Citations

In this paper, we present the design and equivalent circuit model (ECM) of a fractal slot-loaded super wideband (SWB) antenna for compact and high-performance applications operating in the 3–40 GHz range. The proposed antenna features a compact dimension of 40 × 35 × 1.57 mm³, a measured bandwidth ratio of 13:1, a peak gain of 9.7 dBi, an average radiation efficiency of 94%, and a low cross-polarization level across the entire bandwidth. The presented ECM is derived using transmission line theory and incorporates the individual behavior of each constituting element of the antenna. A dual sequential optimization approach is employed to determine the optimal element values. The ECM results show good agreement with both simulated and measured results in terms of the magnitude of reflection coefficient |S11| and both real and imaginary impedances with low mean absolute percentage errors of 4.9%, 7.5%, and 7.7%, respectively, demonstrating the model’s ability to accurately predict the antenna’s performance.

Abstract Encephalitis with antibodies to leucine-rich glioma-inactivated 1 (LGI1-Ab-E) is a common form of autoimmune encephalitis, presenting with seizures and neuropsychiatric changes, predominantly in older males. More than 90% of patients carry the human leukocyte antigen (HLA) class II allele, HLA-DRB1*07:01. However, this is also present in 25% of healthy controls. Therefore, we hypothesized the presence of additional genetic predispositions. In this genome-wide association study and meta-analysis, we studied a discovery cohort of 131 French LGI1-Ab-E and a validation cohort of 126 American, British and Irish LGI1-Ab-E patients, ancestry-matched to 2613 and 2538 European controls, respectively. Outside the known major HLA signal, we found two single nucleotide polymorphisms at genome-wide significance (P < 5 × 10−8), implicating PTPRD, a protein tyrosine phosphatase, and LINC00670, a non-protein coding RNA gene. Meta-analysis defined four additional non-HLA loci, including the protein coding COBL gene. Polygenic risk scores with and without HLA variants proposed a contribution of non-HLA loci. In silico network analyses suggested LGI1 and PTPRD-mediated interactions via the established receptors of LGI1, ADAM22 and ADAM23. Our results identify new genetic loci in LGI1-Ab-E. These findings present opportunities for mechanistic studies and offer potential markers of susceptibility, prognostics and therapeutic responses.

Abstract Background Slower speaking rates and higher pause rates are found in individuals with migraine or post‐traumatic headache during headache compared to when headache‐free. We aimed to determine whether headache intensity influences the speaking rate and pause rate of participants with migraine or acute post‐traumatic headache (aPTH) following mild traumatic brain injury (mTBI). Methods Using a speech elicitation tool, participants with migraine, aPTH, and healthy controls (HC) submitted speech samples over a period of 3 months. Speaking and pause rates were calculated when participants were headache‐free and when they had mild or moderate headache. In this observational study, speaking and pause rates in participants with migraine and aPTH were compared to HC, controlling for age, sex, and days since mTBI (participants with aPTH only). Results A total of 2902 longitudinal speech samples from 13 individuals with migraine (mean age = 33.5, SD = 6.6; 12 females/1 male), 43 individuals with aPTH (mean age = 44.4, SD = 13.5; 28 females/15 males), and 56 HC (mean age = 40.8, SD = 13.0; 36 females/20 males) were collected. There was no difference in speaking rate between HC and the combined headache cohort of participants (migraine and aPTH) when they had headache freedom or a mild headache. When participants had moderate intensity headache, their speaking rate was significantly slower compared to that of HC and compared to their speaking rate during mild headache intensity or headache freedom. For the combined headache cohort of participants, pause rates were significantly higher when they had headache freedom or had a headache of mild or moderate intensity relative to HC. Compared to participants' pause rate during headache freedom, their pause rate was significantly higher during mild and moderate headache intensity. Participants with aPTH had significantly slower speaking rates compared to participants with migraine during headache freedom, mild headache intensity, and moderate headache intensity. Participants with aPTH had significantly higher pause rates compared to participants with migraine when experiencing moderate headache intensity. Discussion For both aPTH and migraine, more severe headache pain was associated with higher pause rates and slower speaking rates, suggesting that speaking rate and pause rate could serve as objective biomarkers for headache‐related pain. Slower speaking rate in participants with aPTH could reflect additional consequences of TBI‐related effects on motor control and speech production.

AbstractBackgroundImmune thrombocytopenia (ITP) and Evans syndrome (ES) are manifestations of immune dysregulation. Genetic variants in immune‐related genes have been identified in patients with ITP and especially ES. We aimed to explore familial autoimmunity in patients with ITP and ES to understand possible contributions to chronicity.ProcedureWe assessed family history in two ways: via patient report for ITP and ES and by population‐based analysis using the Utah Population Database (UPDB) for ITP. A total of 266 patients with ITP and 21 patients with ES were identified via chart review, and 252 of the 266 patients with ITP were also identified in the UPDB.ResultsChart review showed familial autoimmunity in 29/182 (15.9%) and 25/84 (29.8%) of patients with newly diagnosed+persistent (nd+p) ITP and chronic ITP (cITP), respectively, (p = .009). The UPDB analysis revealed that autoimmunity in relatives of patients with nd+pITP was higher than in relatives of controls (odds ratio [OR]: 1.69 [1.19–2.41], p = .004), but was not significantly increased in relatives of patients with cITP (OR 1.10 [0.63–1.92], p = .734). Incomplete family history in medical records likely contributed to the observed discrepancy.ConclusionsThe findings suggest that familial autoimmunity may have a stronger association with the development of ITP rather than its duration. Twelve (57.1%) patients with ES reported autoimmunity in their relatives. UPDB analysis was omitted due to the small number of patients with ES. The use of population databases offers a unique opportunity to assess familial health and may provide clues about contributors to immune dysregulation features within families.

Abstract Background Prior studies have established an association between a history of abuse and more severe migraine presentation. Objectives This cross‐sectional, observational study of a clinic‐based migraine population used validated measures to elucidate migraine‐specific and migraine‐related burdens among patients with a history of abuse. Methods Patients with migraine ( n = 866) from the American Registry for Migraine Research self‐reported if they had a history of emotional, physical, and/or sexual abuse and completed questionnaires assessing migraine‐related burden: Migraine Disability Assessment, Subjective Cognitive Impairment Scale for Migraine Attacks, Work Productivity and Activity Impairment, Patient‐Reported Outcomes Measurement Information System Pain Interference, Patient Health Questionnaire‐2, and Generalized Anxiety Disorder‐7. Migraine‐related burden in patients with versus without a history of abuse was compared. Subsequently, a mediation analysis evaluated the impact of depression and anxiety symptoms in the relationship between abuse history and migraine burden. Results A history of abuse was reported by 36.5% ( n = 316/866) of participants. After controlling for patient age, sex, years lived with headache, and headache frequency, a history of abuse was significantly associated with more severe migraine‐related disability. The combined burden of depression and anxiety symptoms mediated the relationship. Conclusion A history of abuse is associated with greater migraine‐related disability. Future studies should determine if identification and management of the psychological and physical sequelae of abuse reduce migraine burden.

PURPOSE Cancer center clinical trial offices (CCTOs) support trial development, activation, conduct, regulatory adherence, data integrity, and compliance. In 2018, the Association of American Cancer Institutes (AACI) Clinical Research Innovation (CRI) Steering Committee conducted and published survey results to benchmark North American CCTOs, including trial volume, accrual, full time equivalents (FTEs), and budget. The survey was readministered in 2023 to assess contemporary CCTO performance and capacity with results presented here. METHODS The 28 question 2023 survey was sent to directors of AACI's clinical member cancer centers. Survey participation was voluntary, no compensation was provided, and data requested covered operations during 2022. Definitions were consistent with National Cancer Institute (NCI) CCTO reporting requirements and AACI staff anonymously compiled results for descriptive statistical reporting. RESULTS The survey response rate was 61% (60/99). The median annual CCTO budget was $11.5 million (M) US dollars (USD) versus $8.2M USD in 2018. These budgets support a median of 150 FTEs versus 104 previously, and a median total of 384 versus 280 interventional treatment trials and a median of 479 versus 531 interventional treatment accruals. Sources of support for CCTO annual budgets were primarily from industry revenue (45.3%) or institutional support (31.7%). Nearly 60% of centers reported activating NCI-sponsored studies within 90 days but only 9% reported meeting a 90-day activation timeline for industry sponsored studies. CONCLUSION Contemporary benchmarks for CCTO operations through this survey demonstrate larger staff sizes, larger budgets, more trials supported, but fewer patients enrolled to interventional treatment trials in comparison with 2018. These data shine a critical light on the increasing complexity of cancer clinical trials, the importance of external funding sources, and necessary operational efficiency upgrades to provide cutting-edge cancer research and care.

Alloreactive memory, unlike naive, CD8 + T cells resist transplantation tolerance protocols and are a critical barrier to long-term graft acceptance in the clinic. We here show that semiallogeneic pregnancy successfully reprogrammed memory fetus/graft-specific CD8 + T cells (T FGS ) toward hypofunction. Female C57BL/6 mice harboring memory CD8 + T cells generated by the rejection of BALB/c skin grafts and then mated with BALB/c males achieved rates of pregnancy comparable with naive controls. Postpartum CD8 + T FGS from skin-sensitized dams upregulated expression of T cell exhaustion (T EX ) markers (Tox, Eomes, PD-1, TIGIT, and Lag3). Transcriptional analysis corroborated an enrichment of canonical T EX genes in postpartum memory T FGS and revealed a downregulation of a subset of memory-associated transcripts. Strikingly, pregnancy induced extensive epigenetic modifications of exhaustion- and memory-associated genes in memory T FGS , whereas minimal epigenetic modifications were observed in naive T FGS . Finally, postpartum memory T FGS durably expressed the exhaustion-enriched phenotype, and their susceptibility to transplantation tolerance was significantly restored compared with memory T FGS . These findings advance the concept of pregnancy as an epigenetic modulator inducing hypofunction in memory CD8 + T cells that has relevance not only for pregnancy and transplantation tolerance, but also for tumor immunity and chronic infections.

INTRODUCTION: Accurate risk prediction can facilitate screening and early detection of pancreatic cancer (PC). We conducted a systematic review to critically evaluate effectiveness of machine learning (ML) and artificial intelligence (AI) techniques applied to electronic health records (EHR) for PC risk prediction. METHODS: Ovid MEDLINE(R), Ovid EMBASE, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Scopus, and Web of Science were searched for articles that utilized ML/AI techniques to predict PC, published between January 1, 2012, and February 1, 2024. Study selection and data extraction were conducted by 2 independent reviewers. Critical appraisal and data extraction were performed using the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. Risk of bias and applicability were examined using prediction model risk of bias assessment tool. RESULTS: Thirty studies including 169,149 PC cases were identified. Logistic regression was the most frequent modeling method. Twenty studies utilized a curated set of known PC risk predictors or those identified by clinical experts. ML model discrimination performance (C-index) ranged from 0.57 to 1.0. Missing data were underreported, and most studies did not implement explainable-AI techniques or report exclusion time intervals. DISCUSSION: AI/ML models for PC risk prediction using known risk factors perform reasonably well and may have near-term applications in identifying cohorts for targeted PC screening if validated in real-world data sets. The combined use of structured and unstructured EHR data using emerging AI models while incorporating explainable-AI techniques has the potential to identify novel PC risk factors, and this approach merits further study.