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This study investigated the effectiveness of placing skin-ring structures to enhance the precision of skin dose calculations in patients who had undergone head and neck volumetric modulated arc therapy using the Acuros XB algorithm. The skin-ring structures in question were positioned 2 mm below the skin surface (skin A) and 1 mm above and below the skin surface (skin B) within the treatment-planning system. These structures were then tested on both acrylic cylindrical and anthropomorphic phantoms and compared with the Gafchromic EBT3 film (EBT3). The results revealed that the maximum dose differences between skins A and B for the cylindrical and anthropomorphic phantoms were approximately 12% and 2%, respectively. In patients 1 and 2, the dose differences between skins A and B were 9.2% and 8.2%, respectively. Ultimately, demonstrated that the skin-dose calculation accuracy of skin B was within 2% and did not impact the deep organs.

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Two-photon high-speed fluorescence calcium imaging stands as a mainstream technique in neuroscience for capturing neural activities with high spatiotemporal resolution. However, challenges arise from the inherent tradeoff between acquisition speed and image quality, grappling with a low signal-to-noise ratio (SNR) due to limited signal photon flux. Here, a contrast-enhanced video-rate volumetric system, integrating a tunable acoustic gradient (TAG) lens-based high-speed microscopy with a TAG-SPARK denoising algorithm is demonstrated. The former facilitates high-speed dense z-sampling at sub-micrometer-scale intervals, allowing the latter to exploit the spatial redundancy of z-slices for self-supervised model training. This spatial redundancy-based approach, tailored for 4D (xyzt) dataset, not only achieves >700% SNR enhancement but also retains fast-spiking functional profiles of neuronal activities. High-speed plus high-quality images are exemplified by in vivo Purkinje cells calcium observation, revealing intriguing dendritic-to-somatic signal convolution, i.e., similar dendritic signals lead to reverse somatic responses. This tailored technique allows for capturing neuronal activities with high SNR, thus advancing the fundamental comprehension of neuronal transduction pathways within 3D neuronal architecture.

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Data augmentation is a technique usually deployed to mitigate the possible performance limitation from training a neural network model on a limited dataset, especially in the medical domain. This paper presents a study on effects of applying different rotation settings to augment cardiac volumes from the Multi-modality Whole Heart Segmentation dataset, in order to improve the segmentation performance. This study presents a comparison between conventional 2D (slice-wise) rotation primarily on the axial axis, 3D (volume-wise) rotation, and our proposed rotation setting that takes into account possible cardiac alignment according to its anatomy. The study has suggested two key considerations: 2D slice-wise rotation should be avoided when using 3D data for segmentation, due to intrinsic structural correlation between subsequent slices, and that 3D rotations may help improve segmentation performance on data previously unseen to the model.

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Many compartments are prone to pose safety hazards such as loose fasteners or object intrusion due to their confined space, making manual inspection challenging. To address the challenges of complex inspection environments, diverse target categories, and variable scales in confined compartments, this paper proposes a novel GMS-YOLO network, based on the improved YOLOv8 framework. In addition to the lightweight design, this network accurately detects targets by leveraging more precise high-level and low-level feature representations obtained from GhostHGNetv2, which enhances feature-extraction capabilities. To handle the issue of complex environments, the backbone employs GhostHGNetv2 to capture more accurate high-level and low-level feature representations, facilitating better distinction between background and targets. In addition, this network significantly reduces both network parameter size and computational complexity. To address the issue of varying target scales, the first layer of the feature fusion module introduces Multi-Scale Convolutional Attention (MSCA) to capture multi-scale contextual information and guide the feature fusion process. A new lightweight detection head, Shared Convolutional Detection Head (SCDH), is designed to enable the model to achieve higher accuracy while being lighter. To evaluate the performance of this algorithm, a dataset for object detection in this scenario was constructed. The experiment results indicate that compared to the original model, the parameter number of the improved model decreased by 37.8%, the GFLOPs decreased by 27.7%, and the average accuracy increased from 82.7% to 85.0%. This validates the accuracy and applicability of the proposed GMS-YOLO network.

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Purpose: The body contour of patients with cervical cancer is prone to change between radiotherapy sessions. This study aimed to investigate the effect of body contour changes on the setup and dosimetric accuracy of radiotherapy. Methods: 15 patients with cervical cancer after surgery were randomly selected for retrospective analysis. The body contours on the once-per-week cone-beam computed tomography (CBCT) were registered to the planning CT (pCT) for subsequent evaluation. A body contour conformity index (CIbody) was defined to quantify the variation of body changes. The body volume measured by CBCT was collected, and its relative difference in reference with the first CBCT was calculated and denoted by ΔVn. The relative setup errors, denoted by ΔSELR, ΔSEAP, ΔSESI, and ΔSEvec for left-right, anterior-posterior, superior-inferior, and vectorial shifts, respectively, were defined as the difference in measured setup errors between the reference and following CBCTs. The planned dose was calculated on the basis of virtual CT generated from CBCT and pCT by altering the CT body contour to fit the body on CBCT without deformable registration. The correlations between body contour changes and relative setup errors as well as dosimetric parameters were evaluated using Spearman's correlation coefficient rs . Results: CIbody was found to be negatively correlated with the superior-inferior and vectorial relative setup errors ΔSESI (rs = -0.448, p = 0.001) and ΔSEvec (rs = -0.387, p = 0.002), and no significant correlation was found between relative setup errors and ΔVn. Moreover, ΔVn was negatively correlated with ΔD2 (rs = -0.829, p < 0.001), ΔD98 (rs = -0.797, p < 0.001), and ΔTVPIV (rs = -0.819, p < 0.001). ΔD2, ΔD98, and ΔTVPIV were negatively correlated with ΔVn (p < 0.005). No correlation was found for other examined dosimetric parameters. Conclusion: The body contour change of patients could be associated with the setup variability. The effect of body contour changes on dose distribution is minimal. The extent of body change could be used as a metric for radiation therapists to estimate the setup errors.

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Significance: Rapid acquisition of large imaging volumes with microscopic resolution is an essential unmet need in biological research, especially for monitoring rapid dynamical processes such as fast activity in distributed neural systems. Aim: We present a multifocal strategy for fast, volumetric, diffraction-limited resolution imaging over relatively large and scalable fields of view (FOV) using single-camera exposures. Approach: Our multifocal microscopy approach leverages diffraction to image multiple focal depths simultaneously. It is based on a custom-designed diffractive optical element suited to low magnification and large FOV applications and customized prisms for chromatic correction, allowing for wide bandwidth fluorescence imaging. We integrate this system within a conventional microscope and demonstrate that our design can be used flexibly with a variety of magnification/numerical aperture (NA) objectives. Results: We first experimentally and numerically validate this system for large FOV microscope imaging (three orders-of-magnitude larger volumes than previously shown) at resolutions compatible with cellular imaging. We then demonstrate the utility of this approach by visualizing high resolution three-dimensional (3D) distributed neural network at volume rates up to 100 Hz. These demonstrations use genetically encoded Ca 2 + indicators to measure functional neural imaging both in vitro and in vivo. Finally, we explore its potential in other important applications, including blood flow visualization and real-time, microscopic, volumetric rendering. Conclusions: Our study demonstrates the advantage of diffraction-based multifocal imaging techniques for 3D imaging of mm-scale objects from a single-camera exposure, with important applications in functional neural imaging and other areas benefiting from volumetric imaging.

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A precise prediction of the cure-induced shrinkage of an epoxy resin is performed using a finite element simulation procedure for the material behaviour. A series of experiments investigating the cure shrinkage of the resin system has shown a variation in the measured cure-induced strains. The observed variation results from the thermal history during the pre-cure. A proposed complex thermal expansion model and a conventional chemical shrinkage model are utilised to predict the cure shrinkage observed with finite element simulations. The thermal expansion model is fitted to measured data and considers material effects such as the glass transition temperature and the evolution of the expansion with the degree of cure. The simulations accurately capture the exothermal heat release from the resin and the cure-induced strains across various temperature profiles. The simulations follow the experimentally observed behaviour. The simulation predictions achieve good accuracy with 2-6% discrepancy compared with the experimentally measured shrinkage over a wide range of cure profiles. Demonstrating that the proposed complex thermal expansion model affects the potential to minimise the shrinkage of the studied epoxy resin. A recommendation of material parameters necessary to accurately determine cure shrinkage is listed. These parameters are required to predict cure shrinkage, allow for possible minimisation, and optimise cure profiles for the investigated resin system. Furthermore, in a study where the resin movement is restrained and therefore able to build up residual stresses, these parameters can describe the cure contribution of the residual stresses in a component.

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Hydrogen fuel holds promise for clean energy solutions, particularly in onboard applications such as fuel cell vehicles. However, the development of efficient hydrogen storage systems remains a critical challenge. This study addresses this challenge by exploring the potential of high-strength novel materials, including glass, to maximize onboard hydrogen storage capacity. A mathematical approach was employed to evaluate the feasibility and efficacy of various high-strength materials for hydrogen storage. This study focused on capillary arrays as a promising storage medium and utilized mathematical modeling techniques to estimate the storage capacity enhancement achievable with different materials. The analysis revealed significant variations in storage capacity enhancements in different high-strength novel materials, with glass having promising results. Glass-based materials demonstrated the potential to meet or exceed US Department of Energy (DOE) targets for both gravimetric and volumetric hydrogen storage capacities in capillary arrays. By leveraging a mathematical approach, this study identified high-strength novel materials, including glass and polymers, capable of substantially improving onboard hydrogen storage capacity: 29 wt.% with 40 g/L for quartz glass and 25 wt.% with 38 g/L for Kevlar compared to 5.2 wt.% with 26.3 g/L from a conventional type IV tank. These findings underscore the importance of material selection in optimizing hydrogen storage systems and provide valuable insights for the design and development of next-generation hydrogen storage technologies for onboard applications.

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PURPOSE: This study evaluates deep learning (DL) based dose prediction methods in head and neck cancer (HNC) patients using two types of input contours. MATERIALS AND METHODS: Seventy-five HNC patients undergoing two-step volumetric-modulated arc therapy were included. Dose prediction was performed using the AIVOT prototype (AiRato.Inc, Sendai, Japan), a commercial software with an HD U-net-based dose distribution prediction system. Models were developed for the initial plan (46 Gy/23Fr) and boost plan (24 Gy/12Fr), trained with 65 cases and tested with 10 cases. The 8-channel model used one target (PTV) and seven organs at risk (OARs), while the 10-channel model added two dummy contours (PTV ring and spinal cord PRV). Predicted and deliverable doses, obtained through dose mimicking on another radiation treatment planning system, were evaluated using dose-volume indices for PTV and OARs. RESULTS: For the initial plan, both models achieved approximately 2% prediction accuracy for the target dose and maintained accuracy within 3.2 Gy for OARs. The 10-channel model outperformed the 8-channel model for certain dose indices. For the boost plan, both models exhibited prediction accuracies of approximately 2% for the target dose and 1 Gy for OARs. The 10-channel model showed significantly closer predictions to the ground truth for D50% and Dmean. Deliverable plans based on prediction doses showed little significant difference compared to the ground truth, especially for the boost plan. CONCLUSION: DL-based dose prediction using the AIVOT prototype software in HNC patients yielded promising results. While additional contours may enhance prediction accuracy, their impact on dose mimicking is relatively small.

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BACKGROUND: Dental resin composites' performance is intricately linked to their polymerisation shrinkage characteristics. This study compares polymerisation shrinkage using advanced 3D micro-computed tomography (micro-CT) and traditional 2D linear assessments. It delves into the crucial role of filler content on shrinkage and the degree of conversion in dental resin composites, providing valuable insights for the field. METHODS: Five experimental dental composite materials were prepared with increasing filler contents (55-75 wt%) and analysed using either 3D micro-CT for volumetric shrinkage or a custom-designed linometer for 2D linear shrinkage. The degree of conversion was assessed using Optical Photothermal Infrared (O-PTIR) and Fourier-Transform Infrared (FTIR) spectroscopy. Light transmittance through a 2-mm layer was evaluated using a NIST-calibrated spectrometer. Scanning Electron Microscopy (SEM) and Energy-Dispersive X-ray Spectroscopy (EDX) examined surface morphology and elemental distribution. Correlation between the investigated parameters was determined using Spearman correlation analyses. RESULTS: The study found significant differences in polymerisation-related properties among different filler content categories, with volumetric shrinkage consistently demonstrating higher mean values than linear shrinkage across most groups. Volumetric shrinkage decreased with increasing curing depth, showing no direct correlation between filler content and shrinkage levels at different curing depths. The results highlighted a strong negative correlation between filler content and degree of conversion, volumetric and linear shrinkage, as well as maximum shrinkage rate. Light transmittance showed a moderate correlation with the filler content and a weak correlation with other tested parameters. CONCLUSIONS: This study underscores the importance of considering both volumetric and linear shrinkage in the design and analysis of dental composite materials. The findings advocate optimising filler content to minimise shrinkage and enhance material performance. Integrating micro-CT and O-PTIR techniques offers novel insights into dental composites' polymerisation behaviour, providing a foundation for future research to develop materials with improved clinical outcomes.

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Our aim was to compare the performance of complementary clinical laboratory approaches to monitoring exposure to apixaban and rivaroxaban, the most prescribed direct-acting oral anticoagulants (DOAC's): an automated commercial anti-Xa chromogenic assay suitable for emergency and pre-surgery testing and a laboratory-developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) method employed for non-emergency analysis in plasma and in dried blood volumetric absorptive microsamples (VAMS) collectible by the patients in their homes. The full validation of the LC-MS/MS method was performed. Cross-validation of the methodologies was accomplished by processing 60 specimens collected for whole blood count and DOAC monitoring in a central clinical laboratory. For VAMS samples, dried plasma and whole blood calibrators were found to be suitable, and a cycle run for seven days could be implemented for rational and economic sample processing. The anti-Xa chromogrenic assay and the LC-MS/MS method delivered discordant plasma analyte concentrations. Moreover, the lack of agreement between plasma and VAMS concentrations was observed. Clinical laboratories must be aware of the differences between the performance of apixaban and rivaroxaban LC-MS/MS and anti-Xa assays. Hematocrit must always be measured along with VAMS samples to obtain accurate results.

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This study retrospectively evaluates the clinical outcomes of definitive volumetric modulated arc therapy (VMAT) for high-risk or very high-risk locoregional prostate cancer patients from an Asian institution. Consecutive patients who received VMAT (76 Gy in 38 fractions) between January 2017 and June 2022 were included. Whole pelvic radiotherapy (WPRT) (46 Gy in 23 fractions) was employed for clinically node-negative disease (cN0) and a Roach estimated risk of ≥15%, as well as simultaneous integrated boost (SIB) of 55-57.5 Gy to node-positive (cN1) disease. The primary endpoint was biochemical relapse-free survival (BRFS). Secondary endpoints included radiographic relapse-free survival (RRFS), metastasis-free survival (MFS) and prostate cancer-specific survival (PCSS). A total of 209 patients were identified. After a median follow-up of 47.5 months, the 4-year actuarial BRFS, RRFS, MFS and PCSS were 85.2%, 96.8%, 96.8% and 100%, respectively. The incidence of late grade ≥ 2 genitourinary (GU) and gastrointestinal (GI) toxicity were 15.8% and 11.0%, respectively. No significant difference in cancer outcomes or toxicity was observed between WPRT and prostate-only radiotherapy for cN0 patients. SIB to the involved nodes did not result in increased toxicity. International Society of Urological Pathology (ISUP) group 5 and cN1 stage were associated with worse RRFS (p < 0.05). PSMA PET-CT compared to conventional imaging staging was associated with better BRFS in patients with ISUP grade group 5 (p = 0.039). Five-year local experience demonstrates excellent clinical outcomes. PSMA PET-CT staging for high-grade disease and tailored pelvic irradiation based on nodal risk should be considered to maximize clinical benefit.

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There are limited treatment options for individuals with drug-resistant idiopathic generalized epilepsy (IGE). Small, limited case series suggest that centromedian thalamus deep brain stimulation (CM-DBS) may be an effective treatment option. The optimal CM-DBS target for IGE is underexamined. Here, we present a retrospective analysis of CM-DBS targeting and efficacy for five patients with drug-resistant IGE. Volume of tissue activated (VTA) overlap with CM nucleus was performed using an open-source toolbox. Median follow-up time was 13 months. Median convulsive seizure frequency reduction was 66%. One patient had only absence seizures, with >99% reduction in absence seizure frequency. Four patients had electrode contacts positioned within the CM nucleus target, all of whom had >50% reduction in primary semiology seizure, with 85% median seizure reduction (p = .004, paired-sample t test). Volumetric "sweet-spot" mapping revealed that best outcomes were correlated with stimulation of the middle ventral CM nucleus. Connectivity strength between the sweet-spot region and central peri-Rolandic cortex was increased significantly relative to other cortical regions (p = 8.6 × 10-4, Mann-Whitney U test). Our findings indicate that CM-DBS can be an effective treatment for patients with IGE, highlight the importance of accurate targeting and targeting analysis, and within the context of prior work, suggest that ideal CM-DBS targets may be syndrome specific.

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PURPOSE: The aim of this study is to determine the effect of forcing and filling the electron density (ED) to 1.0 of the planning target volume (PTV) overdose distribution in lung SBRT treatment leading to shortening patient treatment time and increasing patient comfort by reducing MU/fraction due to ED manipulation effect. METHODS: In this study, 36 lung SBRT plans of 12 suitable patients who prescribed a total dose of 50 Gy in five fractions were generated with Monaco v.5.10 TPS using the Monte Carlo (MC) algorithm and volumetric modulated arc therapy (VMAT) technique by PTV ED values forcing as well as filling to 1.0 and comparatively assessed. The first group of plans was created by using the patient's original ED, second and third groups of plans were reoptimized by forcing and filling the ED of PTV to 1.0, respectively, therefore acquiring a new dose distribution which lead to comparatively assessment the effects of changes in ED on PTV and OAR doses. RESULTS: Assessment of treatment plans revealed that mean MU/fx numbers were decreased by 76% and 75.25% between Groups 1 and 2, Groups 1 and 3, respectively. The number of segments was also reduced in Group 1 by up to 15% compared with Groups 2 and 3. Maximum HI and CI differences for PTV between Groups 1 and 2 were less than 1% and Groups 1 and 3 were 1.5% which indicates all 3 group plans were comparable in terms of dose distribution within PTV. CONCLUSIONS: Forcing and filling the ED of PTV to 1.0 strategy has provided reduced a number of segments and MU/fx without a significant change in PTV mean and maximum doses, thereby decreasing treatment time and patient discomfort during treatment. This process should be considered in line of a potential number of patients as well as prescribed dose and MU/fx numbers.

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Tissue engineering has long sought to rapidly generate perfusable vascularized tissues with vessel sizes spanning those seen in humans. Current techniques such as biological 3D printing (top-down) and cellular self-assembly (bottom-up) are resource intensive and have not overcome the inherent tradeoff between vessel resolution and assembly time, limiting their utility and scalability for engineering tissues. We present a flexible and scalable technique termed SPAN - Sacrificial Percolation of Anisotropic Networks, where a network of perfusable channels is created throughout a tissue in minutes, irrespective of its size. Conduits with length scales spanning arterioles to capillaries are generated using pipettable alginate fibers that interconnect above a percolation density threshold and are then degraded within constructs of arbitrary size and shape. SPAN is readily used within common tissue engineering processes, can be used to generate endothelial cell-lined vasculature in a multi-cell type construct, and paves the way for rapid assembly of perfusable tissues.

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Volumetric subcellular imaging has long been essential for studying structures and dynamics in cells and tissues. However, due to limited imaging speed and depth of field, it has been challenging to perform live-cell imaging and single-particle tracking. Here we report a 2.5D fluorescence microscopy combined with highly inclined illumination beams, which significantly reduce not only the image acquisition time but also the out-of-focus background by ∼2-fold compared to epi-illumination. Instead of sequential z-scanning, our method projects a certain depth of volumetric information onto a 2D plane in a single shot using multi-layered glass for incoherent wavefront splitting, enabling high photon detection efficiency. We apply our method to multi-color immunofluorescence imaging and volumetric super-resolution imaging, covering ∼3-4 µm thickness of samples without z-scanning. Additionally, we demonstrate that our approach can substantially extend the observation time of single-particle tracking in living cells.

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High entropy alloys (HEAs) are alloys composed of five or more primary elements in equal or nearly equal proportions of atoms. In the present study, the thermophysical properties of the CoCrFeNiCu high entropy alloy (HEA) were investigated by a molecular dynamics (MD) method at nanoscale. The effects of the content of individual elements on lattice thermal conductivity k p were revealed, and the results suggested that adjusting the atomic content can be a way to control the lattice thermal conductivity of HEAs. The effects of temperature on k p were investigated quantitively, and a power-law relationship of k p with T -0.419 was suggested, which agrees with previous findings. The effects of temperature and the content of individual elements on volumetric specific heat capacity C v were also studied: as the temperature increases, the C v of all HEAs slightly decreases and then increases. The effects of atomic content on C v varied with the comprising elements. To further understand heat transfer mechanisms in the HEAs, the phonon density of states (PDOS) at different temperatures and varying atomic composition was calculated: Co and Ni elements facilitate the high-frequency vibration of phonons and the Cu environment weakens the heat transfer via low-frequency vibration of photons. As the temperature increases, the phonon mean free path (MFP) in the equiatomic CoCrFeNiCu HEA decreases, which may be attributed to the accelerated momentum of atoms and intensified collisions of phonons. The present research provides theoretical foundations for alloy design and have implications for high-performance alloy smelting.

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BACKGROUND: To evaluate clinical outcomes and volumetric changes following endoscopic endonasal approach (EEA) for tuberculum sellae (TS) and planum sphenoidale (PS) meningiomas. Key objectives included evaluating pre- and postoperative tumor volumes, visual assessments and EEA-related complications. METHODS: A single-center retrospective study was conducted at Foothills Medical Centre, University of Calgary, Canada, from 2009 to 2022 including 24 patients meeting inclusion criteria for midline skull base tumors, confirmed as WHO Grade I or II meningiomas with optic canal extension. RESULTS: EEA achieved gross total resection in 87.5% of cases, with a mean tumor volume reduction of 92.24%. Postoperatively, 91.67% exhibited visual improvement or stability. Cerebrospinal fluid leaks occurred in 12.5% of cases, necessitating revision surgery in one case. Persistent postoperative endocrine dysfunction affected 4.17%. Preoperative tumor volume did not demonstrate a correlation with complications. CONCLUSIONS: This study delivers reproducible data for pre- and postoperative tumor volume following the EEA after TS or PS meningiomas. The EEA demonstrated favorable radiographic and clinical outcomes in TS and PS meningiomas, achieving gross total resection with minimal morbidity.

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BACKGROUND: The aim of this study was to evaluate clinical one-dimensional changes such as root surface coverage, decrease seen in the amount of gingival recession and keratinised gingival width (KGW) obtained throughout a 6-month follow-up period following the treatment of Cairo class II gingival recession with free gingival graft (FGG) and gingival unit graft (GUG). Three-dimensional changes in gingival volume and thickness were also compared digitally using an indirect method. METHODS: A total of 20 patients with localised Cairo class II gingival recession were randomly separated into two groups; 10 patients were treated with FGG and 10 patients treated with GUG. Preoperatively and at 6 months postoperatively, the initial position of the gingiva and KGW were recorded for all the patients and plaster models were formed from the obtained impressions with the traditional method. The plaster models were transferred to a digital environment by scanning with a model scanner. Using a software program, changes in gingival papillary height and gingival volume and thickness were compared between the groups and according to the baseline values from The Standard Tessellation Language (STL) files obtained. RESULTS: Compared to the baseline values, a significant increase was determined in the KGW, and a significant decrease in pocket depth, clinical attachment level, and gingiva recession depth in all the groups (p<0.05). No statistically significant difference was determined between the groups in respect of the changes in mean gingiva thickness, gingiva volume, and mean vertical papillary height (p>0.05). CONCLUSION: The study results showed that GUG treatment for Cairo class II localised gingival recession is an effective method in respect of increasing gingiva volume and thickness, increasing KGW, coverage of the root surface, and forming tissue contours that allow the patient to easily maintain oral hygiene. However, there was not seen to be any adventage of GUG and FGG over each other.

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Alternaria is a ubiquitous fungal genus with many allergenic and pathogenic species inhabiting grasslands. We hypothesise that grasslands (natural/man-made) host a diversity of fungal species whose spores have varying emission patterns. Therefore, the purpose of this study was to examine the potential of grasslands for emission, diversity and composition of Alternaria and other fungal species. To test the hypothesis, Hirst-type and multi-vial Cyclone samplers collected air samples from two grassland sites (unmanaged and managed) and a non-grassland site at Lakeside campus of the University of Worcester, United Kingdom for the period May to September 2019. The unmanaged grassland was originally planted with grasses and left uncut for three years. The managed grassland was a roadside verge that was cut once every year, typically after most grasses have flowered. We used optical microscopy and Illumina MiSeq sequencing to investigate the emission, abundance, diversity and composition of the fungal spores from each site alongside meteorological variables. Kruskal-Wallis and Wilcoxon tests examined differences in the bi-hourly Alternaria concentrations between the sites. Shannon's and Simpson's Index determined the diversity of the fungal spores between the unmanaged and non-grassland sites. The results showed that grasslands are a strong source of Alternaria spores with considerably higher numbers of clinically important days compared with the non-grassland site. The managed grassland varied in Alternaria spore emission pattern from the unmanaged, probably due to differences in environmental variables and cutting frequency. The unmanaged grassland and non-grassland sites showed a high diversity of fungi including Alternaria, Cladosporium, Ascochyta, Botrytis and Aureobasidium. Overall, the study shows that grasslands are a strong source of fungal spores with allergenic and pathogenic potential and have varying emission patterns, compared with nearby urban areas where monitoring stations are located. This information is useful for atmospheric modelling of airborne fungal spore sources and has implications for allergy sufferers in particular.