The T cell repertoire for recognition of a phylogenetically distant protein antigen. Peptide specificity and MHC restriction of staphylococcal nuclease-specific T cell clones [published erratum appears in J Exp Med 1987 Mar 1;165(3):933]

Previous studies (1) have indicated that the repertoire of murine T cells specific for a potentially complex protein antigen is in fact specific for a limited number of antigenic epitopes on that antigen in association with a given Ia molecule. Since those studies generally analyzed responses to antigens that differ in only a few amino acids from homologous murine molecules, it was possible that tolerance to self proteins was responsible for the limited T cell repertoire seen in responses to closely related proteins. It was therefore of interest to determine whether T cell recognition of a structurally and phylogenetically more distant protein molecule would also show specificity for a limited number of immunodominant peptides on that molecule. A series of experiments was designed to study the antigen fine specificity and MHC restriction of T cell clones specific for the bacterially derived antigen staphylococcal nuclease (Nase). T cell clones generated in (H-2b X H-2a)F1 (B6AF1) T cells were shown to be specific for Nase and to be restricted by either Ab alpha Ab beta or Ek alpha Ek beta. The fine specificity of these clones was then analyzed using cyanogen bromide and tryptic fragments and a series of overlapping 20-amino-acid synthetic peptides corresponding to and spanning the entire sequence of the Nase molecule. Two Ab alpha Ab beta-restricted clones were highly responsive to peptide 91-110, and not to other synthetic Nase peptides. In contrast, seven Ek alpha Ek beta-restricted clones were consistently responsive to peptide 81-100 and not to 91-110 or to other Nase peptides. Certain of these Ek alpha Ek beta-restricted T cells expressed an interesting crossreactivity, in that they responded to peptide 51-70 as well as to 81-100, although the response to 51-70 was characterized by a markedly shifted dose-response curve, indicating a reduced efficiency of activation by this peptide. Analysis of the amino acid sequences of these regions indicates that this unexpected crossreaction may have a structural basis. A single Nase-specific T cell line generated from BALB/c T cells was, in contrast to any of the B6AF1 clones studied, responsive only to peptide 61-80 and not to other peptides, including 81-100 or 91-110. Collectively, these findings show that Nase-specific T cells are responsive to discrete Nase peptides. Moreover, the present findings suggest that in T cell recognition of a complex and highly foreign protein antigen, a limited number of peptide epitopes are preferentially recognized by T cells in association with a given Ia molecule.     

A critical overview of the current myofascial pain literature – January 2018

The majority of papers included in the quarterly review discuss various aspects of dry needling (DN), which continues to be of interest to researchers and clinicians. A study by Liu et al. is the first paper to examine the effects of DN of acetylcholine, esterase and receptors. The study provides support for the integrated trigger point hypothesis and for DN. A paper by Hightower and colleagues found an intriguing link between low magnesium levels in the drink water supply, vitamin D, and myofascial pain, cancer, tendon ruptures, and colon polyps. Contributions originated in the Brazil, China, Germany, Iran, India, Poland, South Korea, Spain, Taiwan, Turkey, and the US.     

Predicting prostate tumour location from multiparametric MRI using Gaussian kernel support vector machines: a preliminary study

The performance of a support vector machine (SVM) algorithm was investigated to predict prostate tumour location using multi-parametric MRI (mpMRI) data. The purpose was to obtain information of prostate tumour location for the implementation of bio-focused radiotherapy. In vivo mpMRI data were collected from 16 patients prior to radical prostatectomy. Sequences included T2-weighted imaging, diffusion-weighted imaging and dynamic contrast enhanced imaging. In vivo mpMRI was registered with ‘ground truth’ histology, using ex vivo MRI as an intermediate registration step to improve accuracy. Prostate contours were delineated by a radiation oncologist and tumours were annotated on histology by a pathologist. Five patients with minimal imaging artefacts were selected for this study. A Gaussian kernel SVM was trained and tested on different patient data subsets. Parameters were optimised using leave-oneout cross validation. Signal intensities of mpMRI were used as features and histology annotations as true labels. Prediction accuracy, as well as area under the curve (AUC) of the receiver operating characteristics (ROC) curve, were used to assess performance. Results demonstrated the prediction accuracy ranged from 70.4 to 87.1% and AUC of ROC ranged from 0.81 to 0.94. Additional investigations showed the apparent diffusion coefficient map from diffusion weighted imaging was the most important imaging modality for predicting tumour location. Future work will incorporate additional patient data into the framework to increase the sensitivity and specificity of the model, and will be extended to incorporate predictions of biological characteristics of the tumour which will be used in bio-focused radiotherapy optimisation.     

Profiles of self-rated health in midlife adults with chronic illnesses

BACKGROUND: Self-rated health (SRH), an important indicator of cognitive appraisal of health, consistently predicts mortality, morbidity, and health services utilization. However, few explanations account for how these cognitive appraisals of health might differ within a population of midlife adults with chronic illnesses who may be at risk for further illnesses over time. OBJECTIVES: The purpose of this study was two-fold: (a) to uncover classes of chronically ill midlife adults who shared unique profiles of characteristics that predicted SRH over time and (b) to reveal the predictive factors of SRH for each class over time. METHODS: Using 5 waves of data (1992-2000) from the Health and Retirement Study, the sample included 6,335 respondents (ages 51 to 61 at baseline) who reported at least one chronic illness. Selected components of the Interaction Model of Client Health Behavior guided the inclusion of relevant predictors of SRH from the literature. Latent class regression was employed to simultaneously classify respondents and identify factors that predicted SRH for each class over time. RESULTS: The final model reflected 3 distinct profiles of SRH over time: positive health, average health, and negative health. Four time-varying predictors differed significantly across the 3 classes: overweight, work limitation, depressed mood, and living with a partner. Three time-varying predictors--comorbidity, vigorous activity less than 3 times per week, and current smoking--had the same influence on all 3 classes. DISCUSSION: The differential effects of these predictors on SRH over time distinguish these results from prior research. In future studies, profiles of SRH that are unique to each class could be used to develop class-specific targeted interventions to improve cognitive appraisal of health, whereas generic interventions would be based on the class-independent predictors of SRH.