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Abstract Background Alzheimer’s disease (AD) is a neurodegenerative disease characterized by Aβ plaques and neurofibrillary tangles. Chronic inflammation and synaptic dysfunction lead to disease progression and cognitive decline. Small extracellular vesicles (sEVs) are implicated in AD progression by facilitating the spread of pathological proteins and inflammatory cytokines. This study investigates synaptic dysfunction and neuroinflammation protein markers in plasma-derived sEVs (PsEVs), their association with Amyloid-β and tau pathologies, and their correlation with AD progression. Methods A total of 90 [AD = 35, mild cognitive impairment (MCI) = 25, and healthy age-matched controls (AMC) = 30] participants were recruited. PsEVs were isolated using a chemical precipitation method, and their morphology was characterized by transmission electron microscopy. Using nanoparticle tracking analysis, the size and concentration of PsEVs were determined. Antibody-based validation of PsEVs was done using CD63, CD81, TSG101, and L1CAM antibodies. Synaptic dysfunction and neuroinflammation were evaluated with synaptophysin, TNF-α, IL-1β, and GFAP antibodies. AD-specific markers, amyloid-β (1–42), and p-Tau were examined within PsEVs using Western blot and ELISA. Results Our findings reveal higher concentrations of PsEVs in AD and MCI compared to AMC (p

Abstract Breast cancer, a leading cause of female mortality due to delayed detection owing to asymptomatic nature and limited early diagnostic tools, was investigated using a multi-modal approach. Plasma-derived small EVs from breast cancer patients (BrCa, n = 74) and healthy controls (HC, n = 30) were analyzed. Small EVs (n = 104), isolated through chemical precipitation, underwent characterization via transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA). Validation involved antibody-based tests (TSG101, CD9, CD81, CD63). Infrared spectra of small EVs were obtained, revealing significant differences in lipid acyl chains, particularly in the C–H stretching of CH3. The study focused on the lipid region (3050–2900 cm−1), identifying peaks (3015 cm−1, 2960 cm−1, 2929 cm−1) as distinctive lipid characteristics. Spectroscopic lipid-to-lipid ratios [(I3015/I2929), (I2960/I2929)] emerged as prominent breast cancer markers. Exploration of protein, nucleic acid, and carbohydrate ratios indicated variations in alpha helices, asymmetric C–H stretching vibrations, and C–O stretching at 1033 cm−1. Principal component analysis (PCA) successfully differentiated BrCa and HC small EVs, and heatmap analysis and receiver operating characteristic (ROC) curve evaluations underscored the discriminatory power of lipid ratios. Notably, (I2960/I2929) exhibited 100% sensitivity and specificity, highlighting its potential as a robust BrCa sEV marker for breast cancer detection.

Abstract It has been increasingly recognized that there is a subset of patients with refractory systemic JIA, who have failed all available medications and may benefit from HSCT. The increasing experience with HSCT in SJIA, suggests that despite the complicated post-HSCT course, short-term, the transplanted patients either achieved SJIA remission or reduced burden of disease. Longer follow-up, however, is needed to better define the long-term outcomes. The discussion at the NextGen 2022 conference was focused on the optimal timing for the procedure, the need for a good control of inflammatory SJIA activity prior to HSCT, and the role of the reduced intensity conditioning regimens as there was a remote concern that such regimens might increase the risk of SJIA relapse after the transplantation. There was unanimous agreement about the importance of long-term registries to address these questions.

BackgroundThere have been over 772 million confirmed cases of COVID-19 worldwide. A significant portion of these infections will lead to long COVID (post–COVID-19 condition) and its attendant morbidities and costs. Numerous life-altering complications have already been associated with the development of long COVID, including chronic fatigue, brain fog, and dangerous heart rhythms. ObjectiveWe aim to derive an actionable long COVID case definition consisting of significantly increased signs, symptoms, and diagnoses to support pandemic-related clinical, public health, research, and policy initiatives. MethodsThis research employs a case-crossover population-based study using International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) data generated at Veterans Affairs medical centers nationwide between January 1, 2020, and August 18, 2022. In total, 367,148 individuals with ICD-10-CM data both before and after a positive COVID-19 test were selected for analysis. We compared ICD-10-CM codes assigned 1 to 7 months following each patient’s positive test with those assigned up to 6 months prior. Further, 350,315 patients had novel codes assigned during this window of time. We defined signs, symptoms, and diagnoses as being associated with long COVID if they had a novel case frequency of ≥1:1000, and they significantly increased in our entire cohort after a positive test. We present odds ratios with CIs for long COVID signs, symptoms, and diagnoses, organized by ICD-10-CM functional groups and medical specialty. We used our definition to assess long COVID risk based on a patient’s demographics, Elixhauser score, vaccination status, and COVID-19 disease severity. ResultsWe developed a long COVID definition consisting of 323 ICD-10-CM diagnosis codes grouped into 143 ICD-10-CM functional groups that were significantly increased in our 367,148 patient post–COVID-19 population. We defined 17 medical-specialty long COVID subtypes such as cardiology long COVID. Patients who were COVID-19–positive developed signs, symptoms, or diagnoses included in our long COVID definition at a proportion of at least 59.7% (268,320/449,450, based on a denominator of all patients who were COVID-19–positive). The long COVID cohort was 8 years older with more comorbidities (2-year Elixhauser score 7.97 in the patients with long COVID vs 4.21 in the patients with non–long COVID). Patients who had a more severe bout of COVID-19, as judged by their minimum oxygen saturation level, were also more likely to develop long COVID. ConclusionsAn actionable, data-driven definition of long COVID can help clinicians screen for and diagnose long COVID, allowing identified patients to be admitted into appropriate monitoring and treatment programs. This long COVID definition can also support public health, research, and policy initiatives. Patients with COVID-19 who are older or have low oxygen saturation levels during their bout of COVID-19, or those who have multiple comorbidities should be preferentially watched for the development of long COVID.

Summary: Juvenile idiopathic arthritis (JIA) is a complex rheumatic disease encompassing several clinically defined subtypes of varying severity. The etiology of JIA remains largely unknown, but genome-wide association studies (GWASs) have identified up to 22 genes associated with JIA susceptibility, including a well-established association with HLA-DRB1. Continued investigation of heritable risk factors has been hindered by disease heterogeneity and low disease prevalence. In this study, we utilized shared genomic segments (SGS) analysis on whole-genome sequencing of 40 cases from 12 multi-generational pedigrees significantly enriched for JIA. Subsets of cases are connected by a common ancestor in large extended pedigrees, increasing the power to identify disease-associated loci. SGS analysis identifies genomic segments shared among disease cases that are likely identical by descent and anchored by a disease locus. This approach revealed statistically significant signals for major histocompatibility complex (MHC) class I and class III alleles, particularly HLA-A∗02:01, which was observed at a high frequency among cases. Furthermore, we identified an additional risk locus at 12q23.2–23.3, containing genes primarily expressed by naive B cells, natural killer cells, and monocytes. The recognition of additional risk beyond HLA-DRB1 provides a new perspective on immune cell dynamics in JIA. These findings contribute to our understanding of JIA and may guide future research and therapeutic strategies.

OBJECTIVES: Drug reaction with eosinophilia and systemic symptoms (DRESS) is a severe, delayed hypersensitivity reaction (DHR). We observed DRESS to inhibitors of interleukin 1 (IL-1) or IL-6 in a small group of patients with Stills disease with atypical lung disease. We sought to characterise features of patients with Stills disease with DRESS compared with drug-tolerant Stills controls. We analysed human leucocyte antigen (HLA) alleles for association to inhibitor-related DHR, including in a small Kawasaki disease (KD) cohort. METHODS: In a case/control study, we collected a multicentre series of patients with Stills disease with features of inhibitor-related DRESS (n=66) and drug-tolerant Stills controls (n=65). We retrospectively analysed clinical data from all Stills subjects and typed 94/131 for HLA. European Stills-DRESS cases were ancestry matched to International Childhood Arthritis Genetics Consortium paediatric Stills cases (n=550) and compared for HLA allele frequencies. HLA association also was analysed using Stills-DRESS cases (n=64) compared with drug-tolerant Stills controls (n=30). KD subjects (n=19) were similarly studied. RESULTS: Stills-DRESS features included eosinophilia (89%), AST-ALT elevation (75%) and non-evanescent rash (95%; 88% involving face). Macrophage activation syndrome during treatment was frequent in Stills-DRESS (64%) versus drug-tolerant Stills (3%; p=1.2×10-14). We found striking enrichment for HLA-DRB1*15 haplotypes in Stills-DRESS cases versus INCHARGE Stills controls (p=7.5×10-13) and versus self-identified, ancestry-matched Stills controls (p=6.3×10-10). In the KD cohort, DRB1*15:01 was present only in those with suspected anakinra reactions. CONCLUSIONS: DRESS-type reactions occur among patients treated with IL-1/IL-6 inhibitors and strongly associate with common HLA-DRB1*15 haplotypes. Consideration of preprescription HLA typing and vigilance for serious reactions to these drugs are warranted.

Abstract Pancreatic Neuroendocrine tumors (PanNET) are challenging to diagnose and often detected at advanced stages due to a lack of specific and sensitive biomarkers. This study utilized proteomics as a valuable approach for cancer biomarker discovery; therefore, mass spectrometry-based proteomic profiling was conducted on plasma samples from 12 subjects (3 controls; 5 Grade I, 4 Grade II PanNET patients) to identify potential proteins capable of effectively distinguishing PanNET from healthy controls. Data are available via ProteomeXchange with the identifier PXD045045. 13.2% of proteins were uniquely identified in PanNET, while 60% were commonly expressed in PanNET and controls. 17 proteins exhibiting significant differential expression between PanNET and controls were identified with downstream analysis. Further, 5 proteins (C1QA, COMP, HSP90B1, ITGA2B, and FN1) were selected by pathway analysis and were validated using Western blot analysis. Significant downregulation of C1QA (p = 0.001: within groups, 0.03: control vs. grade I, 0.0013: grade I vs. grade II) and COMP (p = 0.011: within groups, 0.019: control vs grade I) were observed in PanNET Grade I & II than in controls. Subsequently, ELISA on 38 samples revealed significant downregulation of C1QA and COMP with increasing disease severity. This study shows the potential of C1QA and COMP in the early detection of PanNET, highlighting their role in the search for early-stage (Grade-I and Grade-II) diagnostic markers and therapeutic targets for PanNET.

Abstract Background The prevalence of Celiac Disease (CD) in Juvenile Idiopathic Arthritis (JIA) has been reported to be 0.1–7% in various small studies. As a result of the limited number of research and their inconclusive results there are no clear recommendations for routine CD screening in asymptomatic patients with JIA. Our aim is to estimate the prevalence of IgA deficiency and tissue transglutaminase (tTG) IgA in a cohort of JIA followed in two large academic medical centers. Methods Serum was collected and stored from all subjects and analyzed in a reference laboratory for total IgA (Quantitative Nephelometry) and tTG IgA antibody levels (Semi-Quantitative Enzyme-Linked Immunosorbent Assay). Fisher’s exact tests were performed for statistical significance. Risk estimates (odds ratios) with 95% confidence intervals were calculated. Results 808 JIA cases and 140 controls were analyzed. Majority were non-Hispanic whites (72% vs. 68% p = 0.309). A total of 1.2% of cases were IgA deficient compared to none of the controls (p = 0.373). After excluding IgA deficient subjects, 2% of cases had tTG IgA ≥ 4u/mL compared to 3.6% of controls (p = 0.216) (OR = 0.5; 95% C.I = 0.1–1.4); and 0.8% of cases had tTG IgA > 10u/mL compared to 1.4% of controls (p = 0.627) (OR = 0.5; 95%C.I = 0.1–2.9). Conclusions Using the largest JIA cohort to date to investigate prevalence of celiac antibodies, the prevalence of positive tTG IgA was 0.8% and of IgA deficiency was 1.2%. The results did not demonstrate a higher prevalence of abnormal tTG IgA in JIA. The study did not support the routine screening of asymptomatic JIA patients for CD.

Abstract Background Parkinson’s disease is generally asymptomatic at earlier stages. At an early stage, there is an extensive progression in the neuropathological hallmarks, although, at this stage, diagnosis is not possible with currently available diagnostic methods. Therefore, the pressing need is for susceptibility risk biomarkers that can aid in better diagnosis and therapeutics as well can objectively serve to measure the endpoint of disease progression. The role of small extracellular vesicles (sEV) in the progression of neurodegenerative diseases could be potent in playing a revolutionary role in biomarker discovery. Methods In our study, the salivary sEV were efficiently isolated by chemical precipitation combined with ultrafiltration from subjects (PD = 70, healthy controls = 26, and prodromal PD = 08), followed by antibody-based validation with CD63, CD9, GAPDH, Flotillin-1, and L1CAM. Morphological characterization of the isolated sEV through transmission electron microscopy. The quantification of sEV was achieved by fluorescence (lipid-binding dye-labeled) nanoparticle tracking analysis and antibody-based (CD63 Alexa fluor 488 tagged sEV) nanoparticle tracking analysis. The total alpha-synuclein (α-synTotal) in salivary sEVs cargo was quantified by ELISA. The disease severity staging confirmation for n = 18 clinically diagnosed Parkinson’s disease patients was done by 99mTc-TRODAT-single-photon emission computed tomography. Results We observed a significant increase in total sEVs concentration in PD patients than in the healthy control (HC), where fluorescence lipid-binding dye-tagged sEV were observed to be higher in PD (p = 0.0001) than in the HC using NTA with a sensitivity of 94.34%. In the prodromal PD cases, the fluorescence lipid-binding dye-tagged sEV concentration was found to be higher (p = 0.008) than in HC. This result was validated through anti-CD63 tagged sEV (p = 0.0006) with similar sensitivity of 94.12%. We further validated our findings with the ELISA based on α-synTotal concentration in sEV, where it was observed to be higher in PD (p = 0.004) with a sensitivity of 88.24%. The caudate binding ratios in 99mTc-TRODAT-SPECT represent a positive correlation with sEV concentration (r = 0.8117 with p = 0.0112). Conclusions In this study, for the first time, we have found that the fluorescence-tagged sEV has the potential to screen the progression of disease with clinically acceptable sensitivity and can be a potent early detection method for PD. Graphical Abstract

Background: We describe the utilization of telemedicine visits (video or telephone) across the type 1 diabetes (T1D) Exchange Quality Improvement Collaborative (T1DX-QI) during the COVID-19 pandemic. Metrics, site-level survey results, and examples of interventions conducted to support telemedicine in T1D are shown. Materials and Methods: Thirteen clinics (11 pediatric, 2 adult) provided monthly telemedicine metrics between December 2019 and August 2020 and 21 clinics completed a survey about their telemedicine practices. Results: The proportion of telemedicine visits in T1DX-QI before the pandemic was

Abstract Background Joint acoustic emissions from knees have been evaluated as a convenient, non-invasive digital biomarker of inflammatory knee involvement in a small cohort of children with Juvenile Idiopathic Arthritis (JIA). The objective of the present study was to validate this in a larger cohort. Findings A total of 116 subjects (86 JIA and 30 healthy controls) participated in this study. Of the 86 subjects with JIA, 43 subjects had active knee involvement at the time of study. Joint acoustic emissions were bilaterally recorded, and corresponding signal features were used to train a machine learning algorithm (XGBoost) to classify JIA and healthy knees. All active JIA knees and 80% of the controls were used as training data set, while the remaining knees were used as testing data set. Leave-one-leg-out cross-validation was used for validation on the training data set. Validation on the training and testing set of the classifier resulted in an accuracy of 81.1% and 87.7% respectively. Sensitivity / specificity for the training and testing validation was 88.6% / 72.3% and 88.1% / 83.3%, respectively. The area under the curve of the receiver operating characteristic curve was 0.81 for the developed classifier. The distributions of the joint scores of the active and inactive knees were significantly different. Conclusion Joint acoustic emissions can serve as an inexpensive and easy-to-use digital biomarker to distinguish JIA from healthy controls. Utilizing serial joint acoustic emission recordings can potentially help monitor disease activity in JIA affected joints to enable timely changes in therapy.

Background and aimCancer related fatigue significantly impairs the ability to undertake sustained physical activity across the domains of daily living, work and recreation. The purpose of this study is to monitor cancer related fatigue and the factors affected or caused by it for 12 months in head and neck cancer patients following their diagnosis. Their perceptions of how fatigue might affect their activity levels in addition to identifying avenues to improve engagement with physical activity will be also explored.MethodsA single centre longitudinal mixed-methods study will be conducted. Forty head and neck cancer patients will be recruited over 6 months following the confirmation of their treatment plan, after which fatigue and physical activity will be assessed at four time points over 12 months. Additionally, other factors which influence fatigue such as body composition, blood counts, systemic inflammation levels, haemoglobin concentration, thyroid function, sleep quality, cardiorespiratory fitness and upper and lower extremity strength will be measured to understand how the multifactorial problem of fatigue may evolve over time and influence physical activity levels. Semi-structured interviews will be conducted after treatment completion and at end of twelve months which will analyse the participants fatigue experiences, understand how their perceived fatigue may have impacted physical activity and report the factors which may improve engagement with physical activity during cancer. Quantitative data will be analysed and reported using standard descriptive statistics and post-hoc pairwise comparisons. The changes in outcome measures across time will be analysed using the MIXED procedure in SPSS software. Statistical significance will be accepted at pDiscussionThe results from this study may help inform the planning and delivery of appropriately timed interventions for the management of cancer related fatigue.

Abstract Background Juvenile Idiopathic Arthritis (JIA) is an autoimmune disease with a heterogenous clinical presentation and unpredictable response to available therapies. This personalized transcriptomics study sought proof-of-concept for single-cell RNA sequencing to characterize patient-specific immune profiles. Methods Whole blood samples from six untreated children, newly diagnosed with JIA, and two healthy controls were cultured for 24 h with or without ex vivo TNF stimulation and subjected to scRNAseq to examine cellular populations and transcript expression in PBMCs. A novel analytical pipeline, scPool, was developed wherein cells are first pooled into pseudocells prior to expression analysis, facilitating variance partitioning of the effects of TNF stimulus, JIA disease status, and individual donor. Results Seventeen robust immune cell-types were identified, the abundance of which was significantly affected by TNF stimulus, which resulted in notable elevation of memory CD8 + T-cells and NK56 cells, but down-regulation of naïve B-cell proportions. Memory CD8 + and CD4 + T-cells were also both reduced in the JIA cases relative to two controls. Significant differential expression responses to TNF stimulus were also characterized, with monocytes showing more transcriptional shifts than T-lymphocyte subsets, while the B-cell response was more limited. We also show that donor variability exceeds the small degree of possible intrinsic differentiation between JIA and control profiles. An incidental finding of interest was association of HLA-DQA2 and HLA-DRB5 expression with JIA status. Conclusions These results support the development of personalized immune-profiling combined with ex-vivo immune stimulation for evaluation of patient-specific modes of immune cell activity in autoimmune rheumatic disease.

IntroductionCurrent multistep methods utilized for preparing and cryopreserving single-cell suspensions from blood samples for single-cell RNA sequencing (scRNA-seq) are time-consuming, requiring trained personnel and special equipment, so limiting their clinical adoption. We developed a method, Simple prEservatioN of Single cElls (SENSE), for single-step cryopreservation of whole blood (WB) along with granulocyte depletion during single-cell assay, to generate high quality single-cell profiles (SCP).MethodsWB was cryopreserved using the SENSE method and peripheral blood mononuclear cells (PBMCs) were isolated and cryopreserved using the traditional density-gradient method (PBMC method) from the same blood sample (n=6). The SCPs obtained from both methods were processed using a similar pipeline and quality control parameters. Further, entropy calculation, differential gene expression, and cellular communication analysis were performed to compare cell types and subtypes from both methods.ResultsHighly viable (86.3 ± 1.51%) single-cell suspensions (22,353 cells) were obtained from the six WB samples cryopreserved using the SENSE method. In-depth characterization of the scRNA-seq datasets from the samples processed with the SENSE method yielded high-quality profiles of lymphoid and myeloid cell types which were in concordance with the profiles obtained with classical multistep PBMC method processed samples. Additionally, the SENSE method cryopreserved samples exhibited significantly higher T-cell enrichment, enabling deeper characterization of T-cell subtypes. Overall, the SENSE and PBMC methods processed samples exhibited transcriptional, and cellular communication network level similarities across cell types with no batch effect except in myeloid lineage cells.DiscussionComparative analysis of scRNA-seq datasets obtained with the two cryopreservation methods i.e., SENSE and PBMC methods, yielded similar cellular and molecular profiles, confirming the suitability of the former method’s incorporation in clinics/labs for cryopreserving and obtaining high-quality single-cells for conducting critical translational research.

BackgroundParkinson's disease (PD) is an increasingly common neurodegenerative condition, which causes movement dysfunction and a broad range of non-motor symptoms. There is no molecular or biochemical diagnosis test for PD. The miRNAs are a class of small non-coding RNAs and are extensively studied owing to their altered expression in pathological states and facile harvesting and analysis techniques.MethodsA total of 48 samples (16 each of PD, aged-matched, and young controls) were recruited. The small extracellular vesicles (sEVs) were isolated and validated using Western blot, transmission electron microscope, and nanoparticle tracking analysis. Small RNA isolation, library preparation, and small RNA sequencing followed by differential expression and targeted prediction of miRNA were performed. The real-time PCR was performed with the targeted miRNA on PD, age-matched, and young healthy control of plasma and plasma-derived sEVs to demonstrate their potential as a diagnostic biomarker.ResultsIn RNA sequencing, we identified 14.89% upregulated (fold change 1.11 to 11.04, p < 0.05) and 16.54% downregulated (fold change −1.04 to −7.28, p < 0.05) miRNAs in PD and controls. Four differentially expressed miRNAs (miR-23b-3p, miR-29a-3p, miR-19b-3p, and miR-150-3p) were selected. The expression of miR-23b-3p was “upregulated” (p = 0.002) in plasma, whereas “downregulated” (p = 0.0284) in plasma-derived sEVs in PD than age-matched controls. The ROC analysis of miR-23b-3p revealed better AUC values in plasma (AUC = 0.8086, p = 0.0029) and plasma-derived sEVs (AUC = 0.7278, p = 0.0483) of PD and age-matched controls.ConclusionWe observed an opposite expression profile of miR-23b-3p in PD and age-matched healthy control in plasma and plasma-derived sEV fractions, where the expression of miR-23b-3p is increased in PD plasma while decreased in plasma-derived sEV fractions. We further observed the different miR-23b-3p expression profiles in young and age-matched healthy control.

Abstract Introduction Algorithm‐enabled remote patient monitoring (RPM) programs pose novel operational challenges. For clinics developing and deploying such programs, no standardized model is available to ensure capacity sufficient for timely access to care. We developed a flexible model and interactive dashboard of capacity planning for whole‐population RPM‐based care for T1D. Methods Data were gathered from a weekly RPM program for 277 paediatric patients with T1D at a paediatric academic medical centre. Through the analysis of 2 years of observational operational data and iterative interviews with the care team, we identified the primary operational, population, and workforce metrics that drive demand for care providers. Based on these metrics, an interactive model was designed to facilitate capacity planning and deployed as a dashboard. Results The primary population‐level drivers of demand are the number of patients in the program, the rate at which patients enrol and graduate from the program, and the average frequency at which patients require a review of their data. The primary modifiable clinic‐level drivers of capacity are the number of care providers, the time required to review patient data and contact a patient, and the number of hours each provider allocates to the program each week. At the institution studied, the model identified a variety of practical operational approaches to better match the demand for patient care. Conclusion We designed a generalizable, systematic model for capacity planning for a paediatric endocrinology clinic providing RPM for T1D. We deployed this model as an interactive dashboard and used it to facilitate expansion of a novel care program (4 T Study) for newly diagnosed patients with T1D. This model may facilitate the systematic design of RPM‐based care programs.

Abstract Generating synthetic samples for a tabular data is a strenuous task. Most of the time, the columns (features) in the dataset may not follow an ideal distribution function. The objective of the proposed algorithm, Histogram Augmentation Technique (HAT), is to generate a dataset whose distribution is similar to that of the original dataset. This augmentation is achieved based on individual columns, where separate algorithms are designed for continuous and discrete columns. Humans also use features of an object for interpretation. When humans make a judgement, they notice prominent features and characterise the perceived object. However, conventional Machine Learning classifiers are designed and trained on the basis of samples. Taking the features as the basis for classification, Feature Importance Classifier (FIC) has been attempted in this work. FIC treats every feature independent of each other, and ranks the features based on its dependence with the classified label. It has been found that the FIC has the highest accuracy and has improved the accuracy by 5.54% on average, when it's compared to other classifiers. The suggested algorithms have been experimented on five datasets and compared with two augmentation algorithms and four state‐of‐the‐art ML classification algorithms.

Wire and arc additive manufacturing (WAAM) is an additive manufacturing (AM) process that can produce large metallic components with low material waste and high production rates. However, WAAM’s high deposition rates require high heat input which can result in potential defects such as pores, cracks, lack of fusion or distortion. For practical implementation of the WAAM process in an industrial environment it is necessary to ensure defects-free production. However, the NDT inspection using traditional NDT techniques (ultrasound, eddy currents, x-ray, for example) is a very demanding task, especially during part production. Therefore, reliable online NDT inspection and monitoring techniques are needed for the industrial spread of WAAM. The objective of this work is to detect flaw formation on WAAM produced parts using in-situ acquired acoustic data with a frequency bandwidth from 10 to 1MHz. WAAM parts were processed with deliberately introduced contaminations while its acoustic signal was obtained to correlate different signal characteristics with defects. To identify flaw formation, two distinct types of microphones were employed to acquire data from the same deposition process. The processing of the signal consisted of applying time and frequency domain techniques, namely, Power Spectral Density and Short Time Fourier Transform. The acoustic signatures obtained allowed for the differentiation between flawed and flaw free signals and for the spatial location of the contaminations. The acoustic signal acquired also showed that the data acquired by conventional microphones is not enough to fully characterize the acoustic spectrum emitted by the WAAM process. This work demonstrates the potential of acoustic data and signal processing in the online inspection of WAAM produced parts.

Childhood-onset systemic lupus erythematosus (cSLE) is an autoimmune disease associated with significant morbidity and mortality. Rituximab is a B-cell depleting therapy utilized in the treatment of SLE. In adults, rituximab has been associated with increased risk of adverse outcomes in patients who develop coronavirus disease 2019 (COVID-19). We aimed to assess the impact of prior rituximab treatment on clinical outcomes from Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in children with SLE. To describe the impact of rituximab on outcomes from SARS-CoV-2 infection, we conducted a retrospective study of pediatric SLE patients in our center diagnosed with COVID-19 who had previously received rituximab between February 2019 and October 2022. Patients’ clinical characteristics, disease activity, and outcomes were assessed. Of the eight subjects assessed, five required hospitalizations for COVID-19, four required ICU admission, and two were seen in the emergency department for their symptoms. One patient ultimately expired from her illness. The median time between rituximab administration and COVID-19 diagnosis was 3 months. We assessed the clinical outcomes, including the need of ICU admission and fatal outcome, of COVID-19 in our cSLE patient population after rituximab administration. Approximately 60% of our patients required hospitalization for their illness, and seven out of eight patients required healthcare utilization to include hospitalization and/or emergency department visits.

Introduction: Juvenile Idiopathic Arthritis (JIA) is the most common rheumatic condition of childhood. It represents a heterogeneous group of childhood arthritis. Aim: To study the clinical profile and laboratory characteristics of all newly diagnosed JIA patients. Materials and Methods: This hospital-based prospective observational study was conducted in the Department of Paediatric Rheumatology in Indira Gandhi Institute of Child Health, Bengaluru, Karnataka, India between December 2017 to April 2019. All children who fulfilled International League of Associations for Rheumatology (ILAR) criteria for the diagnosis of JIA were enrolled in the study, and their clinical and laboratory parameters were evaluated. The analysis between matched-pairs data like the comparison between age of onset and age of presentation in males and females were done by paired t-test. Results: Fifty one children were included in the study with M:F of 1:1.12. Mean age at onset was 8.71±4.02 years and median duration of disease was 13 months (2-96 months). The most common subgroup was polyarticular JIA 18 (35.3%) followed by Systemic Onset Juvenile Idiopathic Arthritis (SOJIA) 14 (27.5%), enthesitis-related arthritis 13 (25.5%) and oligoarticular JIA 4 (7.8%). Knee (94%) was the most common joint involved followed by the ankle (70.5%). Fever was the most common extra-articular feature present in 73% of cases. Hepatomegaly, splenomegaly and lymphadenopathy was present in 33.3%, 9.8% and 21.6% children, respectively. Anaemia, leukocytosis, thrombocytosis and elevated Erythrocyte Sedimentation Rate (ESR) were more common in SOJIA. Macrophage Activation Syndrome (MAS) was diagnosed in 2 cases of SOJIA (14.3%) with no mortality. Conclusion: Polyarticular JIA was the common subtype in the study, followed by SOJIA. Most common joint involved was knee, followed by ankle and fever is the most common extraarticular manifestation.

We present an adolescent male with a single intracardiac mass and pulmonary emboli, complicated by peripheral venous thrombosis and subsequent development of pulmonary pseudoaneurysms, leading to diagnosis of Hughes-Stovin syndrome. Remission was achieved with cyclophosphamide, corticosteroids, and pseudoaneurysm resection and maintained with infliximab and methotrexate.

There are increasing pressures within the higher education sector to incorporate digital pedagogies into teaching and learning, a trend amplified by recent extensive recourse to online delivery within the sector. This trend carries with it both opportunities and challenges in effectively fostering those graduate competences that a converging consensus identifies as essential for sustainability education to nurture. The challenge for educators is to design programs capable of fostering a range of competences fit for wicked sustainability problems. The principal objective of this paper is to review the literature regarding the competences that would adequately equip graduates of sustainability coursework programs with substantial online delivery components for a professional environment of uncertainty, complexity, and wicked problems. From the review of scholarship focused on competences for online experiential learning, sustainability education and wicked problems solving, we assemble a set of precepts to guide the design of effective learning outcomes, settings and pedagogies for an approach to sustainability education that better prepares students for such a challenging environment. While the precepts apply to sustainability education generally, we argue that they provide particular guidance for educators concerned with e-learning. We also present educational, social and technological enablers to underpin design, development and delivery processes.

Abstract The idea of which species are native, based on their biogeographic origin, is central to many policies and programmes. Yet definitions are contested and the meanings of ‘nativeness’ are often complex and confusing for many people. For example, a plant that would be considered 'native' in Australia might have a native bioregion that is thousands of kilometres from a given garden planting. The idea of nativeness is culturally constructed and connotes different meanings in different contexts. As conservation research and practice increasingly incorporate human values and behaviours, operationalising the social dimensions of abstract ecological concepts such as nativeness is needed to generate a more holistic evidence base and improve the management of native and non‐native species. We used a sequential mixed‐methods systematic review approach to review and synthesise literature on people's (including general publics, gardeners, conservationists) perceptions of nativeness of species and landscapes. A meta‐synthesis of qualitative research identified six dimensions that underlie people's perceptions in relation to nativeness: Belonging (a sense that there is a right or wrong place for a species to exist); human influence (the role of humans in moving species outside of their historic ranges); functional compatibility (a species' alignment with the local environment and ecology); amenity (desirable and useful features provided by a species); negative impacts (risk and manageability of detrimental impacts caused by a species); and identity (species forming part of one's place‐based identity). A systematic review of the quantitative urban literature found that most research on perceptions of native and non‐native species and landscapes did not operationalise nativeness in a multidimensional way, focusing predominantly on the ‘Negative impacts’ dimension. This may often be inadequate for meaningfully capturing people's views. Our results also highlight the need to strengthen interdisciplinarity between natural and social sciences, and for better integration of social science theories to improve the interpretability and transferability of research findings. We provide recommendations for future research that operationalises nativeness using a broader range of meanings that will inform a deeper, more nuanced understanding of the human dimensions of conservation issues, especially within the contested and briskly evolving terrain of urban greening. A free Plain Language Summary can be found within the Supporting Information of this article.