Size Measurements Research Articles

Deep learning techniques for imaging diagnosis and treatment of aortic aneurysm.

This study aims to review the application of deep learning techniques in the imaging diagnosis and treatment of aortic aneurysm (AA), focusing on screening, diagnosis, lesion segmentation, surgical assistance, and prognosis prediction. A comprehensive literature review was conducted, analyzing studies that utilized deep learning models such as Convolutional Neural Networks (CNNs) in various aspects of AA management. The review covered applications in screening, segmentation, surgical planning, and prognosis prediction, with a focus on how these models improve diagnosis and treatment outcomes. Deep learning models demonstrated significant advancements in AA management. For screening and diagnosis, models like ResNet achieved high accuracy in identifying AA in non-contrast CT scans. In segmentation, techniques like U-Net provided precise measurements of aneurysm size and volume, crucial for surgical planning. Deep learning also assisted in surgical procedures by accurately predicting stent placement and postoperative complications. Furthermore, models were able to predict AA progression and patient prognosis with high accuracy. Deep learning technologies show remarkable potential in enhancing the diagnosis, treatment, and management of AA. These advancements could lead to more accurate and personalized patient care, improving outcomes in AA management.

Evaluation of methods for characterizing the fine particulate matter emissions from aircraft and other diffusion flame combustion aerosol sources

The U. S. Environmental Protection Agency in collaboration with the U. S. Air Force Arnold Engineering Development Complex conducted the VAriable Response In Aircraft nvPM Testing (VARIAnT) 3 and 4 test campaigns to compare nonvolatile particulate matter (nvPM) emissions measurements from a variety of diffusion flame combustion aerosol sources (DFCASs), including a Cummins diesel engine, a diesel powered generator, two gas turbine start carts, a J85-GE-5 turbojet engine burning multiple fuels, and a Mini-CAST soot generator. The VARIAnT research program was devised to understand reported variability in the ARP6320A sampling system nvPM measurements. The VARIAnT research program has conducted four test campaigns to date with the VARIAnT 3 and 4 campaigns devoted to: (1) assessing the response of three different black carbon mass analyzers to particles of different size, morphology, and chemical composition; (2) characterizing the particles generated by 6 different combustion sources according to morphology, effective density, and chemical composition; and (3) assessing any significant difference between black carbon as determined by the 3 mass analyzers and the total PM determined via other techniques. Results from VARIAnT 3 and 4 campaigns revealed agreement of about 20% between the Micro-Soot Sensor, the Cavity Attenuated Phase Shift (CAPS PMSSA) monitor and the thermal-optical reference method for elemental carbon (EC) mass, independent of the calibration source used. For the LII-300, the measured mass concentrations in VARIAnT 3 fall within 18% and in VARIAnT 4 fall within 27% of the reference EC mass concentration when calibrated on a combustor rig in VARIAnT 3 and on an LGT-60 start cart in VARIAnT 4, respectively. It was also found that the three mass instrument types (MSS, CAPS PMSSA, and LII-300) can exhibit different BC to reference EC ratios depending on the emission source that appear to correlate to particle geometric mean mobility diameter, morphology, or some other parameter associated with particle geometric mean diameter (GMD) with the LII-300 showing a slightly stronger apparent trend with GMD. Systematic differences in LII-300 measured mass concentrations have been reduced by calibrating with a turbine combustion as a particle source (combustor or turbine engine). With respect to the particle size measurements, the sizing instruments (TSI SMPS, TSI EEPS, and Cambustion DMS 500) were found to be in general agreement in terms of size distributions and concentrations with some exceptions. Gravimetric measurements of the total aerosol mass produced by the various DFCAs differed from the reference EC, BC and integrated particle size distribution measured aerosol masses. The measurements of particle size distributions and single particle analysis performed using the miniSPLAT indicated the presence of larger particles (≳150 nm) having more compact morphologies, higher effective density, and a composition dominated by OC and containing ash. This increased large particle fraction is also associated with higher values of single scattering albedo measured by the CAPS PMSSA instrument and higher OC measurements. These measurements indicate gas turbine engine emissions can be a more heterogeneous mix of particle types beyond the original E−31 assumption that engine exit exhaust particles are mainly composed of black carbon.

Denoising Multiphase Functional Cardiac CT Angiography Using Deep Learning and Synthetic Data.

Coronary CT angiography is increasingly used for cardiac diagnosis. Dose modulation techniques can reduce radiation dose, but resulting functional images are noisy and challenging for functional analysis. This retrospective study describes and evaluates a deep learning method for denoising functional cardiac imaging, taking advantage of multiphase information in a three-dimensional convolutional neural network. Coronary CT angiograms (n = 566) were used to derive synthetic data for training. Deep learning-based image denoising was compared with unprocessed images and a standard noise reduction algorithm (block-matching and three-dimensional filtering [BM3D]). Noise and signal-to-noise ratio measurements, as well as expert evaluation of image quality, were performed. To validate the use of the denoised images for cardiac quantification, threshold-based segmentation was performed, and results were compared with manual measurements on unprocessed images. Deep learning-based denoised images showed significantly improved noise compared with standard denoising-based images (SD of left ventricular blood pool, 20.3 HU ± 42.5 [SD] vs 33.4 HU ± 39.8 for deep learning-based image denoising vs BM3D; P < .0001). Expert evaluations of image quality were significantly higher in deep learning-based denoised images compared with standard denoising. Semiautomatic left ventricular size measurements on deep learning-based denoised images showed excellent correlation with expert quantification on unprocessed images (intraclass correlation coefficient, 0.97). Deep learning-based denoising using a three-dimensional approach resulted in excellent denoising performance and facilitated valid automatic processing of cardiac functional imaging. Keywords: Cardiac CT Angiography, Deep Learning, Image Denoising Supplemental material is available for this article. © RSNA, 2024.

Effects of Blood-Derived Products on Cellular Senescence and Inflammatory Response: A Study on Skin Rejuvenation.

Blood-derived products, such as citrate platelet-rich plasma (CPRP) and hyperacute serum (HAS), are recognized for their rich growth factor content. When human dermal fibroblast (HDF) cells are exposed to combined mitogenic and DNA-damaging stimuli, it can lead to an increased burden of senescent cells and a modified senescence-associated secretory phenotype. In this study, the senescent state was comprehensively assessed through various methods, including phosphorylated histone H2AX (γH2AX) staining, p21 and p16 q-PCR, p21-western blot, growth curves, and senescence-associated ß-galactosidase staining. Two primary treatments with blood products were administered, one early (immediately after etoposide) and the other late (11 days after etoposide treatment). The effects of the blood product treatment were evaluated by measuring interleukin 6 and 8 (IL-6 and IL-8) levels, as well as collagen 1 (COL1) and p21 mRNA expression. Additionally, 2,3-bis-(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT) assays, cell size measurements, viability assays, and cell number calculations were conducted. The results revealed that cells treated with hyperacute serum in the early treatment phase exhibited the lowest observed IL-6 and IL-8 levels. In contrast, a clear inflammatory response for IL-8 was observed in cells treated with hyperacute serum and citrate platelet-rich plasma during the late treatment. Furthermore, an upregulation of COL1 expression was observed in the early treatment, while cells in the late treatment group remained unaffected. Notably, citrate platelet-rich plasma-treated cells showed a decrease in COL1 expression. Overall, the treatment with blood products appears to have slightly positive effects on skin rejuvenation.

Evaluation of chemical quality attributes in bruised bananas during storage

The influence of three impact energies resulted from simulated impactor, three storage temperatures conditions, and 12 days of storage duration was evaluated in the chemical characteristics of bruised banana fruit. The study used the pendulum impactor for impact energy generation (low, medium, high). The bruise size measurements, total soluble solids, titratable acidity, maturity index (sugar:acid ratio), and pH were analysed. Some minerals were determined like sodium, calcium, and potassium. The results showed that increasing all factors significantly affected the bruise susceptibility value of banana. Bananas conditioned at 22 °C after being impacted by high damage recorded the highest total soluble solids (20.95 °Brix), sugar:acid ratio (131.38%), and lower acidity (0.15%). Storage at 22 °C accelerated the changes in pH after 12 days of storage. Calcium and potassium were influenced by storage temperatures. Regarding the regression model, the 3 indicators accounts for 61.8% and 82.8% of bruise area and total soluble solids variance, respectively. The bruise susceptibility was correlated negatively with acidity and positively correlated with other bruise parameters, pH, total soluble solids. Overall, the chemical attributes provide a clue to understanding the bruise susceptibility of banana fruit. Also, the study successfully emphasized that the mechanical damage proposed by the study can affect the bruise magnitude and the chemical quality attributes of banana fruit during storage, thus the methodology of the study can be applied for different produce at multiple storage conditions.

Opinion: Should high-resolution differential mobility analyzers be used in mainstream aerosol studies?

Abstract. Differential mobility analyzers (DMAs) are widely used instruments to measure the size distributions of submicron aerosols. High-resolution DMAs (HRDMAs) are defined here as plain DMAs maintaining a steady flow over an unusually broad range of sheath gas flow rates Q. HRDMAs, first developed by Georg Reischl's group, have existed for a long time. However, they have not been widely adopted, except in the size range below 10 nm, often in new particle formation studies. Here we question the commonly held view that HRDMAs are necessarily complex, bulky and expensive machines, mainly of interest in exotic applications outside mainstream aerosol research. Rather, many studies central to aerosol research could be carried out with HRDMAs with considerable advantage in size range, resolution, sensitivity and measurement speed. DMA manufacturers will hopefully take the challenge of developing commercial HRDMAs of complexity and cost comparable to those of today's commercial instruments, adapted for broad use by aerosol scientists, though with greatly improved flexibility and performance. Some of the technical challenges that still need to be overcome are discussed, such as the development of high-flow condensation counter detectors, and the control of high sample and sheath gas flow rates.

A smart fruit size measuring method and system in natural environment

The measurement of fruit size (length, width, and area) is one of the key components in the assessment of fruit ripeness for consumption and fruit quality. Due to issues with fruit shape and ambient occlusion, noncontact measurement of fruits in their natural growth state in natural environment is more difficult. This study proposes a fast and low-cost noncontact measurement solution combining deep learning, image analysis and robotic platform. First, based on the YOLOv5 object detection algorithm and converged dataset, a 95.6% detection accuracy and 0.05 s detection speed was achieved. Second, a Cycle GAN model for fruit occlusion recovery was established, and the occlusion of the fruit under different natural conditions was adaptively repaired, with a 5.48% average relative error under different occlusion conditions. Third, through image morphological operations, the size measurements were achieved, with an average relative error of 8.43% for individual fruits and the 10.12% overall error under the complex natural environment. This method and platform provide a systematic, fast (0.2s) and low-cost solution for the noncontact measurement of fruit size.

Real-time in situ monitoring of dust particle growth in a low-pressure nanodusty plasma based on laser-induced photodetachment

Particulate matter air pollution in the form of ultrafine dust is a growing global concern. In this Letter, we will use a nanodusty Ar/HMDSO plasma as a model system for a heavily contaminated gas and we present the development of a technique for real-time in situ measurements of the dust particle size. The method is based on laser-induced photodetachment of bound electrons from the surface of dust particles. These photo-released electrons are measured as an increase in the free electron density of the plasma using microwave cavity resonance spectroscopy. We show that instead of reconstructing the entire resonance profile, the temporal response of a single microwave frequency was enough to perform the measurements. More specifically, the decay timescale of the cavity response can be interpreted as the re-charging timescale of the dust particles. Then, using a stochastic model, this timescale can be modeled, which eventually retrieves the dust particle size. We found good agreement between the predicted dust particle size and the average dust particle size obtained from ex situ scanning electron microscopy measurements. This method allows for the real-time monitoring of the dust particle size and a controlled production of nanometer-scale dust particles, which gives opportunities both for fundamental dusty plasma physics and models, as well as for applications in monitoring ultrafine dust air pollution.

Pupil size measurements with a multifunctional aberrometer/coherence interferometer/tomographer and two infrared-based pupillometers.

To compare precision of pupil size measurements of a multifunctional device (Pentacam AXL Wave [Pentacam]) and 2 infrared-based pupillometers (PupilX, Colvard) and to compare repeatability of Pentacam and PupilX. Department of Ophthalmology, Goethe-University, Frankfurt am Main, Germany. Prospective, comparative trial. Pupil diameter of healthy eyes was measured with Colvard once and Pentacam without glare (WO) and with glare (WG), PupilX in 0, 1, and 16 lux 3 times each. In a second series, measurements with Pentacam WO and PupilX in 0.06 and 0.12 lux were assessed. 36 eyes of participants aged 21 to 63 years were included. Mean pupil diameter was 6.05 mm with Colvard, 5.79 mm (first series), 5.50 mm (second series) with Pentacam WO, 3.42 mm WG, 7.26 mm PupilX in 0, 4.67 mm 1, 3.66 mm 16, 6.82 mm in 0.06, and 6.39 mm in 0.12 lux. Measurements with Pentacam WO were significantly different to PupilX in 0, 0.06, 0.12, and 1 lux (all P < .001), but not to Colvard ( P = .086). Pupil size measured with Pentacam WG and PupilX in 16 lux was not significantly different ( P = .647). Consecutive measurements with Pentacam WO and WG had mean SD of 0.23 mm and 0.20 mm, respectively, and with PupilX 0.11 in 0, 0.24 mm 1, and 0.20 mm in 16 lux. Pentacam provided good assessment of pupil size but was not equivalent to PupilX in low lighting conditions. Repeatability was more favorable for Pentacam.

Barrier or opportunity? How trade regulations shape Colombian firms' export strategies

AbstractFirms increasingly have to contend with trade regulations to access foreign markets. We quantify their relative importance and the heterogeneous effects for Colombians firms exporting to Latin America between 2007 and 2017, focusing on specific types and channels. Using panel evidence from a firm‐level gravity model with a difference‐in‐differences identification strategy, technical barriers to trade (TBTs) and quantity control measures both decrease trade on average. Other non‐tariff measures and tariffs play a minor role. At its core, TBT and quantity measures reallocate trade from small to big firms. The same mechanism benefits firms participating in global value chains. However, quantity controls make it more likely that big firm will leave export markets to the benefit of smaller ones. Our results control for the endogeneity of trade regulations and are robust to the use of different samples and measures of firm size.

Improving accuracy of age estimates for insect evidence-calibration of physiological age at emergence (k) using insect size but without "k versus size" model.

Postmortem interval may be estimated based on the age of insect evidence collected on a death scene. Reference data that are used in such estimation frequently comprise thermal summation constant (i.e. k), which is equal to the insect age upon completion of immature development expressed in accumulated degree-days or degree-hours (ADD or ADH). Essentially, k is a central point of an insect group and it may poorly represent insect evidence that is near the limits of variation for the group. Accordingly, it was postulated to calibrate k for particular insect evidence and insect size and sex were found to be useful for this purpose in some of the species. However, the calibration is only possible by using the model that correlates k with insect size. Since very few such models were published, this lack of data limits the calibration of k in forensic casework. In this article, we develop a formula that is useful for the calibration of k without the use of "k versus size" model (and related datasets). The formula uses k from the general thermal summation model for a species (with its standard error), size range for the species (retrieved from entomology literature), and size measurements for particular insect evidence. The calibration of k with the formula was validated using the Creophilus maxillosus (Coleoptera: Staphylinidae) and Necrodes littoralis (Coleoptera: Silphidae) datasets. It was particularly useful while analyzing unusually small and large insects, in case of which the formula reduced the inaccuracy of k from the general model on average by ~25 ADD in C. maxillosus and ~40 ADD in N. littoralis. We discuss the limitations and prospects of the calibration protocol that employs the formula.

Effects of a neuromuscular training program on the performance and inter-limb asymmetries in highly trained junior male tennis players

BackgroundThe objective of this study was to assess the effectiveness of neuromuscular training on the performance of highly trainer junior tennis players. MethodsTwelve male tennis players (age: 13.4 ± 0.36 years; weight: 50.2 ± 6.29 kg; height: 163 ± 4.41 cm) participated and were randomly divided into two groups. The experimental group (EG) performed neuromuscular training that included exercises for speed, strength, throws, agility, jumps and coordination twice a week for a duration of 10 weeks. Performance was evaluated using various variables, including bilateral and unilateral countermovement jump, 30 cm drop jump and horizontal jump, 505 change of direction test conducted with both the right and left legs, 20-m sprint, and overhead 3 kg medicine ball throw. Asymmetries were also evaluated during the unilateral tests. The impact of the training was assessed through the utilization of ANCOVA tests and effect size measurements. ResultsThe results indicated a significant enhancement in the EG, specifically in bilateral vertical jump and horizontal jump, as well as explosive strength and speed. Conversely, the control group (CG) did not display similar advancements. Furthermore, there was no increase in asymmetries. ConclusionThis suggests that the implementation of a neuromuscular training program could prove to be an effective approach in enhancing explosive power in the lower limbs among young competitive tennis players. Finally, this training program could contribute to the enhancement of their physical attributes in lower body of young tennis players.

Comparative Study of Droplet Diameter Distribution: Insights from Experimental Imaging and Computational Fluid Dynamics Simulations

The interfacial area between two phases plays a crucial role in the mass transfer rate of gas–liquid processes such as absorption. In this context, the droplet size distribution within the flow field of a droplet-based absorber significantly affects the surface area, thereby influencing the absorption efficiency. This study focuses on developing a computational fluid dynamics (CFD) model to predict the size and distribution of water droplets free-falling in a transparent square tube. This model serves as a digital twin of our experimental setup, enabling a comparative analysis of experimental and computational results. For the accurate measurement of droplet size and distribution, specialized experimental equipment was developed, and a high-speed camera along with Fiji software was used for the capturing and processing of droplet images. At the point of injection and at two different heights, the sizes and distributions of falling droplets were measured using this setup. The interaction between the liquid water droplets and the gas phase within the square tube was modeled using the Eulerian–Lagrangian (E-L) framework in the STAR-CCM+ software. The E-L multiphase CFD model yielded approximations with errors ranging from 11 to 27% for various average mean diameters, including d10, d20, d30, and d32, of the liquid droplets at two distinct heights (200 mm and 400 mm) for both nozzle plates. This comprehensive approach provides valuable insights into the dynamics of droplet-based absorption processes.

Evaluation of the Stability of Newborn Hospital Parenteral Nutrition Solutions.

(1) Background: parenteral nutrition (PN) solutions are an extremely complex mixture. It is composed of a multitude of chemical elements that can give rise to a large number of interactions that condition its stability and safety. The aim of this study was to evaluate the stability of PN solutions for preterm infants. (2) Methods: eight samples were prepared according to the protocol for prescribing PN in preterm infants. Samples PN1-PN7 had the normal progression of macronutrients and standard amounts of micronutrients for a 1 kg preterm infant. The PN8 sample had a high concentration of electrolytes, with the idea of forcing stability limits. Samples were stored both at room temperature and under refrigeration. Measurements of globule size, pH, density, and viscosity were performed in both storage protocols on different days after processing. (3) Results: the changes in the composition of the samples did not affect the evolution of the stability at the different measurement times and temperatures. Viscosity was affected by the compositional changes made in the PN samples, but no alterations due to time or temperature were observed. Density and pH remained stable, without significant changes due to time, storage temperature, or different composition. (4) Conclusion: all samples remained stable during the study period and did not undergo significant alterations due to compositional changes or different experimental conditions.

A study on the radiomic correlation between CBCT and pCT scans based on modified 3D-RUnet image segmentation.

The present study is based on evidence indicating a potential correlation between cone-beam CT (CBCT) measurements of tumor size, shape, and the stage of locally advanced rectal cancer. To further investigate this relationship, the study quantitatively assesses the correlation between positioning CT (pCT) and CBCT in the radiomics features of these cancers, and examines their potential for substitution. In this study, 103 patients diagnosed with locally advanced rectal cancer and undergoing neoadjuvant chemoradiotherapy were selected as participants. Their CBCT and pCT images were used to divide the participants into two groups: a training set and a validation set, with a 7:3 ratio. An improved conventional 3D-RUNet (CLA-UNet) deep learning model was trained on the training set data and then applied to the validation set. The DSC, HD95 and ASSD were calculated for quantitative evaluation purposes. Then, radiomics features were extracted from 30 patients of the test set. The experiments demonstrate that, the modified model achieves an average DSC score 0.792 for pCT and 0.672 for CBCT scans. 1037 features were extracted from each patient's CBCT and pCT images, 73 image features were found to have R values greater than 0.9, including three features related to the staging and prognosis of rectal cancer. In this study, we proposed an automatic, fast, and consistent method for rectal cancer GTV segmentation for pCT and CBCT scans. The findings of radiomic results indicate that CBCT images have significant research value in the field of radiomics.

The evolution of positive allometry and exaggerated traits in a diverse beetle clade

Abstract Understanding variation in trait allometry and the drivers of variation in sexually selected traits is a major theme in evolutionary biology. The static allometries of sexually selected traits are often positive due to disproportional investment by large individuals into trait size. Comparative studies of weapon allometry are rare, and typically focus on variation along a single dimension (e.g. length), despite weapons often diverging dramatically in shape. Furthermore, studies predominantly focus on groups where weapons have evolved as novel structures (e.g. horns), despite most weapons arising from modifications of existing structures. We test the hypothesis that sexual selection drives variation in static allometry using a phylogenetic comparative approach with 59 brentine weevil species showing remarkable variation in trait exaggeration and sexual size dimorphism (SSD). Contrasting two dimensions of head size exaggeration (a sexually selected trait) and elytron length (a nonsexual trait), positive static allometry was common across both measures of male head size, but not females, and there was positive covariance between male head static allometry and SSD across species. Positive static allometry for male elytron length was less common, but did show positive covariance with SSD, possibly due to the function of wings as compensatory structures for bearing large weapons. Our findings support the hypothesis that sexual selection drives the evolution of allometries both within and among species, and that the modification of existing structures to be used as weapons does not limit the potential for positive static allometry. Read the free Plain Language Summary for this article on the Journal blog.

Characterization of the cryptic interspecific hybrid Lemna×mediterranea by an integrated approach provides new insights into duckweed diversity.

Lemnaceae taxonomy is challenged by the particular morphology of these tiny free-floating angiosperms. Although molecular taxonomy has helped clarify the phylogenetic history of this family, some inconsistency with morphological data leads to frequent misclassifications in the genus Lemna. Recently, the finding that Lemna japonica is an interspecific hybrid between Lemna minor and Lemna turionifera provided a clear explanation for one such taxonomic question. Here we demonstrated that L. minor is also capable of hybridizing with Lemna gibba, generating a cryptic but widespread taxon in the Mediterranean area. The nothotaxon Lemna ×mediterranea is described and compared with clones of the putative parental species L. minor and L. gibba. Genetic analysis by nuclear and plastid markers, as well as genome size measurement, revealed that two different cytotypes, diploid and triploid, originated by at least two independent hybridization events. Despite high overall similarity, morphometrical, physiological, and biochemical analyses showed an intermediate position of L. ×mediterranea between its parental species in most qualitative and quantitative characters, and also separation of the two hybrid cytotypes by some criteria. These data provide evidence that hybridization and polyploidization, driving forces of terrestrial plant evolution, contribute to duckweed genetic diversity and may have shaped the phylogenetic history of these mainly asexual, aquatic plants.

Homologous mutations in human β, embryonic, and perinatal muscle myosins have divergent effects on molecular power generation

Mutations at a highly conserved homologous residue in three closely related muscle myosins cause three distinct diseases involving muscle defects: R671C in β-cardiac myosin causes hypertrophic cardiomyopathy, R672C and R672H in embryonic skeletal myosin cause Freeman-Sheldon syndrome, and R674Q in perinatal skeletal myosin causes trismus-pseudocamptodactyly syndrome. It is not known whether their effects at the molecular level are similar to one another or correlate with disease phenotype and severity. To this end, we investigated the effects of the homologous mutations on key factors of molecular power production using recombinantly expressed human β, embryonic, and perinatal myosin subfragment-1. We found large effects in the developmental myosins but minimal effects in β myosin, and magnitude of changes correlated partially with clinical severity. The mutations in the developmental myosins dramatically decreased the step size and load-sensitive actin-detachment rate of single molecules measured by optical tweezers, in addition to decreasing overall enzymatic (ATPase) cycle rate. In contrast, the only measured effect of R671C in β myosin was a larger step size. Our measurements of step size and bound times predicted velocities consistent with those measured in an in vitro motility assay. Finally, molecular dynamics simulations predicted that the arginine to cysteine mutation in embryonic, but not β, myosin may reduce pre-powerstroke lever arm priming and ADP pocket opening, providing a possible structural mechanism consistent with the experimental observations. This paper presents direct comparisons of homologous mutations in several different myosin isoforms, whose divergent functional effects are a testament to myosin's highly allosteric nature.

A new automatic analysis tool for the determination of primary particle size from electron microscopy images: Application of the Cellpose software

To assess if an aggregated or an agglomerated material has to be considered as a nano-material, the size distribution of its constituent primary particles needs to be measured and the median diameter determined. To this end, the reference method uses either transmission or scanning electron microscopy to obtain images of the sample. The size of a significant number, usually a few hundreds, of primary particles are then measured manually. This task is highly time-consuming and subjected to operator bias. Some attempts have been made to automatize the size measurements. The algorithms and software available are generally successful at segmenting images of spherical objects with no or partial overlap but fail to properly segment irregular objects with strong overlap.The advances made with deep learning algorithms are promising to solve the segmentation issues encountered so far on complicated samples. In this paper, we tested the open source deep learning Cellpose software on transmission and scanning electron microscope images of different samples to retrieve the median diameter of the primary particles and compare the results with both the manual and theoretical values. This software was chosen for its ease of use, its free availability and the fact that it is pre-trained, allowing the use of a limited set of training images.For the samples used in this study, the quality of the segmentation was highly dependent on the number of objects on which the software model was trained, but a number of 500 to 1000 objects was enough to obtain good performances. The diameters measured using Cellpose segmentation are most of the time in agreement within 10% with the manual values. Interestingly, for scanning electron microscopy data, the results obtained with Cellpose are closer to the theoretical values when compared to the measurements obtained by hand, implying a smaller operator bias. If an uncertainty assessment still needs to be investigated for the diameters determined using Cellpose, this first attempt to use this software to segment electron microscope images of diverse samples is very promising and opens the possibility to fully automatize the identification of nano-structured materials.

Associations Between D3Cr Muscle Mass and Magnetic Resonance Thigh Muscle Volume With Strength, Power, Physical Performance, Fitness, and Limitations in Older Adults in the SOMMA Study.

How magnetic resonance (MR) derived thigh muscle volume and deuterated creatine dilution derived muscle mass (D3Cr muscle mass) differentially relate to strength, fitness, and other functions in older adults-and whether associations vary by sex-is not known. Men (N = 345) and women (N = 482) aged ≥70 years from the Study of Muscle, Mobility, and Aging completed leg extension strength (1-repetition max) and cardiopulmonary exercise testing to assess fitness (VO2peak). Correlations and adjusted regression models stratified by sex were used to assess the association between muscle size measures, study outcomes, and sex interactions. D3Cr muscle mass and MR thigh muscle volume were correlated (men: r = 0.62, women: r = 0.51, p < .001). Each standard deviation (SD) decrement in D3Cr muscle mass was associated with lower 1-repetition max strength (-14kg men, -4kg women, p < .001 for both; p-interaction = .003) and lower VO2peak (-79mL/min men, -30mL/min women, p < .001 for both, p-interaction: .016). Each SD decrement in MR thigh muscle volume was also associated with lower strength (-32kg men, -20kg women, p < .001 for both; p-interaction = .139) and lower VO2peak (-217mL/min men, -111mL/min women, p < .001 for both, p-interaction = .010). There were associations, though less consistent, between muscle size or mass with physical performance and function; associations varied by sex. Less muscle-measured by either D3Cr muscle mass or MR thigh muscle volume-was associated with lower strength and fitness. Varied associations by sex and assessment method suggest consideration be given to which measurement to use in future studies.