Quantum electrodynamics in modern optics and photonics: tutorial

One of the key frameworks for developing the theory of light–matter interactions in modern optics and photonics is quantum electrodynamics (QED). Contrasting with semiclassical theory, which depicts electromagnetic radiation as a classical wave, QED representations of quantized light fully embrace the concept of the photon. This tutorial review is a broad guide to cutting-edge applications of QED, providing an outline of its underlying foundation and an examination of its role in photon science. Alongside the full quantum methods, it is shown how significant distinctions can be drawn when compared to semiclassical approaches. Clear advantages in outcome arise in the predictive capacity and physical insights afforded by QED methods, which favors its adoption over other formulations of radiation–matter interaction

Raman Spectroscopy of Lymphocytes for the Identification of Prostate Cancer Patients with Late Radiation Toxicity Following Radiotherapy

The success of radiotherapy in tumour control depends on the total dose given. However, the tolerance of the normal tissues surrounding the tumour limits this dose. It is not known why some patients develop radiation toxicity and, currently, it is not possible to predict before treatment which patients will experience adverse effects. Thus, there is an unmet clinical need for a new test to identify patients at risk of radiation toxicity. Here, we report a new approach based on Raman spectroscopy.Blood samples were collected from 42 patients who had undergone radiotherapy for prostate cancer and had shown either severe or no/minimal late radiation toxicity in follow up. Radiation response was assessed following in vitro irradiation using Raman spectroscopy in addition to the G2 chromosomal radiosensitivity assay and the H2AX DNA damage assay.A Partial Least Squares Discriminant Analysis model was developed to classify patients using known radiation toxicity scores. A sensitivity of 95%, specificity of 92% and overall accuracy of 93% was achieved. In the future, this technology may have potential to lead to individualised patient radiotherapy by identifying which patients are at risk of radiation toxicity

Vibrational Spectroscopy of Liquid Biopsies for Prostate Cancer Diagnosis

Background: Screening for prostate cancer with prostate specific antigen and digital rectal examination allows early diagnosis of prostate malignancy but has been associated with poor sensitivity and specificity. There is also a considerable risk of over-diagnosis and overtreatment, which highlights the need for better tools for diagnosis of prostate cancer. This study investigates the potential of high throughput Raman and Fourier Transform Infrared (FTIR) spectroscopy of liquid biopsies for rapid and accurate diagnosis of prostate cancer. Methods: Blood samples (plasma and lymphocytes) were obtained from healthy control subjects and prostate cancer patients. FTIR and Raman spectra were recorded from plasma samples, while Raman spectra were recorded from the lymphocytes. The acquired spectral data was analysed with various multivariate statistical methods, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and classical least squares (CLS) fitting analysis. Results: Discrimination was observed between the infrared and Raman spectra of plasma and lymphocytes from healthy donors and prostate cancer patients using PCA. In addition, plasma and lymphocytes displayed differentiating signatures in patients exhibiting different Gleason scores. A PLS-DA model was able to discriminate these groups with sensitivity and specificity rates ranging from 90% to 99%. CLS fitting analysis identified key analytes that are involved in the development and progression of prostate cancer. Conclusions: This technology may have potential as an alternative first stage diagnostic triage for prostate cancer. This technology can be easily adaptable to many other bodily fluids and could be useful for translation of liquid biopsy-based diagnostics into the clinic

Effect of hemolysis on Fourier transform infrared and Raman spectra of blood plasma

Hemolysis is a very common phenomenon and is referred as the release of intracellular components from red blood cells to the extracellular fluid. Hemolyzed samples are often rejected in clinics due to the interference of hemoglobin and intracellular components in laboratory measurements. Plasma and serum based vibrational spectroscopy studies are extensively applied to generate spectral biomarkers for various diseases. However, no studies have reported the effect of hemolysis in blood based vibrational spectroscopy studies. This study was undertaken to evaluate the effect of hemolysis on infrared and Raman spectra of blood plasma. In this study, prostate cancer plasma samples (n = 30) were divided into three groups (nonhemolyzed, mildly hemolyzed, and moderately hemolyzed) based on the degree of hemolysis and FTIR and Raman spectra were recorded using high throughput (HT)-FTIR and HT-Raman spectroscopy. Discrimination was observed between the infrared and Raman spectra of nonhemolyzed and hemolyzed plasma samples using principal component analysis. A classical least square fitting analysis showed differences in the weighting of pure components in nonhemolyzed and hemolyzed plasma samples. Therefore, it is worth to consider the changes in spectral features due to hemolysis when comparing the results within and between experiments

Prediction of DNA Damage and G2 Chromosomal Radio-Sensitivity Ex-vivo in Peripheral Blood Mononuclear Cells with Label-Free Raman Microspectroscopy

Liquid biopsies are a potentially rich store of biochemical information that can be linked to an individual’s response to therapeutic treatments, including radiotherapy, and which may ultimately play a role in the individualization of treatment regimens. Peripheral blood mononuclear cells (PBMCs) can be used for the biochemical profiling of the individual, but also, being living cells, can provide insights into the individuals response to ionizing radiation exposure

The transition from the adiabatic to the sudden limit in core level photoemission: A model study of a localized system

We consider core electron photoemission in a localized system, where there is a charge transfer excitation. The system is modelled by three electron levels, one core level and two outer levels. The model has a Coulomb interaction between these levels and the continuum states into which the core electron is emitted. The model is simple enough to allow an exact numerical solution, and with a separable potential an analytic solution. We calculate the ratio r(omega) between the weights of the satellite and the main peak as a function of the photon energy omega. The transition from the adiabatic to the sudden limit takes place for quite small photoelectron kinetic energies. For such small energies, the variation of the dipole matrix element is substantial and described by the energy scale Ed. Without the coupling to the photoelectron, the corresponding ratio r0(omega) is determined by Ed and the satellite excitation energy dE. When the interaction potential with the continuum states is introduced, a new energy scale Es=1/(2Rs^2) enters, where Rs is a length scale of the interaction potential. At threshold there is typically a (weak) constructive interference between intrinsic and extrinsic contributions, and the ratio r(omega)/r0(omega) is larger than its limiting value for large omega. The interference becomes small or weakly destructive for photoelectron energies of the order Es. For larger energies r(omega)/r0(omega) therefore typically has a weak undershoot. If this undershoot is neglected, r(omega)/r0(omega) reaches its limiting value on the energy scale Es.Comment: 18 pages, latex2e, 13 eps figure

A Dynamic Model of Interactions of Ca^(2+), Calmodulin, and Catalytic Subunits of Ca^(2+)/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca^(2+) into the postsynaptic spine through the pores of activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca^(2+) influx during the first few seconds of activity is interpreted within the Ca^(2+)-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca^(2+) ions. As a first step toward clarifying how the Ca^(2+)-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca^(2+), calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca^(2+) play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing ofCa^(2+) signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca^(2+) is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca^(2+) transients arises from the kinetics of interaction of fluctuating Ca^(2+) with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning

Tumour risks and genotype-phenotype correlations associated with germline variants in succinate dehydrogenase subunit genes SDHB, SDHC and SDHD.

BACKGROUND: Germline pathogenic variants in SDHB/SDHC/SDHD are the most frequent causes of inherited phaeochromocytomas/paragangliomas. Insufficient information regarding penetrance and phenotypic variability hinders optimum management of mutation carriers. We estimate penetrance for symptomatic tumours and elucidate genotype-phenotype correlations in a large cohort of SDHB/SDHC/SDHD mutation carriers. METHODS: A retrospective survey of 1832 individuals referred for genetic testing due to a personal or family history of phaeochromocytoma/paraganglioma. 876 patients (401 previously reported) had a germline mutation in SDHB/SDHC/SDHD (n=673/43/160). Tumour risks were correlated with in silico structural prediction analyses. RESULTS: Tumour risks analysis provided novel penetrance estimates and genotype-phenotype correlations. In addition to tumour type susceptibility differences for individual genes, we confirmed that the SDHD:p.Pro81Leu mutation has a distinct phenotype and identified increased age-related tumour risks with highly destabilising SDHB missense mutations. By Kaplan-Meier analysis, the penetrance (cumulative risk of clinically apparent tumours) in SDHB and (paternally inherited) SDHD mutation-positive non-probands (n=371/67 with detailed clinical information) by age 60 years was 21.8% (95% CI 15.2% to 27.9%) and 43.2% (95% CI 25.4% to 56.7%), respectively. Risk of malignant disease at age 60 years in non-proband SDHB mutation carriers was 4.2%(95% CI 1.1% to 7.2%). With retrospective cohort analysis to adjust for ascertainment, cumulative tumour risks for SDHB mutation carriers at ages 60 years and 80 years were 23.9% (95% CI 20.9% to 27.4%) and 30.6% (95% CI 26.8% to 34.7%). CONCLUSIONS: Overall risks of clinically apparent tumours for SDHB mutation carriers are substantially lower than initially estimated and will improve counselling of affected families. Specific genotype-tumour risk associations provides a basis for novel investigative strategies into succinate dehydrogenase-related mechanisms of tumourigenesis and the development of personalised management for SDHB/SDHC/SDHD mutation carriers

Developing a Collaboration with the Houston Independent School District: Testing the Generalizability of a Partnership Model

Moving evidence-based practices into real-world settings is a high priority for education and public health. This paper describes the development of a partnership among the Houston Independent School District, the American Institutes of Research, and the Houston Federation of Teachers to support research on and program sustainability for the Good Behavior Game, a team-based classroom behavior management strategy that has shown positive impact in randomized field trials. The conceptual framework guiding partnership development is presented, followed by an application of the framework in Houston. Lessons learned and implications for the next stage of research and practice are then discussed

From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" worksho