We developed a reusable magnetic surface plasmon resonance (SPR) sensor chip for detecting various target molecules repeatedly in a conventional SPR system. Here, ferromagnetic patterns on a SPR sensor chip were utilized to trap a layer of magnetic particles, and they were utilized as a solid substrate for SPR sensing in a conventional SPR system. After a sensing experiment, the used magnetic particles were removed by external magnetic fields, and a new layer of magnetic particles was immobilized to the SPR sensor chip for additional sensing measurements. Since magnetic particles were trapped on the ferromagnetic patterns, we could use our reusable SPR chip for SPR sensing measurements in a traditional SPR system without any applied magnetic fields. Significantly, ferromagnetic patterns on the sensor chip surface deflected the strong external fields, so that the large aggregation of magnetic particles on the sensor surface was reduced. We demonstrated using a single reusable SPR sensor chip to measure the nucleoprotein (NP) of H1N1 influenza virus solution ranging repeatedly for more than 7 times without significant signal degradation. Also, different target molecules could be repeatedly measured in a single SPR chip. Since our reusable SPR sensor chip can be repeatedly used in a conventional SPR system without any chemical processes for refreshment, the cost for SPR sensing should be significantly reduced. In this case, our reusable SPR sensor chip can be a major breakthrough and can be used for versatile practical applications of SPR sensors.A compact, portable, label-free, and ultra-sensitive sensor is proposed to detect cancerous cells based on Multi-Core Fiber (MCF) comprising of seven cores arranged in a hexagonal shape spliced with Single-Mode Fiber (SMF). Here, cytosensing based on fiber optic Localized Surface Plasmon Resonance (LSPR) is used for the efficient detection of different types of cancer cells. The proposed sensor structure is etched in a controlled manner to increase the evanescent wave (EWs) and coupling of modes between the cores of MCF. The etched MCF based LSPR probe has high refractive index sensitivity (RIS). To further increase the sensitivity, the sensor structure is immobilized with different nanomaterials (NMs) such as optimized size of gold nanoparticles (AuNPs), graphene oxide (GO), and copper oxide nanoflowers (CuO-NFs). AuNPs increase the sensitivity using LSPR, whereas, GO and CuO-NFs helps to increase the biocompatibility of sensor. The developed probe is further coated with 2-deoxy-D-glucose (2-DG) over NMs that are specific for the detection of cancer cells. In this work, various cancerous cell lines i.e. HepG2, Hepa 1-6, MCF-7, A549, and normal cell lines i.e. NCF and LO2 are detected using the developed sensing probe. Various analysis of proposed sensor such as selectivity, reusability, anti-interference ability, and involvement of GLUT receptor in detection has also been performed. The proposed etched sensor is ultra-sensitive for detection of HepG2, Hepa1 6, A549, MCF-7, LO2, and NCF cell lines with a limit of detection (LoD) of 3, 2, 2, 2, 4, 10 cells/mL, respectively in the linear range of 1 × 102-1 × 106 cells/mL.Practical obstacles, such as intricate designs and expensive equipment/materials, in the fabrication of wearable sweat sensors, have limited their feasibility as a personalized healthcare device. Herein, we have fabricated a cellulose-based wearable patch, which further paired with a smartphone-based fluorescence imaging module and a self-developed smartphone app for non-invasive and in situ multi-sensing of sweat biomarkers including glucose, lactate, pH, chloride, and volume. The developed Smart Wearable Sweat Patch (SWSP) sensor comprises highly fluorescent sensing probes embedded in paper substrates, and microfluidic channels consisted of cotton threads to harvest sweat from the skin surface and to transport it to the paper-based sensing probes. The imaging module was fabricated by a 3D printer, equipped with UV-LED lamps and an optical filter to provide the in situ capability of capturing digital images of the sensors via a smartphone. A smartphone app was also designed to quantify the concentration of the biomarkers via a detection algorithm. Additionally, we have recommended an Internet of Things (IoT)-based model for our developed SWSP sensor to promote its potential application for the future. The field studies on human subjects were also conducted to investigate the feasibility of our developed SWSP sensor for the analysis of sweat biomarkers. Our findings convincingly demonstrated the applicability of our developed SWSP sensor as a smart, user-friendly, ultra-low-cost (~0.03 $ per sweat patch), portable, selective, rapid, and non-invasive healthcare monitoring device for immense applications in health personalization, sports performance monitoring, and medical diagnostics.Epilepsies are a group of neurological disorders characterised by recurrent epileptic seizures. Seizures, defined as abnormal transient discharges of neuronal activity, can affect the entire brain circuitry or remain more focal in the specific brain regions and neuronal networks.  https://www.selleckchem.com/products/Temsirolimus.html  Human pluripotent stem cell (hPSC)-derived neurons are a promising option for modelling epilepsies, but as such, they do not model groups of connected neuronal networks or focal seizures. Our solution is a Modular Platform for Epilepsy Modelling In Vitro (MEMO), a lab-on-chip device, in which three hPSC-derived networks are separated by a novel microfluidic cell culture device that allows controlled network-to-network axonal connections through microtunnels. In this study, we show that the neuronal networks formed a functional circuitry that was successfully cultured in MEMO for up to 98 days. The spontaneous neuronal network activities were monitored with an integrated custom-made microelectrode array (MEA). The networks developed spontaneous burst activity that was synchronous both within and between the axonally connected networks, i.e. mimicking both local and circuitry functionality of the brain. A convulsant, kainic acid, increased bursts only in the specifically treated networks. The activity reduction by an anticonvulsant, phenytoin, was also localised to treated networks. Therefore, modelling focal seizures in human neuronal networks is now possible with the developed chip.