A significant amount of noteworthy articles reviewing different label-free biosensors are being published in the last years. Most of the times, the comparison among the different biosensors is limited by the procedure used of calculating the limit of detection and the measurement uncertainty. This article clarifies and establishes a simple procedure to determine the calibration function and the uncertainty of the concentration measured at any point of the measuring interval of a generic label-free biosensor. The value of the limit of detection arises naturally from this model as the limit at which uncertainty tends when the concentration tends to zero. The need to provide additional information, such as the measurement interval and its linearity, among others, on the analytical systems and biosensor in addition to the detection limit is pointed out. Finally, the model is applied to curves that are typically obtained in immunoassays and a discussion is made on the application validity of the model and its limitations.

The specificity and affinity of antibody-antigen interactions is a fundamental way to achieve reliable biosensing responses. Different proteins involved with dry eye dysfunction: ANXA1, ANXA11, CST4, PRDX5, PLAA and S100A6; were validated as biomarkers. In this work several antibodies were tested for ANXA1, ANXA11 and PRDX5 to select the best candidates for each biomarker. The results were obtained by using Biophotonic Sensing Cells (BICELLs) as an efficient methodology for label-free biosensing and compared with the Enzyme-Linked Immuno Sorbent Assay (ELISA) technique.

The bioreceptor immobilization process (biofunctionalization) turns to be one of the bottlenecks when developing a competent and high sensitivity label-free biosensor. Classical approaches seem to be effective but not efficient. Although biosensing capacities are shown in many cases, the performance of the biosensor is truncated by the inefficacious biofunctionalization protocol and the lack of reproducibility. In this work, we describe a unique biofunctionalization protocol based on chemical surface modification through silane chemistry on SiO₂ optical sensing transducers. Even though silane chemistry is commonly used for sensing applications, here we present a different mode of operation, applying an unusual silane compound used for this purpose (3-Ethoxydimethylsilyl)propylamine, APDMS, able to create ordered monolayers, and minimizing fouling events. To endorse this protocol as a feasible method for biofunctionalization, we performed multiple surface characterization techniques after all the process steps: Contact angle (CA), X-ray photoelectron spectroscopy (XPS), ellipsometry, and fluorescence microscopy. Finally, to evidence the outputs from the SiO₂ surface characterization, we used those SiO₂ surfaces as optical transducers for the label-free biosensing of matrix metalloproteinase 9 (MMP9). We found and demonstrated that the originally designed protocol is reproducible, stable, and suitable for SiO2-based optical sensing transducers.

We report the integration of an automated chemical optical sensing unit for the parallel interrogation of 12 BICELLs in a sensing chip. The work was accomplished under the European Project Enviguard (FP7-OCEAN-2013-614057) with the aim of demonstrating an optical nano-biosensing unit for the in-situ detection of various chemical pollutants simultaneously in oceanic waters. In this context, we designed an optical sensing chip based on resonant nanopillars (R-NPs) transducers organized in a layout of twelve biophotonic sensing cells (BICELLs). The sensing chip is interrogated in reflection with a 12-channels optical spectrometer equipped with an embedded computer-on-chip performing image processing for the simultaneous acquisition and analysis (resonant mode fitting) of the 12 spectra. A microfluidic chip and an automated flow control system composed of four pumps and a multi-path micro-valve makes it possible to drive different complex protocols. A rack was designed ad-hoc for the integration of all the modules. As a proof of concept, fluids of different refractive index (RI) were flowed in the system in order to measure the time response (sensogram) of the R-NPs under optical reflectance, and assess the sensors’ bulk sensitivity (285.9 ± 16.4 nm/RIU) and Limit of Detection (LoD) (2.95 × 10⁻⁶ RIUS). The real-time response under continuous flow of a sensor chip based on R-NP is showed for the first time, obtaining 12 sensograms simultaneously, featuring the unit as a potential excellent multiplexed detection system. These results indicate the high potential of the developed chemical sensing unit to be used for in-situ, multiplex and automatic optical biosensing.

In this work, we used a label-free biosensor that provides optical readouts to perform continuous detection of human interleukin 8 (IL-8), which is especially overexpressed in certain cancers and, thus, could be an effective biomarker for cancer prognosis estimation and therapy evaluation. For this purpose, we engineered a compact, portable, and easy-to-assemble biosensing module device. It combines a fluidic chip for reagent flow, a biosensing chip for signal transduction, and an optical readout head based on fiber optics in a single module. The biosensing chip is based on independent arrays of resonant nanopillar transducer (RNP) networks. We integrated the biosensing chip with the RNPs facing down in a simple and rapidly fabricated polydimethyl siloxane (PDMS) microfluidic chip, with inlet and outlet channels for the sample flowing through the RNPs. The RNPs were vertically oriented from the backside through an optical fiber mounted on a holder head fabricated ad hoc on polytetrafluoroethylene (PTFE). The optical fiber was connected to a visible spectrometer for optical response analysis and consecutive biomolecule detection. We obtained a sensogram showing anti-IL-8 immobilization and the specific recognition of IL-8. This unique portable and easy-to-handle module can be used for biomolecule detection within minutes and is particularly suitable for in-line sensing of physiological and biomimetic organ-on-a-chip systems. Cancer biomarkers’ continuous monitoring arises as an efficient and non-invasive alternative to classical tools (imaging, immunohistology) for determining clinical prognostic factors and therapeutic responses to anticancer drugs. In addition, the multiplexed layout of the optical transducers and the simplicity of the monolithic sensing module yield potential high-throughput screening of a combination of different biomarkers, which, together with other medical exams (such as imaging and/or patient history), could become a cutting-edge technology for further and more accurate diagnosis and prediction of cancer and similar diseases.