Methodological limitations have hampered the use of heavy water (2H2O), a convenient, universal biosynthetic label, for measuring protein synthesis. Analyses of 2H-labeled amino acids are sensitive to contamination; labeling of peptides has been measured for a few serum proteins, but this approach awaits full validation. Here we describe a method for quantifying protein synthesis by peptide mass spectrometry (MS) after 2H2O labeling, as applied to various proteins of the major histocompatibility complex (MHC). Human and murine antigen-presenting cells were cultured in medium containing 5% 2H2O; class I and class II MHC proteins were immunoprecipitated, bands were excised, and Ala-/Gly-rich, allele-specific tryptic peptides were identified by liquid chromatography–tandem mass spectrometry (LC–MS/MS). Mass isotopomer distributions were quantified precisely by LC–MS and shifted markedly on 2H2O labeling. Experimental data agreed closely with models obtained by mass isotopomer distribution analysis (MIDA) and were consistent with contributions from Ala, Gly, and other amino acids to labeling. Estimates of fractional protein synthesis from peptides of the same protein were precise and internally consistent. The method was capable of discriminating between MHC isotypes and alleles, applicable to primary cells, and readily extendable to other proteins. It simplifies measurements of protein synthesis, enabling novel applications in physiology, in genotype/phenotype interactions, and potentially in kinetic proteomics.

This study compared a remote-delivered pain management program, the Pain Course, when delivered in online and workbook formats. Participants (n = 178) were randomised into 2 groups: (1) an Internet Group (n = 84) who were provided with secure accounts to the program in an online format; or (2) a Workbook Group (n = 94) who were mailed workbook versions of the program. The content of both programs was identical and comprised 5 core lessons, which participants were encouraged to work through over an 8-week period, according to a prescribed timetable. All participants were provided with weekly contact with a clinical psychologist through email and telephone throughout the program. The overall findings suggest that the workbook format was no less effective or acceptable than the validated online format. Significant improvements (avg. improvement; Internet Group vs Workbook Group) in levels of disability (PDI: 16% vs 24%; RMDQ: 12% vs 15%), anxiety (GAD-7: 36% vs 26%), and depression (PHQ-9: 36% vs 36%) were observed in both groups immediately posttreatment. Further improvements were observed in disability levels to 3-month follow-up, and improvements across the other primary outcomes were maintained until 12-month follow-up. High treatment completion rates and levels of satisfaction were reported in both groups, and both groups required a similarly small amount of clinician contact per participant (M = 74.85 minutes; SD = 41.03). These results highlight the public health potential of remote-delivered pain management programs, delivered in either workbook or online formats, as methods of increasing access to pain management.

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BackgroundMulti-morbidity in older adults is commonly associated with depressed mood. Similarly, subjective reports of pain are also associated with both physical illness and increased depressive symptoms. However, whether pain independently contributes to the experience of depression in older people with multi-morbidity has not been studied.MethodsIn this study, participants were 1281 consecutive older adults presenting to one of 19 primary care services in Australia (recruitment rate = 75%). Participants were asked to indicate the presence of a number of common chronic illnesses, to rate their current pain severity and to complete the Geriatric Depression Scale.ResultsResults confirmed that the number of medical illnesses reported was strongly associated with depressive symptoms. Twenty-six percent of participants with multi-morbidity scored in the clinical range for depressive symptoms in comparison to 15% of participants with no illnesses or a single illness. In regression analyses, the presence of chronic pain (t = 5.969, p < 0.0005), diabetes (t = 4.309, p < 0.0005), respiratory (t = 3.720, p < 0.0005) or neurological illness (t = 2.701, p = 0.007) were all independent contributors to depressive symptoms. Even when controlling for each individual illness, and the overall number of illnesses (t = 2.207, p = 0.028), pain severity remained an independent predictor of depressed mood (F change = 28.866, p < 0.0005, t = 5.373, p < 0.0005).ConclusionsPhysicians should consider screening for mood problems amongst those with multi-morbidity, particularly those who experience pain.