Real-time in vivo dose measurement using ruby-based fibre optic dosimetry during internal radiation therapy.

In vivo dosimetry (IVD) in a commonly used liver cancer treatment of selective internal radiation therapy (SIRT) has been done based on the post-treatment image-based dosimetry approach. Real-time IVD is necessary to verify the dose delivery and detect errors during the treatment for better patient outcomes. This study aims to develop a fibre optic dosimeter (FOD) for in vivo real-time dose rate measurement during internal beta radiation therapy, e.g., SIRT. A ruby fibre optic probe was prepared and studied the radioluminescence (RL) characteristics, including its major challenge of stem effect arising from Cherenkov radiation and luminescence from the irradiated fibre. The stem signal was suppressed adequately using the stem removal technique of optical filtering, and only 2.3 ± 1.1% stem signal was contributed to the measured RL signal. A linear dose rate response was observed during the exposure of the ruby probe to varying dose rates using a 6 MeV electron beam and a positron-emitting radionuclide fluorine-18. The ruby exhibited a temporally non-constant RL signal, which increased the RL signal by 0.84 ± 0.29 counts/sec2 during the irradiation of the maximum dose rate used in this study of 9 Gy/min for 2 min. The ability of ruby FOD to measure the absolute dose rate with sufficient stem effect suppression and the linear RL dose rate response indicates its suitability for real-time IVD during internal beta radiation therapy. Future work will investigate the time-dependent RL characteristic of ruby and validate post-treatment image-based dosimetry using ruby-based FOD.

A study on the effects of containment policies and vaccination on the spread of SARS-CoV-2.

This paper presents a method to predict the spread of the SARS-CoV-2 in a population with a known age-structure, and then, to quantify the effects of various containment policies, including those policies that affect each age-group differently. The model itself is a compartmental model in which each compartment is divided into a number of age-groups. The parameters of the model are estimated using an optimisation scheme and some known results from the theory of monotone systems such that the model output agrees with some collected data on the spread of SARS-CoV-2. To highlight the strengths of this framework, a few case studies are presented in which different populations are subjected to different containment strategies. They include cases in which the containment policies switch between scenarios with different levels of severity. Then a case study on herd immunity due to vaccination is presented. And then it is shown how we can use this framework to optimally distribute a limited number of vaccine units in a given population to maximise their impact and reduce the total number of infectious individuals.

A Stratified Model to Quantify the Effects of Containment Policies on the Spread of COVID-19

BackgroundThe SARS-Cov-2 virus is spreading fast all over the world and has already imposed a significant social and economic cost in many countries. Different countries have utilised a variety of containment policies with an emphasis on social distancing as a strategy to stop the spread of COVID-19. Quantifying the effects of such policies in different time-scales and comparing the efficacy of various available policies is of utmost importance for policy-makers in different countries. That is even more important when the policy-makers want to plan for long-term strategies and to weigh each option based on its epidemiological effects and socio-economic costs. In the absence of detailed knowledge of the interactions between individuals in a population and the characteristics of the SARS-Cov-2 virus, quantifying the effects of these policies is very difficult. Hence, there is an immediate need for models that can predict the spread of COVID-19 in a population, without the need for such detailed information. The MethodIn this manuscript, a method is presented that can be used to predict the spread of COVID-19 in any country and under any containment policy imposed separately on different groups in the population. The method tunes the parameters of a known stratified model based on the available data on the spread of COVID-19. The model includes a set of nonlinear ordinary differential equations and is easy to simulate and easy to understand. As it is presented in this manuscript, the population is divided into age-groups. But given the availability of the data, there is no reason to limit the stratification into only age-groups and we can consider any relevant groups. To estimate the parameters of the model such that it reflects the characteristics of the spread of COVID-19 in a population, the method relies on an optimisation scheme. More specifically, the optimisation scheme estimates the contact rates between different age groups in the population. But a very important and useful feature of the model is that the estimated parameters for one population can be translated and used for any other population with a known age-structure, which in this day and age, includes almost any country or city in the world. Also, it is shown that the method is quite insensitive to the underlying assumptions in the optimisation scheme and also to deliberate or non-deliberate errors that might have occurred in collecting the data. ResultsThe capabilities of the model are demonstrated using a case study under different containment policies, from an uncontained population to mitigation and suppression policies. Also, we can use the model to quantify the effects of strategies which include switching between different containment policies at pre-determined points in time. The model allows us to quantify the effects of each of these policies on the spread of the disease in a population, in particular, the instantaneous and total numbers of infectious individuals in a population which are important parameters for policy-makers. The simulation results, as explained in the following, provide some insight into various policies and some of the results are possibly counter-intuitive for many people. For example, the model predicts that closing down schools and universities without any other containment policy imposed on older age-groups has almost no impact on the number of patients that might need support-care in hospitals. The method provides an easy-to-use tool to use the information collected on the spread of COVID-19 in a country or region and then use that information in another population which might not have been as widely affected by the disease yet.

Early detection and monitoring of cerebral ischemia using calcium-responsive MRI probes.

Cerebral ischemia is one of the leading causes of mortality and disability in infants and adults and its timely diagnosis is essential for an efficient treatment. We present a methodology for fast detection and real-time monitoring of fluctuations of calcium ions associated with focal ischemia using a molecular functional MRI approach. We used a dinuclear paramagnetic gadolinium(III) complex chelate that changes MR image contrast through its reversible interaction with extracellular calcium ions, while applying a remote transient middle cerebral artery occlusion as a model for ischemic stroke. Our method sensitively recognizes the onset and follows the dynamics of the ischemic core and penumbra with submillimeter spatial and second-scale temporal resolution, thus paving the way for noninvasive monitoring and development of targeted treatment strategies for cerebral ischemia.

Targeting Lyn regulates Snail family shuttling and inhibits metastasis.

The acquisition of an invasive phenotype by epithelial cells occurs through a loss of cellular adhesion and polarity, heralding a multistep process that leads to metastatic dissemination. Since its characterization in 1995, epithelial-mesenchymal transition (EMT) has been closely linked to the metastatic process. As a defining aspect of EMT, loss of cell adhesion through downregulation of E-cadherin is carried out by several transcriptional repressors; key among them the SNAI family of transcription factors. Here we identify for the first time that Lyn kinase functions as a key modulator of SNAI family protein localization and stability through control of the Vav-Rac1-PAK1 (Vav-Rac1-p21-activated kinase) pathway. Accordingly, targeting Lyn in vitro reduces EMT and in vivo reduces metastasis of primary tumors. We also demonstrate the clinical relevance of targeting Lyn as a key player controlling EMT; patient samples across many cancers revealed a strong negative correlation between Lyn and E-cadherin, and high Lyn expression in metastatic tumors as well as metastasis-prone primary tumors. This work reveals a novel pancancer mechanism of Lyn-dependent control of EMT and further underscores the role of this kinase in tumor progression.

Association of thrombophilia and catheter-associated thrombosis in children: a systematic review and meta-analysis.

UNLABELLED: Essentials It is unclear if thrombophilia increases the risk of catheter-associated thrombosis in children. We conducted a meta-analysis on thrombophilia and pediatric catheter-associated thrombosis. Presence of ≥1 trait confers additional risk of venous thrombosis in children with catheters. Limitations of included studies preclude us from recommending routine thrombophilia testing. SUMMARY: Background The association between thrombophilia and deep vein thrombosis (DVT) associated with central venous catheter (CVC) use, the most important pediatric risk factor for thrombosis, is unclear in children. Pediatric studies with small sample sizes have reported conflicting results. We sought to evaluate whether, among children with CVCs, thrombophilia increases the risk of CVC-associated DVT (CADVT). Materials and methods We systematically searched MEDLINE, EMBASE, the Web of Science, the Cochrane Central Register for Controlled Trials, PubMed and reference lists for controlled studies published from the inception of the database until September 2015. Included were studies of children aged <21 years with CVCs who were systematically tested for thrombophilic traits that are commonly screened for in clinical practice. Pooled prevalence rates and pooled odds ratios (pORs) of CADVT with thrombophilia were estimated by use of a random effects model. Results We analyzed 16 cohort studies with 1279 children, 277 of whom had CADVT, and with 12 traits tested. There was significant heterogeneity in the included studies. The presence of one or more traits was associated with CADVT (pOR 3.20; 95% confidence interval [CI] 1.56-6.54). Although the prevalence of most traits was < 0.10, children with protein C deficiency, elevated factor VIII levels and the FV Leiden mutation had an increased prevalence of CADVT. The association with thrombophilia seemed to be stronger for symptomatic CADVT (pOR 6.71; 95% CI 1.93-23.37) than for asymptomatic CADVT (pOR 2.14; 95% CI 1.10-4.18). Conclusions On the basis of the low prevalence of specific traits, the relatively weak association with CADVT, and the limitations of the included studies, we cannot recommend routine testing of thrombophilias in children with CADVT.

Improving the fracture toughness and the strength of epoxy using nanomaterials--a review of the current status.

The incorporation of nanomaterials in the polymer matrix is considered to be a highly effective technique to improve the mechanical properties of resins. In this paper the effects of the addition of different nanoparticles such as single-walled CNT (SWCNT), double-walled CNT (DWCNT), multi-walled CNT (MWCNT), graphene, nanoclay and nanosilica on fracture toughness, strength and stiffness of the epoxy matrix have been reviewed. The Young's modulus (E), ultimate tensile strength (UTS), mode I (GIC) and mode II (GIIC) fracture toughness of the various nanocomposites at different nanoparticle loadings are compared. The review shows that, depending on the type of nanoparticles, the integration of the nanoparticles has a substantial effect on mode I and mode II fracture toughness, strength and stiffness. The critical factors such as maintaining a homogeneous dispersion and good adhesion between the matrix and the nanoparticles are highlighted. The effect of surface functionalization, its relevancy and toughening mechanism are also scrutinized and discussed. A large variety of data comprised of the mechanical properties of nanomaterial toughened composites reported to date has thus been compiled to facilitate the evolution of this emerging field, and the results are presented in maps showing the effect of nanoparticle loading on mode I fracture toughness, stiffness and strength.

Lyn tyrosine kinase regulates androgen receptor expression and activity in castrate-resistant prostate cancer.

Castrate-resistant prostate cancer (CRPC) progression is a complex process by which prostate cells acquire the ability to survive and proliferate in the absence or under very low levels of androgens. Most CRPC tumors continue to express the androgen receptor (AR) as well as androgen-responsive genes owing to reactivation of AR. Protein tyrosine kinases have been implicated in supporting AR activation under castrate conditions. Here we report that Lyn tyrosine kinase expression is upregulated in CRPC human specimens compared with hormone naive or normal tissue. Lyn overexpression enhanced AR transcriptional activity both in vitro and in vivo and accelerated CRPC. Reciprocally, specific targeting of Lyn resulted in a decrease of AR transcriptional activity in vitro and in vivo and prolonged time to castration. Mechanistically, we found that targeting Lyn kinase induces AR dissociation from the molecular chaperone Hsp90, leading to its ubiquitination and proteasomal degradation. This work indicates a novel mechanism of regulation of AR stability and transcriptional activity by Lyn and justifies further investigation of the Lyn tyrosine kinase as a therapeutic target for the treatment of CRPC.Oncogenesis (2014) 3, e115; doi:10.1038/oncsis.2014.30; published online 18 August 2014.