Structural Dissimilarity Research Articles

The microbiota comparative analysis of the characteristics between colorectal adenomatous polyps and normal mucosal intestinal.

The aim of this study is to systematically examine and compare the characteristics distinguishing colorectal adenomatous polyps from normal mucosal intestinal microbiota. A total of 30 specimens were obtained from patients diagnosed with colorectal adenomatous polyps (adenoma group) who underwent endoscopic removal at Wenzhou People's Hospital between September 2021 and November 2021. Concurrently, 30 normal mucosal specimens were collected from patients without adenomatous polyps (control group). Subsequently, microbiome total DNA extraction was carried out, followed by PCR amplification targeting the V3-V4 region of the 16S rDNA. High-throughput sequencing was conducted using the Illumina MiSeq platform. Subsequent to sequencing, bioinformatics analysis was used to assess the diversity, composition, and functional aspects of the intestinal microbiota in both study groups. A notable dissimilarity in the microbiota structure was identified, specifically within the transverse colon, between these two groups ( P < 0.05). Species composition analysis revealed that Escherichia , Fusobacterium , and Bacteroides were predominant bacteria in both groups, with Escherichia and Enterobacter displaying significant differences at the genera level between the control group and the adenoma group ( P < 0.05). Correlation analysis and functional prediction demonstrated substantial disparities in interactions among dominant intestinal microbial genera within patients from both groups. Additionally, it was discovered that the intestinal microbiomes in patients in the adenoma group exhibited a significantly higher pathogenic potential. Upon conducting a comprehensive analysis, it was discerned that the microbiota present in the transverse colon of the control group exhibited distinctive characteristics that may contribute to the maintenance of intestinal health.

Enhanced oceanic fog nowcasting through satellite-based recurrent neural networks

ABSTRACT The presence of fog in offshore regions poses significant hazards to navigation and aviation, making fog nowcasting indispensable for various industries, including oil and gas. This study presented a novel approach utilizing Recurrent Neural Networks (RNN) within a deep learning framework to address this need. Leveraging geostationary GOES-16 satellite data from the summers of 2018 and 2019, fog maps were generated as input. The model incorporated Convolutional Long Short-Term Memory (ConvLSTM) layers and was trained with a unique loss function combining Minimum Squared Error (MSE) and structural DISSIMilarity (DSSIM) metrics. Validation results demonstrated an approximate 60% accuracy for both two-hour and three-hour nowcasting. Furthermore, evaluation against in-situ data from an offshore platform revealed a Probability of Detection (PoD) of 0.75 and False Alarm Rate (FAR) of 0.14 for two-hour nowcasting, PoD of 0.75 and FAR of 0.20 for three-hour nowcasting, and PoD of 0.70 and FAR of 0.20 for six-hour nowcasting. These findings suggested the operational viability of the proposed method for short-term fog forecasting in offshore environments.

Sequence-Similar Protein Domain Pairs With Structural or Topological Dissimilarity.

For a variety of applications, protein structures are clustered by sequence similarity, and sequence-redundant structures are disregarded. Sequence-similar chains are likely to have similar structures, but significant structural variation, as measured with RMSD, has been documented for sequence-similar chains and found usually to have a functional explanation. Moving two neighboring stretches of backbone through each other may change the chain topology and alter possible folding paths. The size of this motion is compatible to a variation in a flexible loop. We search and find domains with alternate chain topology in CATH4.2 sequence families relatively independent of sequence identity and of structural similarity as measured by RMSD. Structural, topological, and functional representative sets should therefore keep sequence-similar domains not just with structural variation but also with topological variation. We present BCAlign that finds Alignment and superposition of protein Backbone Curves by optimizing a user chosen convex combination of structural derivation and derivation between the structure-based sequence alignment and an input sequence alignment. Steric and topological obstructions from deforming a curve into an aligned curve are then found by a previously developed algorithm. For highly sequence-similar domains, sequence-based structural alignment better represents the chains motion and generally reveals larger structural and topological variation than structure-based does. Fold-switching protein pairs have been reported to be most frequent between X-ray and NMR structures and estimated to be underrepresented in the PDB as the alternate configuration is harder to resolve. Here we similarly find chain topology most frequently altered between X-ray and NMR structures.

Turbulence scale and strength analysis in the roughness and inertial sublayers over urban areas: A wind tunnel study

The dissimilarity of dynamics and turbulence structures between the roughness and inertial sublayers (RSL, ISL) over roughness elements show that ISL turbulence is much more homogeneous. Conventional logarithmic law of the wall is merely applicable for the RSL mean-wind-speed profiles. To characterize the turbulence scales and elucidate the mechanism, the flows in the atmospheric surface layer (ASL) over real urban morphology are measured in wind tunnel experiments fabricated by 3D-printing, reduced-scale model of downtown Kowloon Peninsula, Hong Kong. Elevated dispersive stress at urban canopy signifies the influence from individual buildings and inhomogeneous RSL flows. A positive momentum contribution appears in the low-frequency regime. The large-scale turbulence in RSL thus enhances the mixing and transport, resulting in inhomogeneous flows. The contribution from ejection Q2 and sweep Q4 increases and decreases, respectively, with increasing RSL motion strength. The conventional −5/3 law is observed by empirical mode decomposition (EMD) and the largest amplitude fluctuation occurs more often when the turbulence length scale is comparable to the turbulent boundary layer (TBL) thickness. The single-point amplitude modulation (AM) shows that the large- and small-scale turbulence correlates tightly at the bottom of RSL. Besides, the joint probability density function (JPDF) illustrates that accelerating large scales often occur with decelerating small scales, and they are intensified with increasing wall-normal distance. As a result, large-scale turbulence influences substantially the flow structures over urban areas and the small-scale turbulence (even) in RSLs in the vicinity of building obstacles.

Two new species of Dulcicalothrix (Nostocales, Cyanobacteria) from India and erection of Brunnivagina gen. nov., with observations on the problem of using multiple ribosomal operons in cyanobacterial taxonomy.

Two new species of Dulcicalothrix, D. adhikaryi sp. nov. and D. iyengarii sp. nov., were discovered in India and are characterized and described in accordance with the rules of the International Code of Nomenclature for algae, fungi, and plants (ICN). As a result of phylogenetic analysis, Calothrix elsteri is reassigned to Brunnivagina gen. nov. During comparison with all Dulcicalothrix for which sequence data were available, we observed that the genus has six ribosomal operons in three orthologous types. Each of the three orthologs could be identified based upon indels occurring in the D1-D1' helix sequence in the ITS rRNA region between the 16S and 23S rRNA genes, and in these three types, there were operons containing ITS rRNA regions with and without tRNA genes. Examination of complete genomes in Dulcicalothrix revealed that, at least in the three strains for which complete genomes are available, there are five ribosomal operons, two with tRNA genes and three with no tRNA genes in the ITS rRNA region. Internal transcribed spacer rRNA regions have been consistently used to differentiate species, both on the basis of secondary structure and percent dissimilarity. Our findings call into question the use of ITS rRNA regions to differentiate species in the absence of efforts to obtain multiple operons of the ITS rRNA region through cloning or targeted PCR amplicons. The ITS rRNA region data for Dulcicalothrix is woefully incomplete, but we provide herein a means for dealing with incomplete data using the polyphasic approach to analyze diverse molecular character sets. Caution is urged in using ITS rRNA data, but a way forward through the complexity is also proposed.

Attention Heat Map-Based Black-Box Local Adversarial Attack for Synthetic Aperture Radar Target Recognition

Synthetic aperture radar (SAR) automatic target recognition (ATR) models based on deep neural networks (DNNs) are susceptible to adversarial attacks. In this study, we proposed an SAR black-box local adversarial attack algorithm named attention heat map- based black-box local adversarial attack (AH-BLAA). First, we designed an attention heat map extraction module combined with the layer-wise relevance propagation (LRP) algorithm to obtain the high concerning areas of the SAR-ATR models. Then, to gener- ate SAR adversarial attack examples, we designed a perturbation generator module, introducing the structural dissimilarity (DSSIM) metric in the loss function to limit image distortion and the dif- ferential evolution (DE) algorithm to search for optimal perturba- tions. Experimental results on the MSTAR and FUSAR-Ship datasets showed that compared with existing adversarial attack algorithms, the attack success rate of the AH-BLAA algorithm increased by 0.63% to 33.59% and 1.05% to 17.65%, respectively. Moreover, the low- est perturbation ratios reached 0.23% and 0.13%, respectively.

Different macrophytes and eutrophic gradients regulate microbial communities of phytoremediation for eutrophication pollution and carbon reduction

Phytoremediation on eutrophicated ecosystems has received growing research interest, and macrophytes and eutrophic gradients are considered as key influencing factors. This study used Vallisneria natans, Iris pseudacorus, and their mixed plantings in aquatic ecosystems (9 m × 2 m × 0.5 m, L × W × D) receiving increased eutrophic nitrogen and phosphorus gradients (4, 40, 80 mg/L of nitrogen and 0.4, 4, 8 mg/L of phosphorus), to unveil phytoremediation effects and corresponding microbial mechanisms. Different phytoremediations could effectively improve water quality with removal efficiencies of 57.4%–98.7% on ammonium, 45.7%–93.7% on total nitrogen, 46.7%–100% on available phosphorus, and 38.4%–95.2% on total phosphorus, respectively. Macrophytes and eutrophic gradients jointly affected diversities, compositions, structures, interactions, and functions of sedimental bacterial and archaeal communities. Microbial diversities increased with macrophytes presence and increased eutrophic gradients. Principal component analysis demonstrated that different macrophytes diverged microbial community structures, and increment of eutrophic gradients reduced structural dissimilarities. Dominant compositional communities, including Chloroflexi, Firmicutes, Proteobacteria, Anaerolineae, and Nitrososphaeria, were also keystone taxa of community co-occurrence networks in phytoremediations. Increased eutrophic gradients enhanced microbial cooperative interactions, whilst V. natans fostered bacterial interactions, and I. pseudacorus and mixed plantings strengthened archaeal interactions. Functional prediction indicated that bacterial “phosphate transferase” and archaeal “methanogenesis” were significantly reduced, whilst archaeal “nitrification”, “denitrification”, “comammox”, and “methane oxidation” were elevated by macrophytes and eutrophic gradients, indicating likely mechanisms for nutrient and GHGs metabolisms. This study extended our knowledge on microbial mechanisms of phytoremediations with different macrophytes treating eutrophicated waters of increased gradients, therefore providing references for further developing phytoremediation technologies.

Sustainable Aviation Fuel Molecules from (Hemi)Cellulose: Computational Insights into Synthesis Routes, Fuel Properties, and Process Chemistry Metrics.

Production of sustainable aviation fuels (SAFs) can significantly reduce the aviation industry's carbon footprint. Current pathways that produce SAFs in significant volumes from ethanol and fatty acids can be costly, have a relatively high carbon intensity (CI), and impose sustainability challenges. There is a need for a diversified approach to reduce costs and utilize more sustainable feedstocks effectively. Here, we map out catalytic synthesis routes to convert furanics derived from the (hemi)cellulosic biomass to alkanes and cycloalkanes using automated network generation with RING and semiempirical thermochemistry calculations. We find >100 energy-dense C8-C16 alkane and cycloalkane SAF candidates over 300 synthesis routes; the top three are 2-methyl heptane, ethyl cyclohexane, and propyl cyclohexane, although these are relatively short. The shortest, least endothermic process chemistry involves C-C coupling, oxygen removal, and hydrogen addition, with dehydracyclization of the heterocyclic oxygens in the furan ring being the most endothermic step. The global warming potential due to hydrogen use and byproduct CO2 is typically 0.7-1 kg CO2/kg SAF product; the least CO2 emitting routes entail making larger molecules with fewer ketonization, hydrogenation, and hydrodeoxygenation steps. The large number of SAF candidates highlights the rich potential of furanics as a source of SAF molecules. However, the structural dissimilarity between reactants and target products precludes pathways with fewer than six synthetic steps, thus necessitating intensified processes, integrating multiple reaction steps in multifunctional catalytic reactors.

Convolutional neural network advances in demosaicing for fluorescent cancer imaging with color-near-infrared sensors.

Single-chip imaging devices featuring vertically stacked photodiodes and pixelated spectral filters are advancing multi-dye imaging methods for cancer surgeries, though this innovation comes with a compromise in spatial resolution. To mitigate this drawback, we developed a deep convolutional neural network (CNN) aimed at demosaicing the color and near-infrared (NIR) channels, with its performance validated on both pre-clinical and clinical datasets. We introduce an optimized deep CNN designed for demosaicing both color and NIR images obtained using a hexachromatic imaging sensor. A residual CNN was fine-tuned and trained on a dataset of color images and subsequently assessed on a series of dual-channel, color, and NIR images to demonstrate its enhanced performance compared with traditional bilinear interpolation. Our optimized CNN for demosaicing color and NIR images achieves a reduction in the mean square error by 37% for color and 40% for NIR, respectively, and enhances the structural dissimilarity index by 37% across both imaging modalities in pre-clinical data. In clinical datasets, the network improves the mean square error by 35% in color images and 42% in NIR images while enhancing the structural dissimilarity index by 39% in both imaging modalities. We showcase enhancements in image resolution for both color and NIR modalities through the use of an optimized CNN tailored for a hexachromatic image sensor. With the ongoing advancements in graphics card computational power, our approach delivers significant improvements in resolution that are feasible for real-time execution in surgical environments.

Higher‐order dissimilarity in biodiversity: Identifying dissimilarities of spatial or temporal dissimilarity structures

Abstract Elucidating biodiversity patterns and their background processes is critical in biodiversity science. Dissimilarity, which is calculated based on multivariate biological quantities, is a major component of biodiversity. As spatial and temporal biodiversity information availability increases, the scope of dissimilarity studies has been expanded to cover various levels and types of spatiotemporal biodiversity facets (e.g. gene, community and ecosystem function), and diverse pairwise dissimilarity indices have been developed. However, further development of the dissimilarity concept is required in comparative studies on spatiotemporal structures of biodiversity compositional patterns, such as those exploring commonalities of biogeographical boundaries among taxa, compared to the conventional ones to consider higher dimensions of dissimilarity: dissimilarity of dissimilarity structures. This study proposes a novel and general concept, higher‐order dissimilarity (HOD), for quantitatively evaluating the dissimilarities of spatial or temporal dissimilarity structures among different datasets, proposes specific implementations of HOD as operational indices, and illustrates the potential resolution of scientific and practical questions through HOD. We further demonstrate the advantages of the HOD concept by applying it to actual patterns, such as long‐term and/or large‐spatial hypothetical monitoring datasets. Our conceptual framework on HOD extends the existing framework of biodiversity science and is versatile, with many potential applications in acquiring more valuable information from ever‐increasing biodiversity data.

Phenotypic plasticity rather than ecotypic differentiation explains the broad realized niche of a Neotropical orchid species.

Local adaptation is common in plant species, and knowing whether a population is locally adapted has fundamental and applied relevance. However, local adaptation in tropical plants remains largely less studied, and covering this gap is not simple since reciprocal transplantation - the gold standard for detecting local adaptation - is not feasible for most species. Here, we combined genetic, climatic and phenotypic data to investigate ecotypic differentiation, an important aspect of local adaptation, in coastal and inland populations of the orchid Epidendrum fulgens Brongn., a long-lived tropical plant for which reciprocal transplantation would not be feasible. We used nine microsatellite markers to estimate genetic divergence between inland and coastal populations. Moreover, occurrence data and climate data were used to test for differences in the realized niche of those populations. Finally, we assessed saturated water content, leaf specific area, height, and stomatal density in common garden and in situ to investigate the effects of ecotypic differentiation and plasticity on the phenotype. Coastal and inland groups' niches do not overlap, the former occupying a wetter and warmer area. However, this differentiation does not seem to be driven by ecotypic differentiation since there was no positive correlation between genetic structure and climate dissimilarity. Moreover, specific leaf area and leaf saturated water content, which are important phenotypic traits related to soil fertility and drought stress, were rather plastic. We conclude that ecotypic differentiation is absent, since phenotypic plasticity is an important mechanism explaining the niche broadness of this species.

Characterising the Tasmanian devil (Sarcophilus harrisii) pouch microbiome in lactating and non-lactating females

Wildlife harbour a diverse range of microorganisms that affect their health and development. Marsupials are born immunologically naïve and physiologically underdeveloped, with primary development occurring inside a pouch. Secretion of immunological compounds and antimicrobial peptides in the epithelial lining of the female’s pouch, pouch young skin, and through the milk, are thought to boost the neonate’s immune system and potentially alter the pouch skin microbiome. Here, using 16S rRNA amplicon sequencing, we characterised the Tasmanian devil pouch skin microbiome from 25 lactating and 30 non-lactating wild females to describe and compare across these reproductive stages. We found that the lactating pouch skin microbiome had significantly lower amplicon sequence variant richness and diversity than non-lactating pouches, however there was no overall dissimilarity in community structure between lactating and non-lactating pouches. The top five phyla were found to be consistent between both reproductive stages, with over 85% of the microbiome being comprised of Firmicutes, Proteobacteria, Fusobacteriota, Actinobacteriota, and Bacteroidota. The most abundant taxa remained consistent across all taxonomic ranks between lactating and non-lactating pouch types. This suggests that any potential immunological compounds or antimicrobial peptide secretions did not significantly influence the main community members. Of the more than 16,000 total identified amplicon sequence variants, 25 were recognised as differentially abundant between lactating and non-lactating pouches. It is proposed that the secretion of antimicrobial peptides in the pouch act to modulate these microbial communities. This study identifies candidate bacterial clades on which to test the activity of Tasmanian devil antimicrobial peptides and their role in pouch young protection, which in turn may lead to future therapeutic development for human diseases.

Dissimilarity of megabenthic community structure between deep-water seamounts with cobalt-rich crusts: Case study in the northwestern Pacific Ocean

As anthropogenic disturbance on deep-sea seamount ecosystems grows, there is an urgent need for a better understanding of the biodiversity and community structure in benthic ecosystems, which can vary at local and regional scales. A survey of the benthic megafauna on two adjacent deep-water seamounts in the northwestern Pacific Ocean was conducted, which are covered by cobalt-rich crusts, to assess the biodiversity patterns and dissimilarity of assemblage composition. Based on a multidisciplinary dataset generated from video recordings, multibeam bathymetry data, and near-bottom currents, environmental and spatial factors impacting the megabenthic communities were explored. Results showed that these two deep-water seamounts were dominated by hexactinellids, crinoids, and octocorals. The seamounts were able to support diverse and moderately abundant megafauna, with a total of 6436 individuals classified into 94 morphospecies. The survey covered a distance of 52.2 km across a depth range of 1421–3335 m, revealing multiple distinct megabenthic assemblages. The megabenthic communities of the two deep-water seamounts, with comparable environmental conditions, exhibited similarities in overall density, richness, and faunal lists, while dissimilarities in the relative abundance of taxa and assemblage composition. No gradual depth-related change in terms of abundance, richness, or species turnover was observed across the two seamounts, despite the statistical significance of depth in structuring the overall communities. The spatial distribution of megabenthic communities displayed a discontinuous and patchy pattern throughout the two deep-water seamounts. This patchiness was driven by the interactive effects of multiple environmental factors. Near-bottom currents and microhabitat features were the primary drivers influencing their dissimilarities in megabenthic community structure. This case study on the megabenthic community structure of two adjacent seamounts with cobalt-rich crusts can serve as an environmental baseline, providing a reference status for the conservation and management of seamount ecosystems, particularly valuable for areas being considered for deep-sea mining.

PhoD-harboring bacterial community assembly and co-occurrence in soil aggregates during roadside slope restoration

Soil organic phosphorus (OP) mineralization plays a vital role in the ecological restoration of roadside slopes. However, the changes in the functional bacterial (phoD-harboring) community involved in OP mineralization in soil aggregates during slope restoration are still unknown. In this study, a space-for-time substitution was conducted to compare the differences in the phoD-harboring bacterial community structure and assembly in soil aggregates of four particle sizes (<0.053, 0.25–2, 0.053–0.25, and >2 mm) at different slope restoration ages (7, 11, and 14 years). The results showed no significant differences in the phoD-harboring community diversity and structure among soil aggregates in the same restoration year. Community structure dissimilarity increased with restoration time. Species replacement dominated slope soils restored for 7, 11, and 14 years, accounting for 78.40 %, 79.68 %, and 68.96 % of the total β-diversity, respectively. Community assembly processes shifted from coexisting deterministic (68 %) and stochastic (32 %) processes in the 7-year restoration slope soil to dominantly deterministic (98 % and 91 %) processes in the 11- and 14-year restoration slope soils, respectively. Dominant phoD-harboring bacteria tended to shift from r-to K-strategies as slope restoration progressed, and the C:P ratio significantly correlated with both community structure and assembly. The increasing C:P ratio over restoration time stimulated phoD-harboring bacteria to secrete alkaline phosphatase to improve P availability, enhancing the complexity and stability of the network. This study elucidates the changing patterns of phoD-harboring bacteria in soil aggregates and provides a theoretical basis for the management of soil P during roadside restoration.

Chiral silver nanoparticles with surface-anchored L(D)-Cys exhibit dissimilar biological characteristics in vitro but not in vivo

This work investigated the influence of surface chirality on cellular internalization, cytotoxicity, and tissue distribution of silver nanoparticles (AgNPs). D-cysteine and L-cysteine are chiral forms of the amino acid cysteine. These enantiomers exhibit distinct spatial arrangements, with D-cysteine having a different configuration from L-cysteine. This structural dissimilarity can lead to variations in how these forms interact with biological systems, potentially impacting their cytotoxic responses. Four distinct types of AgNPs were synthesized, each possessing a unique surface coating: pristine AgNPs (pAgNPs), L-cysteine coated AgNPs (AgNPs@L-Cys), D-cysteine coated AgNPs (AgNPs@D-Cys), and racemic AgNPs coated with both L-Cys and D-Cys (AgNPs@L/D-Cys). We found chiral-dependent cytotoxicity of AgNPs on J774A.1 cells. Specifically, AgNPs@L-Cys exhibited the highest toxicity, and AgNPs@D-Cys exhibited the lowest toxicity. Meanwhile, the cellular uptake of the AgNPs correlated nicely with their cytotoxicity, with AgNPs@L-Cys being internalized to the greatest extent while AgNPs@D-Cys displays the least internalization. Scavenger receptors and clathrin predominantly mediate the cellular internalization of these AgNPs. Strikingly, the dissimilar cellular internalization and cytotoxicity of AgNPs with different chirality were eliminated upon protein corona coverage. Notably, following intravenous injection in mice, these four types of AgNPs showed similar patterns among various organs due to the inevitable protein adsorption in the bloodstream. These findings underscored the pivotal role of surface chirality in governing the biological interactions and toxicity of AgNPs.

The small tumor antigen of Merkel cell polyomavirus accomplishes cellular transformation by uniquely localizing to the nucleus despite the absence of a known nuclear localization signal

BackgroundMerkel Cell Carcinoma (MCC) is an aggressive skin cancer that is three times deadlier than melanoma. In 2008, it was found that 80% of MCC cases are caused by the genomic integration of a novel polyomavirus, Merkel Cell Polyomavirus (MCPyV), and the expression of its small and truncated large tumor antigens (ST and LT-t, respectively). MCPyV belongs to a family of human polyomaviruses; however, it is the only one with a clear association to cancer.MethodsTo investigate the role and mechanisms of various polyomavirus tumor antigens in cellular transformation, Rat-2 and 293A cells were transduced with pLENTI MCPyV LT-t, MCPyV ST, TSPyV ST, HPyV7 ST, or empty pLENTI and assessed through multiple transformation assays, and subcellular fractionations. One-way ANOVA tests were used to assess statistical significance.ResultsSoft agar, proliferation, doubling time, glucose uptake, and serum dependence assays confirmed ST to be the dominant transforming protein of MCPyV. Furthermore, it was found that MCPyV ST is uniquely transforming, as the ST antigens of other non-oncogenic human polyomaviruses such as Trichodysplasia Spinulosa-Associated Polyomavirus (TSPyV) and Human Polyomavirus 7 (HPyV7) were not transforming when similarly assessed. Identification of structural dissimilarities between transforming and non-transforming tumor antigens revealed that the uniquely transforming domain(s) of MCPyV ST are likely located within the structurally dissimilar loops of the MCPyV ST unique region. Of all known MCPyV ST cellular interactors, 62% are exclusively or transiently nuclear, suggesting that MCPyV ST localizes to the nucleus despite the absence of a canonical nuclear localization signal. Indeed, subcellular fractionations confirmed that MCPyV ST could achieve nuclear localization through a currently unknown, regulated mechanism independent of its small size, as HPyV7 and TSPyV ST proteins were incapable of nuclear translocation. Although nuclear localization was found to be important for several transforming properties of MCPyV ST, some properties were also performed by a cytoplasmic sequestered MCPyV ST, suggesting that MCPyV ST may perform different transforming functions in individual subcellular compartments.ConclusionsTogether, these data further elucidate the unique differences between MCPyV ST and other polyomavirus ST proteins necessary to understand MCPyV as the only known human oncogenic polyomavirus.

Dissimilarity in flea and host assemblages and their interaction networks along a spatial distance gradient: different patterns revealed by different network dissimilarity metrics.

We investigated the distance-decay pattern (an increase in dissimilarity with increasing geographic distance) in regional assemblages of fleas and their small mammalian hosts, as well as their interaction networks, in four biogeographic realms. Dissimilarity of assemblages (βtotal) was partitioned into species richness differences (βrich) and species replacement (βrepl) components. Dissimilarity of networks was assessed using two metrics: (a) whole network dissimilarity (βWN) partitioned into species replacement (βST) and interaction rewiring (βOS) components and (b) D statistics, measuring dissimilarity in the pure structure of the networks, without using information on species identities and calculated for hosts-shared-by-fleas networks (Dh) and fleas-shared-by-hosts networks (Df). We asked whether the distance-decay pattern (a) occurs among interactor assemblages or their interaction networks; (b) depends on the network dissimilarity metric used; and (c) differs between realms. The βtotal and βrepl of flea and host assemblages increased with distance in all realms except for host assemblages in the Afrotropics. βrich for flea and host assemblages increased with distance in the Nearctic only. In networks, βWN and βST demonstrated a distance-decay pattern, whereas βOS was mainly spatially invariant except in the Neotropics. Correlations of Dh or Df and geographic distance were mostly non-significant. We conclude that investigations of dissimilarity in interaction networks should include both types of dissimilarity metrics (those that consider partner identities and those that consider the pure structure of networks). This will allow elucidating the predictability of some facets of network dissimilarity and the unpredictability of other facets.

Coconut-sourced MCT oil: its potential health benefits beyond traditional coconut oil

AbstractPlant dietary lipids remain one of the most intriguing and complex classes of biological molecules. Among them, medium-chain triglycerides (MCTs) have garnered recognition for their unique physico-chemical properties and potential health benefits. Despite their classification as saturated fats, they stand apart from other saturated fatty acids due to their distinctive characteristics, positioning them as a valuable component in nutrition. While traditional dietary fats primarily contain long-chain triglycerides (LCTs), MCTs consist of medium-chain fatty acids (MCFAs), naturally found in coconut and palm oils. The structural dissimilarity grants MCTs advantageous attributes, encompassing rapid digestion and absorption, providing a swift source of energy. Importantly, MCT oil derived from coconuts surpasses traditional coconut oil in efficiency and speed of energy conversion due to its higher concentration of readily metabolizable MCTs, making it a superior choice in human nutrition. This comprehensive study delves deeply into the potential of coconut-derived MCT oil, illuminating its chemical constituents, production from coconut oil, distinctive physical and chemical properties, and metabolic characteristics. Additionally, it highlights a range of potential biological activities of the oil, including its efficacy in managing gastrointestinal disorders and promising roles in anticancer, neuroprotective, and antimicrobial effects. The report also discusses the extensive applications of MCT oil across diverse industrial and technological sectors, as well as its utilization in structured lipids, oleogels, and as a carrier for capsaicin. Addressing safety concerns and providing dosage guidelines, this paper emphasizes MCT oil as an alternative to coconut oil in various applications, offering a holistic perspective on its benefits.

Local and landscape factors shape alpha and beta trophic interaction diversity in urban gardens.

Promoting urban green spaces is an effective strategy to increase biodiversity in cities. However, our understanding of how local and landscape factors influence trophic interactions in these urban contexts remains limited. Here, we sampled cavity-nesting bees and wasps and their natural enemies within 85 urban gardens in Zurich (Switzerland) to identify factors associated with the diversity and dissimilarity of antagonistic interactions in these communities. The proportions of built-up area and urban green area at small landscape scales (50 m radius), as well as the management intensity, sun exposure, plant richness and proportion of agricultural land at the landscape scale (250 m radius), were key drivers of interaction diversity. This increased interaction diversity resulted not only from the higher richness of host and natural enemy species, but also from species participating in more interactions. Furthermore, dissimilarity in community structure and interactions across gardens (beta-diversity) were primarily influenced by differences in built-up areas and urban green areas at the landscape scale, as well as by management intensity. Our study offers crucial insights for urban planning and conservation strategies, supporting sustainability goals by helping to understand the factors that shape insect communities and their trophic interactions in urban gardens.

Development and assessment of a multiepitope synthetic antigen for the diagnosis of Dengue virus infection

Immunodiagnostic tests for detecting dengue virus infections encounter challenges related to cross-reactivity with other related flaviviruses. Our research focuses on the development of a synthetic multiepitope antigen tailored for dengue immunodiagnostics. Selected dengue epitopes involved structural linearity and dissimilarity from the proteomes of Zika and Yellow fever viruses which served for computationally modeling the three-dimensional protein structure, resulting in the design of two proteins: rDME-C and rDME-BR. Both proteins consist of seven epitopes, separated by the GPGPG linker, and a carboxy-terminal 6 × -histidine tag. The molecular weights of the final proteins rDME-C and rDME-BR are 16.83 kDa and 16.80 kDa, respectively, both with an isoelectric point of 6.35. The distinguishing factor between the two proteins lies in the origin of their epitope sequences, where rDME-C is based on the reference dengue proteome, while rDME-BR utilizes sequences from prevalent Dengue genotypes in Brazil from 2008 to 2019. PyMol analysis revealed exposure of epitopes in the secondary structure. Successful expression of the antigens was achieved in soluble form and fluorescence experiments indicated a disordered structure. In subsequent testing, rDME-BR and rDME-C antigens were assessed using an indirect Elisa protocol against Dengue infected serum, previously examined with a commercial diagnostic test. Optimal concentrations for antigens were determined at 10 µg/mL for rDME-BR and 30 µg/mL for rDME-C, with serum dilutions ranging from 1:50 to 1:100. Both antigens effectively detected IgM and IgG antibodies in Dengue fever patients, with rDME-BR exhibiting higher sensitivity. Our in-house test showed a sensitivity of 77.3 % and 82.6 % and a specificity of 89.4 % and 71.4 % for rDME-C and rDEM-BR antigens. No cross-reactivity was observed with serum from Zika-infected mice but with COVID-19 serum samples. Our findings underscore the utility of synthetic biology in crafting Dengue-specific multiepitope proteins and hold promise for precise clinical diagnosis and monitoring responses to emerging Dengue vaccines.