New Method For Early Detection Research Articles

Anti-CD64 Antibody-Conjugated PLGA Nanoparticles Containing Methotrexate and Gold for Theranostics Application in Rheumatoid Arthritis.

Rheumatoid arthritis, an autoimmune disorder, exerts a considerable effect on quality of life. The inflammatory mechanism involved in rheumatoid arthritis is not clearly known, and therefore the need to develop effective medicines as well as new methods for early detection is a challenge. In this study, we developed PLGA nanoparticles containing gold and methotrexate in core and anti-CD64 antibody conjugated to nanoparticle surface via coupling process. The nanoparticles were examined for their surface morphology using SEM and TEM. The mean particle size, zeta potential, and PDI values of nanoparticles were 413.6 ± 2.89 nm, -10.12 ± 2.12 mV, and 0.23 ± 0.04, respectively, indicating good stability and particle homogeneity. In vitro drug release revealed a controlled release pattern with 93.44 ± 1.60% up to 72 h of release in the presence of pH 5.8, indicating the influence of pH and NIR on drug release. In vivo results on adjuvant-induced arthritis on Wistar rats indicated that animals receiving antibody-conjugated nanoparticles showed improvement in clinical indices and arthritic score as compared to non-conjugated nanoparticles and free drugs. This innovative drug delivery system will be an excellent strategy to maximize therapeutic effectiveness by limiting dosage-related side effects.

A magnetic control enrichment technique combined with terahertz metamaterial biosensor for detecting SARS-CoV-2 spike protein

The highly contagious SARS-CoV-2 virus, responsible for the COVID-19 pandemic continues to pose significant challenges to public health. Developing new methods for early detection and diagnosis is crucial in combatting the disease, mitigating its impact and be prepared for future challenges in pandemic diseases. In this study, we propose a terahertz (THz) biosensing technology that capitalizes on the properties of THz metamaterial in conjunction with magnetic nanoparticles. This approach can accurately identify the SARS-CoV-2 spike protein by pinpointing its location on the THz resonance sources grooved surface. The magnetic nanoparticles are employed to selectively bind with target molecules, and migrate towards the THz metamaterial unit cell when exposed to an applied magnetic field. The presence of target molecules in to the metamaterial variation in the frequency, amplitude, and phase of the resonance response, thus enabling swift, accurate and sensitive detection. To assess the effectiveness of the proposed technique, we have conducted a comparative analysis between real samples on platforms controlled by magnetic manipulation and those without the control. It was confirmed that the proposed THz sensing method demonstrated a linear detection range spanning from 0.005 ng mL−1 to 1000 ng mL−1 with a detection limit of 0.002 ng mL−1. Furthermore, it exhibited a frequency shift of 24 GHz and a stability index of 95%. The THz biosensing technique may pave a new avenue in identifying and preempting the spread of potential pandemic diseases.

Environment factors, DNA methylation, and cancer.

Today, the rapid development of science and technology and the rapid change in economy and society are changing the way of life of human beings and affecting the natural, living, working, and internal environment on which human beings depend. At the same time, the global incidence of cancer has increased significantly yearly, and cancer has become the number one killer that threatens human health. Studies have shown that diet, living habits, residential environment, mental and psychological factors, intestinal flora, genetics, social factors, and viral and non-viral infections are closely related to human cancer. However, the molecular mechanisms of the environment and cancer development remain to be further explored. In recent years, DNA methylation has become a key hub and bridge for environmental and cancer research. Some environmental factors can alter the hyper/hypomethylation of human cancer suppressor gene promoters, proto-oncogene promoters, and the whole genome, causing low/high expression or gene mutation of related genes, thereby exerting oncogenic or anticancer effects. It is expected to develop early warning markers of cancer environment based on DNA methylation, thereby providing new methods for early detection of cancers, diagnosis, and targeted therapy. This review systematically expounds on the internal mechanism of environmental factors affecting cancer by changing DNA methylation, aiming to help establish the concept of cancer prevention and improve people's health.

“Somebody was standing in my corner”: a mixed methods exploration of survivor, coach, and hospital staff perspectives and outcomes in an Australian cancer survivorship program

PurposeCancer survivorship in Australia continues to increase due to new methods for early detection and treatment. Cancer survivors face challenges in the survivorship phase and require ongoing support. A telephone-delivered cancer survivorship program (CSP), including health and mental health coaches, was developed, piloted, and evaluated in Eastern Australia.MethodsCancer survivors’ (n = 7), coaches’ (n = 7), and hospital staff (n = 3) experiences of the CSP were explored through semi-structured interviews. Quantitative data routinely collected throughout the pilot of the CSP was described (N = 25).ResultsThree syntheses and 11 themes were generated through thematic analysis. The first synthesis centred around operational factors and highlighted a need to streamline communication from the point of recruitment, through to program delivery, emphasising that the program could be beneficial when timed right and tailored correctly. The second synthesis indicated that the CSP focused on appropriate information, filled a gap in support, and met the needs of cancer survivors by empowering them. The third synthesis focussed on the value of mental health support in the CSP, but also highlighted challenges coaches faced in providing this support. Descriptive analysis of quantitative data indicated improvements in self-management, weekly physical activity, and meeting previously unmet needs.ConclusionsCancer survivors expressed appreciation for the support they received through the CSP and, in line with other cancer survivorship research, predominantly valued just having somebody in their corner.Implications for cancer survivorsRecommendations are made for improving cancer survivorship programs in the future.

Early Detection and Classification of Heart Diseases by Employing IFCMML and 2L-C Model with I-GA Machine Learning Methods

Objectives: To identify a new method for early detection and classification of Heart Diseases (HD); to improve the accuracy of the results by employing I-FCMML (Improved Fuzzy C-Means Machine Learning) and 2L-C (Two-Level Classifier) models along with the I-GA (Improved Genetic Algorithm) methods. Methods: The I-FCMML algorithm is utilized for feature selection and extraction. Machine learning techniques such as Ensembled Random Forest method (ERFM) and Robust Gradient Boost Method (RGBT) are employed to predict the likelihood of HD and 2L-C, I-GA is used to classify and detect the HD at a premature stage based on features like age, gender, blood pressure, etc. IFCMML with 2L-C & I-GA extracts all the features from the dataset (Cleveland HD dataset from the Cleveland Clinic Foundation, Ohio, USA) which includes 303 observations, 14 features and selects the suitable function to perform disease classification and detection with high accuracy. To evaluate the performance of the proposed method, MATLAB is used for implementation. The results are compared with existing algorithms such as 3P-ANN, ANN-FAHP, ADWFS, EDSS, and FE-PCA. Findings: Early HD detection and classification is achieved with 96.02% accuracy, 95.80% sensitivity, 94.76% specificity, 95% precision, 94% recall, 0.90 True Positive, 0.87 True Negative, and 94.13% F-Score to detect and classify the HD in a robust manner, which is comparatively high than the existing methods. Novelty: According to the findings of the comprehensive study, the proposed new method I-FCMML with 2L-C & I-GA has the potential to provide accurate and competent detection and classification of HD at an early stage, which could help for timely treatment and management of HD patients, and it also outperforms the existing methods such as 3P-ANN, ANNFAHP, ADWFS, EDSS, and FE-PCA. Keywords: Heart Disease Detection; Classification Algorithm; Genetic Algorithm; Fuzzy C-Means ML; Image Processing

Development of a phage-based electrochemical biosensor for detection of Escherichia coli O157: H7 GXEC-N07

Escherichia coli (E. coli) O157:H7 is one of the most important foodborne pathogens that causing severe foodborne diseases. With the development of foodborne diseases, there is an urgent need to seek new methods for early detection and monitoring of E. coli O157:H7. In this study, an electrochemical biosensor using phage EP01 as the recognition agent for detection of E. coli O157:H7 GXEC-N07 was established due to the specificity and high efficiency of phage EP01 in recognizing GXEC-N07. The biosensor was developed by depositing phages conjugated carboxyl graphene oxide (CFGO) and conductive carbon black (CB) onto the surface of glass carbon electrodes (GCEs). When detecting GXEC-N07 in the concentration range of 102 ∼ 107 CFU/mL, the biosensor showed good linearity with a low detection limit of 11.8 CFU/mL, and the whole progress was in less than 30 min. The biosensor was successfully applied to the quantitative detection of GXEC-N07 in fresh milk and raw pork. The recovery values ranged from 60.8 % to 114.2 %. The biosensor provides a rapid, specific, low cost, and label free tool for E. coli O157:H7 GXEC-N07 detection. It is expected to become a powerful method for the detection of bacteria that threatening food safety and public health security.

Early detection of Sclerotinia sclerotiorum on oilseed rape leaves based on optical properties

Oilseed rape ( Brassica napus L.) is susceptible to Sclerotinia sclerotiorum and its yield would reduce dramatically by the sclerotinia disease. Early detection of the pathogen to prevent the spread of sclerotinia is of great significance. In this paper, the optical response of oilseed rape leaves to Sclerotinia sclerotiorum was analyzed and a new method for early detection of sclerotinia disease based on optical properties was proposed. The optical absorption ( μ a ) and reduced scattering ( μ s ′ ) coefficients of healthy and infected (invisible-symptom and visible-symptom) oilseed rape leaves were measured by using a single integrating sphere (SIS) system over 500–1000 nm. Results showed that with the development of Sclerotinia sclerotiorum infection from healthy to visible-symptom leaves, μ a decreased in 600–700 nm that contained obvious absorption peaks by pigments, while μ s ′ increased in 500–1000 nm. Then linear discriminant analysis (LDA) and support vector machines (SVM) models were developed to discriminate infected leaves from healthy ones, with the raw data of μ a in 500–700 nm, μ s ′ in 500–700 nm, and ( μ a - μ s ′ ) in 600–700 nm, as well as corresponding effective wavelengths optimally selected by the successive projections algorithm (SPA). Results showed that the LDA models with the raw and SPA-selected data of μ a in 500–700 nm, and the SPA-selected ( μ a - μ s ′ ) data, and the SVM model with SPA-selected μ a data all provided 100.00% classification accuracy. Overall, this study proved that the optical properties of oilseed rape responded to Sclerotinia sclerotiorum at early stage, and could be a new basis for early detection of sclerotinia disease. • Optical absorption and scattering parameters were measured for oilseed rape leaves. • Optical response of oilseed rape leaves to Sclerotinia sclerotiorum was analyzed. • Optical parameters were optimally selected for Sclerotinia sclerotiorum detection. • Models for classifying infected and healthy oilseed rape leaves were developed. • Early detection of Sclerotinia sclerotiorum was achieved based on optical properties.

Fabrication of a new SPME fiber based on Polyacrylic acid/ MIL-88(Fe)-NH2 composite as a self-healing coating for the analysis of breast cancer biomarkers in the urine sample

Analysis of cancer biomarkers in the body fluids is a new method for early detection of illness. However, due to the complex matrices of samples, the application of a pre-treatment method is unavoidable before the final analysis by gas chromatography (GC). Solid-phase microextraction (SPME) is a simple and, promising pre-concentration and separation method that its coatings are modified with different materials on the fibers. A new innovative self-healing polyacrylic acid PAA/MIL-88(Fe)-NH2 composite was synthesized as an SPME coating. The parameters including pH, crosslinker, and MIL-88(Fe)-NH2 content were optimized to formulate the composite. The prepared fiber was used to extract 2-pentanone, 2-heptanone, ethyl propionate, p-xylene, 1,2,4-trimethylbenzene, and o-cresol as a biomarker in breast cancer from urine samples. The prepared PAA/MIL-88(Fe)-NH2 SPME fibers demonstrate excellent repeatability (relative standard deviation (RSD%)< 3.4%) and satisfactory reproducibility (RSD%<6.9%). The central composite design method was applied for the optimization of extraction parameters. Under the optimum conditions, linear dynamic ranges for biomarkers were in the acceptable range with correlation coefficients higher than 0.98. The detection limits of them were less down 0.0016 µg L−1. Self-healing ability of fiber coating increased useful lifetime (about 120 times extraction with one fiber) as well as accuracy, reproducibility, and recovery of fibers.

Synthetic biomarkers: a twenty-first century path to early cancer detection.

Detection of cancer at an early stage when it is still localized improves patient response to medical interventions for most cancer types. The success of screening tools such as cervical cytology to reduce mortality has spurred significant interest in new methods for early detection (for example, using non-invasive blood-based or biofluid-based biomarkers). Yet biomarkers shed from early lesions are limited by fundamental biological and mass transport barriers - such as short circulation times and blood dilution - that limit early detection. To address this issue, synthetic biomarkers are being developed. These represent an emerging class of diagnostics that deploy bioengineered sensors inside the body to query early-stage tumours and amplify disease signals to levels that could potentially exceed those of shed biomarkers. These strategies leverage design principles and advances from chemistry, synthetic biology and cell engineering. In this Review, we discuss the rationale for development of biofluid-based synthetic biomarkers. Weexamine how these strategies harness dysregulated features of tumours to amplify detection signals, use tumour-selective activation to increase specificity and leverage natural processing of bodily fluids (for example, blood, urine and proximal fluids) for easy detection. Finally, we highlight the challenges that exist for preclinical development and clinical translation of synthetic biomarker diagnostics.

TREND database: Retinal images of healthy young subjects visualized by a portable digital non-mydriatic fundus camera.

Topological characterization of the Retinal microvascular nEtwork visualized by portable fuNDus camera (TREND) is a database comprising of 72 color digital retinal images collected from the students of the Faculty of Medicine at the University of Montenegro, in the period from February 18th to March 11th 2020. The database also includes binarized images of manually segmented microvascular networks associated with each raw image. The participant demographic characteristics, health status, and social habits information such as age, sex, body mass index, smoking history, alcohol use, as well as previous medical history was collected. As proof of the concept, a smaller set of 10 color digital fundus images from healthy older participants is also included. Comparison of the microvascular parameters of these two sets of images demonstrate that digital fundus images recorded with a hand-held portable camera are able to capture the changes in patterns of microvascular network associated with aging. The raw images from the TREND database provide a standard that defines normal retinal anatomy and microvascular network geometry in young healthy people in Montenegro as it is seen with the digital hand-held portable non-mydriatic MiiS HORUS Scope DEC 200.This knowledge could facilitate the application of this technology at the primary level of health care for large scale telematic screening for complications of chronic diseases, such as hypertensive and diabetic retinopathy. In addition, it could aid in the development of new methods for early detection of age-related changes in the retina, systemic chronic diseases, as well as eye-specific diseases. The associated manually segmented images of the microvascular networks provide the standard that can be used for development of automatic software for image quality assessment, segmentation of microvascular network, and for computer-aided detection of pathological changes in retina. The TREND database is freely available at https://doi.org/10.5281/zenodo.4521043.

Deciphering Prunus Responses to PPV Infection: A Way toward the Use of Metabolomics Approach for the Diagnostic of Sharka Disease.

Sharka disease, caused by Plum pox virus (PPV), induces several changes in Prunus. In leaf tissues, the infection may cause oxidative stress and disrupt the photosynthetic process. Moreover, several defense responses can be activated after PPV infection and have been detected at the phytohormonal, transcriptomic, proteomic, and even translatome levels. As proposed in this review, some responses may be systemic and earlier to the onset of symptoms. Nevertheless, these changes are highly dependent among species, variety, sensitivity, and tissue type. In the case of fruit tissues, PPV infection can modify the ripening process, induced by an alteration of the primary metabolism, including sugars and organic acids, and secondary metabolism, including phenolic compounds. Interestingly, metabolomics is an emerging tool to better understand Prunus–PPV interactions mainly in primary and secondary metabolisms. Moreover, through untargeted metabolomics analyses, specific and early candidate biomarkers of PPV infection can be detected. Nevertheless, these candidate biomarkers need to be validated before being selected for a diagnostic or prognosis by targeted analyses. The development of a new method for early detection of PPV-infected trees would be crucial for better management of the outbreak, especially since there is no curative treatment.

A new method for early detection of latent infection by ‘Candidatus Liberibacter asiaticus’ in citrus trees

Background: ‘Candidatus Liberibacter asiaticus’ (CLas) is a major causal agent of citrus greening disease. The disease primarily involves an asymptomatic, often latent infection of CLas. However, there is no effective technique to distinguish latent-infected trees from healthy ones. This study describes the development of a new detection method for latent CLas infection using cuttings. Methods: Root tissues regenerated from cuttings using symptomatic and asymptomatic citrus trees were prepared for real-time a polymerase chain reaction (PCR) test which was used to investigate latent CLas. When some of the regenerated roots were negative for CLas in the first real-time PCR assay, a subsequent cultivation in soils was performed using the CLas-negative cuttings. CLas development during cultivation was evaluated by a second real-time PCR assay using soil-grown roots from seedlings. Results: Previously, CLas had not been detected from leaves of the latent-infected trees in our greenhouse by real-time PCR. In this study, however, CLas was detected at a moderate frequency from the root tissues of cuttings derived from the latent-infected trees, by the same PCR test. For cuttings with regenerated roots that tested negative for CLas by real-time PCR, CLas was frequently detected from roots grown in nursery soil with autoclaving, after cultivation for a month or more. Conclusions: Latent infection with CLas was detectable by real-time PCR using root tissues regenerated by cuttings and roots grown in nursery soil with autoclaving. These results suggest that the new method of investigation would provide great opportunities for early detection of CLas in asymptomatic citrus trees from field surveys, and would accelerate the eradication practice of citrus greening.

Prognosis of combustion instability in a gas turbine combustor using spectral centroid & spread

Premixed gas turbine decreases exhaust emission but is vulnerable to combustion instability. This paper proposes a new method for early detection of combustion instability that damages combustors, thereby helping to operate energy production system in a more stable way. The proposed method is based on analysis of the spectral centroid and the spectral spread of dynamic pressure so that it enables early recognition of periodic waveform generation. To validate this method, transient dynamic pressure data from single and multi-mode instabilities, obtained from the H2/CH4/CO flames in a model gas turbine combustor, are used. The effectiveness of the method is compared with that of two conventional methods based on a root-mean-square dynamic pressure and a temporal kurtosis. Among these three methods, the method using spectral features shows the best performance in terms of speed, sensitivity, and accuracy in detecting combustion instability. However, the spectral method sometimes misclassifies unstable flames as having a stable status when multi-mode combustion instability occurs. Therefore, spectral features are modified by weighting the amplitude of dynamic pressure oscillation, which shows better performance as a precursor for multi-mode combustion instability detection.

An Approach to Early Detection of Metabolic Syndrome through Non-Invasive Methods in Obese Children.

Background: Metabolic Syndrome (MetS) has a high prevalence in children, and its presence increases in those with a high BMI. This fact confirms the need for early detection to avoid the development of other comorbidities. Non-invasive variables are presented as a cost-effective and easy to apply alternative in any clinical setting. Aim: To propose a non-invasive method for the early diagnosis of MetS in overweight and obese Chilean children. Methods: We conducted a cross-sectional study on 221 children aged 6 to 11 years. We carried out multivariate logistic regressions, receiver operating characteristic curves, and discriminant analysis to determine the predictive capacity of non-invasive variables. The proposed new method for early detection of MetS is based on clinical decision trees. Results: The prevalence of MetS was 26.7%. The area under the curve for the BMI and waist circumference was 0.827 and 0.808, respectively. Two decision trees were calculated: the first included blood pressure (≥104.5/69 mmHg), BMI (≥23.5 Kg/m2) and WHtR (≥0.55); the second used BMI (≥23.5 Kg/m2) and WHtR (≥0.55), with validity index of 74.7% and 80.5%, respectively. Conclusions: Early detection of MetS is possible through non-invasive methods in overweight and obese children. Two models (Clinical decision trees) based on anthropometric (non-invasive) variables with acceptable validity indexes have been presented. Clinical decision trees can be applied in different clinical and non-clinical settings, adapting to the tools available, being an economical and easy to measurement option. These methods reduce the use of blood tests to those patients who require confirmation.

Familial tendency for hypertension is associated with increased vascular stiffness.

Hypertension is the leading cause of cardiovascular disease and premature death. New methods for early detection of hypertension and its consequences can reduce complications arising from uncontrolled hypertension. Pulse-wave velocity (PWV), a measure of arterial stiffness, has been recognized as a valuable tool in assessing risk for cardiovascular complications, although its use in clinical practice is currently limited. Here we examine whether brachial--ankle PWV (baPWV) and femoral--ankle PWV (faPWV) are elevated in nonhypertensive volunteers, with and without a history of familial hypertension. Volunteers were recruited and questioned as to their medical background and family history. Participants were divided into two groups based on history of familial hypertension and were measured for baPWV and faPWV. Carotid--femoral PWV was computed from these measurements. A total of 82 healthy nonhypertensive volunteers (mean age 31.4 ± 9.6) were recruited. Among the study cohort, 43.7% had a history of familial hypertension. There were no between-group differences in any other clinical or demographic characteristics. Both baPWV and faPWV were significantly elevated in volunteers with a history of familial hypertension (10.86 ± 1.69 vs. 9.68 ± 1.52 m/s, P < 0.004, and 7.01 ± 1.65 vs. 6.28 ± 1.26 m/s, P < 0.028, respectively). Volunteers with a history of familial hypertension present with elevated baPWV and faPWV. This is suggestive of increased central and peripheral arterial stiffness in susceptible individuals before the onset of hypertension. Routine measurement of these parameters may allow for early intervention and risk stratification, especially in persons with a history of familial hypertension.

A New Passive Microwave Tool for Operational Forest Fires Detection: A Case Study of Siberia in 2019

The purpose of this paper is to present a new method for early detection of forest fires, especially in forest zones prone to fires using microwave remote sensing and information-modeling tools. A decision-making system is developed as a tool for operational coupled analysis of modeling results and remote sensing data. The main operating structure of this system has blocks that calculate the moisture of forest canopy, the soil-litter layer, and the forest physical temperature using the observed brightness temperature provided by the flying platform IL-18 equipped with passive microwave radiometers of 1.43, 13.3 and 37.5 GHz frequencies. The hydrological parameters of the forest are assessed with both a developed regional hydrological model and remote sensing observations. The hydrological model allows for the detection of fire-prone zones that are subject to remote sensing when modeling results are corrected and thermal temperatures are evaluated. An approach for the real time forest fires classification via daytime remote sensing observations is proposed. The relative theoretical and experimental results presented here have allowed us to use a new approach to forests monitoring during periods of potential fire. A decision-making algorithm is presented that aims at analyzing data flows from radiometers located on the remote sensing platform to calculate the probability of forest fire occurring in geographical pixels. As case study, the state of forest fires that occurred in Siberia in 2019 using microwave remote sensing measurements conducted by a flying IL-18 laboratory is presented. This remote sensing platform is equipped with optical and microwave tools that allow the optical and microwave images of the observed forest areas. The main operating frequencies of microwave radiometers are 1.43, 13.3 and 37.5 GHz. Microwave radiometers provide data on water content in the forest canopy and on litter and physical temperatures. Based on the long-term measurements made in Siberia, the possible improvement of the proposed decision-making system for future relevant studies is discussed in detail. The basic idea of cost-effective monitoring of forested areas consists of a two-stage exploration of fire risk zones. The first monitoring stage is performed using the hydrological model of the study area to identify low moisture areas of the forest canopy and litter. The second stage of monitoring is conducted using the remote sensing platform only in the local fire-dangerous areas in order to more precisely identify the areas prone to fire and to detect and diagnose real burning zones. The developed algorithm allows the calculation of physical temperatures and the detection of temperature anomalies based on measured brightness temperatures. Finally, the spatial distribution of the probability of forest fire occurrence is given as an example of the decision-making system along with a comparison of this distribution with the satellite images provided by the EOSDIS Land data.

Early diagnosis of skin cancer by ultrasound frequency analysis.

The diagnosis of cancer by modern computer tools, at the very first stages of the incident, is a very important issue that has involved many researchers. In the meantime, skin cancer is a great deal of research because many people are involved with it. The purpose of this paper is to introduce an innovative method based on tissue frequency analyzes to obtain the accurate and real‐time evaluation of skin cancers. According to the Biological resonance theory, body cells have natural and unique frequencies based on their biological fluctuations, which, if the structure, profile and cellular status change, its frequency also varies. This concept and theory is considered as the basis for analyzing skin tissue health in the proposed method. Reflected ultrasound waves from tissue have been processed and studied based on frequency analysis as a new method for early detection and diagnosis of accurate location and type of skin diseases. The developed algorithm was approved through 400 patients from CRED; its ability to evaluate benign and malignant skin lesions was shown (AUC = 0.959), with comparable clinical precision; as for the selected threshold, sensitivity, and specificity were 93.8% and 97.3%, respectively. Therefore, this method can detect skin malignancy with an accurate, noninvasive and real‐time procedure.

Clinical Progress Note: Pediatric Acute Kidney Injury.

Acute kidney injury (AKI) occurs in 5%-30% of noncritically ill hospitalized children. Initially thought to be simply a symptom of more severe pathologies, it is now recognized that AKI independently increases mortality and is associated with the development of chronic kidney disease (CKD), even in children. The wide acceptance of the Kidney Disease Improving Global Outcome (KDIGO) diagnostic criteria has enabled a more uniform definition of AKI from both clinical and research perspectives. A better understanding of the pathophysiology and risk factors for AKI has led to new methods for early detection and prevention efforts. While serum creatinine (SCr) was historically one of the sole markers of AKI, novel biomarkers can facilitate earlier diagnosis of AKI, identify subclinical AKI, and guide clinical management. This clinical practice update addresses the latest clinical advances in risk assessment, diagnosis, and prevention of pediatric AKI, with a focus on AKI biomarkers.

Meeting report from the 2018 12th Biennial Ovarian Cancer Research Symposium detection and prevention of ovarian cancer

The objective of this review is to summarize recent research advances in the detection and prevention of ovarian cancer and discuss the experts’ opinions of future directions. The 12th Biennial...

A new method for early detection of pancreatic cancer biomarkers: detection of microRNAs by nanochannels

Objective To develop an effective new method for early detection of pancreatic cancer biomarkers and to aid early clinical diagnosis. Methods A DNA probe (Probe) capable of specifically recognizing the target miRNA was designed. The specific probe of miRNA 21 is designed first, and then mixed with the miRNA 21 sample to form a complex molecule, and the complex molecule is added to the nanochannels to detect the received signal. The probe is designed to detect the electrical signal by means of pre-matching and post-matching and observe the stability of the signal. The miRNA 21, miRNA 155, miRNA 196a were added to the nano-single channel to detect the characteristic signals and blocking time. The miRNA 21·probe 21 mixture was mixed with other five cancer-associated microRNAs, and the signal results of the detection were collected and compared. Results The signal of miRNA 21 was successfully detected. Whether the probe is designed at the front or the back, there are two signal results. The Probe should be designed to match the middle region of the miRNA. The three microRNA complex molecules have different characteristic signals and blocking times, which can be effectively distinguished. Conclusion Nanochannels can effectively detect pancreatic cancer-related microRNAs.