across all fixation methods ( P = .089). Conclusion All 3 femoral fixation methods achieved adequate failure loads, although the interference screw had a greater failure load than the suture anchor and there was no significant difference between these implants and the staple. There were no significant differences in stiffness between the fixation methods. Clinical Relevance The maximum failure load occurred with an interference screw for femoral fixation of a modified Lemaire LET; however, because of socket size, this implant may be at greater risk of anterior cruciate ligament reconstruction tunnel collision compared to a smaller-diameter suture anchor drill hole. The failure load of the suture anchor was the lowest; however, it appears sufficient for stable fixation based on the force experienced by an LET graft reported in the literature.

Identifying and characterizing intermolecular forces in the condensed phase is crucial for understanding both micro- and macroscopic properties of solids; ranging from solid-state reactivity to thermal expansion. Insight into these interactions enables a holistic comprehension of bulk properties, and thus understanding them has direct implications for supramolecular design. However, even modest changes to intermolecular interactions can create unpredictable changes to solid-state structures and dynamics. For example, copper(II) acetylacetonate (Cu(C5}H7O2)2) and copper(II) hexafluoroacetylacetonate (Cu(C5HF6O2)2) exhibit similar molecular conformations, yet differences between the methyl and trifluoromethyl groups produce distinct sets of intermolecular forces in the condensed phase. Ultimately, these differences produce unique molecular arrangements in the solid state, with corresponding differences in material properties between the two crystals. In this work, terahertz spectroscopy is used to measure low-frequency vibrational dynamics, which, by extension, provide detailed insight into the underlying intermolecular forces that exist in each system. The experimental data is coupled to theoretical quantum mechanical simulations to precisely quantify the interplay between various energetic effects, and these results highlight the delicate balance that is struck between electronic and dispersive interactions that underpin the structural and related differences between the two systems.

Chromosome instability is a prevalent vulnerability of cancer cells that has yet to be fully exploited therapeutically. To identify genes uniquely essential to chromosomally unstable cells, we mined the Cancer Dependency Map for genes essential in tumor cells with high levels of copy number aberrations. We identify and validate KIF18A, a mitotic kinesin, as a vulnerability of chromosomally unstable cancer cells. Knockdown of KIF18A leads to mitotic defects and reduction of tumor growth. Screening of a chemical library for inhibitors of KIF18A enzymatic activity identified a hit that was optimized to yield VLS-1272, which is orally bioavailable, potent, ATP non-competitive, microtubule-dependent, and highly selective for KIF18A versus other kinesins. Inhibition of KIF18A’s ATPase activity prevents KIF18A translocation across the mitotic spindle, resulting in chromosome congression defects, mitotic cell accumulation, and cell death. Profiling VLS-1272 across >100 cancer cell lines demonstrates that the specificity towards cancer cells with chromosome instability differentiates KIF18A inhibition from other clinically tested anti-mitotic drugs. Treatment of tumor xenografts with VLS-1272 results in mitotic defects leading to substantial, dose-dependent inhibition of tumor growth. The strong biological rationale, robust preclinical data, and optimized compound properties enable the clinical development of a KIF18A inhibitor in cancers with high chromosomal instability.