Prescribed fire (PB) is used to achieve ecological objectives and to reduce fuel hazard thus limiting detrimental impacts of wildfire and appropriate selection of prescription window is critical for these goals. Operational use of PB in the Mediterranean forest is scarce and information about its effects on soil remains incomplete. This study for the first time i) compared the immediate impact of spring and autumn PB and experimental summer fire on key properties of forest floor and mineral topsoil in Mediterranean black pine forest, and ii) assessed the capacity of PB to reduce fuel, with limited immediate impacts on soil. PB significantly reduced the 32.5 % of pre-fire forest floor depth, while summer fire consumed 88.5 % and exposed about 30 % of the mineral soil surface. Mean maximum temperature during fire at the mineral soil surface was 23 degrees C in PB, in contrast to 128 degrees C in summer fire, while soil heating at 2 cm depth was negligible in both cases. PB did not cause immediate changes in OM quality parameters, and chemical (C and N concentrations, C/N and pH) and microbiological properties (Cmic, Cmic/C, and beta-glucosidase, acid phosphatase and alkaline phosphatase activities) in forest floor or mineral topsoil (0-2 cm). By contrast, summer fire greatly increased OM recalcitrance and reduced Cmic, Cmic/C and enzyme activities in forest floor immediately after fire. In the mineral topsoil, only microbial properties were significantly reduced. The maximum temperature reached during fire in forest floor and topsoil was associated with most of the overall changes in properties in both layers. The findings suggest that prescribed fire can

Households, factories, office buildings and communities can reduce their energy consumption, while maintaining the same level of activity and comfort, by identifying and avoiding unnecessary energy waste.Governments around the world are taking initiatives in this direction and also international coordinated initiatives such as the future ISO 50001.To support these plans, the general goal of ENERCARE project is to design a new open information platform built on customizable, adaptive and open service-oriented architecture, providing connectivity to the energy grids and information to the users.ENERCARE will provide an innovative platform for the development of a key piece in a new generation suite of Smart Grid products.Through the spread of services on energy management, will encourage more energy conservation at demand side and will contribute to the achievement of lowcarbon society to come.ENERCARE will work to increase the social awareness of the citizens in saving energy and the improvement in new and more efficient habits triggered by IT solutions.

Geospatial fire behaviour and fire hazard simulators, fire effects models and smoke emission software commonly use standard fuel models in order to simplify data collection and the inclusion of complex fuel scenarios. These fuel models are often mapped using remotely sensed data. However, given the great complexity of fuelbeds, with properties that vary widely in both time and space, the use of these standard fuel models can greatly limit accurate fuel mapping. This affects fuel hazard assessment, fuel reduction treatment plans, fire management decision-making and evaluation of the environmental impact of wildfire. In this study, we developed unique customized fire behaviour fuel models for shrub and bracken communities, by using k-medoids clustering analysis based on both fuel structural characteristics and potential fire behaviour. We used an original database of 722 destructive sample plots in nine different shrub and bracken communities covering the entire distribution area in Galicia (NW Spain), one of the regions in Europe most affected by forest fires. Measurements of cover, height and fuel fractions loads differentiated by size and vegetative state (live or dead) were used to estimate the potential rate of fire spread with five different models including fireline intensity, heat per unit area and the flame length for each sampling site and considering extreme environmental conditions. The optimal number of clusters was established by combining practical knowledge about the shrubland communities under study and their associated fire behaviour, with maximization of the mean value of the silhouette variable and minimization of the within-cluster sum of squares. The structural characteristics of the medoids derived from the analysis were associated with each of the proposed customized fuel models. Finally, a simple dichotomous classification based only on shrub height was developed to enable construction of spatially explicit fuel model maps based on remotely sensed data. Thus, the methodology applied allows generation of a more realistic representation of fuel distribution in the landscape, based on fuel structure measurements of natural regional ecosystems rather than on the use of standard models. We believe that the proposed methodology is generally applicable to communities composed of other shrub and fern species in different biogeographical regions.

Background:DICER1 alterations are associated with intracranial tumors in the pediatric population, including pineoblastoma, pituitary blastoma, and the recently described "primary DICER1-associated CNS sarcoma" (DCS). DCS is an extremely aggressive tumor with a distinct methylation signature and a high frequency of co-occurring mutations. However, little is known about its treatment approach and the genomic changes occurring after exposure to chemoradiotherapy.Methods:We collected clinical, histological, and molecular data from eight young adults with DCS. Genomic analysis was performed by Next-generation Sequencing (NGS). Subsequently, an additional germline variants analysis was completed. In addition, an NGS analysis on post-progression tumor tissue or liquid biopsy was performed when available. Multiple clinicopathological characteristics, treatment variables, and survival outcomes were assessed.Results:Median age was 20 years. Most lesions were supratentorial. Histology was classified as fusiform cell sarcomas (50%), undifferentiated (unclassified) sarcoma (37.5%), and chondrosarcoma (12.5%). Germline pathogenic DICER1 variants were present in two patients, 75% of cases had more than one somatic alteration in DICER1, and the most frequent commutation was TP53. Seven patients were treated with surgery, Ifosfamide, Cisplatin, and Etoposide (ICE) chemotherapy and radiotherapy. The objective response was 75%, and the median time to progression (TTP) was 14.5 months. At progression, the most common mutations were in KRAS and NF1. Overall survival was 30.8 months.Conclusions:DCS is an aggressive tumor with limited therapeutic options that requires a comprehensive diagnostic approach, including molecular characterization. Most cases had mutations in TP53, NF1, and PTEN, and most alterations at progression were related to MAPK, RAS and PI3K signaling pathways.

Los síndromes linfoproliferativos postrasplante (PTLD, por sus siglas en inglés) constituyen una complicación relativamente frecuente entre los receptores de trasplante de órgano sólido o de médula ósea. Representan un amplio espectro de lesiones, que oscilan desde los cambios histológicos tempranos producidos por la infección del virus de Epstein-Barr hasta las neoplasias de alto grado con respuestas variables a las intervenciones terapéuticas. El compromiso del sistema nervioso central (SNC) se ha descrito hasta en 22% de los casos, 12% de ellos en forma primaria, asociados a un peor pronóstico; en general el abordaje diagnóstico y terapéutico no está estandarizado, en parte, debido a la limitación fisiológica que implica la barrera hematoencefálica. El tratamiento tiene opciones limitadas; se acepta el uso de metotrexate a altas dosis o de rituximab intravenoso o intratecal. A continuación, se presenta el caso de un hombre de 76 años, receptor de un trasplante hepático por hemocromatosis, quien a los 6 años postrasplante consulta por alteración de la marcha. Tras documentar una lesión intra-axial, la biopsia por estereotaxia documenta un PTLD tardío, primario con lesión única en SNC. Después de la reducción inicial de la inmunosupresión, el tratamiento con rituximab y metotrexate intravenosos a altas dosis durante cinco ciclos, se logró respuesta parcial en este paciente, con toxicidad renal leve.

Introducción. En los meningiomas, ocurren con frecuencia mutaciones en la región promotora de la transcriptasa inversa de la telomerasa.Objetivo. Estimar la importancia pronóstica de las mutaciones de la transcriptasa inversa de la telomerasa en pacientes colombianos con meningiomas de grados II y III.Materiales y métodos. Es un estudio de cohorte, retrospectivo y multicéntrico, que incluyó pacientes con diagnóstico de meningioma persistente o recidivante, de grados II y III, según la clasificación de la OMS, reclutados entre el 2011 y el 2018, con tratamiento sistémico (sunitinib, everolimus con octreótido o sin él, y bevacizumab). El estado de la mutación del promotor de la transcriptasa inversa de la telomerasa se determinó por medio de la PCR. Resultados. Se incluyeron 40 pacientes, en 21 (52,5 %) de los cuales se encontraron mutaciones en la transcriptasa inversa de la telomerasa, siendo las variantes más frecuentes la C228T (87,5 %) y la C250T (14,3 %). Estas fueron más frecuentes entre los pacientes con meningiomas anaplásicos (p=0,18), en aquellos con más de dosrecurrencias (p=0,04), y en los que presentaron lesiones en la región parasagital y la fosa anterior (p=0,05). Los sujetos caracterizados por tener alteraciones puntuales fueron tratados con mayor frecuencia con la serie de medicamentos everolimus, sunitinib y bevacizumab (p=0,06). Tras el inicio del tratamiento médico, la supervivencia global fue de 23,7 meses (IC95% 13,1-34,2) en los pacientes con mutaciones y, de 43,4 meses (IC95% 37,5-49,3), entre aquellos sin mutaciones (p=0,0001).Los resultados del análisis multivariado demostraron que, únicamente, el número de recurrencias y la presencia de mutaciones en el gen de la transcriptasa inversa de la telomerasa, fueron factores que afectaron negativamente la supervivencia global. Conclusiones. Las mutaciones en el gen promotor de la transcriptasa inversa de la telomerasa permiten identificar los pacientes con alto riesgo, cuya detección podría ser de utilidad para seleccionar el mejor esquema terapéutico.

In this study, 310 destructively sampled plots were used to develop two equation systems for the three main pine species in NW Spain (P. pinaster; P. radiata and P. sylvestris): one for estimating loads of understorey fuel com-ponents by size and condition (live and dead) and another one for forest floor fuels. Additive systems of equations were simultaneously fitted for estimating fuel loads using overstorey, understorey and forest floor variables as regressors. The systems of equations included both the effect of pine species and the effect of understorey compositions dominated by ferns-brambles or by woody species, due to their obvious structural and physiological differences. In general, the goodness-of-fit statistics indicated that the estimates were reasonably robust and accurate for all of the fuel fractions. The best results were obtained for total understorey vegetation, total forest floor and raw humus fuel loads, with more than 76% of the observed variability explained, whereas the poorest results were obtained for coarse fuel loads of understory vegetation with a 53% of observed variability explained.To reduce the overall costs associated with the field inventories necessary for operational use of the models, the additive systems were fitted again using only overstorey variables as potential regressors. Only relationships for fine (<6 mm) and total understorey vegetation and total forest floor fuel loads were obtained, indicating the complexity of the forest overstorey-understorey and overstorey-forest floor relationships. Nevertheless, these models explained around 52% of the observed variability.Finally, equations estimating the total understorey vegetation and the total forest floor fuel loads based only on canopy cover were fitted. These models explained only 26%-32% of the observed variability; however, their main advantage is that although understorey vegetation in forested landscapes is largely invisible to remote sensing, canopy cover can be estimated with moderate accuracy, allowing for landscape-scale estimates of total fuel loads. The equations represent an appreciable advance in understorey and forest floor fuel load assessment in the region and areas with similar characteristics and may be instrumental in generating fuel maps, fire management improvement and better C storage assessment by vegetation type, among many other uses.

Shrub-dominated ecosystems cover large areas globally and play essential roles in ecological processes. Aboveground biomass expressed on an area basis (AGB) is central to many of the ecological processes and services provided by shrublands and is important as the main fuel source for wildfires. Hence, its accurate estimation in shrublands is crucial for ecologists and land managers. This is especially relevant in fire-prone regions such as NW Spain, where shrublands are an important part of the landscape, providing multiple services, but are severely impacted by wildfires. Although biomass models are available for numerous shrub species at the individual plant level, operational models based directly on easily measured shrub stand attributes are scarce. In this study, equations for estimating AGB and loads of different fuel components by size and condition (live and dead) from stand biometric variables were developed for the nine most prevalent shrub communities in NW Spain. Non-linear iterative seemingly unrelated regression was used to fit compatible systems of equations for estimating fuel loads, with shrub stand height and cover and litter depth as predictors for individual shrub communities and all data combined. In general, the goodness-of-fit statistics indicated that the estimates were reasonably accurate for all communities (grouped and ungrouped). The best results were obtained for AGB and total fuel load, including litter, whereas the poorest results were obtained for standing live and dead fine fuel load. Model performance was reduced when height was the only independent variable, although the reduction was small for most fuel categories, except litter load for which the variability was adequately explained by the litter depth. These results illustrate the feasibility of the stand level approach for constructing operational models of shrub fuel load that are accurate for most of fuel components, while also highlighting the ongoing challenges in live and dead fine fuel modelling. The equations developed represent an appreciable advance in shrubland biomass assessment in the region and areas with similar characteristics and may be instrumental in generating fuel maps, fire management improvement and better C storage assessment by vegetation, among other many uses.

Introduction: Mutations in the promoter region of telomerase reverse transcriptase occur frequently in meningiomas. Objective: To estimate the prognostic value of telomerase reverse transcriptase mutations in Colombian patients with grade II and III meningioma. Materials and methods: Multicenter retrospective cohort study of patients diagnosed with refractory or recurrent WHO grade II and III meningioma, recruited between 2011 and 2018, managed with systemic therapy (sunitinib, everolimus +/-octreotide and bevacizumab). Mutation status of the telomerase reverse transcriptase promoter was performed by PCR. Results: 40 patients were included, of which telomerase reverse transcriptase mutations were found in 21 (52.5%), the most frequent variants being C228T and C250T, 87.5% and 14.3%, respectively. These were more frequent among patients with anaplastic meningiomas (p = 0.18), with >2 recurrences (p = 0.04), and in lesions of the parasagittal region and anterior fossa (p = 0.05). Subjects characterized as having punctual alterations were more frequently exposed to the sequence E -Su -Bev (p = 0.06). OS after initiation of medical treatment was 23.7 months (95% CI 13.1-34.2) and 43.4 months (95% CI 37.5-49.3; p = 0.0001) between subjects with and without mutations, respectively. In multivariate analysis, it was shown that only the number of recurrences and the presence of telomerase reverse transcriptase mutations negatively affected OS. Conclusions: Telomerase reverse transcriptase allows identifying high-risk patients and could be useful to select the best sequence of medical treatment.

BACKGROUND:Tap test improves symptoms of idiopathic normal pressure hydrocephalus (iNPH); hence, it is widely used as a diagnostic procedure. However, it has a low sensitivity and there is no consensus on the parameters that should be used nor the volume to be extracted. We propose draining cerebrospinal fluid (CSF) during tap test until a closing pressure of 0 cm H2O is reached as a standard practice. We use this method with all our patients at our clinic.METHODS:This is a descriptive cross-sectional study where all patients with presumptive diagnosis of iNPH from January 2014 to December 2019 were included in the study. We used a univariate descriptive analysis and stratified analysis to compare the opening pressure and the volume of CSF extracted during the lumbar puncture, between patients in whom a diagnosis of iNPH was confirmed and those in which it was discarded.RESULTS:A total of 92 patients were included in the study. The mean age at the time of presentation was 79.4 years and 63 patients were male. The diagnosis of iNPH was confirmed in 73.9% patients. The mean opening pressure was 14.4 cm H2O mean volume of CSF extracted was 43.4 mL.CONCLUSION:CSF extraction guided by a closing pressure of 0 cm H2O instead of tap test with a fixed volume of CSF alone may be an effective method of optimizing iNPH symptomatic improvement and diagnosis.

Atypical (WHO grade II) and malignant meningiomas (WHO Grade III) are a rare subset of primary intracranial tumors. Due to the high recurrence rate after surgical resection and radiotherapy, there has been a recent interest in exploring other systemic treatment options for these refractory tumors. Recent advances in molecular sequencing of tumors have elucidated new pathways and drug targets currently being studied. This article provides a thorough overview of novel investigational therapeutics, including targeted therapy, immunotherapy, and new technological modalities for atypical and malignant meningiomas. There is encouraging preclinical evidence regarding the efficacy of the emerging treatments discussed in this chapter. Several clinical trials are currently recruiting patients to translate targeted molecular therapy for recurrent and high-grade meningiomas.

Normal pressure hydrocephalus syndrome, characterized by ventriculomegaly and the classic triad of symmetric gait disturbance, cognitive decline, and urinary incontinence, is the most common cause of hydrocephalus in the adult population and a significant cause of reversible dementia among older adults. The only effective treatment for this syndrome, to date, is a cerebrospinal fluid shunting procedure, commonly a ventriculoperitoneal, ventriculoatrial, or lumboperitoneal shunt. The shunting success rate ranges between 73 and 96%. Hence, early identification, proper diagnosis, and treatment are paramount.We designed a protocol-based program supported on the best available evidence for an integral approach of patients with normal pressure hydrocephalus syndrome. The protocol consists of a series of patient-centered tests and interventions performed on adults with clinical suspicion, leading to optimized and sustainable outcomes for patients living with this condition.The program obtained the recognition of the Joint Commission International as an accredited center of excellence. The objectives of our center are increasing awareness and knowledge of normal pressure hydrocephalus syndrome within the community, delivering optimized interdisciplinary care, mitigating risks, improving quality of life to patients and their families, and ultimately saving from oblivion a significant number of patients who would be otherwise condemned.

Background: Amplification of EGFR and its active mutant EGFRvIII are common in glioblastoma (GB). While EGFR and EGFRvIII play critical roles in pathogenesis, targeted therapy with EGFR-tyrosine kinase inhibitors (TKIs) or antibodies has shown limited efficacy. To improve the likelihood of effectiveness, we targeted adult patients with recurrent GB enriched for simultaneous EGFR amplification and EGFRvIII mutation, with osimertinib/bevacizumab at doses described for non-small cell lung cancer (NSCLC). Methods: We retrospectively explored whether previously described EGFRvIII mutation in association with EGFR gene amplification could predict response to osimertinib/bevacizumab combination in a subset of 15 patients treated at recurrence. The resistance pattern in a subgroup of subjects is described using a commercial NGS panel in liquid biopsy. Results: There were ten males (66.7%), and the median patient’s age was 56 years (range 38-70 years). After their initial diagnosis, 12 patients underwent partial (26.7%) or total resection (53.3%). Subsequently, all cases received IMRT and concurrent and adjuvant temozolomide (TMZ; the median number of cycles 9, range 6-12). The median follow-up after recurrence was 17.1 months (95% CI 12.3-22.6). All patients received osimertinib/bevacizumab as a second-line intervention with a median progression-free survival (PFS) of 5.1 months (95% CI 2.8-7.3) and overall survival (OS) of 9.0 months (95% CI 3.9-14.0). The PFS6 was 46.7%, and the overall response rate (ORR) was 13.3%. After exposure to the osimertinib/bevacizumab combination, the main secondary alterations were MET amplification, STAT3 , IGF1R , PTEN , and PDGFR . Conclusions: While the osimertinib/bevacizumab combination was marginally effective in most GB patients with simultaneous EGFR amplification plus EGFRvIII mutation, a subgroup experienced a long-lasting meaningful benefit. The findings of this brief cohort justify the continuation of the research in a clinical trial. The pattern of resistance after exposure to osimertinib/bevacizumab includes known mechanisms in the regulation of EGFR , findings that contribute to the understanding and targeting in a stepwise rational this pathway.

An accurate estimation of forests’ aboveground biomass (AGB) is required because of its relevance to the carbon cycle, and because of its economic and ecological importance. The selection of appropriate variables from satellite information and physical variables is important for precise AGB prediction mapping. Because of the complex relationships for AGB prediction, non-parametric machine-learning techniques represent potentially useful techniques for AGB estimation, but their use and comparison in forest remote-sensing applications is still relatively limited. The objective of the present study was to evaluate the performance of automatic learning techniques, support vector regression (SVR) and random forest (RF), to predict the observed AGB (from 318 permanent sampling plots) from the Landsat 8 Landsat 8 Operational Land Imager (OLI) sensor, spectral indexes, texture indexes and physical variables the Sierra Madre Occidental in Mexico. The result showed that the best SVR model explained 80% of the total variance (root mean square error (RMSE) = 8.20 Mg ha−1). The variables that best predicted AGB, in order of importance, were the bands that belong to the region of red and near and middle infrared, and the average temperature. The results show that the SVR technique has a good potential for the estimation of the AGB and that the selection of the model hyperparameters has important implications for optimizing the goodness of fit.

Various different factors have led to the accumulation of biomass in forest soils in the Mediterranean-climate region in the last few decades, thus exacerbating the effects of wildfires. Although prescribed burning is used to decrease the fuel load and reduce the currency of mega-wildfires, the impacts on soil organic matter (SOM) and nutrient cycling, and therefore on forest ecosystem sustainability, are uncertain. The present study was designed to cover a range of conditions and therefore to assess the variability in the responses in similar geographical areas. Three prescribed burning treatments producing different levels of soil burn severity were conducted in two different types of forests (Pinus nigra and Pinus pinaster) and one (previously treated by prescribed burning) shrubland ecosystem (Cytisus oromediterraneus), all characterized by different fuel loads and depths of soil organic layer, in Central Spain. After the treatments, the SOM content, its thermal properties, and the distribution of Phosphorus (P) forms (P-31 NMR spectroscopy) were measured in the soil organic layer and mineral soils (0-2 cm depth), and the results were related to the temperatures reached. The prescribed burning les to low-moderate perturbations in SOM quality and Carbon (C) and P dynamics. The organic P, which in the unburnt plots represented 70% of the extractable P, was greatly depleted (by 56 and 95% with respect the initials values). This effect was concurrent with decreases in the most thermolabile SOM fractions, suggesting that organic P is readily mineralized, even at relatively low temperatures. Release of large amounts of soluble orthophosphate may occur when the prescribed burning leads to a high level of soil burn severity. The findings show that prescribed burning treatments should be planned carefully in order to prevent long-term perturbation of C and P cycling.

PURPOSE:To compare the effectiveness of octreotide/everolimus vs. sunitinib for the systemic treatment of recurrent aggressive meningiomas.METHODS:31 patients with recurrent or refractory WHO II or WHO III meningiomas were examined in two reference centers in Colombia. Patients who had systemic treatment (sunitinib, everolimus/octreotide) and a complete follow-up were included. Overall survival (OS), progression-free survival (PFS) and toxicities were evaluated. Additionally, tissue samples were examined for PDGFRβ and VEGFR2, their expression was correlated with outcomes.RESULTS:Twenty-two patients (72%) were female with a median age of 55 years (SD±15.3). The most prevalent histology was anaplastic meningioma in 20 patients (65%) with 48% of patients suffering from three previous relapses before the start of systemic treatment. A total of 14 patients received combination therapy with octreotide/everolimus, 11 received sunitinib and the remaining 6 received other second-line agents. Median OS was 37.3 months (95%CI 28.5-42.1) and the PFS during the treatment with everolimus/octreotide (EO) and sunitinib (Su) was 12.1 months (95%CI 9.2-21.1) and 9.1 months (95%CI 6.8-16.8); p = 0.43), respectively. The OS of the group treated with the EO→Su→Bev sequence (1st/2nd/3rd line) was 6.5 months longer than the Su→EO→Bev sequence (36.0 vs. 29.5 months) (p = 0.0001). When analyzing molecular markers, the positive PDGFRβ and negative VEGFR2 expression were associated with longer survival both in OS and PFS.CONCLUSION:Sunitinib and octreotide/everolimus have similar efficacy and safety in the systemic management of refractory meningioma. VEGFR2 and PDGFRβ expression are associated with better outcomes.

Understanding the temporal patterns of fire occurrence and their relationships with fuel dryness is key to sound fire management, especially under increasing global warming. At present, no system for prediction of fire occurrence risk based on fuel dryness conditions is available in Mexico. As part of an ongoing national-scale project, we developed an operational fire risk mapping tool based on satellite and weather information. We demonstrated how differing monthly temporal trends in a fuel greenness index, dead ratio (DR), and fire density (FDI) can be clearly differentiated by vegetation type and region for the whole country, using MODIS satellite observations for the period 2003 to 2014. We tested linear and non-linear models, including temporal autocorrelation terms, for prediction of FDI from DR for a total of 28 combinations of vegetation types and regions. In addition, we developed seasonal autoregressive integrated moving average (ARIMA) models for forecasting DR values based on the last observed values. Most ARIMA models showed values of the adjusted coefficient of determination (R2 adj) above 0.7 to 0.8, suggesting potential to forecast fuel dryness and fire occurrence risk conditions. The best fitted models explained more than 70% of the observed FDI variation in the relation between monthly DR and fire density. These results suggest that there is potential for the DR index to be incorporated in future fire risk operational tools. However, some vegetation types and regions show lower correlations between DR and observed fire density, suggesting that other variables, such as distance and timing of agricultural burn, deserve attention in future studies.

Se expone el caso de una mujer de 19 años a quien se le realizó el diagnóstico de un xantoastrocitoma pleomórfico anaplásico parietooccipital izquierdo, neoplasia poco frecuente que suele presentarse en la población pediátrica y en los adultos jóvenes. Dicho tumor debuta generalmente con crisis convulsivas y sus características histológicas patognomónicas son el pleomorfismo celular, la vacuolización lipídica de su citoplasma y la reactividad a la proteína ácida fibrilar glial (PAFG) y S100. El estudio de nuevos marcadores que puedan brindar otras oportunidades terapéuticas ha permitido encontrar mutaciones en el oncogén BRAF. Este tumor presenta una variante anaplásica más agresiva que se trata con cirugía y quimiorradiación. En nuestro caso, después de varias progresiones a otras intervenciones, se utilizó bevacizumab y carmustine como tratamiento de segunda línea con respuesta completa.

Understanding the linkage between accumulated fuel dryness and temporal fire occurrence risk is key for improving decision-making in forest fire management, especially under growing conditions of vegetation stress associated with climate change. This study addresses the development of models to predict the number of 10-day observed Moderate-Resolution Imaging Spectroradiometer (MODIS) active fire hotspots—expressed as a Fire Hotspot Density index (FHD)—from an Accumulated Fuel Dryness Index (AcFDI), for 17 main vegetation types and regions in Mexico, for the period 2011–2015. The AcFDI was calculated by applying vegetation-specific thresholds for fire occurrence to a satellite-based fuel dryness index (FDI), which was developed after the structure of the Fire Potential Index (FPI). Linear and non-linear models were tested for the prediction of FHD from FDI and AcFDI. Non-linear quantile regression models gave the best results for predicting FHD using AcFDI, together with auto-regression from previously observed hotspot density values. The predictions of 10-day observed FHD values were reasonably good with R2 values of 0.5 to 0.7 suggesting the potential to be used as an operational tool for predicting the expected number of fire hotspots by vegetation type and region in Mexico. The presented modeling strategy could be replicated for any fire danger index in any region, based on information from MODIS or other remote sensors.