Search Results (605)

Despite years of extensive research, achieving the optimal properties for calcium phosphate-based biomaterials remains an ongoing challenge. Recently, ‘biomicroconcretes’ systems consisting of setting-phase-forming bone cement matrix and aggregates (granules/microspheres) have been developed and studied. However, further investigations are necessary to clarify the complex interplay between the synthesis, structure, and properties of these materials. This article focusses on the development and potential applications of hybrid biomaterials based on alpha-tricalcium phosphate (αTCP), hydroxyapatite (HA) and methylcellulose (MC) modified with silver (0.1 wt.% or 1.0 wt.%). The study presents the synthesis and characterization of silver-modified hybrid granules and seeks to determine the possibility and efficiency of incorporating these hybrid granules into αTCP-based biomicroconcretes. The αTCP and hydroxyapatite provide structural integrity and osteoconductivity, the presence of silver imparts antimicrobial properties, and MC allows for the self-assembling of granules. This combination creates an ideal environment for bone regeneration, while it potentially may prevent bacterial colonization and infection. The material’s chemical and phase composition, setting times, compressive strength, microstructure, chemical stability, and bioactive potential in simulated body fluid are systematically investigated. The results of the setting time measurements showed that both the size and the composition of granules (especially the hybrid nature) have an impact on the setting process of biomicroconcretes. The addition of silver resulted in prolonged setting times compared to the unmodified materials. Developed biomicroconcretes, despite exhibiting lower compressive strength compared to traditional calcium phosphate cements, fall within the range of human cancellous bone and demonstrate chemical stability and bioactive potential, indicating their suitability for bone substitution and regeneration. Further in vitro studies and in vivo assessments are needed to check the potential of these biomaterials in clinical applications. Full article

Organic fluorescent probes have attracted attention for bioimaging due to their advantages, including high sensitivity, biocompatibility, and multi-functionality. However, some limitations related to low signal-to-background ratio and false positive and negative signals make them difficult for in situ target detection. Recently, organelle targeting self-assembled fluorescent probes have been studied to meet this demand. Most of the dye molecules suffer from a quenching effect, but, specifically, some dyes like Pyrene, Near-Infrared (NIR), Nitrobenzoxadiazole (NBD), Fluorescein isothiocyanate (FITC), Naphthalenediimides (NDI), and Aggregation induced emission (AIE) show unique characteristics when they undergo self-assembly or aggregation. Therefore, in this review, we classified the molecules according to the dye type and provided an overview of the organelle-targeting strategy with an emphasis on the construction of fluorescent nanostructures within complex cellular environments. Results demonstrated that fluorescent probes effectively target and localized inside the organelles (mitochondria, lysosome, and golgi body) and undergo self-assembly to form various nanostructures that possess bio-functionality with long retention time, organelles membrane disruption/ROS generation/enzyme activity suppression ability, and enhanced photodynamic properties for anticancer treatment. Furthermore, we systematically discussed the challenges that remain to be resolved for the high performance of these probes and mentioned some of the future directions for the design of molecules. Full article

To date, five species of reddish-brown Neotriplax have been described, but their highly similar body color and other phenotypic traits make accurate taxonomy challenging. To clarify species-level taxonomy and validate potential new species, the cytochrome oxidase subunit I (COI) was used for phylogenetic analysis and the geometric morphometrics of elytron, pronotum, and hind wing were employed to distinguish all reddish-brown Neotriplax species. Phylogenetic results using maximum likelihood and Bayesian analyses of COI sequences aligned well with the current taxonomy of the Neotriplax species group. Significant K₂P divergences, with no overlap between intra- and interspecific genetic distances, were obtained in Neotriplax species. The automatic barcode gap discovery (ABGD), assemble species by automatic partitioning (ASAP), and generalized mixed Yule coalescent (GMYC) approaches concurred, dividing the similar species into eight molecular operational taxonomic units (MOTUs). Geometric morphometric analysis using pronotum, elytron, hind wing shape and wing vein patterns also validated the classification of all eight species. By integrating these analytical approaches with morphological evidence, we successfully delineated the reddish-brown species of Neotriplax into eight species with three new species: N. qinghaiensis sp. nov., N. maoershanensis sp. nov., and N. guangxiensis sp. nov. Furthermore, we documented the first record of N. lewisii in China. This study underscores the utility of an integrative taxonomy approach in species delimitation within Neotriplax and serves as a reference for the taxonomic revision of other morphologically challenging beetles through integrative taxonomy. Full article

Lipids are primarily transported in the bloodstream by lipoproteins, which are macromolecules of lipids and conjugated proteins also known as apolipoproteins. The processes of lipoprotein assembly, secretion, transportation, modification, and clearance are crucial components of maintaining a healthy lipid metabolism. Disruption in any of these steps results in pathophysiological abnormalities such as dyslipidemia, obesity, insulin resistance, inflammation, atherosclerosis, peripheral artery disease, and cardiovascular diseases. By studying these genetic mutations, researchers can gain valuable insights into the underlying mechanisms that govern the relationship between protein structure and its physiological role. These lipoproteins, including HDL, LDL, lipoprotein(a), and VLDL, mainly serve the purpose of transporting lipids between tissues and organs. However, studies have provided evidence that apo(a) also possesses protective properties against pathogens. In the future, the field of study will be significantly influenced by the integration of recombinant DNA technology and human site-specific mutagenesis for treating hereditary disorders. Several medications are available for the treatment of dyslipoproteinemia. These include statins, fibrates, ezetimibe, niacin, PCSK9 inhibitors, evinacumab, DPP 4 inhibitors, glucagon-like peptide-1 receptor agonists GLP1RAs, GLP-1, and GIP dual receptor agonists, in addition to SGLT2 inhibitors. This current review article exhibits, for the first time, a comprehensive reflection of the available body of publications concerning the impact of lipoproteins on metabolic well-being across various pathological states. Full article

Putting sensors on the bodies of animals to automate animal activity recognition and gain insight into their behaviors can help improve their living conditions. Although previous hard-coded algorithms failed to classify complex time series obtained from accelerometer data, recent advances in deep learning have improved the task of animal activity recognition for the better. However, a comparative analysis of the generalizing capabilities of various models in combination with different input types has yet to be addressed. This study experimented with two techniques for transforming the segmented accelerometer data to make them more orientation-independent. The methods included calculating the magnitude of the three-axis accelerometer vector and calculating the Discrete Fourier Transform for both sets of three-axis data as the vector magnitude. Three different deep learning models were trained on this data: a Multilayer Perceptron, a Convolutional Neural Network, and an ensemble merging both called a hybrid Convolutional Neural Network. Besides mixed cross-validation, every model and input type combination was assessed on a goat-wise leave-one-out cross-validation set to evaluate its generalizing capability. Using orientation-independent data transformations gave promising results. A hybrid Convolutional Neural Network with $L^2$-norm as the input combined the higher classification accuracy of a Convolutional Neural Network with the lower standard deviation of a Multilayer Perceptron. Most of the misclassifications occurred for behaviors that display similar accelerometer traces and minority classes, which could be improved in future work by assembling larger and more balanced datasets. Full article

This paper explores the modeling and simulation of an innovative double-damper suspension system, evaluating its effectiveness through different test scenarios. The double damper integrates two individual dampers into a unified assembly. The modeling process involves representing the damper as two distinct dampers and a body block, accounting for the additional degree of freedom introduced by combining the two dampers. Simulink/MATLAB is employed for modeling the pressure, discharge, and force equations of the damper. A simplified quarter-car model is designed to conduct simulations for different road profiles, evaluating the efficacy of this double-damper model. The reduced-order modeling approach, suitable for complex systems like dampers, is utilized. Dedicated mathematical models are utilized to examine both single- and double-damper configurations, with the resulting non-linear equations solved using Newton’s iterative method. The equations derived for the single damper provide the basis for modeling the double-damper system. In this model, two separate dampers, each possessing similar properties, are simulated and considered to be rigidly linked at their connection point. Consequently, it is assumed that a portion of the force and velocity experienced by the lower damper is transmitted to the upper damper, and vice versa. Simulation results demonstrate that the innovative double-damper design outperforms a single passive damper in attenuating the oscillations of both the sprung and unsprung masses. Moreover, this innovative concept offers increased adaptability to balance between ride comfort and road holding, a feature previously limited to passive suspension systems. Full article

This paper presents a generalized and efficient method for quasi-static analysis of mooring systems, including complex scenarios such as when shared mooring lines interconnect multiple floating wind or wave energy devices. While quasi-static mooring models are well established, most published formulations are focused on specific applications, and no publicly available implementations provide efficient handling of large mooring system networks. The present formulation addresses these gaps by: (1) formulating solutions for edge cases not typically supported by quasi-static models; (2) creating a fully generalized model structure such that any combination of mooring lines, point masses, and floating bodies can be assembled; and (3) deriving analytic expressions for the system Jacobians (stiffness matrices) so that systems with many degrees of freedom can be solved efficiently. These techniques form the theory basis of MoorPy, an open-source mooring analysis library. The model is demonstrated on nine scenarios of increasing complexity with features of interest for offshore renewable energy applications. When compared with steady-state results from a lumped-mass dynamic model, the results show that the quasi-static formulation accurately calculates profiles and tensions and that its analytic approach provides more efficient and reliable computation of system stiffness matrices than finite-differencing methods. These results verify the accuracy of the MoorPy model. Full article

Bursaphelenchus xylophilus is a dangerous quarantine pest that causes extensive damage to pine ecosystems worldwide. Cyclobutrifluram, a succinate dehydrogenase inhibitor (SDHI), is a novel nematicide introduced by Syngenta in 2013. However, the nematocidal effect of cyclobutrifluram against plant-parasitic nematodes remains underexplored. Therefore, here, we aim to address this knowledge gap by evaluating the toxicity, effects, and mode of action of cyclobutrifluram on B. xylophilus. The result shows that cyclobutrifluram is the most effective agent, with an LC₅₀ value of 0.1078 mg·L⁻¹. At an LC₂₀ dose, it significantly reduced the population size to 10.40 × 10³ ± 737.56—approximately 1/23 that of the control group. This notable impact may stem from the agent’s ability to diminish egg-laying and hatching rates, as well as to impede the nematodes’ development. In addition, it has also performed well in the prevention of pine wilt disease, significantly reducing the incidence in greenhouses and in the field. SDH consists of a transmembrane assembly composed of four protein subunits (SDHA to SDHD). Four sdh genes were characterized and proved by RNAi to regulate the spawning capacity, locomotion ability, and body size of B. xylophilus. The mortality of nematodes treated with sdhc-dsRNA significantly decreased upon cyclobutrifluram application. Molecular docking further confirmed that SDHC, a cytochrome-binding protein, is the target. In conclusion, cyclobutrifluram has a good potential for trunk injection against B. xylophilus. This study provides valuable information for the screening and application of effective agents in controlling and preventing PWD in forests. Full article

Biomolecular condensates (BMCs) exhibit physiological and pathological relevance in biological systems. Both liquid and solid condensates play significant roles in the spatiotemporal regulation and organization of macromolecules and their biological activities. Some pathological solid condensates, such as Lewy Bodies and other fibrillar aggregates, have been hypothesized to originate from liquid condensates. With the prevalence of BMCs having functional and dysfunctional roles, it is imperative to understand the mechanism of biomolecular condensate formation and initiation. Using the low-complexity domain (LCD) of heterogenous ribonuclear protein A1 (hnRNPA1) as our model, we monitored initial assembly events using dynamic light scattering (DLS) while modulating pH and salt conditions to perturb macromolecule and condensate properties. We observed the formation of nanometer-sized BMCs (nano-condensates) distinct from protein monomers and micron-sized condensates. We also observed that conditions that solubilize micron-sized protein condensates do not solubilize nano-condensates, indicating that the balance of forces that stabilize nano-condensates and micron-sized condensates are distinct. These findings provide insight into the forces that drive protein phase separation and potential nucleation structures of macromolecular condensation. Full article

For mobile robots, the high-precision integrated calibration and structural robustness of multi-sensor systems are important prerequisites for ensuring healthy operations in the later stage. Currently, there is no well-established validation method for the calibration accuracy and structural robustness of multi-sensor systems, especially for dynamic traveling situations. This paper presents a novel validation method for the calibration accuracy and structural robustness of a multi-sensor mobile robot. The method employs a ground–object–air cooperation mechanism, termed the “ground surface simulation field (GSSF)—mobile robot -photoelectric transmitter station (PTS)”. Firstly, a static high-precision GSSF is established with the true north datum as a unified reference. Secondly, a rotatable synchronous tracking system (PTS) is assembled to conduct real-time pose measurements for a mobile vehicle. The relationship between each sensor and the vehicle body is utilized to measure the dynamic pose of each sensor. Finally, the calibration accuracy and structural robustness of the sensors are dynamically evaluated. In this context, epipolar line alignment is employed to assess the accuracy of the evaluation of relative orientation calibration of binocular cameras. Point cloud projection and superposition are utilized to realize the evaluation of absolute calibration accuracy and structural robustness of individual sensors, including the navigation camera (Navcam), hazard avoidance camera (Hazcam), multispectral camera, time-of-flight depth camera (TOF), and light detection and ranging (LiDAR), with respect to the vehicle body. The experimental results demonstrate that the proposed method offers a reliable means of dynamic validation for the testing phase of a mobile robot. Full article

Background: Respiratory viruses significantly impact global morbidity and mortality, causing more disease in humans than any other infectious agent. Beyond pathogens, various viruses and bacteria colonize the respiratory tract without causing disease, potentially influencing respiratory diseases’ pathogenesis. Nevertheless, our understanding of respiratory microbiota is limited by technical constraints, predominantly focusing on bacteria and neglecting crucial populations like viruses. Despite recent efforts to improve our understanding of viral diversity in the human body, our knowledge of viral diversity associated with the human respiratory tract remains limited. Methods: Following a comprehensive search in bibliographic and sequencing data repositories using keyword terms, we retrieved shotgun metagenomic data from public repositories (n = 85). After manual curation, sequencing data files from 43 studies were analyzed using EVEREST (pipEline for Viral assEmbly and chaRactEriSaTion). Complete and high-quality contigs were further assessed for genomic and taxonomic characterization. Results: Viral contigs were obtained from 194 out of the 868 FASTQ files processed through EVEREST. Of the 1842 contigs that were quality assessed, 8% (n = 146) were classified as complete/high-quality genomes. Most of the identified viral contigs were taxonomically classified as bacteriophages, with taxonomic resolution ranging from the superkingdom level down to the species level. Captured contigs were spread across 25 putative families and varied between RNA and DNA viruses, including previously uncharacterized viral genomes. Of note, airway samples also contained virus(es) characteristic of the human gastrointestinal tract, which have not been previously described as part of the lung virome. Additionally, by performing a meta-analysis of the integrated datasets, ecological trends within viral populations linked to human disease states and their biogeographical distribution along the respiratory tract were observed. Conclusion: By leveraging publicly available repositories of shotgun metagenomic data, the present study provides new insights into viral genomes associated with specimens from the human respiratory tract across different disease spectra. Further studies are required to validate our findings and evaluate the potential impact of these viral communities on respiratory tract physiology. Full article

To detect and differentiate two essential amino acids (L-Valine and L-Phenylalanine) in the human body, a novel asymmetrically folded dual-aperture metal ring terahertz metasurface sensor was designed. A solvent mixture of water and glycerol with a volume ratio of 2:8 was proposed to reduce the absorption of terahertz waves by reducing the water content. A sample chamber with a controlled liquid thickness of 15 μm was fabricated. And a terahertz time-domain spectroscopy (THz-TDS) system, which is capable of horizontally positioning the samples, was assembled. The results of the sensing test revealed that as the concentration of valine solution varied from 0 to 20 mmol/L, the sensing resonance peak shifted from 1.39 THz to 1.58 THz with a concentration sensitivity of 9.98 GHz/mmol∗L⁻¹. The resonance peak shift phenomenon in phenylalanine solution was less apparent. It is assumed that the coupling enhancement between the absorption peak position of solutes in the solution and the sensing peak position amplified the terahertz localized electric field resonance, which resulted in the increase in frequency shift. Therefore, it could be shown that the sensor has capabilities in performing the marker sensing detection of L-Valine. Full article

Autologous-engineered artificial tissues constitute an ideal alternative for radical surgery in terms of natural anticoagulation, self-repair, tissue regeneration, and the possibility of growth. Previously, we focused on the development and practical application of artificial tissues using “in-body tissue architecture (iBTA)”, a technique that uses living bodies as bioreactors. This study aimed to further develop iBTA by fabricating tissues with diverse shapes and evaluating their physical properties. Although the breaking strength increased with tissue thickness, the nominal breaking stress increased with thinner tissues. By carving narrow grooves on the outer periphery of an inner core with narrow grooves, we fabricated approximately 2.2 m long cord-shaped tissues and net-shaped tissues with various designs. By assembling the two inner cores inside the branched stainless-steel pipes, a large graft with branching was successfully fabricated, and its aortic arch replacement was conducted in a donor goat without causing damage. In conclusion, by applying iBTA technology, we have made it possible, for the first time, to create tissues of various shapes and designs that are difficult using existing tissue-engineering techniques. Thicker iBTA-induced tissues exhibited higher rupture strength; however, rupture stress was inversely proportional to thickness. These findings broaden the range of iBTA-induced tissue applications. Full article

Securing high-quality cell sources is important in regenerative medicine. In this study, we developed a device that can accumulate autologous stem cells in the body. When small wire-assembled molds were embedded in the dorsal subcutaneous pouches of beagles for several weeks, collagen-based tissues with minimal inflammation formed inside the molds. At 3 weeks of embedding, the outer areas of the tissues were composed of immature type III collagen with large amounts of cells expressing SSEA3 or SSEA4 markers, in addition to growth factors such as HGF or VEGF. When separated from the tissues by collagenase treatment, approximately four million cells with a proportion of 70% CD90-positive and 20% SSEA3- or SSEA4-positive cells were recovered from the single mold. The cells could differentiate into bone or cartilage cells. The obtained cell-containing tissues are expected to have potential as therapeutic materials or cell sources in regenerative medicine. Full article

Fluctuations are omnipresent; they exist in any matter, due either to its quantum nature or to its nonzero temperature. In the current review, we briefly cover the quantum electrodynamic Casimir (QED) force as well as the critical Casimir (CC) and Helmholtz (HF) forces. In the QED case, the medium is usually a vacuum and the massless excitations are photons, while in the CC and HF cases the medium is usually a critical or correlated fluid and the fluctuations of the order parameter are the cause of the force between the macroscopic or mesoscopic bodies immersed in it. We discuss the importance of the presented results for nanotechnology, especially for devising and assembling micro- or nano-scale systems. Several important problems for nanotechnology following from the currently available experimental findings are spelled out, and possible strategies for overcoming them are sketched. Regarding the example of HF, we explicitly demonstrate that when a given integral quantity characterizing the fluid is conserved, it has an essential influence on the behavior of the corresponding fluctuation-induced force. Full article