Sensors & diagnostics最新文献

Reckoning the significance of next-generation biosensors and point-of-care sensors, scientists are interested in developing superior nanomaterials with advantageous characteristics that can serve as electrode modifiers in the development of functional devices. MXenes are a broad class of two-dimensional metal carbides and nitrides characterized by their exceptional hydrophilicity, high specific surface area, and high conductivity. MXenes and their derived nanocomposites are presently gaining importance as electrode materials for the electrochemical detection of various biomarkers. This review assesses and summarises current notable accomplishments in the concepts, fabrication, and diverse applications of MXene-based nanocomposites for electrochemical monitoring of a variety of clinically relevant biomarkers. Furthermore, an outline of the existing impediments linked to technological advancement is included, accompanied by proposals for further investigation into the issues.

Given the susceptibility of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) and Norovirus (NoV) to survive in cold chain food, thereby posing significant public health risks, we present a novel approach for biosensor development utilizing a graphene field-effect transistor (GFET) modified with nucleic acid aptamers. The biosensor's innovative design incorporates 1-pyrenebutyric acid N-hydroxysuccinimide ester (PBASE) as a coupling agent to facilitate the attachment of nucleic acid aptamers onto channel graphene. This modification induces a redistribution of charge on the graphene surface, resulting in a shift of the Dirac point upon target capture by the nucleic acid aptamer. Through this pioneering methodology, we successfully engineered SARS-CoV-2 GFET and NoV GFET biosensors capable of detecting trace amounts of SARS-CoV-2 and norovirus within a rapid 5-minute timeframe, showcasing detection limits of 33 fg mL⁻¹ and 6.17 pg mL⁻¹, respectively. Subsequently, we applied these sensors to detect SARS-CoV-2 in frozen meat and norovirus in shellfish, yielding promising results with excellent specificity and stability. This groundbreaking sensing mechanism holds significant promise for the detection of foodborne viruses across a diverse range of food samples.

Electrochemical aptamer-based (EAB) sensors represent a promising biosensing platform, leveraging the selectivity of aptamers and the advantages of electrochemical methods. These sensors offer high sensitivity, rapid response, low limits of detection, cost-effectiveness, and miniaturization potential. While gold electrodes have been predominantly used in EAB sensors, alternatives such as carbon nanotubes (CNTs) are gaining attention. CNTs offer advantages like large surface area and conductivity but pose challenges due to their reactivity and 3D network structure. In this study, we explore the development of EAB sensors using single-wall carbon nanotube (SWCNT) networks, emphasizing on the challenges and electroanalytical insights. Three key electrochemical parameters are proposed for assessing EAB sensor performance: (i) variations in peak current, (ii) shifts in peak position, and (iii) the restoration of the background current. Focusing solely on peak current changes can be misleading, as factors like aptamer surface depletion can influence it. Additionally, both partial and integrated currents should be monitored in square wave voltammetry (SWV) analysis, considering both ON and OFF behaviours across frequencies. This comprehensive approach provides a preliminary assessment of successful binding and surface passivation in EAB sensors when combined with surface analytical techniques such as surface plasmon resonance (SPR) measurements.

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We present an analysis of the molecular vibrational assessments of different grades of oral precancerous tissue sections, aiming to an early, alternative method other than histopathology to definitively distinguish their grades and remove the interobserver variability related to histopathological grading. Assessment of the prognosis of oral potentially malignant disorders (OPMDs) is dependent only on clinical features, and no defined criteria are still proposed to analyze the treatment outcome. Chair-side analysis of the lymph node metastasis and staging of oral squamous cell carcinoma (OSCC) is also dependent on palpatory findings followed by magnetic resonance imaging (MRI). Among these, Fourier-transform infrared (FTIR) micro-spectroscopy emerges as a highly promising and versatile approach for analyzing oral cancer and precancer specimens, enabling the identification of chemical and molecular changes in tissue samples. In this work, an adequate number of tissue sections affected by different grades of precancer (mild dysplasia, moderate dysplasia, and severe dysplasia) were investigated for biochemical changes in the epithelium and sub-epithelium layers as characterized by their corresponding molecular vibration spectrum. The current study demonstrated distinct alterations based on the spectrum shift of proteins (particularly amide I and amide III) over the progression of precancer. Additionally, using the amide I and amide III regions, a peak fitting method was employed to estimate the secondary structures of proteins. Further, chemometric techniques of principal components analysis–linear discriminant analysis (PCA–LDA) were used to create discrimination models for the precancerous and control groups. Our investigation revealed that the predictive performance of the amide III region was better than that of the amide I region, achieving a 95% accuracy rate. To the best of our knowledge, this is one of the first studies on the application of FTIR micro-spectroscopy for the classification of oral precancers in humans, aided by machine learning.

A novel and efficient thiosemicarbazone based chemosensor for the detection of transition metals through UV-visible fluorescence has been reported in this research. Dibenzyl thiosemicarbazones can bind with the transition metal ions and lead to the enhancement of the fluorescence. The reported dibenzyl thiosemicarbazone can detect Zn²⁺, Co²⁺, Ni²⁺ and Hg²⁺ appreciably due to inhibition of electron transfer while quenching of fluorescence occurs in Mn²⁺ and Cu²⁺ due to photoinduced electron transfer.

Ethanol gas excreted by human skin can be used to determine auto-brewery syndrome (drunken disease), blood alcohol levels, and/or a body state of alcoholism. Considering the limitations of continuous non-invasive alcohol gas monitoring based on the electrochemical method, which requires high sensitivity and selectivity, a CNF film sensor was developed. This sensor was developed by utilizing pyrroloquinoline quinone-dependent alcohol dehydrogenase (PQQ-ADH) and multiwalled carbon nanotubes (MWCNTs) based on cellulose nanofiber (CNF) film platform. With a compact design, a PQQ-ADH/MWCNTs/CNF film sensor was built in a three-electrode system. This system could continuously detect ethanol gas with ultra-high sensitivity, a wide detection range (24 ppb–25 ppm), and high selectivity for ethanol. Finally, the CNF film sensor was used for ethanol gas monitoring in the human subject, and we were able to detect metabolism abnormalities of the subject by analyzing the declining slope (detoxification rate) of the ethanol gas concentration monitored. The CNF film sensor aims to gain valuable insights and enhance future standard health screening practices through non-invasive wearable daily monitoring sensors.

Herein, a chromone-based simple reversible fluorescent “turn-on” probe, HMCP [6-(hydroxymethyl)-N′-((6-methyl-4-oxo-4H-chromen-3-yl)methylene)picolinohydrazide], was successfully utilized to detect Al³⁺ over a group of other coexisting metal cations in MeOH/H₂O (9 : 1, v/v) (HEPES buffer, pH = 7.2). The “turn on” emission response along with the effective enhancement of the fluorescence intensity upon addition of Al³⁺ can be attributed to the inhibition of photo-induced electron transfer (PET) and CN isomerization, as well as the initiation of chelation-enhanced-fluorescence (CHEF). The HMCP sensor binds Al³⁺ in a 1 : 1 stoichiometry with an excellent binding constant and good detection limit on the orders of 10³ M⁻¹ and 10⁻⁷ M, respectively. The mode of binding interaction between HMCP with Al³⁺ was evidenced by ¹H NMR titration, HRMS, and Job's plot analyses. Theoretical calculations and molecular logic gate applications were also used to demonstrate the binding mode. A DNA binding study was also executed to elucidate the possible bioactivity of the probe and found that HMCP interacts with DNA more effectively than the other analogues studied. Furthermore, the applicability of the probe in a live cell imaging study indicated that HMCP is highly efficient for the detection of exogenous Al³⁺ in living cells. In addition, real water sample analysis and a dip-stick experiment demonstrate that the probe can be used in a wide range of practical and convenient applications.

Novel biomaterials that bridge the knowledge gap in coupling molecular/protein signatures of disease/stress with rapid readouts are a critical need of society. One such scenario is an imbalance between bodily heat production and heat dissipation which leads to heat stress in organisms. In addition to diminished animal well-being, heat stress is detrimental to the poultry industry as poultry entails fast growth and high yields, resulting in greater metabolic activity and higher body heat production. When stressed, cells overexpress heat shock proteins (such as HSP70, a well-established intracellular stress indicator) and may undergo changes in their mechanical properties. Liquid crystals (LCs, fluids with orientational order) are facile sensors as they can readily transduce chemical signals to easily observable optical responses. In this work, we introduce a hybrid LC–cell biomaterial within which the difference in the expression of HSP70 is linked to optical changes in the response pattern via the use of convolutional neural networks (CNNs). The machine-learning (ML) models were trained on hundreds of such LC-response micrographs of chicken red blood cells with and without heat stress. The trained models exhibited remarkable accuracy of up to 99% on detecting the presence of heat stress in unseen microscopy samples. We also show that cross-linking chicken and human RBCs using glutaraldehyde in order to simulate a diseased cell was an efficient strategy for planning, building, training, and evaluating ML models. Overall, our efforts build towards designing biomaterials that can rapidly detect disease in organisms that is accompanied by a distinct change in the mechanical properties of cells. We aim to eventuate CNN-enabled LC-sensors that can rapidly report the presence of disease in scenarios where human judgment could be prohibitively difficult or slow.

Chronic kidney disease (CKD) is a growing global health concern, necessitating early and accurate diagnostic tools to manage and mitigate its progression. Point-of-care (POC) biosensors and devices offer a promising solution for rapid, cost-effective, and accessible diagnostics. This review explores the latest advancements in POC biosensors and devices specifically designed for CKD diagnostics. In this review, we discuss the biosensors most likely to achieve on-site detection of CKD, focusing on their design and application in real samples, including electrochemical, fluorescent, and colorimetric sensors. Also, the innovative platforms are summarized from lateral flow devices, lab-on-a-chip devices, and microfluidic-based devices. The potential of these technologies for real-time monitoring, early detection, and personalized treatment is underscored. The review concludes by envisioning future perspectives and the transformative impact of POC biosensors in CKD diagnostics, aiming to improve patient outcomes and healthcare efficiency.