Quantification Of Glucose Research Articles

Engineered Glucose Oxidase‐Carbon Nanotube Conjugates for Tissue‐Translatable Glucose Nanosensors

AbstractContinuous and non‐invasive glucose monitoring and imaging is important for disease diagnosis, treatment, and management. However, glucose monitoring remains a technical challenge owing to the dearth of tissue‐transparent glucose sensors. In this study, we present the development of near‐infrared fluorescent single‐walled carbon nanotube (SWCNT) based nanosensors directly functionalized with glucose oxidase (GOx) capable of immediate and reversible glucose imaging in biological fluids and tissues. We prepared GOx‐SWCNT nanosensors by facile sonication of SWCNT with GOx in a manner that—surprisingly—does not compromise the ability of GOx to detect glucose. Importantly, we find by using denatured GOx that the fluorescence modulation of GOx‐SWCNT is not associated with the catalytic oxidation of glucose but rather triggered by glucose‐GOx binding. Leveraging the unique response mechanism of GOx‐SWCNT nanosensors, we developed catalytically inactive apo‐GOx‐SWCNT that enables both sensitive and reversible glucose imaging, exhibiting a ΔF/F0 of up to 40 % within 1 s of exposure to glucose without consuming the glucose analyte. We finally demonstrate the potential applicability of apo‐GOx‐SWCNT in biomedical applications by glucose quantification in human plasma and glucose imaging in mouse brain slices.

Engineered Glucose Oxidase-Carbon Nanotube Conjugates for Tissue-Translatable Glucose Nanosensors.

Continuous and non-invasive glucose monitoring and imaging is important for disease diagnosis, treatment, and management. However, glucose monitoring remains a technical challenge owing to the dearth of tissue-transparent glucose sensors. In this study, we present the development of near-infrared fluorescent single-walled carbon nanotube (SWCNT) based nanosensors directly functionalized with glucose oxidase (GOx) capable of immediate and reversible glucose imaging in biological fluids and tissues. We prepared GOx-SWCNT nanosensors by facile sonication of SWCNT with GOx in a manner that-surprisingly-does not compromise the ability of GOx to detect glucose. Importantly, we find by using denatured GOx that the fluorescence modulation of GOx-SWCNT is not associated with the catalytic oxidation of glucose but rather triggered by glucose-GOx binding. Leveraging the unique response mechanism of GOx-SWCNT nanosensors, we developed catalytically inactive apo-GOx-SWCNT that enables both sensitive and reversible glucose imaging, exhibiting a ΔF/F0 of up to 40 % within 1 s of exposure to glucose without consuming the glucose analyte. We finally demonstrate the potential applicability of apo-GOx-SWCNT in biomedical applications by glucose quantification in human plasma and glucose imaging in mouse brain slices.

Alternative strategies to provide actionable results when supply of urinalysis strips is unavailable

Abstract Urinalysis “dip strips” offer physicians qualitative results of 6 analytes which are immediately actionable: protein, glucose, leukocyte esterase, nitrates, blood, and ketones; however, the strips are instrument specific such that they are at the mercy of supply chain shortages. Due to vendor supply issues, we implemented a strategy that would continue to support clinical decision making in the absence of supplies for protein, glucose, white blood cells (WBC) and blood (RBC) detection. Method: In supply shortage situations, an automated algorithm triggered such that urine samples would be sent to the automation chemistry line to run quantification of protein and glucose and make sure an automated urine microscopy was performed for RBC and WBC detection. The algorithm triggered printing two labels so nursing would collect two specimens. We monitored the turn-around time from the specimen being received in the laboratory to results, made sure that the culture reflex order was triggered, and tracked complaints by physicians regarding not having all usual urinalysis results provided by the strips. Prior to implementation, correlation between sample types for protein and glucose measurement was found acceptable. RESULTS: When we put in place the algorithm, the turn-around time of urine microscopic study was identical to that obtained when the urinalysis was done with the strips; however, the quantification of glucose and protein took approximately 30 minutes more. Urine reflex cultures were triggered correctly with the algorithm as they derive entirely from a WBC count >20. During the period we had the algorithm in place we only had one complaint by a physician wanting to have results of nitrates. Conclusion: The successful implementation of the algorithm allowed the laboratory to provide actionable urinalysis analytes in a timely manner with minimal complaints from physicians.

Prediction of glucose and sucrose values of black tea samples using NIR spectroscopy and chemometrics

FT-NIR and chemometrics are considered one of the most important analytical tools for the quality control of tea. The present study focused on developing and validating a rapid quantification method for the quantification of sugar, specifically sucrose and glucose in black tea using FT-NIR spectroscopy. Calibration models were established by partial least squares (PLS) regression analysis. Fructose, glucose, and sucrose concentrations in black tea were analyzed using high-performance liquid chromatography. The spectral range and the number of PLS factors were optimized for the Residual Predictive Deviation (RPD) and correlation coefficient (r2) of determination. The NIR spectral region between 5878 and 3996 cm−1 (1701–2500 nm) was selected as the best range for predicting glucose, sucrose, and fructose concentrations in black tea. The calibration model developed for sucrose has high RPD (4.29) and r2 (0.95) indicating the potential for predicting the inherent sucrose content in black tea with high accuracy. The calibration model developed for glucose has RPD of 2.73 and r2 (0.87) showing the potential for predicting glucose content in black tea with reasonable accuracy. Both calibration models could be useful for quality assurance purposes in black tea, and easier and faster than the wet chemical HPLC method. FT-NIR spectroscopy coupled with chemometrics has been demonstrated for the first time to quantify the inherent glucose and sucrose concentrations in black tea. Calibration models could be used to determine adulteration of black tea with sucrose and glucose.

Alternative Strategies to Provide Actionable Results When a Supply of Urinalysis Strips Is Unavailable.

Urinalysis instrument-specific dip strips offer physicians qualitative results for actionable analytes (protein, glucose, leukocyte esterase, nitrates, hemoglobin, and ketones). To explain a strategy implemented to support clinical decision-making by providing urine quantification of protein, glucose, white blood cells (WBCs), and red blood cells because of urine strip shortages. During shortages, we implemented an automated algorithm that triggered sending urine samples to the automation line for quantification of protein and glucose and ensured that urine microscopy was performed to obtain WBC and red blood cell counts. The algorithm printed 2 labels so nursing staff would collect 2 specimens. We monitored the turnaround time from the specimen being received in the laboratory to result verification, ensured that the culture reflex order was triggered, and tracked complaints by physicians regarding not having usual urinalysis results. Prior to implementation, correlation between sample types for protein and glucose measurement was found acceptable. The algorithm was put in place twice during 2022. The turnaround time of urine microscopic study was identical to that obtained when the urinalysis was done with the strips; however, the quantification of glucose and protein took approximately 30 minutes more. Urine reflex cultures were triggered correctly with the algorithm, as they were derived entirely from a WBC count higher than 10 per high-power field. During the shortage period we had only 1 complaint, by a physician wanting to have results of nitrates. During urine strip shortages, we successfully implemented a diversion algorithm that provided actionable urinalysis analytes in a timely manner with minimal provider complaints.

Verification of the analytical performance of the serum glucose assay on the Abbott Alinity ci®

The precision and reliability of the serum glucose assay on the Abbott Alinity ci® analyzer were systematically evaluated. The study was conducted over 30 days in the biochemistry laboratory of Mohammed VI University Hospital. Two phases were carried out: reproducibility assessment involving daily measurements across low, medium, and high glucose levels, and repeatability testing involving 30 replicates per sample. The hexokinase enzymatic approach was employed for glucose quantification. Data analysis utilized the BYG middleware and complied with FSCB and RICOS standards. For reproducibility, the coefficient of variation (CV) values were low, ranging from 1.49% to 1.84%. Repeatability CV values were even lower, varying from 0.34% to 0.94%. Results aligned well with quality control limits, confirming the assay's consistency and precision. This study underscores the robustness and reliability of the hexokinase method on the Alinity ci® platform for serum glucose analysis, with implications for accurate patient care. By adhering to strict analytical performance verification, laboratories ensure dependable clinical outcomes. This research contributes to the foundation of knowledge supporting serum glucose measurement reliability.

(Invited) Non-Enzymatic Glucose Sensor Fabricated By Ni-Nanowires Decorated Graphene Gated FETs

In this study, an innovative non-invasive glucose sensor made of nickel nanowire-decorated graphene-gated field-effect transistors is demonstrated. Due to the redox reaction between nickel nanowires and glucose molecules in weakly alkaline solution, electron exchange occurs when Ni(III) reacts with glucose to form Ni(II) and gluconolactone. In order to improve the sensitivity of the glucose sensor and reduce the detection limit, we compared the characteristics of the glucose sensor fabricated by nickel nanowires on gold surface and graphene/gold surface, respectively. Since the CVD-grown graphene film has excellent electrical conductivity and no defects, the electrons generated by the redox reaction can be quickly and evenly dispersed and are not easily neutralized, resulting in a change on the gate potential, thereby affecting the current between the source and the drain metal, and then the glucose concentration in the solution can be deduced. It can be seen from the experiments that the glucose sensor with graphene film has better current stability, lower detection limit and better linear relationship between current and concentration. The demonstrated nickel wire-decorated graphene-gated FET biosensor can be used for the quantification of glucose with a linear range of 10-50 mM and a detection limit of 51nM. Figure 1

H2 O2 -Induced Persistent Luminescence Signal Enhancement Applied to Biosensing.

Persistent luminescence nanoparticles (PLNPs) are innovative materials able to emit light for a long time after the end of their excitation. Thanks to this property, their detection can be separated in time from the excitation, making it possible to obtain images with a high signal-to-noise ratio. This optical property can be of particular interest for the development of in vitro biosensors. Here, wereport the unexpected effect of hydrogen peroxide (H2 O2 ) on the signal intensity of ZnGa2 O4 :Cr3+ (ZGO) nanoparticles. In the presence of H2 O2 , the signal intensity of ZGO can be amplified. This signal amplification can be used to detect and quantify H2 O2 in various media, using non-functionalized ZGO nanoparticles. This small molecule can be produced by several oxidases when they react with their substrate. Indeed, the quantification of glucose, lactic acid, and uric acid is possible. The limit of detection could be lowered by modifying the nanoparticles synthesis route. These optimized nanoparticles can also be used as new biosensor to detect larger molecules such as antigen, using the appropriate antibody. This unique property, i.e., persistent luminescence signal enhancement induced by H2 O2 , represents a new way to detect biomolecules which could lead to a very large number of bioassay applications.

Cu-MOF derived CuO@g-C3N4 nanozyme for cascade catalytic colorimetric sensing.

The use of peroxidase mimics has great potential for various real applications due to their strong catalytic activity. Herein, a facile strategy was proposed to directly prepare CuO@g-C3N4 by Cu-MOF derivatization and demonstrated its efficacy in constructing a multiple enzymatic cascade system by loading protein enzymes onto it. The resulting CuO@g-C3N4 possessed high peroxidase-like activity, with a Michaelis constant (Km) of 0.25 and 0.16mM for H2O2 and 3,3',5,5'-tetramethylbenzidine (TMB), respectively. Additionally, the high surface area of CuO@g-C3N4 facilitated the loading of protein enzymes and maintained their activity over an extended period, expanding the potential applications of CuO@g-C3N4. To test its feasibility, CuO@g-C3N4/protein oxidase complex was prepared and used to sense the ripeness and freshness of fruits and meat, respectively. The mechanism relied on the fact that the ripeness of fruits increasedand freshness of food decreased with the release of marked targets, such as glucose and xanthine, which could produce H2O2 when digested by the corresponding oxidase. The peroxidase mimics of CuO@g-C3N4 could then sensitively colorimetric detect H2O2 in present of TMB. The obtained CuO@g-C3N4/oxidase complex exhibited an excellent linear response to glucose or xanthine in the range of 1.0-120μmol/L or 8.0-350μmol/L, respectively. Furthermore, accurate quantification of glucose and xanthine in real samples is achieved with spiked recoveries ranging from 80.2% to 120.0% and from 94.2% to 112.0%, respectively. Overall, this work demonstrates the potential of CuO@g-C3N4 in various practical applications, such as food freshness detection.

Non-enzymatic amperometric biosensor with anchored Ni nanoparticles for urinary glucose quantification

In a one-step approach, Nickel nanoparticles of <200 nm in diameter were electrodeposited on the surface of laser-induced graphene using the chronoamperometry technique to develop a sensitive, flexible nonenzymatic sensor for detecting glucose in urine. The prepared sensor prototype exhibited remarkable catalytic activity toward the glucose oxidation with a response time of <3 s, sensitivity of 5796.18 μAmM−1 cm−2, a linear range of 12 μM-1.5 mM, and a detection limit of 0.0152 μM. It detected glucose in human urine samples with high reliability of 98.5 % and showed excellent anti-interference ability for glucose sensing. This prototype can form the basis for wearable sensors to detect glucose in a range of concentrations because of the developed sensor's excellent performance, durability, and lifespan.

4D-printed needle panel meters coupled with enzymatic derivatization for reading urea and glucose concentrations in biological samples

On-site analytical techniques continue being developed with advances in modern technology. To demonstrate the applicability of four-dimensional printing (4DP) technologies in the direct fabrication of stimuli-responsive analytical devices for on-site determination of urea and glucose, we used digital light processing three-dimensional printing (3DP) and 2-carboxyethyl acrylate (CEA)–incorporated photocurable resins to fabricate all-in-one needle panel meters. When adding a sample having a value of pH above the pKa of CEA (ca. 4.6–5.0) into the fabricated needle panel meter, the [H+]-responsive layer of the needle, printed using the CEA-incorporated photocurable resins, swelled as a result of electrostatic repulsion among the dissociated carboxyl groups of the copolymer, leading to [H+]-dependent bending of the needle. When coupled with a derivatization reaction (urease-mediated hydrolysis of urea to decrease [H+]; glucose oxidase-mediated oxidization of glucose to increase [H+]), the bending of the needle allowed reliable quantification of urea or glucose when referencing pre-calibrated concentration scales. After method optimization, the method's detection limits for urea and glucose were 4.9 and 7.0 μM, respectively, within a working concentration range from 0.1 to 10 mM. We verified the reliability of this analytical method by determining the concentrations of urea and glucose in samples of human urine, fetal bovine serum, and rat plasma with spike analyses and comparing the results with those obtained using commercial assay kits. Our results confirm that 4DP technologies can allow the direct fabrication of stimuli-responsive devices for quantitative chemical analysis, and that they can advance the development and applicability of 3DP-enabling analytical methods.

Photonic hydrogel for continuous glucose monitoring using smartphone readout

Diabetes has become one of the leading deaths causes worldwide. Developing low-cost, rapid, and reusable sensors can provide a solution for continuous glucose monitoring to reduce the diabetic complications that could be fatal. Here, Phenylboronic acid (PBA)-based hydrogel sensors with embedded photonic nanostructures were developed for rapid and continuous glucose quantification within the physiological range. The photonic nanostructures were imprinted on the PBA-based hydrogel using simple and rapid process. Three different sensors: free-standing (FS), stand-alone (SA), and optical fiber (OF) were fabricated and tested in the glucose concentration range of 0–50 mM. A sensitivity of 6, 3, and 1.2 µW/mM was documented for FS, SA, and OF sensors, respectively. A rapid response time of 20 s and saturation time of 3 min were recorded along with a limit of detection of 1 mM. The sensing capabilities of these sensors were examined in both transmission and reflection configurations. Practicality of the sensors was tested using smartphone readout. The optical power was measured using a smartphone exploiting its photodiode and the power changes were correlated with glucose concentrations. These developed sensors may have applications in remote, continuous, and real-time glucose monitoring systems.

Quantification of Cerebral Glucose Concentrations via Detection of the H1-α-Glucose Peak in 1 H MRS at 7 T.

Sensitive detection and quantification of cerebral glucose is desired. To quantify cerebral glucose by detecting the H1-α-glucose peak at 5.23 ppm in 1 H magnetic resonance spectroscopy at 7 T. Prospective. Twenty-eight non-fasted healthy subjects (aged 20-28 years). Short echo time stimulated echo acquisition mode (short-TE STEAM) and semi-localized by adiabatic selective refocusing (semi-LASER) at 7 T. Single voxel spectra were obtained from the posterior cingulate cortex (27-mL) using a 32-channel head coil. The H1-α-glucose peak in the spectrum with retrospective removal of the residual water peak was fitted using LCModel with a glucose basis set of only the H1-α-glucose peak. Conventional spectral analysis was performed with a glucose basis set of a full spectral pattern of glucose, also. Fitting precision was evaluated with Cramér-Rao lower bounds (CRLBs). The repeatability of glucose quantification via the semi-LASER sequence was tested. Paired or Welch's t-test were used for normally distributed values. A P value of <0.05 was considered significant. The repeatability of measures was analyzed using coefficient of variation (CV). Removal of the residual water peak improved the flatness and stability of baselines around the H1-α-glucose peak and reduced CRLBs for fitting the H1-α-glucose peak. The semi-LASER sequence was superior to the short-TE STEAM in the higher signal-to-noise ratio of the H1-α-glucose peak (mean ± SD 7.9 ± 2.5, P < 0.001). The conventional analysis overfitted the H1-α-glucose peak. The individual CVs of glucose quantification by detecting the H1-α-glucose peak were smaller than the corresponding CRLBs. Cerebral glucose concentration is quantitated to be 1.07 mM by detecting the H1-α-glucose peak in the semi-LASER spectra. Despite requiring long scan times, detecting the H1-α-glucose peak allows true glucose quantification free from the influence of overlapping taurine and macromolecule signals. 2 TECHNICAL EFFICACY STAGE: 1.

(Invited) Non-Enzymatic Glucose Sensor Fabricated By Ni-Nanowires Decorated Graphene Gated FETs

In this study, an innovative non-invasive glucose sensor made of nickel nanowire-decorated graphene-gated field-effect transistors is demonstrated. Due to the redox reaction between nickel nanowires and glucose molecules, electron exchange occurs when Ni(III) reacts with glucose to form Ni(II) and gluconolactone. Changes in electron concentration are amplified by transistors at the bottom, improving detection sensitivity. In this study, the electrical properties of glucose sensor fabricated from nickel nanowire/graphene/gold surfaces was studied. Since the CVD-grown graphene film has excellent electrical conductivity, the electrons generated by the redox reaction can be quickly and evenly dispersed. The results show that the glucose sensor with graphene film has good current stability, low detection limit and good linear relationship between current and concentration. The demonstrated nickel wire-decorated graphene-gated FET biosensor can be used for the quantification of glucose with a linear range of 10-50 mM and a detection limit of 51nM.

What is the best spectroscopic method for simultaneous analysis of organic acids and (poly)saccharides in biological matrices: Example of Aloe vera extracts?

Several species of (poly)saccharides and organic acids can be found often simultaneously in various biological matrices, e.g., fruits, plant materials, and biological fluids. The analysis of such matrices sometimes represents a challenging task. Using Aloe vera (A. vera) plant materials as an example, the performance of several spectroscopic methods (80 MHz benchtop NMR, NIR, ATR-FTIR and UV–vis) for the simultaneous analysis of quality parameters of this plant material was compared. The determined parameters include (poly)saccharides such as aloverose, fructose and glucose as well as organic acids (malic, lactic, citric, isocitric, acetic, fumaric, benzoic and sorbic acids). 500 MHz NMR and high-performance liquid chromatography (HPLC) were used as the reference methods.UV–vis data can be used only for identification of added preservatives (benzoic and sorbic acids) and drying agent (maltodextrin) and semiquantitative analysis of malic acid. NIR and MIR spectroscopies combined with multivariate regression can deliver more informative overview of A. vera extracts being able to additionally quantify glucose, aloverose, citric, isocitric, malic, lactic acids and fructose. Low-field NMR measurements can be used for the quantification of aloverose, glucose, malic, lactic, acetic, and benzoic acids. The benchtop NMR method was successfully validated in terms of robustness, stability, precision, reproducibility and limit of detection (LOD) and quantification (LOQ), respectively.All spectroscopic techniques are useful for the screening of (poly)saccharides and organic acids in plant extracts and should be applied according to its availability as well as information and confidence required for the specific analytical goal. Benchtop NMR spectroscopy seems to be the most feasible solution for quality control of A. vera products.

Ni3V2O8 Nanosheets Grafted on 3D Helical‐shaped Carbon Nanocoils as A Binder‐free Hierarchical Composite for Efficient Non‐enzymatic Glucose Sensing

AbstractHigh fabrication cost, chemical instability, and complex immobilization of enzyme molecules are critical issues of enzyme‐based glucose sensors. Designing state‐of‐the‐art, binder‐free, and non‐enzymatic glucose sensing probes plays an imperative role to cope with the aforementioned issues. 3D carbonaceous nanomaterials coated with transition metal vanadates (TMVs) are a favorable biomimetic platform for glucose quantification. Peculiar hierarchical structure, enhanced conductivity, synergistic interaction, multiple oxidation states, and high catalytic activity would make such composite a potential contender for non‐enzymatic glucose sensing. Herein, 3D helical‐shaped carbon nanocoils (CNCs) are grown on nickel foam (NF) via chemical vapor deposition method to prepare a robust CNCs/NF scaffold. Then, a hydrothermal route is followed to grow interconnected free‐standing Ni3V2O8 nanosheets (NSs) on CNCs/NF scaffold. This novel and binder‐free Ni3V2O8 NSs/CNCs/NF hierarchical composite possesses superior electrochemical active area (ECSA) and exceptional electrochemical efficacy. Amperometric analysis exhibits extremely prompt detection time (0.1 s), elevated sensitivity (5214 µA mM−1 cm−2), and low detection limit (0.04 µM). Developed sensor demonstrates appreciable recoveries (93.3 to 103.3%) regarding glucose concentration in human serum. The appealing analytical results show that deployment of a 3D helical‐shaped hierarchical smart scaffold can be an effective strategy for developing efficient and advanced non‐enzymatic glucose sensors.

Fast-Training Deep Learning Algorithm for Multiplex Quantification of Mammalian Bioproduction Metabolites via Contactless Short-Wave Infrared Hyperspectral Sensing.

Within the biopharmaceutical sector, there exists the need for a contactless multiplex sensor, which can accurately detect metabolite levels in real time for precise feedback control of a bioreactor environment. Reported spectral sensors in the literature only work when fully submerged in the bioreactor and are subject to probe fouling due to a cell debris buildup. The use of a short-wave infrared (SWIR) hyperspectral (HS) cam era allows for efficient, fully contactless collection of large spectral datasets for metabolite quantification. Here, we report the development of an interpretable deep learning system, a convolution metabolite regression (CMR) approach that detects glucose and lactate concentrations using label-free contactless HS images of cell-free spent media samples from Chinese hamster ovary (CHO) cell growth flasks. Using a dataset of <500 HS images, these CMR algorithms achieved a competitive test root-mean-square error (RMSE) performance of glucose quantification within 27 mg/dL and lactate quantification within 20 mg/dL. Conventional Raman spectroscopy probes report a validation performance of 26 and 18 mg/dL for glucose and lactate, respectively. The CMR system trains within 10 epochs and uses a convolution encoder with a sparse bottleneck regression layer to pick the best-performing filters learned by CMR. Each of these filters is combined with existing interpretable models to produce a metabolite sensing system that automatically removes spurious predictions. Collectively, this work will advance the safe and efficient adoption of contactless deep learning sensing systems for fine control of a variety of bioreactor environments.

Nanomaterials integrated with microfluidic paper-based analytical devices for enzyme-free glucose quantification

In this study, nanomaterials capable of enzyme-free glucose quantification and colorimetric readout are integrated into a microfluidic paper-based analytical devices (μPADs). Gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were utilized as a peroxidase-like nanozyme and a colorimetric probe to achieve glucose monitoring. In this developed device, glucose is oxidized by AuNPs to generate hydrogen peroxide (H2O2), which flows in the paper microchannels toward detection zones. H2O2 then etches the immobilized AgNPs to induce a color change. The intensity of color change is easily monitored using a smartphone application. Following method optimization, we obtained a linear range from 0.50 to 10.0 mmol L−1 (R2 = 0.9921) and a detection limit (LOD) of 340.0 μmol L−1. This falls in the clinically relevant range for glucose monitoring and diabetes diagnosis in humans. In addition, the total analysis time is just 20 min, which is significantly less than the same experiment performed in the solution phase. Also, our method is markedly selective; other substrates do not interfere. The recovery test in human control samples was in the range of 98.47–102.34% and the highest relative standard deviation (RSD) was 3.58%. The enzyme-free approach for glucose sensing is highly desirable for diabetes diagnosis as it replaces the more expensive enzyme with cheaper nanomaterials. Furthermore, since nanomaterials are more environmentally stable compared to enzymes, it has the potential for widespread deployment as point-of-care diagnostics (POC) in resource-limited settings.

Digital electronic based portable device for colorimetric quantification of ketones and glucose level in human urine

Development of a digital, frugal, portable testing device for quantification of glucose and ketones in the human urine sample is presented in this article. Based on the spectroscopic absorption principle, the colorimetric detection of the analytes is explored. Glucose in the human urine sample is quantified by the formation of the red-colored cuprous oxide due to the reaction with Benedict’s solution. The reaction of urine with alkaline sodium nitroprusside is exploited to estimate the presence of ketones. A 3D printed portable photometer is fabricated, which can measure the glucose concentration ranging from 10 mg/dL to 1400 mg/dL and the ketone concentration spanning over 5 mg/dL to 160 mg/dL. This is helpful for preliminary detection of Diabetes related health issues such as Glycosuria or Ketonuria. Clinical sample analyses showed a reasonable match with the pathology test. The device is made digitally smart by integrating a Mobile App to store patient data.

Plasma small‐extracellular vesicles enriched in miR‐122‐5p promote disease aggressiveness in pediatric anaplastic large‐cell lymphoma

Plasma small‐extracellular vesicles enriched in miR‐122‐5p promote disease aggressiveness in pediatric anaplastic large‐cell lymphoma