Sarcopenic obesity is associated with telomere shortening: findings from the NHANES 1999-2002.

Sarcopenic obesity (SO) is characterised by the concurrent presence of sarcopenia and excess adiposity. Telomere shortening has been associated with sarcopenia and obesity alone but the association between SO and telomere length (TL) has not been investigated. This study aimed to investigate SO and TL in an adult population. Data were from 5397 individuals (mean age = 44.7 years, 51.3% male) enrolled in the National Health and Nutrition Examination Survey. Body composition (BC) was assessed by Dual Energy X-Ray Absorptiometry. Two models were used to assess SO: a BC model including four phenotypes derived from the combination of high or low adiposity and muscle mass; and, a truncal fat mass to appendicular skeletal mass ratio (TrFM/ASM). TL was assessed using quantitative polymerase chain reaction and expressed as base pairs. The mean TL, relative to the reference DNA, was calculated and expressed as the mean T/S ratio. A General Linear Model was applied to determine associations between TL for SO. In adjusted analysis, only individuals with SO, defined as the presence of high adiposity-low muscle mass (four-phenotype model), had significantly shorter telomeres (p = 0.05) than the reference group (i.e. low adiposity-high muscle mass), with a mean T/S ratio of 1.02 (95%CI: 0.98-1.05) compared to 1.05 (95%CI: 1.01-1.09), respectively. TrFM/ASM was not associated with TL. Preliminary findings suggest that sarcopenia and obesity may act synergistically to shorten telomeres.

Drug treatment of cystic fibrosis.

Cystic fibrosis is the most common life-limiting autosomal recessive condition in Australia. A defect in the cystic fibrosis transmembrane conductance regulator protein affects chloride transport across epithelial cells. Patients with cystic fibrosis produce thick sticky mucus. This causes problems in multiple organs, particularly the lungs. Cystic fibrosis modulator therapies can partially correct the underlying pathophysiology and improve chloride transport, thereby improving morbidity. Life expectancy is improving, so many patients are now developing chronic diseases associated with ageing. All health professionals should be aware that the cystic fibrosis modulator therapies are metabolised via cytochrome P450 pathways in the liver. There are therefore significant drug-drug interactions with medicines metabolised by the same pathways.

Pediatric problematic severe asthma: Recent advances in management.

Problematic severe asthma remains a significant challenge to manage, accounting for the majority of healthcare utilization among children with asthma. The heterogeneity is recognized and the clinical phenotypes of "difficult-to-treat" asthma (DA) and "severe therapy-resistant asthma" (STRA) help to guide management. Recent evidence supports molecular distinctions between these phenotypes and shows poor correlations between peripheral and airway markers of inflammation, especially in STRA. Airway neutrophils in the context of childhood severe asthma have been explored, but their role in disease causation, protection, or as bystanders remain unknown, and thus, treatment implications are unclear. Several novel management strategies, including once-daily maintenance therapy, single-device maintenance and reliever therapy, and novel biological treatments are being increasingly used for DA and STRA. However, pediatric data for efficacy of novel treatments is scarce, and when available, is restricted to adolescents. The aim of this review is to highlight recent advances in objective biomarkers that aid stratification and management of childhood severe asthma and to highlight gaps in pediatric evidence. Specifically, the urgent need for efficacy studies to improve the management of problematic severe asthma in children younger than 12 years.

A randomized controlled trial of a structured exercise intervention after the completion of acute cancer treatment in adolescents and young adults.

BACKGROUND: Cancer treatments are frequently associated with impaired physical fitness, quality of life (QOL), and fatigue, often persisting into survivorship.  Studies in older adults with cancer have demonstrated benefits from exercise; however, this has not been rigorously investigated in adolescents and young adults (AYA). The aim of this study was to determine whether a structured 10-week exercise intervention was associated with improved cardiorespiratory fitness (VO2peak ), fatigue, and QOL in AYA who have recently completed cancer treatment. METHOD: Forty-three AYA (median age 21 ± 6 years) were randomly assigned to an exercise group (n = 22) or a control group (n = 21). The exercise group received a structured 10-week exercise program comprising progressive aerobic and resistance exercise; the control arm received routine care. VO2peak was measured at baseline, 10 weeks, and six months. Fatigue and QOL were assessed by the FACIT fatigue scale and the PEDS QL, respectively. RESULTS: Mean VO2peak at baseline was 26.5 ± 7.2 mL.kg-1 .min-1 , which is substantially lower than population norms. The exercise group demonstrated significant improvement in VO2peak at 10 weeks compared with controls (33.8 ± 8.1 vs 29.6 ± 7.6 mL.kg-1 .min-1 , P = 0.0002), but by six months, the difference was no longer significant (32.9 ± 7.0 vs 30.9 ± 11.0 mL.kg-1 .min-1 , P = 0.21). There were no significant differences in fatigue or total QOL scores between groups. CONCLUSION: Cancer treatment is associated with reduced VO2peak in AYA. Improvement in VO2peak was accelerated by a 10-week exercise program; however, no significant benefit was observed in QOL or fatigue. The plateau in VO2peak at six months suggests that a maintenance exercise program may be beneficial.

Development of a non-invasive exhaled breath test for the diagnosis of head and neck cancer.

BACKGROUND: Improving the ability to identify early-stage head and neck squamous cell carcinoma (HNSCC) can improve treatment outcomes and patient morbidity. We sought to determine the diagnostic accuracy of breath analysis as a non-invasive test for detecting HNSCC. METHODS: Standardised breath samples were collected from 181 patients suspected of HNSCC prior to any treatment. A selected ion flow-tube mass spectrometer was used to analyse breath for volatile organic compounds. Diagnosis was confirmed by histopathology. A binomial logistic regression model was used to differentiate breath profiles between cancer and control (benign disease) patients based on mass spectrometry derived variables. RESULTS: In all, 66% of participants had early-stage primary tumours (T1 and T2) and 58% had regional node metastasis. The optimised logistic regression model using three variables had a sensitivity and specificity of 80% and 86%, respectively, with an AUC for ROC curve of 0.821 (95%CI 0.625-1.0) in the testing cohort. CONCLUSIONS: Breath analysis for non-invasive diagnosis of HNSCC appears to be practical and accurate. Future studies should be conducted in a primary care setting to determine the applicability of breath analysis for early identification of HNSCC.

An observational study investigating the use of patient-owned technology to quantify physical activity in survivors of critical illness.

BACKGROUND: Physical activity after intensive care unit (ICU) discharge is challenging to measure but could inform research and practice. A patient's smartphone may provide a novel method to quantify physical activity. OBJECTIVES: We aimed to evaluate the feasibility and accuracy of using smartphone step counts among survivors of critical illness. METHODS: We performed a prospective observational cohort study in 50 patients who had an ICU length of stay>48 h, owned a smartphone, were ambulatory before admission, and were likely to attend follow-up at 3 and 6 months after discharge. At follow-up, daily step counts were extracted from participants' smartphones and two FitBit pedometers, and exercise capacity (6-min walk test) and quality of life (European Quality of Life-5 Dimensions) were measured. RESULTS: Thirty-nine (78%) patients returned at 3 months and 33 (66%) at 6 months, the median [interquartile range] smartphone step counts being 3372 [1688-5899] and 2716 [1717-5994], respectively. There was a strong linear relationship, with smartphone approximating 0.71 (0.58, 0.84) of FitBit step counts, P < 0.0001, R-squared = 0.87. There were weak relationships between step counts and the 6-min walk test distance. CONCLUSION: Although smartphone ownership and data acquisition limit the viability of using extracted smartphone steps at this time, mean daily step counts recorded using a smartphone may act as a surrogate for a dedicated pedometer; however, the relationship between step counts and other measures of physical recovery remains unclear.

Wide Disagreement Between Alternative Assessments of Premorbid Physical Activity: Subjective Patient and Surrogate Reports and Objective Smartphone Data.

OBJECTIVES: Surrogate-decision maker and patient self-reported estimates of the distances walked prior to acute illness are subjective and may be imprecise. It may be possible to extract objective data from a patient's smartphone, specifically, step and global position system data, to quantify physical activity. The objectives were to 1) assess the agreement between surrogate-decision maker and patient self-reported estimates of distance and time walked prior to resting and daily step-count and 2) determine the feasibility of extracting premorbid physical activity (step and global position system) data from critically ill patients. DESIGN: Prospective cohort study. SETTING: Quaternary ICU. PATIENTS: Fifty consecutively admitted adult patients who owned a smartphone, who were ambulatory at baseline, and who remained in ICU for more than 48 hours participated. MEASURMENTS AND MAIN RESULTS: There was no agreement between patients and surrogates for all premorbid walking metrics (mean bias 108% [99% lower to 8,700% higher], 83% [97% to 2,100%], and 71% [96% to 1,080%], for distance, time, and steps, respectively). Step and/or global position system data were successfully extracted from 24 of 50 phones (48%; 95% CI, 35-62%). Surrogate-decision makers, but not patient self-reported, estimates of steps taken per day correlated with smartphone data (surrogates: n = 13, ρ = 0.56, p < 0.05; patients: n = 13, ρ = 0.30, p = 0.317). CONCLUSION: There was a lack of agreement between surrogate-decision maker and patient self-reported subjective estimates of distance walked. Obtaining premorbid physical activity data from the current-generation smartphones was feasible in approximately 50% of patients.

Culture-Independent Detection of Nontuberculous Mycobacteria in Clinical Respiratory Samples.

Culture-based detection of nontuberculous Mycobacteria (NTM) in respiratory samples is time consuming and can be subject to overgrowth by nonmycobacterial bacteria. We describe a single-reaction TaqMan quantitative PCR assay for the direct detection of NTM species in clinical samples that is specific, sensitive, and robust.

Multidomain Assembler (MDA) Generates Models of Large Multidomain Proteins.

Homology modeling predicts protein structures using known structures of related proteins as templates. We developed MULTIDOMAIN ASSEMBLER (MDA) to address the special problems that arise when modeling proteins with large numbers of domains, such as fibronectin with 30 domains, as well as cases with hundreds of templates. These problems include how to spatially arrange nonoverlapping template structures, and how to get the best template coverage when some sequence regions have hundreds of available structures while other regions have a few distant homologs. MDA automates the tasks of template searching, visualization, and selection followed by multidomain model generation, and is part of the widely used molecular graphics package UCSF CHIMERA (University of California, San Francisco). We demonstrate applications and discuss MDA's benefits and limitations.

Dementia with Lewy Bodies: Genomics, Transcriptomics, and Its Future with Data Science.

Dementia with Lewy bodies (DLB) is a significant public health issue. It is the second most common neurodegenerative dementia and presents with severe neuropsychiatric symptoms. Genomic and transcriptomic analyses have provided some insight into disease pathology. Variants within SNCA, GBA, APOE, SNCB, and MAPT have been shown to be associated with DLB in repeated genomic studies. Transcriptomic analysis, conducted predominantly on candidate genes, has identified signatures of synuclein aggregation, protein degradation, amyloid deposition, neuroinflammation, mitochondrial dysfunction, and the upregulation of heat-shock proteins in DLB. Yet, the understanding of DLB molecular pathology is incomplete. This precipitates the current clinical position whereby there are no available disease-modifying treatments or blood-based diagnostic biomarkers. Data science methods have the potential to improve disease understanding, optimising therapeutic intervention and drug development, to reduce disease burden. Genomic prediction will facilitate the early identification of cases and the timely application of future disease-modifying treatments. Transcript-level analyses across the entire transcriptome and machine learning analysis of multi-omic data will uncover novel signatures that may provide clues to DLB pathology and improve drug development. This review will discuss the current genomic and transcriptomic understanding of DLB, highlight gaps in the literature, and describe data science methods that may advance the field.

ER-GUARD: an evolutionarily conserved antioxidant defense system at ER membranes.

Oxidative protein folding in the endoplasmic reticulum (ER) is essential for all eukaryotic cells yet generates hydrogen peroxide (H2O2), a reactive oxygen species (ROS). The ER-transmembrane protein that provides reducing equivalents to ER and guards the cytosol for antioxidant defense remains unidentified. Here we combine AlphaFold2-based and functional reporter screens in C. elegans to identify a previously uncharacterized and evolutionarily conserved protein ERGU-1 that fulfills these roles. Deleting C. elegans ERGU-1 causes excessive H2O2 and transcriptional gene up-regulation through SKN-1, homolog of mammalian antioxidant master regulator NRF2. ERGU-1 deficiency also impairs organismal reproduction and behaviors. Both C. elegans and human ERGU-1 proteins localize to ER membranes and form network reticulum structures. We name this system ER-GUARD, Endoplasmic Reticulum Guardian Aegis of Redox Defense. Human and Drosophila homologs of ERGU-1 can rescue C. elegans mutant phenotypes, demonstrating evolutionarily ancient and conserved functions. Together, our results reveal an ER-membrane-specific protein machinery and defense-net system ER-GUARD for peroxide detoxification and suggest a previously unknown but conserved pathway for antioxidant defense in animal cells.

Pilot study of paediatric regional lung function assessment via X-ray velocimetry (XV) imaging in children with normal lungs and in children with cystic fibrosis.

INTRODUCTION: Cystic fibrosis (CF) is a life-limiting autosomal recessive genetic condition. It is caused by mutations in the gene that encodes for a chloride and bicarbonate conducting transmembrane channel. X-ray velocimetry (XV) is a novel form of X-ray imaging that can generate lung ventilation data through the breathing cycle. XV technology has been validated in multiple animal models, including the ß-ENaC mouse model of CF lung disease. It has since been assessed in early-phase clinical trials in adult human subjects; however, there is a paucity of data in the paediatric cohort, including in CF. The aim of this pilot study was to investigate the feasibility of performing a single-centre cohort study in paediatric patients with CF and in those with normal lungs to demonstrate the appropriateness of proceeding with further studies of XV in these cohorts. METHODS AND ANALYSIS: This is a cross-sectional, single-centre, pilot study. It will recruit children aged 3-18 years to have XV lung imaging performed, as well as paired pulmonary function testing. The study will aim to recruit 20 children without CF with normal lungs and 20 children with CF. The primary outcome will be the feasibility of recruiting children and performing XV testing. Secondary outcomes will include comparisons between XV and current assessments of pulmonary function and structure. ETHICS AND DISSEMINATION: This project has ethical approval granted by The Women's and Children's Hospital Human Research Ethics Committee (HREC ID 2021/HRE00396). Findings will be disseminated through peer-reviewed publication and conferences. TRIAL REGISTRATION NUMBER: ACTRN12623000109606.

IHMCIF: An Extension of the PDBx/mmCIF Data Standard for Integrative Structure Determination Methods.

IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB.

UCSF ChimeraX: Tools for structure building and analysis.

Advances in computational tools for atomic model building are leading to accurate models of large molecular assemblies seen in electron microscopy, often at challenging resolutions of 3-4 Å. We describe new methods in the UCSF ChimeraX molecular modeling package that take advantage of machine-learning structure predictions, provide likelihood-based fitting in maps, and compute per-residue scores to identify modeling errors. Additional model-building tools assist analysis of mutations, post-translational modifications, and interactions with ligands. We present the latest ChimeraX model-building capabilities, including several community-developed extensions. ChimeraX is available free of charge for noncommercial use at https://www.rbvi.ucsf.edu/chimerax.

UCSF Chimera, MODELLER, and IMP: an integrated modeling system.

Structural modeling of macromolecular complexes greatly benefits from interactive visualization capabilities. Here we present the integration of several modeling tools into UCSF Chimera. These include comparative modeling by MODELLER, simultaneous fitting of multiple components into electron microscopy density maps by IMP MultiFit, computing of small-angle X-ray scattering profiles and fitting of the corresponding experimental profile by IMP FoXS, and assessment of amino acid sidechain conformations based on rotamer probabilities and local interactions by Chimera.

UCSF ChimeraX: Structure visualization for researchers, educators, and developers.

UCSF ChimeraX is the next-generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera. ChimeraX brings (a) significant performance and graphics enhancements; (b) new implementations of Chimera's most highly used tools, many with further improvements; (c) several entirely new analysis features; (d) support for new areas such as virtual reality, light-sheet microscopy, and medical imaging data; (e) major ease-of-use advances, including toolbars with icons to perform actions with a single click, basic "undo" capabilities, and more logical and consistent commands; and (f) an app store for researchers to contribute new tools. ChimeraX includes full user documentation and is free for noncommercial use, with downloads available for Windows, Linux, and macOS from https://www.rbvi.ucsf.edu/chimerax.

Quantitative analysis of cryo-EM density map segmentation by watershed and scale-space filtering, and fitting of structures by alignment to regions.

Cryo-electron microscopy produces 3D density maps of molecular machines, which consist of various molecular components such as proteins and RNA. Segmentation of individual components in such maps is a challenging task, and is mostly accomplished interactively. We present an approach based on the immersive watershed method and grouping of the resulting regions using progressively smoothed maps. The method requires only three parameters: the segmentation threshold, a smoothing step size, and the number of smoothing steps. We first apply the method to maps generated from molecular structures and use a quantitative metric to measure the segmentation accuracy. The method does not attain perfect accuracy, however it produces single or small groups of regions that roughly match individual proteins or subunits. We also present two methods for fitting of structures into density maps, based on aligning the structures with single regions or small groups of regions. The first method aligns centers and principal axes, whereas the second aligns centers and then rotates the structure to find the best fit. We describe both interactive and automated ways of using these two methods. Finally, we show segmentation and fitting results for several experimentally-obtained density maps.

Visualization software for molecular assemblies.

Software for viewing three-dimensional models and maps of viruses, ribosomes, filaments, and other molecular assemblies is advancing on many fronts. New developments include molecular representations that offer better control over level of detail, lighting that improves the perception of depth, and two-dimensional projections that simplify data interpretation. Programmable graphics processors offer quality, speed, and visual effects not previously possible, while 3D printers, haptic interaction devices, and auto-stereo displays show promise in more naturally engaging our senses. Visualization methods are developed by diverse groups of researchers with differing goals: experimental biologists, database developers, computer scientists, and package developers. We survey recent developments and problems faced by the developer community in bringing innovative visualization methods into widespread use.

Breath methane to hydrogen ratio as a surrogate marker of intestinal dysbiosis in head and neck cancer.

Exhaled breath compounds can non-invasively detect head and neck squamous cell carcinoma (HNSCC). Here we investigated exhaled compounds related to intestinal bacterial carbohydrate fermentation. Fasting breath samples were collected into 3 litre FlexFoil PLUS bags from patients awaiting a biopsy procedure for suspected HNSCC. Samples were analysed using a Syft selected ion flow-tube mass spectrometer and a Quintron BreathTracker. Two tailed non-parametric significance testing was conducted with corrections for multiple imputations. 74 patients were diagnosed (histological) with HNSCC and 61 patients were benign (controls). The methane to hydrogen ratio was significantly different between cancer and non-cancer controls (p = 0.0440). This ratio increased with tumour stage with a significant difference between T1 and T4 tumours (p = 0.0259). Hydrogen levels were significantly higher in controls who were smokers (p = 0.0129), with no smoking dependent methane changes. There were no differences in short chain fatty acids between groups. Exhaled compounds of intestinal carbohydrate fermentation can detect HNSCC patients. These findings suggest a modified carbohydrate fermentation profile in HNSCC patients that is tumour stage and smoking status dependent.

Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures.

Structures of biomolecular systems are increasingly computed by integrative modeling. In this approach, a structural model is constructed by combining information from multiple sources, including varied experimental methods and prior models. In 2019, a Workshop was held as a Biophysical Society Satellite Meeting to assess progress and discuss further requirements for archiving integrative structures. The primary goal of the Workshop was to build consensus for addressing the challenges involved in creating common data standards, building methods for federated data exchange, and developing mechanisms for validating integrative structures. The summary of the Workshop and the recommendations that emerged are presented here.