Bayesian variable selection and survival modeling: assessing the Most important comorbidities that impact lung and colorectal cancer survival in Spain

ancer survival represents one of the main indicators of interest in cancer epidemiology. However, the survival of cancer patients can be affected by several factors, such as comorbidities, that may interact with the cancer biology. Moreover, it is interesting to understand how different cancer sites and tumour stages are affected by different comorbidities. Identifying the comorbidities that affect cancer survival is thus of interest as it can be used to identify factors driving the survival of cancer patients. This information can also be used to identify vulnerable groups of patients with comorbidities that may lead to worst prognosis of cancer. We address these questions and propose a principled selection and evaluation of the effect of comorbidities on the overall survival of cancer patients. In the first step, we apply a Bayesian variable selection method that can be used to identify the comorbidities that predict overall survival. In the second step, we build a general Bayesian survival model that accounts for time-varying effects. In the third step, we derive several posterior predictive measures to quantify the effect of individual comorbidities on the population overall survival. We present applications to data on lung and colorectal cancers from two Spanish population-based cancer registries. The proposed methodology is implemented with a combination of the R-packages mombf and rstan. We provide the code for reproducibility at https://github.com/migariane/BayesVarImpComorbiCancer

The effects of fear of COVID-19 among Spanish healthcare professionals in three years after the pandemic onset via validation of the FCV-19S: a prospective study

Despite being validated in different populations to assess fear of COVID-19, the Fear of COVID-19 Scale (FCV-19S) has scatter validations in healthcare professionals, often with several limitations, especially in Spanish-speaking professionals. Our research aims to extend previous studies by: (i) using a large sample of Spanish nurses and physicians; (ii) incorporating longitudinal data; and (iii) using a covariance-based SEM methodology to test different factor structures. 686 Spanish healthcare professionals (M = 42.7 years; 80.5% women; 76.7% nurses) participated in 2021 (Time 1), of whom, 216 were reassessed one year later (Time 2). The results (S-Bχ2 = 69.134, df = 13, p < 0.001, CFI = 0.974, and SRMR ≤ 0.031) supported a two-factor structure with a factor of somatic reactions and another of emotional expressions of fear of COVID-19. The FCV-19S evidenced strong factorial measurement invariance regarding gender, professional category, age and professional experience and also showed significantly higher levels of fear of COVID-19 in women, nurses, and professionals under 40 years old. The internal consistency was high for the somatic factor (ω = 0.86; α = 0.85), the emotional factor (ω = 0.82; α = 0.82) and the overall scale (α = 0.89). The scale showed good convergent, divergent, and incremental validity with respect to psychological symptomatology, perceived health, burnout, and worry about contagion. Finally, the FCV-19S showed criterion validity regarding generalized anxiety disorder, burnout, and the risk of leaving the profession. The FCV-19S evidenced excellent psychometric properties in Spanish healthcare professionals and was predictive of different health outcomes one year after administration. Study implications and limitations are also discussed

Electrostatic Tuning of the Ligand Binding Mechanism by Glu27 in Nitrophorin 7.

Nitrophorins (NP) 1-7 are NO-carrying heme proteins found in the saliva of the blood-sucking insect Rhodnius prolixus. The isoform NP7 displays peculiar properties, such as an abnormally high isoelectric point, the ability to bind negatively charged membranes, and a strong pH sensitivity of NO affinity. A unique trait of NP7 is the presence of Glu in position 27, which is occupied by Val in other NPs. Glu27 appears to be important for tuning the heme properties, but its influence on the pH-dependent NO release mechanism, which is assisted by a conformational change in the AB loop, remains unexplored. Here, in order to gain insight into the functional role of Glu27, we examine the effect of Glu27 → Val and Glu27 → Gln mutations on the ligand binding kinetics using CO as a model. The results reveal that annihilation of the negative charge of Glu27 upon mutation reduces the pH sensitivity of the ligand binding rate, a process that in turn depends on the ionization of Asp32. We propose that Glu27 exerts a through-space electrostatic action on Asp32, which shifts the pKa of the latter amino acid towards more acidic values thus reducing the pH sensitivity of the transition between open and closed states

Estudio de la botica de la Alhambra en el siglo XVI

Stock inventories are a very useful source of information in the study of the history of pharmaceutical science. Thisarticle reports on two accounts from the XVI century related to this subject, which on analysis provide interestingand relevant information on the functioning of a pharmacy in the citadel of the Alhambra Palace in Granada,during the early modern age.Los inventarios que recogen las existencias de las boticas son documentos de gran interés para la Historia de laFarmacia. Se informa en este artículo del hallazgo de dos relaciones de este tipo, fechadas en el siglo XVI, cuyoanálisis ofrece interesantes datos sobre la botica de la Alhambra de Granada en la Edad Moderna

Summarizing and communicating on survival data according to the audience: a tutorial on different measures illustrated with population-based cancer registry data

Aur&eacute;lien Belot, Aminata Ndiaye, Miguel-Angel Luque-Fernandez, Dimitra-Kleio Kipourou, Camille Maringe, Francisco Javier Rubio, Bernard Rachet Cancer Survival Group, Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK Abstract: Survival data analysis results are usually communicated through the overall survival probability. Alternative measures provide additional insights and may help in communicating the results to a wider audience. We describe these alternative measures in two data settings, the overall survival setting and the relative survival setting, the latter corresponding to the particular competing risk setting in which the cause of death is unavailable or unreliable. In the overall survival setting, we describe the overall survival probability, the conditional survival probability and the restricted mean survival time (restricted to a prespecified time window). In the relative survival setting, we describe the net survival probability, the conditional net survival probability, the restricted mean net survival time, the crude probability of death due to each cause and the number of life years lost due to each cause over a prespecified time window. These measures describe survival data either on a probability scale or on a timescale. The clinical or population health purpose of each measure is detailed, and their advantages and drawbacks are discussed. We then illustrate their use analyzing England population-based registry data of men 15&ndash;80&nbsp;years old diagnosed with colon cancer in 2001&ndash;2003, aiming to describe the deprivation disparities in survival. We believe that both the provision of a detailed example of the interpretation of each measure and the software implementation will help in generalizing their use. Keywords: survival, competing risks, relative survival setting, conditional survival, restricted mean survival time, net survival, crude probability of death, number of life years los

NFV Orchestration over Disaggregated Metro Optical Networks with End-to-End Multi-Layer Slicing enabling Crowdsourced Live Video Streaming

Network infrastructure must support emerging applications, fulfill 5G requirements, and respond to the sudden increase of societal need for remote communications. Remarkably, crowdsourced live video streaming (CLVS) challenges operators' infrastructure with tides of users attending major sport or public events that demand high bandwidth and low latency jointly with computing capabilities at the networks' edge. The Metro-Haul project entered the scene proposing a cost-effective, agile, and disaggregated infrastructure for the metro segment encompassing optical and packet resources jointly with computing capabilities. Recently, a major Metro-Haul outcome took the form of a field trial of network function virtualization (NFV) orchestration over the multi-layer packet and disaggregated optical network testbed that demonstrated a CLVS use case. We showcased the average service creation time below 5 min, which met the key performance indicator as defined by the 5G infrastructure public private partnership. In this paper, we expand our field trial demonstration with a detailed view of the Metro-Haul testbed for the CLVS use case, the employed components, and their performance. The throughput of the service is increased from approximately 9.6 Gbps up to 35 Gbps per virtual local area network with high-performance VNFs based on single-root input/output virtualization technology

Markov Influence Diagrams.

Markov influence diagrams (MIDs) are a new type of probabilistic graphical model that extends influence diagrams in the same way that Markov decision trees extend decision trees. They have been designed to build state-transition models, mainly in medicine, and perform cost-effectiveness analyses. Using a causal graph that may contain several variables per cycle, MIDs can model various patient characteristics without multiplying the number of states; in particular, they can represent the history of the patient without using tunnel states. OpenMarkov, an open-source tool, allows the decision analyst to build and evaluate MIDs-including cost-effectiveness analysis and several types of deterministic and probabilistic sensitivity analysis-with a graphical user interface, without writing any code. This way, MIDs can be used to easily build and evaluate complex models whose implementation as spreadsheets or decision trees would be cumbersome or unfeasible in practice. Furthermore, many problems that previously required discrete event simulation can be solved with MIDs; i.e., within the paradigm of state-transition models, in which many health economists feel more comfortable

Demonstration of the event identification capabilities of the NEXT-White detector

In experiments searching for neutrinoless double-beta decay, the possibility of identifying the two emitted electrons is a powerful tool in rejecting background events and therefore improving the overall sensitivity of the experiment. In this paper we present the first measurement of the efficiency of a cut based on the different event signatures of double and single electron tracks, using the data of the NEXT-White detector, the first detector of the NEXT experiment operating underground. Using a 228Th calibration source to produce signal-like and background-like events with energies near 1.6 MeV, a signal efficiency of 71.6 ± 1.5 stat± 0.3 sys% for a background acceptance of 20.6 ± 0.4 stat± 0.3 sys% is found, in good agreement with Monte Carlo simulations. An extrapolation to the energy region of the neutrinoless double beta decay by means of Monte Carlo simulations is also carried out, and the results obtained show an improvement in background rejection over those obtained at lower energies. [Figure not available: see fulltext.

Radiogenic backgrounds in the NEXT double beta decay experiment

Natural radioactivity represents one of the main backgrounds in the search for neutrinoless double beta decay. Within the NEXT physics program, the radioactivity- induced backgrounds are measured with the NEXT-White detector. Data from 37.9 days of low-background operations at the Laboratorio Subterráneo de Canfranc with xenon depleted in 136Xe are analyzed to derive a total background rate of (0.84±0.02) mHz above 1000 keV. The comparison of data samples with and without the use of the radon abatement system demonstrates that the contribution of airborne-Rn is negligible. A radiogenic background model is built upon the extensive radiopurity screening campaign conducted by the NEXT collaboration. A spectral fit to this model yields the specific contributions of 60Co, 40K, 214Bi and 208Tl to the total background rate, as well as their location in the detector volumes. The results are used to evaluate the impact of the radiogenic backgrounds in the double beta decay analyses, after the application of topological cuts that reduce the total rate to (0.25±0.01) mHz. Based on the best-fit background model, the NEXT-White median sensitivity to the two-neutrino double beta decay is found to be 3.5σ after 1 year of data taking. The background measurement in a Qββ±100 keV energy window validates the best-fit background model also for the neutrinoless double beta decay search with NEXT-100. Only one event is found, while the model expectation is (0.75±0.12) events. [Figure not available: see fulltext.]

Energy calibration of the NEXT-White detector with 1% resolution near Q ββ of 136Xe

Excellent energy resolution is one of the primary advantages of electroluminescent high-pressure xenon TPCs. These detectors are promising tools in searching for rare physics events, such as neutrinoless double-beta decay (ββ0ν), which require precise energy measurements. Using the NEXT-White detector, developed by the NEXT (Neutrino Experiment with a Xenon TPC) collaboration, we show for the first time that an energy resolution of 1% FWHM can be achieved at 2.6 MeV, establishing the present technology as the one with the best energy resolution of all xenon detectors for ββ0ν searches. [Figure not available: see fulltext.