Early Damage Detection Research Articles

Novel biomarkers in patients with uncontrolled hypertension with and without kidney damage

Introduction Estimated glomerular filtration rate (eGFR) and urine albumin/creatinine ratio (ACR) are insensitive biomarkers for early detection of hypertension-mediated organ damage (HMOD). In this nationwide cross-sectional study, we assessed potential biomarkers for early HMOD in healthy persons and patients with hypertension. We hypothesised that plasma levels of biomarkers: (1) are different between healthy controls and patients with hypertension, (2): can classify patients with hypertension according to the degree of hypertension severity. Design and methods Patients with hypertension prescribed ≥2 antihypertensive agents were selected from a multicentre study. Healthy controls were selected from an ongoing study of living kidney donor candidates. Uncontrolled hypertension was defined as systolic daytime ambulatory blood pressure ≥135 mmHg. Kidney HMOD was defined by ACR > 3.0 mg/mmol or eGFR < 60 mL/min/1.73 m2. Patients with hypertension were categorised into three groups: (1) controlled hypertension; (2) uncontrolled hypertension without kidney HMOD; (3) uncontrolled hypertension with kidney HMOD. Fifteen biomarkers were analysed using a Luminex bead-based immunoassay, and nine fell within the specified analytical range. Results Plasma levels of Interleukin 1 receptor antagonist (IL-1RA), neutrophil gelatinase-associated lipocalin (NGAL) and uromodulin were significantly different between healthy controls (n = 39) and patients with hypertension (n = 176). In regression models, with controlled hypertension (n = 55) as the reference category, none of the biomarkers were associated with uncontrolled hypertension without (n = 59) and with (n = 62) kidney HMOD. In models adjusted for cardiovascular risk factors and eGFR, osteopontin (OPN) was associated with uncontrolled hypertension without kidney HMOD (odds ratio (OR) 1.77 (1.05–2.98), p = 0.03), and regulated upon activation normal T-cell expressed and secreted (RANTES) with uncontrolled hypertension with kidney HMOD (OR 0.57 (0.34–0.95), p = 0.03). Conclusions None of the biomarkers could differentiate our hypertension groups when established risk factors were considered. Plasma OPN may identify patients with uncontrolled hypertension at risk for kidney HMOD.

An Activatable Semiconducting Nanoprobe for Early and Accurate Diagnosis of Liver Injury.

Liver injury, caused by factors like viral hepatitis and drug overdose, poses a significant health risk, with current diagnostic methods lacking specificity, increasing the need for more precise molecular imaging techniques. Herein, we present an activatable semiconducting liver injury reporter (SLIR) for early and accurate diagnosis of liver injury. The SLIR, which is composed of semiconducting polymers with an electron-withdrawing quenching segment, remains nonfluorescent until it encounters biothiols such as cysteine in the liver. SLIR accumulates efficiently in the liver and respond rapidly to biothiols, allowing accurate and early detection of liver damage. The recovery of SLIR fluorescence negatively reflects the dynamics of oxidative stress in the liver and provides information on the severity of tissue damage. Thus, the specificity of SLIR, the fast response, and the efficient targeting of the liver make it a promising tool for the precise diagnosis of liver damage at an early stage.

Unveiling Cardiac Involvement in Juvenile Dermatomyositis Through Speckle-Tracking Echocardiography.

Early detection of cardiac involvement in Juvenile Dermatomyositis (JDM) is difficult due to the absence of clinical signs and symptoms, with systolic dysfunction often emerging in late stages and associated with a poor prognosis. This study aimed to employ two-dimensional speckle-tracking echocardiography (STE) for subclinical assessment of left ventricular (LV) systolic failure in JDM and explore potential associations between impaired LV systolic function (LV-GLS) and disease activity. A prospective study enrolled 20 healthy volunteers and 26 JDM patients (< 18years old) without cardiac symptoms. Clinical data were collected from medical records, and echocardiograms were conducted by a pediatric cardiologist. Our study cohort demonstrated similar age to controls (13.5 ± .6 vs. 13.8 ± 4.7; p = 0.465). Median illness duration at echocardiography was 5 (1.5-17.5) years, and conventional echocardiography indicated normal LV ejection fraction (> 55%) in all participants. However, STE revealed lowered LV GLS in JDM patients (-22.2 ± 4.1% vs. -26.5 ± 5.3% p = 0.022). Pulse steroid users displayed lower GLS average values compared to non-users (β = 4.99, 95% CI 1.34-8.64, p = 0.009). Negative correlations existed between LV-GLS and age at diagnosis (r = -0.499; p = 0.011), diastolic parameters (E/E' ratio) and age at diagnosis (r = -0.469; p = 0.018), as well as RV global strain and age at diagnosis (r = -0.443; p = 0.024). Employing STE in JDM patients facilitated the identification of preclinical cardiac dysfunction. Given JDM patients' younger age, early myocardial damage detection through STE may impact treatment decisions and long-term cardiovascular prognosis.

Research on Damage Identification of Truss Structures based on Bayesian Updating and Rejection Sampling Method

The research on the early damage detection method of truss structure has important practical value for taking remedial measures in time and reducing the hidden danger of safety. In this study, a specific structural truss beam was designed and the seismic action was simulated. Subsequently, specific nodes are analyzed to assess the resulting structural damage. Bayesian updating method solves the uncertainty problem effectively by introducing the prior distribution and updating the posterior distribution with new observation data. This allows the model to infer global patterns from local information and represent the predicted outcomes in probabilistic form. Compared with the traditional parameter estimation methods, Bayesian updating can make full use of the existing observational data and obtain more reliable and accurate model prediction results in the case of limited data. The Bayesian method of updating the truss structure is flexible and adaptable, allowing updates and adjustments to be made at any given time based on new observational data. As a result, it has significant advantages in analyzing and predicting real-time data and is suitable for scenarios where models need to be dynamically adjusted.

Internet of things (IoT)-based structural health monitoring of laboratory-scale civil engineering structures

Rapid advances in the Internet of Things (IoT) domain have made it a crucial technology for the real-time structural health monitoring (SHM) of civil engineering infrastructures. The availability of quick and accurate vibration data is essential for SHM, and such data can be obtained through IoT devices mounted on the structures. This study proposes a real-time damage prediction and localization approach using a low-cost "do-it-yourself" wireless sensor node with IoT capabilities for SHM. The proposed sensor node comprised a microcontroller (NODE MCU ESP8266) and a 6-axis accelerometer (MPU6050). The IoT devices track the real-time frequency of the laboratory-scale structure indirectly via measurement of acceleration-time history, and their results are compared with conventional industry-standard accelerometers. Promising results, with a <6% average difference from the conventional accelerometer (difference ranging from 1.3 to 14.3%), provided an innovative SHM for vibration-based real-time SHM using the IoT paradigm. The performance of the proposed methodology was validated numerically and experimentally on two laboratory-scale structures, and the potential of IoT technology for enhancing the efficiency of SHM was demonstrated. The proposed method thus can enable the early detection of damages in infrastructures such as buildings and bridges and thus can reduce the likelihood of accidents via continuous SHM.

The potential role of artificial intelligence in the clinical management of Hansen's disease (leprosy).

Missed and delayed diagnoses of Hansen's disease (HD) are making the battle against it even more complex, increasing its transmission and significantly impacting those affected and their families. This strains public health systems and raises the risk of lifelong impairments and disabilities. Worryingly, the three countries most affected by HD witnessed a growth in new cases in 2022, jeopardizing the World Health Organization's targets to interrupt transmission. Artificial intelligence (AI) can help address these challenges by offering the potential for rapid case detection, customized treatment, and solutions for accessibility challenges-especially in regions with a shortage of trained healthcare professionals. This perspective article explores how AI can significantly impact the clinical management of HD, focusing on therapeutic strategies. AI can help classify cases, ensure multidrug therapy compliance, monitor geographical treatment coverage, and detect adverse drug reactions and antimicrobial resistance. In addition, AI can assist in the early detection of nerve damage, which aids in disability prevention and planning rehabilitation. Incorporating AI into mental health counseling is also a promising contribution to combating the stigma associated with HD. By revolutionizing therapeutic approaches, AI offers a holistic solution to reduce the burden of HD and improve patient outcomes.

Kanker in Nederland: trends &amp; prognoses tot en met 2032. De impact voor de mondzorg in Nederland

For years, cancer has been one of the diseases that causes the greatest disease burden in the Netherlands. Cancer does not only have a huge impact on patients and their loved ones, but also on society and healthcare. If the number of cancer patients increases further in the coming years, this impact will only aggravate. This development will also impact dental practice. It is therefore important to assess what awaits us in the coming years. Both with regard to supporting and treating (former) oncology patients. Forinstance, detecting secondary effects of cancer treatments such as oral mucositis and medication- and radiation-related jaw necrosis, as well as the early detection of oral cavity carcinomas and sun-related skin damage on the lips and face. Based on this, plans can be made to meet the demand for dental care as well as possible and to reduce the impact of cancer for both the individual patient and for society as a whole.

Point Shear Wave Elastography Detected Liver Stiffness Increased in Pediatric Patient With Thalassemia Major.

Transient elastography (TE) and point shear wave elastography (pSWE) are 2 elastographic ultrasound examinations used in liver stiffness (LS) measurement. It was shown that the LS value detected by TE in pediatric β-thalassemia major patients has increased, and there was no LS evaluation obtained with pSWE in literature. Thus, in this study, it was aimed to evaluate LS with pSWE examination in children with thalassemia major and to determine LS-related parameters in these patients. Sixty-three schoolchildren with a diagnosis of β-thalassemia major and 21 healthy controls between the ages of 7 and 18 years were included. In addition to routine anamnesis, physical examination, and laboratory examinations, renal and liver ultrasounds were performed. Liver stiffness values were measured by pSWE examination. Serum levels of urea, aspartate-aminotransferase, alanine-aminotransferase, iron, and ferritin were significantly higher in patients, and serum creatinine, iron binding capacity, and hemoglobin levels were found to be significantly lower (P < 0.05 for each). Liver stiffness values were significantly higher in patients compared with healthy controls. In linear regression analysis, serum iron and iron binding capacity values were found to be closely related with LS (P < 0.001 vs. β = 0.482 and P = 0.047 vs. β = 0.237, respectively). Liver stiffness values obtained by pSWE examination increase significantly in patients. According to the results of our study, in addition to the previously known TE method, we think that the LS evaluation obtained by pSWE, a new method that can make more accurate measurements, can be used in the possible early detection of target organ damage in children with thalassemia major.

Assessment of articular cartilage degradation in response to an impact injury using µMRI

ABSTRACT Purpose Degradation of articular cartilage (AC) due to injury to the knee joint may initiate post-traumatic osteoarthritis (PTOA). Failure to diagnose the onset of the disease at an early stage makes the cure ineffective for PTOA. This study investigated the consequences of a mechanical injury to the knee in a rabbit model using microscopic magnetic resonance imaging (µMRI) at high resolution. Materials and methods A mechanical injury was induced to the knee joints of 12 rabbits. Cartilage blocks were extracted from the non-impacted and impacted knee joints after 2 and 14 weeks post-impact. The specimens were studied using µMRI T2 relaxation and inductively coupled plasma analysis to determine the early degradation of the articular cartilage. Results The data established a connection between T2 relaxation time and the early progression of knee PTOA after an impact injury. T2 values were found to be higher in the impacted cartilage at both 2 and 14 weeks, in particular, T2–55° values in the impacted samples displayed a significant rise of 6.93% after 2 weeks and 20.02% after 14 weeks. Lower glycosaminoglycan measurement and higher water content in the impacted cartilage confirmed the µMRI results. Conclusions This µMRI T2 study was able to detect cartilage damage in the impacted knees. In addition, greater degradation in the affected knees at 14 weeks than at 2 weeks indicated the progressive nature of cartilage deterioration over time. The µMRI results were in accord with the biochemical analysis, indicating the detection of early structural damage in the cartilage.

Microalbuminuria sensitive near‐infrared AIE probe for point‐of‐care evaluating kidney diseases

AbstractUrinary microalbumin (mALB) serves as an exceptionally sensitive indicator for the early detection of kidney damage, playing a pivotal role in identifying chronic renal failure and kidney lesions in individuals. Nevertheless, the current fluorescent methodologies for point‐of‐care (POC) diagnosis of mALB in real urine still exhibit suboptimal performance. Herein, the development and synthesis of QM‐N2, an albumin‐activated near‐infrared (NIR) aggregation‐induced emission (AIE) fluorescent probe, are presented. The strategic incorporation and positioning of quaternary ammonium salts within the quinoline‐malononitrile (QM) scaffold significantly influence solubility and luminescence characteristics. Specifically, the quaternary ammonium salt‐free variant, QM‐OH, and the quaternary ammonium salt integrated at the donor function group (DFG) site, QM‐N1, display limited solubility in aqueous solutions while demonstrating a distinct fluorescence signal. Conversely, the incorporation of quaternary ammonium salt at the conformational functional group (CFG) site in QM‐N2 imparts superior dispersibility in water and reduces the initial fluorescence. Furthermore, the integration of a well‐defined D‐π‐A structure within QM‐N2 enables itself with near‐infrared emission, which is crucial for mitigating interference from autofluorescence present in urine samples. Upon interaction with albumin, QM‐N2 forms a tight bond with the IIA site of the subdomain of human serum albumin (HSA), inducing alterations in protein configuration and constraining the intrinsic motion of fluorescent molecules. This interaction induces fluorescence, facilitating the sensitive detection of trace albumin. Ultimately, QM‐N2 is applied for POC testing of mALB using portable equipment, particularly in the diagnosis of mALB‐related diseases, notably chronic renal failure. This positioning underscores its potential as an ideal candidate for self‐health measurement at home or in community hospitals.

Application of covariance statistical method for damage identification on railway truss bridge using acceleration response: experimental and numerical validation

This paper presents a novel statistical analysis-based approach to non-parametric damage detection in truss bridges. The method utilizes the normalized acceleration response time histories (NARTHs) of a bridge under random excitation. The coefficients of variation matrices are calculated using NARTHs for the truss bridge in both its baseline and damaged states. The results are shown as the difference in covariance matrices (DCMs) between the two conditions (pristine and damaged). The row or column-wise summation of the DCM matrix yields a summation of the difference in covariance matrix (SDCM) bar plot having one distinct peak for the damaged member. The location and relative severity of the damage can be determined by examining the DCM matrix and the SDCM bar plot. The variation in magnitude of the coefficients demonstrates the relative severity of damage. Experimental investigation of the proposed method for detecting damage on the truss bridge shows promising results. The approach is then numerically validated using a finite element model of a truss bridge. The proposed method effectively identified, located, and evaluated damage, even when the acceleration time histories are contaminated with noise. The case of multiple-member damage detection in the truss structure is further investigated in the study. The early detection of damage and monitoring of its progression through this method can assist in creating efficient maintenance strategies for truss bridge infrastructure.

TGF-β Isoforms and GDF-15 in the Development and Progression of Atherosclerosis.

The effect of oxidised lipoproteins on the endothelium, monocytes, platelets, and macrophages is a key factor in the initiation and development of atherosclerosis. Antioxidant action, lipoprotein metabolism, and chronic inflammation are the fields of research interest for better understanding the development of the disease. All the fields are related to inflammation and hence to the secretion of cytokines, which are being investigated as potential diagnostic markers for the onset of atherosclerosis. Pathways of vascular damage are crucial for the development of new laboratory readouts. The very early detection of endothelial cell damage associated with the onset of atherosclerosis, allowing the initiation of therapy, remains a major research goal. This article summarises the latest results on the relationship of tumour growth factor beta (TGF-β) isoforms and growth differentiation factor 15 (GDF-15) to the pathogenesis of atherosclerosis: which cells involved in atherosclerosis produce them, which effectors stimulate their synthesis and secretion, how they influence atherosclerosis development, and the relationship between the levels of TGF-β and GDF-15 in the blood and the development and extent of atherosclerosis.

Highly Sensitive Early Diagnosis of Kidney Damage Using Renal Clearable Zwitterion-Coated Ferrite Nanoprobe via Magnetic Resonance Imaging In Vivo.

Iron oxide nanoprobes exhibit substantial potential in magnetic resonance imaging (MRI) of kidney diseases and can eliminate the nephrotoxicity of gadolinium-based contrast agents (GBCAs). Nevertheless, there is an extreme shortage of highly sensitive and renal clearable iron oxide nanoprobes suitable for early kidney damage detection through MRI. Herein, a renal clearable ultra-small ferrite nanoprobe (UMFNPs@ZDS) is proposed for highly sensitive early diagnosis of kidney damage via structural and functional MRI in vivo for the first time. The nanoprobe comprises a ferrite core coated with a zwitterionic layer, and possesses a high T1 relaxivity (12.52 mm-1s-1), a small hydrodynamic size (6.43nm), remarkable water solubility, excellent biocompatibility, and impressive renal clearable ability. In a rat model of unilateral ureteral obstruction (UUO), the nanoprobe-based MRI can not only accurately visualize the locations of renal injury, but also provide comprehensive functional data including peak value, peak time, relative renal function (RRF), and clearance percentage via MRI. The findings prove the immense potential of ferrite nanoprobes as a superior alternative to GBCAs for the early diagnosis of kidney damage.

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

The role of computed tomography in the early detection of damage to the small intestine and mesentery in closed combined trauma (clinical case)

Introduction. The number of victims with abdominal trauma over the past 20 years has not tended to decrease due to an increase in the number of road accidents, falls from heights, man-made disasters and natural disasters. Diagnosis of damage to hollow organs should be fast and accurate, since the time factor in providing medical care to such patients is crucial. The delay of surgery for intestinal injury for 24 hours or more is associated with an increase in the mortality rate of up to 30%. In such cases, computed tomography is the method of choice for hemodynamically stable patients with closed abdominal trauma.The aim is to demonstrate the possibilities of computed tomography in the early detection of damage to the small intestine and mesentery using the example of a clinical case of closed combined abdominal trauma with damage to a hollow organ and multiple injuries of the musculoskeletal system.Materials and methods. A clinical case of combined trauma of a patient in a traffic accident is described.Conclusion. In this clinical case, the victim with a combined injury was shown the modern possibilities of computed tomography in early detection of damage to the walls of the small intestine and mesentery, which made it possible to make a timely decision on emergency surgery, avoid serious complications, restore the patient's ability to work and quality of life.

Research on the evolutionary of spectral features of the initial damaged parts of 'Red Delicious' apples

It is crucial for early detection of mechanical damage to improve the quality of commodity fruit. For the problem of low identification accuracy of damage detection models due to the small degree of damage and unclear damage features in the initial damage of fruit and vegetables, this research analyzed the evolution process of spectral information in the initial damage of (0–3 h) of 'Red Delicious' apples. Three sensitive bands of 650–734 nm, 850–970 nm, and 1255–1314 nm, were extracted, and the average spectral reflectance and spectral curve shape features tanθ of the sensitive bands were analyzed. The conclusion is as follows: (1) In the 650–734 nm band, spectral reflectance decreasing and then stabilizing, reflecting enzymatic browning development. More severe damage led to lower reflectance. Over time, tanθ decreased, with more severe damage showing faster reduction, reflecting changes in chlorophyll content in the peel. (2) In the 850–970 nm band, reflectance showed a decreasing-then-increasing trend, reflecting moisture content changes in the damaged area. More severe damage resulted in lower reflectance. Over time, tanθ initially rose, then decreased and stabilized. More severe damage led to greater tanθ. (3) In the 1255–1314 nm band, reflectance initially increased, then decreased and stabilized, reflecting temperature changes in the damaged area. More severe damage led to higher reflectance. Over time, tanθ first increased, then decreased, with more severe damage showing smaller tanθ. The study on the evolutionary pattern of the spectral features after the impact of 'Red Delicious' apples provides theoretical basis for more reliable detection of the initial minor damage of apples in the future.

System identification and monitoring of bridge structures

The research presented is part of the SPP100+ of the German Research Foundation. Subject of the research is the early detection of damage, especially on large bridge structures. For this purpose, investigations are carried out at the technical center of the I4S, in particular to take into account the environmental conditions (EOC) in the context of system identification of mechanical structures. The lifetime of the considered structures is divided into macro and micro time domains. In the micro time domain, state space models serve as a basis for damage localization. The parameters of the models are estimated based on output-only methods and H2/H∞ optimization. The damage localization is done by SP2E, the state projection estimation error method in conjunction with a machine learning method, for the categorization of the EOC. This paper presents the monitoring method in micro time domain of lifetime and first results of experimental investigation and vibration-based output-only measurements at the bridge Floßgrabenbrücke.

Drug-induced Kidney Disease: Revisited.

Drug-induced kidney disease (DIKD) is a frequent cause of acute and chronic kidney disease (CKD) that leads to high morbidity, hospitalization, and increased healthcare costs. There is a need to constantly update our knowledge in this field, given the ever-burgeoning list of newer treatments that are emerging, especially in the field of cancer immunotherapy. Generalizing the complex pathways causing DIKD from different agents, the common mechanisms include direct toxicity, immune-mediated injury, and drug-induced alterations in renal blood flow. Proper management of this condition involves risk minimization, early detection of renal damage, and timely discontinuation of potential agents to avoid irreversible renal damage.

MiRNA-221: A Potential Biomarker of Progressive Liver Injury in Chronic Liver Disease (CLD) due to Hepatitis B Virus (HBV) and Nonalcoholic Fatty Liver Disease (NAFLD).

Background: Early detection of progressive liver damage in chronic liver disease (CLD) patients is crucial for better treatment response. Several studies have shown the association of microRNA (miRNA) in the progression of CLD in regulating cell proliferation, fibrosis, and apoptosis as well as in carcinogenesis. Objectives: The study was aimed at determining the expression of miRNA-221 among different stages of fibrosis in CLD patients due to hepatitis B virus (HBV) and nonalcoholic fatty liver disease (NAFLD) and thus evaluate its role as an early biomarker in CLD. Methods: A total of 100 participants (75 CLD patients and 25 healthy control) were recruited in this cross-sectional study and divided into four groups, of which 25 as healthy control, 25 in CLD without fibrosis, 25 were CLD with fibrosis, and 25 were CLD with cirrhosis. Total RNA was extracted from plasma followed by cDNA synthesis, and finally, the expression of miRNA-221 was analyzed for its diagnostic potential as a single biomarker using the qRT-PCR method. Results: The plasma level of miRNA-221 was significantly upregulated in different fibrosis stages of CLD (p < 0.05), and this upregulation was positively correlated with the progression of fibrosis (p < 0.05). Significantly increased expression of miRNA-221 was found in NAFLD patients compared to HBV patients in the CLD without fibrosis patient group (p < 0.05), while expression of miRNA-221 was significantly upregulated among HBV patients in the CLD with the fibrosis group. miRNA-221 showed high diagnostic accuracy in discriminating different stages of fibrosis from healthy control (p < 0.05). Conclusion: miRNA-221 may be used as a potential plasma biomarker for early prediction of fibrosis progression in CLD patients.

ANALYSIS OF NATURAL FREQUENCIES FOR EARLY DAMAGE DETECTION IN CFRP SHAFTS USING RSM-BASED FREQUENCY CONTOUR PLOTS

This study explores early damage detection in carbon fiber-reinforced polymer shafts by analyzing natural frequencies. Modern engineering components often face increased flexibility and high stress levels, leading to cracks in rotating parts, which can result in premature failures. To address this issue, modal analysis, specifically natural frequency analysis, is employed to identify deviations caused by cracks. Cracks alter stiffness and mass distribution, leading to shifts in natural frequencies. The study employs finite element models to simulate various crack locations and depths, normalizing them with respect to shaft diameter and length. A cantilever shaft configuration is utilized with refined mesh structures near the transverse crack. The analysis leverages the frequency contour method with response surface methodology to visualize how crack depth and location influence normalized natural frequencies. Results indicate that crack depth has a significant impact on natural frequencies, while crack location has a subtler effect. Combining depth and location produces the most pronounced frequency variations. The corresponding R² values for the normalized first and third natural frequencies are 95.69% and 96.32%, while for the normalized second natural frequency this value is 75.70%. The study also demonstrates the use of frequency contour curves for accurate crack detection, with the 1st and 3rd natural frequencies being reliable indicators.