Bestimmung von Organdosen und effektiven Dosen in der Radioonkologie

Hintergrund und Ziel:: Mit zunehmender Heilungschance in der Radioonkologie muss auch das durch Streustrahlung induzierte Strahlenrisiko außerhalb des Zielvolumens beurteilt werden können. Das Krebsrisiko einer Strahlenbehandlung kann aufgrund von Organdosen und einer etwas eingeschränkten effektiven Dosis abgeschätzt und verglichen werden. Material und Methodik:: Die Dosen in strahlenempfindlichen Organen außerhalb der Strahlenfelder können mit Hilfe des PC-Programms PERIDOSE von van der Giessen abgeschätzt werden. Die effektiven Dosen werden nach dem Konzept der ICRP bestimmt, wobei jedoch das Zielvolumen und die damit zusammenhängenden Organe unberücksichtigt bleiben. Ergebnisse:: Organdosen außerhalb der Strahlenfelder sind meist < 1% der Dosis im Zielvolumen, in Einzelfällen jedoch bis zu etwa 3%. Die effektiven Dosen während einer Strahlentherapie betragen je nach Zielvolumen, angewendeter Bestrahlungstechnik und applizierter Dosis im ICRU-Punkt zwischen 60 und 900 mSv. Schlussfolgerung:: Für die Abschätzung von Strahlenrisiken können Organdosen in der Radioonkologie mit Hilfe des Programms PERIDOSE berechnet werden. Für die Bewertung des Strahlenrisikos nach ICRP muss bei der effektiven Dosis das oft fortgeschrittene Alter der Patienten berücksichtigt werden, damit z. B. die hohen Gonadendosen für die effektive Dosis nicht überbewertet werde

Predicción de demanda y producción de energía eléctrica mediante redes neuronales y validación de los resultados mediante ensayos realizados en el laboratorio de recursos energéticos distribuidos de la UPV

[ES] El objetivo de este TFM es aplicar una metodología para predecir la producción y generación de energía de la microrred del Laboratorio de Recursos Energéticos Distribuidos de la UPV (LabDER) usando redes neuronales artificiales. Esta metodología se puede extrapolar a otras microrredes. Se dispone la potencia generada en tiempo real para cada una de las fuentes: solar fotovoltaica, eólica y baterías. Además, se dispone de datos meteorológicos tales como irradiación, velocidad de viento, temperatura ambiente entre otros. Con esta información se pretende predecir las curvas de demanda y de generación global de cada componente para optimizar la gestión de la energía. El tratamiento de los datos y la predicción se realizará mediante el lenguaje Python y usando la herramienta tensorflow. Tensorflow es una herramienta que permite generar diferentes tipos de redes neuronales como es el caso del clásico ¿perceptrón¿, redes convolucionales o redes recurrentes. Con el fin de obtener mejores resultados, esta herramienta permite crear redes neuronales artificiales con diferentes algoritmos de optimización para su entrenamiento. La primera parte de este trabajo consistirá en adaptar los datos de entrada (datos de la red y datos meteorológicos) para que pueden ser utilizados como inputs en la red neuronal. Posteriormente se seleccionarán los diferentes tipos de redes neuronales según lo que se decida predecir. Por ejemplo, para la producción global diaria, se podrían obtener resultados óptimos mediante un perceptrón clásico, mientras que para obtener la curva de producción sería mejor trabajar con redes neuronales recurrentes. Finalmente, mediante Tensorflow se puede definir una red neuronal con sus diferentes capas, el ritmo de aprendizaje y el algoritmo de entrenamiento entre otros. Esta herramienta permite crear una red a medida para obtener resultados adaptando los diferentes parámetros para así conseguir un mejor entrenamiento. Este tipo de redes implica un alto coste computacional.Martinez, AA. (2021). Predicción de demanda y producción de energía eléctrica mediante redes neuronales y validación de los resultados mediante ensayos realizados en el laboratorio de recursos energéticos distribuidos de la UPV. Universitat Politècnica de València. http://hdl.handle.net/10251/164734TFG

Birth weight as a risk factor for neonatal mortality: Breed-specific approach to identify at-risk puppies

Abstract: In numerous species, low birth weight is a risk factor for neonatal mortality. In the canine species, definition of a low birth weight is complex due to the huge interbreed variability in size. To identify puppies at higher risk of neonatal death, data from 6,694 puppies were analysed. The data were collected from 75 French breeding kennels, examining 27 breeds and totaling 1,202 litters of puppies. Generalised linear mixed models allowed to identify birth weight, birth weight heterogeneity within the litter, and size of the breeding kennel as significant risk factors for neonatal mortality. Receiver Operating Characteristics (ROC) and classification and regression tree (CART) analyses were combined to define breed specific thresholds for birth weight allowing the identification of puppies at higher risk of neonatal mortality. Due to differences in birth weights between breeds, including when belonging to the same breed size, analyses were conducted at the breed level. First, ROC analysis thresholds were successfully established for 12 breeds (area under the ROC ≥ 0.70; sensitivity ≥ 75%; specificity: 45–68%) and they ranged from 162 g in the Maltese to 480 g in the Bernese Mountain dog. Secondly, CART analysis thresholds from 22 breeds ranged from 105 g in the Maltese and 436 g in the Boxer. Puppies were grouped into three categories according to birth weight: low, moderate and high risk of neonatal mortality (higher than the ROC threshold, between ROC and CART thresholds, and lower than the CART threshold respectively). In the current study, 44% of the puppies were classified as at moderate risk and 5.3% for a high risk of neonatal mortality. Thresholds defined by CART analysis (and not ROC analysis) were used to define low birth weight puppies and were sometimes quite different between breeds with similar birth weight distributions suggesting a variable relationship between birth weight reduction and neonatal death. These results allow the identification of puppies at an increased risk of neonatal death, thus requiring specific nursing to improve their chances of survival. With these high risk puppies identified, both animal welfare and kennel productivity is predicted to improve

A Case Study of Zoonotic <i>Chlamydia abortus</i> Infection: Diagnostic Challenges From Clinical and Microbiological Perspectives

Chlamydia abortus is the most common causative agent of abortion in small ruminants, but it is poorly recognized as a human pathogen. In most published case studies, diagnosis remained difficult and often resulted in delayed initiation of therapy. In this case study of severe C abortus infection in a pregnant farmer from Switzerland, we highlight the clinical and microbiological diagnostic challenges and provide evidence of a zoonotic epidemiological link

A qualitative study on safety perception among healthcare workers of a tertiary academic care center during the SARS-CoV-2 pandemic

Background: Protecting healthcare workers (HCWs) from exposure to SARS-CoV-2 during patient care is central to managing the current pandemic. Higher levels of trust in personal protective equipment (PPE) and infection prevention and control (IPC) strategies have been previously related to lower levels of emotional exhaustion, yet little is known on how to achieve such a perception of safety. We thus sought to identify institutional actions, strategies and policies related to HCWs’ safety perception during the early phase of the pandemic at a tertiary care center in Switzerland by interviewing HCWs from different clinics, professions, and positions. Methods: For this qualitative study, 36 face-to-face semi-structured interviews were performed. Interviews were based on a guide that addressed the perception of institutional strategies and policies during the first phase of the pandemic in March 2020. The participants included doctors (n = 19) and nurses (n = 17) in senior and non-senior positions from eight clinics in the University Hospital Basel, Switzerland, all involved in patient care. All interviews were audio-recorded and transcribed verbatim. Data were analyzed using qualitative content analysis and organized using MAXQDA (VERBI Software GmbH, Berlin). Findings: Five recurring themes were identified to affect HCWs’ perception of their safety during the SARS-CoV-2 pandemic: (1) transparency and clarity of information, (2) communication on the availability of PPE (with the provision of information alone increasing the feeling of safety even if supplies of PPE were reported as low), (3) uniformity and consistency of guidelines, (4) digital resources to support face-to-face teaching (although personal information transfer is still being considered superior in terms of strengthening safety perception) and (5) support and appreciation for the work performed. Conclusions: This study identifies institutional policies and actions influencing HCWs’ safety perception during the first wave of the COVID-19 pandemic, the most important of which is the factor of transparent communication. This knowledge reveals potential areas of action critical to improving preparedness and management in hospitals faced with an infectious disease threat

Deltaic and Coastal Sediments as Recorders of Mediterranean Regional Climate and Human Impact Over the Past Three Millennia

International audienc

Contrasting properties of particle-particle and hole-hole excitations in ²⁰⁶Tl and ²¹⁰Bi nuclei

A complete-spectroscopy investigation of low-lying, low-spin states in the one-proton-hole and one-neutron-hole nucleus 206Tl has been performed by using thermal neutron capture and γ-coincidence technique with the FIPPS Ge array at ILL Grenoble. The new experimental results, together with data for the one-proton-particle and one-neutron-particle nucleus 210Bi (taken from a previous study done at ILL in the EXILL campaign), allowed for an extensive comparison with predictions of shell-model calculations performed with realistic interactions. No phenomenological adjustments were introduced in the calculations. In 210Bi, state energies, transition multipolarities and decay branchings agree well with theory for the three well separated multiplets of states which dominate the low-lying excitations. On the contrary, in 206Tl significant discrepancies are observed: in the same energy region, six multiplets were identified, with a significant mixing among them being predicted, as a consequence of the smaller energy separation between the active orbitals. The discrepancies in 206Tl are attributed to the larger uncertainties in the determination of the off-diagonal matrix elements of the realistic shell-model interaction with respect to the calculated diagonal matrix elements, the only ones playing a major role in the case of 210Bi. The work points to the need of more advanced approaches in the construction of the realistic interactions

Industry-Scale Orchestrated Federated Learning for Drug Discovery

To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n{\deg}831472), which was comprised of 10 pharmaceutical companies, academic research labs, large industrial companies and startups. The MELLODDY platform was the first industry-scale platform to enable the creation of a global federated model for drug discovery without sharing the confidential data sets of the individual partners. The federated model was trained on the platform by aggregating the gradients of all contributing partners in a cryptographic, secure way following each training iteration. The platform was deployed on an Amazon Web Services (AWS) multi-account architecture running Kubernetes clusters in private subnets. Organisationally, the roles of the different partners were codified as different rights and permissions on the platform and administrated in a decentralized way. The MELLODDY platform generated new scientific discoveries which are described in a companion paper.Comment: 9 pages, 4 figures, to appear in AAAI-23 ([IAAI-23 track] Deployed Highly Innovative Applications of AI

Modulation of the vertical particle transfer efficiency in the oxygen minimum zone off Peru

The fate of the organic matter (OM) produced by marine life controls the major biogeochemical cycles of the Earth's system. The OM produced through photosynthesis is either preserved, exported towards sediments or degraded through remineralisation in the water column. The productive eastern boundary upwelling systems (EBUSs) associated with oxygen minimum zones (OMZs) would be expected to foster OM preservation due to low O2 conditions. But their intense and diverse microbial activity should enhance OM degradation. To investigate this contradiction, sediment traps were deployed near the oxycline and in the OMZ core on an instrumented moored line off Peru. Data provided high-temporal-resolution O2 series characterising two seasonal steady states at the upper trap: suboxic ([O2]  50%) and remineralisation (intermediate Teff 20  50%) has been reported in summer and winter associated with extreme limitation in O2 concentrations or OM quantity for OM degradation. However, higher levels of O2 or OM, or less refractory OM, at the oxycline, even in a co-limitation context, can decrease the OMZ transfer efficiency to below 50%. This is especially true in summer during intraseasonal wind-driven oxygenation events. In late winter and early spring, high oxygenation conditions together with high fluxes of sinking particles trigger a shutdown of the OMZ transfer (Teff < 6%). Transfer efficiency of chemical elements composing the majority of the flux (nitrogen, phosphorus, silica, calcium carbonate) follows the same trend as for carbon, with the lowest transfer level being in late winter and early spring. Regarding particulate isotopes, vertical transfer of δ15N suggests a complex pattern of 15N impoverishment or enrichment according to Teff modulation. This sensitivity of OM to O2 fluctuations and particle concentration calls for further investigation into OM and O2-driven remineralisation processes. This should include consideration of the intermittent behaviour of OMZ towards OM demonstrated in past studies and climate projections