Deep conditional generative model for longitudinal single-slice abdominal computed tomography harmonization.

Purpose: Two-dimensional single-slice abdominal computed tomography (CT) provides a detailed tissue map with high resolution allowing quantitative characterization of relationships between health conditions and aging. However, longitudinal analysis of body composition changes using these scans is difficult due to positional variation between slices acquired in different years, which leads to different organs/tissues being captured. Approach: To address this issue, we propose C-SliceGen, which takes an arbitrary axial slice in the abdominal region as a condition and generates a pre-defined vertebral level slice by estimating structural changes in the latent space. Results: Our experiments on 2608 volumetric CT data from two in-house datasets and 50 subjects from the 2015 Multi-Atlas Abdomen Labeling Challenge Beyond the Cranial Vault (BTCV) dataset demonstrate that our model can generate high-quality images that are realistic and similar. We further evaluate our method's capability to harmonize longitudinal positional variation on 1033 subjects from the Baltimore longitudinal study of aging dataset, which contains longitudinal single abdominal slices, and confirmed that our method can harmonize the slice positional variance in terms of visceral fat area. Conclusion: This approach provides a promising direction for mapping slices from different vertebral levels to a target slice and reducing positional variance for single-slice longitudinal analysis. The source code is available at: https://github.com/MASILab/C-SliceGen.

Perceptions and attitudes of Rohingya community stakeholders to pregnancy termination services: a qualitative study in camps of Cox's Bazar, Bangladesh.

BACKGROUND: Rohingya women suffer from inaccessibility to sexual and reproductive health services in Myanmar. After the forcible displacement of the Rohingya from Myanmar to Bangladesh in 2017, pregnancy termination services have been increasingly important and desired, while knowledge gaps and obstacles to access services still exist. The role of community stakeholders is critical as gatekeepers and decision-makers to improve and strengthen pregnancy termination services for women in camps. However, there is paucity of evidence on their perspectives about pregnancy termination. This qualitative study aims to understand the perception and attitudes of Rohingya community stakeholders to pregnancy termination in the camps of Cox's Bazar. METHODS: We used purposive sampling to select 48 participants from the community stakeholders, 12 from each group: majhis (Rohingya leaders), imams (religious leaders), school teachers, and married men. We conducted in-depth interviews of all the participants between May-June 2022 and October-November 2022. Data were coded on Atlas.ti and analysed using a thematic content analysis approach. RESULTS: Multiple socio-cultural and religious factors, gendered norms and stigma associated with pregnancy termination acted as barriers to women seeking services for it. From a religious stance, there was greater acceptance of pregnancy termination in the earlier period than in the later period of pregnancy. We observed that pregnancy termination among community stakeholders in earlier stages of pregnancy than later. However, circumstances, such as a woman's marital status, whether she sought her husband's permission or her ability of childcare capacity, were often framed by community stakeholders as 'acceptable' for pregnancy termination. Health concerns and social and contextual factors can influence community stakeholders supporting pregnancy termination. CONCLUSIONS: The community stakeholders perspectives on barriers and enablers of pregnancy termination were variable with the context. These perspectives may support or impede women's ability to choice to seek pregnancy termination services. To improve women's choice to pregnancy termination, it is critical to consider roles of community stakeholders in creating their supporting attitudes to women's choice and access, and to designing targeted culturally appropriate interventions with communities support and engagement.

Sleep Duration Polygenic Risk and Phenotype: Associations with Biomarkers of Accelerated Aging in the Baltimore Longitudinal Study of Aging.

We sought to explore whether genetic risk for, and self-reported, short sleep are associated with biological aging and whether age and sex moderate these associations. Participants were a subset of individuals from the Baltimore Longitudinal Study of Aging who had complete data on self-reported sleep (n = 567) or genotype (n = 367). Outcomes included: Intrinsic Horvath age, Hannum age, PhenoAge, GrimAge, and DNAm-based estimates of plasminogen activator inhibitor-1 (PAI-1) and granulocyte count. Results demonstrated that polygenic risk for short sleep was positively associated with granulocyte count; compared to those reporting <6 hr sleep, those reporting >7 hr demonstrated faster PhenoAge and GrimAge acceleration and higher estimated PAI-1. Polygenic risk for short sleep and self-reported sleep duration interacted with age and sex in their associations with some of the outcomes. Findings highlight that polygenic risk for short sleep and self-reported long sleep is associated with variation in the epigenetic landscape and subsequently aging.

Correlates of life course physical activity in participants of the Baltimore longitudinal study of aging.

Physical activity is consistently associated with better health and longer life spans. However, the extent to which length and intensity of exercise across the life course impact health outcomes relative to current activity is undefined. Participants of the Baltimore Longitudinal Study of Aging were asked to categorize their level of physical activity in each decade of life from adolescence to the current decade. In linear mixed effects models, self-reported past levels of physical activity were significantly associated with activity assessed at study visits in the corresponding decade of life either by questionnaire or accelerometry. A pattern of life course physical activity (LCPA) derived by ranking participants on reported activity intensity across multiple decades was consistent with the trajectories of activity estimated from standard physical activity questionnaires assessed at prior study visits. In multivariable linear regression models LCPA was associated with clinical characteristics, measures of body composition and indicators of physical performance independent of current physical activity. After adjustment for minutes of high intensity exercise, LCPA remained significantly associated with peak VO2, fasting glucose, thigh muscle area and density, abdominal subcutaneous fat, usual gait speed, lower extremity performance, and multimorbidity (all p < 0.01) at the index visit. The observed associations suggest that an estimate of physical activity across decades provides complementary information to information on current activity and reemphasizes the importance of consistently engaging in physical activity over the life course.

Cross-sectional analysis of healthy individuals across decades: Aging signatures across multiple physiological compartments.

The study of age-related biomarkers from different biofluids and tissues within the same individual might provide a more comprehensive understanding of age-related changes within and between compartments as these changes are likely highly interconnected. Understanding age-related differences by compartments may shed light on the mechanism of their reciprocal interactions, which may contribute to the phenotypic manifestations of aging. To study such possible interactions, we carried out a targeted metabolomic analysis of plasma, skeletal muscle, and urine collected from healthy participants, age 22-92 years, and identified 92, 34, and 35 age-associated metabolites, respectively. The metabolic pathways that were identified across compartments included inflammation and cellular senescence, microbial metabolism, mitochondrial health, sphingolipid metabolism, lysosomal membrane permeabilization, vascular aging, and kidney function.

Plant Protein but Not Animal Protein Consumption Is Associated with Frailty through Plasma Metabolites.

There is evidence that the association of protein intake and frailty may depend on the source of dietary protein. The mechanism underlying this association is not clear. In this study, we explore circulating metabolites as mediators of the relationship between dietary protein and of frailty in participants of the Baltimore Longitudinal Study of Aging (BLSA). Cross-sectional analyses in 735 BLSA participants of associations between plant and animal protein intake and frailty. Usual protein intake from plant and animal sources were estimated with a Food Frequency Questionnaire (FFQ) and frailty was assessed with a 44-item Frailty Index (FI). Compared with the lowest quartile, higher quartiles of plant, but not animal, protein were associated with lower FI. Twenty-five plasma metabolites were associated with plant protein intake; of these, fifteen, including phosphatidylcholines, cholesterol esters, sphingomyelins, and indole metabolites, mediated the association between plant protein intake and FI. The protective association between plant protein consumption and FI is mediated by lower abundance of lipid metabolites and higher abundance of tryptophan-related metabolites.

Research from Low-Income and Middle-Income Countries will Benefit Global Health and the Physiotherapy Profession, but it Requires Support.

Disparities in research publications are common in the physiotherapy and rehabilitation fields.1 A small proportion of published research arises from low-income and middle-income countries (LMICs),1,2 home to 85% of the world's population. Systems-level, institutional-level, and individual-level factors contribute to these disparities. With urgent and unified actions, global health and the standard of physiotherapy research in LMICs can be improved and strengthened. In this editorial, we will discuss the challenges encountered by researchers from LMICs in conducting and publishing high-quality research and propose potential strategies to address these challenges.

Epigenetic signature of human immune aging in the GESTALT study.

Age-associated DNA methylation in blood cells convey information on health status. However, the mechanisms that drive these changes in circulating cells and their relationships to gene regulation are unknown. We identified age-associated DNA methylation sites in six purified blood-borne immune cell types (naive B, naive CD4+ and CD8+ T cells, granulocytes, monocytes, and NK cells) collected from healthy individuals interspersed over a wide age range. Of the thousands of age-associated sites, only 350 sites were differentially methylated in the same direction in all cell types and validated in an independent longitudinal cohort. Genes close to age-associated hypomethylated sites were enriched for collagen biosynthesis and complement cascade pathways, while genes close to hypermethylated sites mapped to neuronal pathways. In silico analyses showed that in most cell types, the age-associated hypo- and hypermethylated sites were enriched for ARNT (HIF1ß) and REST transcription factor (TF) motifs, respectively, which are both master regulators of hypoxia response. To conclude, despite spatial heterogeneity, there is a commonality in the putative regulatory role with respect to TF motifs and histone modifications at and around these sites. These features suggest that DNA methylation changes in healthy aging may be adaptive responses to fluctuations of oxygen availability.

Longitudinal Variability Analysis on Low-dose Abdominal CT with Deep Learning-based Segmentation.

Metabolic health is increasingly implicated as a risk factor across conditions from cardiology to neurology, and efficiency assessment of body composition is critical to quantitatively characterizing these relationships. 2D low dose single slice computed tomography (CT) provides a high resolution, quantitative tissue map, albeit with a limited field of view. Although numerous potential analyses have been proposed in quantifying image context, there has been no comprehensive study for low-dose single slice CT longitudinal variability with automated segmentation. We studied a total of 1816 slices from 1469 subjects of Baltimore Longitudinal Study on Aging (BLSA) abdominal dataset using supervised deep learning-based segmentation and unsupervised clustering method. 300 out of 1469 subjects that have two year gap in their first two scans were pick out to evaluate longitudinal variability with measurements including intraclass correlation coefficient (ICC) and coefficient of variation (CV) in terms of tissues/organs size and mean intensity. We showed that our segmentation methods are stable in longitudinal settings with Dice ranged from 0.821 to 0.962 for thirteen target abdominal tissues structures. We observed high variability in most organ with ICC<0.5, low variability in the area of muscle, abdominal wall, fat and body mask with average ICC≥0.8. We found that the variability in organ is highly related to the cross-sectional position of the 2D slice. Our efforts pave quantitative exploration and quality control to reduce uncertainties in longitudinal analysis.

Single slice thigh CT muscle group segmentation with domain adaptation and self-training.

Purpose: Thigh muscle group segmentation is important for assessing muscle anatomy, metabolic disease, and aging. Many efforts have been put into quantifying muscle tissues with magnetic resonance (MR) imaging, including manual annotation of individual muscles. However, leveraging publicly available annotations in MR images to achieve muscle group segmentation on single-slice computed tomography (CT) thigh images is challenging. Approach: We propose an unsupervised domain adaptation pipeline with self-training to transfer labels from three-dimensional MR to single CT slices. First, we transform the image appearance from MR to CT with CycleGAN and feed the synthesized CT images to a segmenter simultaneously. Single CT slices are divided into hard and easy cohorts based on the entropy of pseudo-labels predicted by the segmenter. After refining easy cohort pseudo-labels based on anatomical assumption, self-training with easy and hard splits is applied to fine-tune the segmenter. Results: On 152 withheld single CT thigh images, the proposed pipeline achieved a mean Dice of 0.888 (0.041) across all muscle groups, including gracilis, hamstrings, quadriceps femoris, and sartorius muscle. Conclusions: To our best knowledge, this is the first pipeline to achieve domain adaptation from MR to CT for thigh images. The proposed pipeline effectively and robustly extracts muscle groups on two-dimensional single-slice CT thigh images. The container is available for public use in GitHub repository available at: https://github.com/MASILab/DA_CT_muscle_seg.