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

Laryngeal embryonal rhabdomyosarcoma in an adult - A case presentation in the eyes of geneticists and clinicians

<p>1. Abstract</p> <p>Background</p> <p>Rhabdomyosarcoma is a solid tumor, resulting from dysregulation of the skeletal myogenesis program. For rhabdomyosarcomas (RMS) with a predilection for the head and neck, genitourinary tract, extremities, trunk, retroperitoneum, the larynx is still an unusual site. Till now only several cases of this laryngeal tumor have been described in world literature in the adult population. The entire spectrum of genetic factors underlying RMS development and progression is unclear until today. Multiple signaling pathways seem to be involved in ERMS development and progression.</p> <p>Case presentation</p> <p>In this paper we report an interesting RMS case in which the disease was located within the glottic region. We report an embryonal rhabdomyosarcoma of the larynx in 33 year-old man. After unsuccessful chemotherapy hemilaryngectomy was performed. In follow up CT no signs of recurrence were found. Recently patient is recurrence free for 62 months.</p> <p>Conclusions</p> <p>Considering the histological diagnosis and the highly aggressive nature of the lesion for optimal diagnosis positron electron tomography (PET) and computerized tomography (CT) of the neck and thorax should be performed. At this time surgical treatment with adjuvant radiotherapy seems to be the treatment of choice for this disease. Rhabdomyosarcoma of the larynx has a better prognosis than elsewhere in the body, probably because of its earlier recognition and accessibility to radical surgery.</p

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