Genetic predisposition to long telomeres is associated with increased mortality after melanoma: A study of 2101 melanoma patients from hospital clinics and the general population.

Whether there is an association between measured and genetically predicted telomere length and melanoma mortality is unclear. We tested the hypothesis that measured and genetically predicted telomere length is associated with mortality after a melanoma diagnosis. We followed 2,101 patients with melanoma from hospital clinics and the general population for risk of death for up to 26 years. All had telomere length measured in DNA from leukocytes, and 2052 of these were genotyped for the three single nucleotide polymorphisms rs7726159 (TERT), rs1317082 (TERC), and rs2487999 (OBFC1); all three genotypes are associated with telomere length and combined into an allele count from 0 to 6. For each telomere-lengthening allele, the hazard ratios (HRs) for mortality in the age-adjusted and multivariable-adjusted Cox analysis were 1.12 (95% confidence interval: 1.02-1.23) and 1.11 (1.01-1.23). However, for each standard deviation increase in measured telomere length, HR for mortality was 0.97 (0.88-1.08). In conclusion, in more than 2000 melanoma patients from hospital clinics and from the general population, genetically predicted long telomeres were associated with increased mortality, but measured leukocyte telomere length was not.

Measured and genetically predicted plasma YKL-40 levels and melanoma mortality.

PURPOSE: High plasma levels of YKL-40 might be associated with mortality in patients with melanoma, and it is unknown if YKL-40 is causally related to mortality. EXPERIMENTAL DESIGN: We studied two cohorts: 2618 patients with melanoma from hospital clinics and 1413 general population patients with melanoma, totalling 4031 patients followed up for mortality end-points for up to 20 years. All were genotyped for CHI3L1 rs4950928, highly predictive of lifelong plasma YKL-40, and plasma YKL-40 levels were measured in 2165 patients. We tested the hypotheses that measured and genetically predicted high plasma YKL-40 are associated with increased mortality in patients with melanoma. RESULTS: For the hospital melanoma cohort, age- and sex-adjusted hazard ratios for death in individuals with measured plasma YKL-40 in the 96-100th percentile versus 1-95th percentile and per 10-percentile increase were 1.52 (95% confidence interval, 1.07-2.16) and 1.07 (1.02-1.11), respectively, most pronounced for patients with localised melanomas. Each C-allele of the CHI3L1 rs4950928 genotype was associated with plasma YKL-40 level increases of 32% in the hospital melanoma cohort (p = 6 × 10-48) and 43% in the general population melanoma cohort (p = 7 × 10-13). Multifactorially adjusted ratios for these increases in the combined cohorts were 1.04 (1.00-1.09) observationally for measured plasma YKL-40 and 0.98 (0.86-1.12) for the genetically predicted plasma YKL-40. CONCLUSION: Measured, but not genetically predicted, increasing plasma YKL-40 was associated with increased mortality in patients with melanoma. Plasma YKL-40 is a marker but less likely to be a cause of increased mortality in patients with melanoma.

Gait Estimation and Analysis from Noisy Observations.

People's walking style - their gait - can be an indicator of their health as it is affected by pain, illness, weakness, and aging. Gait analysis aims to detect gait variations. It is usually performed by an experienced observer with the help of different devices, such as cameras, sensors, and/or force plates. Frequent gait analysis, to observe changes over time, is costly and impractical. This paper initiates an inexpensive gait analysis based on recorded video. Our methodology first discusses estimating gait movements from predicted 2D joint locations that represent selected body parts from videos. Then, using a long-short-term memory (LSTM) regression model to predict 3D (Vicon) data, which was recorded simultaneously with the videos as ground truth. Feet movements estimated from video are highly correlated with the Vicon data, enabling gait analysis by measuring selected spatial gait parameters (step and cadence length, and walk base) from estimated movements. Using inexpensive and reliable cameras to record, estimate and analyse a person's gait can be helpful; early detection of its changes facilitates early intervention.

Sway Risk Analysis Based on Age Group Classification.

Human postural sway is the horizontal movement, which is generated to control a person's balance while walking or standing. Changes in postural sway patterns are a reflection of changes in brain signals and in physical health affected by a person's aging process. This increases the likelihood of falling. In this paper, we propose a method to estimate the age groups of elderly people based on the extracted sway measurements. These measurements are computed based on learning the postural sway signal from video footage only. Then, we use the person's real age and the estimated age group to define a risk of a fall for the elderly people becoming more likely. This may lead to an early intervention and help them to prevent serious falls or injuries by putting countermeasures in place, e.g. physical exercise regimes. The conducted experiments show the reliability of the proposed method to produce a risk analysis tool for elderly based on their estimated sway signals.

Respiratory influence on left atrial volume calculation with 3D-echocardiography.

BACKGROUND: Left atrial volume (LAV) estimation with 3D echocardiography has been shown to be more accurate than 2D volume calculation. However, little is known about the possible effect of respiratory movements on the accuracy of the measurement. METHODS: 100 consecutive patients admitted with chest pain were examined with 3D echocardiography and LAV was quantified during inspiratory breath hold, expiratory breath hold and during free breathing. RESULTS: Of the 100 patients, only 65 had an echocardiographic window that allowed for 3D echocardiography in the entire respiratory cycle. Mean atrial end diastolic volume was 45.4 ± 14.5 during inspiratory breath hold, 46.4 ± 14.8 during expiratory breath hold and 45.6 ± 14.3 during free respiration. Mean end systolic volume was 17.6 ± 7.8 during inspiratory breath hold, 18.8 ± 8.0 during expiratory breath hold and 18.3 ± 8.0 during free respiration. No significant differences were seen in any of the measured parameters. CONCLUSIONS: The present study adds to the feasibility of 3D LAV quantitation. LAV estimation by 3D echocardiography may be performed during either end-expiratory or end-inspiratory breath-hold without any significant difference in the calculated volume. Also, the LAV estimation may be performed during free breathing.