Using software development progress data to understand threats to project outcomes

Peer reviewe

Acquired demyelination but not genetic developmental defects in myelination leads to brain tissue stiffness changes

Changes in axonal myelination are an important hallmark of aging and a number of neurological diseases. Demyelinated axons are impaired in their function and degenerate over time. Oligodendrocytes, the cells responsible for myelination of axons, are sensitive to mechanical properties of their environment. Growing evidence indicates that mechanical properties of demyelinating lesions are different from the healthy state and thus have the potential to affect myelinating potential of oligodendrocytes. We performed a high-resolution spatial mapping of the mechanical heterogeneity of demyelinating lesions using atomic force microscope-enabled indentation. Our results indicate that the stiffness of specific regions of mouse brain tissue is influenced by age and degree of myelination. Here we specifically demonstrate that acquired acute but not genetic demyelination leads to decreased tissue stiffness, which could influence the remyelination potential of oligodendrocytes. We also demonstrate that specific brain regions have unique ranges of stiffness in white and grey matter. Our ex vivo findings may help the design of future in vitro models to mimic the mechanical environment of the brain in healthy and diseased states. The mechanical properties of demyelinating lesions reported here may facilitate novel approaches in treating demyelinating diseases such as multiple sclerosis

Bringing onco‐innovation to Europe’s healthcare systems. The potential of biomarker testing, real world evidence, tumour agnostic therapies to empower personalised medicine

Rapid and continuing advances in biomarker testing are not being matched by uptake in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. The potential that genomics has brought to biomarker testing in diagnosis, prediction and research is being realised, pre‐eminently in many cancers, but also in an ever‐wider range of conditions— notably BRCA1/2 testing in ovarian, breast, pancreatic and prostate cancers. Nevertheless, the implementation of genetic testing in clinical routine setting is still challenging. Development is impeded by country‐related heterogeneity, data deficiencies, and lack of policy alignment on standards, approval—and the role of real‐world evidence in the process—and reimbursement. The acute nature of the problem is compellingly illustrated by the particular challenges facing the development and use of tumour agnostic therapies, where the gaps in preparedness for taking advantage of this innovative approach to cancer therapy are sharply exposed. Europe should already have in place a guarantee of universal access to a minimum suite of biomarker tests and should be planning for an optimum testing scenario with a wider range of biomarker tests integrated into a more sophisticated health system articulated around personalised medicine. Improving healthcare and winning advantages for Europe’s industrial competitiveness and innovation require an appropriate policy framework—starting with an update to outdated recommendations. We show herein the main issues and proposals that emerged during the previous advisory boards organised by the European Alliance for Personalized Medicine which mainly focus on possible scenarios of harmonisation of both oncogenetic testing and management of cancer patients

Bringing onco-innovation to Europe’s healthcare systems: the potential of biomarker testing, real world evidence, tumour agnostic therapies to empower personalised medicine

International audienceRapid and continuing advances in biomarker testing are not being matched by uptake in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. The potential that genomics has brought to biomarker testing in diagnosis, prediction and research is being realised, pre-eminently in many cancers, but also in an ever-wider range of conditions—notably BRCA1/2 testing in ovarian, breast, pancreatic and prostate cancers. Nevertheless, the implementation of genetic testing in clinical routine setting is still challenging. Development is impeded by country-related heterogeneity, data deficiencies, and lack of policy alignment on standards, approval—and the role of real-world evidence in the process—and reimbursement. The acute nature of the problem is compellingly illustrated by the particular challenges facing the development and use of tumour agnostic therapies, where the gaps in preparedness for taking advantage of this innovative approach to cancer therapy are sharply exposed. Europe should already have in place a guarantee of universal access to a minimum suite of biomarker tests and should be planning for an optimum testing scenario with a wider range of biomarker tests integrated into a more sophisticated health system articulated around personalised medicine. Improving healthcare and winning advantages for Europe’s industrial competitiveness and innovation require an appropriate policy framework—starting with an update to outdated recommendations. We show herein the main issues and proposals that emerged during the previous advisory boards organised by the European Alliance for Personalized Medicine which mainly focus on possible scenarios of harmonisation of both oncogenetic testing and management of cancer patients

Two-site recognition of Staphylococcus aureus peptidoglycan by lysostaphin SH3b

Lysostaphin is a bacteriolytic enzyme targeting peptidoglycan, the essential component of the bacterial cell envelope. It displays a very potent and specific activity toward staphylococci, including methicillin-resistant Staphylococcus aureus. Lysostaphin causes rapid cell lysis and disrupts biofilms, and is therefore a therapeutic agent of choice to eradicate staphylococcal infections. The C-terminal SH3b domain of lysostaphin recognizes peptidoglycans containing a pentaglycine crossbridge and has been proposed to drive the preferential digestion of staphylococcal cell walls. Here we elucidate the molecular mechanism underpinning recognition of staphylococcal peptidoglycan by the lysostaphin SH3b domain. We show that the pentaglycine crossbridge and the peptide stem are recognized by two independent binding sites located on opposite sides of the SH3b domain, thereby inducing a clustering of SH3b domains. We propose that this unusual binding mechanism allows synergistic and structurally dynamic recognition of S. aureus peptidoglycan and underpins the potent bacteriolytic activity of this enzyme

A comparative analysis of multi-level computer-assisted decision making systems for traumatic injuries

<p>Abstract</p> <p>Background</p> <p>This paper focuses on the creation of a predictive computer-assisted decision making system for traumatic injury using machine learning algorithms. Trauma experts must make several difficult decisions based on a large number of patient attributes, usually in a short period of time. The aim is to compare the existing machine learning methods available for medical informatics, and develop reliable, rule-based computer-assisted decision-making systems that provide recommendations for the course of treatment for new patients, based on previously seen cases in trauma databases. Datasets of traumatic brain injury (TBI) patients are used to train and test the decision making algorithm. The work is also applicable to patients with traumatic pelvic injuries.</p> <p>Methods</p> <p>Decision-making rules are created by processing patterns discovered in the datasets, using machine learning techniques. More specifically, CART and C4.5 are used, as they provide grammatical expressions of knowledge extracted by applying logical operations to the available features. The resulting rule sets are tested against other machine learning methods, including AdaBoost and SVM. The rule creation algorithm is applied to multiple datasets, both with and without prior filtering to discover significant variables. This filtering is performed via logistic regression prior to the rule discovery process.</p> <p>Results</p> <p>For survival prediction using all variables, CART outperformed the other machine learning methods. When using only significant variables, neural networks performed best. A reliable rule-base was generated using combined C4.5/CART. The average predictive rule performance was 82% when using all variables, and approximately 84% when using significant variables only. The average performance of the combined C4.5 and CART system using significant variables was 89.7% in predicting the exact outcome (home or rehabilitation), and 93.1% in predicting the ICU length of stay for airlifted TBI patients.</p> <p>Conclusion</p> <p>This study creates an efficient computer-aided rule-based system that can be employed in decision making in TBI cases. The rule-bases apply methods that combine CART and C4.5 with logistic regression to improve rule performance and quality. For final outcome prediction for TBI cases, the resulting rule-bases outperform systems that utilize all available variables.</p

Bone mineral density in partially recovered early onset anorexic patients - a follow-up investigation

<p>Abstract</p> <p>Background and aims</p> <p>There still is a lack of prospective studies on bone mineral development in patients with a history of early onset Anorexia nervosa (AN). Therefore we assessed associations between bone mass accrual and clinical outcomes in a former clinical sample. In addition to an expected influence of regular physical activity and hormone replacement therapy, we explored correlations with nutritionally dependent hormones.</p> <p>Methods</p> <p>3-9 years (mean 5.2 ± 1.7) after hospital discharge, we re-investigated 52 female subjects with a history of early onset AN. By means of a standardized approach, we evaluated the general outcome of AN. Moreover, bone mineral content (BMC) and bone mineral density (BMD) as well as lean and fat mass were measured by dual-energy x-ray absorptiometry (DXA). In a substudy, we measured the serum concentrations of leptin and insulin-like growth factor-I (IGF-I).</p> <p>Results</p> <p>The general outcome of anorexia nervosa was good in 50% of the subjects (BMI ≥ 17.5 kg/m², resumption of menses). Clinical improvement was correlated with BMC and BMD accrual (χ²= 5.62/χ²= 6.65, p = 0.06 / p = 0.036). The duration of amenorrhea had a negative correlation with BMD (r = -.362; p < 0.01), but not with BMC. Regular physical activity tended to show a positive effect on bone recovery, but the effect of hormone replacement therapy was not significant. Using age-related standards, the post-discharge sample for the substudy presented IGF-I levels below the 5^thpercentile. IGF-I serum concentrations corresponded to the general outcome of AN. By contrast, leptin serum concentrations showed great variability. They correlated with BMC and current body composition parameters.</p> <p>Conclusions</p> <p>Our results from the main study indicate a certain adaptability of bone mineral accrual which is dependent on a speedy and ongoing recovery. While leptin levels in the substudy tended to respond immediately to current nutritional status, IGF-I serum concentrations corresponded to the individual's age and general outcome of AN.</p

Trends in template/fragment-free protein structure prediction

Predicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward

Bringing onco‐innovation to Europe’s healthcare systems: The potential of biomarker testing, real world evidence, tumour agnostic therapies to empower personalised medicine

Rapid and continuing advances in biomarker testing are not being matched by uptake in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. The potential that genomics has brought to biomarker testing in diagnosis, prediction and research is being realised, pre‐eminently in many cancers, but also in an ever‐wider range of conditions— notably BRCA1/2 testing in ovarian, breast, pancreatic and prostate cancers. Nevertheless, the implementation of genetic testing in clinical routine setting is still challenging. Development is impeded by country‐related heterogeneity, data deficiencies, and lack of policy alignment on standards, approval—and the role of real‐world evidence in the process—and reimbursement. The acute nature of the problem is compellingly illustrated by the particular challenges facing the development and use of tumour agnostic therapies, where the gaps in preparedness for taking advantage of this innovative approach to cancer therapy are sharply exposed. Europe should already have in place a guarantee of universal access to a minimum suite of biomarker tests and should be planning for an optimum testing scenario with a wider range of biomarker tests integrated into a more sophisticated health system articulated around personalised medicine. Improving healthcare and winning advantages for Europe’s industrial competitiveness and innovation require an appropriate policy framework—starting with an update to outdated recommendations. We show herein the main issues and proposals that emerged during the previous advisory boards organised by the European Alliance for Personalized Medicine which mainly focus on possible scenarios of harmonisation of both oncogenetic testing and management of cancer patients

Structures and Aggregation of the Methylamine−Borane Molecules, MenH3−nN·BH3 (n = 1−3), Studied by X-ray Diffraction, Gas-Phase Electron Diffraction, and Quantum Chemical Calculations

The structures of the molecules methylamine-borane, MeH(2)N.BH(3), and dimethylamine-borane, Me(2)HN.BH(3), have been investigated by gas-phase electron diffraction (GED) and quantum chemical calculations. The crystal structures have also been determined for methylamine-, dimethylamine-, and trimethylamine-borane, Me(n)H(3-n)N.BH(3) (n = 1-3); these are noteworthy for what they reveal about the intermolecular interactions and, particularly, the N-H...H-B dihydrogen bonding in the cases where n = 1 or 2. Hence, structures are now known for all the members of the ammonia- and amine-borane series Me(n)H(3-n)N.BH(3) (n = 0-3) in both the gas and solid phases. The structural variations and energetics of formation of the gaseous adducts are discussed in relation to the basicity of the Me(n)H(3-n)N fragment. The relative importance of secondary interactions in the solid adducts with n = 0-3 has been assessed by the semi-classical density sums (SCDS-PIXEL) approach