Non-invasive Disease Diagnosis Research Articles

Применение метода абсорбционной диодной лазерной спектроскопии для измерения содержания -=SUP=-13-=/SUP=-С и -=SUP=-12-=/SUP=-С в выдыхаемом воздухе

The paper reports on experimental studies of the absorption of 13C16O2 in a mixture with 12C16O2 in exhaled air by laser absorption spectroscopy using a diode laser tunable in the frequency range 4860-4880 cm-1. The results of the studies showed that the minimum detectable concentration of 13C16O2 is at a level of less than 20 ppm, and this approach is promising for measuring the content of 13C16O2 in exhaled air for non-invasive online diagnosis of oncological diseases of the gastrointestinal tract at early stages

A Novel Portable Unilateral Magnetic Resonance Magnet for Noninvasive Quantification of Human Liver Fat

Fatty liver disease has become one of the common liver diseases seriously affecting people’s health and quality of life. Existing means to quantify liver fat content are usually invasive and high-cost. Our research aims to design a single-sided magnet to develop a low-cost, non-invasive, and lightweight unilateral magnetic resonance (UMR) system that can satisfy the needs for fatty liver screening and diagnosis. A novel single-sided permanent magnet with a pear-shaped magnetic field iso-surface was designed to avoid the excitation of subcutaneous tissue in the human body. The weight of the magnet was optimized to 12.9 kg, and the mean magnetic field strength of the region of interest (ROI) was 0.07 T. The radio frequency (RF) coil set, the pulse sequence, and the modeling method for measuring proton density fat fraction (PDFF) were also introduced. Experiments for phantoms and volunteers were carried out by the UMR system to verify the performance of detection. The phantom detection results show that the UMR system can effectively avoid the influence of the subcutaneous tissue part on PDFF detection, with reasonable accuracy (around 5% fat fraction error) and robustness (within 10% relative error). Compared with a conventional MRI scanner, measurement results of volunteers (around 3% fat fraction error) show the effectiveness of the UMR system for screening fatty liver diseases. The UMR system developed based on the proposed portable single-sided magnet could be a low-cost and reliable diagnostic tool for noninvasive fatty liver disease diagnosis.

In situ assembly of one-dimensional Pt@ZnO nanofibers driven by a ZIF-8 framework for achieving a high-performance acetone sensor.

To obtain a high-performance gas sensor, it is essential to ingeniously design sensing materials containing the features of high catalytic performance, abundant oxygen vacancies, and splendid grain dispersibility through a simple method. Inspired by the fact that ZIF-8 contains semiconductor metal atoms, well-arranged ZnO nanoparticle (NP)-in situ assembled one-dimensional nanofibers (NFs) are obtained by one-step electrospinning. By incorporating Pt NPs into the cavity of ZIF-8 NPs, well-dispersed Pt@ZnO NPs driven by Pt@ZIF-8 composites are obtained after annealing. The well-arranged Pt@ZnO NP-assembled NFs not only exhibit abundant oxygen vacancies but also avoid the self-aggregation of ZnO and Pt NPs. Meanwhile, the small Pt NPs could improve the catalytic effect in return. Therefore, the gas sensor fabricated based on the above materials exhibits an acetone sensitivity of 6.1 at 370 °C, compared with pristine ZnO NFs (1.6, 5 ppm). Moreover, the well-arranged Pt@ZnO NP-assembled NFs show exceptional sensitivity to acetone with a 70.2 ppb-level detection limit in theory. The synergistic advantages of the designed sensing material open up new possibilities for non-invasive disease diagnosis.

The Latest Developments in Using Proteomic Biomarkers from Urine and Serum for Non-Invasive Disease Diagnosis and Prognosis.

Due to diagnostic improvements, medical diagnostics is demanding non-invasive or minimally invasive methods. Non-invasively obtained body fluids (eg., Urine, serum) can replace cerebral fluid, amniotic fluid, synovial fluid, bronchoalveolar lavage fluid, and others for diagnostic reasons. Many illnesses are induced by perturbations of cellular signaling pathways and associated pathway networks as a result of genetic abnormalities. These disturbances are represented by a shift in the protein composition of the fluids surrounding the tissues and organs that is, tissue interstitial fluid (TIF). These variant proteins may serve as diagnostic "signatures" for a variety of disorders. This review provides a concise summary of urine and serum biomarkers that may be used for the diagnosis and prognosis of a variety of disorders, including cancer, brain diseases, kidney diseases, and other system diseases. The studies reviewed in this article suggest that serum and urine biomarkers of various illnesses may be therapeutically useful for future diagnostics. Correct illness management is crucial for disease prognosis, hence non-invasive serum and urine biomarkers have been extensively studied for diagnosis, subclassification, monitoring disease activity, and predicting treatment results and consequences.

Resonant Inertial Mass Sensing for VOCs—CMOS-Compatible SoC Integration Advantages and Challenges: A Review

Volatile organic compounds (VOCs) have gained the biomedical community’s attention given their relevance in exhaled human breath analysis for noninvasive disease diagnosis. Today, only bulky, expensive, and high-skill bench-top equipment is commercially available to reach the outstanding resolution and selectivity required for their detection. However, these solutions fail to meet the society demands of portable and low-cost devices required for point-of-care diagnosis and e-health. In this line, resonant inertial mass sensing has emerged as a promising technique to achieve high-resolution VOCs’ identification, fulfilling the portability requirements. Their excellent distributed mass sensitivity and integration capabilities within standard CMOS microfabrication techniques constitute excellent candidates for building lab-on-chip applications in line with current technological trends. The capability of operating as self-sustained oscillators provides an inherent real-time tracking system with quasi-digital output. Resonator coating using novel sensing films for specific analyte caption is required to boost the mass loading effect and improve sensing selectivity. This article reviews and analyzes the resonator topologies proposed in the literature together with the techniques used for electromechanical transduction, as well as coating materials and procedures. The ultimate goal is to discuss the advantages achieved for CMOS fully integrated solutions, analyzing the state of the art in the field and providing specific design guidelines while foreseeing upcoming trends.

Noninvasive Prenatal Diagnosis of Beta-Thalassemia Disease by Using Digital PCR Analysis of Cell-Free Fetal DNA in Maternal Plasma

Introduction: Prenatal diagnosis of thalassemia disease was usually based on invasive technique. Noninvasive diagnosis using cell-free fetal DNA (cff-DNA) was described with various laboratory techniques. The aim of this study was to identify the performance of dPCR for analyzing cff-DNA in maternal plasma to diagnose fetal beta-thalassemia diseases. Methods: Thirty-five couples at risk of fetal beta-thalassemia disease caused by four common mutations of HBB were enrolled at 12–18 weeks. The dPCR assay was designed to detect and quantify paternally inherited beta-thalassemia allele (PIB) and maternally inherited beta-thalassemia allele (MIB) from cff-DNA in maternal plasma. Results: Of 29 couples with different paternal/maternal mutations, all cases who inherited paternal mutation had detectable PIB-M. The MIB-mutant/wild-type (MIB-M/MIB-N) ratio in the mothers whose fetuses did not inherit maternal mutation was 0.87 ± 0.07 which was significantly lower than that of the mothers whose fetuses inherited maternal mutation, 1.01 ± 0.05. The sensitivity and specificity of MIB-M/MIB-N ratio >0.95 in predicting fetus inheriting maternal mutation were 100 and 92.3%, respectively. In four couples with same paternal/maternal mutation, IB-M/IB-N ratio of >0.95 correctly predicted the presence of an inheritance of at least one beta-thalassemia allele. In two couples with paternal Hb E/beta-thalassemia, the presence of PIB-M and the MIB-M/MIB-N ratio of >0.95 correctly predicted the presence of paternal/maternal mutations, respectively. Conclusions: The method of analyzing cff-DNA in maternal plasma by dPCR is efficient for prenatal diagnosis of beta-thalassemia.

Wearable High-Density MXene-Bioelectronics for Neuromuscular Diagnostics, Rehabilitation, and Assistive Technologies.

High-density surface electromyography (HDsEMG) allows noninvasive muscle monitoring and disease diagnosis. Clinical translation of current HDsEMG technologies is hampered by cost, limited scalability, low usability, and minimal spatial coverage. Here, this study presents, validates, and demonstrates the broad clinical applicability of dry wearable MXene HDsEMG arrays (MXtrodes) fabricated from safe and scalable liquid-phase processing of Ti3 C2 Tx . The fabrication scheme allows easy customization of array geometry to match subject anatomy, while the gel-free and minimal skin preparation enhance usability and comfort. The low impedance and high conductivity of the MXtrode arrays allow detection of the activity of large muscle groups at higher quality and spatial resolution than state-of-the-art wireless electromyography sensors, and in realistic clinical scenarios. To demonstrate the clinical applicability of MXtrodes in the context of neuromuscular diagnostics and rehabilitation, simultaneous HDsEMG and biomechanical mapping of muscle groups across the whole calf during various tasks, ranging from controlled contractions to walking is shown. Finally, the integration of HDsEMG acquired with MXtrodes with a machine learning pipeline and the accurate prediction of the phases of human gait are shown. Theresults underscore the advantages and translatability of MXene-based wearable bioelectronics for studying neuromuscular function and disease, as well as for precision rehabilitation.

Cell-Free Fetal DNA and Non-Invasive Prenatal Diagnosis of Chromosomopathies and Pediatric Monogenic Diseases: A Critical Appraisal and Medicolegal Remarks.

Cell-free fetal DNA (cffDNA) analysis is a non-invasive prenatal diagnostic test with a fundamental role for the screening of chromosomic or monogenic pathologies of the fetus. Its administration is performed by fetal DNA detection in the mother's blood from the fourth week of gestation. Given the great interest regarding its validation as a diagnostic tool, the authors have set out to undertake a critical appraisal based on a wide-ranging narrative review of 45 total studies centered around such techniques. Both chromosomopathies and monogenic diseases were taken into account and systematically discussed and elucidated. Not surprisingly, cell-free fetal DNA analysis for screening purposes is already rather well-established. At the same time, considerable interest in its diagnostic value has emerged from this literature review, which recommends the elaboration of appropriate validation studies, as well as a broad discourse, involving all stakeholders, to address the legal and ethical complexities that such techniques entail.

Modern Radiation Diagnostics and Intelligent Personalized Technologies in Hepatopancreatology

Timely instrumental diagnosis of diseases of the hepatopancreatoduodenal region, especially of an oncological nature, is the key to successful treatment, improving prognosis and improving the quality of life of patients. At the moment, the possibilities of radiation diagnostics make it possible to identify and evaluate the nature of the blood supply to the neoplasm, its prevalence, cellularity, and in the case of MRI studies with hepatospecific contrast agents, also evaluate the functional activity of liver cells. Nevertheless, the steady development of methods for treating cancer patients, in particular, chemotherapy, and a personalized approach to the choice of patient management tactics require a detailed assessment of the morphological types of certain neoplasms. The need for dynamic monitoring of the results of treatment, monitoring of accidentally detected, potentially malignant neoplasms, and the development of screening programs determine the steady increase in the number of CT and MR examinations performed annually in the world and in our country. These factors have led to the application of texture analysis or radiomics and machine learning algorithms. At the same time, such techniques as radiography, ultrasound, CT and MRI with extracellular and tissue-specific contrast enhancement, and MRI-DWI do not lose their significance. The ongoing research allows the Federal State Budgetary Institution National Medical Research Center of Surgery named after A.V. Vishnevsky of the Ministry of Health of Russia to implement the concept of preoperative non-invasive diagnosis and differential diagnosis of surgical and oncological diseases of the hepatopancreatoduodenal region and apply the knowledge gained in planning surgical treatment. Implementation of the problem of post-processor data processing of radiation diagnostics of surgical and oncological diseases of the hepatopancreatoduodenal region using radiomics and AI technologies is important and extremely relevant for modern medicine.

Giada Sebastiani: a leading voice on liver fibrosis

Giada Sebastiani has always believed that unless something is actually impossible, then with enough self-belief it can be achieved. Her motto is “Never, never give up”. Born and raised in the mainland part of Venice, Italy, she chose medicine to ask and answer questions with science and satisfy her philanthropic need to help others. “I saw that medicine would fit all these tendencies”, Sebastiani tells The Lancet Gastroenterology & Hepatology. Today, she is a hepatologist and the Research Director of the Division of Gastroenterology and Hepatology at McGill University Health Centre in Montreal, Canada, where her principal focus is non-alcoholic fatty liver disease (NAFLD) and non-invasive diagnosis of liver disease.

Haplotype-Assisted Noninvasive Prenatal Diagnosis of Genetic Diseases by Massively Parallel Sequencing of Maternal Plasma Cell-Free DNA.

Early prenatal diagnosis of genetic diseases allows for timely intervention or prevention of thediseases in newborns. Conventional prenatal diagnosis of most genetic diseases relies on testing fetal DNA obtained by invasive procedures such as amniocentesis or chorionic villus sampling, which are associated with small risks of fetal loss. Maternal circulating blood contains cell-free DNA (cfDNA) from the fetal genome and can thus be used to noninvasively detect fetal genetic diseases such as chromosomal abnormalities, copy number variants, and single gene diseases. However, due to the presence of a high level of maternal cfDNA in the maternal blood stream, a relative haplotype dosage (RHDO) analysis is required to detect the mutant loci in the fetal genome when performing noninvasive prenatal diagnosis (NIPD) by massively parallel sequencing (MPS) of cfDNA. In this chapter, we describe a protocol utilizing the RHDO strategy for NIPD of any gene of interest associating with single gene diseases.

Biocompatible engineered erythrocytes as plasmonic sensor initiators for high-sensitive screening of non-small cell lung cancer-derived exosomal miRNA in an integrated system

The development of a holistic solution is crucial for exosome-based liquid biopsy, which is a significant advancement from basic research to clinical application for the early and non-invasive diagnosis of disease. However, the challenge of current technology is how to facilitate the separation and quickly connect with the detection. Herein, employing miRNA-155 as a target, a novel integrated concentration and determination system of exosomes (ICDSE) was fabricated for the targeted enrichment of exosomes from the plasma of patients with non-small cell lung cancer and instant downstream analysis of exosomal miRNA. This ICDSE consists of aptamer-engineered erythrocytes with a supramolecular plasmonic biosensor. The streamlined analytical procedure benefited from engineered erythrocytes as an interlinkage, needlessly removing them before extracting total RNA due to the lack of nuclei. With the assistance of a specific aptamer and simple centrifugation, engineered erythrocytes achieved exceptional enrichment of exosomes within 30 min. The LOD of the biosensor for miR-155 approached 2.03 fM due to the substantially high refractive index of the quadruplet supramolecular dendrimer and zirconium metal-organic framework. Impressively, the developed ICDSE successfully isolated and evaluated exosomes from clinical specimens of patients with NSCLC, which can also be promising for other diseases with identifiable exosome signatures. Thus, our ICDSE is expected to have widespread biomedical applications, as it is economical and well-accepted.

A Parallel Spiking Neural Network Based on Adaptive Lateral Inhibition Mechanism for Objective Recognition.

Spiking neural network (SNN) has attracted extensive attention in the field of machine learning because of its biological interpretability and low power consumption. However, the accuracy of pattern recognition cannot completely surpass deep neural networks (DNNs). The main reason is that the inherent nondifferentiability of spiking neurons makes SNN unable to be trained directly by the gradient descent algorithm, and there is also no unified training algorithm for SNN. Inspired by the biological vision system, this paper proposes a parallel convolution SNN structure combined with an adaptive lateral inhibition mechanism. And, a way of dynamically evolving the time constant with the training of SNN is proposed to ensure the diversity of neurons. This paper verifies the effectiveness of the proposed methods on static datasets and neuromorphic datasets and extends it to the recognition of breast tumors. Experimental results show that the SNN has obvious advantages in dynamical datasets. For breast tumors, it is also an edge-based task, because the edge of a medical image contains the most important information in the image. This kind of information can provide great help for the noninvasive and accurate diagnosis of diseases. The Experimental results show that the proposed method is very close to the recognition results of DNNs on static datasets, and its performance on neuromorphic datasets exceeds that of DNNs.

Artificial intelligence in cardiology: Hope for the future and power for the present.

Cardiovascular disease (CVD) is the principal cause of mortality and morbidity globally. With the pressures for improved care and translation of the latest medical advances and knowledge to an actionable plan, clinical decision-making for cardiologists is challenging. Artificial Intelligence (AI) is a field in computer science that studies the design of intelligent agents which take the best feasible action in a situation. It incorporates the use of computational algorithms which simulate and perform tasks that traditionally require human intelligence such as problem solving and learning. Whilst medicine is arguably the last to apply AI in its everyday routine, cardiology is at the forefront of AI revolution in the medical field. The development of AI methods for accurate prediction of CVD outcomes, non-invasive diagnosis of coronary artery disease (CAD), detection of malignant arrythmias through wearables, and diagnosis, treatment strategies and prediction of outcomes for heart failure (HF) patients, demonstrates the potential of AI in future cardiology. With the advancements of AI, Internet of Things (IoT) and the promotion of precision medicine, the future of cardiology will be heavily based on these innovative digital technologies. Despite this, ethical dilemmas regarding the implementation of AI technologies in real-world are still unaddressed.

Modular Assembly of MXene Frameworks for Noninvasive Disease Diagnosis via Urinary Volatiles.

Volatile organic compounds (VOCs) in urine are valuable biomarkers for noninvasive disease diagnosis. Herein, a facile coordination-driven modular assembly strategy is used for developing a library of gas-sensing materials based on porous MXene frameworks (MFs). Taking advantage of modules with diverse composition and tunable structure, our MFs-based library can provide more choices to satisfy gas-sensing demands. Meanwhile, the laser-induced graphene interdigital electrodes array and microchamber are laser-engraved for the assembly of a microchamber-hosted MF (MHMF) e-nose. Our MHMF e-nose possesses high-discriminative pattern recognition for simultaneous sensing and distinguishing of complex VOCs. Furthermore, with the MHMF e-nose being a plug-and-play module, a point-of-care testing (POCT) platform is modularly assembled for wireless and real-time monitoring of urinary volatiles from clinical samples. By virtue of machine learning, our POCT platform achieves noninvasive diagnosis of multiple diseases with a high accuracy of 91.7%, providing a favorable opportunity for early disease diagnosis, disease course monitoring, and relevant research.

Application of smart responsive materials in phosphopeptide and glycopeptide enrichment

蛋白质的磷酸化和糖基化作为研究最广泛的两种翻译后修饰(PTMs),在疾病的早期无创诊断、预后和治疗评估中表现出越来越大的潜力。蛋白质的异常磷酸化和糖基化经常被用于临床蛋白质组学研究和疾病相关生物标志物的发现。目前已有多种材料被开发用于磷酸化肽和糖肽的富集研究,其中,智能响应材料由于具有独特的响应特性,已被陆续报道用于磷酸化肽和糖肽的富集。智能响应材料可对外界刺激做出响应,发生结构和性质上的变化,将光、电、热、机械等信号转化为生物化学信号。响应分子是决定智能响应材料响应特性的先决条件,它们在不同刺激条件下(如温度、pH、光、机械应力、电磁场等)的可逆异构化将导致材料的宏观物理和化学性质的动态变化。与传统材料相比,智能响应材料可以可逆地“打开”和“关闭”,具有更好的可调控性。由于引起智能材料响应的刺激信号对其性能具有重要的影响,综述根据施加的刺激种类对智能响应材料进行分类,具体分为外源性响应材料和内源性响应材料,且分别总结了外源性响应材料、内源性响应材料以及内外源共同响应材料在磷酸化肽和糖肽富集方面的工作。此外,综述对智能响应材料在磷酸化肽和糖肽富集方面的发展前景进行了展望,并且提出了智能响应材料在其他蛋白质翻译后修饰方面的应用中存在的挑战。

Thrilling AI – A novel, signal-based digital biomarker for diagnosing canine heart diseases

Abstract Auscultation methods enable non-invasive diagnosis of diseases, e.g. of the heart, based on heartbeat sounds. Regular, early examinations using machine learning techniques could help to detect diseases at an early stage to prevent serious health conditions and then provide optimal therapy through continuous monitoring. There is already a lot of work on human data using AI algorithms to detect patterns in signals or images. However, there is hardly no work on detecting heart murmurs with digital such as Myxomatous Mitral Valve Disease. In this paper, we present a canine auscultation project that aims to provide a tool to establish a baseline of classification parameters from audio signals that could be used to monitor canine health status by analyzing deviations from this baseline. In the future, data analysis could also lead to prediction and early detection of other diseases.

Non-invasive diagnosis, antithrombotic treatment, and invasive management of ischaemic heart disease.

Non-invasive diagnosis, antithrombotic treatment, and invasive management of ischaemic heart disease.

Early Detection of Skin Disorders and Diseases Using Radiometry

Skin diseases and disorders have a significant impact on people’s health and quality of life. Current medical practice suggests different methodologies for detecting and diagnosing skin diseases and conditions. Most of these require medical tests, laboratory analyses, images, and healthcare professionals to assess the results. This consumes time, money, and effort, and the waiting time is stressful for the patient. Therefore, it is an essential requirement to develop a new automatic method for the non-invasive diagnosis of skin diseases and disorders without the need for healthcare professionals or being in a medical clinic. This research proposes millimeter-wave (MMW) radiometry as a non-contact sensor for the non-invasive diagnosis of skin diseases and conditions. Reflectance measurements performed using 90 GHz radiometry were conducted on two samples of participants; sample 1 consisted of 60 participants (30 males and 30 females) with healthy skin, and sample 2 contained 60 participants (30 males and 30 females) suffering from skin diseases and conditions, which were: basal cell carcinoma (BCC), squamous cell carcinoma (SCC), burn wounds, and eczema. Radiometric measurements show substantial differences in reflectance in the range of 0.02–0.27 between healthy and unhealthy regions of the skin on the same person. These results indicate that radiometry, as a non-contact sensor, can identify and distinguish between healthy and diseased regions of the skin. This indicates the potential of using radiometry as a non-invasive technique for the early detection of skin diseases and disorders.

Humidity-Tolerant Room-Temperature Selective Dual Sensing and Discrimination of NH3 and NO Using a WS2/MWCNT Composite.

Continuous detection of toxic and hazardous gases like nitric oxide (NO) and ammonia (NH3) is needed for environmental management and noninvasive diagnosis of various diseases. However, to the best of our knowledge, dual detection of these two gases has not been previously reported. To address the challenge, we demonstrate the design and fabrication of low-cost NH3 and NO dual gas sensors using tungsten disulfide/multiwall carbon nanotube (WS2/MWCNT) nanocomposites as sensing channels which maintained their performance in a humid environment. The composite-based device has shown successful dual detection at temperatures down to 18 °C and relative humidity of 90%. For 0.1 ppm ammonia, it exhibited a p-type conduction with response and recovery times of 102 and 261 s, respectively; on the other hand, with NO (10 ppb, n-type), these times were 285 and 198 s, respectively. The device with 5 mg MWCNTs possesses a superior selectivity along with a relative response of ≈7% (5 ppb) and ≈5% (0.1 ppm) for NO and NH3, respectively, at 18 °C. The response is less affected by relative humidity, and this is attributed to the presence of MWCNTs that are hydrophobic in nature. Upon simultaneous exposure to NO (5-10 ppb) and NH3 (0.1-5 ppm), the response was dominated by NO, implying clear discrimination to the simultaneous presence of these two gases. We propose a sensing mechanism based on adsorption/desportion and accompanied charge transfer between the adsorbed gas molecules and sensing surface. The results suggest that an optimized weight ratio of WS2 and MWCNTs could govern favorable sensing conditions for a particular gas molecule.