Search Results (666)

Erythrocyte (RBC) aging involves significant structural and nanomechanical alterations crucial to their function. This study aims to bridge the gap between analyses based on statistical morphometric parameters, e.g., membrane roughness, and those based on point-dependent nanomechanical properties, e.g., stiffness or Young’s modulus. Using Atomic Force Microscopy, we investigated morphology, membrane roughness, and nanomechanical properties on the very same RBCs under dehydrated (air) and hydrated (physiological buffer) conditions. The cells were studied at different stages of in vitro aging: one, seven, and 12 days. Our results quantitatively show that across dehydration, as well as along the aging pathway, RBCs become progressively more rigid while their membrane roughness decreases, a trend observed in both environments. Notably, the differences between the hydrated and dehydrated states were large in young cells but diminished when erythrocytes aged. Despite these parallel trends, high-resolution mapping on the nanoscale revealed that roughness and Young’s modulus do not correlate, indicating that these parameters are linked to different properties. In conclusion, this work provides a comprehensive protocol for a biophysical description of RBC aging and establishes that the simultaneous measurement of membrane roughness and nanomechanical properties offers a complementary approach, yielding a more complete characterization of cellular properties. Full article

Multivalent lectin–glycan interactions (MLGIs) are vital for viral infection, cell-cell communication and regulation of immune responses. Their structural and biophysical data are thus important, not only for providing insights into their underlying mechanisms but also for designing potent glycoconjugate therapeutics against target MLGIs. However, such information remains to be limited for some important MLGIs, significantly restricting the research progress. We have recently demonstrated that functional nanoparticles, including ∼4 nm quantum dots and varying sized gold nanoparticles (GNPs), densely glycosylated with various natural mono- and oligo- saccharides, are powerful biophysical probes for MLGIs. Using two important viral receptors, DC-SIGN and DC-SIGNR (together denoted as DC-SIGN/R hereafter), as model multimeric lectins, we have shown that α-mannose and α-manno-α-1,2-biose (abbreviated as Man and DiMan, respectively) coated GNPs not only can provide sensitive measurement of MLGI affinities but also reveal critical structural information (e.g., binding site orientation and mode) which are important for MLGI targeting. In this study, we produced mannuronic acid (ManA) coated GNPs (GNP-ManA) of two different sizes to probe the effect of glycan modification on their MLGI affinity and antiviral property. Using our recently developed GNP fluorescence quenching assay, we find that GNP-ManA binds effectively to both DC-SIGN/R and increasing the size of GNP significantly enhances their MLGI affinity. Consistent with this, increasing the GNP size also significantly enhances their ability to block DC-SIGN/R-augmented virus entry into host cells. Particularly, ManA coated 13 nm GNP potently block Ebola virus glycoprotein-driven entry into DC-SIGN/R-expressing cells with sub-nM levels of EC₅₀. Our findings suggest that GNP-ManA probes can act as a useful tool to quantify the characteristics of MLGIs, where increasing the GNP scaffold size substantially enhances their MLGI affinity and antiviral potency. Full article

The distribution of forest aboveground biomass density (AGBD) is a key indicator of carbon stock and ecosystem health in the Eastern Himalayas, which represents a global biodiversity hotspot that sustains diverse forest types across an elevation gradient from lowland rainforests to alpine meadows and contributes to the livelihoods of more than 200 distinct indigenous communities. This study aimed to identify the key factors influencing forest AGBD across this region by analyzing the underlying biophysical and anthropogenic drivers through machine learning (random forest). We processed AGBD data from the Global Ecosystem Dynamics Investigation (GEDI) spaceborne LiDAR and applied filtering to retain 30,257 high-quality footprints across ten ecoregions. We then analyzed the relationship between AGBD and 17 climatic, topographic, soil, and anthropogenic variables using random forest regression models. The results revealed significant spatial variability in AGBD (149.6 ± 79.5 Mg ha⁻¹) across the region. State-wise, Sikkim recorded the highest mean AGBD (218 Mg ha⁻¹) and Manipur the lowest (102.8 Mg ha⁻¹). Within individual ecoregions, the Himalayan subtropical pine forests exhibited the highest mean AGBD (245.5 Mg ha⁻¹). Topographic factors, particularly elevation and latitude, were strong determinants of biomass distribution, with AGBD increasing up to elevations of 2000 m before declining. Protected areas (PAs) consistently showed higher AGBD than unprotected forests for all ecoregions, while proximity to urban and agricultural areas resulted in lower AGBD, pointing towards negative anthropogenic impacts. Our full model explained 41% of AGBD variance across the Eastern Himalayas, with better performance in individual ecoregions like the Northeast India-Myanmar pine forests (R² = 0.59). While limited by the absence of regionally explicit stand-level forest structure data (age, stand density, species composition), our results provide valuable evidence for conservation policy development, including expansion of PAs, compensating avoided deforestation and modifications in shifting cultivation. Future research should integrate field measurements with remote sensing and use high-resolution LiDAR with locally derived allometric models to enhance biomass estimation and GEDI data validation. Full article

Ultra-high dose rate radiotherapy known as Flash radiotherapy (FLASH-RT) offers tremendous opportunities to improve the therapeutic ratio of radiotherapy by sparing the normal tissue while maintaining similar tumoricidal efficacy. However, the underlying biophysical basis of the FLASH effect remains under active investigation with several proposed mechanisms involving oxygen depletion, altered free-radical chemistry, and differential biological responses. This article provides an overview of available experimental and computational tools that can be utilized to probe the tumor and normal tissue microenvironment. We analyze in vitro, ex vivo, and in vivo systems used to study FLASH responses. We describe various computational and imaging technologies that can potentially aid in understanding the biophysics of FLASH-RT and lead to safer clinical translational. Full article

Cassava is the sixth most important food crop and is cultivated in more than 100 countries. The crop tolerates low soil fertility and drought, enabling it to play a role in climate adaptation strategies. Cassava generally requires careful preparation to remove toxic hydrogen cyanide (HCN) before its consumption, but HCN concentrations can vary considerably between varieties. Climate change and low inputs, particularly carbon and nutrients, affect agriculture in Pacific Island countries where cassava is commonly grown alongside traditional crops (e.g., taro). Despite increasing popularity in this region, there is limited experimental data about cassava crop management for different local varieties, their relative toxicity and nutritional value for human consumption, and their interaction with changing climate conditions. To help address this knowledge gap, three field experiments were conducted at the Koronivia Research Station of the Fiji Ministry of Agriculture. Two varieties of cassava with contrasting HCN content were planted at three different times coinciding with the start of the wet (September-October) or dry (April) seasons. A time series of measurements was conducted during the full 18-month or differing 6-month durations of each crop, based on destructive harvests and phenological observations. The former included determination of total biomass, HCN potential, carbon isotopes (δ¹³C), and elemental composition. Yield and nutritional value were significantly affected by variety and time of planting, and there were interactions between the two factors. Findings from this work will improve cassava management locally and will provide a valuable dataset for agronomic and biophysical model testing. Full article

Cell membrane capacitance (C_m) is a potential biomarker that reflects the structural and functional integrity of cell membranes. It is essential for physiological processes such as signal transduction, ion transport, and cellular homeostasis. In clinical practice, C_m can be determined using bioimpedance spectroscopy (BIS), a non-invasive technique for analysing the intrinsic electrical properties of biological tissues across a range of frequencies. C_m may be relevant in various clinical fields, where high capacitance is associated with healthy and intact membranes, while low capacitance indicates cellular damage or disease. Despite its promise as a prognostic indicator, several knowledge gaps limit the broader clinical application of C_m. These include variability in measurement techniques (e.g., electrode placement, frequency selection), the lack of standardised measurement protocols, uncertainty on how C_m is related to pathology, and the relatively low amount of C_m research. By addressing these gaps, C_m may become a valuable tool for examining cellular health, early disease detection, and evaluating treatment efficacy in clinical practice. This review explores the fundamental principles of C_m measured with the BIS technique, its mathematical basis and relationship to the biophysical Cole model, and its potential clinical applications. It identifies current gaps in our knowledge and outlines future research directions to enhance the understanding and use of C_m. For example, C_m has shown promise in identifying membrane degradation in sepsis, predicting malnutrition in anorexia nervosa, and as a prognostic factor in cancer. Full article

Advanced Synthetic Aperture Radar (SAR) has become an essential modality in remote sensing, offering all-weather capabilities and sensitivity to vegetation biophysical parameters and surface conditions, while effectively complementing optical sensor data. This study evaluates the impact of precipitation on the Normalized Polarimetric Radar Vegetation Index (NPRVI) using dual-polarization Sentinel-1 C-band SAR data from agricultural fields at the Beltsville Agricultural Research Center (BARC). Field-measured precipitation and Global Precipitation Measurement (GPM) precipitation datasets were temporally aligned with Sentinel-1 acquisition times to assess the sensitivity of radar signals to precipitation events. NPRVI exhibited a strong sensitivity to precipitation, particularly within the 1 to 7 h prior to the satellite overpass, even for small amounts of precipitation. A quality assessment (QA) framework was developed to flag and correct precipitation-affected radar observations through interpolation. The adjusted NPRVI values, based on the QA framework using precipitation within a 6 h window, showed strong agreement between field- and GPM-derived data, with an RMSE of 0.09 and a relative RMSE of 19.8%, demonstrating that GPM data can serve as a viable alternative for quality adjustment despite its coarse spatial resolution. The adjusted NPRVI for both soybean and corn fields significantly improved the temporal consistency of the time series and closely followed NDVI trends, while also capturing crop-specific seasonal variations, especially during periods of NDVI saturation or limited variability. These findings underscore the value of the proposed radar-based QA framework in enhancing the interpretability of vegetation dynamics. NPRVI, when adjusted for precipitation effects, can serve as a reliable and complementary tool to optical vegetation indices in agricultural and environmental monitoring. Full article

This article investigates issues in the local operationalization of the Planetary Boundaries concept (PBc), crucial for assessing human impacts on the Earth system and guiding sustainable development policies. Originally designed for the global scale, this concept requires local adaptation to align territorial actions with global environmental goals. Following a qualitative analysis of 34 review articles, a systematic categorization method is employed to identify recurrent localization and operationalization issues. Their analysis provides three main contributions that improve the understanding of PBc downscaling mechanisms. First, it identifies a prevalent quantification-based localization approach. Second, it categorizes local operationalization constraints into three distinct groups. Third, it reveals underlying patterns demonstrating that the prevalent approach, despite ensuring scientific rigor, generates methodological and practical constraints to effective local operationalization. This “operational paradox” reveals fundamental tensions between the PBc’s biophysical interpretation, localization by quantification, and local operationalization, contrasting measurement or meaning, precision or participation, and standardized solutions or locally adapted responses. For future research, the analysis of the interactions between these contributions suggests operating a paradigm shift based on a socio-biophysical interpretation of the PBc and the contextualization of the resulting components. This alternative approach could prioritize territorial anchoring, stakeholder inclusion, and the co-construction of sustainability trajectories. Full article

Multispectral images obtained from Unmanned Aerial Vehicles (UAVs) have become strategic tools in precision agriculture, particularly for analyzing spatial variability in soil attributes. This study aimed to evaluate the spatial distribution of soil electrical (EC) and total organic carbon (TOC) in irrigated forage cactus areas in the Brazilian semiarid region, using field measurements and UAV-based multispectral imagery. The study was conducted in a communal agricultural settlement located in the Mimoso Alluvial Valley (MAV), where EC and TOC were measured at 96 points, and seven biophysical indices were derived from UAV multispectral imagery. Geostatistical models, including cokriging with spectral indices (NDVI, EVI, GDVI, SAVI, and NDSI), were applied to map soil attributes at different spatial scales. Cokriging improved the spatial prediction of EC and TOC by reducing uncertainty and increasing mapping accuracy. The standard deviation of EC decreased from 1.39 (kriging) to 0.67 (cokriging with EVI), and for TOC from 15.55 to 8.78 (cokriging with NDVI and NDSI), reflecting a 43.5% reduction in uncertainty. The indices, EVI, NDVI, and NDSI, showed strong potential in representing and enhancing the spatial variability in soil attributes. NDVI and NDSI were particularly effective at finer grid resolutions, supporting more efficient irrigation strategies and sustainable agricultural practices. Full article

Background/Objective: Small-for-gestational-age (SGA) status constitutes a significant risk factor for adverse neonatal outcomes and predisposes individuals to long-term health complications. Detecting pregnancies at risk early in gestation could significantly improve perinatal outcomes. Recent evidence suggests that ophthalmic artery Doppler assessment in the first trimester may contribute to the prediction of impaired placentation reflected in increased risk for preeclampsia. This study aimed to investigate the association between first-trimester ophthalmic artery Doppler parameters and the subsequent birth of small-for-gestational-age (SGA) neonates. Methods: In this prospective observational analysis, 4054 pregnant women underwent ophthalmic artery Doppler evaluation at 11–13 weeks gestation. Maternal demographics, biophysical and biochemical markers, and ophthalmic artery Doppler measurements of pulsatility index (PI) and peak systolic velocity (PSV) ratio were obtained. Outcomes were classified based on birthweight into the ≤3rd percentile and >3rd percentile and ≤10th percentile and >10th percentile groups. To determine the predictive value of Doppler indices, statistical methods included comparative analyses and the receiver operating characteristic (ROC) curves. Results: The analysis indicated that increased PSV ratio at 11–13 weeks gestation correlated with an increased risk of SGA. The PI was not found to be a significant discriminator between pregnancies complicated by SGA and non-SGA pregnancies. Conclusions: First-trimester ophthalmic artery Doppler assessment offers promise as a non-invasive technique for the early identification of pregnancies at risk for SGA neonates. Further validation through large, multicenter studies is needed to confirm its utility and to standardize its use in clinical protocols. Full article

Forest ecosystems serve as pivotal components of the global carbon cycle, with canopy height representing a critical biophysical parameter for quantifying ecosystem functionality, thereby holding substantial implications for forest resource management and carbon sequestration assessments. The precise extraction of ground elevation and vegetation canopy height is essential for advancing topographic and ecological research. The Terrestrial Ecosystem Carbon Inventory Satellite (referred to as TECIS hereafter) offers unprecedented capabilities for the large-scale, high-precision extraction of ground elevation and vegetation canopy height. Using the Northeast China Tiger and Leopard National Park as our study area, we first processed TECIS data to derive topographic and canopy height profiles. Subsequently, the accuracy of TECIS-derived ground and canopy height estimates was validated using onboard light detection and ranging (LiDAR) measurements. Finally, we systematically evaluated the influence of multiple factors on estimation accuracy. Our analysis revealed that TECIS-derived ground and canopy height estimates exhibited mean errors of 0.7 m and −0.35 m, respectively, with corresponding root mean square error (RMSE) values of 3.83 m and 2.70 m. Furthermore, slope gradient, vegetation coverage, and forest composition emerged as the dominant factors influencing canopy height estimation accuracy. These findings provide a scientific basis for optimizing the screening and application of TECIS data in global forest carbon monitoring. Full article

Reconstructing relationships between urban agglomeration and relevant ecosystems from an ecosystem services perspective and quantitatively assessing their interactive status holds significant implications for achieving coordinated development. Taking Shandong Peninsula Urban Agglomeration (SPUA) as our study area, we developed a Cities-ESV Coupling Index (I) serving as a composite metric for assessing city–ecosystem coupling dynamics through a multidimensional framework encompassing the following: (1) urban development level, (2) ecosystem service value (ESV), (3) ecosystem service physical quantity, and (4) spatial balance degree of ecosystem service, operationalized through 10 selected indicators. Our methodology integrates ESV quantification, biophysical assessment, correlation analysis modeling, and spatial autocorrelation modeling to comprehensively evaluate coupling relationships between cities and ecosystems across 16 cities and 78 counties. This study innovatively integrates ESV quantification with biophysical assessment methodologies in indicator selection, while strategically incorporating spatial agglomeration metrics. The multidimensional framework effectively addresses the prevalent oversimplification in existing ecosystem service measurement paradigms. The findings are as follows: the total ESV is 13,977.87 × 10⁸ CNY/a, which accounts for about 20% of the total GDP of SPUA. The Cities-ESV coupling index (I) of four cities, including Dongying, Linyi, Yantai, and Weifang, ranks among the top in SPUA, while that of seven counties, namely Weshan, Qixia, Yiyuan, Yishui, Mengyin, and Linqu, is at a relatively high-level. The conclusion is as follows: the total ESV in SPUA had been continuously decreasing. The coupling relationship between cities and ecosystems are significantly negatively correlated, and the Cities-ESV coupling index (I) of SPUA has obvious regional differentiation characteristics. Therefore, differentiated ecological land protection policies should be formulated to curb the trend of continuous decline in ESV. Full article

Nitroxides are stable organic free radicals with a wide range of applications. They have found applications in chemistry, biochemistry, biophysics, molecular biology, and biomedicine as EPR/NMR imaging techniques. As spin labels and probes, they are used in electron paramagnetic resonance (EPR) spectroscopy in the study of proteins, lipids, nucleic acids, and enzymes, as well as for measuring oxygen concentration in cells and cellular organelles, as well as tissues and intracellular pH. Their unique redox properties have allowed them to be used as exogenous antioxidants. In this review, we have discussed the chemical properties of nitroxides and their antioxidant properties. Furthermore, we have considered their use as radioprotectors and protective agents in ischemia/reperfusion in vivo and in vitro. We also presented other applications of nitroxides in protecting cells and tissues from oxidative stress and in protein studies and discussed their use in EPR/MRI. Full article

Fluorescent cholesterol probes are indispensable tools for studying membrane structure, dynamics, and trafficking. To better understand the structure–function relationship of fluorescent cholesteryl probes, we developed a series of five new modular naphthalimide-containing cholesteryl probes (CND15–CND19). These probes incorporate an L-lysine linker between the cholesterol moiety and the fluorophore, along with a series of distinct head groups. We conducted extensive biophysical characterizations of these probes, including the determination of their solvatochromic properties and lipid partitioning behavior using giant unilamellar vesicles. Molecular dynamics simulations were employed to identify key molecular interactions of these probes within model lipid membranes. Furthermore, live-cell imaging in 3T3 fibroblasts demonstrated the potential applications of these analogs in live-cell imaging, measuring cellular membrane dynamics and studying cholesterol-related processes. The results of this study underscore the critical role of the linker and head group in designing fluorescent cholesterol-mimicking probes. These findings provide valuable insights into optimizing probe designs for future cholesterol and membrane biology research. Full article

Being an essential issue in global climate warming, the response of urban green spaces to air pollution and climate variability because of rapid urbanization has become an increasing concern at both the local and global levels. This study explored the response of urban vegetation to air pollution and climate variability in the Bucharest metropolis in Romania from a spatiotemporal perspective during 2000–2024, with a focus on the 2020–2024 period. Through the synergy of time series in situ air pollution and climate data, and derived vegetation biophysical variables from MODIS Terra/Aqua satellite data, this study applied statistical regression, correlation, and linear trend analysis to assess linear relationships between variables and their pairwise associations. Green spaces were measured with the MODIS normalized difference vegetation index (NDVI), leaf area index (LAI), photosynthetically active radiation (FPAR), evapotranspiration (ET), and net primary production (NPP), which capture the complex characteristics of urban vegetation systems (gardens, street trees, parks, and forests), periurban forests, and agricultural areas. For both the Bucharest center (6.5 km × 6.5 km) and metropolitan (40.5 km × 40.5 km) test areas, during the five-year investigated period, this study found negative correlations of the NDVI with ground-level concentrations of particulate matter in two size fractions, PM2.5 (city center r = −0.29; p < 0.01, and metropolitan r = −0.39; p < 0.01) and PM10 (city center r = −0.58; p < 0.01, and metropolitan r = −0.56; p < 0.01), as well as between the NDVI and gaseous air pollutants (nitrogen dioxide—NO₂, sulfur dioxide—SO₂, and carbon monoxide—CO. Also, negative correlations between NDVI and climate parameters, air relative humidity (RH), and land surface albedo (LSA) were observed. These results show the potential of urban green to improve air quality through air pollutant deposition, retention, and alteration of vegetation health, particularly during dry seasons and hot summers. For the same period of analysis, positive correlations between the NDVI and solar surface irradiance (SI) and planetary boundary layer height (PBL) were recorded. Because of the summer season’s (June–August) increase in ground-level ozone, significant negative correlations with the NDVI (r = −0.51, p < 0.01) were found for Bucharest city center and (r = −76; p < 0.01) for the metropolitan area, which may explain the degraded or devitalized vegetation under high ozone levels. Also, during hot summer seasons in the 2020–2024 period, this research reported negative correlations between air temperature at 2 m height (TA) and the NDVI for both the Bucharest city center (r = −0.84; p < 0.01) and metropolitan scale (r = −0.90; p < 0.01), as well as negative correlations between the land surface temperature (LST) and the NDVI for Bucharest (city center r = −0.29; p< 0.01) and the metropolitan area (r = −0.68, p < 0.01). During summer seasons, positive correlations between ET and climate parameters TA (r = 0.91; p < 0.01), SI (r = 0.91; p < 0.01), relative humidity RH (r = 0.65; p < 0.01), and NDVI (r = 0.83; p < 0.01) are associated with the cooling effects of urban vegetation, showing that a higher vegetation density is associated with lower air and land surface temperatures. The negative correlation between ET and LST (r = −0.92; p < 0.01) explains the imprint of evapotranspiration in the diurnal variations of LST in contrast with TA. The decreasing trend of NPP over 24 years highlighted the feedback response of vegetation to air pollution and climate warming. For future green cities, the results of this study contribute to the development of advanced strategies for urban vegetation protection and better mitigation of air quality under an increased frequency of extreme climate events. Full article