Personalised profiling to identify clinically relevant changes in tremor due to multiple sclerosis

Background: There is growing interest in sensor-based assessment of upper limb tremor in multiple sclerosis and other movement disorders. However, previously such assessments have not been found to offer any improvement over conventional clinical observation in identifying clinically relevant changes in an individual's tremor symptoms, due to poor test-retest repeatability. Method: We hypothesised that this barrier could be overcome by constructing a tremor change metric that is customised to each individual's tremor characteristics, such that random variability can be distinguished from clinically relevant changes in symptoms. In a cohort of 24 people with tremor due to multiple sclerosis, the newly proposed metrics were compared against conventional clinical and sensor-based metrics. Each metric was evaluated based on Spearman rank correlation with two reference metrics extracted from the Fahn-Tolosa-Marin Tremor Rating Scale: a task-based measure of functional disability (FTMTRS B) and the subject's self-assessment of the impact of tremor on their activities of daily living (FTMTRS C). Results: Unlike the conventional sensor-based and clinical metrics, the newly proposed ’change in scale’ metrics presented statistically significant correlations with changes in self-assessed impact of tremor (max R2>0.5,p< 0.05 after correction for false discovery rate control). They also outperformed all other metrics in terms of correlations with changes in task-based functional performance (R2=0.25 vs. R2=0.15 for conventional clinical observation, both p< 0.05).Conclusions: The proposed metrics achieve an elusive goal of sensor-based tremor assessment: improving on conventional visual observation in terms of sensitivity to change. Further refinement and evaluation of the proposed techniques is required, but our core findings imply that the main barrier to translational impact for this application can be overcome. Sensor-based tremor assessments may improve personalised treatment selection and the efficiency of clinical trials for new treatments by enabling greater standardisation and sensitivity to clinically relevant changes in symptoms

Health enhancing strength training in nonagenarians (STRONG): rationale, design and methods

<p>Abstract</p> <p>Background</p> <p>The Health Enhancing Strength Training in Nonagenarians (STRONG) is a randomised control trial to assess the effectiveness of an aerobic and strength training program for improving muscle strength, functional capacity and quality of life in nonagenarians.</p> <p>Methods</p> <p>Sixty (51 women) nonagenarians (age range: 90–102 years) who live in a geriatric nursing home will be randomly assigned to either a usual care (control) group (n = 30) or an intervention (training) group (n = 30). Participants allocated in the usual care group will receive general physical activity guidelines and participants allocated in the intervention group will also enrol in three weekly non-consecutive individualized training sessions (~45–50 min each) during 8 weeks. The exercise program will consist of muscular strength [with a special focus on leg press at 30% (start of the program) to 70% 1 repetition maximum (end)] and aerobic exercises (cycle-ergometry during 3–5 to 15 minutes at 12–14 points in the rate of perceived exertion scale).</p> <p>Results</p> <p>Results from STRONG will help to better understand the potential of regular physical activity for improving the well-being of the oldest population groups.</p> <p>Conclusion</p> <p>The increase in life expectancy together with the dramatic decrease in birth rates in industrialized countries calls the attention to health care systems and public health policymakers to focus attention on promoting healthy lifestyle in the highest sector of the population pyramid. Our study attempts to improve functional capacity and QOL of nonagenarians by implementing an individualised aerobic and strength training program in a geriatric residential care. Results from STRONG will help to better understand the potential of regular physical activity for improving the well being even in persons aged 90 years or over.</p> <p>Trail Registration</p> <p>ClinicalTrials.gov ID: NCT00848978</p

Abstract PD6-07: PD-L1 is highly expressed in tumor infiltrating lymphocytes in pregnancy associated breast cancer

Abstract Background: Pregnancy associated breast cancer (PABC), diagnosed during or after gestation, is typically triple negative, and is associated with a poor prognosis. Those diagnosed within two years have an even worse outcome. We previously assessed the immune microenvironment of invasive breast carcinomas in young women and reported that tumor infiltrating lymphocytes (TILs) were more prominent in PABC. Programmed cell death protein 1 (PD-1) is upregulated following activation of lymphocytes, while programmed death ligand 1 (PD-L1) is one of the primary ligands that it interacts with to inhibit T-cell activation and proliferation. PD-L1 may also be constitutively expressed on tumor cells as a result of oncogenic signaling or epithelial-mesenchymal transition. Emerging evidence suggests that the effect of the local immune system, particularly the interactions between PD-1 and PD-L1, is also key in breast cancer progression and in breast tumor responses to chemotherapy and targeted therapy. In this study, we assessed expression of PD-1 and PD-L1 in both TILs and tumor cells in PABC and in age-/stage-/grade-matched nulliparous women, and correlated their expression with clinicopathologic characteristics in this aggressive type of breast carcinomas. Design: 21 patients diagnosed with PABC within two years of pregnancy (mean age=35.7, range=26-48) and 15 matched controls (mean age=37.5, range=29-51) were evaluated. Slides were reviewed and pathologic tumor characteristics, including TILs, were noted. Immunohistochemical stains for PD-1 and PD-L1 were performed. Extent (1=1-25% positive tumor cells, 2=26-50%, 3=51-75%, 4=76-100%) and intensity (1=weak, 2=moderate or 3=strong) of staining were assessed. A composite score (CS) was calculated by multiplying the extent by intensity (range=0-12; weak=1-3; moderate=4-8 and strong=9-12). Results: The mean CS for PD-L1 in TILs was significantly higher in PABC (5.86) compared to controls (3.07), p=0.03. Further, strong expression of PD-L1 in TILs was only observed in PABC (9/21, 42.9%); none of the controls had strong PD-L1, p=0.01. The high expression of PD-L1 in PABC TILs was independent of tumor grade, hormone receptor and HER2 status, and other histologic features including lymph node metastasis. Expression of PD-1 in TILs was similar in both PABC and controls (mean CS 6.81 and 5.36, respectively). Immunoreactivity in the tumor cells themselves was rare with only two PABC and four control cases expressing PD-1 and PD-L1. Conclusion: 1. TILs in PABC have significantly higher PD-L1 expression. 2. Strong expression of PD-L1 in TILs was only observed in PABC. 3. High PD-L1 expression in TILs was independent of the tumor characteristics in this series. 4. PD-1 is expressed similarly in TILs in both PABC and controls. 5. Rare cases may have PD-1 and PD-L1 expression in the tumor cells themselves. The results of our study showing significant expression of PD-L1 in PABC TILs add to the understanding of the role of the microenvironment in breast cancer progression. These complex interactions between tumors cells and the local immune system may predict response to therapy and investigation into the role of immune based therapies is under way in these aggressive breast carcinomas that affect young women. Citation Format: Blanco Jr LZ, Pincus JL, Siziopikou KP. PD-L1 is highly expressed in tumor infiltrating lymphocytes in pregnancy associated breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr PD6-07.</jats:p

Overfishing of small pelagic fishes increases trophic overlap between immature and mature striped dolphins in the Mediterranean Sea

The interactions among diet, ecology, physiology, and biochemistry affect N and C stable isotope signatures in animal tissues. Here, we examined if ecological segregation among animals in relation to sex and age existed by analyzing the signatures of δ15N and δ13C in the muscle of Western Mediterranean striped dolphins. Moreover, we used a Bayesian mixing model to study diet composition and investigated potential dietary changes over the last two decades in this population. For this, we compared isotope signatures in samples of stranded dolphins obtained during two epizootic events occurring in 1990 and 2007–2008. Mean δ13C values for females and males were not significantly different, but age-related variation indicated δ13C enrichment in both sexes, suggesting that females and males most likely fed in the same general areas, increasing their consumption of benthic prey with age. Enrichment of δ15N was only observed in females, suggesting a preference for larger or higher trophic level prey than males, which could reflect different nutritional requirements. δ13C values showed no temporal variation, although the mean δ15N signature decreased from 1990 to 2007–2008, which could indicate a dietary shift in the striped dolphin over the last two decades. The results of SIAR indicated that in 1990, hake and sardine together contributed to 60% on the diet of immature striped dolphins, and close to 90% for mature striped dolphins. Conversely, the diet of both groups in 2007–2008 was more diverse, as hake and sardine contributed to less than 40% of the entire diet. These results suggest a dietary change that was possibly related to changes in food availability, which is consistent with the depletion of sardine stocks by fishing

Multi-omics Data and Analytics Integration in Ovarian Cancer

Part 6: Medical-Health SystemsInternational audienceCancer, which involves the dysregulation of genes via multiple mechanisms, is unlikely to be fully explained by a single data type. By combining different “omes”, researchers can increase the discovery of novel bio-molecular associations with disease-related phenotypes. Investigation of functional relations among genes associated with the same disease condition may further help to develop more accurate disease-relevant prediction models. In this work, we present an integrative framework called Data & Analytic Integrator (DAI), to explore the relationship between different omics via different mathematical formulations and algorithms. In particular, we investigate the combinatorial use of molecular knowledge identified from omics integration methods netDx, iDRW and SSL, by fusing the derived aggregated similarity matrices and by exploiting these in a semi-supervised learner. The analysis workflows were applied to real-life data for ovarian cancer and underlined the benefits of joint data and analytic integration