The use of theranostic gadolinium-based nanoprobes to improve radiotherapy efficacy

A new efficient type of gadolinium-based theranostic agent (AGuIX®) has recently been developed for MRI-guided radiotherapy (RT). These new particles consist of a polysiloxane network surrounded by a number of gadolinium chelates, usually 10. Owing to their small size (<5 nm), AGuIX typically exhibit biodistributions that are almost ideal for diagnostic and therapeutic purposes. For example, although a significant proportion of these particles accumulate in tumours, the remainder is rapidly eliminated by the renal route. In addition, in the absence of irradiation, the nanoparticles are well tolerated even at very high dose (10 times more than the dose used for mouse treatment). AGuIX particles have been proven to act as efficient radiosensitizers in a large variety of experimental in vitro scenarios, including different radioresistant cell lines, irradiation energies and radiation sources (sensitizing enhancement ratio ranging from 1.1 to 2.5). Pre-clinical studies have also demonstrated the impact of these particles on different heterotopic and orthotopic tumours, with both intratumoural or intravenous injection routes. A significant therapeutical effect has been observed in all contexts. Furthermore, MRI monitoring was proven to efficiently aid in determining a RT protocol and assessing tumour evolution following treatment. The usual theoretical models, based on energy attenuation and macroscopic dose enhancement, cannot account for all the results that have been obtained. Only theoretical models, which take into account the Auger electron cascades that occur between the different atoms constituting the particle and the related high radical concentrations in the vicinity of the particle, provide an explanation for the complex cell damage and death observed.

Cross-participant modelling based on joint or disjoint feature selection: an fMRI conceptual decoding study

Multivariate classification techniques have proven to be powerful tools for distinguishing experimental conditions in single sessions of functional magnetic resonance imaging (fMRI) data. But they are vulnerable to a considerable penalty in classification accuracy when applied across sessions or participants, calling into question the degree to which fine-grained encodings are shared across subjects. Here, we introduce joint learning techniques, where feature selection is carried out using a held-out subset of a target dataset, before training a linear classifier on a source dataset. Single trials of functional MRI data from a covert property generation task are classified with regularized regression techniques to predict the semantic class of stimuli. With our selection techniques (joint ranking feature selection (JRFS) and disjoint feature selection (DJFS)), classification performance during cross-session prediction improved greatly, relative to feature selection on the source session data only. Compared with JRFS, DJFS showed significant improvements for cross-participant classification. And when using a groupwise training, DJFS approached the accuracies seen for prediction across different sessions from the same participant. Comparing several feature selection strategies, we found that a simple univariate ANOVA selection technique or a minimal searchlight (one voxel in size) is appropriate, compared with larger searchlights.

Femoral exostosis causing vastus medialis pain in an active young lady: a case report.

BACKGROUND:
Musculoskeletal conditions are a common reason for consultation to General Practitioners (GPs)/family physicians in primary care. Osteochondromas are the most common benign bone tumours and usually occur in the metaphyseal region of long bones. Despite the distal femur being the commonest location to find these benign bone tumours, this is the first case report in the literature specifically describing vastus medialis muscle pain as the presenting symptom due to underlying bursa formation secondary to local pressure effects.

CASE PRESENTATION:
Twenty nine year old female of white British ethnic origin, presenting to a primary care clinic with a three year history of intermittent left distal medial thigh pain.

CONCLUSION:
The benign bone tumour, femoral exostosis/osteochondroma, was diagnosed via Magnaetic Resonance Imaging (MRI) and treated conservatively, with surgical excision an option if not resolving. GPs/family physicians need to be aware of this diagnosis and that femoral exostosis/osteochondroma can present to primary care physicians, particularly within the second decade of life.

Multifocal remitting-relapsing cerebral demyelination twenty years following allogeneic bone marrow transplantation

We report a case study of a female who received an allogeneic bone marrow transplantation (BMT) from a sex-mismatched related donor and who, after a twenty-year interval, developed an acute fulminant biopsy-proven demyelinating disorder of cerebral white matter which followed a remitting-relapsing chronic course. In situ hybridization studies using Y-chromosome-specific markers revealed Y-chromosome-positive mononuclear cells in biopsy samples of white matter. Magnetic resonance imaging (MRI) studies of the asymptomatic healthy male donor showed multiple white matter lesions. These observations suggest that donor lymphocytes were sensitized to central nervous system (CNS) antigens prior to or at the time of transplantation but remained dormant for 20 years before becoming activated to cause widespread demyelination.

Multigenerational Undernutrition Increases Susceptibility to Obesity and Diabetes that Is Not Reversed after Dietary Recuperation

People in developing countries have faced multigenerational undernutrition and are currently undergoing major lifestyle changes, contributing to an epidemic of metabolic diseases, though the underlying mechanisms remain unclear. Using a Wistar rat model of undernutrition over 50 generations, we show that Undernourished rats exhibit low birth-weight, high visceral adiposity (DXA/MRI), and insulin resistance (hyperinsulinemic-euglycemic clamps), compared to age-/gender-matched control rats. Undernourished rats also have higher circulating insulin, homocysteine, endotoxin and leptin levels, lower adiponectin, vitamin B12 and folate levels, and an 8-fold increased susceptibility to Streptozotocin-induced diabetes compared to control rats. Importantly, these metabolic abnormalities are not reversed after two generations of unrestricted access to commercial chow (nutrient recuperation). Altered epigenetic signatures in insulin-2 gene promoter region of Undernourished rats are not reversed by nutrient recuperation, and may contribute to the persistent detrimental metabolic profiles in similar multigenerational undernourished human populations.

Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns

In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

Prostate cancer radiotherapy: potential applications of metal nanoparticles for imaging and therapy

Prostate cancer (CaP) is the most commonly diagnosed cancer in males. There have been dramatic technical advances in radiotherapy delivery, enabling higher doses of radiotherapy to primary cancer, involved lymph nodes and oligometastases with acceptable normal tissue toxicity. Despite this, many patients relapse following primary radical therapy, and novel treatment approaches are required. Metal nanoparticles are agents that promise to improve diagnostic imaging and image-guided radiotherapy and to selectively enhance radiotherapy effectiveness in CaP. We summarize current radiotherapy treatment approaches for CaP and consider pre-clinical and clinical evidence for metal nanoparticles in this condition.

Prostate cancer (CaP) is the most commonly diagnosed cancer in males and is responsible for more than 10,000 deaths each year in the UK.1 Technical advances in radiotherapy delivery, including image-guided intensity-modulated radiotherapy (IG-IMRT), have enabled the delivery of higher radiation dose to the prostate, which has led to improved biochemical control. Further improvements in cancer imaging during radiotherapy are being developed with the advent of MRI simulators and MRI linear accelerators.2–4

Nanotechnology promises to deliver significant advancements across numerous disciplines.5 The widest scope of applications are from the biomedical field including exogenous gene/drug delivery systems, advanced biosensors, targeted contrast agents for diagnostic applications and as direct therapeutic agents used in combination with existing treatment modalities.6–11 This diversity of application is especially evident within cancer research, with a myriad of experimental anticancer strategies currently under investigation.

This review will focus specifically on the potential of metal-based nanoparticles to augment the efficacy of radiotherapy in CaP, a disease where radiotherapy constitutes a major curative treatment modality.12 Furthermore, we will also address the clinical state of the art for CaP radiotherapy and consider how these treatments could be best combined with nanotherapeutics to improve cancer outcomes.