Imaging innate immunity.

Innate immunity is the first line of defense against infectious intruders and also plays a major role in the development of sterile inflammation. Direct microscopic imaging of the involved immune cells, especially neutrophil granulocytes, monocytes, and macrophages, has been performed since more than 150 years, and we still obtain novel insights on a frequent basis. Initially, intravital microscopy was limited to small-sized animal species, which were often invertebrates. In this review, we will discuss recent results on the biology of neutrophils and macrophages that have been obtained using confocal and two-photon microscopy of individual cells or subcellular structures as well as light-sheet microscopy of entire organs. This includes the role of these cells in infection defense and sterile inflammation in mammalian disease models relevant for human patients. We discuss their protective but also disease-enhancing activities during tumor growth and ischemia-reperfusion damage of the heart and brain. Finally, we provide two visions, one experimental and one applied, how our knowledge on the function of innate immune cells might be further enhanced and also be used in novel ways for disease diagnostics in the future.

Imaging the different timescales of germinal center selection.

Germinal centers (GCs) are the site of antibody affinity maturation, a fundamental immunological process that increases the potency of antibodies and thereby their ability to protect against infection. GC biology is highly dynamic in both time and space, making it ideally suited for intravital imaging. Using multiphoton laser scanning microscopy (MPLSM), the field has gained insight into the molecular, cellular, and structural changes and movements that coordinate affinity maturation in real time in their native environment. On the other hand, several limitations of MPLSM have had to be overcome to allow full appreciation of GC events taking place across different timescales. Here, we review the technical advances afforded by intravital imaging and their contributions to our understanding of GC biology.

Adsorption and Distribution of Triplex-hybridizing Bioconjugated Gold Nanoclusters inside Spermatozoa- A Study using Confocal Microscopy and Fluorescence Lifetime Imaging.

The study of the interactions between biofunctionalized gold nanoclusters (Au NCs) and spermatozoa is highly relevant to evaluate the potential of Au NCs as imaging probes and transfection agents in the reproductive biology. In this work, confocal laser scanning microscopy (CLSM) was used to investigate the distribution of Au NCs bioconjugated with peptide (nuclear localisation sequence, NLS) and oligonucleotide (locked nucleic acid, LNA) ligands in bovine spermatozoa. Fluorescence lifetime imaging (FLIM) was employed to detect changes in the NC´s chemical environment. We observed a pronounced regio-selective accumulation of the bioconjugates in spermatozoa with high concentration at the equatorial segment. Furthermore, 3D-CLSM showed successful non-endosomal cellular uptake of the conjugates by intact sperm cells and the distribution of the bioconjugates was found to be influenced by the ligand types. Interestingly, the FLIM data showed differences in lifetime depending on membrane integrity. Furthermore, ligand-dependent changes in lifetime between NC bioconjugates carrying peptide and oligonucleotide ligands were found, probably attributed to specific interactions with sperm cell compartments.

New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests.

Tree allometric models, essential for monitoring and predicting terrestrial carbon stocks, are traditionally built on global databases with forest inventory measurements of stem diameter (D) and tree height (H). However, these databases often combine H measurements obtained through various measurement methods, each with distinct error patterns, affecting the resulting H:D allometries. In recent decades, terrestrial laser scanning (TLS) has emerged as a widely accepted method for accurate, non-destructive tree structural measurements. This study used TLS data to evaluate the prediction accuracy of forest inventory-based H:D allometries and to develop more accurate pantropical allometries. We considered 19 tropical rainforest plots across four continents. Eleven plots had forest inventory and RIEGL VZ-400(i) TLS-based D and H data, allowing accuracy assessment of local forest inventory-based H:D allometries. Additionally, TLS-based data from 1951 trees from all 19 plots were used to create new pantropical H:D allometries for tropical rainforests. Our findings reveal that in most plots, forest inventory-based H:D allometries underestimated H compared with TLS-based allometries. For 30-metre-tall trees, these underestimations varied from -1.6 m (-5.3%) to -7.5 m (-25.4%). In the Malaysian plot with trees reaching up to 77 m in height, the underestimation was as much as -31.7 m (-41.3%). We propose a TLS-based pantropical H:D allometry, incorporating maximum climatological water deficit for site effects, with a mean uncertainty of 19.1% and a mean bias of -4.8%. While the mean uncertainty is roughly 2.3% greater than that of the Chave2014 model, this model demonstrates more consistent uncertainties across tree size and delivers less biased estimates of H (with a reduction of 8.23%). In summary, recognizing the errors in H measurements from forest inventory methods is vital, as they can propagate into the allometries they inform. This study underscores the potential of TLS for accurate H and D measurements in tropical rainforests, essential for refining tree allometries.

Novel cytoskeletal traits in the intestinal parasites (Squirmida, Platyproteum vivax) of Pacific peanut worms (Sipuncula, Phascolosoma agassizii).

The cytoskeletal organization of a squirmid, namely Platyproteum vivax, was investigated with confocal laser scanning microscopy (CLSM) to refine inferences about convergent evolution among intestinal parasites of marine invertebrates. Platyproteum inhabits Pacific peanut worms (Phascolosoma agassizii) and has traits that are similar to other lineages of myzozoan parasites, namely gregarine apicomplexans within Selenidium, such as conspicuous feeding stages, called "trophozoites," capable of dynamic undulations. SEM and CLSM of P. vivax revealed an inconspicuous flagellar apparatus and a uniform array of longitudinal microtubules organized in bundles (LMBs). Extreme flattening of the trophozoites and a consistently oblique morphology of the anterior end provided a reliable way to distinguish dorsal and ventral surfaces. CLSM revealed a novel system of microtubules oriented in the flattened dorsoventral plane. Most of these dorsoventral microtubule bundles (DVMBs) had a punctate distribution and were evenly spaced along a curved line spanning the longitudinal axis of the trophozoites. This configuration of microtubules is inferred to function in maintaining the flattened shape of the trophozoites and facilitate dynamic undulations. The novel traits in Platyproteum are consistent with phylogenomic data showing that this lineage is only distantly related to Selenidium and other marine gregarine apicomplexans with dynamic intestinal trophozoites.

Mapping and spectroscopy of telecom quantum emitters with confocal laser scanning microscopy.

Efficiently coupling single-photon emitters in the telecommunication C-band that are not deterministically positioned to photonic structures requires both spatial and spectral mapping. This study introduces the photoluminescence mapping of telecom C-band self-assembled quantum dots (QDs) by confocal laser scanning microscopy, a technique previously unexplored in this wavelength range which fulfills these two requirements. We consider the effects of distortions inherent to any imaging system but largely disregarded in prior works to derive accurate coordinates from photoluminescence maps. We obtain a position uncertainty below 11 nm for 10% of the QDs when assuming no distortions, highlighting the potential of the scanning approach. After distortion correction, we found that the previously determined positions are on average shifted by 428 nm from the corrected positions, demonstrating the necessity of this correction for accurate positioning. Then, through error propagation, the position uncertainty for 10% of the QDs increases to 110 nm.

Antimicrobial efficacy of chitosan versus sodium hypochlorite: A systematic review and meta-analysis.

AIM: This meta-analysis aimed to compare the antibacterial efficacy of chitosan/chitosan nanoparticles (Ch/Ch-NPs) versus sodium hypochlorite/chlorhexidine (NaOCl/CHX). MATERIALS AND METHODS: A search was performed in four electronic databases until December 08, 2023. Studies with missing, unclear, and insufficient data sets were excluded. The included studies were assessed by two independent reviewers using the Joanna Briggs Institute Critical Appraisal Checklist for Quasi-Experimental Studies. The meta-analysis of standardized mean difference was performed using a random effects model. Additionally, funnel plots as well as Egger's regression intercept test were used to evaluate potential publication bias. RESULTS: A total of 426 samples were used in nine included studies. There was no difference in antibacterial efficacy between Ch/Ch-NPs-NaOCl (SMD: 0.005; 95% CI: -0.844-0.854; p = 0.990). However, the antibacterial efficacy of NaOCl was statistically more effective than Ch/Ch-NPs (SMD: 0.807; 95% CI: 0.015-1.599; p = 0.046) using the bacterial culture method, and Ch/Ch-NPs was statistically higher than NaOCl (SMD: -1.827; 95% CI: -2.720, -0.934; p < 0.000) using confocal laser scanning microscopy. CONCLUSIONS: Ch/Ch-NPs may be an alternative to NaOCl against Enterococcus faecalis. The methods used in the in vitro studies evaluating the antibacterial efficacy of irrigation solutions against E. faecalis may have had an impact on the results.

The Effect of Enzymatic Treatment with Mutanase, Beta-Glucanase, and DNase on a Saliva-Derived Biofilm Model.

INTRODUCTION: The dental biofilm matrix is an important determinant of virulence for caries development and comprises a variety of extracellular polymeric substances that contribute to biofilm stability. Enzymes that break down matrix components may be a promising approach to caries control, and in light of the compositional complexity of the dental biofilm matrix, treatment with multiple enzymes may enhance the reduction of biofilm formation compared to single enzyme therapy. The present study investigated the effect of the three matrix-degrading enzymes mutanase, beta-glucanase, and DNase, applied separately or in combinations, on biofilm prevention and removal in a saliva-derived in vitro-grown model. METHODS: Biofilms were treated during growth to assess biofilm prevention or after 24 h of growth to assess biofilm removal by the enzymes. Biofilms were quantified by crystal violet staining and impedance-based real-time cell analysis, and the biofilm structure was visualized by confocal microscopy and staining of extracellular DNA (eDNA) and polysaccharides. RESULTS: The in vitro model was dominated by Streptococcus spp., as determined by 16S rRNA gene amplicon sequencing. All tested enzymes and combinations had a significant effect on biofilm prevention, with reductions of >90% for mutanase and all combinations including mutanase. Combined application of DNase and beta-glucanase resulted in an additive effect (81.0% ± 1.3% SD vs. 36.9% ± 21.9% SD and 48.2% ± 14.9% SD). For biofilm removal, significant reductions of up to 73.2% ± 5.5% SD were achieved for combinations including mutanase, whereas treatment with DNase had no effect. Glucans, but not eDNA decreased in abundance upon treatment with all three enzymes. CONCLUSION: Multi-enzyme treatment is a promising approach to dental biofilm control that needs to be validated in more diverse biofilms.

Biofilm formation of the food spoiler Brochothrix thermosphacta on different industrial surface materials using a biofilm reactor.

Brochothrix thermosphacta is considered as a major food spoiler bacteria. This study evaluates biofilm formation by B. thermosphacta CD337(2) - a strong biofilm producer strain - on three food industry materials (polycarbonate (PC), polystyrene (PS), and stainless steel (SS)). Biofilms were continuously grown under flow at 25 °C in BHI broth in a modified CDC biofilm reactor. Bacterial cells were enumerated by plate counting, and biofilm spatial organization was deciphered by combining confocal laser scanning microscopy and image analysis. The biofilms had the same growth kinetics on all three materials and reach 8log CFU/cm2 as maximal concentration. Highly structured biofilms were observed on PC and PS, but less structured ones on SS. This difference was confirmed by structural quantification analysis using the image analysis software tool BiofilmQ. Biofilm on SS show less roughness, density, thickness and volume. The biofilm 3D structure seemed to be related to the coupon topography and roughness. The materials used in this study do not affect biofilm growth. However, their roughness and topography affect the biofilm architecture, which could influence biofilm behaviour.

Application of the Knife-Edge Technique on Transition Metal Dichalcogenide Monolayers for Resolution Assessment of Nonlinear Microscopy Modalities.

We report application of the knife-edge technique at the sharp edges of WS2 and MoS2 monolayer flakes for lateral and axial resolution assessment in all three modalities of nonlinear laser scanning microscopy: two-photon excited fluorescence (TPEF), second- and third-harmonic generation (SHG, THG) imaging. This technique provides a high signal-to-noise ratio, no photobleaching effect and shows good agreement with standard resolution measurement techniques. Furthermore, we assessed both the lateral resolution in TPEF imaging modality and the axial resolution in SHG and THG imaging modality directly via the full-width at half maximum parameter of the corresponding Gaussian distribution. We comprehensively analyzed the factors influencing the resolution, such as the numerical aperture, the excitation wavelength and the refractive index of the embedding medium for the different imaging modalities. Glycerin was identified as the optimal embedding medium for achieving resolutions closest to the theoretical limit. The proposed use of WS2 and MoS2 monolayer flakes emerged as promising tools for characterization of nonlinear imaging systems.

Assessment of multispecies biofilm growth on root canal dentin under different radiation therapy regimens.

OBJECTIVES: To assess the growth of a multispecies biofilm on root canal dentin under different radiotherapy regimens. MATERIALS AND METHODS: Sixty-three human root dentin cylinders were distributed into six groups. In three groups, no biofilm was formed (n = 3): NoRT) non-irradiated dentin; RT55) 55 Gy; and RT70) 70 Gy. In the other three groups (n = 18), a 21-day multispecies biofilm (Enterococcus faecalis, Streptococcus mutans, and Candida albicans) was formed in the canal: NoRT + Bio) non-irradiated + biofilm; RT55 + Bio) 55 Gy + biofilm; and RT70 + Bio) 70 Gy + biofilm. The biofilm was quantified (CFUs/mL). Biofilm microstructure was assessed under SEM. Microbial penetration into dentinal tubules was assessed under CLSM. For the biofilm biomass and dentin microhardness pre- and after biofilm growth assessments, 45 bovine dentin specimens were distributed into three groups (n = 15): NoRT) non-irradiated + biofilm; RT55 + Bio) 55 Gy + biofilm; and RT70 + Bio) 70 Gy + biofilm. RESULTS: Irradiated specimens (70 Gy) had higher quantity of microorganisms than non-irradiated (p = .010). There was gradual increase in biofilm biomass from non-irradiated to 55 Gy and 70 Gy (p < .001). Irradiated specimens had greater reduction in microhardness after biofilm growth. Irradiated dentin led to the growth of a more complex and irregular biofilm. There was microbial penetration into the dentinal tubules, regardless of the radiation regimen. CONCLUSION: Radiotherapy increased the number of microorganisms and biofilm biomass and reduced dentin microhardness. Microbial penetration into dentinal tubules was noticeable. CLINICAL RELEVANCE: Cumulative and potentially irreversible side effects of radiotherapy affect biofilm growth on root dentin. These changes could compromise the success of endodontic treatment in oncological patients undergoing head and neck radiotherapy.

Multispectral Light Detection and Ranging Technology and Applications: A Review.

Light Detection and Ranging (LiDAR) is a well-established active technology for the direct acquisition of 3D data. In recent years, the geometric information collected by LiDAR sensors has been widely combined with optical images to provide supplementary spectral information to achieve more precise results in diverse remote sensing applications. The emergence of active Multispectral LiDAR (MSL) systems, which operate on different wavelengths, has recently been revolutionizing the simultaneous acquisition of height and intensity information. So far, MSL technology has been successfully applied for fine-scale mapping in various domains. However, a comprehensive review of this modern technology is currently lacking. Hence, this study presents an exhaustive overview of the current state-of-the-art in MSL systems by reviewing the latest technologies for MSL data acquisition. Moreover, the paper reports an in-depth analysis of the diverse applications of MSL, spanning across fields of "ecology and forestry", "objects and Land Use Land Cover (LULC) classification", "change detection", "bathymetry", "topographic mapping", "archaeology and geology", and "navigation". Our systematic review uncovers the potentials, opportunities, and challenges of the recently emerged MSL systems, which integrate spatial-spectral data and unlock the capability for precise multi-dimensional (nD) mapping using only a single-data source.

Vehicle-Bridge Interaction Modelling Using Precise 3D Road Surface Analysis.

Uneven road surfaces are the primary source of excitation in the dynamic interaction between a bridge and a vehicle and can lead to errors in bridge weigh-in-motion (B-WIM) systems. In order to correctly reproduce this interaction in a numerical model of a bridge, it is essential to know the magnitude and location of the various roadway irregularities. This paper presents a methodology for measuring the 3D road surface using static terrestrial laser scanning and a numerical model for simulating vehicle passage over a bridge with a measured road surface. This model allows the evaluation of strain responses in the time domain at any bridge location considering different parameters such as vehicle type, lateral position and speed, road surface unevenness, bridge type, etc. Since the time domain strains are crucial for B-WIM algorithms, the proposed approach facilitates the analysis of the different factors affecting the B-WIM results. The first validation of the proposed methodology was carried out on a real bridge, where extensive measurements were performed using different sensors, including measurements of the road surface, the response of the bridge when crossed by a test vehicle and the dynamic properties of the bridge and vehicle. The comparison between the simulated and measured bridge response marks a promising step towards investigating the influence of unevenness on the results of B-WIM.

Laboratory Investigations of the Leica RTC360 Laser Scanner-Distance Measuring Performance.

A Leica RTC360 laser scanner was investigated using a linear horizontal comparator system with four targets of different reflectance. Several thousand panorama scans were conducted along the 30 m long comparator, basically in 40 mm steps. For a selected target, more detailed investigations were carried out with a 2 mm step width for a 2 m wide section. The absolute offset between the scanner and the relative interferometer measurements was determined with a calibrated total station. The investigations revealed several systematic effects like an offset in the distance measurement of about 1.3 mm. Furthermore, sections with stochastic behavior as well as sections with pseudo-cyclic parts were observed, depending on the reflectance of the target. The deterministic sections showed curved and striped patterns with some discontinuities of about 2 mm at 20 m, resulting in a saw-tooth like pattern along the distances. Within all the experiments, the distance deviations were below the manufacturer specifications of the 3D point accuracy. However, it was demonstrated that the distance measurements had clear systematic components. In using these new findings, the specification of the measurement "noise" in the data sheet has to be seen as critical.

Automated Phenotypic Trait Extraction for Rice Plant Using Terrestrial Laser Scanning Data.

To quickly obtain rice plant phenotypic traits, this study put forward the computational process of six rice phenotype features (e.g., crown diameter, perimeter of stem, plant height, surface area, volume, and projected leaf area) using terrestrial laser scanning (TLS) data, and proposed the extraction method for the tiller number of rice plants. Specifically, for the first time, we designed and developed an automated phenotype extraction tool for rice plants with a three-layer architecture based on the PyQt5 framework and Open3D library. The results show that the linear coefficients of determination (R2) between the measured values and the extracted values marked a better reliability among the selected four verification features. The root mean square error (RMSE) of crown diameter, perimeter of stem, and plant height is stable at the centimeter level, and that of the tiller number is as low as 1.63. The relative root mean squared error (RRMSE) of crown diameter, plant height, and tiller number stays within 10%, and that of perimeter of stem is 18.29%. In addition, the user-friendly automatic extraction tool can efficiently extract the phenotypic features of rice plant, and provide a convenient tool for quickly gaining phenotypic trait features of rice plant point clouds. However, the comparison and verification of phenotype feature extraction results supported by more rice plant sample data, as well as the improvement of accuracy algorithms, remain as the focus of our future research. The study can offer a reference for crop phenotype extraction using 3D point clouds.

ARM4CH: A Methodology for Autonomous Reality Modelling for Cultural Heritage.

Nowadays, the use of advanced sensors, such as terrestrial, mobile 3D scanners and photogrammetric imaging, has become the prevalent practice for 3D Reality Modeling (RM) and the digitization of large-scale monuments of Cultural Heritage (CH). In practice, this process is heavily related to the expertise of the surveying team handling the laborious planning and time-consuming execution of the 3D scanning process tailored to each site's specific requirements and constraints. To minimize human intervention, this paper proposes a novel methodology for autonomous 3D Reality Modeling of CH monuments by employing autonomous robotic agents equipped with the appropriate sensors. These autonomous robotic agents are able to carry out the 3D RM process in a systematic, repeatable, and accurate approach. The outcomes of this automated process may also find applications in digital twin platforms, facilitating secure monitoring and the management of cultural heritage sites and spaces, in both indoor and outdoor environments. The main purpose of this paper is the initial release of an Industry 4.0-based methodology for reality modeling and the survey of cultural spaces in the scientific community, which will be evaluated in real-life scenarios in future research.

Laser Triangulation Sensors Performance in Scanning Different Materials and Finishes.

The variety of equipment implementing laser triangulation technology for 3D scanning makes it difficult to analyse their performance, comparability, and traceability. In this study, three laser triangulation sensors arranged in different configurations are analysed using high precision spheres made of different materials and surface finishes. Three types of reference parameters were used: diameter, form error, and standard deviation of the point cloud. The experimentation was based on studying the quality of the point clouds generated by the three sensors, which enabled us to find and quantify an edge effect in the horizon of the scanned surface. A procedure to reach the optimal filtering conditions was proposed, and a chart of recommended usage of each sphere (material and finish) was created for the different types of sensors. This filter enables removal of both spurious points and those few points that spoil the form error, greatly improving the quality of the measurement.

Multi-Sensor Image and Range-Based Techniques for the Geometric Documentation and the Photorealistic 3D Modeling of Complex Architectural Monuments.

The selection of the optimal methodology for the 3D geometric documentation of cultural heritage is a subject of high concern in contemporary scientific research. As a matter of fact, it requires a multi-source data acquisition process and the fusion of datasets from different sensors. This paper aims to demonstrate the workflow for the proper implementation and integration of geodetic, photogrammetric and laser scanning techniques so that high-quality photorealistic 3D models and other documentation products can be generated for a complicated, large-dimensional architectural monument and its surroundings. As a case study, we present the monitoring of the Mehmet Bey Mosque, which is a landmark in the city of Serres and a significant remaining sample of the Ottoman architecture in Greece. The surveying campaign was conducted in the context of the 2022-2023 annual workshop of the Interdepartmental Program of Postgraduate Studies "Protection Conservation and Restoration of Cultural Monuments" of the Aristotle University of Thessaloniki, and it served as a geometric background for interdisciplinary cooperation and decision-making on the monument restoration process. The results of our study encourage the fusion of terrestrial laser scanning and photogrammetric datasets for the 3D modeling of the mosque, as they supplement each other as regards geometry and texture.

Advancing Global Pose Refinement: A Linear, Parameter-Free Model for Closed Circuits via Quaternion Interpolation.

Global pose refinement is a significant challenge within Simultaneous Localization and Mapping (SLAM) frameworks. For LIDAR-based SLAM systems, pose refinement is integral to correcting drift caused by the successive registration of 3D point clouds collected by the sensor. A divergence between the actual and calculated platform paths characterizes this error. In response to this challenge, we propose a linear, parameter-free model that uses a closed circuit for global trajectory corrections. Our model maps rotations to quaternions and uses Spherical Linear Interpolation (SLERP) for transitions between them. The intervals are established by the constraint set by the Least Squares (LS) method on rotation closure and are proportional to the circuit's size. Translations are globally adjusted in a distinct linear phase. Additionally, we suggest a coarse-to-fine pairwise registration method, integrating Fast Global Registration and Generalized ICP with multiscale sampling and filtering. The proposed approach is tested on three varied datasets of point clouds, including Mobile Laser Scanners and Terrestrial Laser Scanners. These diverse datasets affirm the model's effectiveness in 3D pose estimation, with substantial pose differences and efficient pose optimization in larger circuits.

3D Road Boundary Extraction Based on Machine Learning Strategy Using LiDAR and Image-Derived MMS Point Clouds.

The precise extraction of road boundaries is an essential task to obtain road infrastructure data that can support various applications, such as maintenance, autonomous driving, vehicle navigation, and the generation of high-definition maps (HD map). Despite promising outcomes in prior studies, challenges persist in road extraction, particularly in discerning diverse road types. The proposed methodology integrates state-of-the-art techniques like DBSCAN and RANSAC, aiming to establish a universally applicable approach for diverse mobile mapping systems. This effort represents a pioneering step in extracting road information from image-based point cloud data. To assess the efficacy of the proposed method, we conducted experiments using a large-scale dataset acquired by two mobile mapping systems on the Yildiz Technical University campus; one system was configured as a mobile LiDAR system (MLS), while the other was equipped with cameras to operate as a photogrammetry-based mobile mapping system (MMS). Using manually measured reference road boundary data, we evaluated the completeness, correctness, and quality parameters of the road extraction performance of our proposed method based on two datasets. The completeness rates were 93.2% and 84.5%, while the correctness rates were 98.6% and 93.6%, respectively. The overall quality of the road curb extraction was 93.9% and 84.5% for the two datasets. Our proposed algorithm is capable of accurately extracting straight or curved road boundaries and curbs from complex point cloud data that includes vehicles, pedestrians, and other obstacles in urban environment. Furthermore, our experiments demonstrate that the algorithm can be applied to point cloud data acquired from different systems, such as MLS and MMS, with varying spatial resolutions and accuracy levels.