Algorithm and performance of a clinical IMRT beam-angle optimization system

This paper describes the algorithm and examines the performance of an IMRT beam-angle optimization (BAO) system. In this algorithm successive sets of beam angles are selected from a set of predefined directions using a fast simulated annealing (FSA) algorithm. An IMRT beam-profile optimization is performed on each generated set of beams. The IMRT optimization is accelerated by using a fast dose calculation method that utilizes a precomputed dose kernel. A compact kernel is constructed for each of the predefined beams prior to starting the FSA algorithm. The IMRT optimizations during the BAO are then performed using these kernels in a fast dose calculation engine. This technique allows the IMRT optimization to be performed more than two orders of magnitude faster than a similar optimization that uses a convolution dose calculation engine.Comment: Final version that appeared in Phys. Med. Biol. 48 (2003) 3191-3212. Original EPS figures have been converted to PNG files due to size limi

On Component Forces in Physics: A Pragmatic View

Do component forces exist? I argue that the answer lies in the affirmative, on historical and operational grounds

Vibrational Biospectroscopy in the Clinical Setting: Exploring the Impact of New Advances in the Field of Immunology

The investigation of pathological diseases largely relies on laboratory examinations. The ability to identify and characterise cells is an essential process for clinicians to reach an accurate diagnosis and inform appropriate treatments. There is currently a gap between the advancement of scientific knowledge on cellular and molecular pathways and the development of novel techniques capable of detecting subtle cellular changes associated with disease. Biospectroscopy is the use of spectroscopy techniques to investigate biological materials. Within a biological sample, important molecules such as lipids, carbohydrates, nucleic acids, and proteins are held together by chemical bonds; these bonds will vibrate following excitation with infrared light. By measuring the vibrational energy of each molecule present in a biological sample, a unique spectrum, known as the “molecular fingerprint” is generated. As disease-related changes in biological samples will be reflected in the molecular fingerprint, biospectroscopy is a well-placed candidate for the investigation of disease. Biospectroscopy has been gaining wider acceptance and application in the clinical setting over the past decade; however, it has yet to reach diagnostic laboratories and healthcare clinics as a routine platform for clinical assessment. Immunological disorders are complex, often demonstrating interaction across multiple molecular pathways which results in delayed diagnosis. Vibrational spectroscopy is being applied in many fields, and here we present a review of its use in cellular immunology. Potential benefits, including an enhanced definition of molecular processes and the use of spectroscopy in disease diagnosis, monitoring, and treatment response, are discussed. The translation of vibrational spectroscopic techniques into clinical practice offers rapid, noninvasive, and inexpensive methods to obtain information on the molecular composition of biological samples. The potential clinical benefits of biospectroscopy include providing a more prompt and accurate disease diagnosis, thus improving patient care and resulting in better health outcomes

Does Scientific Progress Consist in Increasing Knowledge or Understanding?

Bird argues that scientific progress consists in increasing knowledge. Dellsén objects that increasing knowledge is neither necessary nor sufficient for scientific progress, and argues that scientific progress rather consists in increasing understanding. Dellsén also contends that unlike Bird’s view, his view can account for the scientific practices of using idealizations and of choosing simple theories over complex ones. I argue that Dellsén’s criticisms against Bird’s view fail, and that increasing understanding cannot account for scientific progress, if acceptance, as opposed to belief, is required for scientific understanding

Classification of Systemic Lupus Erythematosus Using Raman Spectroscopy of Blood and Automated Computational Detection Methods: A Novel Tool for Future Diagnostic Testing

The aim of this study was to explore the proof of concept for using Raman spectroscopy as a diagnostic platform in the setting of systemic lupus erythematosus (SLE). We sought to identify unique Raman signatures in serum blood samples to successfully segregate SLE patients from healthy controls (HC). In addition, a retrospective audit was undertaken to assess the clinical utility of current testing platforms used to detect anti-double stranded DNA (dsDNA) antibodies (n = 600). We examined 234 Raman spectra to investigate key variances between SLE patients (n = 8) and HC (n = 4). Multi-variant analysis and classification model construction was achieved using principal component analysis (PCA), PCA-linear discriminant analysis and partial least squares-discriminant analysis (PLS-DA). We achieved the successful segregation of Raman spectra from SLE patients and healthy controls (p-value < 0.0001). Classification models built using PLS-DA demonstrated outstanding performance characteristics with 99% accuracy, 100% sensitivity and 99% specificity. Twelve statistically significant (p-value < 0.001) wavenumbers were identified as potential diagnostic spectral markers. Molecular assignments related to proteins and DNA demonstrated significant Raman intensity changes between SLE and HC groups. These wavenumbers may serve as future biomarkers and offer further insight into the pathogenesis of SLE. Our audit confirmed previously reported inconsistencies between two key methodologies used to detect anti-dsDNA, highlighting the need for improved laboratory testing for SLE. Raman spectroscopy has demonstrated powerful performance characteristics in this proof-of-concept study, setting the foundations for future translation into the clinical setting

Component-resolved diagnostics in the clinical and laboratory investigation of allergy

The diagnosis and management of allergy is complex; the clinical symptoms associated with allergic reactions span a broad spectrum of severity, from mild hay fever-type symptoms through to life-threatening anaphylaxis. Obtaining an allergy-focused clinical history is therefore vital for identifying possible allergic triggers and directing testing. However, this focus could be changing as scientific and technological advances have paved the way for developments within in vitro testing for allergy. With knowledge of allergens at the molecular level expanding, there are now the facilities to characterize the sensitization profiles of allergy sufferers and determine the specific molecules (or components) against which the allergen-inducing immunoglobulin type E proteins have been produced. This technology is termed component-resolved diagnostics. We know that accurate identification of immunoglobulin type E specificity, the source of the causative allergen, and knowledge of potential allergic cross-reactivities are required for optimal clinical management of allergy patients. These factors can make allergy a diagnostic challenge outside of a specialist centre, and contribute to the difficulties associated with requesting and interpreting allergy tests. The incorporation of component-resolved diagnostics into current practice has provided a platform for patient-tailored risk stratification and improved the application of allergen-specific immunotherapy, revolutionizing specialist management of these patients. This review discusses the roles of each type of testing in allergy management and predictions for future pathway

Investigation of Long-Term CD4+ T Cell Receptor Repertoire Changes Following SARS-CoV-2 Infection in Patients with Different Severities of Disease

Background: The difference in the immune response to severe acute respiratory syndrome coro-navirus 2 (SARS-CoV-2) in patients with mild versus severe disease remains poorly understood. Recent scientific advances have recognised the vital role of both B cells and T cells; however, many questions remain unanswered, particularly for T cell responses. T cells are essential for helping the generation of SARS-CoV-2 antibody responses but have also been recognised in their own right as a major factor influencing COVID-19 disease outcomes. The examination of T cell receptor (TCR) family differences over a 12-month period in patients with varying COVID-19 disease severity is crucial for understanding T cell responses to SARS-CoV-2. Methods: We applied a machine learning approach to analyse TCR vb family responses in COVID-19 patients (n = 151) across multiple timepoints and disease severities alongside SARS-CoV-2 infection-naïve (healthy control) individ-uals (n = 62). Results: Blood samples from hospital in-patients with moderate, severe, or critical disease could be classified with an accuracy of 94%. Furthermore, we identified significant variances in TCR vb family specificities between disease and control subgroups. Conclusions: Our findings suggest advantageous and disadvantageous TCR repertoire patterns in relation to disease severity. Following validation in larger cohorts, our methodology may be useful in detecting protective immunity and the assessment of long-term outcomes, particularly as we begin to unravel the immunological mechanisms leading to post-COVID complications

Chemistry of o-Xylidene-Metal Complexes. Part 3.&apos; Tungsten o-Xylidene Complexes derived from Tetrachloro(oxo)tungsten(vl) ; X-Ray Crystal Structures of [~( C H 2 C 6 H 4~H z -o )~]~~.~~~~6 and [{~(CH2C,H4CH2=~)20}2~g(C4H*0)41*

Reaction of WCI4O with the di-Grignard reagent O-C&amp;(CH2MgC1)2 or the chloride-free &apos; o-xylidene &apos; complex Mg(CH2C6H4CH2-o) (thf) in tetrahydrofuran (thf) yields either the thermally stable tris(chelate), [We use the umbrella term &apos; o-xylidenemetal complex &apos; to describe, without prejudice as to bonding, all O-C~I&amp;(CH~)~-metal complexes in which the organic ligand binds in (a) a bridging mode, as i

Treatment Outcomes of Anti-Neutrophil Cytoplasmic Autoantibody-Associated Vasculitis in Patients Over Age 75 Years: A Meta-Analysis

Background: The benefits of treating anti-neutrophil cytoplasmic autoantibody-associated vasculitis (AAV) in advancing age remains unclear with most published studies defining elderly as ≥65 years. This study aims to determine outcomes of induction immunosuppression in patients aged ≥75 years. Methods: A cohort of patients aged ≥75 years with a diagnosis of AAV between 2006 and 2018 was constructed from 2 centres. Follow-up was to 2 years or death. Analysis included multivariable Cox regression to compare mortality and end-stage renal disease (ESRD) based on receipt of induction immunosuppression therapy with either cyclophosphamide or rituximab. A systematic review of outcome studies was subsequently undertaken amongst this patient group through Pubmed, Cochrane and Embase databases from inception until October 16, 2019. Results: Sixty-seven patients were identified. Mean age was 79 ± 2.9 years and 82% (n = 55) received induction immunosuppression. Following systematic review, 4 studies were eligible for inclusion, yielding a combined total of 290 patients inclusive of our cohort. The aggregated 1-year mortality irrespective of treatment was 31% (95% CI 25–36%). Within our cohort, induction immunosuppression therapy was associated with a significantly lower 2-year mortality risk (hazard ratio [HR] 0.29 [95% CI 0.09–0.93]). The pooled HR by meta-analysis confirmed this with a significant risk reduction for death (HR 0.31 [95% CI 0.16–0.57], I2 = 0%). Treated patients had a lower pooled rate of ESRD, but was not statistically significant (HR 0.71 [95% CI 0.15–3.35]). Conclusion: This meta-analysis suggests that patients ≥75 years with AAV do benefit from induction immunosuppression with a significant survival benefit. Age alone should not be a limiting factor when considering treatment