Bone mechanical stimulation with piezoelectric materials

This chapter summarized explores in vivo use of a piezoelectric polymer for bone mechanical stimulatio

Piezoelectric actuators for bone mechanical stimulation: exploring the concept.

Arthroplasty is liable to cause intense changes on strain levels and distribution in the boné surrounding the implant, namely stress shielding. Several solutions have been proposed for this, namely design variations and development of controlled-stiffness implants. A new approach to this problem, with potential application to other orthopaedic problems and other medical fields, would be the development of smart implants integrating systems for bone mechanical stimulation. Ideally, the implant should presente sensing capability and the ability to maintain physiological levels of strain at the implant interface. Piezoelectric materials’ huge potential as a mean to produce direct mechanical stimulation lies on the possibility of producing stimuli at a high range of frequencies and in multiple combinations. The present in vitro and preliminary in vivo studies were a first step towards the validation of the concept

Towards Enhanced Performance Thin-film Composite Membranes via Surface Plasma Modification

Advancing the design of thin-film composite membrane surfaces is one of the most promising pathways to deal with treating varying water qualities and increase their long-term stability and permeability. Although plasma technologies have been explored for surface modification of bulk micro and ultrafiltration membrane materials, the modification of thin film composite membranes is yet to be systematically investigated. Here, the performance of commercial thin-film composite desalination membranes has been significantly enhanced by rapid and facile, low pressure, argon plasma activation. Pressure driven water desalination tests showed that at low power density, flux was improved by 22% without compromising salt rejection. Various plasma durations and excitation powers have been systematically evaluated to assess the impact of plasma glow reactions on the physico-chemical properties of these materials associated with permeability. With increasing power density, plasma treatment enhanced the hydrophilicity of the surfaces, where water contact angles decreasing by 70% were strongly correlated with increased negative charge and smooth uniform surface morphology. These results highlight a versatile chemical modification technique for post-treatment of commercial membrane products that provides uniform morphology and chemically altered surface properties

Mechanisms of cisplatin resistance and targeting of cancer stem cells: Adding glycosylation to the equation

Cisplatin-based chemotherapeutic regimens are the most frequently used (neo)adjuvant treatments for the majority of solid tumors. While platinum-based chemotherapeutic regimens have proven effective against highly proliferative malignant tumors, significant relapse and progression rates as well as decreased overall survival are still observed. Currently, it is known that sub-populations of chemoresistant cells share biological properties with cancer stem cells (CSC), which are believed to be responsible for tumor relapse, invasion and ultimately disease dissemination through acquisition of mesenchymal cell traits. In spite of concentrated efforts devoted to decipher the mechanisms underlying CSC chemoresistance and to design targeted therapeutics to these cells, proteomics has failed to unveil molecular signatures capable of distinguishing between malignant and non-malignant stem cells. This has hampered substantial developments in this complex field. Envisaging a novel rationale for an effective therapy, the current review summarizes the main cellular and molecular mechanisms underlying cisplatin resistance and the impact of chemotherapy challenge in CSC selection and clinical outcome. It further emphasizes the growing amount of data supporting a role for protein glycosylation in drug resistance. The dynamic and context-dependent nature of protein glycosylation is also comprehensively discussed, hence highlighting its potentially important role as a biomarker of CSC. As the paradigm of cancer therapeutics shifts towards precision medicine and patient-tailored therapeutics, we bring into focus the need to introduce glycomics and glycoproteomics in holistic pan-omics models, in order to integrate diverse, multimodal and clinically relevant information towards more effective cancer therapeutics.This work was supported by European Union funds (FEDER/COMPETE) and by national funds (FCT, the Portuguese Foundation for Science and Technology) under the projects with the references FCOMP-01-0124-FEDER 028188 (PTDC/BBB-EBI/0786/2012) and PTDC/BBB-EBI/0567/2014. C.R. acknowledges the support by Gastric Glyco Explorer Initial Training Network (Seventh Framework Programme grant no. 316929). IPATIMUP integrates the i3S Research Unit, which is partially supported by FCT, (PEst-C/SAU/LA0003/2013). Grants were received from FCT: SFRH/BPD/111048/2015 to J.A.F and SFRH/BD/111242/2015 to A.P. FCT is co-financed by European Social Fund (ESF) under Human Potential Operation Programme (POPH) from National Strategic Reference Framework (NSRF)

Bone turnover markers for early detection of fracture healing disturbances: A review of the scientific literature

Imaging techniques are the standard method for assessment of fracture healing processes. However, these methods are perhaps not entirely reliable for early detection of complications, the most frequent of these being delayed union and non-union. A prompt diagnosis of such disorders could prevent prolonged patient distress and disability. Efforts should be directed towards the development of new technologies for improving accuracy in diagnosing complications following bone fractures. The variation in the levels of bone turnover markers (BTMs) have been assessed with regard to there ability to predict impaired fracture healing at an early stage, nevertheless the conclusions of some studies are not consensual. In this article the authors have revised the potential of BTMs as early predictors of prognosis in adult patients presenting traumatic bone fractures but who did not suffer from osteopenia or postmenopausal osteoporosis. The available information from the different studies performed in this field was systematized in order to highlight the most promising BTMs for the assessment of fracture healing outcome

Impacts of climate extremes in Brazil the development of a web platform for understanding long-term sustainability of ecosystems and human health in amazonia (pulse-Brazil)

This is the final version of the article. Available from the American Meteorological Society via the DOI in this record.This work was funded by the joint FAPESP 2011/51843-2 and NERC NE/J016276/1 International Opportunities Fund. PULSE-Brazil development is also funded by the FAPESP grant (2012/51876-0) under the Belmont Forum Cooperation Agreement. Marengo and Aragão thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for their Research Productivity Fellowship

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male nondeployed Regular US Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naive Bayes, random forests, support vector regression and elastic net penalized regression) were explored. Of the Army suicides in 2004-2009, 41.5% occurred among 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100 000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded