Size Spectrum Research Articles

Multi-channel prismatic localized surface plasmon resonance biosensor for real-time competitive assay multiple COVID-19 characteristic miRNAs

A multi-channel prismatic localized surface plasmon resonance (LSPR) biosensor was developed for quantitative and real-time detection of multiple COVID-19 characteristic miRNAs. The well-dispersed and dense gold nanoparticles (AuNPs) arrays for LSPR biosensing were fabricated through a nano-thickness diblock copolymer template (BCPT). Both theoretical and experimental analyses were conducted to investigate the effects of particle size, interparticle spacing, and surface coverage on LSPR sensing spectrum and intensity sensitivity of varied AuNPs sizes. A competitive assay strategy was proposed and used for non-amplification miRNA detection with a low limit detection of 3.41 nM, while a four-channel prismatic LSPR system enables parallel detection of multiple miRNAs. Furthermore, this sensing strategy can effectively and specifically identify target miRNA, distinguish mismatched miRNA and interfering miRNA, and exhibit low non-specific adsorption. This BCPT-based LSPR biosensor demonstrates the practicality and potential of a multi-channel, adaptable, and integrated prismatic sensor in medical testing and diagnostic applications.

Morphological characterization of some local watermelon (Citrullus lanatus L.) genotypes of Turkey

The scope of this study, some of the local Turkish watermelon genotypes were evaluated morphologically. A total of 20 local genotypes and three commercial varieties were assessed regarding their cotyledon, leaf, fruit, and seed phenotypes. An extensive morphological analysis was performed on a diverse set of genotypes. Traits such as cotyledon shape and color intensity, leaf size and lobing, and fruit size, shape, and color were measured and compared. Hierarchical clustering analysis, correlation matrices, and principal component analysis were employed to interpret the data. The study revealed significant morphological variability among the watermelon genotypes. Cotyledons ranged from narrow to broad, with a predominance of large sizes and dark green coloration. Leaf characteristics varied widely, with a notable distribution across different sizes and degrees of lobing. Fruit analysis showed a broad spectrum of shapes, sizes, and colors, indicating a rich genetic diversity. Two main genotype clusters were identified, suggesting a clear distinction based on morphological traits.

Assessing water diversion impacts on the fish community size structure in headwater stream stretches

Water diversion for hydropower plants is one of the leading causes of habitat alteration and biotic homogenization. The impacts of small hydropower plants on fish communities are usually assessed using taxonomic composition and structure indicators. Size-based indicators are useful tools to evaluate the effects of environmental factors and anthropogenic perturbations on riverine ecosystems. In this study, we investigated the impact of water diversion on fish community body size structure in 16 small hydropower plants in the upper Ter River basin (NE Iberian Peninsula). We tested the use of multiple size-based metrics under different sampling intensities (one- vs. four-pass electrofishing) and compared control vs. diverted stream stretches. Results revealed that water diversion had a negative effect on fish community average and median length, while size spectrum and size diversity metrics showed no responses to the impact. Altitude was positively related with body size metrics and was the strongest natural driver affecting them. Moreover, we found that all the size-based metrics exhibited consistent values under different sampling efforts. Our findings suggest that size-based metrics could be useful indicators for bioassessment of river flow alteration and that one-pass electrofishing was robust enough to characterize the stream fish community size structure in our study.

Influence of microplastics and biogenic particles on the size spectra of tropical estuarine and marine pelagic ecosystems

Size spectra analysis has been widely used to study pelagic ecosystems worldwide. It has a solid theoretical and empirical basis and can be used to provide useful information on ecosystem structure and trophic efficiency. The objective of this study was to obtain complete Normalized Biovolume Size Spectra (NBSS), including zooplankton, microplastics, and other suspended particles, along an estuary-shelf gradient. Plankton net samples (300 μm mesh) were obtained in the Rio Formoso Estuary, in Tamandaré Bay and on the continental shelf off Tamandaré, Brazil, during two years (from April/2013 to May/2015). Particles were identified by image analysis (ZooScan) and infrared spectroscopy (FTIR). Generally, NBSS slopes were close to −1 (i.e., between −1.09 and −0.85), except for NBSSz (zooplankton only) in the Estuary (−1.59) and in the Bay (−1.44), where the steepest slopes were observed, due to the importance of small-sized zooplankton in these areas. The NBSSz slope was significantly steeper in the Estuary and in the Bay than on the Shelf. The inclusion of particles into the NBSS (NBSSp) turned the slope significantly less steep in the Estuary and in the Bay. Intercepts were significantly higher in the Estuary than in the other areas, after including particles in the analysis (NBSSp), due to the extremely high total volume of biogenic particles in the estuary. The most relevant impacts of microplastics were detected within the larger size classes (> 2.60 mm Feret length, > 0.58 log10 mm3). In the Estuary, large-sized microplastics were similarly important (in terms of volume) as zooplankton. Large-sized polyethylene and polypropylene were more relevant in the Bay, large-sized nylon fibers on the Shelf (in the rainy season). The present study, a pioneering effort towards a synthetic analysis of zooplankton, microplastics, and other particles, highlights the importance of including non-living particles in size-based studies and ecosystem models.

Relationships Between Plankton Size Spectra, Net Primary Production, and the Biological Carbon Pump

AbstractPhotosynthesis in the surface ocean and subsequent export of a fraction of this fixed carbon leads to carbon dioxide sequestration in the deep ocean. Ecological relationships among plankton functional groups and theoretical relationships between particle size and sinking rate suggest that carbon export from the euphotic zone is more efficient when communities are dominated by large organisms. However, this hypothesis has never been tested against measured size spectra spanning the >5 orders of magnitude found in plankton communities. Using data from five ocean regions (California Current Ecosystem, North Pacific subtropical gyre, Costa Rica Dome, Gulf of Mexico, and Southern Ocean subtropical front), we quantified carbon‐based plankton size spectra from heterotrophic bacteria to metazoan zooplankton (size class cutoffs varied slightly between regions) and their relationship to net primary production and sinking particle flux. Slopes of the normalized biomass size spectra (NBSS) varied from −1.6 to −1.2 (median slope of −1.4 equates to large 1–10 mm organisms having a biomass equal to only 7.6% of the biomass in small 1–10 μm organisms). Net primary production was positively correlated with the NBSS slope, with a particularly strong relationship in the microbial portion of the size spectra. While organic carbon export co‐varied with NBSS slope, we found only weak evidence that export efficiency is related to plankton community size spectra. Multi‐variate statistical analysis suggested that properties of the NBSS added no explanatory power over chlorophyll, primary production, and temperature. Rather, the results suggest that both plankton size spectra and carbon export increase with increasing system productivity.

Quantitative and rapid detection of nanoplastics labeled by luminescent metal phenolic networks using surface-enhanced Raman scattering

The escalating prevalence of nanoplastics contamination in environmental ecosystems has emerged as a significant health hazard. Conventional analytical methods are suboptimal, hindered by their inefficiency in analyzing nanoplastics at low concentrations and their time-intensive processes. In this context, we have developed an innovative approach that employs luminescent metal–phenolic networks (L-MPNs) coupled with surface-enhanced Raman spectroscopy (SERS) to separate and label nanoplastics, enabling rapid, sensitive and quantitative detection. Our strategy utilizes L-MPNs composed of zirconium ions, tannic acid, and rhodamine B to uniformly label nanoplastics across a spectrum of sizes (50–500 nm) and types (e.g., polystyrene, polymethyl methacrylate, polylactic acid). Rhodamine B (RhB) functions as a Raman reporter within these L-MPNs-based SERS tags, providing the requisite sensitivity for trace measurement of nanoplastics. Moreover, the labeling with L-MPNs aids in the efficient separation of nanoplastics from liquid media. Utilizing a portable Raman instrument, our methodology offers cost-effective, swift, and field-deployable detection capabilities, with excellent sensitivity in nanoplastic analysis and a detection threshold as low as 0.1 μg/mL. Overall, this study proposes a highly promising strategy for the robust and sensitive analysis of a broad spectrum of particle analytes, underscored by the effective labeling performance of L-MPNs when coupled with SERS techniques.

Quantifying Exhaled Particles in Healthy Humans During Various Respiratory Activities Under Realistic Conditions.

Background: Quantitatively collecting and characterizing exhaled aerosols is vital for infection risk assessment, but the entire droplet size spectrum has often been neglected. We analyzed particle number and size distribution of healthy participants in various respiratory activities, considering inter-individual variability, and deployed a simplified far-field model to inform on infection risks. Methods: Participants repeated the same respiratory activities on two visits. Particles were collected using an airtight extraction helmet supplied with High Efficiency Particulate Air (HEPA) filtered air. The sampling volume flow was transported to two particle counters covering the small and large particle spectrum. The applied simple mass balance model included respiratory activity, viral load, room size, and air exchange rates. Results: Thirty participants completed the study. The major fraction of the number-based size distribution was <5 μm in all respiratory activities. In contrast, the major fraction of the volume-based size distribution was 2-12 μm in tidal breathing, but >60 μm in all other activities. Aerosol volume flow was lowest in tidal breathing, 10-fold higher in quiet/normal speaking, deep breathing, coughing, and 100-fold higher in loud speaking/singing. Intra-individual reproducibility was high. Between participants, aerosol volume flow varied by two orders of magnitude in droplets <80 μm, and three orders of magnitude in droplets >80 μm. Simple model calculations not accounting for potential particle size-dependent differences in viral load and infection-related differences were used to model airborne pathogen concentrations. Conclusions: Quantitative analysis of exhaled aerosols for the entire droplet size spectrum as well as the variability in aerosol emission between individuals provides information that can support infection research. Clinical Trial Registration number: NCT04771585.

Abstract 3557: A pancancer gamma delta T cell repertoire atlas

Abstract While representing only a small portion of T cell population, Gamma delta (γδ) T cells have unique contributions to both innate and adaptive immunity. Compared to αβ T, γδ T cells have a more diverse TCR repertoire, allowing them to recognize a broader range of tumor antigens. Recent breakthrough discoveries indicate that the antitumor efficacy of γδ T cells can be potentiated or rescued through targeted therapeutic approaches. Despite their functional and translational significance, a comprehensive understanding of the γδ T cell repertoire within tumor tissues has yet to be fully achieved.In this work, we generated a pan-cancer γδ T cell repertoire Atlas through reanalyzing RNA-seq data from more than 11,000 tumors in TCGA utilizing TRUST4, an advanced computational method for reconstruction of TCR repertoires. This allowed us to offer the most accurate and comprehensive examination of the γδ TCR landscape spanning 33 cancer types, marking it the largest collection of γδ clones on human cancer to date. We processed 660 billion RNAseq reads, identified ~3 million CDR3 reads, applied a series of stringent filtering criteria to remove biologically implausible, ambiguous sequences, and out-of-frame TCRs, which resulted in 22,205 unique γδ TCR clones from 6,751 tumors. TCR gene enrichment scores were calculated to represent overall expression of γδ in each tumor. The γδ enrichment is highly variable between and within cancer types. As expected, tumors traditionally classified as immune-cold (UVM and GBM) show the lowest scores. Cancers intrinsically related to lymphatic system (LAML, THYM and DLBC), exhibit the highest scores. Beyond THYM, the top five solid-tumor cancers carrying the highest enrichment are PRAD, KIRC, TGCT, LUAD and KICH. We further profiled the clone counts, spectrum of clone sizes, CDR3 length, V-J pair usage, and clonality in 33 cancers. Overall, a dominant presence of large clone segment is not observed in most cancers. The most prevalent V-J pairs are TRGV10/9/2-TRGJ1 for γ, and TRDV1-TRDJ1 for δ chain. Cancers including LAML, KIRC, LUAD, SKCM, CESC, LUSC, STAD, display a relatively higher proportion of intermediate to larger clones. THYM exists the highest γδ diversity, with the lowest clonality and most diverse V-J pairs. In addition, we evaluated the prognostics value of γδ genes by multivariate Cox regression, adjusting for age, sex, stage, and tumor purity, and identified 38 γδ genes associated with patient survival with p&amp;lt;0.05 in 25 cancer types. Finally, within HNSC, we observed higher γδ gene enrichment (p=1.6e-9) and clone diversity (p=0.014) in HPV+ vs. HPV- tumors. The γδ gene enrichment is also found associated with patients’ survival (p=0.002) in HPV+, but not in HPV- HNSC. Similarly, COAD tumors with high Microsatellite Instability (MSI) shows higher γδ gene enrichment and clone diversity compared to MSI low COAD. Collectively, our findings serve as a foundational resource for γδ T cell research in oncology. . Citation Format: Xiaoqing Yu, Song Li, Ling Cen, Xuefeng Wang. A pancancer gamma delta T cell repertoire atlas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3557.

Bayesian hierarchical modelling of size spectra

Abstract A fundamental pattern in ecology is that smaller organisms are more abundant than larger organisms. This pattern is known as the individual size distribution (ISD), which is the frequency distribution of all individual body sizes in an ecosystem. The ISD is described by a power law and a major goal of size spectra analyses is to estimate the exponent of the power law, λ. However, while numerous methods have been developed to do this, they have focused almost exclusively on estimating λ from single samples. Here, we develop an extension of the truncated Pareto distribution within the probabilistic modelling language Stan. We use it to estimate multiple λs simultaneously in a hierarchical modelling approach. The most important result is the ability to examine hypotheses related to size spectra, including the assessment of fixed and random effects, within a single Bayesian generalized mixed model. While the example here uses size spectra, the technique can also be generalized to any data that follow a power law distribution.

Influence of different thermodynamic parameters on variation across the aerosol size spectrum

During a severe accident in a nuclear power plant, fission products can be released into the containment in the form of radioactive aerosols. The behavior of these aerosols is influenced by various thermodynamic parameters, including temperature, pressure, and relative humidity. Changes in these parameters can impact the aerosol size spectrum, leading to variation in aerosol transport and deposition. Having a comprehensive grasp of how thermodynamic parameters impact change in the aerosol size spectrum is crucial for managing and mitigating the consequences of a severe accident, as it allows for better prediction of aerosol behavior and appropriate interventions. A series of experimental works on in-/soluble aerosols and their mixtures has been carried out using the IN–EX facility located at the Forschungszentrum Juelich the Germany. The changes in the aerosol size spectrum of SnO2 , CsI and two different mass composition mixtures (SnO2 : CsI = 7:3 or 4:6) under various thermodynamic conditions are discussed and analyzed. The results show that increasing the temperature leads to a broader aerosol spectrum for SnO2 , but not for CsI aerosols. With the increasing pressure, the aerosol size spectrum shifts towards smaller particles for CsI, but not for SnO2 . Furthermore, increasing the relative humidity causes the aerosol size spectrum of both SnO2 and CsI particles to shift towards larger particles, whereas CsI particles are more pronounced. The behavior of such mixtures relies on the composition of the primary substance within it. These findings provide robust information for improving the strategies of severe accident management.

Ultrasensitive Silicon Photonic Refractive Index Sensor Based on Hybrid Double Slot Subwavelength Grating Microring Resonator.

Silicon photonic-based refractive index sensors are of great value in the detection of gases, biological and chemical substances. Among them, microring resonators are the most promising due to their compact size and narrow Lorentzian-shaped spectrum. The electric field in a subwavelength grating waveguide (SWG) is essentially confined in the low-refractive index dielectric, favoring enhanced analyte-photon interactions, which represents higher sensitivity. However, it is very challenging to further significantly improve the sensitivity of SWG ring resonator refractive index sensors. Here, a hybrid waveguide blocks double slot subwavelength grating microring resonator (HDSSWG-MRR) refractive index sensor operating in a water refractive index environment is proposed. By designing a new waveguide structure, a sensitivity of up to 1005 nm/RIU has been achieved, which is 182 nm/RIU higher than the currently highest sensitivity silicon photonic micro ring refractive index sensor. Meanwhile, utilizing a unique waveguide structure, a Q of 22,429 was achieved and a low limit of detection of 6.86 × 10-5 RIU was calculated.

Precise Spectral Overlap-Based Donor-Acceptor Pair for a Sensitive Traffic Light-Typed Bimodal Multiplexed Lateral Flow Immunoassay.

Bimodal-type multiplexed immunoassays with complementary mode-based correlation analysis are gaining increasing attention for enhancing the practicability of the lateral flow immunoassay (LFIA). Nonetheless, the restriction in visually indistinguishable multitargets induced by a single fluorescent color and difficulty in single acceptor ineffectual fluorescence quenching due to the various spectra of multiple different donors impede the further execution of colorimetric-fluorescence bimodal-type multiplexed LFIAs. Herein, the precise spectral overlap-based donor-acceptor pair construction strategy is proposed by regulating the size of the nanocore, coating it with an appropriate nanoshell, and selecting a suitable fluorescence donor with distinct colors. By in situ coating Prussian blue nanoparticles (PBNPs) on AuNPs with a tunable size and absorption spectrum, the resultant APNPs demonstrate efficient fluorescence quenching ability, higher colloidal stability, remarkable colorimetric intensity, and an enhanced antibody coupling efficiency, all of which facilitate highly sensitive bimodal-type LFIA analysis. Following integration with competitive-type immunoreaction, this precise spectral overlap-supported spatial separation traffic light-typed colorimetric-fluorescence dual-response assay (coined as the STCFD assay) with the limits of detection of 0.013 and 0.152 ng mL-1 for ractopamine and clenbuterol, respectively, was proposed. This work illustrates the superiority of the rational design of a precise spectral overlap-based donor-acceptor pair, hinting at the enormous potential of the STCFD assay in the point-of-care field.

Object Detection in Remote Sensing Images Based on Adaptive Multi-Scale Feature Fusion Method

Multi-scale object detection is critical for analyzing remote sensing images. Traditional feature pyramid networks, which are aimed at accommodating objects of varying sizes through multi-level feature extraction, face significant challenges due to the diverse scale variations present in remote sensing images. This situation often forces single-level features to span a broad spectrum of object sizes, complicating accurate localization and classification. To tackle these challenges, this paper proposes an innovative algorithm that incorporates an adaptive multi-scale feature enhancement and fusion module (ASEM), which enhances remote sensing image object detection through sophisticated multi-scale feature fusion. Our method begins by employing a feature pyramid to gather coarse multi-scale features. Subsequently, it integrates a fine-grained feature extraction module at each level, utilizing atrous convolutions with varied dilation rates to refine multi-scale features, which markedly improves the information capture from widely varied object scales. Furthermore, an adaptive enhancement module is applied to the features of each level by employing an attention mechanism for feature fusion. This strategy concentrates on the features of critical scale, which significantly enhance the effectiveness of capturing essential feature information. Compared with the baseline method, namely, Rotated FasterRCNN, our method achieved an mAP of 74.21% ( 0.81%) on the DOTA-v1.0 dataset and an mAP of 84.90% (+9.2%) on the HRSC2016 dataset. These results validated the effectiveness and practicality of our method and demonstrated its significant application value in multi-scale remote sensing object detection tasks.

Deep-sea meiofaunal communities in the south-eastern Levantine basin and their shaping factors - Morphological-taxonomy-free metabarcoding approach.

The <3% dissimilar Amplicon Sequence Variant (ASV) clusters of the 18S-V4 barcode were used as species-proxies for the evaluation of ASV composition and ASV diversity indices characterizing the hitherto poorly investigated meiofaunal communities of the south-eastern part of the Levantine basin. Accompanied by abundance measurements, the relationships of these characteristics with sedimentary and bottom terrain parameters were interpreted. The construction of community composition profiles, namely ASVs' list and their estimated abundances, was done using our previously established procedure (Harbuzov etal., 2022, Marine Genomics 65, 100980), combining metabarcoding with sample reads normalization by the abundance of hard-bodied meiofaunal taxa. The study province included the 54-1418 m depth range, across vertical sub-bottom horizons ranging 0-17 cm. Oxygen, hydrogen sulfide and methane concentrations in the pore water, as well as sediment grain size spectra and sedimentary protein and carbohydrate levels, were measured, followed by an evaluation of their involvement in the shaping of the meiofaunal communities' characteristics. Community composition was generally site-and-horizon dependent and its abundance decreased with increasing bottom depth and across sub-bottom horizons, typical to benthic habitats which are nourished by organic carbon from the euphotic zone. The relatively sharply inclined continental slope bottom located in the northern part of the Israeli coast was an exception. Its meiofaunal community characteristics were speculated to be affected by intensive sediment mixing and lateral transport of food from the shelf, in addition to the effect of the euphotic zone-originated food sources.

Continuous Zonal Gradients Characterize Epipelagic Plankton Assemblages and Hydrography in the Subtropical North Atlantic

The subtropical North Atlantic is a key region for understanding climate impact in the ocean. Plankton studies in this region have been generally framed in biogeographic provinces or focused on latitudinal gradients. In this study, we demonstrate the benefits of using empirically constructed continuous gradients versus the use of average values for biogeographical provinces to characterize plankton assemblages along a longitudinal transect at 24.5° N using an unprecedented array of stations including hydrographic observations, abundance of phytoplankton and zooplankton, and plankton size spectra in the epipelagic layer (0–200 m). In addition, the variability of zooplankton assemblages was analyzed using detailed taxonomic identification at selected stations. We found significant gradients in most hydrographic and plankton variables. The former, including surface temperature and salinity, the depth of the upper mixing layer, and the depth of the chlorophyll maximum, displayed non-linear gradients with maximum or minimum values near the center of the transect. In contrast, most plankton variables showed linear zonal gradients. Phytoplankton, microzooplankton (&lt;100 µm), and the slope and the intercept of the size spectra increased (and Trichodesmium decreased) to the west. Total mesozooplankton (&gt;200 µm) did not show any significant zonal pattern, but the taxonomic assemblages were characterized by a gradual replacement of large Calanoids by small-bodied Cyclopoid copepods from east to west. The use of continuous gradients provides more detailed information on the zonal structure of subtropical plankton than the classical approach using discrete areas.

High‐precision body mass predictors for small mammals: a case study in the Mesozoic

AbstractBody mass is a pivotal quantity in palaeobiology but must be inferred from an imperfect fossil record. We analyse the performance of regression models derived from various dentoskeletal predictors in mammals to inform fossils from the early, Mesozoic history of this radiation. Our focus is on the critical small end of the size spectrum; critical because the earliest mammals were small, because small size persisted onto the stems of the major extant radiations, and because small mammals compose a large proportion of crown diversity. The sampling strategy is diverse in terms of both phylogeny and skeletal predictors: the former allows a general application, while the latter enables comparison of various models. Linear regressions based on extant small mammals indicate a universal correlation of body mass with observed measurements, but with clear differences in precision. Postcranial predictors outperform jaw and dental metrics, with certain femoral joint dimensions providing surprisingly precise predictions. Our results indicate complex patterns of size evolution within the small‐bodied category, including the possibility that multiple Mesozoic species approached the theoretical lower limit of mammalian body size. The ability to study such dynamics only becomes possible when predicting body mass within a strict, highly focused phylogenetic context. The heuristic value of the models we provide here is not limited to the Mesozoic but is applicable to small‐bodied mammals of any geologic age.

Temperature‐Dependence Assumptions Drive Projected Responses of Diverse Size‐Based Food Webs to Warming

AbstractFood web projections are critical for evaluating potential risks to ecosystems and fisheries under global warming. The temperature dependence of biological processes and regional differences in food web structure are two important sources of uncertainty and variation in climate forced projections of fish communities, but we do not know their magnitude or relative contribution. Here we systematically evaluated a range of different assumptions about temperature‐dependence on rates, including size‐dependent effects, controlling food intake, metabolism, and non‐predation mortality in fishes using species‐resolved size spectrum food web models that link individual‐level physiological processes to population and community dynamics. We simulated the physiological effect of warming in a range of size‐structured food web models calibrated to different marine ecosystems and in simplified trait‐based models. Higher food intake in warmed conditions increased total fish biomass, catches, and mean body weight, but these effects were offset by the negative effects of warming on metabolism and mortality, which combined resulted in lower total biomasses and catches for most food webs. These effects were enhanced when warming increased metabolic rates more than food intake, and the outcomes were also sensitive to size dependency of temperature responses. Importantly, these general patterns were not uniform across all food webs—individual functional groups and fish species within food webs responded to warming in different ways depending on their position in the food web and its structure. Hence, caution is warranted when generalizing food web or species outcomes to warming because they are mediated by community interactions. Uncertainty related to temperature dependence and ecological interactions will impact food web projections and should be represented in climate change projections.

Overview of Predation by Birds, Cephalopods, Fish and Marine Mammals on Marine Benthic Amphipods

With about 8000 marine benthic species, the amphipod crustaceans form one of the richest animal groups of the worldwide Ocean. They have colonized a wide range of soft- and hard-bottom natural and artificial habitats extending from the intertidal to hadal zones. Moreover, they show a broad size spectrum, with numerous giant species exceeding 20 cm in length and some species smaller than 2 mm. When biofouling artificial hard surfaces, some tube-building species can form very dense populations comprising up to 100,000 individuals per square meter. Amphipods are important prey for fish and mammals. Along with cephalopod juveniles, they are also included in the trophic diet of shorebirds that consume amphipods mostly during the low tide on tidal flats. They display diel migration, which reinforces the predation by demersal fish in the suprabenthic zone just above the sea bed, as well as by pelagic fish in the water column. Despite their importance in terms of biodiversity and trophic transfer, no general overview is available on the role of benthic amphipods in marine ecosystem food webs. Various methods, including laboratory and field experiments, as well as the analysis of stomach contents and DNA extraction, have been used to identify the prey/predator trophic links. Based on an extensive literature review, this study discusses the role of marine benthic amphipods as potential food for higher trophic levels in natural and artificial hard-bottom communities created via the construction of offshore wind farms.

99mTc-AgNPs-ICG: nanoparticle for hybrid image

Introduction: Currently nanotechnology has radically changed the diagnosis of many human pathologies. The aim of this work is to obtain silver nanoparticles for hybrid imaging (99mTc-AgNPs-ICG) having potential clinical imaging applications. Materials and method: We mixed 2 ml of ascorbic acid (1.7x10-4 M), 5 mCi of 99mTcO4- , 2 ml of citric acid (8.0x10-4 M) and 0.5 ml of silver nitrate (2.5x10-3 M). Solution pH was 5, and it was shaken for 20 minutes at 37º C. Afterwards, 2 µL of Indocyanine Green (1.3x10-3 M) was added (99mTc-AgNPs-ICG). Physiochemical properties of the solution were characterized by UV (λ1 = 420 nm, λ2 = 254 nm) and gamma detector. Fluorescence image, particle size and IR spectrum were evaluated. Results: Silver nanoparticles were obtained in aqueous solution a pH of 5. Their pH, color and spectrum were stable for seven days. Furthermore, the principal peak characterized by HPLC, UV and Gamma detector had similar retention times. Its UV spectrum showed an absorption band of 420 nm, which corresponds to the plasmon absorption band of these nanoparticles. The particle size was 46 nm ± 1.5 nm. The IR spectrum showed absorption bands in 3193, 2624, 1596 y 1212 cm-1. Conclusions: We describe for the first time in literature the synthesis of hybrid (radioactive and fluorescent) silver nanoparticles. Their physiochemical properties were characterized, being stable and their labelling was reproducible having potential biomedical applications. Received for review: November 2023. Accepted for publication: February 2024. Correspondence: Centro de Investigaciones Nucleares, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay. Mataojo 2055, P.O. 11400, Montevideo, Uruguay. Tel: (+5982) 5250901/108; fax: (+5982) 5250895. Contact e-mail: pabloc7@gmail.com This article was approved by the Editorial Committee.

Development of the Latest Technology Based Accounting Information System to Increase Company Efficiency

This research explores the impact of developing Accounting Information Systems (AIS) based on cutting-edge technology on company efficiency. We gathered data from questionnaires distributed to companies that have adopted state-of-the-art technology in their AIS. The research results indicate that the use of artificial intelligence (AI) significantly enhances operational efficiency in companies. Companies adopting blockchain technology also achieve higher levels of user satisfaction. User training and company size also have a positive impact on efficiency and better decision-making.In the discussion, we highlight the importance of investing in user training and maintaining state-of-the-art technology. We also acknowledge that implementation costs can be a constraint, particularly for smaller companies. This research has certain limitations, including a sample that may not cover the entire spectrum of industries and company sizes. However, further research can delve deeper through case studies. In the continually evolving business world, the development of AIS based on cutting-edge technology is a key factor in achieving efficiency, better decision-making, and user satisfaction. Companies must understand and address these challenges to attain a competitive edge and long-term success.