Tuplix Calculus

We introduce a calculus for tuplices, which are expressions that generalize matrices and vectors. Tuplices have an underlying data type for quantities that are taken from a zero-totalized field. We start with the core tuplix calculus CTC for entries and tests, which are combined using conjunctive composition. We define a standard model and prove that CTC is relatively complete with respect to it. The core calculus is extended with operators for choice, information hiding, scalar multiplication, clearing and encapsulation. We provide two examples of applications; one on incremental financial budgeting, and one on modular financial budget design.Comment: 22 page

Joubert syndrome: genotyping a Northern European patient cohort

Joubert syndrome (JBS) is a rare neurodevelopmental disorder belonging to the group of ciliary diseases. JBS is genetically heterogeneous, with >20 causative genes identified to date. A molecular diagnosis of JBS is essential for prediction of disease progression and genetic counseling. We developed a targeted next-generation sequencing (NGS) approach for parallel sequencing of 22 known JBS genes plus 599 additional ciliary genes. This method was used to genotype a cohort of 51 well-phenotyped Northern European JBS cases (in some of the cases, Sanger sequencing of individual JBS genes had been performed previously). Altogether, 21 of the 51 cases (41%) harbored biallelic pathogenic mutations in known JBS genes, including 14 mutations not previously described. Mutations in C5orf42 (12%), TMEM67 (10%), and AHI1 (8%) were the most prevalent. C5orf42 mutations result in a purely neurological Joubert phenotype, in one case associated with postaxial polydactyly. Our study represents a population-based cohort of JBS patients not enriched for consanguinity, providing insight into the relative importance of the different JBS genes in a Northern European population. Mutations in C5orf42 are relatively frequent (possibly due to a Dutch founder mutation) and mutations in CEP290 are underrepresented compared with international cohorts. Furthermore, we report a case with heterozygous mutations in CC2D2A and B9D1, a gene associated with the more severe Meckel–Gruber syndrome that was recently published as a potential new JBS gene, and discuss the significance of this finding

A computed tomography based study on rotational alignment accuracy of the femoral component in total knee arthroplasty using computer-assisted orthopaedic surgery

Rotation of the femoral component in total knee arthroplasty (TKA) is of high importance in respect of the balancing of the knee and the patellofemoral joint. Though it is shown that computer assisted surgery (CAOS) improves the anteroposterior (AP) alignment in TKA, it is still unknown whether navigation helps in finding the accurate rotation or even improving rotation. Therefore the aim of our study was to evaluate the postoperative femoral component rotation on computed tomography (CT) with the intraoperative data of the navigation system. In 20 navigated TKAs the difference between the intraoperative stored rotation data of the femoral component and the postoperative rotation on CT was measured using the condylar twist angle (CTA). This is the angle between the epicondylar axis and the posterior condylar axis. Statistical analysis consisted of the intraclass correlation coefficient (ICC) and Bland-Altman plot. The mean intraoperative rotation CTA based on CAOS was 3.5° (range 2.4–8.6°). The postoperative CT scan showed a mean CTA of 4.0° (1.7–7.2). The ICC between the two observers was 0.81, and within observers this was 0.84 and 0.82, respectively. However, the ICC of the CAOS CTA versus the postoperative CT CTA was only 0.38. Though CAOS is being used for optimising the position of a TKA, this study shows that the (virtual) individual rotational position of the femoral component using a CAOS system is significantly different from the position on a postoperative CT scan

Cross validation of bi-modal health-related stress assessment

This study explores the feasibility of objective and ubiquitous stress assessment. 25 post-traumatic stress disorder patients participated in a controlled storytelling (ST) study and an ecologically valid reliving (RL) study. The two studies were meant to represent an early and a late therapy session, and each consisted of a "happy" and a "stress triggering" part. Two instruments were chosen to assess the stress level of the patients at various point in time during therapy: (i) speech, used as an objective and ubiquitous stress indicator and (ii) the subjective unit of distress (SUD), a clinically validated Likert scale. In total, 13 statistical parameters were derived from each of five speech features: amplitude, zero-crossings, power, high-frequency power, and pitch. To model the emotional state of the patients, 28 parameters were selected from this set by means of a linear regression model and, subsequently, compressed into 11 principal components. The SUD and speech model were cross-validated, using 3 machine learning algorithms. Between 90% (2 SUD levels) and 39% (10 SUD levels) correct classification was achieved. The two sessions could be discriminated in 89% (for ST) and 77% (for RL) of the cases. This report fills a gap between laboratory and clinical studies, and its results emphasize the usefulness of Computer Aided Diagnostics (CAD) for mental health care

Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning

For centuries humans have been fascinated by the natural beauty of horses in motion and their different gaits. Gait classification (GC) is commonly performed through visual assessment and reliable, automated methods for real-time objective GC in horses are warranted. In this study, we used a full body network of wireless, high sampling-rate sensors combined with machine learning to fully automatically classify gait. Using data from 120 horses of four different domestic breeds, equipped with seven motion sensors, we included 7576 strides from eight different gaits. GC was trained using several machine-learning approaches, both from feature-extracted data and from raw sensor data. Our best GC model achieved 97% accuracy. Our technique facilitated accurate, GC that enables in-depth biomechanical studies and allows for highly accurate phenotyping of gait for genetic research and breeding. Our approach lends itself for potential use in other quadrupedal species without the need for developing gait/animal specific algorithms

Prediction of continuous and discrete kinetic parameters in horses from inertial measurement units data using recurrent artificial neural networks

Vertical ground reaction force (GRFz) measurements are the best tool for assessing horses' weight-bearing lameness. However, collection of these data is often impractical for clinical use. This study evaluates GRFz predicted using data from body-mounted IMUs and long short-term memory recurrent neural networks (LSTM-RNN). Twenty-four clinically sound horses, equipped with IMUs on the upper-body (UB) and each limb, walked and trotted on a GRFz measuring treadmill (TiF). Both systems were time-synchronised. Data from randomly selected 16, 4, and 4 horses formed training, validation, and test datasets, respectively. LSTM-RNN with different input sets (All, Limbs, UB, Sacrum, or Withers) were trained to predict GRFz curves or peak-GRFz. Our models could predict GRFz shapes at both gaits with RMSE below 0.40 N.kg−1. The best peak-GRFz values were obtained when extracted from the predicted curves by the all dataset. For both GRFz curves and peak-GRFz values, predictions made with the All or UB datasets were systematically better than with the Limbs dataset, showing the importance of including upper-body kinematic information for kinetic parameters predictions. More data should be gathered to confirm the usability of LSTM-RNN for GRFz predictions, as they highly depend on factors like speed, gait, and the presence of weight-bearing lameness

Extensive Phenotyping for Potential Weight-Inducing Factors in an Outpatient Population with Obesity

Background: Obesity has been associated with miscellaneous weight-inducing determinants. A comprehensive assessment of known obesity-related factors other than diet and physical activity within one cohort is currently lacking. Objectives: To assess the prevalence of potential contributors to obesity and self-reported triggers for marked weight gain in an adult population with obesity and between obesity classes. Methods: In this observational cohort study, we assessed 408 persons with obesity (aged 41.3 ± 14.2 years, BMI 40.5 ± 6.2) visiting our obesity clinic. They were evaluated for use of weight-inducing drugs, hormonal abnormalities, menarcheal age, (high) birth weight, sleep deprivation, and obstructive sleep apnea syndrome (OSAS). We additionally assessed self-reported triggers for marked weight gain and performed genetic testing in patients suspected of genetic obesity. Results: Nearly half of the patients were using a potentially weight-inducing drug, which was also the most reported trigger for marked weight gain. For the assessed hormonal conditions, a relatively high prevalence was found for hypothyroidism (14.1%), polycystic ovary syndrome (12.0%), and male hypogonadism (41.7%). A relatively low average menarcheal age (12.6 ± 1.8 years) was reported, whereas there was a high prevalence of a high birth weight (19.5%). Sleep deprivation and OSAS were reported in, respectively, 14.5 and 13.7% of the examined patients. Obesity class appeared to have no influence on the majority of the assessed factors. Of the genetically analyzed patients, a definitive genetic diagnosis was made in 3 patients (1.9%). Conclusions: A thorough evaluation of patients with obesity yields a relatively high prevalence of various potentially weight-inducing factors. Diagnostic screening of patients with obesi

Rationale and design of the PHOspholamban RElated CArdiomyopathy intervention STudy (i-PHORECAST)

Background: The p.Arg14del (c.40_42delAGA) phospholamban (PLN) pathogenic variant is a founder mutation that causes dilated cardiomyopathy (DCM) and arrhythmogenic cardiomyopathy (ACM). Carriers are at increased risk of malignant ventricular arrhythmias and heart failure, which has been ascribed to cardiac fibrosis. Importantly, cardiac fibrosis appears to be an early feature of the disease, occurring in many presymptomatic carriers before the onset of overt disease. As with most monogenic cardiomyopathies, no evidence-based treatment is available for presymptomatic carriers. Aims: The PHOspholamban RElated CArdiomyopathy intervention STudy (iPHORECAST) is designed to demonstrate that pre-emptive treatment of presymptomatic PLN p.Arg14del carriers using eplerenone, a mineralocorticoid receptor antagonist with established antifibrotic effects, can reduce disease progression and postpone the onset of overt disease. Methods: iPHORECAST has a multicentre, prospective, randomised, open-label, blinded endpoint (PROBE) design. Presymptomatic PLN p.Arg14del carriers are randomised to receive either 50 mg eplerenone once daily or no treatment. The primary endpoint of the study is a multiparametric assessment of disease progression including cardiac magnetic resonance parameters (left and right ventricular volumes, systolic function and fibrosis), electrocardiographic parameters (QRS voltage, ventricular ectopy), signs and/or symptoms related to DCM and ACM, and cardiovascular death. The follow-up duration is set at 3 years. Baseline results: A total of 84 presymptomatic PLN p.Arg14del carriers (n = 42 per group) were included. By design, at baseline, all participants were in New York Heart Association (NHYA) class I and had a left ventricular ejection fraction > 45% and < 2500 ventricular premature contractions during 24-hour Holter monitoring. There were no statistically significant differences between the two groups in any of the baseline characteristics. The study is currently well underway, with the last participants expected to finish in 2021. Conclusion: iPHORECAST is a multicentre, prospective randomised controlled trial designed to address whether pre-emptive treatment of PLN p.Arg14del carriers with eplerenone can prevent or delay the onset of cardiomyopathy. iPHORECAST has been registered in the clinicaltrials.gov-register (number: NCT01857856)