Early-stage Damage Research Articles

Numerical investigation of bandgap characteristics in integrated metallic metafilters for nonlinear guided wave applications

Guided waves propagating in nonlinear media, featuring second harmonic generation, represent a promising avenue for early-stage damage detection due to their high sensitivity and long-range propagation capabilities. However, nonlinear ultrasonic measurements are hindered by nonlinearities induced by the experimental system, necessitating careful calibrations that have restricted their application to laboratory settings. While several phononic crystal and metamaterial designs have been devised to enhance nonlinear-based ultrasonic testing, most are tailored for suppressing second harmonics within a frequency range of 100–300 kHz, primarily utilizing low-frequency excitation. In this paper, we propose a metallic ring-shaped metafilter designed to explore high-order bandgaps. To fully understand the bandgap characteristics, we begin by analyzing mode shapes, providing insights into the underlying wave mechanics. The efficacy of the designed filter is subsequently assessed through 3D time step elastodynamic simulations. In addition, this study underscores the significance of parameters such as the number of rings employed in the filter, signal duration, and bandgap width in optimizing its performance. Furthermore, the observed mode conversion phenomena from S0 to A0 guided wave modes underscore the filter’s capacity to influence guided wave propagation. The defect localization technique, based on the time difference of arrival of second-order wave modes, accurately predicts the defect location with an error margin of less than 0.2%. The present investigation showcases advancements in the sensitivity of nonlinear-based guided wave testing for characterizing microstructural changes, promising substantial potential for detecting incipient damage in practical structural health monitoring applications.

A multitask SHM algorithm to identify damage with random severity and location in IPE beams using EMI technique

Existing electromechanical impedance (EMI) damage identification algorithms often face challenges in terms of generalizability. This paper presents a robust algorithm that can simultaneously estimate the region and severity of damage with random damage scenarios across a surface and any severity, rather than being limited to specific points and severities. The host structure was an I-beam. Simulated damage was introduced as a subtle added mass to evaluate the algorithm's effectiveness in early-stage damage identification. Initially, various EMI tests with different damage specifications were conducted, and validated through numerical simulation. Damage-sensitive features were extracted and were input into three ML models: support vector machine, random forest, and multilayer perceptron. An ensemble learning approach was employed to combine the individual predictions from these models. The algorithm achieved classification accuracies of 97.3 % and 94.4 % on the validation and test sets, respectively, for identifying damaged regions. The algorithm also quantifies damage severity, achieving R-squared values of 92 % and 88 % on the validation and test sets, respectively.

Ratcheting damage evaluation based on critically refracted longitudinal wave combined with recurrence quantification analysis

Excessive accumulation of irreversible plastic strain in ratcheting poses a highly urgent need in early-stage damage evaluation. A strategy integrating critically refracted longitudinal (LCR) wave with recurrence quantification analysis (RQA) is proposed for iron. The signals at different damage stages are reconstructed in multidimensional phase space, and three features, recurrence rate RR, determinism DET, and entropy ENTR, are extracted. With increasing ratcheting cycle, the normalized ENTR difference, ENTRdif, exhibits an obvious increase within ∼1 % life followed by a stabilization trend, while the normalized RR difference, RRdif, fluctuates after an initial rapid rise. Both features show higher sensitivity to the amplitude-based indexes in the LCR wave and pulse-echo methods. The ultrasonic response mechanism is discussed with the rearrangement and mobility of dislocations confirmed by microstructural observation.

Fracture evolution characteristics of asphalt concrete using digital image correlation and acoustic emission techniques

The cracking damage of asphalt concrete significantly affects the service life of pavement. The objective of this research is to investigate fracture mechanisms of asphalt concrete by employing a synergistic approach combining digital image correlation (DIC) and acoustic emission (AE) techniques under three-point bending tests. Firstly, the crack tip opening displacement (CTOD) and the fracture process zone (FPZ) derived from DIC were utilized to classify fracture stages and describe the entire crack propagation process. Meanwhile, AE-related parameters were applied to detect the internal damage and fracture characteristics. Subsequently, the results from DIC and AE were utilized for comparative analysis to evaluate the cracking resistance of different materials. Finally, the fractal dimension and AE b-value were used to distinguish the characteristics of the critical damage conditions. The results indicated that both techniques are effective in classifying the fracture stage of asphalt concrete. DIC can visualize and analyze crack propagation processes and paths on concrete surfaces, especially at the stage of macrocrack initiation and propagation. AE allows for continuous monitoring and highly sensitive detection of early-stage damage inside concrete. The distinct advantages of DIC and AE result in different fracture stage identification results at the early stage, but consistent after the appearance of macrocracks. Based on the relationship between CTOD and AE cumulative count, a simple approach is proposed to directly evaluate the cracking resistance of different asphalt concretes. The formation of macrocracks in asphalt concrete can be reflected by a shift where the correlation dimension drops steeply to the minimum value, and a minimum inflection point in the AE b-value curve acts as a precursor of complete fracture. The research offers an in-depth insight of both surface deformation and internal damage, thus enhancing the understanding of crack growth behavior and fracture process in asphalt concrete.

Efficacy of PZT Sensors Network Different Configurations in Damage Detection of Fiber-Reinforced Concrete Prisms under Repeated Loading.

Real-time structural health monitoring (SHM) and accurate diagnosis of imminent damage are critical to ensure the structural safety of conventional reinforced concrete (RC) and fiber-reinforced concrete (FRC) structures. Implementations of a piezoelectric lead zirconate titanate (PZT) sensor network in the critical areas of structural members can identify the damage level. This study uses a recently developed PZT-enabled Electro-Mechanical Impedance (EMI)-based, real-time, wireless, and portable SHM and damage detection system in prismatic specimens subjected to flexural repeated loading plain concrete (PC) and FRC. Furthermore, this research examined the efficacy of the proposed SHM methodology for FRC cracking identification of the specimens at various loading levels with different sensor layouts. Additionally, damage quantification using values of statistical damage indices is included. For this reason, the well-known conventional static metric of the Root Mean Square Deviation (RMSD) and the Mean Absolute Percentage Deviation (MAPD) were used and compared. This paper addresses a reliable monitoring experimental methodology in FRC to diagnose damage and predict the forthcoming flexural failure at early damage stages, such as at the onset of cracking. Test results indicated that damage assessment is successfully achieved using RMSD and MAPD indices of a strategically placed network of PZT sensors. Furthermore, the Upper Control Limit (UCL) index was adopted as a threshold for further sifting the scalar damage indices. Additionally, the proposed PZT-enable SHM method for prompt damage level is first established, providing the relationship between the voltage frequency response of the 32 PZT sensors and the crack propagation of the FRC prisms due to the step-by-step increased imposed load. In conclusion, damage diagnosis through continuous monitoring of PZTs responses of FRC due to flexural loading is a quantitative, reliable, and promising application.

Investigation of the Zero-Frequency Component of Nonlinear Lamb Waves in a Symmetrical Undulated Plate.

When an ultrasonic pulse propagates in a thin plate, nonlinear Lamb waves with higher harmonics and a zero-frequency component (ZFC) will be generated because of the nonlinearity of materials. The ZFC, also known as the static displacement or static component, has its unique application on the evaluation of early-stage damages in the elastic symmetrical undulated plate. In this study, analysis of the excitation mechanism of the ZFC and the second harmonic component (SHC) was theoretically and numerically investigated, and the material early-stage damage of a symmetrical undulated was characterized by studying the propagation of nonlinear Lamb waves. Both the ZFC and SHC can be effectively employed in monitoring the material damages of the undulated plate in its early stage. However, several factors must be considered for the propagation of the SHC in an undulated plate because of the geometric curvature and interference between the second harmonics during propagation, preventing efficient application of this technique. If the fundamental wave can propagate in the plate regardless of the plate boundary conditions, an accumulative effect always exists for the ZFC in a thin plate, indicating that the ZFC is independent of the structural geometry. This study reveals that the ZFC-based inspection technique is more efficient and powerful in characterizing the damages of a symmetrical undulated plate in the early stage of service compared to the second harmonic method.

Urinary Tamm-Horsfall protein excretion is a potential early biomarker of renal distal tubular damage in canine leishmaniosis

This study evaluates distal tubular damage in early stages of renal disease in dogs with naturally acquired leishmaniosis. Pherograms of urinary proteins separated in vertical electrophoresis system (SDS-PAGE) were evaluated. Peptide fingerprint and fragmentation (MALDI-TOF TOF) identified bands located at 100 and 60 kDa as Tamm-Horsfall protein (THP) and albumin, respectively. The variables examined were: urine protein to creatinine ratio (UPC), total number of bands, quantification of THP urinary excretion through the optical density (OD %) of bands located at 100 kDa, blood creatinine, and urine specific gravity (USG). Positive correlation was found between UPC and the number of bands (ρ = 0.75849, P = <0.0001). Negative correlation was identified between UPC and OD % of 100 kDa bands (ρ = −0.85332, P = <0.0001), and the number of bands and OD % of 100 kDa bands (ρ = −0.74479, P = <0.0001). The area under the ROC curve was 0.991 (95 % CI, 0.976–1). The optimal cut-off UPC that better discriminated between urines with high or low OD% of THP was 0.46 with 92.6 % sensitivity and 96.2 % specificity. Our findings indicate that non azotemic dogs with borderline proteinuria might excrete low amount of THP, which could suggest tubular damage in early stages of chronic kidney disease.

Vibration-based Damage Diagnosis for a Population of Composite Structures Under Uncertainty via Hyper-Sphere and Transfer Component Analysis Based Methods

The problem of vibration-based damage diagnosis, including the detection and type characterization of damages in a population of nominally identical composite structures under operational uncertainty is investigated. This is an important problem for various types of fleets, such as aircraft, drones, fixed wing UAVs and others, which becomes highly challenging if the variability in the composite materials and the manufacturing of the population is significant, while the diagnosis of early-stage damages is pursued. Such a population of 27 composite coupons subjecting to operating variability due to alterations in the temperature, the excitation and the experimental setup is considered in this study. Furthermore, early-stage delamination and impact-induced damages are implemented in 10 of the coupons. Damage diagnosis is herein attempted via two data-driven methods that may account for various types of uncertainty, which are founded on a number of stochastic Multiple-Input Single-Output Transmittance Function AutoRegressive with eXogenous pseudo-eXcitation (MISO-TF-ARX) models. The first employs Hyper Spheres for the representation of the healthy subspace under uncertainty using the parameters of the MISO-TF-ARX models and thus abbreviated as HS-MISO-TF, while the other is based on the Transfer Component Analysis of these parameters, abbreviated as TCA-MISO-TF. The methods’ damage diagnosis performance is experimentally assessed using the above composite coupons and a high number of 7 500 inspection test cases for damage detection, whereas damage characterization is based on 450 test cases. The damage detection and characterization results are presented through Receiver Operating Characteristics curves and confusion matrices, respectively. The obtained results indicate adequate damage detection with the HS-MISO-TF method to achieve 82.1% correct detection for 5% of false alarms, with the TCA-MISO-TF following with 76.4% correct detection. Damage characterization is remarkable with the HS-MISO-TF to correctly characterizing the considered damage type for the 100% of the considered test cases and the TCA-MISO-TF following with 92.2%.

Full life-cycle vibration-based monitoring of a full-scale masonry arch bridge with increasing levels of damage

Structural health monitoring (SHM) is of great significance to maintain the safe operation of infrastructure, particularly for historic structures such as masonry arch bridges, as their material properties are deteriorating under effects such as climate change, but the demands of modern transport systems increase significantly. Vibration-based SHM has become a prevalent method for assessing the vulnerability of masonry arch bridges. However, one of the most critical limitations lies in the inability of correlate bridge’s damage accumulation with the variation trends in its modal parameters. To address this issue, in the present study, full life-cycle vibration-based monitoring was conducted on a full-scale masonry arch bridge, progressing from an undamaged state to failure under laboratory conditions. Accumulated damage was induced by applying point loads with increasing magnitudes until the bridge failed. Vibration data, collected after each loading test, were analysed utilizing the stochastic subspace identification (SSI) method, and frequency and damping ratio for the first five modes were identified. The results demonstrated that the first-order frequency had the most pronounced correlation with the stiffness degradation and the damage accumulation in the masonry arch bridge. The evolution of early-stage damage, the formation of the first hinge, and the activation of a four-hinge mechanism were successfully captured through the frequency degradation. The findings of the study may provide valuable insights into the damage assessment of historic masonry arch bridge infrastructures.

Detecting of Barely Visible Impact Damage on Carbon Fiber Reinforced Polymer Using Diffusion Ultrasonic Improved by Time-Frequency Domain Disturbance Sensitive Zone.

Based on the decorrelation calculation of diffusion ultrasound in time-frequency domain, this paper discusses the repeatability and potential significance of Disturbance Sensitive Zone (DSZ) in time-frequency domain. The experimental study of Barely Visible Impact Damage (BVID) on Carbon Fiber Reinforced Polymer (CFRP) is carried out. The decorrelation coefficients of time, frequency, and time-frequency domains and DSZ are calculated and compared. It has been observed that the sensitivity of the scattered wave disturbance caused by impact damage is non-uniformly distributed in both the time and frequency domains. This is evident from the non-uniform distribution of the decorrelation coefficient in time-domain and frequency-domain decorrelation calculations. Further, the decorrelation calculation in the time-frequency domain can show the distribution of the sensitivity of the scattered wave disturbance in the time domain and frequency domain. The decorrelation coefficients in time, frequency, and time-frequency domains increase monotonically with the number of impacts. In addition, in the time-frequency domain decorrelation calculation results, stable and repetitive DSZ are observed, which means that the specific frequency component of the scattered wave is extremely sensitive to the damage evolution of the impact region at a specific time. Finally, the DSZ obtained from the first 15 impacts is used to improve the decorrelation calculation in the 16-th to 20-th impact. The results show that the increment rate of the improved decorrelation coefficient is 10.22%. This study reveals that the diffusion ultrasonic decorrelation calculation improved by DSZ makes it feasible to evaluate early-stage damage caused by BVID.

A grid-based methodology for the assessment of time-dependent building damage at large scale

Leakage into underground constructions can result in time-dependent settlements in soft clays. In urban areas with spatial variability in geologic stratification, groundwater conditions and soil compressibility, differential settlements may occur, causing damage to buildings. Current methods for damage assessment that rely on 1D formulations for settlement prediction are not representative for drawdown-induced settlements in heterogeneous environments. Thus, in this paper, we propose a stand-alone approach to integrating spatially distributed, non-Gaussian settlement data into early-stage building damage assessments at a district scale. Deformations computed using a 2D coupled hydro-mechanical finite element model with an advanced constitutive model were then employed to get the time-dependent settlements computed as a 3D grid (along x- and y-directions) over a large area. Building damage was then calculated from these green-field simulations with typically used damage parameters for each building-specific settlement profile and comparing these with damage criteria. The approach was applied to 215 buildings in central Gothenburg, Sweden by simulating scenarios of 10 kPa and 40 kPa pore pressure drawdown in the lower (confined) aquifer. Several scenarios were studied, and the correlation between damage parameters and damage criteria was assessed. Finally, a sensitivity study on grid resolution was performed, as well as a validation against observed damage data. The proposed methodology offers an effective way for early-stage damage assessments at a large area for non-Gaussian settlements so that further investigations and mitigation measures can be targeted to the buildings and locations at the highest risk for damage.

Effects of thermo-oxidative aging on progressive bending damages and electromechanical behaviors of carbon fiber/epoxy 3D woven composites

The effect of thermo-oxidative aging on mechanical properties is important to designing carbon fiber-reinforced composites serviced in long-term atmospheric environments. Here, we report the progressive bending damage behaviors of carbon fiber/epoxy 3D angle-interlock woven composites (3DAWCs) after thermo-oxidative aging. Three-point bending tests were conducted to characterize bending damage behaviors after different aging days. The electrical resistance change of 3DAWCs was also simultaneously measured with the two-probe method during three-point bending tests. Combining side image and digital image correlation (DIC) technology, we found that the bending strength and modulus deteriorated rapidly during thermo-oxidative aging. The strain distribution and progressive bending damage modes also changed significantly, i.e., a symmetrical strain distribution for the unaged specimens, while the existing interface cracks of the aged specimen changed this symmetry. The electrical resistance method (ERM) effectively identified the early-stage damages, and the first derivative of the rate of resistance change (FDC) revealed differences in the progressive damage modes of aged and unaged specimens.

Promoting Sustainable Coal Mining: Investigating Multifractal Characteristics of Induced Charge Signals in Coal Damage and Failure Process

Monitoring and preventing coal–rock dynamic disasters are essential for ensuring sustainable and safe mining. Induced charge monitoring, as a geophysical method, enables sustainable monitoring of coal–rock deformation and failure. The induced charge signal contains crucial information regarding damage evolution, making it imperative and important to explore its temporal characteristics for effective monitoring and early warnings of dynamic disasters in deep mining. This paper conducted induced charge monitoring tests at different loading rates, investigating the multifractal characteristics of induced charge signals during the early and late stages of loading. It proposed the maximum generalized dimension D(q)max, multifractal spectrum width Δα, and height difference Δf as multifractal parameters for induced charge signals. Additionally, quantitative characterization of coal damage was performed, studying the variation patterns of signal multifractal characteristic parameters with coal damage evolution. This study revealed the induced charge signal of the coal body multifractal characteristics in the whole loading process. In the late loading stage, the double logarithmic curve demonstrated some nonlinearity compared to the previous period, indicating the higher non-uniformity of the induced charge time series. D(q)max and Δα in the late loading stage were higher than those in the early stage and increased with loading rates. As coal damage progressed, there were significant jumps of D(q)max in both the early and late stages of damage, with larger jumps indicating richer fracture events in the coal. The width Δα showed an overall trend of increase–decrease–increase with coal damage evolution, while the height difference Δf fluctuated around zero in the early stage of damage development but increased significantly during severe damage and destruction. By studying the multifractal characteristics of induced charge signals, this study provides insights for the early identification of coal–rock dynamic disasters.

Frequency sweep study on the generation of dual-mode second harmonics (DMSH) on an isotropic nonlinear elastic cylindrical rod by T(0,1) mode

Nonlinear ultrasonic (NLU) guided wave (GW) measurements are more sensitive to microscale defects than linear measurements. This nonlinear phenomenon is helpful for early-stage damage detection in material for nondestructive evaluation (NDE) and structural health monitoring (SHM) applications. The amplitude of the higher harmonics generated in the material serves as the basis for the NLU measurement. Recent studies have reported the presence of dual-mode second harmonic (DMSH) on an isotropic nonlinear elastic plate and cylindrical structures. The fundamental non-dispersive mode shear horizontal SH0 and torsional T(0,1) modes can generate simultaneously propagating dual-mode second harmonic(DMSH) on plate and cylindrical guided media respectively. For the case of cylinders, at phase matching condition two dominant second harmonic fundamental longitudinal (l(0,1)) and orthogonal torsional (t(0,1)┴) mode are generated with significant amplitude. The particle vibration of the t(0,1)┴ mode was present in both orthogonal directions compared to conventional T(0,1) mode and hence called orthogonal torsional mode. The present work aims to study the behaviour of DMSH at different frequencies through a frequency sweep study on a weakly nonlinear elastic cylinder of circular cross-section via numerical simulations and validated experimentally for some selected cases. The wave propagation of the T(0,1) mode at several selected frequencies from 300 kHz to 2.2 MHz is chosen to explore the second harmonic mode for better understanding. At frequencies below 1.25 MHz, l(0,1) mode is faster than t(0,1)┴ mode; above 1.25 MHz, it was the other way around. The behaviour of harmonics was observed to be in accordance with the group and phase velocities at the corresponding frequencies in the dispersion curves. The evidence for the presence of DMSH was validated experimentally for some selected frequency cases at different propagation distances. The significance of DMSH is explored via numerical simulations and found that t(0,1)┴ mode is sensitive towards material degradation, while all other generated wave modes were not affected. Research shows that enough energy is available in the generated DMSH to be noticed experimentally and in numerical simulations. This improved understanding of the generation of DMSH across different frequencies would be helpful in new advanced NLU-based NDE and SHM applications.

Hymenopteran parasitoid complex and fall armyworm: a case study in eastern India

Fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) has significantly affected maize crop yields, production efficiency, and farmers’ incomes in the Indian Eastern Gangetic Plains region since it was first observed in India in 2018. A lack of awareness by maize growers of the appropriate selection, method, and timing of insecticide application not only creates a barrier to sustainable FAW control but also contributes to increased environmental pollution, reduced human health and increased production costs. We demonstrated that FAW inflicted the most damage in early whorl growth stage of maize, regardless of whether chemical insecticides were applied. FAW egg masses and larvae collected from maize fields in which no insecticides had been sprayed showed high parasitism rates by parasitoid wasps; in contrast fields that had been sprayed had much lower rates of parasitism on FAW. Ten hymenopteran parasitoids were observed in maize fields across the study region, suggesting a diversity of natural methods to suppress FAW in maize at different growth stages. These included two FAW egg parasitoids and eight FAW larval parasitoids. Microplitis manilae Ashmead was the most abundant FAW larval parasitoid species, and Telenomus cf. remus was the dominant FAW egg parasitoid species. Endemic FAW parasitoids such as those observed in this study have great potential as part of a sustainable, cost-effective agroecological management strategy, which can be integrated with other methods to achieve effective control of FAW.

Evolution Pattern in Bruised Tissue of 'Red Delicious' Apple.

The study of apple damage mechanisms is key to improving post-harvest apple treatment techniques, and the evolution pattern of damaged tissue is fundamental to the study of apple damage mechanisms. In the study, 'Red Delicious' apples were used to explore the relationship between damage and time. A cell death zone was found in the pulp of the damaged tissue after the apple had been bruised. The tissue damage was centered in the cell death zone and developed laterally, with the width of the damage increasing with injury time. The extent of tissue damage in the core and pericarpal directions varied. About 60% of the damaged tissue developed in the core direction and 40% in the pericarpal direction, and the damage ratios in both directions remained consistent throughout the injury. The depth of damage and the rate of damage were influenced by the impact force size and the difference in the size of the damaged part of the apple, but the damage development pattern was independent of the impact force size and the difference in the damaged part. The maximum damage rate was reached at about 30 min, and the depth of damage was stabilized at about 72 min. By studying the evolution pattern of the damaged tissue of the bruised 'Red Delicious' apple, it provides the research idea and theoretical basis for enhancing the prediction accuracy and robustness of early stage damage in apples.

Diagnostic Accuracy of Serum Cystatin C for Early Detection of Kidney Damage in Patients with Type II Diabetes Mellitus: Bahawalpur, Pakistan

Objective: To determine the diagnostic accuracy of serum Cystatin C for early detection of kidney damage taking albumin Creatinine Ratio as a reference standard among people of Bahawalpur having diabetes mellitus type 2.Study Design: A cross-sectional study.Place and Duration of Study: The Study was conducted at the Department of Pathology in collaboration with th th Kidney Center, Bahawalpur Victoria Hospital, Bahawalpur, Pakistan from 27 August 2021 to 26 February 2022.Methods: There was a total of 200 patients having diabetes mellitus type 2 with GFR between 60-90ml/min with an age range from 40-60 years were selected. Study participants with a history of steroid intake, hypothyroidism, chronic liver disease, AIDS, and hypertension were not included in the study. For assessment of diagnostic accuracy of Cystatin C to evaluate the renal damages in early stages, microalbuminuria was evaluated. As per the guidelines provided by the respective manufacturers, individuals exhibiting two albumin creatinine ratio (ACR) levels exceeding 30 mg/g were classified as having diabetic nephropathy (DN).Results: The overall sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of serum Cystatin C for the early detection of kidney damage, with albumin-to-creatinine ratio used as the reference standard among individuals with type 2 diabetes mellitus, were 90.98%, 78.21%, 86.72%, 84.72%, and 86.0%, respectively.Conclusion: The findings of this investigation indicate that serum cystatin C (CysC) exhibits a considerable level of diagnostic accuracy in the early detection of kidney damage among individuals with type 2 diabetes mellitus, utilizing the albumin-to-creatinine ratio as a reference standard.How to cite this: Sajid I, Saeed R, Goheer A, Asghar S, Saqib S, Bashir F. Diagnostic Accuracy of Serum Cystatin C for Early Detection of Kidney Damage in Patients with Type II Diabetes Mellitus: Bahawalpur, Pakistan. Life and Science. 2024; 5(1): 41-47. doi: http://doi.org/10.37185/LnS.1.1.559

Urine metabolome investigation in pediatric urology. Review

Metabolomics is the science of studying small molecules (50–5,000 Da) formed because of the implementation of metabolic pathways in cells and the maintenance of their vital functions. The study of urine metabolome is a promising direction for diagnosing early stages of damage to various cells of the urinary system in pediatric urology, allowing the study of biomarkers or their spectrum, which can improve the identification of existing disorders, and multivariate analysis will provide greater accuracy in making a diagnosis. This study aimed to summarize existing information on urine metabolome and its changes in cases of congenital malformations of the urinary system, accompanied by renal dysplasia, leading to acute kidney injury or chronic kidney disease. A literature search and review was conducted using PubMed, Embase, and Google Scholar. The review presents the possibilities of metabolomic analysis to provide a qualitatively new level of diagnosis and monitoring of damage to the structures of organs and tissues of the urinary system, identifying predictors of pathology progression, and personalized techniques for making medical decisions. However, this method is limited by the high cost of the equipment, need for training of highly qualified personnel, and difficulty in interpreting the results. The study of urine metabolome is very promising for the diagnosis and selection of a timely, rational treatment strategy for children with malformations of the urinary system.

Reprogramming to alleviate Alzheimer’s disease through ameliorating microglial inflammation and neuronal damage

AbstractBackgroundAlzheimer’s disease (AD) is a neurodegenerative disease, characterized by glial cell dysfunction and progressive neuron loss, leading to varying degrees of neuropathology and cognition impairment. Aging and epigenetic alterations accompany the progression of AD and disrupt cellular functions; therefore, whether reprogramming could restore epigenetic information while maintaining cellular identity remains unclear.MethodThe polycistronic expression cassette contained multiple transcription factors of the Oct4, Sox2, and Klf4 genes (OSK) that were cloned into a coexpression vector (Ad‐OSK). The effects of OSK on cognitive function and neuropathology were explored in 4‐month‐old and 6‐month‐old APP/PS1 transgenic AD model mice via stereotaxic injection into the bilateral hippocampus.ResultAd‐OSK maintained microglial and neuronal cellular identities while attenuating microglia‐induced neuroinflammation and neuronal apoptosis. Ectopic expression of OSK in mouse brain tissue alleviates and restores cognitive function, youthful neuronal pathogenesis, Aβ plaque deposition, microglial activation, and myelin damage in early stage and later stage AD mice, respectively. The DNA demethylation process is required for the beneficial effects of OSK induced reprogramming in brain health.ConclusionThese results suggest that brain tissues preserve youthful epigenetic information, which is primarily stored by DNA demethylation during OSK reprogramming and can be accessed to improve brain health in AD mice. Our findings provide the foundation for the future use of OSK adenovirus or mRNA medicine to treat AD.

An affordable and easy-to-use tool to diagnose knee arthritis using knee sound

Arthritis, the most common form of osteoarthritis, affects millions of individuals worldwide. While it can affect any joint in the body, it predominantly affects the hands, neck, back, knees, and hips. Traditional imaging technologies like X-rays are impractical for diagnosing knee pathology and are insufficient for detecting disease symptoms, especially in the early stages of damage. Invasive procedures such as arthroscopy are often required to identify changes, but they are unsuitable for repeated assessments, follow-ups, or monitoring. Vibro-acoustography (VAG), which utilizes vibration and acoustic signals from the human knee during movement, has emerged as a non-invasive diagnostic tool. However, muscle-induced low-frequency irregularities triggered by knee movement significantly impact the accuracy of VAG signals. In this study, a novel machine learning-based approach is introduced for detecting knee osteoarthritis by processing sound signals recorded by a condenser microphone. Knee sounds from both healthy and osteoarthritic patients were captured during knee swing motions (flexion and extension). Three features were extracted from the knee sounds and classified using the Perceptron, MLP, SVM, GRNN, and RBF classifiers. The performance of different features and classifiers was compared, revealing that one feature demonstrated robust results with a high accuracy of 87% and an F1-score of 0.86. Compared to other conventional methods, the proposed approach is characterized by its speed, affordability, portability, and user-friendliness, with the potential for easy development into a mobile application.