Organizaciones virtuales y redes neuronales. Algunas similitudes.

Aunque existen numerosos trabajos que identifican sus principales características y modo de funcionamiento, el estudio de las organizaciones virtuales adolece de una carencia de modelos matemáticos que reflejen su comportamiento de un modo cuantitativo. En este sentido, a lo largo del presente trabajo se tratará de poner de manifiesto las similitudes existentes entre el funcionamiento de las organizaciones virtuales y el de las redes neuronales (SOM, SelfOrganizing Maps). El objetivo es sentar las bases para proponer este tipo de técnica estadística como herramienta para la formulación de modelos sobre organizaciones virtuales. Se plantearán una serie de argumentos de plausibilidad, dejando a investigaciones posteriores la verificación rigurosa de esta propuesta.ORGANIZACION VIRTUAL, REDES SOM, MAPAS DE KOHONEN

Organizaciones virtuales de la integración a la desintegración integrada

En el ámbito organizacional, en los últimos tiempos, han cobrado importancia las relaciones interorganizacionales, motivando el desarrollo de nuevas formas organizativas, siendo una de éstas las “organizaciones virtuales”. En este artículo se da a conocer en qué consisten estas organizaciones y cuáles son sus principales características. Además se tratan dos aspectos importantes de considerar, concretamente, el contexto en el cual han surgido estas organizaciones y el concepto de “virtualidad”

Implementation of the PhenoFlex framework for forecasting the start of the main pollen season in the context of climate change

Climate change is affecting the flowering seasonality of many plant species, disrupting the dynamics of their life cycles and triggering changes in ecosystems. These changes are not uniform across all species and geographic regions, and local monitoring is required to gauge future phenological shifts and to establish mitigation strategies. In this context, aerobiological sampling has proven to be a valuable tool for monitoring the flowering onset in anemophilous species. The start date of the main pollen season for a certain pollen type in a given location is usually linked to the flowering onset of the taxa that produce it. This has encouraged the development of different models in recent years to estimate the start of the main pollen season. However, some of these models rely on rigid assumptions that may not fit the diversity of the environmental conditions in which the plants grow. In 2021, Luedeling et al. developed the PhenoFlex statistical framework to forecast the flowering onset of tree species based on biological processes. This model accommodates for both overlapping and sequential chilling and forcing periods. It also fits all the model parameters for the targeted taxa, avoiding the arbitrary selection of fixed parameters. To date, this framework has not been used in aerobiological contexts. In this study, we delve into the applicability of this framework to aerobiological data and issue some recommendations for model validation and its use in estimating climate change impacts. As an example of application, PhenoFlex models were fitted to aerobiological data for Cupressaceae and Platanus from 8 sampling locations within Malaga Province (southern Spain) with 52 sampling years. The models registered mean absolute errors of 7.7 and 4.5 days, respectively, and were used to generate forecasts according to different future temperature scenarios.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Seasonal and intradaily variations of Parietaria pollen in the atmosphere of Málaga.

Parietaria pollen is one of the main causes of hay fever and asthma in the population, presenting a high allergenicity. That is why, in order to inform the population, it is important to determine whether its behaviour pattern is different in different parts of the city. The objective of this study was to analyze and compare the behaviour pattern of the Parietaria pollen type in two different points within the city of Malaga and to analyze the existing correlation between pollen concentrations and the main meteorological parameters. We used two Hirst-type volumetric pollen traps, one of them installed in the periphery and the other in the city center, between 2017 and 2019. The samples were mounted and counted following the recommendations of the Spanish Aerobiology Network. To calculate the annual pollen integral, the sum of the mean daily concentrations throughout the year was used. To calculate the intradaily variations, the values were accumulated every two hours, expressed as percentages of the daily total. In order to study the relationships between meteorological parameters and pollen concentrations, Spearman correlation tests have been carried out. The values of the annual pollen integral were always much higher in the centre. Daily mean concentrations showed the presence of this pollen type in the atmosphere throughout the year. Regarding the intraday pattern, a more pronounced peak was observed in the city centre, while in the periphery, the distribution is more homogeneous throughout the day. The meteorological parameters play an important role in determining the daily concentrations in the atmosphere. In the light of these results, we can conclude that it is necessary to install several sampling points within the same city, due to its heterogeneity and different land uses, in order to inform the population with a greater precision and, in this way, prevent respiratory allergies.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Airborne pollen concentrations in Sierra de las Nieves National Park (southern Spain) and its allergenic potential.

Sierra de las Nieves was declared National Park in 2021. Around 100 000 people visit the park every year and a high percentage of them may suffer allergy symptoms due to the presence of some pollen types in the atmosphere. The aim of this study was to determine the allergenic potential of the concentrations registered in the atmosphere of Sierra de las Nieves National Park as well as the seasonality of different pollen types. Airborne pollen was sampled by means of a Hirst-type volumetric pollen trap installed in “Las Conejeras” recreational area. In this study, data of the year 2022 were considered. Pollen samples were mounted and counted following the methodology proposed by the Spanish Aerobiology Network. Data were managed by means of the AeRobiology package, implemented in R software. Spearman correlations test between daily pollen concentrations and the main meteorological parameters were performed. Airborne pollen was detected during almost the whole year, with the highest concentrations being reached during the period April-June (89.19% of the total annual pollen integral). The pollen type with the highest number of days with concentrations of high allergenic potential was Quercus (25 days), followed by Castanea and Poaceae (8 days), the period with the highest risk for allergy sufferers being April-July. High temperatures favour pollen release, increasing the airborne pollen concentrations, but precipitation and high relative humidity favour pollen precipitation, reducing airborne pollen concentrations. Wind dynamics play different roles depending on the pollen type considered, due to the heterogeneous distribution of the pollen emission sources. Allergy sufferers should consider the pollination period of the pollen types which they are allergic to when planning their visits to the National Park, especially on days with high temperatures and low relative humidity, meteorological conditions that tend to increase pollen concentrations.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Unraveling heterogeneous susceptibility and the evolution of breast cancer using a systems biology approach

This is an Open Access article distributed under the terms of the Creative Commons Attribution License.-- et al.[Background]: An essential question in cancer is why individuals with the same disease have different clinical outcomes. Progress toward a more personalized medicine in cancer patients requires taking into account the underlying heterogeneity at different molecular levels. [Results]: Here, we present a model in which there are complex interactions at different cellular and systemic levels that account for the heterogeneity of susceptibility to and evolution of ERBB2-positive breast cancers. Our model is based on our analyses of a cohort of mice that are characterized by heterogeneous susceptibility to ERBB2-positive breast cancers. Our analysis reveals that there are similarities between ERBB2 tumors in humans and those of backcross mice at clinical, genomic, expression, and signaling levels. We also show that mice that have tumors with intrinsically high levels of active AKT and ERK are more resistant to tumor metastasis. Our findings suggest for the first time that a site-specific phosphorylation at the serine 473 residue of AKT1 modifies the capacity for tumors to disseminate. Finally, we present two predictive models that can explain the heterogeneous behavior of the disease in the mouse population when we consider simultaneously certain genetic markers, liver cell signaling and serum biomarkers that are identified before the onset of the disease. [Conclusions]: Considering simultaneously tumor pathophenotypes and several molecular levels, we show the heterogeneous behavior of ERBB2-positive breast cancer in terms of disease progression. This and similar studies should help to better understand disease variability in patient populations.JPL was partially supported by FEDER and MICINN (PLE2009-119), FIS (PI07/0057, PI10/00328, PIE14/00066), the Junta de Castilla y León (SAN673/SA26/08; SAN126/SA66/09, SA078A09, CSI034U13), the “Fundación Eugenio Rodríguez Pascual”, the Fundación Inbiomed (Instituto Oncológico Obra Social de la Caja Guipozcoa-San Sebastian, Kutxa), and the “Fundación Sandra Ibarra de Solidaridad frente al Cáncer”. AC was supported by MICINN (PLE2009-119). SCLL is funded by a JAEdoc Fellowship (CSIC)/FSE. MMSF and ABG are funded by fellowships from the Junta de Castilla y Leon. WR was supported by a Forschungsstipendium of the Deutsche Forschungsgemeinschaft (DFG) [RE 3108/1-1]. TN, BPB and DYL acknowledge support from the US Department of Energy Low-Dose SFA Program at Berkeley Lab [DE-AC02-05CH11231], the National Institutes of Health [RC1NS069177] and the California Breast Cancer Research Program [15IB-0063]. JHM was supported by the National Institutes of Health, a National Cancer Institute grant (R01 CA116481), and the Low-Dose Scientific Focus Area, Office of Biological and Environmental Research, US Department of Energy (DE-AC02-05CH11231).Peer Reviewe

A deep learning LSTM-based approach for forecasting annual pollen curves: Olea and Urticaceae pollen types as a case study

Airborne pollen can trigger allergic rhinitis and other respiratory diseases in the synthesised population, which makes it one of the most relevant biological contaminants. Therefore, implementing accurate forecast systems is a priority for public health. The current forecast models are generally useful, but they falter when long time series of data are managed. The emergence of new computational techniques such as the LSTM algorithms could constitute a significant improvement for the pollen risk assessment. In this study, several LSTM variants were applied to forecast monthly pollen integrals in Málaga (southern Spain) using meteorological variables as predictors. Olea and Urticaceae pollen types were modelled as proxies of different annual pollen curves, using data from the period 1992–2022. The aims of this study were to determine the LSTM variants with the highest accuracy when forecasting monthly pollen integrals as well as to compare their performance with the traditional pollen forecast methods. The results showed that the CNN-LSTM were the most accurate when forecasting the monthly pollen integrals for both pollen types. Moreover, the traditional forecast methods were outperformed by all the LSTM variants. These findings highlight the importance of implementing LSTM models in pollen forecasting for public health and research applications.Funding for open Access charge: Universidad de Málaga / CBUA. This work has been partially funded by the Spanish Ministry of Science and Innovation via grant (funded by MCIN/AEI/10.13039/5011 00011033/) PID2020-112540RB-C41, AETHER-UMA (A smart data holistic approach for context-aware data analytics: semantics and context exploitation), and grant ‘‘Environmental and Biodiversity Climate Change Lab (EnBiC2-Lab)’’ LIFEWATCH-2019-11-UMA-01 (AEI/FEDER, UE). A. Picornell has been supported by a postdoctoral grant financed by the Consejería de Transformación Económica, Industria, Conocimiento Universidades (Junta de Andalucía, POSTDOC_21_00056)

Pollen recognition through an open-source web-based system: automated particle counting for aerobiological analysis

Airborne pollen is produced by plants for their sexual reproduction and can have negative impacts on public health. The current monitoring systems are based on manual sampling processes which are tedious and time-consuming. Due to that, pollen concentrations are often reported with a delay of up to one week. In this study, we present an open-source user-friendly web application powered by deep learning for automatic pollen count and classification. The application aims to simplify the process for non-IT users to count and classify different types of pollen, reducing the effort required compared to manual methods. To overcome the challenges of acquiring large labelled datasets, we propose a semi-automatic labelling approach, which combines human expertise and machine learning techniques. The results demonstrate that our approach significantly reduces the effort required for users to count and classify pollen taxa accurately. The model achieved high precision and recall rates (> 96% [email protected]), enabling reliable pollen identification and prediction.Funding for open access charge: Universidad de Málaga/CBUA. This work was financed by the Ministry of Science and Innovation of Spain and FEDER funding inside the Operational Plurir- regional Program of Spain 2014–2020 and the Operational Program of Smart Growing (Environmental and Biodiversity Climate Change Lab, EnBiC2-Lab; LIFEWATCH-2019-11-UMA-01-BD) and by the Span- ish project TED2021-130167B-C33 (‘GEDIER: Application of Digital Twins to more sustainable irrigated farms’). A. Picornell was supported by a postdoctoral grant financed by the Ministry of Economic Transfor- mation, Industry, Knowledge and Universities of the Junta de Andalucía (POSTDOC_21_00056)

Effects of climate change on Platanus flowering in Western Mediterranean cities: current trends and future projections

Ornamental trees can reduce some of the negative impacts of urbanization on citizens but some species, such as Platanus spp., produce pollen with high allergenic potential. This can exacerbate the symptomatology in allergic patients, being a public health problem. Therefore, it would be relevant to determine the environmental conditions regulating the flowering onset of the Platanus species. The aims of this study were to use aerobiological records for modelling the thermal requirements of Platanus flowering and to make future projections based on the effects that climate change could have on it under several possible future scenarios. This study was conducted in Badajoz and Malaga, two Western Mediterranean cities with different climate conditions. In the first step, several main pollen season definitions were applied to the aerobiological data and their onset dates were compared with in situ phenological observations. The main pollen season definition that best fitted the Platanus flowering onset was based on the 4th derivative of a logistic function. This definition was used as a proxy to model the thermal requirements of the Platanus flowering onset by applying the PhenoFlex statistical framework. The errors obtained by this model during the external validation were 3.2 days on average, so it was fed with future temperature estimations to determine possible future trends. According to the different models, the flowering onset of Platanus in Badajoz will show heterogeneous responses in the short and medium term due to different balances in the chilling-forcing compensation, while it will clearly delay in Malaga due to a significant delay in the chilling requirement fulfilment. This may increase the chances of cross-reactivity episodes with other pollen types in the future, increasing its impact on public health.Funding for open Access charge: Universidad de Málaga / CBUA. This work was partially financed by the Ministry of Science and Innovation of Spain and FEDER funding inside the Operational Plurirregional Program of Spain 2014-2020 and the Operational Program of Smart Growing (Project Environmental and Biodiversity Climate Change Lab, EnBiC2-Lab), by the Regional Government of Extremadura (IB20081 and GR21027), and by the University of Málaga under its program for projects led by young researchers (I Plan Propio de Investigación y Transferencia; B1-2021_24). A. Picornell was supported by a postdoctoral grant financed by the Ministry of Economic Transformation, Industry, Knowledge and Universities of the Junta de Andalucía (POSTDOC_21_00056). We acknowledge the E-OBS dataset from the EU-FP6 project UERRA (http://www.uerra.eu) and the Copernicus Climate Change Service, and the data providers in the ECA&D project (https://www.ecad.eu)