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  • 1
    Online Resource
    Online Resource
    Osmolyte Signatures for the Protection of Aspergillus sydowii Cells under Halophilic Conditions and Osmotic Shock
    MDPI AG ; 2021
    In:  Journal of Fungi Vol. 7, No. 6 ( 2021-05-26), p. 414-
    Details
    In: Journal of Fungi, MDPI AG, Vol. 7, No. 6 ( 2021-05-26), p. 414-
    Abstract: Aspergillus sydowii is a moderate halophile fungus extensively studied for its biotechnological potential and halophile responses, which has also been reported as a coral reef pathogen. In a recent publication, the transcriptomic analysis of this fungus, when growing on wheat straw, showed that genes related to cell wall modification and cation transporters were upregulated under hypersaline conditions but not under 0.5 M NaCl, the optimal salinity for growth in this strain. This led us to study osmolyte accumulation as a mechanism to withstand moderate salinity. In this work, we show that A. sydowii accumulates trehalose, arabitol, mannitol, and glycerol with different temporal dynamics, which depend on whether the fungus is exposed to hypo- or hyperosmotic stress. The transcripts coding for enzymes responsible for polyalcohol synthesis were regulated in a stress-dependent manner. Interestingly, A. sydowii contains three homologs (Hog1, Hog2 and MpkC) of the Hog1 MAPK, the master regulator of hyperosmotic stress response in S. cerevisiae and other fungi. We show a differential regulation of these MAPKs under different salinity conditions, including sustained basal Hog1/Hog2 phosphorylation levels in the absence of NaCl or in the presence of 2.0 M NaCl, in contrast to what is observed in S. cerevisiae. These findings indicate that halophilic fungi such as A. sydowii utilize different osmoadaptation mechanisms to hypersaline conditions.
    Type of Medium: Online Resource
    ISSN: 2309-608X
    URL: Article
    DOI: 10.3390/jof7060414
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2784229-0
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  • 2
    Online Resource
    Online Resource
    The Second Derivative of the NDVI Time Series as an Estimator of Fresh Biomass: A Case Study of Eight Forage Associations Monitored via UAS
    MDPI AG ; 2023
    In:  Drones Vol. 7, No. 6 ( 2023-05-26), p. 347-
    Details
    In: Drones, MDPI AG, Vol. 7, No. 6 ( 2023-05-26), p. 347-
    Abstract: The estimation of crop yield is a compelling and highly relevant task in the scenario of the challenging climate change we are facing. With this aim, a reinterpretation and a simplification of the Food and Agriculture Organization (FAO) fundamentals are presented to calculate the fresh biomass of forage crops. A normalized difference vegetation index (NDVI) series observed from a multispectral camera on board an unmanned aircraft system (UAS) was the basis for the estimation. Eight fields in Spain of different rainfed intercropping forages were flown over simultaneously, with eight field measurements from February to June 2020. The second derivative applied to the NDVI time series determined the key points of the growing cycle, whereas the NDVI values themselves were integrated and multiplied by a standardized value of the normalized water productivity (WP*). The scalability of the method was tested using two scales of the NDVI values: the point scale (at the precise field measurement location) and the plot scale (mean of 400 m2). The resulting fresh biomass and, therefore, the proposal were validated against a dataset of field-observed benchmarks during the field campaign. The agreement between the estimated and the observed fresh biomass afforded a very good prediction in terms of the determination coefficient (R2, that ranged from 0.17 to 0.85) and the agreement index (AI, that ranged from 0.55 to 0.90), with acceptable estimation errors between 10 and 30%. The best period to estimate fresh biomass was found to be between the second fortnight of April and the first fortnight of May.
    Type of Medium: Online Resource
    ISSN: 2504-446X
    URL: Article
    DOI: 10.3390/drones7060347
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2934569-8
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  • 3
    Online Resource
    Online Resource
    Multi-Temporal Dual- and Quad-Polarimetric Synthetic Aperture Radar Data for Crop-Type Mapping
    MDPI AG ; 2019
    In:  Remote Sensing Vol. 11, No. 13 ( 2019-06-27), p. 1518-
    Details
    In: Remote Sensing, MDPI AG, Vol. 11, No. 13 ( 2019-06-27), p. 1518-
    Abstract: Land-cover monitoring is one of the core applications of remote sensing. Monitoring and mapping changes in the distribution of agricultural land covers provide a reliable source of information that helps environmental sustainability and supports agricultural policies. Synthetic Aperture Radar (SAR) can contribute considerably to this monitoring effort. The first objective of this research is to extend the use of time series of polarimetric data for land-cover classification using a decision tree classification algorithm. With this aim, RADARSAT-2 (quad-pol) and Sentinel-1 (dual-pol) data were acquired over an area of 600 km2 in central Spain. Ten polarimetric observables were derived from both datasets and seven scenarios were created with different sets of observables to evaluate a multitemporal parcel-based approach for classifying eleven land-cover types, most of which were agricultural crops. The study demonstrates that good overall accuracies, greater than 83%, were achieved for all of the different proposed scenarios and the scenario with all RADARSAT-2 polarimetric observables was the best option (89.1%). Very high accuracies were also obtained when dual-pol data from RADARSAT-2 or Sentinel-1 were used to classify the data, with overall accuracies of 87.1% and 86%, respectively. In terms of individual crop accuracy, rapeseed achieved at least 95% of a producer’s accuracy for all scenarios and that was followed by the spring cereals (wheat and barley), which achieved high producer’s accuracies (79.9%-95.3%) and user’s accuracies (85.5% and 93.7%).
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs11131518
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2513863-7
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  • 4
    Online Resource
    Online Resource
    Fusion of Multi-Temporal PAZ and Sentinel-1 Data for Crop Classification
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 19 ( 2021-09-30), p. 3915-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 19 ( 2021-09-30), p. 3915-
    Abstract: The accurate identification of crops is essential to help environmental sustainability and support agricultural policies. This study presents the use of a Spanish radar mission, PAZ, to classify agricultural areas with a very high spatial resolution. PAZ was recently launched, and it operates at X band, joining the synthetic aperture radar (SAR) constellation along with TerraSAR-X and TanDEM-X satellites. Owing to its novelty and its ability to classify crop areas (both taking individually its time series and blending with the Sentinel-1 series), it has been tested in an agricultural area of the central-western part of Spain during 2020. The random forest algorithm was selected to classify the time series under five alternatives of standalone/fused data. The map accuracy resulting from the PAZ series standalone was acceptable, but it highlighted the need for a denser time-series of data. The overall accuracy provided by eight PAZ images or by eight Sentinel-1 images was below 60%. The fusion of both sets of eight images improved the overall accuracy by more than 10%. In addition, the exploitation of the whole Sentinel-1 series, with many more observations (up to 40 in the same temporal window) improved the results, reaching an overall accuracy around 76%. This overall performance was similar to that obtained by the joint use of all the available images of the two frequency bands (C and X).
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13193915
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 5
    Online Resource
    Online Resource
    Haloadaptative Responses of Aspergillus sydowii to Extreme Water Deprivation: Morphology, Compatible Solutes, and Oxidative Stress at NaCl Saturation
    MDPI AG ; 2020
    In:  Journal of Fungi Vol. 6, No. 4 ( 2020-11-27), p. 316-
    Details
    In: Journal of Fungi, MDPI AG, Vol. 6, No. 4 ( 2020-11-27), p. 316-
    Abstract: Water activity (aw) is critical for microbial growth, as it is severely restricted at aw 〈 0.90. Saturating NaCl concentrations (~5.0 M) induce extreme water deprivation (aw ≅ 0.75) and cellular stress responses. Halophilic fungi have cellular adaptations that enable osmotic balance and ionic/oxidative stress prevention to grow at high salinity. Here we studied the morphology, osmolyte synthesis, and oxidative stress defenses of the halophile Aspergillus sydowii EXF-12860 at 1.0 M and 5.13 M NaCl. Colony growth, pigmentation, exudate, and spore production were inhibited at NaCl-saturated media. Additionally, hyphae showed unpolarized growth, lower diameter, and increased septation, multicellularity and branching compared to optimal NaCl concentration. Trehalose, mannitol, arabitol, erythritol, and glycerol were produced in the presence of both 1.0 M and 5.13 M NaCl. Exposing A. sydowii cells to 5.13 M NaCl resulted in oxidative stress evidenced by an increase in antioxidant enzymes and lipid peroxidation biomarkers. Also, genes involved in cellular antioxidant defense systems were upregulated. This is the most comprehensive study that investigates the micromorphology and the adaptative cellular response of different non-enzymatic and enzymatic oxidative stress biomarkers in halophilic filamentous fungi.
    Type of Medium: Online Resource
    ISSN: 2309-608X
    URL: Article
    DOI: 10.3390/jof6040316
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2784229-0
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  • 6
    Online Resource
    Online Resource
    UAV Multispectral Imaging Potential to Monitor and Predict Agronomic Characteristics of Different Forage Associations
    MDPI AG ; 2021
    In:  Agronomy Vol. 11, No. 9 ( 2021-08-25), p. 1697-
    Details
    In: Agronomy, MDPI AG, Vol. 11, No. 9 ( 2021-08-25), p. 1697-
    Abstract: The capability of UAVs imagery to monitor and predict the evolution of several forage associations was assessed during the whole growing cycle of 2019–20. For this purpose, eight different forage associations grown in triplicate were used: vetch-barley-triticale (VBT), vetch-triticale (VT), vetch-rye (VR), vetch-oats (VO), pea-barley-triticale (PBT), pea-triticale (PT), pea-rye (PR) and pea-oats (PO). Six biophysical parameters were monitored through six vegetation indices on seven measurements dates distributed along the growing cycle. The experiments were carried out on the organic farm “Gallegos de Crespes” located in the municipality of Larrodrigo (Salamanca, Spain). The results obtained in the exploratory and the correlation analysis suggested that a predictive model (PLS regression) could be performed. Overall, vetch-based associations showed slightly higher values for both the field parameters and the vegetation indices than pea-based ones. Correlations were very strong and significant for each association throughout their growing cycle, suggesting that the evolution of the associations would be monitored from the spectral indices. Integrating these multispectral observations in the PLS model, the agronomic parameters of forage associations were predicted with a reliability of more than 50%. A single combination of VNIR (or even only visible) bands was able to feed the regression model, leading to a successful prediction of the agronomic parameters.
    Type of Medium: Online Resource
    ISSN: 2073-4395
    URL: Article
    DOI: 10.3390/agronomy11091697
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2607043-1
    SSG: 23
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  • 7
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    Online Resource
    Breast and Colorectal Cancer Screening Utilization after Hurricane María and the COVID-19 Pandemic in Puerto Rico
    MDPI AG ; 2023
    In:  International Journal of Environmental Research and Public Health Vol. 20, No. 19 ( 2023-10-01), p. 6870-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 20, No. 19 ( 2023-10-01), p. 6870-
    Abstract: Puerto Rico (PR) has faced environmental and public health challenges that could have significantly affected cancer screening access. Using administrative claims data from PR’s Medicaid population, this study assessed trends in colorectal and breast cancer screening from 2016 to 2021, the impact of disasters in screening, and the absolute deficit in screening due to the pandemic. The monthly rates of claims were analyzed using Poisson regression. Significant reductions in breast and colorectal cancer screening utilization were observed. The colorectal cancer screening rate in 2017 was 77% lower a month after Hurricanes Irma and María [RRadj: 0.23; 95% CI: 0.20, 0.25] compared to the same time period in 2016. Breast cancer screening dropped 50% in November 2017 compared to November 2016 [RRadj: 0.50; 95% CI: 0.47, 0.54] . Prospectively, a recovery in utilization has been observed only for breast cancer screening. The results revealed that cancer screening utilization substantially declined after environmental disasters and the pandemic. These findings have potentially severe long-term implications for cancer health disparities and mortality in PR.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph20196870
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2175195-X
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  • 8
    Online Resource
    Online Resource
    Temporal and Spatial Comparison of Agricultural Drought Indices from Moderate Resolution Satellite Soil Moisture Data over Northwest Spain
    MDPI AG ; 2017
    In:  Remote Sensing Vol. 9, No. 11 ( 2017-11-14), p. 1168-
    Details
    In: Remote Sensing, MDPI AG, Vol. 9, No. 11 ( 2017-11-14), p. 1168-
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs9111168
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2513863-7
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  • 9
    Online Resource
    Online Resource
    Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical Techniques
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 3 ( 2022-01-27), p. 614-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 3 ( 2022-01-27), p. 614-
    Abstract: This paper aims to both fit and predict crop biophysical variables with a SAR image series by performing a factorial experiment and estimating time series models using a combination of forecasts. Two plots of barley grown under rainfed conditions in Spain were monitored during the growing cycle of 2015 (February to June). The dataset included nine field estimations of agronomic parameters, 20 RADARSAT-2 images, and daily weather records. Ten polarimetric observables were retrieved and integrated to derive the six agronomic and monitoring variables, including the height, biomass, fraction of vegetation cover, leaf area index, water content, and soil moisture. The statistical methods applied, namely double smoothing, ARIMAX, and robust regression, allowed the adjustment and modelling of these field variables. The model equations showed a positive contribution of meteorological variables and a strong temporal component in the crop’s development, as occurs in natural conditions. After combining different models, the results showed the best efficiency in terms of forecasting and the influence of several weather variables. The existence of a cointegration relationship between the data series of the same crop in different fields allows for adjusting and predicting the results in other fields with similar crops without re-modelling.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14030614
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2513863-7
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  • 10
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    Online Resource
    Lyme Disease: A Review with Emphasis on Latin America
    MDPI AG ; 2024
    In:  Microorganisms Vol. 12, No. 2 ( 2024-02-13), p. 385-
    Details
    In: Microorganisms, MDPI AG, Vol. 12, No. 2 ( 2024-02-13), p. 385-
    Abstract: The spirochete Borrelia burgdorferi sensu lato (Lyme Group) is the causative agent of Lyme disease, transmitted to humans through tick bites carrying the bacteria. Common symptoms include fever, headache, fatigue, and the characteristic erythema migrans skin rash. If left untreated, the infection can affect joints, the cardiac system, and the nervous system. Diagnosis relies on symptoms, clinical signs (such as the rash), and potential exposure to infected ticks, with laboratory tests proving valuable when appropriately employed with validated methods. Most cases of Lyme disease respond effectively to a few weeks of antibiotic treatment. In Latin America, knowledge of Lyme disease is limited and often confounded, underscoring the significance of this review in aiding medical professionals in recognizing the disease. This study delves explicitly into Lyme disease in Argentina, neighboring countries, and other Latin American nations.
    Type of Medium: Online Resource
    ISSN: 2076-2607
    URL: Article
    DOI: 10.3390/microorganisms12020385
    Language: English
    Publisher: MDPI AG
    Publication Date: 2024
    detail.hit.zdb_id: 2720891-6
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