DNA damage and repair kinetics after microbeam radiation therapy emulation in living cells using monoenergetic synchrotron X-ray microbeams

The molecular response of mammalian cells to a monoenergetic synchrotron X-ray microbeam which emulated microbeam radiation configurations has been investigated. Very few γH2AX foci were found outside the irradiated zone within 1 h of irradiation, even within a single nucleus. Furthermore, 12 h after radiation there was a large decrease in foci number but many cells still contained γH2AX foci, of which many were outside the directly irradiated regions

In situ Biological Dose Mapping Estimates the Radiation Burden Delivered to ‘Spared’ Tissue between Synchrotron X-Ray Microbeam Radiotherapy Tracks

Microbeam radiation therapy (MRT) using high doses of synchrotron X-rays can destroy tumours in animal models whilst causing little damage to normal tissues. Determining the spatial distribution of radiation doses delivered during MRT at a microscopic scale is a major challenge. Film and semiconductor dosimetry as well as Monte Carlo methods struggle to provide accurate estimates of dose profiles and peak-to-valley dose ratios at the position of the targeted and traversed tissues whose biological responses determine treatment outcome. The purpose of this study was to utilise γ-H2AX immunostaining as a biodosimetric tool that enables in situ biological dose mapping within an irradiated tissue to provide direct biological evidence for the scale of the radiation burden to ‘spared’ tissue regions between MRT tracks. Γ-H2AX analysis allowed microbeams to be traced and DNA damage foci to be quantified in valleys between beams following MRT treatment of fibroblast cultures and murine skin where foci yields per unit dose were approximately five-fold lower than in fibroblast cultures. Foci levels in cells located in valleys were compared with calibration curves using known broadbeam synchrotron X-ray doses to generate spatial dose profiles and calculate peak-to-valley dose ratios of 30–40 for cell cultures and approximately 60 for murine skin, consistent with the range obtained with conventional dosimetry methods. This biological dose mapping approach could find several applications both in optimising MRT or other radiotherapeutic treatments and in estimating localised doses following accidental radiation exposure using skin punch biopsies

Functional Deficits in nNOSμ-Deficient Skeletal Muscle: Myopathy in nNOS Knockout Mice

Skeletal muscle nNOSμ (neuronal nitric oxide synthase mu) localizes to the sarcolemma through interaction with the dystrophin-associated glycoprotein (DAG) complex, where it synthesizes nitric oxide (NO). Disruption of the DAG complex occurs in dystrophinopathies and sarcoglycanopathies, two genetically distinct classes of muscular dystrophy characterized by progressive loss of muscle mass, muscle weakness and increased fatigability. DAG complex instability leads to mislocalization and downregulation of nNOSμ; but this is thought to play a minor role in disease pathogenesis. This view persists without knowledge of the role of nNOS in skeletal muscle contractile function in vivo and has influenced gene therapy approaches to dystrophinopathy, the majority of which do not restore sarcolemmal nNOSμ. We address this knowledge gap by evaluating skeletal muscle function in nNOS knockout (KN1) mice using an in situ approach, in which the muscle is maintained in its normal physiological environment. nNOS-deficiency caused reductions in skeletal muscle bulk and maximum tetanic force production in male mice only. Furthermore, nNOS-deficient muscles from both male and female mice exhibited increased susceptibility to contraction-induced fatigue. These data suggest that aberrant nNOSμ signaling can negatively impact three important clinical features of dystrophinopathies and sarcoglycanopathies: maintenance of muscle bulk, force generation and fatigability. Our study suggests that restoration of sarcolemmal nNOSμ expression in dystrophic muscles may be more important than previously appreciated and that it should be a feature of any fully effective gene therapy-based intervention

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Benchmarking and validation of a Geant4-SHADOW Monte Carlo simulation for dose calculations in microbeam radiation therapy

Microbeam radiation therapy (MRT) is a synchrotron-based radiotherapy modality that uses high-intensity beams of spatially fractionated radiation to treat tumours. The rapid evolution of MRT towards clinical trials demands accurate treatment planning systems (TPS), as well as independent tools for the verification of TPS calculated dose distributions in order to ensure patient safety and treatment efficacy. Monte Carlo computer simulation represents the most accurate method of dose calculation in patient geometries and is best suited for the purpose of TPS verification. A Monte Carlo model of the ID17 biomedical beamline at the European Synchrotron Radiation Facility has been developed, including recent modifications, using the Geant4 Monte Carlo toolkit interfaced with the SHADOW X-ray optics and ray-tracing libraries. The code was benchmarked by simulating dose profiles in water-equivalent phantoms subject to irradiation by broad-beam (without spatial fractionation) and microbeam (with spatial fractionation) fields, and comparing against those calculated with a previous model of the beamline developed using the PENELOPE code. Validation against additional experimental dose profiles in water-equivalent phantoms subject to broad-beam irradiation was also performed. Good agreement between codes was observed, with the exception of out-of-field doses and toward the field edge for larger field sizes. Microbeam results showed good agreement between both codes and experimental results within uncertainties. Results of the experimental validation showed agreement for different beamline configurations. The asymmetry in the out-of-field dose profiles due to polarization effects was also investigated, yielding important information for the treatment planning process in MRT. This work represents an important step in the development of a Monte Carlo-based independent verification tool for treatment planning in MRT