Characterization of Functional Coatings on Cork Stoppers with Laser-Induced Breakdown Spectroscopy Imaging.

Evaluating the efficiency of surface treatments is a problem of paramount importance for the cork stopper industry. Generically, these treatments create coatings that aim to enhance the impermeability and lubrification of cork stoppers. Yet, current methods of surface analysis are typically time-consuming, destructive, have poor representativity or rely on indirect approaches. In this work, the use of a laser-induced breakdown spectroscopy (LIBS) imaging solution is explored for evaluating the presence of coating along the cylindrical surface and in depth. To test it, several cork stoppers with different shaped areas of untreated surface were analyzed by LIBS, making a rectangular grid of spots with multiple shots per spot, to try to identify the correspondent shape. Results show that this technique can detect the untreated area along with other features, such as leakage and holes, allowing for a high success rate of identification and for its performance at different depths, paving the way for future industry-grade quality control solutions with more complex surface analysis.

Effect of Low-Doses of Gamma Radiation on Electric Arc-Induced Long Period Fiber Gratings.

This work presents an experimental study on the effects of gamma radiation on Long Period Fiber Gratings (LPFGs) in a low-dose test campaign to evaluate their eventual degradation. The study was carried out with standard single-mode fibers where the grating was inscribed using the Electric-Arc Discharge (EAD) technique. Before the gamma campaign, a detailed optical characterization was performed with repeatability tests to verify the accuracy of the setup and the associated error sources. The gamma-induced changes up to a dose of 200 krad and the recovery after radiation were monitored with the Dip Wavelength Shift (DWS). The results show that the gamma sensitivity for a total dose of 200 krad is 11 pm/krad and a total DWS of 2.3 nm has been observed with no linear dependence. Post-radiation study shows that recovery from radiation-induced wavelength shift is nearly complete in about 4000 h. Experimental results show that the changes suffered under gamma irradiation of these LPFGs are temporary making them a good choice as sensors in space applications.

Particle Classification through the Analysis of the Forward Scattered Signal in Optical Tweezers.

The ability to select, isolate, and manipulate micron-sized particles or small clusters has made optical tweezers one of the emergent tools for modern biotechnology. In conventional setups, the classification of the trapped specimen is usually achieved through the acquired image, the scattered signal, or additional information such as Raman spectroscopy. In this work, we propose a solution that uses the temporal data signal from the scattering process of the trapping laser, acquired with a quadrant photodetector. Our methodology rests on a pre-processing strategy that combines Fourier transform and principal component analysis to reduce the dimension of the data and perform relevant feature extraction. Testing a wide range of standard machine learning algorithms, it is shown that this methodology allows achieving accuracy performances around 90%, validating the concept of using the temporal dynamics of the scattering signal for the classification task. Achieved with 500 millisecond signals and leveraging on methods of low computational footprint, the results presented pave the way for the deployment of alternative and faster classification methodologies in optical trapping technologies.

Optical fiber tips for biological applications: From light confinement, biosensing to bioparticles manipulation.

BACKGROUND: The tip of an optical fiber has been considered an attractive platform in Biology. The simple cleaved end of an optical fiber can be machined, patterned and/or functionalized, acquiring unique properties enabling the exploitation of novel optical phenomena. Prompted by the constant need to measure and manipulate nanoparticles, the invention of the Scanning Near-field Optical Microscopy (SNOM) triggered the optimization and development of novel fiber tip microfabrication methods. In fact, the fiber tip was soon considered a key element in SNOM by confining light to sufficiently small extensions, challenging the diffraction limit. As result and in consequence of the newly proposed "Lab On Tip" concept, several geometries of fiber tips were applied in three main fields: imaging (in Microscopy/Spectroscopy), biosensors and micromanipulation (Optical Fiber Tweezers, OFTs). These are able to exert forces on microparticles, trap and manipulate them for relevant applications, as biomolecules mechanical study or protein aggregates unfolding. SCOPE OF REVIEW: This review presents an overview of the main achievements, most impactful studies and limitations of fiber tip-based configurations within the above three fields, along the past 10 years. MAJOR CONCLUSIONS: OFTs could be in future a valuable tool for studying several cellular phenomena such as neurodegeneration caused by abnormal protein fibrils or manipulating organelles within cells. This could contribute to understand the mechanisms of some diseases or biophenomena, as the axonal growth in neurons. GENERAL SIGNIFICANCE: To the best of our knowledge, no other review article has so far provided such a broad view. Despite of the limitations, fiber tips have key roles in Biology/Medicine.

Plasmonic Optical Fiber Sensor Based on Double Step Growth of Gold Nano-Islands.

It is presented the fabrication and characterization of optical fiber sensors for refractive index measurement based on localized surface plasmon resonance (LSPR) with gold nano-islands obtained by single and by repeated thermal dewetting of gold thin films. Thin films of gold deposited on silica (SiO2) substrates and produced by different experimental conditions were analyzed by Scanning Electron Microscope/Dispersive X-ray Spectroscopy (SEM/EDS) and optical means, allowing identifying and characterizing the formation of nano-islands. The wavelength shift sensitivity to the surrounding refractive index of sensors produced by single and by repeated dewetting is compared. While for the single step dewetting, a wavelength shift sensitivity of ~60 nm/RIU was calculated, for the repeated dewetting, a value of ~186 nm/RIU was obtained, an increase of more than three times. It is expected that through changing the fabrication parameters and using other fiber sensor geometries, higher sensitivities may be achieved, allowing, in addition, for the possibility of tuning the plasmonic frequency.

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach.

Recent trends on microbiology point out the urge to develop optical micro-tools with multifunctionalities such as simultaneous manipulation and sensing. Considering that miniaturization has been recognized as one of the most important paradigms of emerging sensing biotechnologies, optical fiber tools, including Optical Fiber Tweezers (OFTs), are suitable candidates for developing multifunctional small sensors for Medicine and Biology. OFTs are flexible and versatile optotools based on fibers with one extremity patterned to form a micro-lens. These are able to focus laser beams and exert forces onto microparticles strong enough (piconewtons) to trap and manipulate them. In this paper, through an exploratory analysis of a 45 features set, including time and frequency-domain parameters of the back-scattered signal of particles trapped by a polymeric lens, we created a novel single feature able to differentiate synthetic particles (PMMA and Polystyrene) from living yeasts cells. This single statistical feature can be useful for the development of label-free hybrid optical fiber sensors with applications in infectious diseases detection or cells sorting. It can also contribute, by revealing the most significant information that can be extracted from the scattered signal, to the development of a simpler method for particles characterization (in terms of composition, heterogeneity degree) than existent technologies.

Fabrication of Multimode-Single Mode Polymer Fiber Tweezers for Single Cell Trapping and Identification with Improved Performance.

Optical fiber tweezers have been gaining prominence in several applications in Biology and Medicine. Due to their outstanding focusing abilities, they are able to trap and manipulate microparticles, including cells, needing any physical contact and with a low degree of invasiveness to the trapped cell. Recently, we proposed a fiber tweezer configuration based on a polymeric micro-lens on the top of a single mode fiber, obtained by a self-guided photopolymerization process. This configuration is able to both trap and identify the target through the analysis of short-term portions of the back-scattered signal. In this paper, we propose a variant of this fabrication method, capable of producing more robust fiber tips, which produce stronger trapping effects on targets by as much as two to ten fold. These novel lenses maintain the capability of distinguish the different classes of trapped particles based on the back-scattered signal. This novel fabrication method consists in the introduction of a multi mode fiber section on the tip of a single mode (SM) fiber. A detailed description of how relevant fabrication parameters such as the length of the multi mode section and the photopolymerization laser power can be tuned for different purposes (e.g., microparticles trapping only, simultaneous trapping and sensing) is also provided, based on both experimental and theoretical evidences.

From sensor fusion to knowledge distillation in collaborative LIBS and hyperspectral imaging for mineral identification.

Multimodal spectral imaging offers a unique approach to the enhancement of the analytical capabilities of standalone spectroscopy techniques by combining information gathered from distinct sources. In this manuscript, we explore such opportunities by focusing on two well-known spectral imaging techniques, namely laser-induced breakdown spectroscopy, and hyperspectral imaging, and explore the opportunities of collaborative sensing for a case study involving mineral identification. In specific, the work builds upon two distinct approaches: a traditional sensor fusion, where we strive to increase the information gathered by including information from the two modalities; and a knowledge distillation approach, where the Laser Induced Breakdown spectroscopy is used as an autonomous supervisor for hyperspectral imaging. Our results show the potential of both approaches in enhancing the performance over a single modality sensing system, highlighting, in particular, the advantages of the knowledge distillation framework in maximizing the potential benefits of using multiple techniques to build more interpretable models and paving for industrial applications.

Identification of Relevant Spectral Ranges in Laser-Induced Breakdown Spectroscopy Imaging Using the Fourier Space.

Laser-induced breakdown spectroscopy (LIBS) imaging has now a well-established position in the subject of spectral imaging, leveraging multi-element detection capabilities and fast acquisition rates to support applications both at academic and technological levels. In current applications, the standard processing pipeline to explore LIBS imaging data sets revolves around identifying an element that is suspected to exist within the sample and generating maps based on its characteristic emission lines. Such an approach requires some previous expert knowledge both on the technique and on the sample side, which hinders a wider and more transparent accessibility of the LIBS imaging technique by non-specialists. To address this issue, techniques based on visual analysis or peak finding algorithms are applied on the average or maximum spectrum, and may be employed for automatically identifying relevant spectral regions. Yet, maps containing relevant information may often be discarded due to low signal-to-noise ratios or interference with other elements. In this context, this work presents an agnostic processing pipeline based on a spatial information ratio metric that is computed in the Fourier space for each wavelength and that allows for the identification of relevant spectral ranges in LIBS. The results suggest a more robust and streamlined approach to feature extraction in LIBS imaging compared with traditional inspection of the spectra, which can introduce novel opportunities not only for spectral data analysis but also in the field of data compression.

Imprinted Hydrogel Nanoparticles for Protein Biosensing: A Review.

Over the past decade, molecular imprinting (MI) technology has made tremendous progress, and the advancements in nanotechnology have been the major driving force behind the improvement of MI technology. The preparation of nanoscale imprinted materials, i.e., molecularly imprinted polymer nanoparticles (MIP NPs, also commonly called nanoMIPs), opened new horizons in terms of practical applications, including in the field of sensors. Currently, hydrogels are very promising for applications in bioanalytical assays and sensors due to their high biocompatibility and possibility to tune chemical composition, size (microgels, nanogels, etc.), and format (nanostructures, MIP film, fibers, etc.) to prepare optimized analyte-responsive imprinted materials. This review aims to highlight the recent progress on the use of hydrogel MIP NPs for biosensing purposes over the past decade, mainly focusing on their incorporation on sensing devices for detection of a fundamental class of biomolecules, the peptides and proteins. The review begins by directing its focus on the ability of MIPs to replace biological antibodies in (bio)analytical assays and highlight their great potential to face the current demands of chemical sensing in several fields, such as disease diagnosis, food safety, environmental monitoring, among others. After that, we address the general advantages of nanosized MIPs over macro/micro-MIP materials, such as higher affinity toward target analytes and improved binding kinetics. Then, we provide a general overview on hydrogel properties and their great advantages for applications in the field of Sensors, followed by a brief description on current popular routes for synthesis of imprinted hydrogel nanospheres targeting large biomolecules, namely precipitation polymerization and solid-phase synthesis, along with fruitful combination with epitope imprinting as reliable approaches for developing optimized protein-imprinted materials. In the second part of the review, we have provided the state of the art on the application of MIP nanogels for screening macromolecules with sensors having different transduction modes (optical, electrochemical, thermal, etc.) and design formats for single use, reusable, continuous monitoring, and even multiple analyte detection in specialized laboratories or in situ using mobile technology. Finally, we explore aspects about the development of this technology and its applications and discuss areas of future growth.

Simultaneous measurement of partial pressure of O2 and CO2 with a hybrid interferometer.

In this Letter, a hybrid interferometer for simultaneous measurement of the partial pressures of O2 and CO2 mixtures is reported. The sensing head consists in the combination of two interferometric structures, one a Fabry-Pérrot cavity and the other a modal interferometer. The intrinsic Fabry-Pérot was formed by splicing a single mode fiber with a graded index fiber length that was then subjected to chemical etching creating an air cavity. The second interferometer is based on a splice of a pure silica tube in series with the Fabry-Pérot. It was observed for a particular gas that its refractive index changes with pressure variation in a specific way, a characteristic that permitted the simultaneous measurement of partial pressures of CO2 and O2 with rms deviations of ~±48.7 kPa and ~±20.1 kPa, respectively.

Fiber optic-based refractive index sensing at INESC Porto.

A review of refractive index measurement based on different types of optical fiber sensor configurations and techniques is presented. It addresses the main developments in the area, with particular focus on results obtained at INESC Porto, Portugal. The optical fiber sensing structures studied include those based on Bragg and long period gratings, on micro-interferometers, on plasmonic effects in fibers and on multimode interference in a large spectrum of standard and microstructured optical fibers.

Differential Refractometric Biosensor for Reliable Human IgG Detection: Proof of Concept.

A new sensing platform based on long-period fiber gratings (LPFGs) for direct, fast, and selective detection of human immunoglobulin G (IgG; Mw = 150 KDa) was developed and characterized. The transducer's high selectivity is based on the specific interaction of a molecularly imprinted polymer (MIPs) design for IgG detection. The sensing scheme is based on differential refractometric measurements, including a correction system based on a non-imprinted polymer (NIP)-coated LPFG, allowing reliable and more sensitive measurements, improving the rejection of false positives in around 30%. The molecular imprinted binding sites were performed on the surface of a LPFG with a sensitivity of about 130 nm/RIU and a FOM of 16 RIU-1. The low-cost and easy to build device was tested in a working range from 1 to 100 nmol/L, revealing a limit of detection (LOD) and a sensitivity of 0.25 nmol/L (0.037 µg/mL) and 0.057 nm.L/nmol, respectively. The sensor also successfully differentiates the target analyte from the other abundant elements that are present in the human blood plasma.

A Plasmonic Biosensor Based on Light-Diffusing Fibers Functionalized with Molecularly Imprinted Nanoparticles for Ultralow Sensing of Proteins.

Plasmonic bio/chemical sensing based on optical fibers combined with molecularly imprinted nanoparticles (nanoMIPs), which are polymeric receptors prepared by a template-assisted synthesis, has been demonstrated as a powerful method to attain ultra-low detection limits, particularly when exploiting soft nanoMIPs, which are known to deform upon analyte binding. This work presents the development of a surface plasmon resonance (SPR) sensor in silica light-diffusing fibers (LDFs) functionalized with a specific nanoMIP receptor, entailed for the recognition of the protein human serum transferrin (HTR). Despite their great versatility, to date only SPR-LFDs functionalized with antibodies have been reported. Here, the innovative combination of an SPR-LFD platform and nanoMIPs led to the development of a sensor with an ultra-low limit of detection (LOD), equal to about 4 fM, and selective for its target analyte HTR. It is worth noting that the SPR-LDF-nanoMIP sensor was mounted within a specially designed 3D-printed holder yielding a measurement cell suitable for a rapid and reliable setup, and easy for the scaling up of the measurements. Moreover, the fabrication process to realize the SPR platform is minimal, requiring only a metal deposition step.

Fiber optic hot-wire flowmeter based on a metallic coated hybrid long period grating/fiber Bragg grating structure.

In this work an all-optical hot-wire flowmeter based on a silver coated fiber combining a long period grating and a fiber Bragg grating (FBG) structure is proposed. Light from a pump laser at 1480 nm propagating down the fiber is coupled by the long period grating into the fiber cladding and is absorbed by the silver coating deposited on the fiber surface over the Bragg grating structure. This absorption acts like a hot wire raising the fiber temperature locally, which is effectively detected by the FBG resonance shift. The temperature increase depends on the flow speed of the surrounding air, which has the effect of cooling the fiber. It is demonstrated that the Bragg wavelength shift can be related to the flow speed. A flow speed resolution of 0.08 m/s is achieved using this new configuration.

Biosensors for Biogenic Amines: A Review.

Biogenic amines (BAs) are well-known biomolecules, mostly for their toxic and carcinogenic effects. Commonly, they are used as an indicator of quality preservation in food and beverages since their presence in higher concentrations is associated with poor quality. With respect to BA's metabolic pathways, time plays a crucial factor in their formation. They are mainly formed by microbial decarboxylation of amino acids, which is closely related to food deterioration, therefore, making them unfit for human consumption. Pathogenic microorganisms grow in food without any noticeable change in odor, appearance, or taste, thus, they can reach toxic concentrations. The present review provides an overview of the most recent literature on BAs with special emphasis on food matrixes, including a description of the typical BA assay formats, along with its general structure, according to the biorecognition elements used (enzymes, nucleic acids, whole cells, and antibodies). The extensive and significant amount of research that has been done to the investigation of biorecognition elements, transducers, and their integration in biosensors, over the years has been reviewed.

iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification.

With the advent of personalized medicine, there is a movement to develop "smaller" and "smarter" microdevices that are able to distinguish similar cancer subtypes. Tumor cells display major differences when compared to their natural counterparts, due to alterations in fundamental cellular processes such as glycosylation. Glycans are involved in tumor cell biology and they have been considered to be suitable cancer biomarkers. Thus, more selective cancer screening assays can be developed through the detection of specific altered glycans on the surface of circulating cancer cells. Currently, this is only possible through time-consuming assays. In this work, we propose the "intelligent" Lab on Fiber (iLoF) device, that has a high-resolution, and which is a fast and portable method for tumor single-cell type identification and isolation. We apply an Artificial Intelligence approach to the back-scattered signal arising from a trapped cell by a micro-lensed optical fiber. As a proof of concept, we show that iLoF is able to discriminate two human cancer cell models sharing the same genetic background but displaying a different surface glycosylation profile with an accuracy above 90% and a speed rate of 2.3 seconds. We envision the incorporation of the iLoF in an easy-to-operate microchip for cancer identification, which would allow further biological characterization of the captured circulating live cells.

Author Correction: iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Optical fiber-based sensing method for nanoparticle detection through supervised back-scattering analysis: a potential contributor for biomedicine.

BACKGROUND: In view of the growing importance of nanotechnologies, the detection/identification of nanoparticles type has been considered of utmost importance. Although the characterization of synthetic/organic nanoparticles is currently considered a priority (eg, drug delivery devices, nanotextiles, theranostic nanoparticles), there are many examples of "naturally" generated nanostructures - for example, extracellular vesicles (EVs), lipoproteins, and virus - that provide useful information about human physiology or clinical conditions. For example, the detection of tumor-related exosomes, a specific type of EVs, in circulating fluids has been contributing to the diagnosis of cancer in an early stage. However, scientists have struggled to find a simple, fast, and low-cost method to accurately detect/identify these nanoparticles, since the majority of them have diameters between 100 and 150 nm, thus being far below the diffraction limit. METHODS: This study investigated if, by projecting the information provided from short-term portions of the back-scattered laser light signal collected by a polymeric lensed optical fiber tip dipped into a solution of synthetic nanoparticles into a lower features dimensional space, a discriminant function is able to correctly detect the presence of 100 nm synthetic nanoparticles in distilled water, in different concentration values. RESULTS AND DISCUSSION: This technique ensured an optimal performance (100% accuracy) in detecting nanoparticles for a concentration above or equal to 3.89 µg/mL (8.74E+10 particles/mL), and a performance of 90% for concentrations below this value and higher than 1.22E-03 µg/mL (2.74E+07 particles/mL), values that are compatible with human plasmatic levels of tumor-derived and other types of EVs, as well as lipoproteins currently used as potential biomarkers of cardiovascular diseases. CONCLUSION: The proposed technique is able to detect synthetic nanoparticles whose dimensions are similar to EVs and other "clinically" relevant nanostructures, and in concentrations equivalent to the majority of cell-derived, platelet-derived EVs and lipoproteins physiological levels. This study can, therefore, provide valuable insights towards the future development of a device for EVs and other biological nanoparticles detection with innovative characteristics.

Towards a Uniform Metrological Assessment of Grating-Based Optical Fiber Sensors: From Refractometers to Biosensors.

A metrological assessment of grating-based optical fiber sensors is proposed with the aim of providing an objective evaluation of the performance of this sensor category. Attention was focused on the most common parameters, used to describe the performance of both optical refractometers and biosensors, which encompassed sensitivity, with a distinction between volume or bulk sensitivity and surface sensitivity, resolution, response time, limit of detection, specificity (or selectivity), reusability (or regenerability) and some other parameters of generic interest, such as measurement uncertainty, accuracy, precision, stability, drift, repeatability and reproducibility. Clearly, the concepts discussed here can also be applied to any resonance-based sensor, thus providing the basis for an easier and direct performance comparison of a great number of sensors published in the literature up to now. In addition, common mistakes present in the literature made for the evaluation of sensor performance are highlighted, and lastly a uniform performance assessment is discussed and provided. Finally, some design strategies will be proposed to develop a grating-based optical fiber sensing scheme with improved performance.