Total white blood cell counts (WBC) are an important indication of infection diagnosis in both human and veterinary medicine. State-of-the-art WBC counts are performed by flow cytometry combined with light scattering or impedance measurements in the clinical analysis laboratory. These technologies are complex and difficult to be miniaturized into a portable point-of-care (POC) system. Spectroscopy is one of the most powerful technologies for POC miniaturization due to its capacity to analyze low sample quantities, little to no sample preparation, and 'real-time' results. WBC is in the proportion of ~1:1000 to red blood cells (RBC), and the latter dominate visible-near infrared (Vis-NIR) information by their large quantities and hemoglobin absorbance. WBC are difficult to be detected by traditional spectral analysis because their information is contained within the interference of hemoglobin bands.

Herein, we perform a feasibility study for the direct detection of WBC counts in canine blood by Vis-NIR spectroscopy for veterinarian applications, benchmarking current chemometric techniques with self-learning artificial intelligence - a new advanced method for high-accuracy quantification from spectral information. Results show that total WBC counts can be detected by Vis-NIR spectroscopy to an average detection limit of 7.8×10⁹ cells/L, with an R² of 0.9880 between impedance flow cytometry analysis and spectral quantification. This result opens new possibilities for reagent-less POC technology in infection diagnosis. As WBC counts in dogs range from 5 to 45 ×10⁹ cells/L, the detection limit obtained in this research allows concluding that the combined use of spectroscopy with SL-AI new algorithm is a step towards the existence of portable and miniaturized Spectral POC hemogram analysis.

Total platelet counts (TPC) allow the determination of thrombocytosis, a risk factor for stroke, heart attack, and blood clots. TPC is generally performed at the laboratory by flow cytometry with laser scattering or impedance detection. Due to inaccuracies in quantification, clinical pathologists rely on microscopy counts using the Neubauer chamber technique as a quality control measure. In many health conditions, regular follow-up of coagulation risk is crucial, therefore point-of-care (POC) diagnosis simplifies these procedures, taking platelet counts to the bedside.

Spectroscopy has a high potential for reagent-less POC miniaturized technologies. However, platelet detection in blood by standard spectroscopy analysis is challenging, due to their small size, low number when compared to red blood cells, and low spectral contrast comparing to hemoglobin.

In this exploratory research, we show that is possible to perform TPC by advanced spectroscopy analysis using a new processing methodology with self-learning artificial intelligence. Results show that TPC can be measured by visible-near infrared spectroscopy above the detection limit of 121×10⁹ cells/L (R²=0.9922), tested within the data range of 53×10⁹ to 860×10⁹ cells/L in dog blood. These results open the possibility for spectroscopy as a diagnostic technology for detecting high levels of platelet counts, directly in whole blood, towards the rapid POC diagnosis of thrombocytosis and stroke prevention.

Red blood cells (RBC) and white blood cells (WBC) counts are an important part of hemogram diagnosis. These are quantified by laboratory flow cytometry analysis with laser scattering or impedance detection. The measurement is also complemented by manual microscopy counts using the Neubauer chamber technique. Scattering of single cells is already used as a standard technology for differentiated cell counts in flow cytometry, but it implies capillary cell separation. This research explores the scattering properties of whole blood to determine correlations with RBC and WBC counts. Scattering information in blood samples can be categorized as i. geometrical scattering where non-absorbed light is scattered by reflection; ii. Mie scattering - where light is scattered by particles of similar size of the wavelength; and iii. Rayleigh scattering - where light is scattered by particles smaller than the wavelength of incident light. Herein, we explore the scattering correction coefficients of visible - near-infrared (Vis-NIR) of 320-850 nm dog blood absorption spectra to derive direct correlations to RBC and WBC counts using multivariate linear regression (MLR). Results show the feasibility of categorical and classification of the scattering properties of dog blood, allowing the discrimination of high and low values of both RBC and WBC, as well as, their categorical quantification: i. RBC with a correlation of 0.5739 and a standard error of 1.33 log10(cells/L); and ii. WBC with a correlation of 0.5900 and a standard error of 7.70 log10(cells/L) when compared to cell cytometry impedance counts.

Rheumatoid arthritis is an autoimmune disorder characterized by persistent erosive synovitis, systemic inflammation, and the presence of autoantibodies, which play an important role in inducing inflammation and joint damage, releasing pro-inflammatory cytokines from monocytes and macrophages [1,2]. Likewise, neutrophil activating protein-2 (CXCL7) is a platelet-derived growth factor belonging to the CXC chemokine subfamily, which is expressed in serum, synovial fluid, and synovial tissue of patients developing rheumatoid arthritis during the first twelve weeks, being useful to reflect local pathological changes [3]. Besides, matrix metalloproteinase-3 (MMP-3), which is induced by inflammatory cytokines such as interleukin-1 (IL-1) and tumor necrosis factor alpha (TNF-α) in rheumatoid synovium, degrades several extracellular matrix components of cartilage and plays central roles in rheumatoid joint destruction [4]. Thereby, monitoring serum CXCL7 and MMP-3 levels is useful for predicting the disease activity in rheumatoid arthritis.

In this work, the construction and analytical performance of a dual electrochemical platform for the simultaneous determination of CXCL7 and MMP-3 is described. After the optimization of experimental variables involved in the preparation and implementation of the biosensor, the analytical usefulness of the developed configuration was demonstrated by its application to the determination of these biomarkers in serum samples from healthy individuals and patients with rheumatoid arthritis. In addition, the results obtained using the dual immunosensor were compared with those provided by the respective ELISA immunoassays, yielding no significant differences between the two methods.

References:

[1] W.H. Bos, G.J. Wolbink, M. Boers, G.J. Tijhuis, N. de Vries, I.E. van der Horst-Bruinsma, P.P. Tak, R.J. van de Stadt, C.J. van der Laken, B.A.C. Dijkmans and D. van Schaardenburg, 2010. Arthritis development in patients with arthralgia is strongly associated with anti-citrullinated protein antibody status: a prospective cohort study. Ann. Rheum. Dis., 69, 490–494

[2] D.L. Scott, F. Wolfe and T.W.J. Huizinga, 2010. Rheumatoid arthritis Lancet, 376, 1094–1108

[3] S. Guerrero, D. Cadano, LM. Agüí, R. Barderas, S. Campuzano, P. Yáñez-Sedeño and J.M. Pingarrón, 2019. Click chemistry-assisted antibodies immobilization for immunosensing of CXCL7 chemokine in serum J. Electroanal. Chem. 837, 246–253

[4] E. Sugiyama, 2007. Role of matrix metalloproteinase-3 in joint destruction in rheumatoid arthritis. Clin. Calcium, 17, 528–534

Bladder cancer (BC) is the 10^th most common cancer in the world. It has no available screening methods for the general population. This leaves diagnosis to be made late on, with the start of symptoms and this is reflected in the poor survival rate.

The use of VOCs that emanate from human waste is providing new perspective for the early detection cancer. VOCs emitted from the human body can be qualitatively and quantitatively measured. Gas chromatography-mass spectrometry (GC-MS) is considered as the golden standard but, due to its high cost and long analysis time, it may not be as efficient for screening. An alternative method is to use an electronic nose, which is designed to mimic the biological olfactory system. This instrument provides real time analysis, is less expensive and easily portable. This study describes the use of an electronic nose to measure VOC biomarkers emanating from urine to diagnose BC.

Here an AlphaMOS FOX 4000 electronic nose was used to analyse samples from 15 BC and 41 non-BC patients, recruited from University Hospital Coventry and Warwickshire, UK. The FOX 4000 consisted of 18 Metal-oxide based sensors. The change in resistance before and after exposure to a urine sample was used as the feature and the data was processed in ‘R’ using two machine learning classifiers. The data was analysed using a 10-fold cross validation with the resultant probabilities used to calculate statistical parameters. The results showed a high separation between BC and non-cancerous with sensitivity and specificity of 0.93 and 0.88 respectively using Sparse Logistic Regression and 0.93 and 0.76 using Random Forest classifier. We concluded that the electronic nose shows potential for discriminating bladder cancer from non-cancer samples. This is the first study in our knowledge which used the AlphaMOS FOX 4000 for this purpose.

Chemoresistive gas sensors based on semiconducting metal oxides (MOX) have been successful realized and fabricated for many years. They are used in many applications, such as automotive, indoor air quality and smart phones. They offer many advantages in compare to other gas sensing principles. They are inexpensive, simple, cheap, stable and can be very sensitive. There is continuous effort to improve the performance of these sensors. All MOX gas sensors used deposited sensing layer over insulating substrate provided with electrodes and heaters. First sensors have used thick film in alumina subtrates or on alumina tubes. Such sensors are still successful on the market. Such gas sensors typically are exhibiting a power consumption of 0.2 to 1 W. Silicon micromachining technology offers some important advantages such as high volume production and small feature size. Typically a thermally insulated heating elements suspended on a dialectric membrane such SiN, SiO or SiC is realized. Au or Pt electrodes are patterned on top of the membrane. This concept helps to reduce the power consumtion. With this concept MOX gas sensors with lower power (<200mW) have been realized.

In this paper we report on novel gas sensors platform using standard MEMS micromachining technology and the rGO material as concept to increase the sensing surface with the goal to increase the sensitivity and reduce the power consumption. A standard IDE (Au Interdigital Electrodes) platform has been used as substrate. On top of the IDE elecrodes a thin rGO-layer with 3D arrangement has been deposited using the Electrophoretic Deposition (EPD) technique. This increases the sensor surface significantly. To fabricate the novel 3D arranged Graphene biosensor, the reduced Graphene Oxide - Polyethylene Glycol - Amine (rGO-PEG-NH2) was suspended in Isopropyl alcohol. The ζ-potential of the in-solution Graphene flakes was optimized adding MgCl2 · 6H2O and enhanced to +46 mV. A high performance ultrasonic mixer is used to crumple and disperse the rGO-PEG-NH2 flakes within the solvent. The layer thickness can be tuned by using deposition time and current. The sensing MOX material (nano particles like CuO, ZnO) has been deposited by drop casting on the surface of the 3D arranged rGO-layer. First results show very promising behavior of the new platform – alcohol, CO and CO₂ have been detected even at room temperature.

Carotenoids are among of the most important bioactive compounds in food products due to their antioxidant, coloring, provitamin A and many health-related properties. Unfortunately, they are some of the most sensitive substances to heat, light, oxygen and acidic environments; hence, common food processing techniques cause important degradations of carotenoids, decreasing both the nutritional value and the appearance of carotenoid-containing foods. For assessing the stability of carotenoids during some thermal food processing procedures, the fruits of Cucurbita maxima Duch. (pumpkin) were selected, the main reason of this choice being both the amount and the diversity of carotenoids they contain, this study including both carotenes and xanthophylls. An optimized high performance liquid chromatography (HPLC) method was developed in order to properly quantify the involved carotenoids. Samples from both raw and processed fruits were extracted with acetone and diethyl ether; liquid-liquid extractions were then performed to transfer carotenoids in diethyl ether, being followed by saponification’s with methanolic potassium hydroxide. HPLC separations were achieved in less than 20 minutes, using a Nucleosil 120-3C₁₈ column, with a gradient involving acetonitrile : water (9 : 1) and ethyl acetate; detection was accomplished using a Waters photodiode array detector. The identification of carotenoids was achieved on the basis of their visible spectral characteristics, retention times amd co-chromatography with standards; for quantification the external standard method was used. A differential degradation of carotenoids was observed, depending on the processing method: during the thermal processing, both xanthophylls and carotenes were affected, zeaxanthin and violaxanthin being the most sensitive carotenoids, while cucurbitaxanthin A and lutein and were the most stable ones. The decrease with almost one third of the provitamin A activity during thermal processing was mainly due to the degradation of beta-carotene.

Natural phenolic antioxidants are extensively studied compounds in modern electroanalysis due to their positive health effect and widely distribution in human diet. Simultaneous occurrence in the sample requires selective methods for their determination. Various types of electrochemical sensors have been developed for these purposes. Among a wide range of natural phenolics, vanillin and its biological precursor ferulic acid are of practical interest but out of consideration in electroanalysis. Electrochemical sensors based on the polyaminobenzene sulfonic acid functionalized single-walled carbon nanotubes and electropolymerized bromocresol purple has been developed for the simultaneous quantification of ferulic acid and vanillin. Conditions of bromocresol purple potentiodynamic electropolymerization (monomer concentration, number of scans, supporting electrolyte pH, electrolysis parameters) have been optimized in order to find the best voltammetric response of the co-existed analytes. The electrode has been characterized by SEM and electrochemical methods and the effectivity of the modifier developed has been confirmed. The well-resolved oxidation peaks of the ferulic acid and vanillin with potential separation of 170 mV has been obtained on the sensor created. The analytes electrooxidation parameters have been calculated. Sensor developed allows direct simultaneous quantification of ferulic acid and vanillin in the ranges of 0.1-5.0 and 5.0-25 µM for both analytes with the LODs of 72 and 64 nM, respectively. Thus, novel sensitive voltammetric sensor is simple in fabrication, reliable, cost-effective and can be applied for the foodstuff screening.

Chemical Oxygen Demand (COD) is a widely used parameter in analysing and controlling the degree of pollution in water. COD is defined as the amount of molecular oxygen (in milligrams of O₂) required to decompose all the organic compounds in 1 L of aqueous solution to carbon dioxide and water. There are many methods reported for COD determination, such as the conventional dichromate titration method. Electro-oxidizing the organic contaminants to completely transform them into CO₂ and H₂O using sensors is considered the best method for COD estimation. Increasing attention has been paid to electrochemical methods because they are highly sensitive, time-saving, low-cost, and easy to operate. In this sense, copper electrodes have been reported based on the fact that copper in alkaline media acts as a powerful electrocatalyst for oxidation of aminoacids and carbohydrates, which are believed to be the major culprits for organic pollution. Cyclic voltammetry was the technique used to obtain the voltammetric responses. Commonly, different organic compounds show different shapes of cyclic voltammograms and different current intensity in different concentrations.

In this work, four kinds of electrodes modified with copper (Cu)/copper oxide (CuO)/nickel copper alloy (Ni Cu alloy) nanoparticles were studied for COD analysis employing the cyclic voltammetry technique: Nafion film covered electrodeposited CuO/Cu nanoparticle electrode (E1), Cu nanoparticle-graphite composite electrode (E2), CuO nanoparticle-graphite composite electrode (E3) and Ni Cu alloy nanoparticle-graphite composite electrode (E4). The COD values were determined by the ploted calibration of COD values vs. the current intensity. Glucose, glycine, potassium hydrogen phthalate (KHP) and ethylene glycol, which show different reducibilities, were chosen to be the standard substances to play the role of organic contaminants with different degradation difficulties.

From the obtained cyclic voltammograms, we can see that glucose is very easy to be oxidized by those four electrodes and electrode E1 shows the best performance, with a linear range of 19.2~1120.8 mg/L and limit of detection of 27.5 mg/L. Besides, the compound KHP is very difficult to be oxidized by these four electrodes. Nevertheless, the obtained voltammetric profiles presented different shapes with the tested organic compounds, suggesting these four electrodes can compose an electronic tongue array for multivariate analysis. As a result, the main component of river samples, which is easy or difficult to be degraded, can be evaluated by the PCA technique. This evaluation is very helpful for the accuracy of COD detection. The resulting sensor-based method demonstrates great potential not only for estimating the precise value of COD, but for predicting the difficulty behavior in its degradation, in a simple, fast, and clean methodology, which is completely suited to the present demands of green techniques.

Mycotoxins are the toxic secondary metabolites naturally produced by fungi, their contamination in agricultural products and food severely threaten food safety and public health worldwide. The reliable, efficient and sensitive quantification of mycotoxins in food have become increasing challenging to tackle due to the complexity of food matrices and their low level. Visual detection has emerged as a popular trend toward miniaturization and simplification of mycotoxins assays yet is constrained with their limited sensitivity. In this review, we mainly focus on the various kinds of the visual immunoassays by utilizing nanomaterials for loading enzyme and nanozyme. These enzymes have been as signal amplification for the improved sensitivity of mycotoxins detection through the various enzymatic catalytic reaction. Besides, the underlying principle and the advantages of the visual immunoassays for mycotoxins have been proposed. And the challenges and perspectives have been proposed to develop improved efficient catalytic detection strategies for mycotoxins in food.