Aflatoxins are among the main carcinogens threatening food safety, while imposing severe detection challenges due to their localized presence and undetectability by visual inspection. We present the use of fluorescence spectroscopy for a non-destructive and sensitive detection of aflatoxins, starting from a laboratory research-grade characterization to its integration in a handheld unit. As a case-study, aflatoxin detection in maize and pistachio is considered. The present aflatoxin influences the natural background fluorescence dependent on the matrix of the food products. Both one- and two photon induced fluorescence are compared, indicating one-photon induced fluorescence as most suited for miniaturization. A compact sensing unit, comprising UV LED excitation (365nm) and fluorescence detection into a single handheld device is presented, showing a promising sensitivity differentiating aflatoxin concentration differences of only 0.6 µg/kg, while complying to the European regulations, paving the way towards an increased food safety.

The huge surge in smartphone users in the last decade has provided an unprecedented opportunity for App-based diagnosis of infectious and chronic diseases. The internet access has further enhanced the prospects of smartphone-based diagnosis as the data captured can be stored in cloud, analyzed remotely and, the finding may then be placed onto the cloud or communicated through the phone. In this work, commercially available urine strips (Uristix Siemens), chemically impregnated with Bromophenol blue, were used to quantify the concentrations of albumin using a smartphone device i.e. iPhone SE. A Tungsten lamp of color temperature 3500 K was used to illuminate the urine strips. The images of the dipstick after being dipped into different concentrations were captured using a smartphone. The RGB color values were converted into tristimulus values to calibrate the chromaticity curve. Further, the concentration of test samples was calculated using a calibration curve based on a nearest neighbour algorithm. Calibration was done using six different albumin concentrations: 160 mg/L, 320 mg/L, 640 mg/L, 2560 mg/L, 5120 mg/L, and 10240 mg/L. We were able to estimate the albumin concentration in the range of 160 - 10240 mg/L using the proposed algorithm. Three different illuminations i. e. 500 Lux, 400 Lux, and 300 Lux were used to check the robustness of the algorithm. The correlation coefficient for the estimation of albumin concentration was found to be ~ 0.94. This may help to monitor the progression of kidney disease and cardiovascular diseases.

Recently, bioassay has been getting much attention as it can comprehensively evaluate water toxicity without identifying the individual chemical component. In this technique, a microscope observation is required to know the critical features of the targeted microorganisms. However, as the size of the microorganism becomes smaller, observation becomes more difficult due to the narrower focal depth of the imaging system. Here, to overcome these difficulties, a novel biospeckle technique is used for the microbioassay utilizing the biospeckle in the diffraction field generated from the microorganisms. Paramecium caudatum (200-300µm) and Euglena gracilis(50-60µm) were used as a microorganism. Dynamic biospeckle patterns were captured using a CCD camera to evaluate the swimming activity of microorganisms under varying water toxicity levels induced by heavy metal pollutants (Zn(NO₃)₂·6H₂O and FeSO₄·7H₂O). To quantitatively evaluate the swimming activity of microorganisms, the crosscorrelation function between the initial frame as a reference frame and the subsequent frames was measured, and the correlation time was evaluated as a measure of their swimming ability. Results show a concentration dependent effect of Zn on both species, leading to decreased swimming ability. Conversely, Fe exhibited varying effects on Paramecia and Euglena, with the latter displaying tolerance at lower concentrations but a notable response at higher concentrations. The advantage of the method is that owing to the non-imaging system, an enormous number of planktons can be processed. This allows for an immediate and statistically significant estimation of their swimming ability in response to environmental pollution.

Oral cancer is among the top three types of cancers in India which accounts for about 30 percent of all types of cancer. We propose here a portable and cost-effective 3D printed smartphone based bimodal (spectroscopy and imaging) device for detection of oral cancer at an early stage. The device has the ability to perform fluorescence spectroscopy and imaging on a single platform using smartphone as an optical spectrometer and a CMOS camera respectively. A miniature 405 nm laser diode has been used as a source. Fluorescence spectra and images of some known fluorophores such as fluorescein, rhodamine, flavin adenine dinucleotide (FAD) and proto-porphyrin (PpIX) have been recorded using the proposed smartphone-based device for validation. The wavelength resolution of device for spectral measurements is 0.25 nm per pixel in the visible range and for imaging the total area captured at the detector is 1cm2 . Preliminary studies have been performed on patients with oral precancer and cancer to evaluate the efficacy of the proposed system for in-vivo diagnosis of the disease at an early stage.

Plasmodium falciparum and Plasmodium vivax species are associated for malarial infections primarily in south-African and south-Asian sub-continents respectively. In this work we extract the refractive index of whole blood (WB) infected with Plasmodium falciparum or Plasmodium vivax species. Surface plasmon microscopy is used for the extraction of refractive index of WB. We conclude that intrinsic physical parameters, such as refractive index, can be used as a quantitative label-free estimator for the detection of different plasmodium species with varying densities in human WB.

Several low-cost, highly sensitive, simple-to-realize and to-use Point-Of-Care-Tests (POCT) have been presented exploiting plasmonic optical fiber sensors. In particular, highly sensitive biosensor configurations are developed by using innovative platforms that efficiently excite the plasmonic phenomena (surface plasmon resonance or Localized surface plasmon resonance) in gold films, continuous or nanostructured. This work proposes an overview of how a designer could tailor the sensor’s components, i.e. the plasmonic transducer and the receptor, to modify the response of the bio/chemical sensor system in terms of substance to be detected and detection range, as well. The proper combination of these two components (transducer and receptor) would produce the desired optimal performance for POCT. For instance, the detection range can be changed from femtomolar to micromolar ranges.

We investigated the creation of SERS-active hierarchical substrates based on self-assembled nanospheres (HSNs). We demonstrate how the “hierarchical” approach could be systematically exploited to extend the SERS hotspots into the third dimension, by enhancing the hot-spots spatial density and intensity. The proposed hierarchical substrates take advantage of the single layer hexagonal closed packed array nanospheres (CPA). An additional layer of upper nanospheres to obtain dense and intense hot spots pattern is employed. To predict the SERS performance and to identify the promising architectures, a numerical analysis is carried out, offering design criteria, an overview of the operating mechanisms and conditions that affect the SERS behavior of substrates. We fabricated HSNs by using a self-assembling approach and the preliminary results reported. The results highlight that HSNs can be used as cost-effective SERS substrates with better performance than simpler single-layer CPA configurations.

The ability to make an accurate diagnosis at the time of treatment is crucial for many diseases. However, current standard diagnostic procedures can only be performed in specialised healthcare facilities. To bring diagnostic methods from a specialised laboratory to the point of treatment, many alternative methods have been proposed. One of them is surfaceenhanced Raman scattering (SERS), which offers advantageous features such as high sensitivity in biotarget detection and higher accuracy. Here, we have developed an advanced SERS platform for the ultrasensitive, rapid and highly specific identification of tumour biomarkers in liquid biopsies. Our particular focus is on the detection of Thyroglobulin (Tg), the most important tumour biomarker for the diagnosis and prognosis of thyroid cancer. Specifically, SERS-active substrates fabricated by nanosphere lithography on chip or on tips of optical fiber (OF) were functionalized with Tg Capture antibodies. Gold nanoparticles were functionalized with Detection antibodies and conjugated with a Raman reporter. The sandwich assay platform was validated in the planar configuration and a detection limit of only 7 pg/ml was successfully achieved. The same approach has been successfully demonstrated on washout fluids from fine needle aspiration biopsies of cancer patients. Finally, the functionalization strategy was translated to the LOF-SERS platform and successfully used to detect Tg concentration. The proposed SERS-assisted immunoassay platform has proven to be highly versatile and can be used with both microfluidic chip POC devices and SERS-OF-based optrodes to perform sensitive, specific and rapid ex vivo assays for Tg detection in liquid intraoperative biopsies.

Numerous medical conditions require extensive monitoring of diverse biomarkers, imposing a significant time and effort burden on healthcare professionals. This underscores the need for fast, reliable, and personalized point-of-care diagnostic tools. In the context of organ transplantation, the physiological status of a brain deceased organ donor requires comprehensive surveillance, accompanied by appropriate medical interventions to mitigate organ degradation. An effective strategy for monitoring this degradation involves tracking the progression and, ideally, the onset of the inflammatory response, the so-called ”cytokine storm”, by monitoring specific biomarkers: micro-RNAs. We propose two approaches based on a surface plasmon resonance imaging biosensor that combine various methodologies to amplify the hybridization signal of an oligonucleotide duplex (sandwich assay or bimaterial nanostructured biochip). In a proof-of-concept experiment involving a protein oligonucleotide complex in a sandwich assay, we successfully demonstrate signal amplification by one order of magnitude. Additionally, using the contribution of localized surface plasmons induced by nanostructuring the biochip, our simulations predict a further significant gain in amplification.

Integrated photonic sensors on silicon nitride platforms are at the forefront of developments for decentralized, real-time detection of biological and chemical substances. Their increasingly precise sensitivity enables broad applications in the medical, pharmaceutical, and chemical sectors. However, attention to the adverse effect of optical loss is often inadequately addressed, limiting the available intensity in the transmission spectrum, thereby impinging on the achievable detection limits. In this computational study, we address the optimization of a microring-based resonator system, harnessing a recently formulated semi-analytical model of surface-roughness-induced scattering for waveguide-based loss optimization. Our focus extends beyond considering sensitivity to propose a comprehensive figure of merit for resonator design by including the quality factor influenced by the coupling coefficient. Simultaneously, we demonstrate how strategic adjustments of gap-coupling metrics can result in significant enhancements in resonator performance. The wavelength range of the target application is set to be around 850nm, focusing on transverse-electric polarization, as well as transverse-magnetic polarization of the input light. The dimensions of the waveguides have been established considering previous studies, with a width falling within 300 and 800nm. Furthermore, the nitride layer thickness will vary between 200 and 400nm, the ring radius between 20 and 60μm and the gap between 200 and 800nm. These parameters form the resonator’s design’s foundational geometry and layer properties. This work emphasizes the need for a holistic design process to fully leverage the potential of integrated photonic devices.

Human perpetual exposure to several pollutants such as smoke, radiation, and toxic chemical substances, causes an excessive production of reactive oxygen species (ROS), that leads to the onset of neurodegeneration diseases. This knowledge has highlighted the importance of frequent monitoring people health with innovative biosensors able to detect pathological conditions at the initial stage. Indeed, it is mainly stated that neurodegenerative diseases can be effectively treated only if diagnosed very early. In this context, the structural aggregation of biomolecules in different districts of the brain, seem to play a key role in the neurodegeneration development mechanism becoming eligible targets for an early diagnosis. Hereby, we propose an innovative technique for detecting such biomolecules, e.g. Tau, by exploiting a pyro-electrohydrodynamic effect that is able to generate and accumulate tiny droplets of analyte on the surface of a reactive glass slide. We call the technique p-jet and we tested it in case of serial dilutions of Tau protein to demonstrate the consistency of the procedure under an immunodetection-based protocol.

Plasmonic optical fiber-based biosensors are currently in their early stage of development as practical and integrated devices, gradually making their way towards the biosensing market. While the majority of these plasmonic biosensors operate using white light sources and glass prisms or multimode optical fibers (OFs), our approach centers on single-mode OFs coupled with tilted fiber Bragg gratings (TFBGs) in the near-infrared wavelength range. Our objective is to enhance surface sensitivity and broaden sensing capabilities of OF-based sensors to develop in situ sensing with remote interrogation. In this study, we comprehensively assess their performance in comparison to the gold-standard plasmonic reference, a commercial device based on the Kretschmann-Raether prism configuration, namely the Biacore X100. We present their respective refractive index sensitivity and their efficiency for insulin detection using a dedicated microfluidics approach. By optimizing a consistent surface biotrapping methodology, we elucidate the dynamic facets of both technologies and highlight their remarkable sensitivity to variations in both bulk and surface properties. The one-to-one comparison between both technologies demonstrates the reliability of optical fiber-based measurements, showcasing similar experimental trends obtained with both the prismatic configuration and gold-coated TFBGs, with an even enhanced limit of detection for the latter. This study lays the foundation for the detection of punctual molecular interactions and opens the way towards the detection of spatially and temporally localized events on the surface of optical probes, paving the way for their implementation in field conditions.

Sensing at the single cell level can provide insights into its dynamics and heterogeneity, yielding information otherwise unattainable with traditional biological methods where average population behavior is observed. In this context, optical tweezers provide the ability to select, separate, manipulate and identify single cells or other types of microparticles, potentially enabling single cell diagnostics. Forward or backscatter analysis of the light interacting with the trapped cells can provide valuable insights on the cell optical, geometrical and mechanical properties. In particular, the combination of tweezers systems with advanced machine learning algorithms can enable single cell identification capabilities. However, typical processing pipelines require a training stage which often struggles when trying to generalize to new sets of data. In this context, fully automated tweezers system can provide mechanisms to obtain much larger datasets with minimum effort form the users, while eliminating procedural variability. In this work, a pipeline for full automation of optical tweezers systems is discussed. A performance comparison between manually operated and fully automated tweezers systems is presented, clearly showing advantages of the latter. A case study demonstrating the ability of the system to discriminate molecular binding events on microparticles is presented.

Combining Digital Holography and Flow Cytometry, a powerful imaging technique which offers an effective approach in biomedicine investigations is obtained. Indeed, the extension of phase-contrast tomography cells in microfluidic environments allows for high-throughput property addressing the rising need for realistic and comprehensive datasets. This is achieved through the rapid collection of numerous flowing and rotating cell populations by refraining from using dyes or fluorescent markers. Cells’ roto-translation motion produces holographic interference patterns which are recorded to allow implementation of the computational procedure that provides reconstructed two-dimensional phase quantitative maps which contain the whole information from the biological specimen, such as morphological biophysical properties. The capacity to examine the same biological sample from multiple perspectives enables complete label-free analysis, an accomplishment made possible through the application of holographic tomography technology. This advanced technology stands at the forefront of single-cell biological investigation. Here, we show the potential of this technique in different biomedical applications. Indeed, effectiveness of this imaging method is highlighted in identifying and analyzing cancer cells, e.g circulating tumor cells, diagnosing blood-related disorders, classifying distinct cell lines within diverse populations, and identifying intricate internal cellular microstructures. Moreover, this innovative approach hints at promising future applications across different domains, including liquid biopsy, addressing drug resistance, and understanding genetic anomalies.

Flow cytometry is widely used for cell identification and characterization and involves labelling biological and clinical samples with fluorochrome-conjugated antibodies specific to cell markers. This requires use of expensive exogenous reagents and necessitates complex pre-processing of samples. Additionally, extensive challenges arise in clinical samples consisting of highly plastic and heterogenous cell types observed in diseases such as cancer. As such, it is challenging to apply flow cytometry to point-of-care diagnostic applications. To address this issue, we investigated the combination of diffuse reflectance spectroscopy (DRS), microfluidics and machine learning to offer rapid, low-cost, label-free cell identification for potential deployment at the point of care. To achieve this, we utilized a compact fibre-optic diffuse reflectance spectrometer with multi-depth sensing capability. This system was applied to a proof-of-concept cell identification study where we were able to discriminate triple negative breast cancer cells from healthy fibroblasts using commercially available flow channel slides (Ibidi GmbH, channel dimensions: 5 mm width, 0.4 mm height). However, we observed high interexperimental variability, which was partially attributed to the relatively large fluidic channels. Thus, we investigated in-house fabrication of microfluidics of varying channel widths (0.6-2mm). To this end, we used a Mars ELEGOO 3D printer and commercially available printing materials to batch fabricate optically and mechanically viable microfluidic chips that were both cheap and customizable. Using these in-house microfluidic devices, we demonstrated DRS-based discrimination of cancer cells of different origins, further indicating the potential of this approach for point-of-care cell identification/characterization. Ultimately, we hope this work will lead to the development of cheap, deployable, and accurate point-of-care tools for rapid, label-free cell identification.

Optoelectronic and spectral analysis of urine can be performed on site by low-cost portable technology, interfaced to signal processing and machine learning algorithm. These algorithms, trained on a set of previously known diagnostic outputs, can correlate the urine optoelectronic measured parameters with the person’s health status. The proposed solution is the development of an optoelectronic setup, suitable to be embedded in a portable configuration, capable of performing on site and in a short amount of time a urine screening based on a set of techniques of increasing three levels of complexity. The proposed parameters to be measured are dominant color and turbidity (1st level), UV induced fluorescence (2nd level), Raman Spectroscopy (3rd level). The system can be used to perform a set of measurements on a set of urine samples of already known health condition to carry out the training of a machine learning algorithm for assessing the risk of developing Acute Kidney Injury. All the technical information is public open access, available at https://github.com/ISELDEETC/PhotoAKI/tree/main/LUMINA.

Incorrect medication poses a significant risk to patient safety. Various control systems are on the market to prevent incorrect medication, but none of these systems monitor the actual chemical composition. The first step was to differentiate the applications where infusions are used and to assess where the effects of incorrectly administered infusions have the most consequences. On one hand, there are the oncology wards; on the other, there are the intensive care units (ICU). For the latter, the major challenge is the variety of compounds, including simple electrolyte solutions, very low-dose catecholamines, highly concentrated glucose solutions, and mixtures of carrier solutions, electrolytes, and other drugs. A sole analytical technique, if practicable, fast, and inexpensive, cannot provide a qualitative and quantitative solution for this challenge. The conceived solution combines different technical approaches, generally suitable as on-site techniques, and evaluated for this application. We present a study on various medications and concentrations using a combination of Raman spectroscopy, UV/Vis spectroscopy, and refractometry. For the ICU scenario, almost all medications could be identified. In the case of Raman-spectroscopy on cytostatic drugs, chemometric approaches were applied to enhance the qualitative and quantitative information value further. This approach enables infusions to be identified up to 99 % correctly based on a connected database containing 500 Raman spectra of different medications and concentrations. This study aims to increase safety in hospitals and to facilitate the work of hospital staff in intensive care units and for oncology patients. Another application is in pharmacies for quality control.

Recent advancements in loco-regional therapy are revolutionizing the point-of-care (POC) drug delivery field, enhancing the convenience, comfort, and effectiveness of these devices for patients. New anticancer drugs have improved the therapy, but there is still significant work to be done in order to selectively target tumour cells. To bridge this gap, here, we present a minimally invasive tool based on optical fibers (OFs) integrated in a microfluidic device for light-triggered loco regional delivery of drug-loaded particles. Specifically, we, here, selected the Lab on Fiber (LOF) technology as an attractive option to guide light and trigger the drug release. LOF, indeed, enables precise drug dosing and targeted transport, laying the foundation for mini-invasive platforms in light-activated loco-regional drug delivery. The platform includes drug-loaded carriers covalently attached on the OF surface through a photocleavable linker. The OF platform has been designed to spread light from the core region towards the cladding area in order to achieve enough power density to photo-cleave the linker and release the carrier. To this aim, side-emitting and core-offset OFs optrodes have been designed, fabricated and characterized achieving power density and scattering efficiency of 30% and 5mW/cm² and 24.9% and 4.64mW/cm². OFs were integrated into a microfluidic device and the particle release upon light activation was quantified. The side-emitting OF microfluidic system, designed for Hepatocellular cancer therapy, released 2.60μg/ml of carriers, while the core-offset OF microfluidic system, for Breast cancer treatment, released 1.06μg/ml of carriers. This approach holds potential for improving cancer treatment outcomes

Microfluidics is a rapidly growing field as it allows high resolution and sensitive detection using minimal amounts of material, ideal for developing point of care and lab on chip devices. The capabilities of microfluidics could be greatly enhanced if sensors can be integrated. The motivation of our work is to develop a technology platform which allows integrating several types of optical sensor within microfluidics. Using femtosecond laser technology, we can realize both channels and optical waveguides in the same material which can be used as building blocks for realizing sensors. Here we used Fused Silica (2.5 cm x 0.75 cm x 500 µm), an inert material which is transparent deep into the UV-spectrum while allowing femtosecond laser processing followed by chemical etching, to develop a compact transparent microfluidic chip platform. We demonstrated the capability by integrating a channel (measuring 1 cm x 500 μm x 300 μm) to perform a dynamic light scattering technique, where the fluid is illuminated and the resulting scattering intensity fluctuations are analyzed to detect the diffusion coefficient and hydrodynamic radius of particles in solution undergoing Brownian motion. To validate this technique, a water solution containing 0.01% polystyrene particles with a diameter of 200 nanometers was pumped through the microfluidic chip. We subjected the solution to 2 seconds of continuous wave laser illumination at three distinct wavelengths: 638 nm, 1307 nm, and 1550 nm. The resulting scattered light was captured by a fiber-coupled optical detector and subsequently amplified. Our findings demonstrate that the particle size can be accurately determined from the scattered light vector, with a maximum deviation of 5%, by fitting an autocorrelation function and extracting the hydrodynamic radius. This research holds significant implications for the development of new optofluidic techniques in biomedical applications.

Urinary tract infections (UTIs) are prevalent clinical conditions that, if untreated, can progress to urosepsis, a potentially fatal systemic infection. Timely detection and accurate assessment are critical for effective intervention. This presentation will show the integration of Liquid Chromatography-Mass Spectrometry (LC-MS)-based metabolomics and proteomics to advance our comprehension of UTI and urosepsis. Emphasis is placed on biomarker discovery and the development of a Point-of-Care (PoC) device for urosepsis assessment using urine samples.

Although lateral flow assays (LFAs) are currently being a handful of diagnostic technologies that can identify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other common respiratory viruses in one strip, it remains a grand challenge to substantially enhance their sensitivity. We propose here a straightforward method to overcome such drawbacks by employing nitrocellulose (NC) membrane femtosecond laser micromachining to control the analyte flow rate. The findings provided in this work indicate that tailoring the diameters of the μ-channels in NC can effectively expedite the immunological reaction time between the analyte and the labeled antibody, leading to an observable signal increase compared to pristine LFA.

Spectrometers are instruments that are used to measure different optical properties such as transmittance, absorbance, and concentration of liquid and solid samples. The standard spectrometers are big, bulky, nonportable, and costly. This makes them inaccessible to integrate into portable devices. We have developed a handheld low-cost camera-based spectrometer. It consists of a camera, direct vision spectroscope, and Raspberry Pi board. The components are enclosed in a 3D-printed structure. The spectrometer is calibrated using laser light sources. In liquid samples, when the light from the source passes through the sample and the transmitted light passes through the direct vision spectroscope, a spectrum is formed. The spectrum seen in the direct vision spectroscope is captured by the camera and processed using a Raspberry Pi board using a Python program. The results can be displayed in a graphical user interface in the mobile phone or computer connected wirelessly to the Raspberry Pi board. Based on the wavelength range of light source, the absorbance spectrum in the visible region can be measured using the spectrometer. The absorbance of different concentrations of food color samples are measured and compared with the standard spectrometer. The results of the device are comparable with the standard spectrometer.

Early disease detection represents a cornerstone in the diagnostic and detection approaches of contemporary medicine. Biomedical chips offer swift, precise, and cost-effective solutions tailored to specific medical objectives. This research suggests employing graphene quantum dots (GQDs) in conjunction with surface plasmon resonance (SPR) technology to create biochips designed for the rapid identification of pancreatic cancer. In biological research, graphene quantum dots leverage surface plasmon resonance technology to monitor biomolecular interactions. These experiments focus on the immune response to the pancreatic cancer marker Carbohydrate antigen19-9 (CA19-9) protein, leading to the development of biosensors with high sensitivity and accuracy for swift screening processes. This approach enables the detection of minimal changes around 10 Units/mL, achieving a linear regression coefficient of R² = 0.90. Consequently, this detection method allows for the rapid diagnosis of pancreatic cancer and the creation of a specific, fast-screening cancer biosensing chip.

This research focuses on exploring the development of graphene oxide quantum dots (GOQDs) for their surface plasmon resonance (SPR) properties and the detection mechanisms involving microRNAs (miRNAs). We have engineered a novel class of GOQDs composites designed to amplify the plasmons' resonance energy states, thereby boosting the interface electric field and enhancing sensing sensitivity. GOQDs exhibit superior fluorescent characteristics and are capable of effectively modulating the resonance and propagation energies of plasmons. They are poised to become a novel kind of material for plasmonic energy modulation. This exploration into miRNAs, particularly miRNA-210, underscores the potential for improved diagnostic and therapeutic strategies, promising advancements in personalized medicine and patient care by facilitating early disease detection and offering insights into novel treatment avenues. Thus, we aimed to assess the potential of circulating miRNAs as sensitive and specific biomarkers for the early diagnosis of preeclampsia. The experimental findings reveal that the linear regression equation for the SPR chip incorporating GOQDs is y = 1.94 + 1.83x, with an R² value of 0.95, indicating both high sensitivity and high linearity. The GOQDs based SPR a prominent assay designed to detect and quantify mature miRNAs in a fast, specific, accurate and reliable manner. Thus, a SPR biosensor based on GOQDs demonstrates high sensitivity and specificity for detecting miRNA-210, with potential for disease diagnosis applications. Future research will involve testing clinical samples to explore commercial applications for early disease and cancer detection.

This study presents a system for the detection of S.aureus NCTC 8325 (S.aureus), using a peroxidase-like DNA nanomachine (PxDm), which has the potential to revolutionize the detection of food pathogens, as it allows for the rapid and accurate identification of unique nucleic acids. PxDm has four binding arms that can efficiently bind and unwind nucleic acid, resulting in the formation of a G-quadruplex (G-4) structure when bound to the analyte. The G-4 structure, along with hemin, forms a DNAzime with peroxidase activity, which enhances the chemiluminescence (CL) of luminol during oxidation by hydrogen peroxide molecules. The rapid and highly selective nature of this diagnostic procedure was demonstrated by evaluating the kinetics of CL within a few minutes. PxDm has numerous advantages over standard diagnostic procedures, including the ability to detect analytes at room temperature and distinguish single nucleotide substitutions. This technology could potentially turn into a laboratory device on a chip for detecting nucleic acid markers of food pathogens.

ell counting is essential in life sciences, medicine, and pharmacology. Traditional approaches such as hemocytometry, require manual counting cells under a microscope. Although hemocytometry is cost-effective, it is also time-consuming and limited by operator experience. To address the drawbacks mentioned above, automated cell counting technologies have been developed to enhance the accuracy and efficiency of cell counting applications through the capture and processing of cell images. However, a limitation of these technologies is that they rely on counting a relatively small number of cells (100-200), indicating a need for further improvement. Additionally, these devices require specialized equipment such as counting chambers and solutions that are compatible with their hardware settings. In this study, we have developed an optofluidic cell-counting device that addresses these problems. Our optofluidic cell-counting platform significantly enhances test accuracy by scanning more than 2000 cells. The proposed method has error rate of <1% for cell viability and <5% for cell concentration results. Platform could provide the count results within only 1 minute, including sample loading, autofocusing, image recording and processing. Presented platform also has a built-in fluidic component that eliminates the need for an external counting chamber, enabling completely automated sample loading and self-cleaning capabilities compatible with any cleaning solutions. Providing a user-friendly and efficient functionality, our optofluidic platform has the potential to be a crucial resource for cost-effective and precise cell-counting applications

Compact and portable biosensing technologies play an important role in replacing traditional counterparts that require costly and heavy equipment, as well as complex infrastructure. The integration of these easy-to-use and cheap devices allows for the conducting of biosensing analyses in resource-limited settings. The study produced a portable optofluidic platform that is lightweight (260 g) and compact (16 cm×10 cm×11 cm). It combines subwavelength nanohole arrays, microfluidics technology, and on-chip computational imaging. It records plasmonic diffraction field images with a CMOS imager and an LED light, allowing for a large field of view for refractive index measurement. This LED source generates diffraction patterns on the imager. The microfluidic pump confirms accurate analyte delivery, allowing real-time analysis of diffraction field images to reveal time dependent binding kinetics of biomolecules. It identifies biomolecular interactions without labelling, allowing for the detection and quantification of biomolecules. Our platform has an outstanding limit-of-detection (LOD) of 5ng/mL for label-free detection of protein IgG. We effectively determined the association and dissociation constants for protein A/G and IgG binding using real-time diffraction field images. The optofluidic biosensor platform is ideal for surface plasmon resonance (SPR) in field applications. It can monitor interactions in real-time, making it useful for studying the way various biological and chemical compounds bind in many areas

Terahertz (THz) technology, particularly THz plasmonics for sensing applications, has gathered substantial interest across various research domains. Metamaterials (MM), artificially designed structures operating at subwavelength scales, offer a solution to enhance the sensitivity of free-space THz detection. Lung cancer, a pervasive and life-threatening disease globally, contributes significantly to cancer-related mortality due to challenges in early diagnosis and the burden of expensive detection methods. Brain cancer, with its considerable heterogeneity and high fatality rates, primarily afflicts children and adolescents. In response to these critical issues, we propose an innovative, cost-effective, and label-free strategy for the rapid discrimination of lung and brain cancer cells, employing THz metamaterial absorbers. This research employs a polarization-insensitive THz narrowband metamaterial absorber (MMA) operating at 4.3 THz, featuring quartz as a substrate and gold as a ring resonator. Simulation outcomes demonstrate that the absorption spectrum peak shifts when the sensor interacts with analytes of varying refractive indices and thicknesses. Covering the sensor with 0.16 μm thick non-destructive analytes yields an impressive sensitivity of up to 68 GHz/RIU. We conducted numerical simulations, exploring variations in analyte thickness, quantity, and refractive index. The results confirm that sensitivity intensifies around the edges of the ring resonator and analyte concentration near it, underscoring the significant influence of field enhancement in the surrounding region. This innovative detection approach promises substantial cost reductions through reusability, offering great potential in the field of cancer detection, enabling differentiation between cancer types, and identifying primary lesions and metastatic cancers.

Detection of nucleic acids has become a promising approach in diagnostics, but current methods often have limitations such as the need for expensive equipment or reduced sensitivity and specificity. Tuberculosis caused by M. tuberculosis is a widespread infectious disease that is also prone to developing antibiotic resistance. In this study, we introduce a novel method for detection and genotyping of M. tuberculosis using a biosensor based on a four-way junction (4WJ) DNA probe and plasmon Au nanospheres.