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ChatGPT and other LLMs are at the forefront of pedagogical considerations in classrooms across the academy. Many studies have spoken to the technology's capacity to generate one-off texts in a variety of genres. This study complements those by inquiring into its capacity to generate compelling texts at scale. In this study, we quantitatively and qualitatively analyze a small corpus of generated texts in two genres and gauge it against novice and published academic writers along known dimensions of linguistic variation. Theoretically, we position and historicize ChatGPT as a writing technology and consider the ways in which generated text may not be congruent with established trajectories of writing development in higher education. Our study found that generated texts are more informationally dense than authored texts and often read as dialogically closed, "empty," and "fluffy." We close with a discussion of potentially explanatory linguistic features, as well as relevant pedagogical implications.

Abstract Existing dementia prediction models using non-neuroimaging clinical measures have been limited in their ability to identify disease. This study used machine learning to re-examine the diagnostic potential of clinical measures for dementia. Data was sourced from the Australian Imaging, Biomarkers, and Lifestyle Flagship Study of Ageing (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Clinical variables included 21 measures across medical history, hematological and other blood tests, and APOE genotype. Tree-based machine learning algorithms and artificial neural networks were used. APOE genotype was the best predictor of dementia cases and healthy controls. Our results, however, demonstrated that there are limitations when using publicly accessible cohort data that may limit the generalizability and interpretability of such predictive models. Future research should examine the use of routine APOE genetic testing for dementia diagnostics. It should also focus on clearly unifying data across clinical cohorts.

Abstract NADPH oxidases (NOX) are membrane-bound proteins involved in the localized generation of reactive oxygen species (ROS) at the cellular surface. In cancer, these highly reactive molecules primarily originate in mitochondria and via NOX, playing a crucial role in regulating fundamental cellular processes such as cell survival, angiogenesis, migration, invasion, and metastasis. The NOX protein family comprises seven members (NOX1-5 and DUOX1-2), each sharing a catalytic domain and an intracellular dehydrogenase site. NOX-derived ROS promote invadopodia formation, aberrant tyrosine kinase activation, and upregulation of matrix metalloproteinases (MMPs). Specifically, NOX5 modulates adhesion, motility, and proteolytic activation, while NOX1 likely contributes to invadopodia formation and adhesive capacity. NOX2 and NOX4 are implicated in regulating the invasive phenotype, expression of MMPs and EMT markers. DUOX1-2 participate in epithelial-mesenchymal transition (EMT), crucial for invasive phenotype development. Soluble molecules such as TGF-β and EGF modulate NOX protein activation, enhancing cell invasion through localized ROS production. This review focuses on elucidating the specific role of NOX proteins in regulating signaling pathways promoting cancer cell spread, particularly EMT, invadopodia formation and invasive capacity.

Abstract Background As previously published, the MMPOWER-3 clinical trial did not demonstrate a significant benefit of elamipretide treatment in a genotypically diverse population of adults with primary mitochondrial myopathy (PMM). However, the prespecified subgroup of subjects with disease-causing nuclear DNA (nDNA) pathogenic variants receiving elamipretide experienced an improvement in the six-minute walk test (6MWT), while the cohort of subjects with mitochondrial DNA (mtDNA) pathogenic variants showed no difference versus placebo. These published findings prompted additional genotype-specific post hoc analyses of the MMPOWER-3 trial. Here, we present these analyses to further investigate the findings and to seek trends and commonalities among those subjects who responded to treatment, to build a more precise Phase 3 trial design for further investigation in likely responders. Results Subjects with mtDNA pathogenic variants or single large-scale mtDNA deletions represented 74% of the MMPOWER-3 population, with 70% in the mtDNA cohort having either single large-scale mtDNA deletions or MT-TL1 pathogenic variants. Most subjects in the nDNA cohort had pathogenic variants in genes required for mtDNA maintenance (mtDNA replisome), the majority of which were in POLG and TWNK. The mtDNA replisome post-hoc cohort displayed an improvement on the 6MWT, trending towards significant, in the elamipretide group when compared with placebo (25.2 ± 8.7 m versus 2.0 ± 8.6 m for placebo group; p = 0.06). The 6MWT results at week 24 in subjects with replisome variants showed a significant change in the elamipretide group subjects who had chronic progressive external ophthalmoplegia (CPEO) (37.3 ± 9.5 m versus − 8.0 ± 10.7 m for the placebo group; p = 0.0024). Pharmacokinetic (exposure–response) analyses in the nDNA cohort showed a weak positive correlation between plasma elamipretide concentration and 6MWT improvement. Conclusions Post hoc analyses indicated that elamipretide had a beneficial effect in PMM patients with mtDNA replisome disorders, underscoring the importance of considering specific genetic subtypes in PMM clinical trials. These data serve as the foundation for a follow-up Phase 3 clinical trial (NuPOWER) which has been designed as described in this paper to determine the efficacy of elamipretide in patients with mtDNA maintenance-related disorders. Classification of evidence Class I ClinicalTrials.gov identifier NCT03323749

Abstract Background Lung cancer constitutes the leading cause of cancer mortality. High levels of endothelin-1 (ET-1), its cognate receptor ETAR and its activating enzyme, the endothelin-converting enzyme-1 (ECE-1), have been reported in several cancer types, including lung cancer. ECE-1 comprises four isoforms, which only differ in their cytoplasmic N-terminus. Protein kinase CK2 phosphorylates the N-terminus of isoform ECE-1c, increasing its stability and leading to enhanced invasiveness in glioblastoma and colorectal cancer cells, which is believed to be mediated by the amino acid residue Lys-6, a conserved putative ubiquitination site neighboring the CK2-phosphorylated residues Ser-18 and Ser-20. Whether Lys-6 is linked to the acquisition of a cancer stem cell (CSC)-like phenotype and aggressiveness in human non–small cell lung cancer (NSCLC) cells has not been studied. Methods In order to establish the role of Lys-6 in the stability of ECE-1c and its involvement in lung cancer aggressiveness, we mutated this residue to a non-ubiquitinable arginine and constitutively expressed the wild-type (ECE-1cWT) and mutant (ECE-1cK6R) proteins in A549 and H1299 human NSCLC cells by lentiviral transduction. We determined the protein stability of these clones alone or in the presence of the CK2 inhibitor silmitasertib, compared to ECE-1cWT and mock-transduced cells. In addition, the concentration of secreted ET-1 in the growth media was determined by ELISA. Expression of stemness genes were determined by Western blot and RT-qPCR. Chemoresistance to cisplatin was studied by MTS viability assay. Migration and invasion were measured through transwell and Matrigel assays, respectively, and the side-population was determined using flow cytometry. Results ECE-1cK6R displayed higher stability in NSCLC cells compared to ECE-1cWT-expressing cells, but ET-1 secreted levels showed no difference up to 48 h. Most importantly, ECE-1cK6R promoted expression of the stemness genes c-Myc, Sox-2, Oct-4, CD44 and CD133, which enhance cellular self-renewal capability. Also, the ECE-1cK6R-expressing cells showed higher cisplatin chemoresistance, correlating with an augmented side-population abundance due to the increased expression of the ABCG2 efflux pump. Finally, the ECE-1cK6R-expressing cells showed enhanced invasiveness, which correlated with the regulated expression of known EMT markers. Conclusions Our findings suggest an important role of ECE-1c in lung cancer. ECE-1c is key in a non-canonical ET-1-independent mechanism which triggers a CSC-like phenotype, leading to enhanced lung cancer aggressiveness. Underlying this mechanism, ECE-1c is stabilized upon phosphorylation by CK2, which is upregulated in many cancers. Thus, phospho-ECE-1c may be considered as a novel prognostic biomarker of recurrence, as well as the CK2 inhibitor silmitasertib as a potential therapy for lung cancer patients.

Abstract Myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD) is diagnosed by serum MOG‐immunoglobulin G (MOG‐IgG) in association with typical demyelination. 111/1127 patients with paired CSF/serum samples were seropositive for MOG‐IgG. Only 7/1016 (0.7%) seronegative patients had CSF‐restricted MOG‐IgG. While 3/7 patients had longitudinally extensive transverse myelitis, four had a confirmed alternate diagnosis (three multiple sclerosis, one CNS vasculitis). In a national referral setting, CSF‐restricted MOG‐IgG had a low sensitivity (2.63%, 95%CI 0.55–7.50%) and low positive predictive value (1.97%, 95%CI 0.45–8.13%). We strongly recommend serum as the preferred diagnostic biospecimen, and urge caution in the interpretation of CSF‐restricted MOG‐IgG in patients without clinico‐radiological features consistent with MOGAD.

In this paper, we report the description and evaluation of an annual workshop titled "Capacity Building Workshops for Competitive S-STEM Proposals from Two-Year Colleges in the Western U.S." which was offered in June of 2019, 2020, and 2021 with the goal of facilitating submissions to the NSF S-STEM program from 2-year colleges (2YCs). The two-day workshop was composed of separate sessions during which participants discussed several aspects of proposal preparation. Participants also received pre- and post-workshop support through webinars and office hours. To evaluate the program, post-workshop surveys were administered through Qualtrics™. The workshop and related activities received overall positive feedback with specific suggestions on how to better support participants. The paper discusses specific challenges faced by 2YC teams in preparing their proposals. Over three offerings, the program welcomed 103 participants on 51 teams from 2YCs. As of 2021, 11 teams total (from the 2019 cohort) submitted proposals. Among them, four were funded, which is approximately double the typical success rate. Six of the declined teams resubmitted and one of them is currently in negotiations.

Background The TaqMan Array Card (TAC) is an arrayed, high-throughput qPCR platform that can simultaneously detect multiple targets in a single reaction. However, the manual post-run analysis of TAC data is time consuming and subject to interpretation. We sought to automate the post-run analysis of TAC data using machine learning models. Methods We used 165,214 qPCR amplification curves from two studies to train and test two eXtreme Gradient Boosting (XGBoost) models. Previous manual analyses of the amplification curves by experts in qPCR analysis were used as the gold standard. First, a classification model predicted whether amplification occurred or not, and if so, a second model predicted the cycle threshold (Ct) value. We used 5-fold cross-validation to tune the models and assessed performance using accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and mean absolute error (MAE). For external validation, we used 1,472 reactions previously analyzed by 17 laboratory scientists as part of an external quality assessment for a multisite study. Results In internal validation, the classification model achieved an accuracy of 0.996, sensitivity of 0.997, specificity of 0.993, PPV of 0.998, and NPV of 0.991. The Ct prediction model achieved a MAE of 0.590. In external validation, the automated analysis achieved an accuracy of 0.997 and a MAE of 0.611, and the automated analysis was more accurate than manual analyses by 14 of the 17 laboratory scientists. Conclusions We automated the post-run analysis of highly-arrayed qPCR data using machine learning models with high accuracy in comparison to a manual gold standard. This approach has the potential to save time and improve reproducibility in laboratories using the TAC platform and other high-throughput qPCR approaches.

Neurodegeneration is characteristically multifaceted, with limited therapeutic options. One of the chief pathophysiological mechanisms driving these conditions is neuroinflammation, prompting increasing clinical interest in immunomodulatory agents. Growth differentiation factor 15 (GDF15; previously also called macrophage inhibitory cytokine-1 or MIC-1), an anti-inflammatory cytokine with established neurotrophic properties, has emerged as a promising therapeutic agent in recent decades. However, methodological challenges and the delayed identification of its specific receptor GFRAL have hindered research progress. This review systematically examines literature about GDF15 in neurodegenerative diseases and neurotrauma. The evidence collated in this review indicates that GDF15 expression is upregulated in response to neurodegenerative pathophysiology and increasing its levels in preclinical models typically improves outcomes. Key knowledge gaps are addressed for future investigations to foster a more comprehensive understanding of the neuroprotective effects elicited by GDF15.

Abstract There are over 5.3 million Americans who face acquired brain injury (ABI)-related disability as well as almost 800,000 who suffer from stroke each year. To improve mobility and quality of life, rehabilitation professionals often focus on walking recovery soon after hospital discharge for ABI. Reduced propulsion capacity (force output of the lower limbs to counteract ground reaction forces) negatively impacts walking ability and complicates recovery during rehabilitation for brain injured people. We describe a method, using backward-directed resistance (BDR) in a robotic-based treadmill device, to allow measurement of maximum walking propulsion force (MWPF) that is not otherwise possible during overground walking assessment. Our objective was to test the construct validity of a maximum walking propulsion force (MWPF) measure that reflects a person’s propulsive strength against applied BDR, while walking on a robotic treadmill-based device for participants with acquired brain injury (ABI). Our study enrolled 14 participants with ABI at an in inpatient rehabilitation in Galveston, TX from 8/1/21 − 4/31/22. The range of weight-adjusted MWPF was 2.6–27.1% body weight (%BW), mean 16.5 ± 8.4%BW, reflecting a wide range of propulsive force capability. The strongest correlation with overground tests was between the 6-minute walk test (6-MWT) distance and the MWPF values (r = 0.83, p

Abstract To compare the efficacy and safety of the proposed aflibercept biosimilar SCD411 and reference aflibercept in patients with neovascular age-related macular degeneration, this randomized, double-masked, parallel-group, multicenter study was conducted in 14 countries from 13 August 2020 to 8 September 2022. Patients with neovascular age-related macular degeneration. With subfoveal, juxtafoveal, or extrafoveal choroidal neovascularization were aged 50 years or older. Intravitreal injection of SCD411 or aflibercept (2.0 mg) were administered every 4 weeks for the first three injections and every 8 weeks until week 48. The primary efficacy endpoint was the change in best-corrected visual acuity from baseline to week 8 with an adjusted equivalence margin of ± 3.0 letters. Patients were randomly assigned to receive either SCD411 (n = 288) or reference aflibercept (n = 288). A total of 566 participants (98.3%) completed week 8 of the study. The least-squares mean difference of change in best-corrected visual acuity from baseline to week 8 (SCD411—aflibercept) was − 0.4 letters (90% confidence interval = − 1.6 to 0.9). The incidence of ocular (69 of 287 [24.0%] vs. 71 of 286 [24.8%]) and serious ocular (5 of 287 [1.7%] vs. 3 of 286 [1.0%]) treatment-emergent adverse effects were similar between the SCD411 and aflibercept groups. Immunogenicity analysis revealed a low incidence of neutralizing antibody formation in both groups. In conclusion, SCD411 has equivalent efficacy compared with reference aflibercept in patients with neovascular age-related macular degeneration and has a comparable safety profile. The results support the potential use of SCD411 for the treatment of neovascular age-related macular degeneration.

IntroductionWe previously found that self-guided Virtual Reality Exposure Therapy (VRET) improved Public Speaking Anxiety (PSA) and reduced heartrate. Elevated heartrate characterises social anxiety and the self-guided VRET seemed to reduce heartrate. Thus, receiving continuous biofeedback about physiological arousal during the VRET could help socially anxious individuals to manage their anxiety. The present study aimed to determine whether biofeedback enhances the responsiveness of VRET.MethodsSeventy-two individuals with high self-reported social anxiety were randomly allocated to VRET-plus-biofeedback (n=38; 25 completers) or VRET-alone (n=35; 25 completers). Three hour-long VRET sessions were delivered over two consecutive weeks. During each session, participants delivered a 20-minute public speech in front of a virtual audience.ResultsParticipants in the VRET-plus-biofeedback group received biofeedback on heartrate and frontal alpha asymmetry (FAA) within the virtual environment and were asked to lower their arousal accordingly. Participants in both groups completed psychometric assessments of social anxiety after each session and at one-month follow-up. PSA improved by the end of treatment and overall social anxiety improved one month after the VRET across both groups. The VRET-plus-biofeedback group showed a steadier reduction in FAA in the first VRET session and a greater reduction in self-reported arousal across the two sessions than the VRET-alone group.ConclusionBiofeedback can steady physiological arousal and lower perceived arousal during exposure. The benefits of self-guided VRET for social anxiety are sustained one month after therapy.

Abstract Next-generation humanised mouse models and single-cell RNA sequencing (scRNAseq) approaches enable in-depth studies into human immune cell biology. Here we used NSG-SGM3 mice engrafted with human umbilical cord haematopoietic stem cells to investigate how human immune cells respond to and/or are changed by traumatic spinal cord injury (SCI). We hypothesised that the use of such mice could help advance our understanding of spinal cord injury-induced immune depression syndrome (SCI-IDS), and also how human leukocytes change as they migrate from the circulation into the lesion site. Our scRNAseq experiments, supplemented by flow cytometry, demonstrate the existence of up to 11 human immune cell (sub-) types and/or states across the blood and injured spinal cord (7 days post-SCI) of humanised NSG-SGM3 mice. Further comparisons of human immune cell transcriptomes between naïve, sham-operated and SCI mice identified a total of 579 differentially expressed genes, 190 of which were ‘SCI-specific’ (that is, genes regulated only in response to SCI but not sham surgery). Gene ontology analysis showed a prominent downregulation of immune cell function under SCI conditions, including for T cell receptor signalling and antigen presentation, confirming the presence of SCI-IDS and the transcriptional signature of human leukocytes in association with this phenomenon. We also highlight the activating influence of the local spinal cord lesion microenvironment by comparing the transcriptomes of circulating versus infiltrated human immune cells; those isolated from the lesion site were enriched for genes relating to both immune cell activity and function (e.g., oxidative phosphorylation, T cell proliferation and antigen presentation). We lastly applied an integrated bioinformatics approach to determine where immune responses in humanised NSG-SGM3 mice appear congruent to the native responses of human SCI patients, and where they diverge. Collectively, our study provides a valuable resource and methodological framework for the use of these mice in translational research.

Abstract Vaccine priming immunogens that activate germline precursors for broadly neutralizing antibodies (bnAbs) have promise for development of precision vaccines against major human pathogens. In a clinical trial of the eOD-GT8 60mer germline-targeting immunogen, higher frequencies of vaccine-induced VRC01-class bnAb-precursor B cells were observed in the high dose compared to the low dose group. Through immunoglobulin heavy chain variable (IGHV) genotyping, statistical modeling, quantification of IGHV1-2 allele usage and B cell frequencies in the naive repertoire for each trial participant, and antibody affinity analyses, we found that the difference between dose groups in VRC01-class response frequency was best explained by IGHV1-2 genotype rather than dose and was most likely due to differences in IGHV1-2 B cell frequencies for different genotypes. The results demonstrate the need to define population-level immunoglobulin allelic variations when designing germline-targeting immunogens and evaluating them in clinical trials.

Abstract CDH1 (E-cadherin) bi-allelic inactivation is the hallmark alteration of breast invasive lobular carcinoma (ILC), resulting in its discohesive phenotype. A subset of ILCs, however, lack CDH1 genetic/epigenetic inactivation, and their genetic underpinning is unknown. Through clinical targeted sequencing data reanalysis of 364 primary ILCs, we identified 25 ILCs lacking CDH1 bi-allelic genetic alterations. CDH1 promoter methylation was frequent (63%) in these cases. Targeted sequencing reanalysis revealed 3 ILCs harboring AXIN2 deleterious fusions (n = 2) or loss-of-function mutation (n = 1). Whole-genome sequencing of 3 cases lacking bi-allelic CDH1 genetic/epigenetic inactivation confirmed the AXIN2 mutation and no other cell-cell adhesion genetic alterations but revealed a new CTNND1 (p120) deleterious fusion. AXIN2 knock-out in MCF7 cells resulted in lobular-like features, including increased cellular migration and resistance to anoikis. Taken together, ILCs lacking CDH1 genetic/epigenetic alterations are driven by inactivating alterations in other cell adhesion genes (CTNND1 or AXIN2), endorsing a convergent phenotype in ILC.

The widespread adoption of Electric Vehicles (EV) has emphasized the urgent need for efficient and secure charging infrastructure. While existing research in EV charging infrastructure has primarily concentrated on minimizing charging time at charging stations (CSs), neglecting security-centric charging optimization, particularly with scaled charging infrastructure considering multiple CSs. To address this gap, this paper presents an enhanced Hybrid-Electric Vehicle Charging Management and Security (H-EVCMS) framework. The H-EVCMS framework is meticulously designed to optimize charging price, manage load balancing, and provide security across multiple CS by leveraging the Open Charge Point Protocol (OCPP). The proposed framework's performance is evaluated by examining various charging scenarios and analyzing the booking and power consumption patterns of each CS. The results demonstrate the advantages of the hybrid approach used by the proposed H-EVCMS over traditional charging infrastructure management, showcasing its potential to address the challenges of scaling EV charging infrastructure while ensuring security and efficiency.

Abstract Background Gallbladder cancer (GBC) is a prevalent and deadly biliary tract carcinoma, often diagnosed at advanced stages with limited treatment options. The 5-year survival rate varies widely from 4 to 60%, mainly due to differences in disease stage detection. With only a small fraction of patients having resectable tumors and a high incidence of metastasis, advanced GBC stages are characterized by significant chemoresistance. Identification of new therapeutic targets is crucial, and recent studies have shown that the Endothelin-1 (ET-1) signaling pathway, involving ETAR and/or ETBR receptors (ETRs), plays a crucial role in promoting tumor aggressiveness in various cancer models. Blocking one or both receptors has been reported to reduce invasiveness and chemoresistance in cancers like ovarian, prostate, and colon. Furthermore, transcriptomic studies have associated ET-1 levels with late stages of GBC; however, it remains unclear whether its signaling or its inhibition has implications for its aggressiveness. Although the role of ET-1 signaling in gallbladder physiology is minimally understood, its significance in other tumor models leads us to hypothesize its involvement in GBC malignancy. Results In this study, we investigated the expression of ET-1 pathway proteins in three GBC cell lines and a primary GBC culture. Our findings demonstrated that both ETAR and ETBR receptors are expressed in GBC cells and tumor samples. Moreover, we successfully down-regulated ET-1 signaling using a non-selective ETR antagonist, Macitentan, which resulted in reduced migratory and invasive capacities of GBC cells. Additionally, Macitentan treatment chemosensitized the cells to Gemcitabine, a commonly used therapy for GBC. Conclusion For the first time, we reveal the role of the ET-1 pathway in GBC cells, providing insight into the potential therapeutic targeting of its receptors to mitigate invasion and chemoresistance in this cancer with limited treatment options. These findings pave the way for further exploration of Macitentan or other ETR antagonists as potential therapeutic strategies for GBC management. In summary, our study represents a groundbreaking contribution to the field by providing the first evidence of the ET 1 pathway's pivotal role in modulating the behavior and aggressiveness of GBC cells, shedding new light on potential therapeutic targets.

Abstract Despite recent advances in cryo-electron microscopy and artificial intelligence-based model predictions, a significant fraction of structure determinations by macromolecular crystallography still requires experimental phasing, usually by means of single-wavelength anomalous diffraction (SAD) techniques. Most synchrotron beamlines provide highly brilliant beams of X-rays of between 0.7 and 2 Å wavelength. Use of longer wavelengths to access the absorption edges of biologically important lighter atoms such as calcium, potassium, chlorine, sulfur and phosphorus for native-SAD phasing is attractive but technically highly challenging. The long-wavelength beamline I23 at Diamond Light Source overcomes these limitations and extends the accessible wavelength range to λ = 5.9 Å. Here we report 22 macromolecular structures solved in this extended wavelength range, using anomalous scattering from a range of elements which demonstrate the routine feasibility of lighter atom phasing. We suggest that, in light of its advantages, long-wavelength crystallography is a compelling option for experimental phasing.

Abstract Virtual reality exposure therapy (VRET) is a novel intervention technique that allows individuals to experience anxiety-evoking stimuli in a safe environment, recognise specific triggers and gradually increase their exposure to perceived threats. Public-speaking anxiety (PSA) is a prevalent form of social anxiety, characterised by stressful arousal and anxiety generated when presenting to an audience. In self-guided VRET, participants can gradually increase their tolerance to exposure and reduce anxiety-induced arousal and PSA over time. However, creating such a VR environment and determining physiological indices of anxiety-induced arousal or distress is an open challenge. Environment modelling, character creation and animation, psychological state determination and the use of machine learning (ML) models for anxiety or stress detection are equally important, and multi-disciplinary expertise is required. In this work, we have explored a series of ML models with publicly available data sets (using electroencephalogram and heart rate variability) to predict arousal states. If we can detect anxiety-induced arousal, we can trigger calming activities to allow individuals to cope with and overcome distress. Here, we discuss the means of effective selection of ML models and parameters in arousal detection. We propose a pipeline to overcome the model selection problem with different parameter settings in the context of virtual reality exposure therapy. This pipeline can be extended to other domains of interest where arousal detection is crucial. Finally, we have implemented a biofeedback framework for VRET where we successfully provided feedback as a form of heart rate and brain laterality index from our acquired multimodal data for psychological intervention to overcome anxiety.

The EV charging network has witnessed significant growth in the UK in the last few years due to the net zero emission target of the government by 2030. The related literature in EV charging management mainly focuses on road-traffic-parameter-based optimization and lacks detail in terms of charging statistics and cyber–security-enabled charging management frameworks. In this context, this paper proposes a novel EV Charging Management and Security (EVCMS) framework using real-time charging statistics and an Open Charge Point Protocol (OCPP). Specifically, a system model for EVCMS is presented considering charging data management and security protocols. An EVCMS framework design is detailed, focusing on charging pricing, optimization, and charging security. The experimental implementation is described in terms of client–server and charge-box-based simulation. The performance of the proposed EVCMS framework is evaluated by considering different charging scenarios and a range of charging-related metrics. An analysis of results and comparative study attest to the benefits of the proposed EVCMS framework for enabling the EV charging ecosystem.

The purpose of this study was to evaluate the reliability and validity of the raw accelerometry output from research-grade and consumer wearable devices compared to accelerations produced by a mechanical shaker table. Raw accelerometry data from a total of 40 devices (i.e., n = 10 ActiGraph wGT3X-BT, n = 10 Apple Watch Series 7, n = 10 Garmin Vivoactive 4S, and n = 10 Fitbit Sense) were compared to reference accelerations produced by an orbital shaker table at speeds ranging from 0.6 Hz (4.4 milligravity-mg) to 3.2 Hz (124.7mg). Two-way random effects absolute intraclass correlation coefficients (ICC) tested inter-device reliability. Pearson product moment, Lin's concordance correlation coefficient (CCC), absolute error, mean bias, and equivalence testing were calculated to assess the validity between the raw estimates from the devices and the reference metric. Estimates from Apple, ActiGraph, Garmin, and Fitbit were reliable, with ICCs = 0.99, 0.97, 0.88, and 0.88, respectively. Estimates from ActiGraph, Apple, and Fitbit devices exhibited excellent concordance with the reference CCCs = 0.88, 0.83, and 0.85, respectively, while estimates from Garmin exhibited moderate concordance CCC = 0.59 based on the mean aggregation method. ActiGraph, Apple, and Fitbit produced similar absolute errors = 16.9mg, 21.6mg, and 22.0mg, respectively, while Garmin produced higher absolute error = 32.5mg compared to the reference. ActiGraph produced the lowest mean bias 0.0mg (95%CI = -40.0, 41.0). Equivalence testing revealed raw accelerometry data from all devices were not statistically significantly within the equivalence bounds of the shaker speed. Findings from this study provide evidence that raw accelerometry data from Apple, Garmin, and Fitbit devices can be used to reliably estimate movement; however, no estimates were statistically significantly equivalent to the reference. Future studies could explore device-agnostic and harmonization methods for estimating physical activity using the raw accelerometry signals from the consumer wearables studied herein.

The Coronavirus Disease 2019 (COVID-19) pandemic has disproportionately impacted people who use drugs (PWUD). This study explored relationships between drug use, COVID-19 testing, vaccination, and infection. This cross-sectional study was conducted in Miami, Florida between March 2021 and October 2022 as part of the National Institutes of Health (NIH) Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) initiative and the Miami Adult Studies on HIV (MASH) cohort. Users of cannabis, cocaine/crack, heroin/fentanyl, methamphetamines, hallucinogens, and/or prescription drug misuse in the previous 12 months were considered PWUD. Sociodemographic data, COVID-19 testing history, and vaccination-related beliefs were self-reported. Vaccinations were confirmed with medical records and positivity was determined with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. Statistical analyses included chi-square tests and logistic regression. Of 1,780 participants, median age was 57 years, 50.7% were male, 50.2% Non-Hispanic Black, and 66.0% reported an annual income less than $15,000. Nearly 28.0% used drugs. PWUD were less likely than non-users to self-report ever testing positive for SARS-CoV-2 (14.7% vs. 21.0%, p = 0.006). However, 2.6% of participants tested positive for SARS-CoV-2, with no significant differences between PWUD and non-users (3.7% vs. 2.2%, p = 0.076). PWUD were more likely than non-users to experience difficulties accessing testing (10.2% vs. 7.1%, p = 0.033), vaccine hesitancy (58.9% vs. 43.4%, p = 0.002) and had lower odds of receiving any dose of a COVID-19 vaccine compared to non-users (aOR, 0.63; 95% CI, 0.49-0.81; p

ABSTRACTIn 2014, the Association of American Medical Colleges (AAMC) published 13 Core Entrustable Professional Activities (EPAs) that graduating students should be able to perform with indirect supervision when entering residency. A ten-school multi-year pilot was commissioned to test feasibility of implementing training and assessment of the AAMC’s 13 Core EPAs. In 2020–21, a case study was employed to describe pilot schools’ implementation experiences. Teams from nine of ten schools were interviewed to identify means and contexts of implementing EPAs and lessons learned. Audiotapes were transcribed then coded by investigators using conventional content analysis and a constant comparative method. Coded passages were organized in a database and analyzed for themes. Consensus among school teams regarding facilitators of EPA implementation included team commitment to piloting EPAs; agreement that: proximal EPA adoption with curriculum reform facilitates EPA implementation; EPAs ‘naturally fit’ in clerkships and provided opportunity for schools to reflect on and adjust curricula and assessments; and inter-school collaboration bolstered individual school progress. Schools did not make high-stakes decisions about student progress (e.g., promotion, graduation), yet EPA assessment results complemented other forms of assessment in providing students with robust formative feedback about their progress. Teams had varied perceptions of school capability to implement an EPA framework, influenced by various levels of dean involvement, willingness, and capability of schools to invest in data systems and provide other resources, strategic deployment of EPAs and assessments, and faculty buy-in. These factors affected varied pace of implementation. Teams agreed on the worthiness of piloting the Core EPAs, but substantial work is still needed to fully employ an EPA framework at the scale of entire classes of students with enough assessments per EPA and with required data validity/reliability. Recommendations stemming from findings may help inform further implementation efforts across other schools adopting or considering an EPA framework.

IntroductionBackward-directed resistance is the resistance applied in the opposite direction of the individual’s walking motion. Progressive application of backward-directed resistance during walking at a target speed engages adaptive motor control to maintain that speed. During split-belt walking, a motor control strategy must be applied that allows the person to keep up with the two belts to maintain their position on the treadmill. This situation becomes more challenging when progressive resistance is applied since each limb needs to adapt to the greater resistance to maintain the position. We propose that strategies aimed at changing relative propulsion forces with each limb may explain the motor control strategy used. This study aimed to identify the changes in propulsive force dynamics that allow individuals to maintain their position while walking on an instrumented split-belt treadmill with progressively increasing backward-directed resistance.MethodsWe utilized an instrumented split-belt treadmill while users had to overcome a set of increasing backward-directed resistance through the center of mass. Eighteen non-impaired participants (mean age = 25.2 ± 2.51) walked against five levels of backward resistance (0, 5, 10, 15, and 20% of participant’s body weight) in two different modalities: single-belt vs. split-belt treadmill. On the single-belt mode, the treadmill’s pace was the participant’s comfortable walking speed (CWS). In split-belt mode, the dominant limb’s belt pace was half of the CWS, and the non-dominant limb’s belt speed was at the CWS.ResultsWe assessed differences between single-belt vs. split-belt conditions in the slope of the linear relationship between change in propulsive impulse relative to change of backward resistance amount. In split-belt conditions, the slower limb showed a significantly steeper increase in propulsion generation compared to the fast limb across resistance levels.DiscussionAs a possible explanation, the slow limb also exhibited a significantly increased slope of the change in trailing limb angle (TLA), which was strongly correlated to the propulsive impulse slope values. We conclude that the motor control strategy used to maintain position on a split-belt treadmill when challenged with backward-directed resistance is to increase the propulsive forces of the slow limb relative to the fast limb by progressively increasing the TLA.Clinical trial registrationClinicalTrials.gov, identifier NCT04877249.

Alzheimer’s disease (AD) is the most common form of dementia. There is no treatment and AD models have focused on a small subset of genes identified in familial AD. Microarray studies have identified thousands of dysregulated genes in the brains of patients with AD yet identifying the best gene candidates to both model and treat AD remains a challenge. We performed a meta-analysis of microarray data from the frontal cortex (n = 697) and cerebellum (n = 230) of AD patients and healthy controls. A two-stage artificial intelligence approach, with both unsupervised and supervised machine learning, combined with a functional network analysis was used to identify functionally connected and biologically relevant novel gene candidates in AD. We found that in the frontal cortex, genes involved in mitochondrial energy, ATP, and oxidative phosphorylation, were the most significant dysregulated genes. In the cerebellum, dysregulated genes were involved in mitochondrial cellular biosynthesis (mitochondrial ribosomes). Although there was little overlap between dysregulated genes between the frontal cortex and cerebellum, machine learning models comprised of this overlap. A further functional network analysis of these genes identified that two downregulated genes, ATP5L and ATP5H, which both encode subunits of ATP synthase (mitochondrial complex V) may play a role in AD. Combined, our results suggest that mitochondrial dysfunction, particularly a deficit in energy homeostasis, may play an important role in AD.

Background Patients with pulmonary atresia or critical pulmonary stenosis with intact ventricular septum (PA/IVS) and biventricular circulation may require pulmonary valve replacement (PVR). Right ventricular (RV) remodeling after PVR is well described in tetralogy of Fallot (TOF); we sought to investigate RV changes in PA/IVS using cardiac magnetic resonance imaging. Methods and Results A retrospective cohort of patients with PA/IVS who underwent PVR at Boston Children's Hospital from 1995 to 2021 with cardiac magnetic resonance imaging before and after PVR was matched 1:3 with patients with TOF by age at PVR. Median regression modeling was performed with post‐PVR indexed RV end‐diastolic volume as the primary outcome. A total of 20 patients with PA/IVS (cases) were matched with 60 patients with TOF (controls), with median age at PVR of 14 years. Pre‐PVR indexed RV end‐diastolic volume was similar between groups; cases had higher RV ejection fraction (51.4% versus 48.6%; P=0.03). Pre‐PVR RV free wall and left ventricular (LV) longitudinal strain were similar, although LV midcavity circumferential strain was decreased in cases (−15.6 versus −17.1; P=0.001). At a median of 2 years after PVR, indexed RV end‐diastolic volume was similarly reduced; cases continued to have higher RV ejection fraction (52.3% versus 46.9%; P=0.007) with less reduction in RV mass (Δ4.5 versus 9.6 g/m2; P=0.004). Post‐PVR, RV and LV longitudinal strain remained unchanged, and LV circumferential strain was similar, although lower in cases. Conclusions Compared with patients with TOF, patients with PA/IVS demonstrate similar RV remodeling after PVR, with lower reduction in RV mass and comparatively higher RV ejection fraction. Although no differences were detected in peak systolic RV or LV strain values, further investigation of diastolic parameters is needed.