Search

Terrestrial laser scanning (TLS) has become a vital tool in forestry for accurately measuring tree parameters, such as diameter at breast height (DBH). However, its application in Mexican forests remains underexplored. This study evaluates the performance of five two-dimensional DBH estimation algorithms (Nelder–Mead, least squares, Hough transform, RANSAC, and convex hull) within a temperate Mexican forest and explores their broader applicability across diverse ecosystems, using published point cloud data from various scanning devices. Results indicate that algorithm accuracy is influenced by local factors like point cloud density, occlusion, vegetation, and tree structure. In the Mexican study area, the Nelder–Mead algorithm achieved the highest accuracy (R² = 0.98, RMSE = 1.59 cm, MAPE = 6.12%), closely followed by least squares (R² = 0.98, RMSE = 1.67 cm, MAPE = 6.42%), with different outcomes in other sites. These findings advance DBH estimation methods by highlighting the importance of tailored algorithm selection and environmental considerations, thereby contributing to more accurate and efficient forest management across various landscapes. [ABSTRACT FROM AUTHOR]

The olive fruit is a drupe whose development and ripening takes several months from flowering to full maturation. During this period, several biochemical and physiological changes occur that affect the skin color, texture, composition, and size of the mesocarp. The final result is a fruit rich in fatty acids, phenolic compounds, tocopherols, pigments, sterols, terpenoids, and other compounds of nutritional interest. In this work, a transcriptomic analysis was performed using flowers (T0) and mesocarp tissue at seven different stages during olive fruit development and ripening (T1–T7) of the 'Picual' cultivar. A total of 1755 genes overexpressed at any time with respect to the flowering stage were further analyzed. These genes were grouped into eight clusters based on their expression profile. The gene enrichment analysis revealed the most relevant biological process of every cluster. Highlighting the important role of hormones at very early stages of fruit development (T1, Cluster 1), whereas genes involved in fatty acid biosynthesis were relevant throughout the fruit developmental process. Hence, genes coding for different fatty acid desaturase (SAD, FAD2, FAD3, FAD4, FAD5, FAD6, and FAD7) enzymes received special attention. In particular, 26 genes coding for different fatty acid desaturase enzymes were identified in the 'Picual' genome, contributing to the improvement of the genome annotation. The expression pattern of these genes during fruit development corroborated their role in determining fatty acid composition. [ABSTRACT FROM AUTHOR]

The rise in cyanobacterial blooms due to eutrophication and climate change has increased cyanotoxin presence in water. Most current water treatment plants do not effectively remove these toxins, posing a potential risk to public health. This study introduces a water treatment approach using nanostructured beads containing magnetic nanoparticles (MNPs) for easy removal from liquid suspension, coated with different adsorbent materials to eliminate cyanotoxins. Thirteen particle types were produced using activated carbon, CMK-3 mesoporous carbon, graphene, chitosan, 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-oxidised cellulose nanofibers (TOCNF), esterified pectin, and calcined lignin as an adsorbent component. The particles' effectiveness for detoxification of microcystin-LR (MC-LR), cylindrospermopsin (CYN), and anatoxin-A (ATX-A) was assessed in an aqueous solution. Two particle compositions presented the best adsorption characteristics for the most common cyanotoxins. In the conditions tested, mesoporous carbon nanostructured particles, P1-CMK3, provide good removal of MC-LR and Merck-activated carbon nanostructured particles, P9-MAC, can remove ATX-A and CYN with high and fair efficacy, respectively. Additionally, in vitro toxicity of water treated with each particle type was evaluated in cultured cell lines, revealing no alteration of viability in human renal, neuronal, hepatic, and intestinal cells. Although further research is needed to fully characterise this new water treatment approach, it appears to be a safe, practical, and effective method for eliminating cyanotoxins from water. [ABSTRACT FROM AUTHOR]

Simple Summary: This HEMATO-MADRID COVID-19 study assessed COVID-19 outcomes in 1818 hematologic cancer patients from February 2020 to October 2022 across different phases, including the Omicron period. Severe cases were more common in patients over 70 years with comorbidities or chronic lymphocytic leukemia. However, during the Omicron period, rates of severe illness reduced notably, especially among vaccinated individuals. Hospitalization, intensive care admissions, and overall mortality decreased in the Omicron phase compared to pre-Omicron, yet mortality rates in hospitalized patients remained high. Older age consistently correlated with higher mortality risk in both phases. Factors like prior stem cell transplantation, vaccination, and specific treatments were linked to improved survival rates among hematologic cancer patients facing COVID-19. A greater understanding of clinical trends in COVID-19 outcomes among patients with hematologic malignancies (HM) over the course of the pandemic, particularly the Omicron era, is needed. This ongoing, observational, and registry-based study with prospective data collection evaluated COVID-19 clinical severity and mortality in 1818 adult HM patients diagnosed with COVID-19 between 27 February 2020 and 1 October 2022, at 31 centers in the Madrid region of Spain. Of these, 1281 (70.5%) and 537 (29.5%) were reported in the pre-Omicron and Omicron periods, respectively. Overall, patients aged ≥70 years (odds ratio 2.16, 95% CI 1.64–2.87), with >1 comorbidity (2.44, 1.85–3.21), or with an underlying HM of chronic lymphocytic leukemia (1.64, 1.19–2.27), had greater odds of severe/critical COVID-19; odds were lower during the Omicron BA.1/BA.2 (0.28, 0.2–0.37) or BA.4/BA.5 (0.13, 0.08–0.19) periods and among patients vaccinated with one or two (0.51, 0.34–0.75) or three or four (0.22, 0.16–0.29) doses. The hospitalization rate (75.3% [963/1279], 35.7% [191/535]), rate of intensive care admission (30.0% [289/963], 14.7% [28/191]), and mortality rate overall (31.9% [409/1281], 9.9% [53/536]) and in hospitalized patients (41.3% [398/963], 22.0% [42/191]) decreased from the pre-Omicron to Omicron period. Age ≥70 years was the only factor associated with higher mortality risk in both the pre-Omicron (hazard ratio 2.57, 95% CI 2.03–3.25) and Omicron (3.19, 95% CI 1.59–6.42) periods. Receipt of prior stem cell transplantation, COVID-19 vaccination(s), and treatment with nirmatrelvir/ritonavir or remdesivir were associated with greater survival rates. In conclusion, COVID-19 mortality in HM patients has decreased considerably in the Omicron period; however, mortality in hospitalized HM patients remains high. Specific studies should be undertaken to test new treatments and preventive interventions in HM patients. [ABSTRACT FROM AUTHOR]

We studied the correspondence between historical series of tree-ring width (TRW) and the normalized difference vegetation index (NDVI, i.e., greenness index) values acquired monthly over an entire year by unmanned aerial vehicles. Dendrochronological techniques revealed differentiated responses between species and seasonality. Pinus engelmannii Carrière and Juniperus deppeana Steudel were affected by warm temperatures (TMAX) during the winter prior to growth and benefited from precipitation (PP) during the seasons prior to the spring period. The standardized precipitation–evapotranspiration index (SPEI) confirmed the high sensitivity of P. engelmannii to drought (r = 0.7 SPEI). Quercus grisea Liebm. presented a positive association with PP at the beginning and end of its growth season. Monthly NDVI data at the individual tree level in the three species (NDVI ~0.37–0.48) statistically confirmed the temporal differences. Q. grisea showed a drastic decrease during the dry season (NDVI = 0.1) that had no impact on drought sensitivity in the same period, according to the climate-TRW relationship. We conclude that a relationship is plausible between the crown greenness index and radial growth, although more extended temporal windows of the NDVI should be explored. Differences in susceptibility to drought found among the species would presumably have implications for the composition of these forests under drought scenarios. [ABSTRACT FROM AUTHOR]

There is a need to convert fire danger indices into operational estimates of fire activity to support strategic fire management, particularly under climate change. Few studies have evaluated multiple accumulation times for indices that combine both dead and remotely sensed estimates of live fuel moisture, and relatively few studies have aimed at predicting fire activity from both such fuel moisture estimates and autoregressive terms of previous fires. The current study aimed at developing models to forecast the 10-day number of fires by state in Mexico, from an accumulated Fuel Dryness Index (FDI) and an autoregressive term from the previous 10-day observed number of fires. A period of 50 days of accumulated FDI (FDI50) provided the best results to forecast the 10-day number of fires from each state. The best predictions (R2 > 0.6–0.75) were obtained in the largest states, with higher fire activity, and the lower correlations were found in small or very dry states. Autoregressive models showed good skill (R2 of 0.99–0.81) to forecast FDI50 for the next 10 days based on previous fuel dryness observations. Maps of the expected number of fires showed potential to reproduce fire activity. Fire predictions might be enhanced with gridded weather forecasts in future studies. [ABSTRACT FROM AUTHOR]

The knowledge of the effects of fuel dryness on fire occurrence is critical for sound forest fire management planning, particularly in a changing climate. This study aimed to analyze the monthly distributions of MODIS active fire (AF) detections and their relationships with a fuel dryness index (FDI) based on satellite-derived weather and vegetation greenness. Monthly AF distributions showed unimodal distributions against FDI, which were described using generalized Weibull equations, fitting a total of 19 vegetation types and ecoregions analyzed in Mexico. Monthly peaks of fire activity occurred at lower FDI values (wetter fuels) in more hygrophytic ecosystems and ecoregions, such as wet tropical forests, compared to higher fire activity in higher FDI values (drier fuels) for the more arid ecosystems, such as desert shrublands. In addition, the range of fuel dryness at which most monthly fire activity occurred was wider for wetter vegetation types and regions compared to a narrower range of fuel dryness for higher monthly fire occurrence in the more arid vegetation types and ecoregions. The results from the current study contribute towards improving our understanding of the relationships between fuel dryness and fire occurrence in a variety of vegetation types and regions in Mexico. [ABSTRACT FROM AUTHOR]

Background: Scarce data exist that analyze the outcomes of hematological patients with SARS-CoV-2 infection during the Omicron variant period who received treatment with remdesivir or nirmatrelvir/ritonavir. Methods: This study aims to address this issue by using a retrospective observational registry, created by the Spanish Hematopoietic Stem Cell Transplantation and Cell Therapy Group, spanning from 27 December 2021 to 30 April 2023. Results: This study included 466 patients, 243 (52%) who were treated with remdesivir and 223 (48%) with nirmatrelvir/ritonavir. Nirmatrelvir/ritonavir was primarily used for mild cases, resulting in a lower COVID-19-related mortality rate (1.3%), while remdesivir was preferred for moderate to severe cases (40%), exhibiting a higher mortality rate (9%). A multivariate analysis in the remdesivir cohort showed that male gender (odds ratio (OR) 0.35, p = 0.042) correlated with a lower mortality risk, while corticosteroid use (OR 9.4, p < 0.001) and co-infection (OR 2.8, p = 0.047) were linked to a higher mortality risk. Prolonged virus shedding was common, with 52% of patients shedding the virus for more than 25 days. In patients treated with remdesivir, factors associated with prolonged shedding included B-cell malignancy as well as underlying disease, severe disease, a later onset of and shorter duration of remdesivir treatment and a higher baseline viral load. Nirmatrelvir/ritonavir demonstrated a comparable safety profile to remdesivir, despite a higher risk of drug interactions. Conclusions: Nirmatrelvir/ritonavir proved to be a safe and effective option for treating mild cases in the outpatient setting, while remdesivir was preferred for severe cases, where corticosteroids and co-infection significantly predicted worse outcomes. Despite antiviral therapy, prolonged shedding remains a matter of concern. [ABSTRACT FROM AUTHOR]

Temperate mixed forests in Mexico are considered highly important ecosystems because of their high levels of biodiversity and capacity to store carbon. The aim of this study was to evaluate temporal and between-forest soil respiration (CO2 efflux) variability, and to assess the effect of vegetation diversity metrics on soil CO2 fluxes in mixed-uneven-aged forests in Durango, Northwestern Mexico. Soil CO2 efflux, soil moisture, and soil temperature were measured in three temperate forest types. A generalized linear model (GLM) was fitted to analyze the relationship between soil CO2 fluxes and stand variables, diversity metrics, soil moisture, and soil temperature. Furthermore, a two-way analysis of variance was used to assess the effect of forest type, month of the year, and their interaction on soil respiration. Annual average, minimum, and maximum soil CO2 efflux rate values were 3.81 (±2.94), 2.28 (±1.47), and 7.97 (±2.94) µmol m−2 s−1, respectively. Soil respiration was positively related to species richness, aboveground biomass, and quadratic mean diameter; however, forest type did not contribute to understanding the dynamics of soil CO2 fluxes. The results highlight the importance of seasonality, species diversity and aboveground biomass stocks to preserve the ecosystem processes driving soil respiration in temperate forests. [ABSTRACT FROM AUTHOR]

Simple Summary: Recent advances in treating elderly patients with chronic lymphocytic leukemia (CLL) have emphasized the importance of geriatric assessment (GA) to evaluate patient fitness and predict treatment outcomes. Targeted therapies (BTK inhibitors and venetoclax) have demonstrated significant clinical benefits and are now a reality in CLL treatment. They have a different toxicity profile that may affect frailty. Therefore, incorporating GA before treatment initiation, considering physical and cognitive function, emotional health, comorbidity, polypharmacy, nutrition, and social support, is essential. Chronic lymphocytic leukemia (CLL) is a disease of the elderly, but chronological age does not accurately discriminate frailty status at the inter-individual level. Frailty describes a person's overall resilience. Since CLL is a stressful situation, it is relevant to assess the patient´s degree of frailty, especially before starting antineoplastic treatment. We are in the era of targeted therapies, which have helped to control the disease more effectively and avoid the toxicity of chemo (immuno) therapy. However, these drugs are not free of side effects and other aspects arise that should not be neglected, such as interactions, previous comorbidities, or adherence to treatment, since most of these medications are taken continuously. The challenge we face is to balance the risk of toxicity and efficacy in a personalized way and without forgetting that the most frequent cause of death in CLL is related to the disease. For this purpose, comprehensive geriatric assessment (GA) provides us with the opportunity to evaluate multiple domains that may affect tolerance to treatment and that could be improved with appropriate interventions. In this review, we will analyze the state of the art of GA in CLL through the five Ws. [ABSTRACT FROM AUTHOR]

Simple Summary: To our knowledge, this is the first study to use free text from electronic healthcare records as a data source extracted with natural language processing to characterize the clinical characteristics and management of patients with chronic lymphocytic leukemia. A total of 534 included patients were stratified regarding the type of therapeutic management during the study period. Our results highlight the increased use of drugs directed to specific target therapies and the lower frequency of treatment with chemoimmunotherapy both in the first line and in relapsed/refractory settings in our sample of seven academic hospitals from 2016 to 2018. This real-world evidence study provides information on the diversity of clinical features and treatment patterns of chronic lymphocytic leukemia, evidencing the need to optimize patients' clinical management through personalizing their therapeutic approach. The SRealCLL study aimed to obtain real-world evidence on the clinical characteristics and treatment patterns of patients with chronic lymphocytic leukemia (CLL) using natural language processing (NLP). Electronic health records (EHRs) from seven Spanish hospitals (January 2016–December 2018) were analyzed using EHRead® technology, based on NLP and machine learning. A total of 534 CLL patients were assessed. No treatment was detected in 270 (50.6%) patients (watch-and-wait, W&W). First-line (1L) treatment was identified in 230 (43.1%) patients and relapsed/refractory (2L) treatment was identified in 58 (10.9%). The median age ranged from 71 to 75 years, with a uniform male predominance (54.8–63.8%). The main comorbidities included hypertension (W&W: 35.6%; 1L: 38.3%; 2L: 39.7%), diabetes mellitus (W&W: 24.4%; 1L: 24.3%; 2L: 31%), cardiac arrhythmia (W&W: 16.7%; 1L: 17.8%; 2L: 17.2%), heart failure (W&W 16.3%, 1L 17.4%, 2L 17.2%), and dyslipidemia (W&W: 13.7%; 1L: 18.7%; 2L: 19.0%). The most common antineoplastic treatment was ibrutinib in 1L (64.8%) and 2L (62.1%), followed by bendamustine + rituximab (12.6%), obinutuzumab + chlorambucil (5.2%), rituximab + chlorambucil (4.8%), and idelalisib + rituximab (3.9%) in 1L and venetoclax (15.5%), idelalisib + rituximab (6.9%), bendamustine + rituximab (3.5%), and venetoclax + rituximab (3.5%) in 2L. This study expands the information available on patients with CLL in Spain, describing the diversity in patient characteristics and therapeutic approaches in clinical practice. [ABSTRACT FROM AUTHOR]

The use of wild animals in research is complicated due to the capture and housing conditions, as well as to legal aspects, making it difficult to develop in vivo and in vitro models for the study of pathologies that affect these species. Here we validate an in vitro model of tendon-derived mesenchymal cells (TDSC) from Eurasian blackbird (Turdus merula) cadaveric samples. Through the expression of surface markers and the ability to differentiate into multiple lineages, the nature of the cells was confirmed. We then evaluated Mesenchymal Stem Cells (MSCs) as an infection model for the Usutu Flavivirus. To this aim, blackbird TDSCs were compared to Vero E6 cells, commonly used in Flavivirus studies. Both cells showed permissiveness to USUV infection as confirmed by immunocytochemistry. Moreover, TDSCs exhibited replication kinetics similar to, although slightly lower than, Vero E6, confirming these cells as a pertinent study model for the study of the pathogenesis of USUV. In this work, we isolated and characterized tendon-derived mesenchymal stem cells, which represent an interesting and convenient in vitro model for the study of wildlife species in laboratories. [ABSTRACT FROM AUTHOR]

Organotypic slice culture models surpass conventional in vitro methods in many aspects. They retain all tissue-resident cell types and tissue hierarchy. For studying multifactorial neurodegenerative diseases such as tauopathies, it is crucial to maintain cellular crosstalk in an accessible model system. Organotypic slice cultures from postnatal tissue are an established research tool, but adult tissue-originating systems are missing, yet necessary, as young tissue-originating systems cannot fully model adult or senescent brains. To establish an adult-originating slice culture system for tauopathy studies, we made hippocampal slice cultures from transgenic 5-month-old hTau.P301S mice. In addition to the comprehensive characterization, we set out to test a novel antibody for hyperphosphorylated TAU (pTAU, B6), with and without a nanomaterial conjugate. Adult hippocampal slices retained intact hippocampal layers, astrocytes, and functional microglia during culturing. The P301S-slice neurons expressed pTAU throughout the granular cell layer and secreted pTAU to the culture medium, whereas the wildtype slices did not. Additionally, cytotoxicity and inflammation-related determinants were increased in the P301S slices. Using fluorescence microscopy, we showed target engagement of the B6 antibody to pTAU-expressing neurons and a subtle but consistent decrease in intracellular pTAU with the B6 treatment. Collectively, this tauopathy slice culture model enables measuring the extracellular and intracellular effects of different mechanistic or therapeutic manipulations on TAU pathology in adult tissue without the hindrance of the blood–brain barrier. [ABSTRACT FROM AUTHOR]

It is critical to understand the ecological processes of forest dynamics by identifying past forest disturbances to take appropriate management actions. Tree-rings are commonly used for this purpose due to their reliability and accuracy. Here, we used a network of ring-width data distributed along a broad ecological gradient for the spatiotemporal identification of forest disturbances in 15 species of 13 sites of young Mexican conifers. We found different spatial and temporal patterns in the occurrence of forest disturbance. The species with the highest disturbance rates were Pinus patula (Ppa; El Jacalón), Pinus montezumae (Pmo; La Cueva), Pinus hartwegii (Phc; Cerro El Moro), and Pinus teocote (Pts; Rancho Joyas del Durazno) of the Gulf of Mexico, and Pinus ayacahuite (Pay; Corral de los Borregos) of the Mexico Center. The highest number of disturbances was found in 1953, 1956, 1976, and 1980; however, we noted that the number of disturbances tended to increase from 1975 to 1990 and particularly from 2000 onwards. The species close to the Gulf of Mexico presented a higher frequency and severity of disturbances than those located close to the Pacific Ocean. Thus, our results demonstrate a spatiotemporal pattern of disturbance events, which deserves further analysis, including regarding the drivers of disturbance. This knowledge is crucial for a better understanding of the dynamics of contemporary species. [ABSTRACT FROM AUTHOR]

Simple Summary: There are contradictory data about coronavirus disease (COVID-19) in patients with hematological malignancies. In this population-based study we evaluated severity and survival of unvaccinated patients with hematological malignancies (HM) and COVID-19 in the Madrid region, Spain, between early February 2020 and February 2021. Also, a comparison was made with non-cancer patients from the SEMI-COVID registry and post COVID-19 conditions were evaluated. Overall, 30-day mortality was 32.7%, with higher mortality among certain groups of patients (aged ≥ 60 years, presence of ≥ 3 comorbidities, diagnosis of AML/ALL, treatment with conventional chemotherapy within 30 days of COVID-19 diagnosis, recipients of systemic corticosteroids as COVID-19 therapy). Mortality rates were similar between earlier and later phases of the pandemic, not paralleling the reduction of mortality in non-cancer patients. Up to 27.3% patients had a post COVID-19 condition. These findings will be useful to understand COVID-19 morbidity and mortality in unvaccinated patients diagnosed with HM. Mortality rates for COVID-19 have declined over time in the general population, but data in patients with hematologic malignancies are contradictory. We identified independent prognostic factors for COVID-19 severity and survival in unvaccinated patients with hematologic malignancies, compared mortality rates over time and versus non-cancer inpatients, and investigated post COVID-19 condition. Data were analyzed from 1166 consecutive, eligible patients with hematologic malignancies from the population-based HEMATO-MADRID registry, Spain, with COVID-19 prior to vaccination roll-out, stratified into early (February–June 2020; n = 769 (66%)) and later (July 2020–February 2021; n = 397 (34%)) cohorts. Propensity-score matched non-cancer patients were identified from the SEMI-COVID registry. A lower proportion of patients were hospitalized in the later waves (54.2%) compared to the earlier (88.6%), OR 0.15, 95%CI 0.11–0.20. The proportion of hospitalized patients admitted to the ICU was higher in the later cohort (103/215, 47.9%) compared with the early cohort (170/681, 25.0%, 2.77; 2.01–3.82). The reduced 30-day mortality between early and later cohorts of non-cancer inpatients (29.6% vs. 12.6%, OR 0.34; 0.22–0.53) was not paralleled in inpatients with hematologic malignancies (32.3% vs. 34.8%, OR 1.12; 0.81–1.5). Among evaluable patients, 27.3% had post COVID-19 condition. These findings will help inform evidence-based preventive and therapeutic strategies for patients with hematologic malignancies and COVID-19 diagnosis. [ABSTRACT FROM AUTHOR]

In recent years, nanotechnology has deployed a new set of theragnostic tools, including magnetic resonance contrast agents, nano-delivery systems and magnetic hyperthermia treatments in cancer therapy, exploiting not only the small size of nanoparticles, but also relevant nanoscale properties such as superparamagnetism. Specifically, magnetic nanostructures can be remotely manipulated by external magnetic fields, incrementing their possibilities not only for theragnosis, but also for biotech procedures. Genetic engineering processes involve a set of steps like extracting cells from complex environments, their selection and subsequent cultivation or modification by transfection and can benefit from the use of bioconjugated magnetic nanoparticles. Magnetofection of cells with genes or biological material uploaded on superparamagnetic nanoparticles attracted by a magnetic field greatly increases the efficiency, specificity and speed of the biotechnological procedure in gene transfer systems. This article presents a preliminary investigation into the enhanced transfection efficiency of fluorescent magnetic mesoporous silica nanostructures functionalized with mCherry plasmid, which were used to transfect HeLa cells in just 15 min via magnetic transfection. This method was compared to passive transfection (4 h) and conventional gene transfer using the commercial K2 Transfection System (16 h). The results demonstrated that the fluorescent magnetic mesoporous silica nanostructures were similarly effective to the commercial kit, without the need for reagents that increase costs in clinical therapy. Furthermore, viability assays conducted with HeLa cells showed negligible toxicity at concentrations of up to 50 μg/mL. [ABSTRACT FROM AUTHOR]

The study of above-ground biomass (AGB) is important for monitoring the dynamics of the carbon cycle in forest ecosystems. The emergence of remote sensing has made it possible to analyze vegetation using land surface temperature (LST), Vegetation Temperature Condition Index (VTCI) and evapotranspiration (ET) information. However, relatively few studies have evaluated the ability of these variables to estimate AGB in temperate forests. The aim of the present study was to evaluate the relationship of LST, VTCI and ET with AGB in temperate forests of Durango, Mexico, regarding each season of the year and to develop a AGB estimation model using as predictors LST, VCTI and ET, together with topographic, reflectance and Gray-Level Co-Occurrence Matrix (GLCM) texture variables. A semi-parametric model was generated to analyze the linear and non-linear responses of the predictive variables of AGB using a generalized linear model (GAM). The results show that the best predictors of AGB were longitude, latitude, spring LST, ET, elevation VTCI, NDVI (Normalized Difference Vegetation Index), slope and GLCM mean (R2 = 0.61; RMSE = 28.33 Mgha−1). The developed GAM model was evaluated with an independent dataset (R2 = 0.58; RMSE = 31.21 Mgha−1), suggesting the potential of this modeling approach to predict AGB for the analyzed temperate forest ecosystems. [ABSTRACT FROM AUTHOR]

Forest certification is a private, voluntary and market-driven instrument designed to promote responsible forest management. This paper focused on the FSC and the NOM NMX-AA-143-SCFI-2008 schemes used in Mexico for the certification of sustainable forest management. In this paper we used the analytical hierarchical process (AHP) to study the factors that determine the main impacts of forest certification in México. A panel of 30 experts was selected as decision-makers to find which principles, criteria and indicators are considered as the most relevant while implementing forest certification. For decision-makers, the environmental principle occupied the first place with 40.26% of importance in the implementation of forest certification, followed by the social principle, and the economic principle with 32.15% and 27.59% of importance, respectively. Regarding the criteria, forest management and production, biodiversity, and forest protection were considered to be the most relevant. Regarding the indicators, the results indicated that forest certification in Mexico can have a positive impact on the existence of educational institutions, community services such as water, energy, medical services and drainage, the quality of the forest management plans, investment in forest management, machinery and equipment, environmental services, recreation, tourism, research, development and community education, planning for the conservation of biological diversity, and planning for biodiversity conservation. [ABSTRACT FROM AUTHOR]

Even though the site index is a popular method for describing forest productivity, its use is limited in uneven-aged multispecies forests. Accordingly, the site form (SF) is an alternative measure of productivity to the site index based on the tree height–diameter relationship. Our study aims to evaluate SF as a measure of productivity in the temperate uneven-aged multispecies forests of Durango, Mexico, applying three methods to estimate SF: (i) as the mean height of dominant trees at a reference diameter (SFH-D); (ii) as the expected mean height of dominant trees at a reference mean diameter (SFMH-MD), and (iii) as the expected height at a reference diameter for a given site (SFh-dbh). We assess the effectiveness of the SF based on two hypotheses: (i) the SF correlates to the total volume production, and (ii) the SF is independent of stand density. The SFH-D and the SFh-dbh showed a high correlation with productivity. However, they also did so with density. Contrary to this, the SFMH-MD had a weak correlation with density and productivity. We conclude that the SF is a suitable approach to describe site quality. Nonetheless, its effectiveness as a site quality indicator may be affected according to the method used. [ABSTRACT FROM AUTHOR]

Hospitalized patients with COVID-19 are at increased risk of thrombosis, acute respiratory distress syndrome and death. The optimal dosage of thromboprophylaxis is unknown. The aim was to evaluate the efficacy and safety of tinzaparin in prophylactic, intermediate, and therapeutic doses in non-critical patients admitted for COVID-19 pneumonia. PROTHROMCOVID is a randomized, unblinded, controlled, multicenter trial enrolling non-critical, hospitalized adult patients with COVID-19 pneumonia. Patients were randomized to prophylactic (4500 IU), intermediate (100 IU/kg), or therapeutic (175 IU/kg) groups. All tinzaparin doses were administered once daily during hospitalization, followed by 7 days of prophylactic tinzaparin at discharge. The primary efficacy outcome was a composite endpoint of symptomatic systemic thrombotic events, need for invasive or non-invasive mechanical ventilation, or death within 30 days. The main safety outcome was major bleeding at 30 days. Of the 311 subjects randomized, 300 were included in the prespecified interim analysis (mean [SD] age, 56.7 [14.6] years; males, 182 [60.7%]). The composite endpoint at 30 days from randomization occurred in 58 patients (19.3%) of the total population; 19 (17.1 %) in the prophylactic group, 20 (22.1%) in the intermediate group, and 19 (18.5%) in the therapeutic dose group (p = 0.72). No major bleeding event was reported; non-major bleeding was observed in 3.7% of patients, with no intergroup differences. Due to these results and the futility analysis, the trial was stopped. In non-critically ill COVID-19 patients, intermediate or full-dose tinzaparin compared to standard prophylactic doses did not appear to affect the risk of thrombotic event, non-invasive ventilation, or mechanical ventilation or death. Trial RegistrationClinicalTrials.gov Identifier (NCT04730856). Edura-CT registration number: 2020-004279-42. [ABSTRACT FROM AUTHOR]

Iron oxide magnetic nanoparticles (MNPs) have been widely studied due to their versatility for diagnosis, tracking (magnetic resonance imaging (MRI)) and therapeutic (magnetic hyperthermia and drug delivery) applications. In this work, iron oxide MNPs with different single-core (8–40 nm) and multi-core (140–200 nm) structures were synthesized and functionalized by organic and inorganic coating materials, highlighting their ability as magnetic nanotools to boost cell biotechnological procedures. Single core Fe3O4@PDA, Fe3O4@SiO2-FITC-SiO2 and Fe3O4@SiO2-RITC-SiO2 MNPs were functionalized with fluorescent components with emission at different wavelengths, 424 nm (polydopamine), 515 (fluorescein) and 583 nm (rhodamine), and their ability as transfection and imaging agents was explored with HeLa cells. Moreover, different multi-core iron oxide MNPs (Fe3O4@CS, Fe3O4@SiO2 and Fe3O4@Citrate) coated with organic (citrate and chitosan, CS) and inorganic (silica, SiO2) shells were tested as efficient nanoheaters for magnetic hyperthermia applications for mild thermal heating procedures as an alternative to simple structures based on single-core MNPs. This work highlights the multiple abilities offered by the synergy of the use of external magnetic fields applied on MNPs and their application in different biomedical approaches. [ABSTRACT FROM AUTHOR]

The remote sensing of fire severity and burned area is fundamental in the evaluation of fire impacts. The current study aimed to: (i) compare Sentinel-2 (S2) spectral indices to predict field-observed fire severity in Durango, Mexico; (ii) evaluate the effect of the compositing period (1 or 3 months), techniques (average or minimum), and phenological correction (constant offset, c, against a novel relative phenological correction, rc) on fire severity mapping, and (iii) determine fire perimeter accuracy. The Relative Burn Ratio (RBR), using S2 bands 8a and 12, provided the best correspondence with field-based fire severity (FBS). One-month rc minimum composites showed the highest correspondence with FBS (R2 = 0.83). The decrease in R2 using 3 months rather than 1 month was ≥0.05 (0.05–0.15) for c composites and <0.05 (0.02–0.03) for rc composites. Furthermore, using rc increased the R2 by 0.05–0.09 and 0.10–0.15 for the 3-month RBR and dNBR compared to the corresponding c composites. Rc composites also showed increases of up to 0.16–0.22 and 0.08–0.11 in kappa values and overall accuracy, respectively, in mapping fire perimeters against c composites. These results suggest a promising potential of the novel relative phenological correction to be systematically applied with automated algorithms to improve the accuracy and robustness of fire severity and perimeter evaluations. [ABSTRACT FROM AUTHOR]

Tree aboveground biomass (e.g., bole, branches, and foliage), M, plays key roles in forest management as it is the basis for evaluating the sink and flux of, for example, carbon and nitrogen, stand productivity, dendro-energy, litter & root biomass, hydrological parameters, among others. With the aim of further simplifying and understanding M, the central objective of this research was to review available techniques to develop, test, and validate two independent novel non-destructive, semi-empirical models using four major M datasets: (i) the shape dimensional bio-physical, MSD; and (ii) the restrictive mathematical, MNR, models. The proposed models advance and test how each of both approaches: (i) constant or (ii) variable scalar coefficients perform when predicting M with major assumptions bearing bio-physical principles. Results showed that M has to be predicted eventually with variable scalar coefficients; both models predicted compatible M figures; the evaluations matched the conventional equation well; and the independent data sets were well validated; the coefficients of determination, r2, and the standard errors, Sx%, had values >96% and <20%, respectively, for most tested conifer tree species. In spite of demonstrating empirically and physically the ontogenetic-dependency of scalar coefficients, the MNR model, with constant β-scalar and variable a-intercept coefficients, performed slightly better, and precision appeared to be a function of the tree species growing in different forest ecosystems. Therefore, better parameterization advances for the testing and validation of the MSD model that uses variable scalar coefficients, which are consistent with ontogenetic principles, are preliminarily recommended for M assessments. The updated revision of models, the independent development, the construction using different assumptions, the individual mathematical and bio-physical parameterization, the consistency on M assessments, and the bearing of physical and biological properties are key pieces of scientific information presented in this report are required in modern forest management when predicting M and associated variables and attributes. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) have contributed considerably to forest monitoring. However, gaps in the knowledge still remain, particularly for natural forests. Species diversity, stand heterogeneity, and the irregular spatial arrangement of trees provide unique opportunities to improve our perspective of forest stands and the ecological processes that occur therein. In this study, we calculated individual tree metrics, including several multispectral indices, in order to discern the spectral reflectance of a natural stand as a pioneer area in Mexican forests. Using data obtained by UAV DJI 4, and in the free software environments OpenDroneMap and QGIS, we calculated tree height, crown area, number of trees and multispectral indices. Digital photogrammetric procedures, such as the ForestTools, Structure from Motion and Multi-View Stereo algorithms, yielded results that improved stand mapping and the estimation of stand attributes. Automated tree detection and quantification were limited by the presence of overlapping crowns but compensated by the novel stand density mapping and estimates of crown attributes. Height estimation was in line with expectations (R2 = 0.91, RMSE = 0.36) and is therefore a useful parameter with which to complement forest inventories. The diverse spectral indices applied yielded differential results regarding the potential vegetation activity present and were found to be complementary to each other. However, seasonal monitoring and careful estimation of photosynthetic activity are recommended in order to determine the seasonality of plant response. This research contributes to the monitoring of natural forest stands and, coupled with accurate in situ measurements, could refine forest productivity parameters as a strategy for the validity of results. The metrics are reliable and rapid and could serve as model inputs in modern inventories. Nevertheless, increased efforts in the configuration of new technologies and algorithms are required, including full consideration of the costs implied by their adoption. [ABSTRACT FROM AUTHOR]

Biometric systems are the basis of forest management and consist of a set of equations that describe the relationships between forest attributes and dendrometric variables. A systematic review of the state of the art of biometric systems in Mexico was carried out by a Mexican consortium (10 researchers), covering a period of 50 years ca (1970–2019), using the main scientific literature delivered by a systematic search (WoS, Scopus, Scielo, Redalyc) and a targeted search (theses, technical reports, etc.). A single selection criterion was established for the inclusion of information in the analysis: the document had to present at least one of the equations of interest. We found 376 documents containing 2524 equations for volume (69%), diameter (11%), height (9%) and site index (11%). These equations were developed for forest species mainly from temperate regions (88%), such as pine (66%) and oak (9%). Consequently, the Mexican states with the highest number of equations were Durango (28%), Chihuahua (17%), Hidalgo (13%) and Oaxaca (8%). Although large, the number of equations identified concentrated on a relatively small number of models: Schumacher & Hall and Fang et al. for volume; Chapman-Richards and Schumacher for site index and diameter; and Chapman-Richards and the allometric equation for height. An analysis of model fit, measured through R2, showed that, on average, the volume, diameter and site index models show high fit (R2 = 0.96), although this pattern was more consistent in the volume models. Publication bias was evaluated by means of a funnel plot analysis, with no apparent bias identified. A limitation of our study is that the information obtained is not updated to the present year; however, the 50-year trends allow us to assume that no recent significant changes in the patterns exist. Finally, we highlight the need to assess the predictive ability of the models to ensure accurate estimates to support better forest management decisions. [ABSTRACT FROM AUTHOR]

Undoped and Mg-doped (y = [Mg2+]/[Fe3+] = 1, 2, 3, and 4 at.%) Fe2O3 thin films were synthesized by a simple spray pyrolysis technique. The thin films were extensively characterized. X-ray diffraction (XRD) and energy-dispersive spectroscopy (EDS) analysis confirmed the successful insertion of Mg in the rhombohedral structure of Fe2O3. In addition, scanning electronic microscope (SEM) and confocal microscope (CM) images showed a homogenous texture of the film, which was free of defects. The rough surface of the film obtained by spray pyrolysis is an important feature for photocatalysis and gas sensor applications. The direct band gap of the doped Fe2O3 films obtained for [Mg2+]/[Fe3+] = 3 at.% was Edir = 2.20 eV, which recommends the Mg-doped iron oxide as an optical window or buffer layer in solar cell devices. The photodegradation performance of Mg-doped Fe2O3 was assessed by studying the removal of methylene blue (MB) under sunlight irradiation, with an effective removal efficiency of 90% within 180 min. The excellent photodegradation activity was attributed to the strong absorption of Mg-doped Fe2O3 in the UV and most of the visible light, and to the effective separation of photogenerated charge carriers. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Tendon-Derived Mesenchymal Stem Cells (TDSCs) as an In Vitro Model for Virological Studies in Wild Birds" published in the journal Viruses. The correction addresses an error in Table 1 of the original publication, where the GenBank accession numbers were omitted. The corrected table, which includes the primer sequences used in the RT-PCR characterization of blackbird TDSCs, is provided. The authors state that this correction does not affect the scientific conclusions of the article. [Extracted from the article]

Nanotechnology offers the possibility of operating on the same scale length at which biological processes occur, allowing to interfere, manipulate or study cellular events in disease or healthy conditions. The development of hybrid nanostructured materials with a high degree of chemical control and complex engineered surface including biological targeting moieties, allows to specifically bind to a single type of molecule for specific detection, signaling or inactivation processes. Magnetite nanostructures with designed composition and properties are the ones that gather most of the designs as theragnostic agents for their versatility, biocompatibility, facile production and good magnetic performance for remote in vitro and in vivo for biomedical applications. Their superparamagnetic behavior below a critical size of 30 nm has allowed the development of magnetic resonance imaging contrast agents or magnetic hyperthermia nanoprobes approved for clinical uses, establishing an inflection point in the field of magnetite based theragnostic agents. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The fluoride content in groundwater varies depending on geological configuration. Fluoride problems tend to occur in places where these minerals are most abundant in rocks. The objective of the present work was to synthesize four biopolymers based on chitosan-polyvinyl alcohol (Ch-PVA) cross-linked with sodium tripolyphosphate pentabasic (TPP) and ethylene glycol diglycidyl ether (EGDE) and determine their ability to remove fluoride from water. The characterization of the Ch-PVA beads was performed by way of Scanning Electron Microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR). The percentage of humidity and the point of zero charge were determined. The Ch-PVA beads showed a surface area of 63.87 m2 g-1, a pore size of 7.6 nm, a point of zero charge of 7.4, and 98.6% humidity. The kinetic adsorption study was adjusted to the pseudo-second-order model and the adsorption equilibrium data were adjusted to the Freundlich adsorption isotherm, showing a maximum fluoride adsorption capacity of 12.64 mg g-1 at pH 7 and 30 °C, for the beads of Ch-PVA-NaOH-TPP. According to the thermodynamic parameters: -ΔG°, +ΔH° and -ΔS°, fluoride adsorption is spontaneous, endothermic in nature and there is no random energy change in the solid/liquid interface during the adsorption process. [ABSTRACT FROM AUTHOR]

Traditional studies aimed at developing allometric models to estimate dry above-ground biomass (AGB) and other tree-level variables, such as tree stem commercial volume (TSCV) or tree stem volume (TSV), usually involves cutting down the trees. Although this method has low uncertainty, it is quite costly and inefficient since it requires a very time-consuming field work. In order to assist in data collection and processing, remote sensing is allowing the application of non-destructive sampling methods such as that based on terrestrial laser scanning (TLS). In this work, TLS-derived point clouds were used to digitally reconstruct the tree stem of a set of teak trees (Tectona grandis Linn. F.) from 58 circular reference plots of 18 m radius belonging to three different plantations located in the Coastal Region of Ecuador. After manually selecting the appropriate trees from the entire sample, semi-automatic data processing was performed to provide measurements of TSCV and TSV, together with estimates of AGB values at tree level. These observed values were used to develop allometric models, based on diameter at breast height (DBH), total tree height (h), or the metric DBH2 × h, by applying a robust regression method to remove likely outliers. Results showed that the developed allometric models performed reasonably well, especially those based on the metric DBH2 × h, providing low bias estimates and relative RMSE values of 21.60% and 16.41% for TSCV and TSV, respectively. Allometric models only based on tree height were derived from replacing DBH by h in the expression DBH2 x h, according to adjusted expressions depending on DBH classes (ranges of DBH). This finding can facilitate the obtaining of variables such as AGB (carbon stock) and commercial volume of wood over teak plantations in the Coastal Region of Ecuador from only knowing the tree height, constituting a promising method to address large-scale teak plantations monitoring from the canopy height models derived from digital aerial stereophotogrammetry. [ABSTRACT FROM AUTHOR]

Accurate quantification of branch volume in trees is important for sustainable forest management, especially as these fractions are increasingly used for bioenergy, and for precise forest CO2 quantification. Whereas a large focus has been placed on the compatible estimation of tree taper and bole volume with and without bark, little effort has been made to develop models that allow a simultaneous prediction of these variables together with tree branch volume. In this study, 595 Pinus cooperi trees and 700 Pinus durangensis trees were sampled in pine-oak forests in the Sierra Madre Occidental, Mexico. A compatible system for predicting two segmented taper functions, over and under bark; the corresponding merchantable volumes; coarse branch volume and whole-tree volume was fitted using a modified continuous autoregressive structure to account for autocorrelation. The proposed compatible equations explained more than 97% of the observed variability in diameter over and under bark, volume over and under bark, and total tree volume and more than 64% of the observed variability in branch volume in both species. The method described can theoretically be replicated for any tree species, thus providing a better understanding of the patterns of volume distribution by components, potentially improving carbon accounting system and forest bioenergy planning. [ABSTRACT FROM AUTHOR]

Mexico has had a non-state forest certification system under the Forest Stewardship Council (FSC) since it was initiated in 1993, and developed a new state-sponsored Mexican Forest Certification System (MFCS) that began in 2008. Several analyses have been made of FSC forest certification in Mexico, but none have summarized the new MFCS system or compared its standards with FSC. We compare the implementation of the non-state FSC market forest certification with the state-sponsored MFCS system in Mexico, and review literature on forest certification, focusing on all studies in Mexico. MFCS has had substantial enrollment of more than 902,802 ha by 2016, compared to 900,388 ha for the more-established FSC program. MFCS can be acceptable for stand-alone forest certification, and might be viewed as a stepwise path to FSC certification. The merits of both systems are analyzed in terms of standard content, likely sustainable forestry practices, access to markets, and community forestry enterprises. [ABSTRACT FROM AUTHOR]

This paper presents new equations for estimating above-ground biomass (AGB) and biomass components of seventeen forest species in the temperate forests of northwestern Mexico. A data set corresponding to 1336 destructively sampled oak and pine trees was used to fit the models. The generalized method of moments was used to simultaneously fit systems of equations for biomass components and AGB, to ensure additivity. In addition, the carbon content of each tree component was calculated by the dry combustion method, in a TOC analyser. The results of cross-validation indicated that the fitted equations accounted for on average 91%, 82%, 83% and 76% of the observed variance in stem wood and stem bark, branch and foliage biomass, respectively, whereas the total AGB equations explained on average 93% of the total observed variance in AGB. The inclusion of total height (h) or diameter at breast height2 x total height (d2h) as a predictor in the d-only based equations systems slightly improved estimates for stem wood, stem bark and total above-ground biomass, and greatly improved the estimates produced by the branch and foliage biomass equations. The predictive power of the proposed equations is higher than that of existing models for the study area. The fitted equations were used to estimate stand level AGB stocks from data on growing stock in 429 permanent sampling plots. Three machine-learning techniques were used to model the estimated stand level AGB and carbon contents; the selected models were used to map the AGB and carbon distributions in the study area, for which mean values of respectively 129.84 Mg ha-1 and 63.80 Mg ha-1 were obtained. [ABSTRACT FROM AUTHOR]

Virgin olive oil (VOO) is the only food product requiring official sensory analysis to be classified in commercial categories, in which the evaluation of the aroma plays a very important role. The selection of parents, with the aim of obtaining new cultivars with improved oil aroma, is of paramount importance in olive breeding programs. We have assessed the volatile fraction by headspace-solid-phase microextraction/gas chromatography-mass spectrometry-flame ionization detection (HS-SPME/GC-MS-FID) and the deduced aroma properties of VOO from a core set of olive cultivars (Core-36) which possesses most of the genetic diversity found in the World Olive Germplasm Collection (IFAPA Alameda del Obispo) located in Cordoba, Spain. The VOO volatile fractions of Core-36 cultivars display a high level of variability. It is mostly made of compounds produced from polyunsaturated fatty acids through the lipoxygenase pathway, which confirms to be a general characteristic of the olive species (Olea europaea L.). The main group of volatile compounds in the oils was six straight-chain carbon compounds derived from linolenic acid, some of them being the main contributors to the aroma of the olive oils according to their odor activity values (OAV). The high level of variability found for the volatile fraction of the oils from Core-36 and, therefore, for the aroma odor notes, suggest that this core set may be a very useful tool for the choice of optimal parents in olive breeding programs in order to raise new cultivars with improved VOO aroma. [ABSTRACT FROM AUTHOR]

Due to the high cost of traditional forest plot measurements, the availability of up-to-date in situ forest inventory data has been a bottleneck for remote sensing image analysis in support of the important global forest biomass mapping. Capitalizing on the proliferation of smartphones, citizen science is a promising approach to increase spatial and temporal coverages of in situ forest observations in a cost-effective way. Digital cameras can be used as a relascope device to measure basal area, a forest density variable that is closely related to biomass. In this paper, we present the Relasphone mobile application with extensive accuracy assessment in two mixed forest sites from different biomes. Basal area measurements in Finland (boreal zone) were in good agreement with reference forest inventory plot data on pine ( R2=0.75 , RMSE=5.33 m 2 /ha), spruce ( R2=0.75,RMSE=6.73 m 2 /ha) and birch ( R2=0.71,RMSE=4.98 m 2 /ha), with total relative RMSE(%)=29.66% . In Durango, Mexico (temperate zone), Relasphone stem volume measurements were best for pine ( R2=0.88 , RMSE=32.46 m 3 /ha) and total stem volume ( R2=0.87 , RMSE=35.21 m 3 /ha). Relasphone data were then successfully utilized as the only reference data in combination with optical satellite images to produce biomass maps. The Relasphone concept has been validated for future use by citizens in other locations. [ABSTRACT FROM AUTHOR]