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Abstract Broadband Coherent anti-Stokes Raman (BCARS) microscopy is an imaging technique that can acquire full Raman spectra (400–3200 cm−1) of biological samples within a few milliseconds. However, the CARS signal suffers from an undesired non-resonant background (NRB), deriving from four-wave-mixing processes, which distorts the peak line shapes and reduces the chemical contrast. Traditionally, the NRB is removed using numerical algorithms that require expert users and knowledge of the NRB spectral profile. Recently, deep-learning models proved to be powerful tools for unsupervised automation and acceleration of NRB removal. Here, we thoroughly review the existing NRB removal deep-learning models (SpecNet, VECTOR, LSTM, Bi-LSTM) and present two novel architectures. The first one combines convolutional layers with Gated Recurrent Units (CNN + GRU); the second one is a Generative Adversarial Network (GAN) that trains an encoder-decoder network and an adversarial convolutional neural network. We also introduce an improved training dataset, generalized on different BCARS experimental configurations. We compare the performances of all these networks on test and experimental data, using them in the pipeline for spectral unmixing of BCARS images. Our analyses show that CNN + GRU and VECTOR are the networks giving the highest accuracy, GAN is the one that predicts the highest number of true positive peaks in experimental data, whereas GAN and VECTOR are the most suitable ones for real-time processing of BCARS images.

Abstract Background Radiation therapy (RT) for breast cancer (BC) can result in subtle cardiac dysfunction that can occur early after treatment. In 2022, the European Society of Cardiology (ESC) published the first guidelines in cardio-oncology with a harmonized definition of cancer therapy-related cardiac dysfunction (CTRCD). The aim of this study was to evaluate CTRCD occurrence over 24 months of follow-up after RT in BC patients and to analyze the association with cardiac radiation exposure. Methods The prospective monocentric BACCARAT study included BC patients treated with RT without chemotherapy, aged 40–75 years, with conventional and 2D Speckle tracking echocardiography performed before RT, 6 and 24 months after RT. Based on ESC cardio-oncology guidelines, CTRCD and corresponding severity were defined with left ventricle ejection fraction and global longitudinal strain decrease, occurring at 6 or 24 months after RT. Dosimetry for whole heart, left ventricle (LV) and left coronary artery (left anterior descending and circumflex arteries (CX)) was considered to evaluate the association with CTRCD, based on logistic regressions (Odds Ratio – OR and 95% confidence interval – 95%CI). Youden index based on receiver operating characteristic curve analysis was used to identify the optimal threshold of dose-volume parameters for predicting CTRCD. Results The study included 72 BC patients with a mean age of 58 ± 8.2 years. A total of 32 (44%) patients developed CTRCD during follow-up: 20 (28%) mild CTRCD, 7 (9%) moderate CTRCD, and 5 (7%) severe CTRCD. Cardiac radiation doses were generally higher among patients with CTRCD rather than non-CTRCD. Dose-response relationships were significant for mean CX dose (OR = 2.48, 95%CI (1.12–5.51), p = 0.02) and marginally significant for V2 of LV (OR = 1.03 95%CI (1.00-1.06), p = 0.05). V2 of LV ≥ 36% and mean CX dose ≥ 1.40 Gy thresholds were determined to be optimal for predicting CTRCD. Conclusion For BC patients treated with RT without chemotherapy, CTRCD can be observed in an important proportion of the population over 24 months after treatment. Left ventricle and circumflex coronary artery exposure were found to be associated with CTRCD and could be used for the prediction of such cardiotoxicity. Further research remains needed to confirm these results. Trial Registration ClinicalTrials.gov Identifier- NCT02605512.

Abstract Background In order to ensure adequate radiation protection of critical groups such as staff, caregivers and the general public coming into proximity of nuclear medicine (NM) patients, it is necessary to consider the impact of the radiation emitted by the patients during their stay at the hospital or after leaving the hospital. Current risk assessments are based on ambient dose rate measurements in a single position at a specified distance from the patient and carried out at several time points after administration of the radiopharmaceutical to estimate the whole-body retention. The limitations of such an approach are addressed in this study by developing and validating a more advanced computational dosimetry approach using Monte Carlo (MC) simulations in combination with flexible and realistic computational phantoms and time activity distribution curves from reference biokinetic models. Results Measurements of the ambient dose rate equivalent Ḣ * (10) at 1 m from the NM patient have been successfully compared against MC simulations with 5 different codes using the ICRP adult reference computational voxel phantoms, for typical clinical procedures with 99mTc-HDP/MDP, 18FDG and Na131I. All measurement data fall in the 95% confidence intervals, determined for the average simulated results. Moreover, the different MC codes (MCNP-X, PHITS, GATE, GEANT4, TRIPOLI-4®) have been compared for a more realistic scenario where the effective dose rate Ė of an exposed individual was determined in positions facing and aside the patient model at 30 cm, 50 cm and 100 cm. The variation between codes was lower than 8% for all the radiopharmaceuticals at 1 m, and varied from 5 to 16% for the face-to face and side-by-side configuration at 30 cm and 50 cm. A sensitivity study on the influence of patient model morphology demonstrated that the relative standard deviation of Ḣ * (10) at 1 m for the range of included patient models remained under 16% for time points up to 120 min post administration. Conclusions The validated computational approach will be further used for the evaluation of effective dose rates per unit administered activity for a variety of close-contact configurations and a range of radiopharmaceuticals as part of risk assessment studies. Together with the choice of appropriate dose constraints this would facilitate the setting of release criteria and patient restrictions.

Abstract We present a factorization theorem of the partonic Drell-Yan off-diagonal processes g q ¯ qg → γ ∗ + X $$ g\overline{q}(qg)\to {\gamma}^{\ast }+X $$ in the kinematic threshold regime z = Q 2 / s ̂ → 1 $$ z={Q}^2/\hat{s}\to 1 $$ at general subleading powers in the (1 − z) expansion. Focusing on the first order of the expansion (next-to-leading power accuracy with respect to the leading power q q ¯ $$ q\overline{q} $$ channel), we validate the bare factorization formula up to O α s 2 $$ \mathcal{O}\left({\alpha}_s^2\right) $$ . This is achieved by carrying out an explicit calculation of the generalized soft function in d-dimensions using the reduction to master integrals and the differential equations method. The collinear function is a universal object which we compute from an operator matching equation at one-loop level. Next, we integrate the soft and collinear functions over the convolution variables and remove the remaining initial state collinear singularities through PDF renormalization. The resulting expression agrees with the known cross section in the literature.

We extend the geneva Monte Carlo framework using the transverse momentum of a color-singlet system as the resolution variable. This allows us to use next-to-next-to-next-to-leading-logarithm (N3LL) resummation via the radish formalism to obtain precise predictions for any color-singlet production process at the fully exclusive level. Thanks to the implementation of two different resolution variables within the geneva framework, we are able to assess the impact of such a choice on differential observables for the first time. As a first application, we present predictions for Drell-Yan lepton-pair production at next-to-next-to-leading order (NNLO) in QCD interfaced to a parton shower simulation that includes additional all-order radiative corrections. We provide fully showered and hadronized events using pythia8, while retaining the NNLO QCD accuracy for observables which are inclusive over the additional radiation. We also show that it is possible to obtain a numerically good agreement between showered geneva predictions and the N3LL resummation for the transverse momentum spectrum by choosing a more local recoil scheme. We compare our final predictions to LHC data at 13 TeV, finding good agreement across several distributions.

Purpose The National Congenital Anomaly and Rare Disease Registration Service (NCARDRS), part of National Disease Registration Service in National Health Service England, quality assures, curates and analyses individual data on the pregnancies, fetuses, babies, children and adults with congenital anomalies and rare diseases across England. The congenital anomaly (CA) register provides a resource for patients and their families, clinicians, researchers and public health professionals in furthering the understanding of CAs.Participants NCARDRS registers CAs occurring in babies born alive and stillborn, fetal losses and terminations in England. NCARDRS collects data from secondary and tertiary healthcare providers, private providers and laboratories covering fetal medicine, maternity or paediatric services. Data describe the pregnancy, mother, baby and anomaly. Established in 2015, NCARDRS expanded CA registration coverage from 22% of total births in England in 2015 to national coverage, which was achieved in 2018. Prior to 2015, data collection was performed independently by regional registers in England; these data are also held by NCARDRS.Findings to date NCARDRS registers approximately 21 000 babies with CAs per year with surveillance covering around 600 000 total births, the largest birth coverage for a CA register globally. Data on prevalence, risk factors and survival for children with CAs are available. Data have been used in several peer-reviewed publications. Birth prevalence statistics, including public health indicators such as the association with maternal age, infant and perinatal mortality, are published annually. NCARDRS supports clinical audit for screening programmes and service evaluation.Future plans NCARDRS provides a valuable resource for the understanding of the epidemiology, surveillance, prevention and treatment of CAs. Currently, approximately 21 000 new registrations of babies or fetuses with suspected or confirmed CAs are added each year. Identifiers are collected, enabling linkage to routinely collected healthcare and population statistics, further enhancing the value of the data.

Abstract In this work, we study the production of Higgs boson pairs at next-to-next-to-leading order in QCD matched to parton showers, using the Geneva framework and working in the heavy-top-limit approximation. This includes the resummation of large logarithms of the zero-jettiness T $$ \mathcal{T} $$ 0 up to the next-to-next-to-next-to-leading-log accuracy. This process features an extremely large momentum transfer, which makes its study particularly relevant for matching schemes such as that employed in Geneva, where the resummation of a variable different from that used in the ordering of the parton shower is used. To further study this effect, we extend the original shower interface designed for Pythia8 to include other parton showers, such as Dire and Sherpa.

Abstract We describe a number of improvements to the Geneva method for matching NNLO calculations to parton shower programs. In particular, we detail changes to the resummed calculation used in the matching procedure, including disentangling the cross section dependence on factorisation and beam scales, and an improved treatment of timelike logarithms. We also discuss modifications in the implementation of the splitting functions which serve to make the resummed calculation differential in the higher multiplicity phase space. These changes improve the stability of the numerical cancellation of the nonsingular term at small values of the resolution parameter. As a case study, we consider the gluon-initiated Higgs boson production process gg → H. We validate the NNLO accuracy of our predictions against independent calculations, and compare our showered and hadronised results with recent data taken at the ATLAS and CMS experiments in the diphoton decay channel, finding good agreement.

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments.

AimThe aim of this study is to evaluate the incidence of SARS-CoV-2 infection and the prevalence of COVID-19-related symptoms in relation to pandemic phases and some relevant variables in a cohort of 8,029 HCWs from one of the largest Italian University Hospitals.MethodsA single-center retrospective study was performed on data collected during SARS-CoV-2 infection surveillance of HCWs. Cox’s multiple regression was performed to estimate hazard ratios of SARS-CoV-2 infection. Logistic multivariate regression was used to assess the risk of asymptomatic infections and the onset of the most frequent symptoms. All analyses were adjusted for sociodemographic and occupational factors, pandemic phases, vaccination status, and previous infections.ResultsA total of 3,760 HCWs resulted positive (2.0%–18.6% across five study phases). The total incidence rate of SARS-CoV-2 infection was 7.31 cases per 10,000 person-days, significantly lower in phase 1 and higher in phases 4 and 5, compared to phase 3. Younger HCWs, healthcare personnel, and unvaccinated subjects showed a higher risk of infection. Overall, 24.5% were asymptomatic infections, with a higher probability for men, physicians, and HCWs tested for screening, fully vaccinated, and those with previous infection. The clinical presentation changed over the phases in relation to vaccination status and the emergence of new variants.ConclusionThe screening activities of HCWs allowed for the early detection of asymptomatic cases, limiting the epidemic clusters inside the hospital wards. SARS-CoV-2 vaccination reduced infections and symptomatic cases, demonstrating again its paramount value as a preventive tool for occupational and public health.

Abstract We present the first calculation of the complete set of NNLO QED corrections for muon-electron scattering. This includes leptonic, non-perturbative hadronic, and photonic contributions. All fermionic corrections as well as the photonic subset that only corrects the electron or the muon line are included with full mass dependence. The genuine four-point two-loop topologies are computed as an expansion in the small electron mass, taking into account both, logarithmically enhanced as well as constant mass effects using massification. A fast and stable implementation of the numerically delicate real-virtual contribution is achieved by combining OpenLoops with next-to-soft stabilisation. All matrix elements are implemented in the McMule framework, which allows for the fully-differential calculation of any infrared-safe observable. This calculation is to be viewed in the context of the MUonE experiment requiring a background prediction at the level of 10 ppm. Our results thus represent a major milestone towards this ambitious precision goal.

Purpose: To assess sinoatrial node (SAN) and atrioventricular node (AVN) doses for breast cancer (BC) patients treated with 3D-CRT and evaluate whether “large” cardiac structures (whole heart and four cardiac chambers) would be relevant surrogates. Material and methods: This single center study was based on 116 BCE patients (56 left-sided, 60 right-sided) treated with 3D-CRT without respiratory gating strategies and few IMN irradiations from 2009 to 2013. The heart, the left and right ventricles (LV, RV), the left and right atria (LA, RA) were contoured using multi-atlases for auto-segmentation. The SAN and the AVN were manually delineated using a specific atlas. Based on regression analysis, the coefficients of determination (R2) were estimated to evaluate whether “large” cardiac structures were relevant surrogates (R2 > 0.70) of SAN and AVN doses. Results: For left-sided BC, mean doses were: 3.60 ± 2.28 Gy for heart, 0.47 ± 0.24 Gy for SAN and 0.74 ± 0.29 Gy for AVN. For right-sided BC, mean heart dose was 0.60 ± 0.25 Gy, mean SAN dose was 1.57 ± 0.63 Gy (>85 % of patients with SAN doses > 1 Gy) and mean AVN dose was 0.51 ± 0.14 Gy. Among all “large” cardiac structures, RA appeared as the best surrogate for SAN doses (R2 > 0.80). Regarding AVN doses, the RA may also be an interesting surrogate for left-sided BC (R2 = 0.78), but none of “large” cardiac structures appeared as relevant surrogates among right-sided BC (all R2

Objectives To explore the effect of changes in national clinical recommendations in 2019 that extended provision of survival focused care to babies born at 22 weeks’ gestation in England and Wales.Design Population based cohort study.Setting England and Wales, comprising routine data for births and hospital records.Participants Babies alive at the onset of care in labour at 22 weeks+0 days to 22 weeks+6 days and at 23 weeks+0 days to 24 weeks+6 days for comparison purposes between 1 January 2018 and 31 December 2021.Main outcome measures Percentage of babies given survival focused care (active respiratory support after birth), admitted to neonatal care, and surviving to discharge in 2018-19 and 2020-21.Results For the 1001 babies alive at the onset of labour at 22 weeks' gestation, a threefold increase was noted in: survival focused care provision from 11.3% to 38.4% (risk ratio 3.41 (95% confidence interval 2.61 to 4.45)); admissions to neonatal units from 7.4% to 28.1% (3.77 (2.70 to 5.27)), and survival to discharge from neonatal care from 2.5% to 8.2% (3.29 (1.78 to 6.09)). More babies of lower birth weight and early gestational age received survival focused care in 2020-21 than 2018-19 (46% to 64% at

The Brazilian Atlantic Forest (AF) covers 13% of Brazil but retains only 26% of its original forest area. Utilizing a Morphological Spatial Pattern Analysis (MSPA), we generated 30 m spatial resolution fragmentation maps for old-growth and secondary forests across the AF. We quantified landscape fragmentation patterns and carbon (C) dynamics over 35 years using MapBiomas data between the years 1985 and 2020. We found that from 1985 to 2020 the forest suffered continuous fragmentation, losing core (nuclei forest fragments) and bridge (areas that connect different core areas) components of the landscape. About 87.5% (290 468.4 km ^2 ) of the remaining forest lacked core areas, with bridges (38.0%) and islets (small, isolated fragments) (35.4%) being predominant. Secondary forests (1986–2020) accounted for 99 450.5 km ^2 and played a significant role in fragmentation pattern, constituting 44.9% of the areas affected by edge effects (perforation, edge, bridge, and loop), 53.7% of islets, and comprising only 1.4% of core forest. Additionally, regeneration by secondary forests contributed to all fragmentation classes in 2020. Even with the regrowth of forests, the total forested area in the biome did not increase between 1985 and 2020. Deforestation emissions reached 818 Tg CO _2 , closely paralleled by edge effects emissions at 810 Tg CO _2 , highlighting a remarkable parity in C emissions between the two processes. Despite slow changes, AF biome continues to lose its C stocks. We estimated that around 1.96 million hectares (19 600 km ^2 ) of regenerated forest would be required to offset the historical C emissions over the analysed period. Hence, MSPA can support landscape monitoring, optimizing natural or active forest regeneration to reduce fragmentation and enhance C stocks. Our study’s findings are critical for guiding land-use policies focusing on minimizing emissions, promoting forest regrowth, and monitoring its permanence. This study offers biome scale, spatially explicit information, critical for AF conservation and management.