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Interferon gamma release assays for recognition regarding hidden Mycobacterium tuberculosis in elderly Hispanic folks.
Solvent effects and excited-state proton transfer (ESPT) of the carbazole derivatives are described to discard the role of the anions as Brönsted bases on the observed fluorescence behaviour of the sensors. The anion-sensor interaction was confirmed by 1H-NMR. Molecular modelling was employed to propose a mode of recognition of the sensor in terms of complex stability and interatomic distances. 1-hydroxycarbazole was employed for the quantitation of fluoride and chloride anions in commercially available medicinal spring water and mouthwash samples.Electrochemical voltammetric sensors are some of the most promising types of sensors for monitoring various physiological analytes due to their implementation as non-invasive and portable devices. Advantages in reduced analysis time, cost-effectiveness, selective sensing, and simple techniques with low-powered circuits distinguish voltammetric sensors from other methods. In this work, we developed a Cu2O-based non-enzymatic portable glucose sensor on a graphene paste printed on cellulose cloth. The electron transfer of Cu2O in a NaOH alkaline medium and sweat equivalent solution at very low potential (+0.35 V) enable its implementation as a low-powered portable glucose sensor. The redox mechanism of the electrodes with the analyte solution was confirmed through cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy studies. The developed biocompatible, disposable, and reproducible sensors showed sensing performance in the range of 0.1 to 1 mM glucose, with a sensitivity of 1082.5 ± 4.7% µA mM-1 cm-2 on Cu2O coated glassy carbon electrode and 182.9 ± 8.83% µA mM-1 cm-2 on Cu2O coated graphene printed electrodes, making them a strong candidate for future portable, non-invasive glucose monitoring devices on biodegradable substrates. For portable applications we demonstrated the sensor on artificial sweat in 0.1 M NaOH solution, indicating the Cu2O nanocluster is selective to glucose from 0.0 to +0.6 V even in the presence of common interference such as urea and NaCl.The sudden outbreak of COVID-19 rapidly developed into a global pandemic, which caused tens of millions of infections and millions of deaths. Although SARS-CoV-2 is known to cause COVID-19, effective approaches to detect SARS-CoV-2 using a convenient, rapid, accurate, and low-cost method are lacking. To date, most of the diagnostic methods for patients with early infections are limited to the detection of viral nucleic acids via polymerase chain reaction (PCR), or antigens, using an enzyme-linked immunosorbent assay or a chemiluminescence immunoassay. This study developed a novel method that uses localized surface plasmon resonance (LSPR) sensors, optical imaging, and artificial intelligence methods to directly detect the SARS-CoV-2 virus particles without any sample preparation. The virus concentration can be qualitatively and quantitatively detected in the range of 125.28 to 106 vp/mL through a few steps within 12 min with a limit of detection (LOD) of 100 vp/mL. check details The accuracy of the SARS-CoV-2 positive or negative assessment was found to be greater than 97%, and this was demonstrated by establishing a regression machine learning model for the virus concentration prediction (R2 > 0.95).Globally, 70 million people are annually affected by TBI. A significant proportion of all TBI cases are actually mild TBI (concussion, 70-85%), which is considerably more difficult to diagnose due to the absence of apparent symptoms. Current clinical practice of diagnosing mTBI largely resides on the patients' history, clinical aspects, and CT and MRI neuroimaging observations. The latter methods are costly, time-consuming, and not amenable for decentralized or accident site measurements. As an alternative (and/or complementary), mTBI diagnostics can be performed by detection of mTBI biomarkers from patients' blood. Herein, we proposed two strategies for the detection of three mTBI-relevant biomarkers (GFAP, h-FABP, and S100β), in standard solutions and in human serum samples by using an electrochemiluminescence (ECL) immunoassay on (i) a commercial ECL platform in 96-well plate format, and (ii) a "POC-friendly" platform with disposable screen-printed carbon electrodes (SPCE) and a portable ECL reader. We further demonstrated a proof-of-concept for integrating three individually developed mTBI assays ("singleplex") into a three-plex ("multiplex") assay on a single SPCE using a spatially resolved ECL approach. The presented methodology demonstrates feasibility and a first step towards the development of a rapid POC multiplex diagnostic system for the detection of a mTBI biomarker panel on a single SPCE.The separation of circulating tumor cells (CTCs) from blood samples is crucial for the early diagnosis of cancer. During recent years, hybrid microfluidics platforms, consisting of both passive and active components, have been an emerging means for the label-free enrichment of circulating tumor cells due to their advantages such as multi-target cell processing with high efficiency and high sensitivity. In this study, spiral microchannels with different dimensions were coupled with surface acoustic waves (SAWs). Numerical simulations were conducted at different Reynolds numbers to analyze the performance of hybrid devices in the sorting and separation of CTCs from red blood cells (RBCs) and white blood cells (WBCs). Overall, in the first stage, the two-loop spiral microchannel structure allowed for the utilization of inertial forces for passive separation. In the second stage, SAWs were introduced to the device. Thus, five nodal pressure lines corresponding to the lateral position of the five outlets were generated. According to their physical properties, the cells were trapped and lined up on the corresponding nodal lines. The results showed that three different cell types (CTCs, RBCs, and WBCs) were successfully focused and collected from the different outlets of the microchannels by implementing the proposed multi-stage hybrid system.Detection of genetic mutations leading to hematological malignancies is a key factor in the early diagnosis of acute myeloid leukemia (AML). FLT3-ITD mutations are an alarming gene defect found commonly in AML patients associated with high cases of leukemia and low survival rates. Available diagnostic assessments for FLT3-ITD are incapable of combining cost-effective detection platforms with high analytical performances. To circumvent this, we developed an efficient DNA biosensor for the recognition of AML caused by FLT3-ITD mutation utilizing electrochemical impedance characterization. The system was designed by adhering gold-sputtered zinc oxide (ZnO) nanorods onto interdigitated electrode (IDE) sensor chips. The sensing surface was biointerfaced with capture probes designed to hybridize with unmutated FLT3 sequences instead of the mutated FLT3-ITD gene, establishing a reverse manner of target detection. The developed biosensor demonstrated specific detection of mutated FLT3 genes, with high levels of sensitivity in response to analyte concentrations as low as 1 nM. The sensor also exhibited a stable functional life span of more than five weeks with good reproducibility and high discriminatory properties against FLT3 gene targets. Hence, the developed sensor is a promising tool for rapid and low-cost diagnostic applications relevant to the clinical prognosis of AML stemming from FLT3-ITD mutations.The integration of surface-enhanced Raman scattering (SERS) spectroscopy with magnetic fluid provides significant utility in point-of-care (POC) testing applications. Bifunctional magnetic-plasmonic composites have been widely employed as SERS substrates. In this study, a simple and cost-effective approach was developed to synthesize magnetic-plasmonic SERS substrates by decorating silver nanoparticles onto magnetic Fe3O4 nanoparticles (AgMNPs), which function both as SERS-active substrates and magnetic fluid particles. The strong magnetic responsivity from AgMNPs can isolate, concentrate, and detect target analytes from the irregular surface of fish skin rapidly. We fabricate a microfluid chip with three sample reservoirs that confine AgMNPs into ever smaller volumes under an applied magnetic field, which enhances the SERS signal and improves the detection limit by two orders of magnitude. The magnetic fluid POC sensor successfully detected malachite green from fish with excellent selectivity and high sensitivity down to the picomolar level. This work achieves a label-free, non-destructive optical sensing approach with promising potential for the detection of various harmful ingredients in food or the environment.Respiration rate is an essential vital sign that requires monitoring under various conditions, including in strong electromagnetic environments such as in magnetic resonance imaging systems. To provide an electromagnetically-immune breath-sensing system, we propose an all-fiber-optic wearable breath sensor based on a fiber-tip microcantilever. The microcantilever was fabricated on a fiber-tip by two-photon polymerization microfabrication based on femtosecond laser, so that a micro Fabry-Pérot (FP) interferometer was formed between the microcantilever and the end-face of the fiber. The cavity length of the micro FP interferometer was reduced as a result of the bending of the microcantilever induced by breath airflow. The signal of breath rate was rebuilt by detecting power variations of the FP interferometer reflected light and applying dynamic thresholds. The breath sensor achieved a high sensitivity of 0.8 nm/(m/s) by detecting the reflection spectrum upon applied flow velocities from 0.53 to 5.31 m/s. This sensor was also shown to have excellent thermal stability as its cross-sensitivity of airflow with respect to the temperature response was only 0.095 (m/s)/°C. When mounted inside a wearable surgical mask, the sensor demonstrated the capability to detect various breath patterns, including normal, fast, random, and deep breaths. We anticipate the proposed wearable breath sensor could be a useful and reliable tool for respiration rate monitoring.Osteopenia and sarcopenia can cause various senile diseases and are key factors related to the quality of life in old age. There is need for portable tools and methods that can analyze osteopenia and sarcopenia risks during daily life, rather than requiring a specialized hospital setting. Gait is a suitable indicator of musculoskeletal diseases; therefore, we analyzed the gait signal obtained from an inertial-sensor-based wearable gait device as a tool to manage bone loss and muscle loss in daily life. To analyze the inertial-sensor-based gait, the inertial signal was classified into seven gait phases, and descriptive statistical parameters were obtained for each gait phase. Subsequently, explainable artificial intelligence was utilized to analyze the contribution and importance of descriptive statistical parameters on osteopenia and sarcopenia. It was found that XGBoost yielded a high accuracy of 88.69% for osteopenia, whereas the random forest approach showed a high accuracy of 93.75% for sarcopenia. Transfer learning with a ResNet backbone exhibited appropriate performance but showed lower accuracy than the descriptive statistical parameter-based identification result. The proposed gait analysis method confirmed high classification accuracy and the statistical significance of gait factors that can be used for osteopenia and sarcopenia management.
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