The biomechanical influence of tibio-talar containment on stability of the ankle joint

Chronic ankle instability (CAI) is a frequent sport orthopaedic entity. Although many risk factors have been studied extensively, little is known how it is influenced by the osseous joint configuration. Based on lateral X-rays, the radius of the talar surface and the tibial coverage of the talus (sector α) were measured on a DICOM/PACS system in 52 patients with CAI and an age- and sex-matched control group. The talar radius was found to be larger in patients with CAI (21.2±2.4mm) than in the control group (17.7±1.9mm; P<0.0001). The tibio-talar sector was smaller in patients with CAI (80°±5.1°) than in the control group (88.4°±7.2°; P<0.0001). The aim of this study is to analyse the biomechanical influence of the clinical data on stability of the ankle joint. A two-dimensional model of the tibio-talar joint in the sagittal plane was developed. The joint configuration was described by the tibio-talar sector (α) and the radius (r) of the talus. The force (F=F BW tan α/2) and energy (E=F BWr [1−cos α/2]) to dislocate the talus out of the tibial plafond were deduced. Ankle stability is a function of the tibio-talar sector: the force necessary to dislocate the joint is decreasing with a smaller sector. The clinical data show that the force needed to dislocate the ankle of CAI patients was 14% weaker than the one needed in the case of healthy subjects (P<0.0001). The energy to dislocate the ankle depends both on the sector and the radius. The clinical data do not show a significant difference between the energy needed to dislocate the joint of CAI patients and the one of healthy subjects. This is because there is a correlation of a small sector and a large radius for CAI ankles. CAI is associated with an unstable osseous joint configuration, which is characterized by a larger radius of the talus and a smaller tibio-talar sector. The findings of the biomechanical model explain the clinical observations and demonstrate how stability of the ankle joint is influenced by the osseous configuration. Surgical ankle ligament stabilization might be more recommended in patients with an unstable osseous configuration as such patients have a disposition for recurrent sprains. Removing anterior osteophytes for anterior impingement should be done carefully in CAI patients because this would decrease the tibial coverage of the talus and thus dispose the talus to dislocate anteriorly. People who have an unstable ankle configuration and who nevertheless engage in activities with high risk of ankle sprains could be asked to wear ankle protecting sports equipmen

On the size of maximal binary codes with 2, 3, and 4 distances

We address the maximum size of binary codes and binary constant weight codes with few distances. Previous works established a number of bounds for these quantities as well as the exact values for a range of small code lengths. As our main results, we determine the exact size of maximal binary codes with two distances for all lengths n≥6 as well as the exact size of maximal binary constant weight codes with 2,3, and 4 distances for several values of the weight and for all but small lengths

On the size of maximal binary codes with 2, 3, and 4 distances

We address the maximum size of binary codes and binary constant weight codes with few distances. Previous works established a number of bounds for these quantities as well as the exact values for a range of small code lengths. As our main results, we determine the exact size of maximal binary codes with two distances for all lengths $n\ge 6$ as well as the exact size of maximal binary constant weight codes with 2,3, and 4 distances for several values of the weight and for all but small lengths.Comment: Main text 23 pp. and Appendix 17p

Extracting biological age from biomedical data via deep learning: too much of a good thing?

Abstract Age-related physiological changes in humans are linearly associated with age. Naturally, linear combinations of physiological measures trained to estimate chronological age have recently emerged as a practical way to quantify aging in the form of biological age. In this work, we used one-week long physical activity records from a 2003–2006 National Health and Nutrition Examination Survey (NHANES) to compare three increasingly accurate biological age models: the unsupervised Principal Components Analysis (PCA) score, a multivariate linear regression, and a state-of-the-art deep convolutional neural network (CNN). We found that the supervised approaches produce better chronological age estimations at the expense of a loss of the association between the aging acceleration and all-cause mortality. Consequently, we turned to the NHANES death register directly and introduced a novel way to train parametric proportional hazards models suitable for out-of-the-box implementation with any modern machine learning software. As a demonstration, we produced a separate deep CNN for mortality risks prediction that outperformed any of the biological age or a simple linear proportional hazards model. Altogether, our findings demonstrate the emerging potential of combined wearable sensors and deep learning technologies for applications involving continuous health risk monitoring and real-time feedback to patients and care providers

La 'Nemours 88'

Concerted activation of different voltage-gated Ca((2+)) channel isoforms may determine the kinetics of insulin release from pancreatic islets. Here we have elucidated the role of R-type Ca(V)2.3 channels in that process. A 20% reduction in glucose-evoked insulin secretion was observed in Ca(V)2.3-knockout (Ca(V)2.3(–/–)) islets, close to the 17% inhibition by the R-type blocker SNX482 but much less than the 77% inhibition produced by the L-type Ca(2+) channel antagonist isradipine. Dynamic insulin-release measurements revealed that genetic or pharmacological Ca(V)2.3 ablation strongly suppressed second-phase secretion, whereas first-phase secretion was unaffected, a result also observed in vivo. Suppression of the second phase coincided with an 18% reduction in oscillatory Ca(2+) signaling and a 25% reduction in granule recruitment after completion of the initial exocytotic burst in single Ca(V)2.3(–/–) β cells. Ca(V)2.3 ablation also impaired glucose-mediated suppression of glucagon secretion in isolated islets (27% versus 58% in WT), an effect associated with coexpression of insulin and glucagon in a fraction of the islet cells in the Ca(V)2.3(–/–) mouse. We propose a specific role for Ca(V)2.3 Ca(2+) channels in second-phase insulin release, that of mediating the Ca(2+) entry needed for replenishment of the releasable pool of granules as well as islet cell differentiation

The biomechanical influence of tibio-talar containment on stability of the ankle joint

Chronic ankle instability (CAI) is a frequent sport orthopaedic entity. Although many risk factors have been studied extensively, little is known how it is influenced by the osseous joint configuration. Based on lateral X-rays, the radius of the talar surface and the tibial coverage of the talus (sector α) were measured on a DICOM/PACS system in 52 patients with CAI and an age- and sex-matched control group. The talar radius was found to be larger in patients with CAI (21.2 ± 2.4 mm) than in the control group (17.7 ± 1.9 mm; P < 0.0001). The tibio-talar sector was smaller in patients with CAI (80° ± 5.1°) than in the control group (88.4° ± 7.2°; P < 0.0001). The aim of this study is to analyse the biomechanical influence of the clinical data on stability of the ankle joint. A two-dimensional model of the tibio-talar joint in the sagittal plane was developed. The joint configuration was described by the tibio-talar sector (α) and the radius (r) of the talus. The force (F = F BW tan α/2) and energy (E = F BW r [1 − cos α/2]) to dislocate the talus out of the tibial plafond were deduced. Ankle stability is a function of the tibio-talar sector: the force necessary to dislocate the joint is decreasing with a smaller sector. The clinical data show that the force needed to dislocate the ankle of CAI patients was 14% weaker than the one needed in the case of healthy subjects (P < 0.0001). The energy to dislocate the ankle depends both on the sector and the radius. The clinical data do not show a significant difference between the energy needed to dislocate the joint of CAI patients and the one of healthy subjects. This is because there is a correlation of a small sector and a large radius for CAI ankles. CAI is associated with an unstable osseous joint configuration, which is characterized by a larger radius of the talus and a smaller tibio-talar sector. The findings of the biomechanical model explain the clinical observations and demonstrate how stability of the ankle joint is influenced by the osseous configuration. Surgical ankle ligament stabilization might be more recommended in patients with an unstable osseous configuration as such patients have a disposition for recurrent sprains. Removing anterior osteophytes for anterior impingement should be done carefully in CAI patients because this would decrease the tibial coverage of the talus and thus dispose the talus to dislocate anteriorly. People who have an unstable ankle configuration and who nevertheless engage in activities with high risk of ankle sprains could be asked to wear ankle protecting sports equipment