Characterizing metabolomic signatures related to coffee and tea consumption and their association with incidence and dynamic progression of type 2 diabetes: A multi-state analysis.

Our study aimed to investigate the impact of tea and coffee consumption and related metabolomic signatures on dynamic transitions from diabetes-free status to incident type 2 diabetes (T2D), and subsequently to T2D-related complications and death. We included 438,970 participants in the UK Biobank who were free of diabetes and diabetes complications at baseline. Of these, 212,146 individuals had information on all metabolic biomarkers. We identified tea- and coffee-related metabolomic signatures using elastic net regression models. We examined associations of tea and coffee intake and related metabolomic signatures with the onset and progression of T2D using multi-state regression models. We observed that tea and coffee consumption and related metabolomic signatures were inversely associated with the risk of five T2D transitions. For example, HRs (95% CIs) per SD increase of the tea-related metabolomic signature were 0.87 (0.85, 0.89), 0.97 (0.95, 0.99), 0.91 (0.90, 0.92), 0.92 (0.91, 0.94), and 0.91 (0.90, 0.92) for transitions from diabetes-free state to incident T2D, from diabetes-free state to total death, from incident T2D to T2D complications, from incident T2D to death, and from T2D complications to death. These findings highlight the benefit of tea and coffee intake in reducing the risk of occurrence and progression of T2D.

Cannabis-related information sources among US residents: A probability-weighted nationally representative survey.

INTRODUCTION: The Department of Health and Human Services recently recommended rescheduling cannabis from Schedule I to Schedule III, which might have broad effects on public health outcomes related to cannabis. In this changing environment, understanding national patterns in how people obtain information about cannabis is critical to informing public health outreach and education. METHODS: We surveyed American adults (≥ 18 years) between June 22nd-26th, 2023 using the AmeriSpeak panel. We assessed past year cannabis use, intentions for cannabis use, and where participants got their information about cannabis. We investigated differences by past year use and explored associations between demographic and cannabis use characteristics with information sources using logistic regression. RESULTS: Participants (n = 1,161) were 48.3±27.3 years of age (mean±standard deviation), 51% female, and 27% reported past year cannabis use. The most common information sources used were friends/family (35.6%) and websites (33.7%), while the least common information sources were health/medical care providers (9.3%), employees at place of purchase (8.6%), and government agencies (4.7%). Past year cannabis use was positively associated with all information sources except government agencies and popular media articles. A higher proportion of those using cannabis medically (with or without recreational use) obtained information from a healthcare provider (16.4% vs. 5.2%, p = 0.006). CONCLUSIONS: As cannabis accessibility increases and legality continues changing, there is a strong need for better clinician education, improved public health outreach, and improved communication between patients and clinicians about cannabis.

Associations Between Acute COVID-19 Symptom Profiles and Long COVID Prevalence: Population-Based Cross-Sectional Study.

Background: Growing evidence suggests that severe acute COVID-19 illness increases the risk of long COVID (also known as post-COVID-19 condition). However, few studies have examined associations between acute symptoms and long COVID onset. Objective: This study aimed to examine associations between acute COVID-19 symptom profiles and long COVID prevalence using a population-based sample. Methods: We used a dual mode (phone and web-based) population-based probability survey of adults with polymerase chain reaction-confirmed SARS-CoV-2 between June 2020 and May 2022 in the Michigan Disease Surveillance System to examine (1) how acute COVID-19 symptoms cluster together using latent class analysis, (2) sociodemographic and clinical predictors of symptom clusters using multinomial logistic regression accounting for classification uncertainties, and (3) associations between symptom clusters and long COVID prevalence using modified Poisson regression. Results: In our sample (n=4169), 15.9% (n=693) had long COVID, defined as new or worsening symptoms at least 90 days post SARS-CoV-2 infection. We identified 6 acute COVID-19 symptom clusters resulting from the latent class analysis, with flu-like symptoms (24.7%) and fever (23.6%) being the most prevalent in our sample, followed by nasal congestion (16.4%), multi-symptomatic (14.5%), predominance of fatigue (10.8%), and predominance of shortness of breath (10%) clusters. Long COVID prevalence was highest in the multi-symptomatic (39.7%) and predominance of shortness of breath (22.4%) clusters, followed by the flu-like symptom (15.8%), predominance of fatigue (14.5%), fever (6.4%), and nasal congestion (5.6%) clusters. After adjustment, females (vs males) had greater odds of membership in the multi-symptomatic, flu-like symptom, and predominance of fatigue clusters, while adults who were Hispanic or another race or ethnicity (vs non-Hispanic White) had greater odds of membership in the multi-symptomatic cluster. Compared with the nasal congestion cluster, the multi-symptomatic cluster had the highest prevalence of long COVID (adjusted prevalence ratio [aPR] 6.1, 95% CI 4.3-8.7), followed by the predominance of shortness of breath (aPR 3.7, 95% CI 2.5-5.5), flu-like symptom (aPR 2.8, 95% CI 1.9-4.0), and predominance of fatigue (aPR 2.2, 95% CI 1.5-3.3) clusters. Conclusions: Researchers and clinicians should consider acute COVID-19 symptom profiles when evaluating subsequent risk of long COVID, including potential mechanistic pathways in a research context, and proactively screen high-risk patients during the provision of clinical care.

Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts.

BACKGROUND: A major challenge in epidemiology is knowing when an exposure effect is large enough to be clinically important, in particular how to interpret a difference in mean outcome in unexposed/exposed groups. Where it can be calculated, the proportion/percentage beyond a suitable cut-point is useful in defining individuals at high risk to give a more meaningful outcome. In this simulation study we compute differences in outcome means and proportions that arise from hypothetical small effects in vulnerable sub-populations. METHODS: Data from over 28,000 mother/child pairs belonging to the Environmental influences on Child Health Outcomes Program were used to examine the impact of hypothetical environmental exposures on mean birthweight, and low birthweight (LBW) (birthweight < 2500g). We computed mean birthweight in unexposed/exposed groups by sociodemographic categories (maternal education, health insurance, race, ethnicity) using a range of hypothetical exposure effect sizes. We compared the difference in mean birthweight and the percentage LBW, calculated using a distributional approach. RESULTS: When the hypothetical mean exposure effect was fixed (at 50, 125, 167 or 250g), the absolute difference in % LBW (risk difference) was not constant but varied by socioeconomic categories. The risk differences were greater in sub-populations with the highest baseline percentages LBW: ranging from 3.1-5.3 percentage points for exposure effect of 125g. Similar patterns were seen for other mean exposure sizes simulated. CONCLUSIONS: Vulnerable sub-populations with greater baseline percentages at high risk fare worse when exposed to a small insult compared to the general population. This illustrates another facet of health disparity in vulnerable individuals.

Survivorship Needs in Patients With Head and Neck Cancer in Regional, Rural and Remote Areas: A Systematic Review.

OBJECTIVE: Understanding survivorship issues among people with head and neck cancer (HNC) is important as survival rates increase. Most research has focused on urban patients, leaving a gap in understanding the challenges faced by those in rural areas. This study aims to summarise the literature on survivorship needs for people with HNC in rural areas. METHODS: PubMed, PsycINFO, Scopus, Medline, CINAHL, Web of Science, and Embase were searched from database inception to 10 July 2024, with no restriction on publication period, country, or language. Data on study aims, country, methodology, and major findings related to HNC survivors in rural areas were extracted. Study quality was assessed using the Joanna Briggs Institute critical appraisal checklists. RESULTS: Twenty-one studies met the inclusion criteria. Eight studies were qualitative, 11 were quantitative, and two adopted a mixed-methods approach. Results demonstrate the impact of complex treatments on physical (n = 13) and psychosocial (n = 14) functioning. This study also emphasises multifaceted challenges, including reduced access to specialised services, resulting in greater travel and financial burden, extending to caregivers. Hence, primary healthcare services are crucial in supporting these patients closer to home. CONCLUSIONS: Addressing the gaps in equitable post-treatment care requires an even distribution of healthcare funding and workforce in rural areas. Future research could target these issues to develop tailored interventions or models of care, such as shared care, to ease access and financial burden.

Comparative analysis of In vivo endothelial cell translatomes across central nervous system vascular beds.

Endothelial cells (ECs) display organ- and tissue-specific heterogeneity. In the eye, the retinal and choroidal vascular beds are distinct networks with different molecular and morphological properties that serve location-specific functions, i.e., the former maintaining a tight barrier and the latter, a permeable fenestrated vasculature. Given that retinal health critically relies on the function of these vascular beds and that their dysfunction is implicated in a variety of retinal diseases, a molecular understanding of both physiological and pathophysiological characteristics of these distinct vasculatures is critical. Given their interspersed anatomic distribution among parenchymal cells, the study of EC gene expression, in vivo, has been hampered by the challenge of isolating pure populations of ocular ECs in sufficient quantities for large-scale transcriptomics. To address this challenge, we present a methodological and analytical workflow to facilitate inter-tissue comparisons of the in vivo EC translatome isolated from choroid, retina, and brain using the Cre-inducible NuTRAP flox construct and two widely-used endothelial Cre mouse lines: constitutive Tie2-Cre and tamoxifen-inducible Cdh5-CreERT2. For each Cre line, inter-tissue comparison of TRAP-RNAseq enrichment (TRAP-isolated translatome vs input transcriptome) showed tissue-specific gene enrichments with differential pathway representation. For each mouse model, inter-tissue comparison of the EC translatome (choroid vs brain, choroid vs retina, and brain vs retina) showed over 50% overlap of differentially expressed genes (DEGs) between the three paired comparisons, with differential pathway representation for each tissue. Pathway analysis of DEGs in the Cdh5-NuTRAP vs Tie2-NuTRAP comparison for retina, choroid, and brain predicted inhibition of processes related to myeloid cell function and activation, consistent with more specific targeting of ECs in the Cdh5-NuTRAP than in the Tie2-NuTRAP model which also targets hematopoietic progenitors giving rise to immune cells. Indeed, while TRAP enriches for EC transcripts in both models, myeloid transcripts were also captured in the Tie2-NuTRAP model which was confirmed using cell sorting. We suggest experimental/analytical considerations should be taken when selecting Cre-lines to target ECs.

Comparison of AI-integrated pathways with human-AI interaction in population mammographic screening for breast cancer.

Artificial intelligence (AI) readers of mammograms compare favourably to individual radiologists in detecting breast cancer. However, AI readers cannot perform at the level of multi-reader systems used by screening programs in countries such as Australia, Sweden, and the UK. Therefore, implementation demands human-AI collaboration. Here, we use a large, high-quality retrospective mammography dataset from Victoria, Australia to conduct detailed simulations of five potential AI-integrated screening pathways, and examine human-AI interaction effects to explore automation bias. Operating an AI reader as a second reader or as a high confidence filter improves current screening outcomes by 1.9-2.5% in sensitivity and up to 0.6% in specificity, achieving 4.6-10.9% reduction in assessments and 48-80.7% reduction in human reads. Automation bias degrades performance in multi-reader settings but improves it for single-readers. This study provides insight into feasible approaches for AI-integrated screening pathways and prospective studies necessary prior to clinical adoption.

The Society for Cardiovascular Magnetic Resonance Registry at 150,000.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is increasingly utilized to evaluate expanding cardiovascular conditions. The Society for Cardiovascular Magnetic Resonance (SCMR) Registry is a central repository for real-world clinical data to support cardiovascular research, including those relating to outcomes, quality improvement, and machine learning. The SCMR Registry is built on a regulatory-compliant, cloud-based infrastructure that houses searchable content and Digital Imaging and Communications in Medicine images. The goal of this study is to summarize the status of the SCMR Registry at 150,000 exams. METHODS: The processes for data security, data submission, and research access are outlined. We interrogated the Registry and presented a summary of its contents. RESULTS: Data were compiled from 154,458 CMR scans across 20 United States sites, containing 299,622,066 total images (∼100 terabytes of storage). Across reported values, the human subjects had an average age of 58 years (range 1 month to >90 years old), were 44% (63,070/145,275) female, 72% (69,766/98,008) Caucasian, and had a mortality rate of 8% (9,962/132,979). The most common indication was cardiomyopathy (35,369/131,581, 27%), and most frequently used current procedural terminology code was 75561 (57,195/162,901, 35%). Macrocyclic gadolinium-based contrast agents represented 89% (83,089/93,884) of contrast utilization after 2015. Short-axis cines were performed in 99% (76,859/77,871) of tagged scans, short-axis late gadolinium enhancement (LGE) in 66% (51,591/77,871), and stress perfusion sequences in 30% (23,241/77,871). Mortality data demonstrated increased mortality in patients with left ventricular ejection fraction <35%, the presence of wall motion abnormalities, stress perfusion defects, and infarct LGE, compared to those without these markers. There were 456,678 patient-years of all-cause mortality follow-up, with a median follow-up time of 3.6 years. CONCLUSION: The vision of the SCMR Registry is to promote evidence-based utilization of CMR through a collaborative effort by providing a web mechanism for centers to securely upload de-identified data and images for research, education, and quality control. The Registry quantifies changing practice over time and supports large-scale real-world multicenter observational studies of prognostic utility.

Models of survivorship care in patients with head and neck cancer in regional, rural, and remote areas: a systematic review.

PURPOSE: Rural people with head and neck cancers (HNC) are likely to experience poorer health outcomes due to limited access to health services, so many benefit from models of care that account for rurality. The aim of this review was to synthesise literature on models of care in this population. METHODS: Studies were identified using seven databases: PubMed, PsycINFO, Scopus, Embase, CINAHL, Medline, and Web of Science. Studies that tested or reported a model of care in rural HNC survivors were included. Data on characteristics and outcomes of the models were synthesised according to the domains in the Cancer Survivorship Care Quality Framework, and study quality was appraised. RESULTS: Seventeen articles were included. Eight were randomised controlled trials (seven with a control group and one single-arm study). Three models were delivered online, nine via telehealth, and five in-person. Majority were led by nurses and allied health specialists and most addressed management of physical (n = 9) and psychosocial effects (n = 6), while only a few assessed implementation outcomes such as cost-effectiveness. None evaluated the management of chronic health conditions. CONCLUSION: Positive outcomes were reported for domains of survivorship care that were measured; however, further evaluation of models of care for rural people with HNC is needed to assess effectiveness across all domains of care. IMPLICATIONS FOR CANCER SURVIVORS: Rural cancer survivors are a diverse population with unique needs. Alternative models of care such as shared care, or models personalised to the individual, could be considered to reduce disparities in access to care and outcomes.

Interaction Between State-Level Cigarette Prices and County-Level Tobacco 21 Coverage on Cigarette Smoking Outcomes Among US Adolescents.

PURPOSE: To examine whether Tobacco 21 (T21) law coverage moderated associations between cigarette prices and adolescent smoking and associated disparities. METHODS: We used nationally representative, repeated cross-sectional 2014-2020 Monitoring the Future study data (n = 20,547-96,083) to examine associations between state-level average cigarette price per pack and county-level T21 coverage (100% vs. < 100%) on past 30-day smoking participation, first and daily cigarette smoking initiation, and smoking intentions in US adolescents in eighth, 10th, and 12th grade. We implemented weighted, grade-stratified, modified Poisson regression models to test for interactions between price and T21 coverage for each outcome. We also tested for disparities by sex, race and ethnicity, parental education, and college educational expectations. RESULTS: Higher cigarette prices were associated with a lower probability of past 30-day smoking participation among eighth graders in counties with < 100% T21 coverage (average marginal effect = -0.003, 95% confidence interval = -0.006, 0.000) but not among eighth graders in counties with 100% T21 coverage (average marginal effect = 0.001, 95% confidence interval = -0.001, 0.004) (p for interaction = 0.005). There were no associations with other smoking outcomes or grades or evidence of differential associations by sociodemographic factors. DISCUSSION: Our findings suggested that higher cigarette prices were associated with lower adolescent smoking among eighth graders living in counties with < 100% T21 coverage. However, no such association was observed in other grades or smoking outcomes. Further investigation is necessary to determine the best combination of policies to reduce adolescent smoking, related sociodemographic disparities, and the use of other tobacco products in areas with fewer tobacco control policies.

Neighborhood racial income inequality and cognitive health.

INTRODUCTION: Neighborhood socioeconomic status (SES) has been linked to dementia, but the distribution of SES within a neighborhood may also matter. METHODS: Data from 460 (47% Black, 46% White) older adults from the Michigan Cognitive Aging Project were linked to census tract-level data from the National Neighborhood Data Archive (NaNDA). Neighborhood SES included two composites reflecting disadvantage and affluence. Neighborhood racial income inequality was the ratio of median incomes for White versus Black residents. Generalized estimating equations examined associations between neighborhood factors and cognitive domains. RESULTS: Neighborhood racial income inequality was uniquely associated with worse cognitive health, and these associations did not differ by participant race. Neighborhood disadvantage was only associated with worse cognitive health among Black participants. DISCUSSION: Both the level and racial distribution of SES within a neighborhood may be relevant for dementia risk. Racial differences in the level and impact of neighborhood SES contribute to dementia inequalities. HIGHLIGHTS: Black participants lived in neighborhoods with lower socioeconomic status (SES) than White participants, on average. Neighborhood SES and racial income inequality were associated with worse cognition. Effects of neighborhood racial income inequality did not differ across racial groups. Effects of neighborhood SES were only evident among Black participants.

Reproducibility between preschool and school-age Social Responsiveness Scale forms in the Environmental influences on Child Health Outcomes program.

Evidence suggests core autism trait consistency in older children, but development of these traits is variable in early childhood. The Social Responsiveness Scale (SRS) measures autism-related traits and broader autism phenotype, with two age-dependent forms in childhood (preschool, 2.5-4.5 years; school age, 4-18 years). Score consistency has been observed within forms, though reliability across forms has not been evaluated. Using data from the Environmental Influences on Child Health Outcomes (ECHO) program (n = 853), preschool, and school-age SRS scores were collected via maternal report when children were an average of 3.0 and 5.8 years, respectively. We compared reproducibility of SRS total scores (T-scores) and agreement above a clinically meaningful cutoff (T-scores ≥ 60) and examined predictors of discordance in cutoff scores across forms. Participant scores across forms were similar (mean difference: 3.3 points; standard deviation: 7), though preschool scores were on average lower than school-age scores. Most children (88%) were classified below the cutoff on both forms, and overall concordance was high (92%). However, discordance was higher in cohorts following younger siblings of autistic children (16%). Proportions of children with an autism diagnoses were also higher among those with discordant scores (27%) than among those with concordant scores (4%). Our findings indicate SRS scores are broadly reproducible across preschool and school-age forms, particularly for capturing broader, nonclinical traits, but also suggest that greater variability of autism-related traits in preschool-age children may reduce reliability with later school-age scores for those in the clinical range.

Polymicrobial arcanobacterium haemolyticum intracerebral abscess: A case report and review of the literature.

Objective: This article describes a case of polymicrobial Arcanobacterium haemolyticum pharyngitis and sinusitis complicated by intracranial complications and reviews similar cases in the literature. Case summary: A 21-year-old immunocompetent male presented with symptoms of sore throat, rhinorrhoea, lethargy, headache, and rash. Imaging demonstrated sinusitis, pre-septal sinusitis, peritonsillar abscess formation, subdural empyema and cerebritis. He was managed with endoscopic sinus surgery, craniotomy for evacuation of subdural empyema and antibiotics. Microbiological samples demonstrated growth of A. haemolyticum, strep. anginosus, and fusobacterium necrophorum. He subsequently developed a cerebral abscess requiring stereotactic needle drainage. After a prolonged course of antibiotics, the patient was discharge and made a good recovery. Discussion: A. haemolyticum is an uncommon cause of non-streptococcal pharyngitis that may occur alongside other microorganisms and is rarely associated with severe intracranial complications. This organism and its antibiotic susceptibility patterns should be considered in complicated upper respiratory tract infections in immunocompetent hosts. Penicillins and macrolide antibiotics form the mainstay of therapy for A. haemolyticum.

BRAIxDet: Learning to detect malignant breast lesion with incomplete annotations.

Methods to detect malignant lesions from screening mammograms are usually trained with fully annotated datasets, where images are labelled with the localisation and classification of cancerous lesions. However, real-world screening mammogram datasets commonly have a subset that is fully annotated and another subset that is weakly annotated with just the global classification (i.e., without lesion localisation). Given the large size of such datasets, researchers usually face a dilemma with the weakly annotated subset: to not use it or to fully annotate it. The first option will reduce detection accuracy because it does not use the whole dataset, and the second option is too expensive given that the annotation needs to be done by expert radiologists. In this paper, we propose a middle-ground solution for the dilemma, which is to formulate the training as a weakly- and semi-supervised learning problem that we refer to as malignant breast lesion detection with incomplete annotations. To address this problem, our new method comprises two stages, namely: (1) pre-training a multi-view mammogram classifier with weak supervision from the whole dataset, and (2) extending the trained classifier to become a multi-view detector that is trained with semi-supervised student-teacher learning, where the training set contains fully and weakly-annotated mammograms. We provide extensive detection results on two real-world screening mammogram datasets containing incomplete annotations and show that our proposed approach achieves state-of-the-art results in the detection of malignant breast lesions with incomplete annotations.

Age- and sex- divergent translatomic responses of the mouse retinal pigmented epithelium.

Aging is the main risk factor for age-related macular degeneration (AMD), a retinal neurodegenerative disease that leads to irreversible blindness, particularly in people over 60 years old. Retinal pigmented epithelium (RPE) atrophy is an AMD hallmark. Genome-wide chromatin accessibility, DNA methylation, and gene expression studies of AMD and control RPE demonstrate epigenomic/transcriptomic changes occur during AMD onset and progression. However, mechanisms by which molecular alterations of normal aging impair RPE function and contribute to AMD pathogenesis are unclear. Here, we specifically interrogate the RPE translatome with advanced age and across sexes in a novel RPE reporter mouse model. We find differential age- and sex- associated transcript expression with overrepresentation of pathways related to inflammation in the RPE. Concordant with impaired RPE function, the phenotypic changes in the aged translatome suggest that aged RPE becomes immunologically active, in both males and females, with some sex-specific signatures, which supports the need for sex representation for in vivo studies.

Biplex quantitative PCR to detect transcriptionally active human papillomavirus 16 from patient saliva.

Head and neck cancers, particularly oropharyngeal cancers (OPC), have been increasingly associated with human papillomavirus (HPV) infections, specifically HPV16. The current methods for HPV16 detection primarily rely on p16 staining or PCR techniques. However, it is important to note the limitations of conventional PCR, as the presence of viral DNA does not always indicate an ongoing viral infection. Moreover, these tests heavily rely on the availability of tissue samples, which can present challenges in certain situations. In this study, we developed a RT-qPCR biplex approach to detect HPV16 oncogenes E6 and E7 RNA in saliva samples from OPC patients. Salivary supernatant was used as the liquid biopsy source. We successfully obtained RNA from salivary supernatant, preserving its integrity as indicated by the detection of several housekeeping genes. Our biplex approach accurately detected E6 and E7 RNA in HPV16-positive cell lines, tissues, and finally in OPC salivary samples. Importantly, the assay specifically targeted HPV16 and not HPV18. This biplexing technique allowed for reduced sample input without compromising specificity. In summary, our approach demonstrates the potential to detect viable HPV16 in saliva from OPC patients. Since the assay measures HPV16 RNA, it provides insights into the transcriptional activity of the virus. This could guide clinical decision-making and treatment planning for individuals with HPV-related OPC.

First Phase Development of a Patient-reported Outcome Measure for Midface Oncology.

Background: Facial cancer surgery involving the midface (comprising the lower eyelids, nose, cheeks, and upper lip) can have debilitating life-changing functional, social, and psychological impacts on the patient. Midface symptoms are inadequately captured by existing patient-reported outcome measures (PROMs). PROMs are increasingly used for individual patient care, quality improvement, and standardized reporting of treatment outcomes. This study aimed to present our findings from the first phase of the development of a midface, specifically periocular and nasal, PROM. Methods: After international guidance for PROM development, the first phase comprised identification of salient issues and item generation. Fifteen patients who had midface surgery and 10 clinicians from various specialties with more than 5 years' experience treating these patients were recruited. Semi-structured interviews explored aesthetic, functional, social, and psychological outcomes, with specific attention to deficiencies in current PROMs. Thematic analysis was used to develop an item pool, and group interviews with clinicians were carried out to create and refine PROM scales. Results: Qualitative data from patient interviews were grouped into aesthetic, functional, and psychosocial domains for the eyelids and nose. Ninety-nine draft items were generated across these domains. Following focus group discussions, the final version of the midface-specific PROM contained 31 items (13 eye-specific, 10-nose-specific, eight general midface items). Conclusions: This midface-specific PROM is valuable in assessing and comparing patient-reported outcomes in those who have undergone complex resection and reconstruction of the midface. This PROM is currently undergoing field testing.

Use of an upright power wheelchair in spinal cord injury: a case series.

Objective: To explore independence, usability, and self-reported quality of life (QOL) in eligible persons with spinal cord injury (SCI) who used a standing powered wheelchair over a 12-week period. Setting: VA SCI research facility. Participants: Four participants with chronic SCI who use a wheelchair as the primary means of mobility. Intervention: A standing power wheelchair was used three times a week (3.5 h/session) for 12 weeks in a supervised setting. Main Outcome Measures: safety, usability and feasibility, blood pressure in seated and standing positions, bowel, bladder, and pain item banks from the SCI-QOL Physical-Medical-Health domain, and overall user satisfaction with the device. Results: Participants consistently maintained normal blood pressure responses between seated and standing positions throughout the training sessions and learned to perform all the mobility tasks safely and independently. Participants reported improvements on the SCI-QOL and were generally satisfied with the upright standing power wheelchair. Conclusions: In this small case series of chronic, non-ambulatory individuals with SCI, the standing powered wheelchair was shown to be safe and efficacious.

Quantifying the role of saltmarsh as a vulnerable carbon sink: A case study from Northern Portugal.

Saltmarshes play a crucial role in carbon sequestration and storage, although they are increasingly threatened by climate change-induced sea level rise (SLR). This study assessed the potential variation in Blue Carbon stocks across regional and local scales, and estimated their economic value and potential habitat loss due to SLR based on the IPCC AR6 scenarios for 2050 and 2100 in three estuarine saltmarshes in northern Portugal, the saltmarshes of the Minho, Lima and Cávado estuaries. The combined carbon stock of these saltmarshes was 38,798 ± 2880 t of organic carbon, valued at 3.96 ± 0.38 M€. Local and regional differences in carbon stocks were observed between common species, with the cordgrass Spartina patens and the reed Phragmites australis consistently showing higher values in the Lima saltmarsh in some of the parameters. Overall, the Lima saltmarsh had the highest total carbon per species cover, with S. patens showing the highest values among common species. Bolboschoenus maritimus had the highest values in the Minho saltmarsh, while the other species presented a similar carbon storage capacity. Potential habitat loss due to SLR was most evident in the Cávado saltmarsh over shorter timescales, with a significant risk of inundation even for median values of SLR, while the Lima saltmarsh was shown to be more resistant and resilient. If habitat loss directly equates to carbon loss within these saltmarshes, projected CO2 emissions may range from 22,000 to 43,449 t by 2050 and 33,000 to 130,000 t by 2100 (under the IPCC SSP5-8.5 scenario). The study shows the importance of Blue Carbon site-specific estimates, acknowledging the potential future repercussions from habitat loss due to SLR. It emphasizes the need to consider local and regional variability in Blue Carbon stocks assessments and highlights the critical importance of preserving and rehabilitating these ecosystems to ensure their continued efficacy as vital carbon sinks, thereby contributing to climate change mitigation efforts.

Estimating the effect of latent time-varying count exposures using multiple lists.

A major challenge in longitudinal built-environment health studies is the accuracy of commercial business databases that are used to characterize dynamic food environments. Different databases often provide conflicting exposure measures on the same subject due to different source credibilities. As on-site verification is not feasible for historical data, we suggest combining multiple databases to correct the bias in health effect estimates due to measurement error in any 1 datasource. We propose a joint model for the time-varying health outcomes, observed count exposures, and latent true count exposures. Our model estimates the time-specific quality of sources and incorporates time dependence of true count exposure by Poisson integer-valued first-order autoregressive process. We take a Bayesian nonparametric approach to flexibly account for location-specific exposures. By resolving the discordance between different databases, our method reduces the bias in the longitudinal health effect of the true exposures. Our method is demonstrated with childhood obesity data in California public schools with respect to convenience store exposures in school neighborhoods from 2001 to 2008.