Separating positional noise from neutral alignment in multicomponent statistical shape models

Given sufficient training samples, statistical shape models can provide detailed population representations for use in anthropological and computational genetic studies, injury biomechanics, musculoskeletal disease models or implant design optimization. While the technique has become extremely popular for the description of isolated anatomical structures, it suffers from positional interference when applied to coupled or articulated input data. In the present manuscript we describe and validate a novel approach to extract positional noise from such coupled data. The technique was first validated and then implemented in a multicomponent model of the lower limb. The impact of noise on the model itself as well as on the description of sexual dimorphism was evaluated. The novelty of our methodology lies in the fact that no rigid transformations are calculated or imposed on the data by means of idealized joint definitions and by extension the models obtained from them

Identification of compound heterozygous variants in LRP4 D\demonstrates that a pathogenic variant outside the third beta-propeller domain can cause sclerosteosis

Sclerosteosis is a high bone mass disorder, caused by pathogenic variants in the genes encoding sclerostin or LRP4. Both proteins form a complex that strongly inhibits canonical WNT signaling activity, a pathway of major importance in bone formation. So far, all reported disease-causing variants are located in the third beta-propeller domain of LRP4, which is essential for the interaction with sclerostin. Here, we report the identification of two compound heterozygous variants, a known p.Arg1170Gln and a novel p.Arg632His variant, in a patient with a sclerosteosis phenotype. Interestingly, the novel variant is located in the first beta-propeller domain, which is known to be indispensable for the interaction with agrin. However, using luciferase reporter assays, we demonstrated that both the p.Arg1170Gln and the p.Arg632His variant in LRP4 reduced the inhibitory capacity of sclerostin on canonical WNT signaling activity. In conclusion, this study is the first to demonstrate that a pathogenic variant in the first beta-propeller domain of LRP4 can contribute to the development of sclerosteosis, which broadens the mutational spectrum of the disorder.Diabetes mellitus: pathophysiological changes and therap

Respiratory Syncytial Virus Disease Burden in Community-Dwelling and Long-Term Care Facility Older Adults in Europe and the United States: A Prospective Study

Background. Data on respiratory syncytial virus (RSV) disease burden in adults remain scarce. We assessed the burden of confirmed RSV-acute respiratory infections (cRSV-ARIs) in community-dwelling (CD) adults and those in long-term care facilities (LTCFs).Methods. In this prospective cohort study covering 2 RSV seasons (October 2019-March 2020 and October 2020-June 2021), RSVARIs were identified through active surveillance, in medically stable CD-adults =50 years (Europe) or adults =65 years in LTCFs (Europe and the United States). RSV infection was confirmed by polymerase chain reaction from combined nasal and throat swabs.Results. Of 1981 adults enrolled, 1251 adults in CD and 664 LTCFs (season 1) and 1223 adults in CD and 494 LTCFs (season 2) were included in the analyses. During season 1, overall incidence rates ([IRs] cases/1000 person-years) and attack rates (ARs) for cRSVARIs were 37.25 (95% confidence interval [CI], 22.62-61.35) and 1.84% in adults in CD and 47.85 (CI, 22.58-101.4) and 2.26% in adults in LTCFs. Complications occurred for 17.4% (CD) and 13.3% (LTCFs) of cRSV-ARIs. One cRSV-ARI occurred in season 2 (IR = 2.91 [CI, 0.40-20.97]; AR = 0.20%), without complications. No cRSV-ARIs led to hospitalization or death. Viral pathogens were codetected in =17.4% of cRSV-ARIs.Conclusions. RSV is an important cause of disease burden in adults in CD and LTCFs. Despite the observed low severity of cRSVARI, our results support the need for RSV prevention strategies among adults =50 years old

Biocontrol Potential of Forest Tree Endophytes

Peer reviewe

Predicting creditworthiness in retail banking with limited scoring data

The preoccupation with modelling credit scoring systems including their relevance to predicting and decision making in the financial sector has been with developed countries, whilst developing countries have been largely neglected. The focus of our investigation is on the Cameroonian banking sector with implications for fellow members of the Banque des Etats de L'Afrique Centrale (BEAC) family which apply the same system. We apply logistic regression (LR), Classification and Regression Tree (CART) and Cascade Correlation Neural Network (CCNN) in building our knowledge-based scoring models. To compare various models’ performances, we use ROC curves and Gini coefficients as evaluation criteria and the Kolmogorov-Smirnov curve as a robustness test. The results demonstrate that an improvement in terms of predicting power from 15.69% default cases under the current system, to 7.68% based on the best scoring model, namely CCNN can be achieved. The predictive capabilities of all models are rated as at least very good using the Gini coefficient; and rated excellent using the ROC curve for CCNN. Our robustness test confirmed these results. It should be emphasised that in terms of prediction rate, CCNN is superior to the other techniques investigated in this paper. Also, a sensitivity analysis of the variables identifies previous occupation, borrower's account functioning, guarantees, other loans and monthly expenses as key variables in the forecasting and decision making processes which are at the heart of overall credit policy