Search Results (25)

Background/Objectives: Low back pain is one of the most prevalent pathologies. Several studies relate its chronification to certain psycho-emotional characteristics, such as self-efficacy or the patient’s lack of confidence in the ability to move. Determine the reliability and validity of the OPTIMAL-confidence scale in people with chronic low back pain and describe the confidence in the movement capacity of this population. Methods: Design: A validation study was designed to evaluate the psychometric properties of the OPTIMAL-Confidence Questionnaire in a population with chronic low back pain. A descriptive observational study in a population with chronic low back pain and a healthy population was designed to describe the confidence in the movement capacity of the population with chronic low back pain. Settings: Health centers of primary care from a region of northwestern Spain. Participants: The final sample was 122 patients diagnosed with chronic low back pain. The sampling was completed with 30 additional healthy subjects. Instruments: OPTIMAL-confidence questionnaire, Numerical Pain Rating Scale, Chronic Pain Self-efficacy Scale, and ad hoc questionnaire to collect socio-demographic and clinical variables. Results: Cronbach’s alpha for the OPTIMAL-confidence questionnaire was 0.91. The association of OPTIMAL-confidence with the self-efficacy, pain intensity, and movement ability scales was moderate and significant (p < 0.001). Regarding the low back pain population, significant differences were observed in confidence levels according to age and the need for walking aids (p < 0.009). The OPTIMAL-confidence questionnaire also showed significant discrimination between the low back pain group and the no back pain group (p < 0.001). The confidence interval was 95%. Conclusions: The population with low back pain shows less confidence in their ability to perform movements, compared to the general population. OPTIMAL is an instrument that can discriminate between patients who present chronic low back pain and those who do not. Full article

We propose a novel mono-temporal framework with a physical basis and ecological consistency to retrieve fire severity at very high spatial resolution. First, we sampled the Composite Burn Index (CBI) in 108 field plots that were subsequently surveyed through unmanned aerial vehicle (UAV) flights. Then, we mimicked the field methodology for CBI assessment in the remote sensing framework. CBI strata were identified through individual tree segmentation and geographic object-based image analysis (GEOBIA). In each stratum, wildfire ecological effects were estimated through the following methods: (i) the vertical structural complexity of vegetation legacies was computed from 3D-point clouds, as a proxy for biomass consumption; and (ii) the vegetation biophysical variables were retrieved from multispectral data by the inversion of the PROSAIL radiative transfer model, with a direct physical link with the vegetation legacies remaining after canopy scorch and torch. The CBI scores predicted from UAV ecologically related metrics at the strata level featured high fit with respect to the field-measured CBI scores (R² > 0.81 and RMSE < 0.26). Conversely, the conventional retrieval of fire effects using a battery of UAV structural and spectral predictors (point height distribution metrics and spectral indices) computed at the plot level provided a much worse performance (R² = 0.677 and RMSE = 0.349). Full article

Current CLL guidelines recommend a two parallel cultures assessment using TPA and IL2+DSP30 mitogens for complex karyotype (CK) detection. Studies comparing both mitogens for CK identification in the same cohort are lacking. We analyzed the global performance, CK detection, and concordance in the complexity assessment of two cytogenetic cultures from 255 CLL patients. IL2+DSP30 identified more altered karyotypes than TPA (50 vs. 39%, p = 0.031). Moreover, in 71% of those abnormal by both, IL2+DSP30 identified more abnormalities and/or abnormal metaphases. CK detection was similar for TPA and IL2+DSP30 (10% vs. 11%). However, 11/33 CKs (33%) were discordant, mainly due to the detection of a normal karyotype or no metaphases in the other culture. Patients requiring treatment within 12 months after sampling (active CLL) displayed significantly more CKs than those showing a stable disease (55% vs. 12%, p < 0.001). Disease status did not impact cultures’ concordance (κ index: 0.735 and 0.754 for stable and active). Although CK was associated with shorter time to first treatment (TTFT) using both methods, IL2+DSP30 displayed better accuracy than TPA for predicting TTFT (C-index: 0.605 vs. 0.580, respectively). In summary, the analysis of two parallel cultures is the best option to detect CKs in CLL. Nonetheless, IL2+DSP30 could be prioritized above TPA to optimize cytogenetic assessment in clinical practice. Full article

Waldenström Macroglobulinemia (WM) is a lymphoplasmacytic lymphoma with bone marrow (BM) involvement and IgM monoclonal gammopathy. To date, no studies have focused specifically on peripheral blood (PB) involvement. In this study, 100 patients diagnosed with WM according to the World Health Organization (WHO) criteria were included based on the demonstration of MYD88mut in BM and the availability of PB multiparametric flow cytometry (MFC) analysis. Leukemic involvement by MFC was detected in 50/100 patients. A low percentage of mature small lymphocytes in PB smears was observed in only 15 cases. MYD88mut by AS-qPCR was detected in PB in 65/100 cases. In cases with leukemic expression by MFC, MYD88mut was detected in all cases, and IGH was rearranged in 44/49 cases. In 21/50 patients without PB involvement by MFC, molecular data were consistent with circulating disease (MYD88mut by AS-qPCR 3/50, IGH rearranged 6/50, both 12/50). Therefore, PB involvement by standard techniques was detected in 71/100 patients. MYD88mut was detected in PB by dPCR in 9/29 triple negative cases. Overall, 80% of the patients presented PB involvement by any technique. Our findings support the role of PB MFC in the evaluation of patients with IgM monoclonal gammopathy and provide reliable information on correlation with molecular features. The development of a feasible MFC assay may stand as an objective tool in the classification of mature B cell neoplasms presenting with IgM monoclonal gammopathy. Full article

In Southern Europe, the abandonment of the traditional transhumant system where sheep graze lowland areas during winter and distant mountain systems during summer has led to an important cultural loss and still poorly understood ecological consequences. We investigate the landscape-scale implications of contemporary sheep grazing patterns in a Globally Important Agricultural Heritage System (GIAHS). Our analysis showed a heterogeneous use of mountain grazing areas between 1990 and 2020. The areas most used by sheep had more abundance of pasture, fewer forests, and structurally different landscapes than those that had been fully abandoned by sheep. Likewise, we have detected decreasing trends in landscape diversity in those areas not used by sheep over the study period, whereas landscape heterogeneity is maintained in those areas grazed by sheep. Our study constitutes an original analysis of landscape patterns and shifts in relation to extensive sheep grazing by using novel approaches that combine interviews, updated satellite time series, and state-of-the-art landscape analysis techniques. Likewise, our results constitute a benchmark as they inform on the importance of preserving extensive sheep grazing if we aim to maintain the cultural heritage, and traditional diverse landscape and the semi-natural grasslands in the Mountains of León. Full article

Calluna vulgaris-dominated heathlands are a priority habitat type in Annex I of the Habitats Directive (92/43/ECC, habitat code 4060). In the Iberian Peninsula, the landscape of the Cantabrian Mountain range has great heterogeneity due to human management during the last 10,000 years. Another factor that can affect these communities is the increase in human-induced atmospheric nitrogen (N) deposition. During the last century, there has been a dramatic increase in N deposition rates. For all these reasons, it is important to know the regeneration dynamics of the heathlands in the context of the disturbances that these communities currently face (i.e., N deposition, fire, and decrease in sheep grazing) in the Cantabrian Mountain range. In this study, we characterized the plant species composition and soil seed bank after prescribed burning in three heathlands on their southern distribution limit in Spain, to gain insights into regenerative capacity and conservation of these communities. The results obtained suggest that the post-burn soil seed bank could restore Calluna-dominated vegetation in these habitats, indicating that the restoration potential from the soil seed bank after wildfires of these habitats is high. Our results also suggest that, in the short term after burning, the main characteristic species such as Calluna and Erica are recovered, which is fundamental to maintain the heathland community structure. Full article

We aimed to compare the potential of physical-based models (radiative transfer and pixel unmixing models) for evaluating the short-term resilience to fire of several shrubland communities as a function of their regenerative strategy and burn severity. The study site was located within the perimeter of a wildfire that occurred in summer 2017 in the northwestern Iberian Peninsula. A pre- and post-fire time series of Sentinel-2 satellite imagery was acquired to estimate fractional vegetation cover (FVC) from the (i) PROSAIL-D radiative transfer model inversion using the random forest algorithm, and (ii) multiple endmember spectral mixture analysis (MESMA). The FVC retrieval was validated throughout the time series by means of field data stratified by plant community type (i.e., regenerative strategy). The inversion of PROSAIL-D featured the highest overall fit for the entire time series (R² > 0.75), followed by MESMA (R² > 0.64). We estimated the resilience of shrubland communities in terms of FVC recovery using an impact-normalized resilience index and a linear model. High burn severity negatively influenced the short-term resilience of shrublands dominated by facultative seeder species. In contrast, shrublands dominated by resprouters reached pre-fire FVC values regardless of burn severity. Full article

The sideroblastic anemias are a heterogeneous group of inherited and acquired disorders characterized by anemia and the presence of ring sideroblasts in the bone marrow. Ring sideroblasts are abnormal erythroblasts with iron-loaded mitochondria that are visualized by Prussian blue staining as a perinuclear ring of green-blue granules. The mechanisms that lead to the ring sideroblast formation are heterogeneous, but in all of them, there is an abnormal deposition of iron in the mitochondria of erythroblasts. Congenital sideroblastic anemias include nonsyndromic and syndromic disorders. Acquired sideroblastic anemias include conditions that range from clonal disorders (myeloid neoplasms as myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms with ring sideroblasts) to toxic or metabolic reversible sideroblastic anemia. In the last 30 years, due to the advances in genomic techniques, a deep knowledge of the pathophysiological mechanisms has been accomplished and the bases for possible targeted treatments have been established. The distinction between the different forms of sideroblastic anemia is based on the study of the characteristics of the anemia, age of diagnosis, clinical manifestations, and the performance of laboratory analysis involving genetic testing in many cases. This review focuses on the differential diagnosis of acquired disorders associated with ring sideroblasts. Full article

Novel treatments in chronic lymphocytic leukemia (CLL) have generated interest regarding the clinical impact of genomic complexity, currently assessed by chromosome banding analysis (CBA) and chromosomal microarray analysis (CMA). Optical genome mapping (OGM), a novel technique based on imaging of long DNA molecules labeled at specific sites, allows the identification of multiple cytogenetic abnormalities in a single test. We aimed to determine whether OGM is a suitable alternative to cytogenomic assessment in CLL, especially focused on genomic complexity. Cytogenomic OGM aberrations from 42 patients were compared with CBA, FISH, and CMA information. Clinical–biological characteristics and time to first treatment (TTFT) were analyzed according to the complexity detected by OGM. Globally, OGM identified 90.3% of the known alterations (279/309). Discordances were mainly found in (peri-)centromeric or telomeric regions or subclonal aberrations (<15–20%). OGM underscored additional abnormalities, providing novel structural information on known aberrations in 55% of patients. Regarding genomic complexity, the number of OGM abnormalities had better accuracy in predicting TTFT than current methods (C-index: 0.696, 0.602, 0.661 by OGM, CBA, and CMA, respectively). A cut-off of ≥10 alterations defined a complex OGM group (C-OGM, n = 12), which included 11/14 patients with ≥5 abnormalities by CBA/CMA and one patient with chromothripsis (Kappa index = 0.778; p < 0.001). Moreover, C-OGM displayed enrichment of TP53 abnormalities (58.3% vs. 3.3%, p < 0.001) and a significantly shorter TTFT (median: 2 vs. 43 months, p = 0.014). OGM is a robust technology for implementation in the routine management of CLL patients, although further studies are required to define standard genomic complexity criteria. Full article

The degree to which burn severity influences the recovery of aboveground carbon density (ACD) of live pools in shrublands remains unclear. Multitemporal LiDAR data was used to evaluate ACD recovery three years after fire in shrubland ecosystems as a function of burn severity immediately after fire across an environmental and productivity gradient in the western Mediterranean Basin. Two large mixed-severity wildfires were assessed: an Atlantic site, dominated by resprouter shrubs and located at the most productive extreme of the gradient, and a Mediterranean site, dominated by obligate seeders and located at the less productive extreme. Initial assessment of burn severity was performed using the differenced Normalized Burn Ratio index computed from Landsat imagery. Thresholds for low and high burn severity categories were established using the Composite Burn Index (CBI). LiDAR canopy metrics were calibrated with field measurements of mean shrub height and cover at plot level in a post-fire situation. Pre-fire and post-fire ACD estimates, and their ratio (ACDr) to calculate carbon stock recovery, were computed from the predictions of LiDAR grid metrics at landscape level using shrubland allometric relationships. Overall, ACDr decreased both with high burn severity and low productivity, although the burn severity impact was not homogeneous within the gradient. In the Atlantic site, ACDr was similar under low and high burn severity, whereas it decreased with burn severity in the Mediterranean site. These results suggest that carbon cycling models could be biased by not accounting for both fire severity and species composition of shrublands under different environmental conditions. Full article

Iron oxide nanoparticles (IONPs) are suitable materials for contrast enhancement in magnetic resonance imaging (MRI). Their potential clinical applications range from diagnosis to therapy and follow-up treatments. However, a deeper understanding of the interaction between IONPs, culture media and cells is necessary for expanding the application of this technology to different types of cancer therapies. To achieve new insights of these interactions, a set of IONPs were prepared with the same inorganic core and five distinct coatings, to study their aggregation and interactions in different physiological media, as well as their cell labelling efficiency. Then, a second set of IONPs, with six different core sizes and the same coating, were used to study how the core size affects cell labelling and MRI in vitro. Here, IONPs suspended in biological media experience a partial removal of the coating and adhesion of molecules. The FBS concentration alters the labelling of all types of IONPs and hydrodynamic sizes ≥ 300 nm provide the greatest labelling using the centrifugation-mediated internalization (CMI). The best contrast for MRI results requires a core size range between 12–14 nm coated with dimercaptosuccinic acid (DMSA) producing R₂^* values of 393.7 s⁻¹ and 428.3 s⁻¹, respectively. These findings will help to bring IONPs as negative contrast agents into clinical settings. Full article

Understanding biological mechanisms that regulate emergence of viral diseases, in particular those events engaging cross-species pathogens spillover, is becoming increasingly important in virology. Species barrier jumping has been extensively studied in animal viruses, and the critical role of a suitable intermediate host in animal viruses-generated human pandemics is highly topical. However, studies on host jumping involving plant viruses have been focused on shifting intra-species, leaving aside the putative role of “bridge hosts” in facilitating interspecies crossing. Here, we take advantage of several VPg mutants, derived from a chimeric construct of the potyvirus Plum pox virus (PPV), analyzing its differential behaviour in three herbaceous species. Our results showed that two VPg mutations in a Nicotiana clevelandii-adapted virus, emerged during adaptation to the bridge-host Arabidopsis thaliana, drastically prompted partial adaptation to Chenopodium foetidum. Although both changes are expected to facilitate productive interactions with eIF(iso)4E, polymorphims detected in PPV VPg and the three eIF(iso)4E studied, extrapolated to a recent VPg:eIF4E structural model, suggested that two adaptation ways can be operating. Remarkably, we found that VPg mutations driving host-range expansion in two non-related species, not only are not associated with cost trade-off constraints in the original host, but also improve fitness on it. Full article

Heterogeneous and patchy landscapes where vegetation and abiotic factors vary at small spatial scale (fine-grained landscapes) represent a challenge for habitat diversity mapping using remote sensing imagery. In this context, techniques of spectral mixture analysis may have an advantage over traditional methods of land cover classification because they allow to decompose the spectral signature of a mixed pixel into several endmembers and their respective abundances. In this work, we present the application of Multiple Endmember Spectral Mixture Analysis (MESMA) to quantify habitat diversity and assess the compositional turnover at different spatial scales in the fine-grained landscapes of the Cantabrian Mountains (northwestern Iberian Peninsula). A Landsat-8 OLI scene and high-resolution orthophotographs (25 cm) were used to build a region-specific spectral library of the main types of habitats in this region (arboreal vegetation; shrubby vegetation; herbaceous vegetation; rocks–soil and water bodies). We optimized the spectral library with the Iterative Endmember Selection (IES) method and we applied MESMA to unmix the Landsat scene into five fraction images representing the five defined habitats (root mean square error, RMSE ≤ 0.025 in 99.45% of the pixels). The fraction images were validated by linear regressions using 250 reference plots from the orthophotographs and then used to calculate habitat diversity at the pixel (α-diversity: 30 × 30 m), landscape (γ-diversity: 1 × 1 km) and regional (ε-diversity: 110 × 33 km) scales and the compositional turnover (β- and δ-diversity) according to Simpson’s diversity index. Richness and evenness were also computed. Results showed that fraction images were highly related to reference data (R² ≥ 0.73 and RMSE ≤ 0.18). In general, our findings indicated that habitat diversity was highly dependent on the spatial scale, with values for the Simpson index ranging from 0.20 ± 0.22 for α-diversity to 0.60 ± 0.09 for γ-diversity and 0.72 ± 0.11 for ε-diversity. Accordingly, we found β-diversity to be higher than δ-diversity. This work contributes to advance in the estimation of ecological diversity in complex landscapes, showing the potential of MESMA to quantify habitat diversity in a comprehensive way using Landsat imagery. Full article

The evaluation of the effect of burn severity on forest soils is essential to determine the impact of wildfires on a range of key ecological processes, such as nutrient cycling and vegetation recovery. The main objective of this study was to assess the potentiality of different spectral products derived from RGB and multispectral imagery collected by unmanned aerial vehicles (UAVs) at very high spatial resolution for discriminating spatial variations in soil burn severity after a heterogeneous wildfire. In the case study, we chose a mixed-severity fire that occurred in the northwest (NW) of the Iberian Peninsula (Spain) in 2019 that affected 82.74 ha covered by three different types of forests, each dominated by Pinus pinaster, Pinus sylvestris, and Quercus pyrenaica. We evaluated soil burn severity in the field 1 month after the fire using the Composite Burn Soil Index (CBSI), as well as a pool of five individual indicators (ash depth, ash cover, fine debris cover, coarse debris cover, and unstructured soil depth) of easy interpretation. Simultaneously, we operated an unmanned aerial vehicle to obtain RGB and multispectral postfire images, allowing for deriving six spectral indices. Then, we explored the relationship between spectral indices and field soil burn severity metrics by means of univariate proportional odds regression models. These models were used to predict CBSI categories, and classifications were validated through confusion matrices. Results indicated that multispectral indices outperformed RGB indices when assessing soil burn severity, being more strongly related to CBSI than to individual indicators. The Normalized Difference Water Index (NDWI) was the best-performing spectral index for modelling CBSI (R²cv = 0.69), showing the best ability to predict CBSI categories (overall accuracy = 0.83). Among the individual indicators of soil burn severity, ash depth was the one that achieved the best results, specifically when it was modelled from NDWI (R²cv = 0.53). This work provides a useful background to design quick and accurate assessments of soil burn severity to be implemented immediately after the fire, which is a key factor to identify priority areas for emergency actions after forest fires. Full article