Density Measurements Research Articles

Red and Green LED Light Therapy: A Comparative Study in Androgenetic Alopecia.

Androgenetic alopecia (AGA) affects both men and women, characterized by progressive hair thinning. While current treatments like minoxidil and finasteride have efficacy limitations and side effects, low-level light therapy (LLLT) using red or near-infrared light has emerged as a promising alternative. Recent animal studies suggest potential benefits from green LED light, though human data are sparse. This study utilized an innovative LED helmet emitting red and green LED light on respective halves of the frontal scalp, delivering an energy density of 40 J/cm2 over 20 min. Clinical photography, physician evaluations on a 7-point scale, patient satisfaction, and measurements of hair density and hair diameter were employed. Data were analyzed using linear mixed-effects models, with significance set at p < 0.05. Seventeen participants (47.1% male, 52.9% female, average age 46.47 years) demonstrated notable improvements after 6 months of treatment. Red and green LEDs both significantly increased hair diameter, non-vellus hair density, and satisfaction scores. Notably, the red LED therapy resulted in a statistically significant decrease in vellus hair density and achieved a greater increase in hair diameter compared to the green LED therapy. Minimal adverse effects were reported, primarily consisting of tolerable scalp heat and mild redness. Both red and green LED therapies effectively enhanced hair growth, increasing density and thickness over 6 months. Red LED demonstrated superior improvements in specific measures. Consequently, both therapies present safe and viable alternatives for the management of AGA, expanding the repertoire of available treatment options.

Age estimation on post-mortem CT based on pelvic bone mineral density measurement and the state of putrefaction: a multivariate method.

Age-at-death estimation is an important issue in forensic medicine and anthropology. Initially, methods relied on morphological criteria, but with the advancement of radiology, new techniques such as morphological studies on multi-slice computed tomography (CT) reconstructions have emerged. Recent studies have shown promising results by investigating the correlation between age and bone mineral density (BMD). However, there is currently a lack of data on post-mortem CTs (PMCT) involving decomposed bodies, and limited information exists regarding changes in Hounsfield Units measurement in a post-mortem context. In light of these gaps, our study aimed to examine the relationship between age at death and pubic and ilium BMD using a sample of forensic bodies. We also aimed to determine whether post-mortem processes, such as putrefaction, could interfere with this correlation. Our retrospective analysis encompassed 637 PMCTs conducted before medicolegal autopsies at Tours University Hospital. Utilizing simple and multiple linear regressions, we investigated the correlation between age and pubic and ilium BMD, as well as the relationship between BMD and the radiologic alteration index (RAI), a scale employed to quantify the degree of putrefaction. Our findings indicate promising outcomes in age-at-death estimation using pubic and/or ilium BMD for bodies exhibiting no or moderate decomposition (RAI < 80), particularly among individuals under 40years old. However, for highly decomposed corpses (RAI ≥ 80), the presence of gas infiltration significantly influences the BMD of both the ilium and pubis. Consequently, we advocate for the incorporation of the RAI score into the age estimation equation to enhance the accuracy of our results in such cases. Further investigation involving a larger cohort of decomposed bodies could facilitate refinement and validation of our method within this specific population.

Influence of initial state and residual stresses on the modulus-density relationship of geomaterials: insights from multiple experimental setups

ABSTRACT Quality control in pavement construction traditionally relies on density measurements of geomaterials. With the introduction of modulus measurement methods, a shift has occurred due to the operational advantages of modulus-estimating devices over conventional density measurement techniques. Modulus-based methods also provide valuable information for the mechanistic-empirical (ME) design of pavement layers. However, a challenge emerges as a single modulus measurement does not directly correspond to a specific density measurement, leading to concerns about replacing density measurements in quality control processes. While it is generally accepted that a geomaterial's modulus primarily depends on its moisture content and density or void ratio, this study explores the complex relationship between modulus and density, particularly in field scenarios with consistent moisture content. Using three different laboratory-scale test set-ups, characterised by unique loading and boundary conditions, the research highlights the significant role of a geomaterial's initial state in obtaining accurate modulus estimates. The results reveal that identical densities can exhibit variations in modulus due to differences in initial densities and the development of residual lateral stresses. These variations in field conditions often stem from different paving or spreading techniques, emphasising the need for a comprehensive approach when establishing density-modulus correlations..

Impact of Carbon Source on Bacterial Cellulose Network Architecture and Prolonged Lidocaine Release

The biosynthesis of bacterial cellulose (BC) is significantly influenced by the type of carbon source available in the growth medium, which in turn dictates the material’s final properties. This study systematically investigates the effects of five carbon sources—raffinose (C18H32O16), sucrose (C12H22O11), glucose (C6H12O6), arabinose (C5H10O5), and glycerol (C3H8O3)—on BC production by Komagataeibacter hansenii. The varying molecular weights and structural characteristics of these carbon sources provide a framework for examining their influence on BC yield, fiber morphology, and network properties. BC production was monitored through daily measurements of optical density and pH levels in the fermentation media from day 1 to day 14, providing valuable insights into bacterial growth kinetics and cellulose synthesis rates. Scanning electron microscopy (SEM) was used to elucidate fibril diameter and pore size distribution. Wide-angle X-ray scattering (WAXS) provided a detailed assessment of crystallinity. Selected BC pellicles were further processed via freeze-drying to produce a foam-like material that maximally preserves the natural three-dimensional structure of BC, facilitating the incorporation and release of lidocaine hydrochloride (5%), a widely used local anesthetic. The lidocaine-loaded BC foams exhibited a sustained and controlled release profile over 14 days in simulated body fluid, highlighting the importance of the role of carbon source selection in shaping the BC network architecture and its impact on drug release profile. These results highlight the versatility and sustainability of BC as a platform for wound healing and drug delivery applications. The tunable properties of BC networks provide opportunities for optimizing therapeutic delivery and improving wound care outcomes, positioning BC as an effective material for enhanced wound management strategies.

A matter of measurement? Segregation and all-cause mortality in Sweden’s three metropolitan regions

Abstract Background Residential segregation can be operationalized and measured in many ways, along distinct dimensions. There are multiple mechanisms through which segregation and health mutually affect each other. Consequently, contextual health effects of segregation may vary depending on how segregation is measured. Methods We used longitudinal Swedish register data to compare associations between local measures of residential segregation (migrant density, migrant isolation, and the mutual information index) and all-cause mortality among the adult migrant and native-born populations in Sweden’s three largest metropolitan regions between 2004-2016. Results Among migrants, modest positive mortality gradients were observed across measures of migrant density and isolation, where a higher level of segregation was associated with higher risks of all-cause mortality (Q5 RR ranged from 1.08-1.20 across cities and measures). However, these effects were largely attenuated by individual-level socioeconomic factors, and reversed when further controlling for neighborhood economic deprivation (Q5 RR ranged from 0.74-0.87). Among the native-born, a positive gradient for mortality was found (Q5 RR ranged from 1.31-1.45), although this was reduced when accounting for neighborhood deprivation (Q5 RR ranged from 1.01 -1.11). For both migrants and the native-born, the mutual information index showed no clear association with mortality, although a mortality advantage is observed for migrants in the most segregated areas after individual and neighborhood level adjustments (Q5 RR ranged from 0.73-0.86). Conclusions Our findings show that the manner in which residential segregation is conceptualized and operationalized alters associations with health. However, individual and other contextual level confounders are important determinants which influences the patterns. Much of the negative health effects of residential segregation can be perceived through the lack of economic opportunities. Key messages • Associations between segregation and all-cause mortality depends on how segregation is conceptualized and measured. • The mortality disadvantage observed in local areas with high migrant density may be attributed to the lack of economic opportunities in the neighborhood.

Isolation and Identification of Multi-Traits PGPR for Sustainable Crop Productivity Under Salinity Stress

High salinity poses a significant threat to arable land globally and contributes to desertification. Growth-promoting rhizobacteria assist plants in mitigating abiotic stresses and enhancing crop productivity through the production of siderophores, exopolysaccharides (EPS), solubilisation of phosphate, indole-3-acetic acid (IAA), and other secondary metabolites. This study aimed to isolate, identify, and characterise bacteria that exhibit robust growth-promoting properties. A total of 64 bacterial isolates from the rhizosphere of Miscanthus sinensis were evaluated for plant growth-promoting (PGP) traits, including IAA, EPS, siderophores, and solubilisation of phosphate. Among them, five isolates were selected as plant growth-promoting rhizobacteria (PGPR) based on their PGP features and identified via 16S rRNA sequencing: Enterococcus mundtii strain INJ1 (OR122486), Lysinibacillus fusiformis strain INJ2 (OR122488), Lysinibacillus sphaericus strain MIIA20 (OR122490), Pseudomonas qingdaonensis strain BD1 (OR122487), and Pseudomonas qingdaonensis strain MIA20 (OR122489), all documented in NCBI GenBank. BD1 demonstrated a higher production of superoxide dismutase (SOD) (17.93 U/mg mL), catalase (CAT) (91.17 U/mg mL), and glutathione (GSH) (0.18 U/mg mL), along with higher concentrations of IAA (31.69 µg/mL) and salicylic acid (SA) (14.08 ng/mL). These isolates also produced significant quantities of amino and organic acids. BD1 exhibited superior PGP traits compared to other isolates. Furthermore, the NaCl tolerance of these bacterial isolates was assessed by measuring their growth at concentrations ranging from 0 to 200 mM at 8-h intervals. Optical density (OD) measurements indicated that BD1 and INJ2 displayed significant tolerance to salt stress. The utilisation of these isolates, which enhances plant growth and PGP traits under salt stress, may improve plant development under saline conditions.

Analysis of Bone Phenotype Differences in MEN1-Related and Sporadic Primary Hyperparathyroidism Using 3D-DXA

Background: The rarity and variability of MEN1-related primary hyperparathyroidism (mPHPT) has led to contradictory data regarding the bone phenotype in this patient population. Methods: A single-center retrospective study was conducted among young age- and sex-matched patients with mPHPT and sporadic hyperparathyroidism (sPHPT). The main parameters of calcium–phosphorus metabolism, bone remodeling markers, and bone mineral density (BMD) measurements were obtained during the active phase of hyperparathyroidism before parathyroidectomy (PTE) and 1 year after. Trabecular Bone Score (TBS) and 3D-DXA analysis of the proximal femur were used to evaluate the differences in bone architecture disruption between groups. Results: Patients with mPHPT had significant lower preoperative BMD compared to sPHPT at lumbar spine—LS (p = 0.002); femur neck—FN (p = 0.001); and total hip—TH (p = 0.002). 3D-DXA analysis showed the prevalence of cortical rather than trabecular bone damage in mPHPT compared to sPHPT: cortical thickness (p &lt; 0.001); cortical surface BMD (p = 0.001); cortical volumetric BMD (p = 0.007); and trabecular volumetric BMD (p = 0.029). One year after, PTE DXA and 3D-DXA parameters were similar between groups, while 3D-visualisation showed more extensive regeneration in cortical sBMD and cortical thickness in mPHPT. Conclusions: mPHPT is associated with lower preoperative BMD values with predominant architecture disruption in the cortical bone. The absence of differences in DXA and 3D-DXA parameters 1 year after PTE between mPHPT/sPHPT combined with significantly lower BMD in mPHPT at the initial stage may indicate faster bone recovery after surgery in mPHPT than in sPHPT.

Data-driven discovery of chemotactic migration of bacteria via coordinate-invariant machine learning

BackgroundE. coli chemotactic motion in the presence of a chemonutrient field can be studied using wet laboratory experiments or macroscale-level partial differential equations (PDEs) (among others). Bridging experimental measurements and chemotactic Partial Differential Equations requires knowledge of the evolution of all underlying fields, initial and boundary conditions, and often necessitates strong assumptions. In this work, we propose machine learning approaches, along with ideas from the Whitney and Takens embedding theorems, to circumvent these challenges.ResultsMachine learning approaches for identifying underlying PDEs were (a) validated through the use of simulation data from established continuum models and (b) used to infer chemotactic PDEs from experimental data. Such data-driven models were surrogates either for the entire chemotactic PDE right-hand-side (black box models), or, in a more targeted fashion, just for the chemotactic term (gray box models). Furthermore, it was demonstrated that a short history of bacterial density may compensate for the missing measurements of the field of chemonutrient concentration. In fact, given reasonable conditions, such a short history of bacterial density measurements could even be used to infer chemonutrient concentration.ConclusionData-driven PDEs are an important modeling tool when studying Chemotaxis at the macroscale, as they can learn bacterial motility from various data sources, fidelities (here, computational models, experiments) or coordinate systems. The resulting data-driven PDEs can then be simulated to reproduce/predict computational or experimental bacterial density profile data independent of the coordinate system, approximate meaningful parameters or functional terms, and even possibly estimate the underlying (unmeasured) chemonutrient field evolution.

A Supervised Ml Algorithm for Detecting and Predicting Fraud Credit Card Transactions

A Credit card fraud presents an escalating threat in today's digital economy, leading to significant financial losses for consumers, businesses, and financial institutions. Traditional detection methods are increasingly inadequate due to the rise in online transactions and the evolving complexity of fraudulent activities. This research aims to create a reliable supervised machine learning model designed to detect and predict fraudulent credit card transactions in real-time. Our approach leverages advanced algorithms and extensive datasets to enhance transaction security, thereby mitigating financial risks. Current systems, like FICO's Fraud Detection System (FDS), utilize a range of supervised learning techniques, including Decision Trees, Random Forests, and Neural Networks. However, they face limitations, including data quality issues, high false positive rates, and the need for continuous retraining to adapt to evolving fraud patterns. To address these challenges, we propose an innovative anomaly detection method based on the Isolation Forest algorithm. Unlike traditional methods that rely on distance and density measures, Isolation Forests isolate anomalies by randomly selecting features and split values, making it more efficient in identifying fraudulent transactions, especially in imbalanced datasets. The proposed system boasts low linear time complexity and minimal memory requirements, enabling the construction of high-performing models even with large datasets. The research demonstrates that the Isolation Forest approach significantly outperforms traditional models in detecting credit card fraud, offering a promising solution for enhancing security in the financial ecosystem.

Orthogonality catastrophe beyond bosonization from post-selection

We show that the dynamics induced by post-selected measurements can serve as a controlled route to access physical processes beyond the boundaries of Luttinger liquid physics. We consider a one-dimensional fermionic wire whose dynamics results from a sequence of weak measurements of the fermionic density at a given site, interspersed with unitary hopping dynamics. This realizes a non-Hermitian variant of the celebrated instance of a local scatterer in a fermionic system and its ensuing orthogonality catastrophe. We observe a distinct crossover in the system's time evolution as a function of the fermion density. In the high-density regime, reminiscent of the Hermitian case, a bosonized version of the model properly describes the dynamics while, as we delve into the low-density regime, the validity of bosonization breaks down, giving rise to irreversible behavior. Notably, this crossover from reversible to irreversible dynamics is nonperturbative in the measurement rate and can manifest itself even with relatively shallow measurement rates, provided that the system's density remains below the crossover threshold. Our results render a conceptually transparent model for exploring nonperturbative effects beyond bosonization, which could be used as a stepping stone to explore novel routes for the control of nonlinear dynamics in low-dimensional quantum systems. Published by the American Physical Society 2024

Automated deep learning-based bone mineral density assessment for opportunistic osteoporosis screening using various CT protocols with multi-vendor scanners

This retrospective study examined the diagnostic efficacy of automated deep learning-based bone mineral density (DL-BMD) measurements for osteoporosis screening using 422 CT datasets from four vendors in two medical centers, encompassing 159 chest, 156 abdominal, and 107 lumbar spine datasets. DL-BMD values on L1 and L2 vertebral bodies were compared with manual BMD (m-BMD) measurements using Pearson’s correlation and intraclass correlation coefficients. Strong agreement was found between m-BMD and DL-BMD in total CT scans (r = 0.953, p < 0.001). The diagnostic performance of DL-BMD was assessed using receiver operating characteristic analysis for osteoporosis and low BMD by dual-energy x-ray absorptiometry (DXA) and m-BMD. Compared to DXA, DL-BMD demonstrated an AUC of 0.790 (95% CI 0.733–0.839) for low BMD and 0.769 (95% CI 0.710–0.820) for osteoporosis, with sensitivity, specificity, and accuracy of 80.8% (95% CI 74.2–86.3%), 56.3% (95% CI 43.4–68.6%), and 74.3% (95% CI 68.3–79.7%) for low BMD and 65.4% (95% CI 50.9–78.0%), 70.9% (95% CI 63.8–77.3%), and 69.7% (95% CI 63.5–75.4%) for osteoporosis, respectively. Compared to m-BMD, DL-BMD showed an AUC of 0.983 (95% CI 0.973–0.993) for low BMD and 0.972 (95% CI 0.958–0.987) for osteoporosis, with sensitivity, specificity, and accuracy of 97.3% (95% CI 94.5–98.9%), 85.2% (95% CI 78.8–90.3%), and 92.7% (95% CI 89.7–95.0%) for low BMD and 94.4% (95% CI 88.3–97.9%), 89.5% (95% CI 85.6–92.7%), and 90.8% (95% CI 87.6–93.4%) for osteoporosis, respectively. The DL-based method can provide accurate and reliable BMD assessments across diverse CT protocols and scanners.

Impact of carbon sources in airport de-icing compounds on the growth of Sphaerotilus natans

Airport de-icing has been linked with the growth of undesirable river biofilms (URBs, formerly “sewage fungus”), a manifestation of organic pollution causing long-term ecological damage to watercourses. URBs are a polymicrobial community, with one key taxon standing out in literature: Sphaerotilus natans, a filamentous bacterium also found in sewage treatment and activated sludges. An industry often implicated in causing URBs is airport de-icing, with large biofilms often developing downstream of airport discharges in winter months. However, it is not yet clear which de-icers may cause URBs and how they influence growth. Therefore, specific objectives were to (i) determine which freeze-point depressants (FPDs) can be utilized by S. natans; (ii) examine differences in the growth kinetics between FPDs; and (iii) compare pure-FPDs to commercial airport de-icers (CADs) as carbon sources, to determine impacts of additives. This study employed a turbidimetric micro-batch culture design to conduct microbial growth experiments, using S. natans and a minimal medium supplemented with airport de-icer as the carbon source. Equimolar carbon concentrations were used to compare the effects of common FPDs and CADs – each containing a specific FPD. Growth was assessed via optical density (OD600) measurements, from which time-to-detection, maximum rate of change, and maximum optical density were derived and kinetics inferred. S. natans was found to grow effectively on all FPDs tested, although the microbial yield was heavily dependent on the carbon concentration for all FPDs and CADs. Sodium acetate generated the quickest growth, with the lowest TTD (lag-time) for all but the lowest concentrations tested. Propylene glycol produced the greatest maxOD (total growth), whereas ethylene glycol had a higher limiting concentration for maxROC (growth rate). The mixture of compounds and additives in commercial products did not significantly impact the growth of S. natans. This research provides evidence from controlled laboratory experiments that airport de-icers support the growth of S. natans. The differences in growth kinetics observed for the FPDs and CADs could inform improved mitigation or treatment to reduce the incidence and ecological impacts of URBs.

A new expression for fluid factor using AVO intercept and gradient: Theory and application on gas sand reservoirs from offshore Australia

Numerous amplitude variation with offset (AVO) fluid indicators have proven to be sensitive to the presence of hydrocarbons. Mathematically, these fluid indicators measure the deviation of seismic responses of hydrocarbon reservoirs from their background in a specific domain. We develop a new expression for the fluid factor commonly used in AVO analysis and interpretation. The expression is a function of the common AVO intercept and gradient, along with a weighting coefficient that suppresses the contribution of lithology and other factors unrelated to fluid content. The coefficient also assists in calibrating the fluid factor to the local geology. We compare the performance of our fluid factor with existing fluid factors. All the fluid factors are tested on a worldwide collection of P- and S-wave velocity and density measurements. The testing is followed by application on synthetic data before applying the attribute on real data from the Northwest Shelf of Australia. In the latter application on the real data, we use two wells for calibration purposes, and the third as a blind well. Our fluid factor demonstrated high capability in detecting the targeted gas zones at the three well locations and identifying new prospective zones.

‘Low-Plane’ Fractures of the Distal Humerus in Elderly Patients with Osteoporosis Show High Postoperative Complication Rates

Background: This study aimed to investigate the fracture patterns and complexity of distal humerus fractures with high-resolution computed tomography (CT) as a function of Dual-Energy X-ray absorptiometry (DXA)-derived bone marrow density (BMD) measurements in an elderly patient cohort. Methods: A retrospective chart review was conducted on patient data collected at a Level I trauma center between January 2007 and January 2022. Inclusion criteria comprised patients aged ≥40 years with a confirmed distal humerus fracture as demonstrated by CT. Additionally, patients were included if they underwent DXA. Patient demographics and detailed information regarding the surgical treatment and trauma mechanism were retrieved from the institutional databank. Fractures were classified as either ‘low-plane’ distal humeral fractures or ‘non-low-plane’ distal humerus fractures. Furthermore, the fracture patterns were classified according to established classification systems. Intra- and postoperative complication and revision rates were analyzed. Results: A total of 41 patients (30 women; mean age 74 ± 13 years) were enrolled. Low-energy trauma was sustained by 68% of the patients. The remaining 32% of the fractures involved medium-energy trauma. A total of 62% of the patients underwent primary osteosynthesis, while 30% of patients were initially treated with an external fixator. ORIF was performed in 89% of cases and, in the majority, double-plate osteosynthesis was used (76%). An olecranon osteotomy was performed in 30% of cases. A total of 5% of cases received total elbow arthroplasty, and 10% of cases were treated conservatively. A total of 61% of patients had osteoporosis, 24% of patients had osteopenia, and 15% of patients had a normal BMD with an overall mean T-score of −2.4. Most of the fractures were complex (including 61% Type C fractures). A total of 66% of cases were considered as ‘low-plane’ fractures. Postoperative complications occurred in 11% of patients (64% of cases among ‘low-plane’ fractures). Revision surgery was required in 20% of cases. Conclusions: The consecutive series of patients showed a high incidence of ‘low-plane’ fractures. However, no statistical significance was found between the BMD and fracture complexity. The very distal ‘low-plane’ fractures showed a high complication rate, which was aggravated by osteoporotic bone conditions. These findings highlight the need for future research with larger patient samples to better understand the relationship between the BMD, fracture complexity, and outcomes in patients with ‘low-plane’ fractures in order to reduce complications and improve clinical outcomes.

Limiting regimes of turbulent horizontal convection. Part 2. Large Prandtl numbers

Horizontal convection at large Rayleigh and Prandtl numbers is studied experimentally in a regime up to seven orders of magnitude larger in terms of Rayleigh numbers than previously achieved. To reach Rayleigh numbers up to $10^{17}$ , the horizontal density gradient is generated using differential solutal convection by a differential input of salt and fresh water controlled by diffusion in a novel experiment in which the zero-net mass flux of water is ensured through permeable membranes. This set-up allows us to accurately measure the Nusselt number in solutal convection by carefully controlling the amount of salt water exchanged through the membranes. Combined measurements of density and velocity across more than five orders of magnitude in Rayleigh numbers show that the flow transitions from the Beardsley &amp; Festa (J. Phys. Oceanogr., vol. 2, issue 4, 1972, pp. 444–455), Shishkina &amp; Wagner (Phys. Rev. Lett., vol. 116, issue 2, 2016, 024302) regime to the Chiu-Webster et al. (J. Fluid Mech., vol. 611, 2008, pp. 395–426) regime and frames the present results within the scope of Shishkina et al. (Geophys. Res. Lett., vol. 43, issue 3, 2016, pp. 1219–1225), and the theory of Part 1 (Passaggia &amp; Scotti, vol. 997, 2024, J. Fluid Mech., A5). In particular, we show that, even for large Prandtl numbers, the circulation eventually clusters underneath the forcing horizontal boundary, leaving a stratified core without motion. Finally, the previous regime diagrams (Hughes &amp; Griffiths, Annu. Rev. Fluid Mech., vol. 40, 2008, pp. 185–208; Shishkina et al., Geophys. Res. Lett., vol. 43, issue 3, 2016, pp. 1219–1225) are extended by combining the present results at high Prandtl numbers, the results at low Prandtl numbers of Part 1, together with previous results from the literature. This work sets a new picture of the transition landscape of horizontal convection over six orders of magnitude in Prandtl number and sixteen orders of magnitude in Rayleigh number.

Theoretical development and validation of asphalt concrete density measurement using non-contact interdigital coplanar capacitive sensor

Asphalt concrete (AC) density serves as a critical criterion for quality control and quality assurance in asphalt pavement construction. Current non-destructive testing (NDT) approaches have shown potential for AC density measurement, but they present disadvantages such as inefficiency and unstable accuracy. This paper developed a novel NDT approach for AC density measurement based on non-contact interdigital coplanar capacitive sensor (ICCS). The feasibility of this approach was evaluated through both numerical and experimental validations. Firstly, the theoretical model of non-contact ICCS for AC density measurement was established based on conformal mapping technique, partial capacitance technique, and dielectric mixing model. Secondly, numerical simulations were performed to validate the developed theoretical model under two scenarios. Thirdly, laboratory experiments were conducted to measure capacitance data and predict density for three common types of ACs. Finally, the error of non-contact ICCS was discussed and compared with that of other NDT instruments. The results indicated that the developed theoretical model could establish the relationship between AC density and capacitance value, which provided the basis for AC density measurement using non-contact ICCS. It was also observed that the capacitance data obtained by the proposed model closely matched those computed by numerical simulations. The maximum errors between theoretical and numerical data were 4.10% and 1.08% for two cases respectively, which proved the feasibility of the theoretical model. Furthermore, experimental results indicated that the capacitance value of AC specimens increased by about 1 pF as the rolling time increases due to a decrease in the volume of air in AC, which reaffirms the validity of AC density measurement using non-contact ICCS. Additionally, the non-contact ICCS demonstrated excellent accuracy with a maximum error of 6.69%, which is comparable to the current mainstream NDT approaches. And it has the advantages of lower cost, simpler data processing and higher efficiency. The findings of this paper offer a new and reliable method and tool for non-destructive and large-scale AC density measurement.

Acute transcutaneous auricular vagus nerve stimulation modulates presynaptic SV2A density in healthy rat brain: An invivo microPET study.

Vagus nerve stimulation (VNS) is the subject of exploration as an adjunct treatment for neurological disorders such as epilepsy, chronic migraine, pain, and depression. A non-invasive form of VNS is transcutaneous auricular VNS (taVNS). Combining animal models and positron emission tomography (PET) may lead to a better understanding of the elusive mechanisms of taVNS. We evaluated the acute effect of electrical stimulation of the left vagus nerve via the ear on brain synaptic vesicle glycoprotein 2A (SV2A) as a measure of presynaptic density and glucose metabolism in naïve rats. Female Sprague-Dawley rats were imaged with [11C]UCB-J (n = 11) or [18F]fluorodeoxyglucose ([18F]FDG) PET (n = 13) on two separate days, (1) at baseline, and (2) after acute unilateral left taVNS or sham stimulation (30 min). We calculated the regional volume of distribution (VT) for [11C]UCB-J and standard uptake values (SUV) for [18F]FDG. We observed regional reductions of [11C]UCB-J binding in response to taVNS ranging from 36% to 59%. The changes in taVNS compared to baseline were significantly larger than those induced by sham stimulation. The differences were observed bilaterally in the frontal cortex, striatum, and midbrain. The [18F]FDG PET uptake remained unchanged following acute taVNS or sham stimulation compared to baseline values. This proof-of-concept study shows for the first time that acute taVNS for 30 min can modulate invivo synaptic SV2A density in cortical and subcortical regions of healthy rats. Preclinical disease models and PET ligands of different targets can be a powerful combination to assess the therapeutic potential of taVNS.

Transcriptome dynamics in developing leaves from C3 and C4 Flaveria species.

C4 species have evolved more than 60 times independently from C3 ancestors. This multiple and parallel evolution of the complex C4 trait suggests common underlying evolutionary mechanisms, which could be identified by comparative analysis of closely related C3 and C4 species. Efficient C4 function depends on a distinctive leaf anatomy that is characterised by enlarged, chloroplast-rich bundle sheath cells and narrow vein spacing. To elucidate the molecular mechanisms that generate the Kranz anatomy, we analysed a developmental series of leaves from the C4 plant Flaveria bidentis and the closely related C3 species Flaveria robusta by comparing anatomies and transcriptomes. Vascular density measurements of all nine leaf developmental stages identified three leaf anatomical zones whose proportions vary with respect to the developmental stage. We then deconvoluted the transcriptome datasets using non-negative matrix factorisation, which identified four distinct transcriptome patterns in the growing leaves of both species. By integrating the leaf anatomy and transcriptome data, we were able to correlate the different transcriptional profiles with different developmental zones in the leaves. These comparisons revealed an important role for auxin metabolism, in particular auxin homeostasis (conjugation and deconjugation), in establishing the high vein density typical of C4 species.

Evaluation of hard tissue characteristics and calcifications in pulp tissue of hypomineralized permanent molars using micro-computed tomography

ObjectivesTo determine and compare pulp volume, dentin mineral density, presence of microcracks, pulp stones, and accessory canals, as well as their localizations in root regions for hypomineralized and healthy teeth. DesignThis study included 60 extracted permanent molar teeth, categorized into hypomineralized and healthy groups (n = 30 each). The hypomineralized group comprised molar teeth with limited white, yellow, or brown opacities, post-eruptive breakdown, or extensive restoration or crown damage. The healthy group included caries-free molar teeth without these characteristics. Using 3D micro-computed tomography images pulp volume, dentin mineral density, and the presence and locations of microcracks, pulp stones, and accessory canals were determined for each group. Statistical analyses were conducted using Independent T-test and Chi-square test, with significance set at p < 0.05. ResultsThere was no statistically significant difference between the groups regarding pulp volume and microcracks (p ≥ 0.05). The number of accessory canals was significantly greater in the cervical (p = 0.011; p < 0.05) and middle (p = 0.010; p < 0.05) regions of the hypomineralized teeth than healthy teeth. Dentin mineral density was statistically higher in the apical, middle, and cervical root regions (p < 0.001; p < 0.05); however, the number of pulp stones was found to be greater in the cervical regions of healthy teeth compared with those with hypomineralization (p = 0.026; p < 0.05). ConclusionThere were lower dentin mineral density measurements, a decreased number of pulp stones in the cervical region, and a greater number of accessory canals in the middle and cervical regions of hypomineralized teeth compared with healthy teeth.

Evaluation of Mechanical Properties of ABS-like Resin for Stereolithography Versus ABS for Fused Deposition Modeling in Three-Dimensional Printing Applications for Odontology.

This study investigates the differences in mechanical properties between acrylonitrile butadiene styrene (ABS) samples produced using fused deposition modeling (FDM) and stereolithography (SLA) using ABS filaments and ABS-like resin, respectively. The central question is to determine how these distinct printing techniques affect the properties of ABS and ABS-like resin and which method delivers superior performance for specific applications, particularly in dental treatments. The evaluation methods used in this study included Shore D hardness, accelerated aging, tensile testing, Izod impact testing, flexural resistance measured by a 3-point bending test, and compression testing. Poisson's ratio was also assessed, along with microstructure characterization, density measurement, confocal microscopy, dilatometry, wettability, Fourier-transform infrared spectroscopy (FTIR), and nanoindentation. It was concluded that ABS has the same hardness in both manufacturing methods; however, the FDM process results in significantly superior mechanical properties compared to SLA. Microscopy demonstrates a more accurate sample geometry when fabricated with SLA. It is also concluded that printable ABS is suitable for applications in dentistry to fabricate models and surgical guides using the SLA and FDM methods, as well as facial protectors for sports using the FDM method.