Self‐Navigated, Retrospective, Data‐Consistent Motion Correction for MPnRAGE

ABSTRACT Purpose To extend and automate a data‐consistent, self‐navigated motion‐correction method for 3D radial T1‐weighted imaging. Methods This method incorporated rigid‐body motion effects into the forward model, solving for parameters that maximize consistency with the data. The method was tested on five datasets with a range of motion types and severities. A separate collection of datasets was used to study the effect that the method has on the test‐retest reliability of cortical thickness estimates. Results Image quality was improved across a wide range of distinct motion types, including some cases that would have been unusable if left uncorrected. The error‐based weighting scheme and the increased timing resolution afforded by the proposed method were especially useful in cases of extreme and rapid motions. Moreover, the method improved test‐retest reliability of cortical thickness measures in pediatric subjects, decreasing the average coefficient of variation from2 . 73 % ± 1 . 75 % $$ 2.73\%\pm 1.75 in uncorrected images (with freesurfer failing on one subject) down to0 . 88 % ± 0 . 21 % $$ 0.88\%\pm 0.21 for images corrected at∼ 2 s $$ \sim 2\kern0.3em $$ timing resolution and0 . 79 % ± 0 . 16 % $$ 0.79\%\pm 0.16 when corrected at faster temporal rates. Conclusion This method was found to be effective when used on T1‐weighted radial data, both qualitatively and quantitatively. The fine‐scale timing resolution and error‐based weighting afforded by this technique will likely provide only a small benefit, unless one is investigating motion‐prone populations or is searching for a very small effect size.

Pathologic Variability Associated With Phenotypic Differences in Siblings With ACTA1 Myopathy

Brain Activity Changes During Bladder Filling in Women With Overactive Bladder After Percutaneous Tibial Neuromodulation

ABSTRACT Purpose Percutaneous tibial neuromodulation (PTNM) is a standard third line therapy for patients with overactive bladder (OAB). While the therapy has demonstrated efficacy, its exact mechanism of action is unclear. Functional neuroimaging is employed to understand brain activity changes during the micturition cycle in women with OAB. In this study, we measure brain perfusion using functional MRI (fMRI) during bladder filling at discrete bladder volumes in women with OAB pre and post PTNM. We also assess brain perfusion at discrete bladder volumes in healthy women without OAB. Materials and Methods Women with and without OAB were enrolled. All participants completed validated urinary symptom questionnaires. Subjects underwent an fMRI exam with arterial spin labeling (ASL) fMRI while their bladders were filled through a urethral catheter at discrete bladder volumes. Subjects with OAB underwent a second ASL fMRI after treatment with PTNM. Results Twelve women with OAB and 13 women without OAB were enrolled. Patients with OAB had increased bladder filling sensations at lower bladder volumes compared to women without OAB. Anterior cingulate cortex (ACC), insula and supplemental motor area (SMA) perfusion during bladder filling did not increase in a linear fashion in healthy women nor women with OAB; there were changes in ACC, insula, and SMA perfusion during bladder filling at set bladder volumes, which changed after a single session of PTNM. Conclusions Perfusion of the ACC, insula, or SMA does not change linearly during bladder filling in women, irrespective of OAB. After a single session of PTNM, perfusion changes during bladder filling in the ACC, Insula, and SMA in a non‐linear fashion.

Metabolomic Relationships Between Lung Cancer and Alzheimer's Disease Using Serum Nuclear Magnetic Resonance Spectroscopy

ABSTRACT Lung cancer (LC) and Alzheimer's disease (AD) are both age‐associated diseases with high rates of mortality. Studies have reported a possible inverse relationship between LC and AD incidences; however, possible shared molecular mechanisms have not been well investigated. Better characterizations of both diseases and their potential molecular relationships may advance the development of successful therapies for both LC and AD. Metabolomics, as a holistic study of the entire measurable metabolome, has the potential to probe into their metabolic connections. Herein, we used high‐resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) spectroscopy to study 36 human serum samples collected from primary lung adenocarcinoma patients with or without AD, or AD and related dementia (ADRD). We identified 88 metabolites with 66 metabolites differentiating LC patients from controls, and 80 metabolites discerning LC patients without ADRD from those with ADRD. Our results demonstrate the capability of metabolomics to reveal inversely dysregulated glycolysis, oxidative phosphorylation, and proline metabolism in LC and ADRD.

Association of Obesity Severity With Cardiometabolic and Renal Disease Burden in the United States

ABSTRACT Objective This study examined the association between obesity severity and cardiometabolic and renal disease, using BMI as a surrogate for obesity severity. Methods This is a cross‐sectional study using data from the United States Behavioral Risk Factor Surveillance System (BRFSS), 2011–2023. Survey‐weighted logistic regression estimated odds ratios (OR) for the diagnosis of diabetes, hypertension, hyperlipidemia, kidney disease, myocardial infarction, stroke, and coronary artery disease among increasing BMI categories. Results Higher BMI was associated with increased odds of all conditions. For BMI ≥ 50 kg/m 2 , odds were notably elevated for diabetes (OR 8.32; 95% CI: 7.78–8.91), hypertension (OR 6.07; 95% CI: 5.58–6.61), and kidney disease (OR 3.60; 95% CI: 3.21–4.03). The odds of cardiovascular disease also rose substantially, including myocardial infarction (OR 2.89; 95% CI: 2.56–3.28) and coronary artery disease (OR 3.44; 95% CI: 3.08–3.84). Mean age at diabetes diagnosis decreased with increasing BMI, from 52.2 years in Class I to 45.3 years in Class IV obesity. Conclusions Obesity severity is incrementally associated with cardiometabolic and renal disease burden, particularly among adults with BMI ≥ 50 kg/m 2 . These findings highlight the urgent need for early, aggressive interventions targeting individuals with all classes of obesity.

Identification of a New Transcriptional Signature of Pre‐Adipocytes in Human Subcutaneous White Adipose Tissue

ABSTRACT Objective White adipose tissue (WAT) expansion occurs through generation of new adipocytes from adipose progenitor cells (APC). The objective of this study was to characterize and validate a new transcriptional profile of APC. Methods Single‐cell (sc)/nuclei (sn) RNA‐Seq was performed on nuclei from whole WAT ( n  = 20), cells from WAT stromal vascular fraction ( n  = 5), and cultured APC in vitro ( n  = 8) using ICELL8 smart‐Seq technology. Additional snRNA‐Seq was performed on WAT using 10x genomic platform. Pseudotime analyses and differentiation of hiPSCs was used to track the temporal patterns of novel gene signatures. Immunohistochemistry was performed to validate a new marker. Results A pre‐adipocyte population was found across the four independent datasets that expressed known pre‐adipocyte markers ( ZNF423 and DLK1 ) in addition to genes typically associated with neurogenes ( DPP10, PTRPT, CTNNA2, NRXN3, CTNNA2, PTPRD, CNTNAP2 and RBFOX1 ). The expression of these genes were temporally regulated with adipocyte differentiation. Immunohistochemistry analyses confirmed these pre‐adipocytes are located in the neurovascular niche of WAT but are not neurons or endothelial cells. Conclusions This work has defined a new transcriptional signature of pre‐adipocytes in human subcutaneuous WAT that are distinct from mesencyhmal stem cell populations and represent novel targets for WAT expansion.

Aromatic plants, nest bacterial diversity, and nestling condition in Corsican blue tits

According to the ‘nest protection hypothesis', some passerines incorporate fresh aromatic plants into their nests which reduce pathogens that can negatively affect nestlings. We experimentally evaluated the effect of five aromatic plant species on the nest bacterial microbiota of Corsican blue tits Cyanistes caeruleus . The experimental addition of aromatic plants decreased bacterial diversity in nests collected post‐hatching. We also detected a weak effect of aromatic plants on nest bacterial composition. In the observational approach, we tested the effect of these plants on the bacterial microbiota diversity and composition of eggshells and nests, and on nestling condition and behaviour. Bacterial diversity decreased with the quantity of aromatic plants in nests containing nestlings and on eggshells during incubation, but only in one of the three studied populations. Again, there was a weak effect of aromatic plants on bacterial composition in nests and no effect on eggshell bacterial composition. Finally, nests with a high quantity of aromatic plants tended to have bigger and taller nestlings in two out of three populations. The quantity of aromatic plants was not associated with speed of feather development and with docility. Our results support the ‘nest protection hypothesis', while highlighting differences in the effect of aromatic plants among populations. To our knowledge, our study is the first to reveal a correlation between the presence of aromatic plants and the bacterial diversity of nests and eggshells in a natural bird population, and to demonstrate experimentally the direct effect of five aromatic plant species on bacterial diversity in nest material.

Perceptions and pathways: Linking biodiversity to health and well‐being in lower‐income contexts

Abstract The biodiversity loss and human health crises are deeply interconnected, but existing frameworks linking the two are largely derived from high‐income contexts, limiting their applicability to much of the world. While these frameworks have been valuable, this gap is especially critical in rapidly urbanising low‐ and middle‐income regions, where health inequalities and biodiversity loss converge. To address this gap, we conducted research in Accra, Ghana, exploring how urban biodiversity influences health and well‐being. Using photovoice, 36 participants documented their lived experiences of local biodiversity and their perceptions of its impact on their health and well‐being. The resulting data were coded both using emergent and a priori codes based on existing conceptual frameworks. We found that biodiversity interacts with multiple domains of health and well‐being through four pathways (‘reducing harm’, ‘building capacities’, ‘restoring capacities’ and ‘causing harm’) that align with existing framings. We also observed two additional pathways (‘spirituality’ and ‘livelihood support’), both of which may have greater prominence in lower income contexts. Incorporating these pathways into our understanding of how biodiversity influences health and well‐being contributes to a more inclusive framework that reflects the socio‐economic and cultural diversity of rapidly urbanising regions in low‐ and middle‐income regions. We present an adapted framework that integrates these pathways, offering a context‐sensitive model to guide future research. Such a framework is essential for informing policy and practice in a way that benefits a broader range of communities, and thus, potentially, better allows us to address health and biodiversity crises together. Read the free Plain Language Summary for this article on the Journal blog.

Development and Validation of an Endometrial Cancer Algorithm in US Claims Data

ABSTRACT Purpose This study developed and validated algorithms to identify the incidence of endometrial cancer using ICD‐9‐CM and ICD‐10‐CM coding systems as part of a post‐authorization safety study (EU PAS: EUPAS45602) of vaginal estrogen, estrogen and progestin combination hormone therapy, and non‐users of vaginal estrogen. Methods Using national claims data in the HealthCare Integrated Research Database, provisional endometrial cancer cases were identified using a screening algorithm comprising at least one endometrial cancer diagnosis code at any location and position between January 1, 2007 and December 31, 2021. One medical record per case was obtained for 700 provisional cases. Two experts in obstetrics and gynecology adjudicated the medical records classifying each patient as a confirmed case, confirmed non‐case, or unknown. Positive predictive value (PPV), conditional sensitivity assuming all cases were identified by the screening algorithm, and their respective 95% confidence intervals (CI) were calculated. Algorithms were generated by choosing the codes and number of encounters to balance endometrial cancer detection and false positives. Algorithms were trained in a sample of non‐users of vaginal estrogen and tested across treatment groups. Results Among the non‐user training set, two visits with ICD‐9‐CM code 182.0 or 182.8 had a PPV of 91.2% (85.4%–95.2%) and sensitivity of 99.3% (95.9%–100.0%). Two visits on separate days with ICD‐10‐CM code C54.1, C54.8, or C54.9 had a PPV of 97.0% (93.6%–98.9%) and sensitivity of 99.5% (97.2%–100.0%). PPVs and sensitivities were over 75% across testing set cohorts for both algorithms. Conclusion Two visits with an endometrial cancer diagnosis code accurately identified endometrial cancer cases in both coding systems. There were very few false positive endometrial cancer diagnoses. PPVs and sensitivities were high and similar in all cohorts.

In‐Process Melt Separation of Depolymerized PET in PET / PE Blends for Upcycling via Twin‐Screw Extrusion

ABSTRACT Our previous work focused on depolymerizing polyethylene terephthalate (PET) in twin‐screw extrusion, as part of a broader project to continuously separate PET from polyolefins in the melt. This study focused on linear low‐density polyethylene (LLDPE) and PET films and the use of ethylene glycol (EG), diethylene glycol (DEG), triethylene glycol (TEG), and bis(2‐hydroxyethyl) terephthalate (BHET) to depolymerize the PET in the extruder to levels above 90% Mw. In this work, the focus will shift to achieving separation of the two polymers in the twin‐screw extruder, which is made possible due to a 90% reduction in the Mw of the PET, which caused a decrease of its viscosity by several orders of magnitude. Owing to the viscosity difference and pressure buildup in the die, the low‐viscosity PET preferentially exited a degassing vent instead of going through the die. This is because the flow of the PET would travel through a non‐pressure vent rather than through a high‐pressure die. However, owing to the higher viscosity of the LLDPE, the pressure was too high to pass through such a small diameter vent hole. Supercritical CO 2 (SCCO 2 ) was used to assist in this extraction, but SCCO 2 negatively impacted the overall degree of separation. Through analysis of the separated materials, it was concluded that a high separation of the two materials was achieved. TGA and FTIR confirmed that the material separated from the vent was 100% PET. The material removed from the die was composed of 95% LLDPE and 5% PET.