Texture Analysis Research Articles

Quantification of Muscle Wasting in CKD by Texture Analysis on 1H-Magnetic Resonance Images

Quantification of Muscle Wasting in CKD by Texture Analysis on 1H-Magnetic Resonance Images

A comprehensive study of the effect of scanning strategy on IN939 fabricated by powder bed fusion-laser beam

This study provides a comprehensive investigation into the effects of different scanning strategies on the material properties of IN939 fabricated using the PBF-LB process. The scanning strategies examined included alternating bi-directional scanning with rotation angles of 0°, 45°, 67°, and 90° between adjacent layers (named as shown), as well as alternating chessboard scanning with rotation angles of 67° and 90° (named as Q67° and Q90°). The results revealed that the 45° and 67° samples had the highest relative density, while the 0° and Q67° samples showed the highest average porosity. Moreover, various types of cracks, including solidification, solid-state, and oxide-induced cracks, were observed. Among the bi-directional scan samples, the 0° sample displayed the most extensive cracking and the highest σmax residual stress values in both XZ and XY planes. Conversely, the 45° and 67° samples exhibited fewer cracks. Notably, the lowest σmax residual stress in the XZ planes among the bi-directional scan samples was observed in the 67° sample. Additionally, microstructural analyses indicated differences in grain size and morphology, among the samples. Texture analysis indicated that the 0° and 90° samples exhibited strong cube textures, whereas the texture intensity weakened for the 45° and 67° samples. Moreover, the alternating chessboard scanning strategy led to rougher surfaces (higher Sa and Sz values) compared to the alternating bi-directional scanning strategy, regardless of the rotation angles. Furthermore, the microhardness values among the samples showed minimal variance, ranging between 321 ± 14 HV and 356± 7 HV.

Application of validated size-exclusion chromatography method for physicochemical characterization of topical gel formulation of deferoxamine conjugated with PEGylated carbon nanoparticles

The focus of current research work was to develop and validate size-exclusion chromatography method and develop and evaluate gel formulation of deferoxamine conjugated with PEGylated carbon nanoparticles (DEF-PEG-CNP) for topical delivery. Size-exclusion chromatography-based method was validated as per ICH guidelines. Effect of Carbopol® 974P and Transcutol® on the nanoparticles’ permeation was studied by 3-level full factorial design of experiment. Gel formulations were characterized for viscosity, cohesive and adhesive force by texture analyzer, and drug permeation through pig ear and human skin. The analytical method was specific as no interference from solvent or excipients were observed and met preset criteria of validation with limit of quantification of 0.24 ± 0.00 μg/mL. The nanoparticles permeation, steady state flux, and retained drug were statistically (p < 0.05) affected by Carbopol® 974P and Transcutol® percentage in the gel formulations. The permeation, steady state flux, and retained nanoparticles from the gel formulations varied from 23.2 ± 2.5 % to 70.9 ± 113.3 %, 0.8 ± 0.3 to 6.6 ± 2.1 μg/cm2.h, and 5.6 ± 0.3 to 38.8 ± 8.8 µg/g, respectively. Permeation of the nanoparticles was 1.9 folds higher in pig skin compared to human skin. Immunofluorescence detected successful permeation of DEF-PEG-CNP particles into skin. In conclusion, the analytical method can quantify the nanoparticles from the gel formulation without interference, and gel formulation of the nanoparticles can permeate across the skin.

Systematic screening of particle engineered polymers for the preparation of multiparticulates embedded orally disintegrating tablets

This paper evaluated polymers' physical and mechanical properties to formulate modified-release multiparticulates to be embedded in orally disintegrating tablets (ODTs). The targeted polymer should have adequate elastic-plastic properties in a multiparticulate system during the manufacturing process, which is affected by its physical properties. The good mechanical properties of the multiparticulate system can effectively aid in retaining the shape of the particles from being affected under applied compression pressure during the formulation process and tablets preparations. Therefore, the formulation should have good mechanical attains. Five polymers (three natural and two synthetic), namely: sodium alginate, polyvinyl alcohol (PVA), methylcellulose (MC), polyacrylic acid (PAA) and Eudragit L100, were evaluated. Polymers in raw form or particle engineered using spray drying were characterised using different analysis techniques: differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), compacts tensile strength, texture analysis, particle size analysis and surface area analysis. The unprocessed PAA exhibited the lowest Young's modulus, measuring at 5.38 MPa, whereas MC displayed the highest value of 14.74 MPa. The polymers were subjected to spray drying at a concentration of 5% w/v. Data of the texture analysis revealed that Young's modulus increased for the spray-dried PAA powder, reaching 13.69 MPa. This suggests an enhanced polymer compressibility subsequent to the spray drying process. Eudragit L100 demonstrated an enhanced tabletability prolife after spray drying. SEM and surface area results showed a correlation with the mechanical findings. Plasticity and elasticity together provide strong, durable tablets with structural integrity. Achieving a balance between these properties is crucial for effective tabletability. The results of this study provide an insight into physical and mechanical properties and changes encountered upon spray drying. A balance between elastic- plastic properties is required for optimal multiparticulate development.

Tribological Analysis of Surface Textures in Porcelain Tiles for Enhancing Pedestrian Walkway Safety

Due to their durability and aesthetic appeal, porcelain tiles have become a staple in modern construction and interior design. However, the persistent challenge of mitigating slip hazards, particularly in moist conditions, remains a critical concern for pedestrian safety. This study investigates the slip resistance performance of porcelain tiles, focusing on the influence of varying surface textures. The study clarifies the intricate relationship between surface texture and slip resistance through comprehensive dynamic friction tests involving four distinct porcelain tile samples and three different shoe samples conducted under arid, damp, and lathered conditions. While dry conditions showcase robust traction, moist environments underscore the significance of surface textures in enhancing grip. Moreover, the study introduces an operational scale of surface roughness, delineating optimal texture boundaries for maximal slip resistance. The implications of these findings extend beyond mere material characterisation, offering actionable insights for architects, designers, and safety professionals to enhance pedestrian safety in diverse settings. By bridging the gap between material science and real-world safety concerns, this research paves the way for innovative porcelain tile designs that prioritise safety without compromising aesthetic appeal.

Enhanced Artificial Intelligence Methods for Liver Steatosis Assessment Using Machine Learning and Color Image Processing: Liver Color Project.

The use of livers with significant steatosis is associated with worse transplantation outcomes. Brain death donor liver acceptance is mostly based on subjective surgeon assessment of liver appearance, since steatotic livers acquire a yellowish tone. The aim of this study was to develop a rapid, robust, accurate, and cost-effective method to assess liver steatosis. From June 1, 2018, to November 30, 2023, photographs and tru-cut needle biopsies were taken from adult brain death donor livers at a single university hospital for the study. All the liver photographs were taken by smartphones then color calibrated, segmented, and divided into patches. Color and texture features were then extracted and used as input, and the machine learning method was applied. This is a collaborative project between Vall d'Hebron University Hospital and Barcelona MedTech, Pompeu Fabra University, and is referred to as LiverColor. A total of 192 livers (362 photographs and 7240 patches) were included. When setting a macrosteatosis threshold of 30%, the best results were obtained using the random forest classifier, achieving an AUROC = 0.74, with 85% accuracy. Machine learning coupled with liver texture and color analysis of photographs taken with smartphones provides excellent accuracy for determining liver steatosis.

Kidney medicine meets computer vision: a bibliometric analysis.

Rapid advances in computer vision (CV) have the potential to facilitate the examination, diagnosis, and treatment of diseases of the kidney. The bibliometric study aims to explore the research landscape and evolving research focus of the application of CV in kidney medicine research. The Web of Science Core Collection was utilized to identify publications related to the research or applications of CV technology in the field of kidney medicine from January 1, 1900, to December 31, 2022. We analyzed emerging research trends, highly influential publications and journals, prolific researchers, countries/regions, research institutions, co-authorship networks, and co-occurrence networks. Bibliographic information was analyzed and visualized using Python, Matplotlib, Seaborn, HistCite, and Vosviewer. There was an increasing trend in the number of publications on CV-based kidney medicine research. These publications mainly focused on medical image processing, surgical procedures, medical image analysis/diagnosis, as well as the application and innovation of CV technology in medical imaging. The United States is currently the leading country in terms of the quantities of published articles and international collaborations, followed by China. Deep learning-based segmentation and machine learning-based texture analysis are the most commonly used techniques in this field. Regarding research hotspot trends, CV algorithms are shifting toward artificial intelligence, and research objects are expanding to encompass a wider range of kidney-related objects, with data dimensions used in research transitioning from 2D to 3D while simultaneously incorporating more diverse data modalities. The present study provides a scientometric overview of the current progress in the research and application of CV technology in kidney medicine research. Through the use of bibliometric analysis and network visualization, we elucidate emerging trends, key sources, leading institutions, and popular topics. Our findings and analysis are expected to provide valuable insights for future research on the use of CV in kidney medicine research.

Sequential extraction of hawthorn pectin: An attempt to reveal their original mode of being in plants and functional properties

Hawthorn is rich in pectin, which is much higher than most cultivated fruits, but conventional extraction methods do not meet the requirements of low energy consumption and green production. Pectin in hawthorn is divided into soluble and insoluble parts, and with the ripening of hawthorn, the original pectin is converted into soluble pectin and pectic acid under the action of enzymes. Therefore, based on the characteristics of hawthorn pectin, this study sequentially extracted hawthorn pectin using water-soluble pectin (WSP) and hot acid-soluble pectin (HAP) method, verifying the feasibility of extracting hawthorn pectin with pure water at room temperature, and systematically analyzing and comparing the physicochemical properties and functional characteristics of the two methods. The combination of texture analysis and gel rheology revealed that WSP formed a more uniform and dense network structure during the gelation process. Additionally, microscopic observations and emulsification index results indicated that the emulsion prepared with WSP (WSE) had a smaller particle size and better stability. This indicates that hawthorn pectin is suitable for extraction with pure water at room temperature, which can maintain its good physical properties while reducing energy consumption, providing a new approach for the large-scale extraction of pectin in the food industry.

Testosterone hormone levels and breast muscle performance of Pelung chickens after zinc sulfate and synthetic testosterone supplementation

Background and Aim: Pelung chicken Gallus gallus gallus (Linnaeus, 1758) is a chicken endemic to Cianjur, West Java, Indonesia. This study aimed to determine the effects of zinc sulfate (ZnSO4) and synthetic testosterone supplementations for 56 days on testosterone hormone levels and breast muscle performance in Pelung chickens. Materials and Methods: This study used 12 Pelung chickens with three treatment groups (G) and four replications, namely, control (G0), ZnSO4 0.9 mg/kg (G1), and synthetic testosterone 3 mg/day (G2). Chickens were acclimatized for 7 days and then supplemented for 56 days. Drinking water and commercial standard feed were provided ad libitum. Blood was collected through the brachial vein for the analysis of testosterone levels using the enzyme-linked immunosorbent assay. The samples were collected every 14 days; on days 0, 14, 28, 42, and 56. Breast muscles were collected for texture analysis, and breast muscle preparations were made with hematoxylin-eosin staining to measure the fascicle area (FA), number of myofibers in one fascicle (NMOF), and myofiber area (MA). The collected data were analyzed using analysis of variance at a 95% confidence level with the help of Statistical Package for the Social Sciences v.29.0. Furthermore, principal component analysis (PCA) was performed with the help of Minitab v. 19. Results: Statistical analysis results on 56 days of testosterone level parameters showed that G2 was significantly different from all treatments (p &lt; 0.05). The results of statistical analysis on Pelung chicken breast muscle performance, especially hardness, chewiness, FA, NMOF, and MA, were significantly different (p &lt; 0.05) compared with the other treatments. The results of PCA showed that the testosterone level parameters were positively correlated with FA, NMOF, MA, hardness, and chewiness, whereas the fracture parameters were negatively correlated with all parameters except the springiness index and were significantly different between the G2 group and the other groups (p &lt; 0.05). Conclusion: It can be concluded that supplementing synthetic testosterone 3 mg/day body weight for 56 days can improve testosterone levels and breast muscle performance, especially hardness, chewiness, FA, NMOF, and MA in Pelung chickens. Keywords: muscle, Pelung chicken, performance, testosterone, texture.

Texture Analysis and Classification using Local Binary Patterns and Statistical Features

Texture analysis and classification are crucial in many applications such as medical applications, satellite imagery analysis, and so on. This paper presents a new technique that incorporates the LBP with the HOG to improve the texture analysis and classification. LBP is famous for finding out the local texture descriptors by comparing the pixel intensities it deals with and can challenge light variations and image transformations. On the other hand, there is HOG which emphasizes edge and gradient information to detect the orientation and shape of a texture in a given image. While LBP describes the local micro-patterns HOG gives the perspective of the global gradient orientation. The combined use of local and global texture information is helpful in the presented problem when prioritizing the recognition of complex texture patterns that cannot be deciphered by a single algorithm. To demonstrate the efficiency of the proposed hybrid method, several experiments are performed on several texture databases. According to the findings, the proposed LBP-HOG strategy proves more beneficial than basic LBP and HOG techniques concerning the classification rate and computing time. The combination method shows improved performance in terms of agreement with the reference of fine and coarse level of texture descriptions along with providing large-scale description of the texture which results in the improved discriminatory power of the texture classes.

Avocado peel by-product in cattle diets and supplementation with oregano oil and effects on production, carcass, and meat quality

Abstract The objective of this work was to evaluate the effects of including a commercial avocado peel meal (Avomel) by-product as a feed source supplemented with Lippia berlandieri Schauer oregano essential oil (OEO) in cattle diets. Eighteen 22-month-old male Charolais x Angus crossbred cattle (334.96 ± 27.48 kg) were randomly distributed in three experimental groups (n = 6): Control, cattle fed with the control diet without Avomel and without OEO; Avomel, cattle fed 10% of Avomel in the diet; and Avomel + OEO, cattle fed 10% Avomel and 600 mg/kg of OEO in the diet. The evaluated variables were bulls’ weight (BW), feed intake (FI), slaughter variables, carcass quality and the pH, water holding capacity (WHC), color and chemical composition of raw rib eye meat, as well as cooking loss (CL), shear force (SF), texture analysis and sensory evaluation of cooked meat. After 120 days of feeding, BW was highest (P &lt; 0.10) for Avomel and lowest (P &lt; 0.10) for Avomel + OEO. The Avomel + OEO group FI was low. Cattle slaughter variables, carcass quality variables, pH, and WHC did not show differences (P &gt; 0.05). Lightness was highest (P &lt; 0.05) for Avomel meat. Meat chemical composition was not affected (P &gt; 0.05). SF of meat was different (P &lt; 0.05) being highest for Avomel + OEO. On meat texture, springiness was different (P &lt; 0.05), i.e., meat treated with Avomel was highest, but no differences (P &gt; 0.05) were detected for hardness, adhesiveness, cohesiveness, gumminess, chewiness, and resilience. Odor, taste, softness, juiciness, and overall acceptability of cooked meat were not different (P &gt; 0.05), data not shown. The commercial by-product avocado peel meal supplemented with OEO could be used in cattle diets without adversely affecting productive performance, carcass traits, and meat quality.

Capacities of sorbents prepared by impregnation of inorganic carriers with PEI using different methods

The study presented here focused on the research of adsorbents for the separation of carbon dioxide from flue gas or other waste gases. Specifically, it focused on the possibility of eliminating the permanent problem with the insufficient resistance of inorganic adsorbents to unwanted – parasitic – adsorption of moisture from the processed gas. Based on the promising data published in recent papers regarding the wet impregnation of adsorbents with branched polyethyleneimine (PEI), four methods for the preparation of PEI-impregnated zeolite were tested. Penetration of the agent into the porous structure of the zeolite was achieved by: applying ultrasound, applying vacuum, combining vacuum and overpressure and boiling off the solvent without further operation. The raw zeolite was characterized by X-ray fluorescence spectrometry and X-ray diffractometry and also subjected to textural analysis. The characterization of the impregnated products mainly included thermogravimetric analysis, textural analysis and organic elemental analysis. In addition to gravimetric screening, the adsorption capacities of raw zeolite and impregnated products were primarily determined using a pressure flow-through apparatus with a fixed bed adsorber. The experimental conditions were determined to be close to real industrial installations: temperature during adsorption 20 and 40 °C, pressure during adsorption 600 kPa and 15% volume fraction of CO2 in the gas. Desorption was carried out by a combination of thermal desorption at 80 °C and vacuum. By reproducing the impregnation procedures from the literature, a PEI loading in the range of 4.1–23.7% was achieved, which is significantly lower than the literature sources state for the same preparation procedures. The measurement of textural properties verified that, depending on the value of PEI loading, there is a gradual reduction of the specific surface area, the total pore volume and the virtual disappearance of micropores and small mesopores. Specifically, at a PEI loading of 4%, the BET surface area decreased compared to the pristine zeolite from 29.4 to 2.9 m2 g–1 and at the same time the total pore volume decreased from 0.13 to 0.02 cm3 g–1, etc. The measurement of capacities did not confirm almost any of the results published in the literature. Without exception, the adsorption capacity decreased with the amount of PEI introduced into the zeolite particles. E.g. if a gas with 80% relative humidity and a content of 15% CO2 was used at a pressure of 600 kPa and a temperature of 40 °C, the capacity (by mass) decreased due to impregnation from 2.4% (for raw zeolite) to 0.8% for the sample with PEI mass fraction of 19%. Tests using dry gas resulted in even more marked deterioration. Thus, one can only partially agree with the literature data in the sense that humidity slightly compensates the negative effect of PEI on capacity. The effect, where the capacity increases with increasing temperature due to the replacement of physical CO2 adsorption by its chemisorption in the PEI layer, was also not confirmed. For example, for the above sample, humidity and pressure, the capacity was 0.9% at 20 °C. The impregnation procedure based on boiling off the solvent turned out to be completely unusable and, despite repeated rigorous attempts to reproduce it, did not lead to a product with a measurable capacity. The results of the study can be summarized in the following sentence. The problem is not that the experiments did not lead to a positive result, but above all the fundamental discrepancy between the published data and the attempts to reproduce them.

Influence of metal-phenolic networks on the properties of soy protein isolates gels

In this study, epigallocatechin-3-gallate (EGCG) was preliminarily coordinated with three types of metal ions to form metal-phenolic networks (MPNs) solutions, which were introduced into soy protein isolate (SPI) solutions to prepare SPI-MPNs composite hydrogels. This study aims to compare the effects of different types and varying addition levels of MPNs on the structure and mechanical properties of SPI gels. Dynamic light scattering and XPS results show that MPNs increase particle sizes in the composite system, and hydrogen bonding between MPNs and SPI causes smaller SPI molecules to aggregate into larger protein clusters. Low-field nuclear magnetic resonance analysis indicates that SPI-MPNs composite gels retain more water, with the majority of the water being successfully immobilized within the gel network. Rheological and textural analysis results indicate that the presence of MPNs can form a more rigid structure, significantly enhancing the mechanical properties of the composite gels. The group of gels with the highest strength exhibited a G’ value that was 2.1 times higher than that of the SPI gels, indicating the formation of a more stable three-dimensional network structure. These findings have significant potential implications for the application of SPI-MPNs composite gels in the food industry.

Soil texture analysis using controlled image processing

Soil texture analysis is crucial for crop selection, fertilizer recommendation, and production. Traditional soil testing in the lab using chemicals is highly time-consuming, expensive, and risky harmful chemicals; proper equipment and trained professionals are required to get the readings and to conduct the analysis. These issues can be resolved using image processing. In this study, we proposed a Blackbox prototype machine to take images in a controlled environment under the fixed intensity of light, distance, and standard dry conditions to analyze soil texture. This innovative machine, with its efficient and precise image processing capabilities, has the potential to revolutionize soil texture analysis. Also, we marked the center points of each type of soil texture as defined in the USDA texture triangle. Hundreds of soil samples were prepared for each type according to the center point's sand, silt, and clay ratio. The image processing-based model is trained for texture analysis. This research aims to reduce the soil texture analysis time and provide a system that can do extensive analyses automatically and with accuracy. The proposed Blackbox prototype machine has proven effective in providing a controlled environment for taking images. Also, the proposed model detects soil texture with a maximum accuracy of 99.5 %. A proposed model trained on the soil samples of different texture classes available in the USDA texture triangle accurately performed texture analysis. The results benefit the recommendation of appropriate crops and fertilizers based on a given soil sample in a very short time and cost-effectively.

Development of Artificial Intelligence-Based Programs for the Diagnosis of Myocarditis in COVID-19 Using Chest Computed Tomography Data»

It has been established that 7.2% of patients hospitalized with coronavirus disease (COVID-19) exhibit signs of heart disease, with 23% of these patients experiencing heart failure. Currently, there is a lack of data on chest computed tomography (CT) for diagnosing myocarditis associated with COVID-19. The aim. To justify the feasibility and develop classification models for diagnosing myocarditis in COVID-19 patients based on chest CT data processing. Materials and methods. A retrospective analysis of data from 140 COVID-19 patients was conducted. Chest CT scans were analyzed using DRAGONFLY software, with permission from Object Research Systems. The COVID-CT-MD database, which includes CT data from 169 confirmed cases of SARS-CoV-2 infection, was used to build classification models. The regions of interest were fragments of heart CT images. Texture analysis methods were employed to create diagnostic models. Results. It was shown that the average density of the myocardium of a patient with a confirmed diagnosis of SARS-CoV-2 infection according to the Hounsfield scale does not essentially differ from the densitometric indicators of a healthy person. Therefore, the research was focused on finding structural changes in CT images for their use in constructing diagnostic models. The use of different classification algorithms had little effect on classification accuracy, probably due to the informational content of the input data. However, the obtained accuracy of the diagnostic models is acceptable and allows them to be used to support medical decision-making regarding diagnosis and treatment. Conclusions. Using classic methods, myocarditis was diagnosed in 7.1% of patients with severe pneumonia caused by the coronavirus. The global data closely aligns with the results of our clinical studies. The obtained results allowed for assessing structural changes in the myocardium characteristic of the acute form of SARS-CoV-2 infection. The constructed classification models indicate that specific changes in the myocardium during the acute form of SARS-CoV-2 infection can be identified using CT. The highest diagnostic accuracy on test samples reached 74%. The implementation of the developed diagnostic programs based on texture analysis of CT data and artificial intelligence technologies enables the diagnosis of myocarditis and the assessment of long-term treatment efficiency. Creation of these diagnostic programs using artificial intelligence technologies significantly simplifies the work of radiologists and improves the efficiency of myocarditis diagnosis in patients with SARS-CoV-2 infection.

Diagnosis of odontogenic keratocysts and non-keratocysts using edge attention convolution neural network.

The study's objective was to develop an automated method for a histopathology recognition model for odontogenic keratocysts (OKC) and non-keratocyst (Non-KC) in jaw cyst sections stained with hematoxylin (H) and eosin (E) on a tiny bit of incisional biopsy prior to surgery. This hastens the speed and precision of diagnosis to patients. Also, navigates the clinicians with the therapeutic doctrine. To build such a system and to increase the accuracy of the existing models, the edge attention CNN model with Keras functional API was implemented which efficiently analyzes the texture information of the images. Approximately 2861 microscopic images at a 40X magnification were taken from 54 OKC, 23 Dentigerous cysts (DC), and 20 Radicular cysts. The model was trained using both RGB and canny edge-detected images. The model gave a good accuracy of 96.8%, which is suitable for real-time. Histopathological images are better analyzed through textural features. The proposed edge attention CNN highlights the edges, making texture analysis more precise. The suggested method will work for OKC and Non-KC diagnosis automation systems. The use of a whole slide imaging scanner has the potential to increase accuracy and remove human bias.

Urethral tissue characterization using multiparametric ultrasound imaging

A decrease in urethral closure pressure is one of the primary causes of stress urinary incontinence in women. Atrophy of the urethral muscles is a primary factor in the 15 % age-related decline in urethral closure pressure per decade. Incontinence not only affects the well-being of women but is also a leading cause of nursing home admission. The objective of this research was to develop a noninvasive test to assess urethral tissue microenvironmental changes using multiparametric ultrasound (mpUS) imaging technique. Transperineal B-scan ultrasound (US) data were captured using clinical scanners equipped with curvilinear or linear transducers. Imaging was performed on volunteers from our institution medical center (n = 15, 22 to 76 y.o.) during Valsalva maneuvers. After expert delineation of the region of interest in each frame, the central axis of the urethra was automatically defined to determine the angle between the urethra and the US beam for further analysis. By integrating angle-dependent backscatter with radiomic texture feature analysis, a mpUS technique was developed to identify biomarkers that reflect subtle microstructural changes expected within the urethral tissue. The process was repeated when the urethra and US beam were at a fixed angle. Texture selection was conducted for both angle-dependent and angle-independent results to remove redundancies. Ultimately, a distinct biomarker was derived using a random forest regression model to compute the urethra score based on features selected from both processes. Angle-dependent backscatter analysis shows that the calculated slope of US mean image intensity decreased by 0.89 (±0.31) % annually, consistent with the expected atrophic disorganization of urethral tissue structure and the associated reduction in urethral closure pressure with age. Additionally, textural analysis performed at a specific angle (i.e., 40 degrees) revealed changes in gray level nonuniformity, skewness, and correlation by 0.08 (±0.04) %, −2.16 (±1.14) %, and −0.32 (±0.35) % per year, respectively. The urethra score was ultimately determined by combining data selected from both angle-dependent and angle-independent analysis strategies using a random forest regression model with age, yielding an R2 value of 0.96 and a p-value less than 0.001. The proposed mpUS tissue characterization technique not only holds promise for guiding future urethral tissue characterization studies without the need for tissue biopsies or invasive functional testing but also aims to minimize observer-induced variability. By leveraging mpUS imaging strategies that account for angle dependence, it provides more accurate assessments. Notably, the urethra score, calculated from US images that reflect tissue microstructural changes, serves as a potential biomarker providing clinicians with deeper insight into urethral tissue function and may aid in diagnosing and managing related conditions while helping to determine the causes of incontinence.

MRI textural plasticity in limbic gray matter associated with clinical response to electroconvulsive therapy for psychosis.

Electroconvulsive therapy (ECT) is effective against treatment-resistant psychosis, but its mechanisms remain unclear. Conventional volumetry studies have revealed plasticity in limbic structures following ECT but with inconsistent clinical relevance, as they potentially overlook subtle histological alterations. Our study analyzed microstructural changes in limbic structures after ECT using MRI texture analysis and demonstrated a correlation with clinical response. 36 schizophrenia or schizoaffective patients treated with ECT and medication, 27 patients treated with medication only, and 70 healthy controls (HCs) were included in this study. Structural MRI data were acquired before and after ECT for the ECT group and at equivalent intervals for the medication-only group. The gray matter volume and MRI texture, calculated from the gray level size zone matrix (GLSZM), were extracted from limbic structures. After normalizing texture features to HC data, group-time interactions were estimated with repeated-measures mixed models. Repeated-measures correlations between clinical variables and texture were analyzed. Volumetric group-time interactions were observed in seven of fourteen limbic structures. Group-time interactions of the normalized GLSZM large area emphasis of the left hippocampus and the right amygdala reached statistical significance. Changes in these texture features were correlated with changes in psychotic symptoms in the ECT group but not in the medication-only group. These findings provide in vivo evidence that microstructural changes in key limbic structures, hypothetically reflected by MRI texture, are associated with clinical response to ECT for psychosis. These findings support the neuroplasticity hypothesis of ECT and highlight the hippocampus and amygdala as potential targets for neuromodulation in psychosis.

Production of AZ80 magnesium alloy wires: influence of heat treatment on microstructure and properties after twin-roll casting

AbstractTwin-roll casting (TRC) of magnesium sheets has already been analysed in numerous ways. The installation of a pilot plant for the twin-roll casting of magnesium wire at the Institute of Metal Forming, TU Bergakademie Freiberg, has opened up a further area for research. The principle of twin-roll casting of wire is comparable, although the microstructure development is different because of the resulting process-specific solidification and forming conditions. In this work, wire was produced for the first time from the magnesium alloy AZ80 using the TRC process. The microstructure consists of dendritic areas, twins, deformed areas and recrystallised grains. A non-basal texture with low intensity is developed, which is retained even after heat treatment. A temperature of 450 °C and a holding time of 1 h have been shown to be favourable for heat treatment to achieve a uniform grain structure. On the basis of the microstructure and texture analysis, the responsible recrystallisation mechanisms were discussed. Finally, mechanical properties at room temperature were presented and compared with extruded and cast material from the literature.

Energy-Efficient Geopolymer Composites Containing Phase-Change Materials-Comparison of Different Contents and Types.

The purpose of this study was to analyze the effects of phase-change components on the properties of geopolymer foams. Geopolymer foams are lightweight foamed geopolymers that are characterized by a high degree of porosity. Phase change materials, on the other hand, are compounds that, when added to a material, allow it to absorb, store, and then release large amounts of energy. Three types of PCMs, i.e., MikroCaps, GR42, and PX25, were introduced at 15% by weight. Geopolymer materials were produced based on silica fly ash, and hydrogen peroxide H2O2 was used to foam the geopolymer structure. The PCM geopolymer composites were cured at 60 °C. The produced materials were tested for physical, chemical, and thermal properties. The tests included oxide and mineral composition analysis of the base material, PCM particle size analysis, apparent density and porosity tests on the foams, water leachability tests, thermal tests (λ, Cv, Cp, α), and structural and textural analysis. The most relevant tests to confirm the performance of the phase-change materials were thermal tests. With the introduction of PCMs, volumetric heat capacity increased by as much as 41% and specific heat by 45%, and thermal diffusivity decreased by 23%. The results confirm the great potential of geopolymer composites as modern insulation materials for buildings and structures.