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Genotypic and enviromentally friendly variation of zinc content material within the feed of springtime bread wheat varieties in the intercontinental gardening shop KASIB.
This proof-of-concept study demonstrated the potential of Raman-DIP to be a reliable tool for cancer drug discovery and drug susceptibility testing.In recent years, the popularity of wearable devices has fostered the investigation of automatic fall detection systems based on the analysis of the signals captured by transportable inertial sensors. Due to the complexity and variety of human movements, the detection algorithms that offer the best performance when discriminating falls from conventional Activities of Daily Living (ADLs) are those built on machine learning and deep learning mechanisms. In this regard, supervised machine learning binary classification methods have been massively employed by the related literature. However, the learning phase of these algorithms requires mobility patterns caused by falls, which are very difficult to obtain in realistic application scenarios. An interesting alternative is offered by One-Class Classifiers (OCCs), which can be exclusively trained and configured with movement traces of a single type (ADLs). In this paper, a systematic study of the performance of various typical OCCs (for diverse sets of input features and hyperparameters) is performed when applied to nine public repositories of falls and ADLs. The results show the potentials of these classifiers, which are capable of achieving performance metrics very similar to those of supervised algorithms (with values for the specificity and the sensitivity higher than 95%). However, the study warns of the need to have a wide variety of types of ADLs when training OCCs, since activities with a high degree of mobility can significantly increase the frequency of false alarms (ADLs identified as falls) if not considered in the data subsets used for training.This work demonstrates the analysis of epinephrine (EP) and uric acid (UA) in a single drop (the volume of the test solution was only 50 µL) using a screen-printed carbon electrode (SPCE) sensor and square-wave voltammetry (SWV). The limit of detection, limit of quantification, linearity, accuracy, precision, and robustness were validated. The normality of the experimental data was tested and confirmed for both methods. Heteroscedasticity was checked by residual analysis followed by a statistical F-test. The latter was confirmed for both analytes. The low relative standard deviations (RSD) at all calibration points and repetitive slopes justified the use of a calibration curve; therefore, the standard addition methodology was avoided (the latter is common in electroanalysis, but time-consuming). Since the conditions for using an ordinary least squares (OLS) regression were not met, weighted linear regression (WLR) was used to improve the accuracy of the analytical results at low concentrations of the analytes. In this manner, the best weighted model was determined and used for the quantification. A comparison was made between the OLS and WLR methods to show the necessity of using the WLR method for EP and UA analysis. The newly developed and validated methods were also shown to be effective in the analysis of real samples. The content of EP in an EP auto-injector and UA in human urine was tested by employing the best weighted model. For EP and UA, the accuracy in terms of the average recovery value was 101.01% and 94.35%, and precision in terms of RSD was 5.65% and 2.75%, respectively. A new analytical methodology is presented that uses a low volume (a single drop), and it offers the advantage of electroanalysis for on-site analysis, where conventional chromatographic techniques cannot be easily employed. Furthermore, the developed technique has additional advantages in terms of speed, cost, and miniaturization.Since the discovery of antibiotics, the emergence of antibiotic resistance has become a global issue that is threatening society. In the era of antibiotic resistance, finding the proper antibiotics through antibiotic susceptibility testing (AST) is crucial in clinical settings. However, the current clinical process of AST based on the broth microdilution test has limitations on scalability to expand the number of antibiotics that are tested with various concentrations. Here, we used color-coded droplets to expand the multiplexing of AST regarding the kind and concentration of antibiotics. Color type and density differentiate the kind of antibiotics and concentration, respectively. Microscopic images of a large view field contain numbers of droplets with different testing conditions. Image processing analysis detects each droplet, decodes color codes, and measures the bacterial growth in the droplet. Testing E. coli ATCC 25922 with ampicillin, gentamicin, and tetracycline shows that the system can provide a robust and scalable platform for multiplexed AST. Furthermore, the system can be applied to various drug testing systems, which require several different testing conditions.As pH value almost affects the function of cells and organisms in all aspects, in biology, biochemical and many other research fields, it is necessary to apply simple, intuitive, sensitive, stable detection of pH and base characteristics inside and outside the cell. VX-11e Therefore, many research groups have explored the design and application of pH probes based on surface enhanced Raman scattering (SERS). In this review article, we discussed the basic theoretical background of explaining the working mechanism of pH SERS sensors, and also briefly described the significance of cell pH measurement, and simply classified and summarized the factors that affected the performance of pH SERS probes. Some applications of pH probes based on surface enhanced Raman scattering in intracellular and extracellular pH imaging and the combination of other analytical detection techniques are described. Finally, the development prospect of this field is presented.Due to the great threat posed by excessive nitrite in food and drinking water to human health, it calls for developing reliable, convenient, and low-cost methods for nitrite detection. Herein, we string nanozyme catalysis and diazotization together and develop a ratiometric colorimetric approach for sensing nitrite in food. First, hollow MnFeO (a mixture of Mn and Fe oxides with different oxidation states) derived from a Mn-Fe Prussian blue analogue is explored as an oxidase mimic with high efficiency in catalyzing the colorless 3,3',5,5'-tetramethylbenzidine (TMB) oxidation to blue TMBox, presenting a notable signal at 652 nm. Then, nitrite is able to trigger the diazotization of the product TMBox, not only decreasing the signal at 652 nm but also producing a new signal at 445 nm. link2 Thus, the analyte-induced reverse changes of the two signals enable us to establish a ratiometric colorimetric assay for nitrite analysis. According to the above strategy, facile determination of nitrite in the range of 3.3-133.3 μM with good specificity was realized, providing a detection limit down to 0.2 μM. Compared with conventional single-signal analysis, our dual-signal ratiometric colorimetric mode was demonstrated to offer higher sensitivity, a lower detection limit, and better anti-interference ability against external detection environments. Practical applications of the approach in examining nitrite in food matrices were also verified.The accurate analysis of circulating tumor cells (CTCs) holds great promise in early diagnosis and prognosis of cancers. However, the extremely low abundance of CTCs in peripheral blood samples limits the practical utility of the traditional methods for CTCs detection. Thus, novel and powerful strategies have been proposed for sensitive detection of CTCs. In particular, nanomaterials with exceptional physical and chemical properties have been used to fabricate cytosensors for amplifying the signal and enhancing the sensitivity. In this review, we summarize the recent development of nanomaterials-based optical and electrochemical analytical techniques for CTCs detection, including fluorescence, colorimetry, surface-enhanced Raman scattering, chemiluminescence, electrochemistry, electrochemiluminescence, photoelectrochemistry and so on.Cyanobacterial bloom is one of the most urgent global environmental issues, which eventually could threaten human health and safety. Sonication treatment (ST) is a potential effective method to control cyanobacteria blooms in the field. Currently, the bottleneck of extensive application of ST is the difficulty to estimate the ST effect on the cyanobacterial cells and then determine suitable ST times in the field. In this study, cyanobacterial Microcystis samples sonicated at different times were first measured by a spectrophotometer to calculate the removal efficiency of Microcystis cells. Additionally, they were observed by TEM to reveal the intracellular structure changes of the cells. Then the samples were measured by an experimental setup based on polarized light scattering to measure the polarization parameters. Experimental results indicated that the polarization parameters can effectively characterize the intracellular structural changes of Microcystis cells with different ST times, which is quite consistent with the results for removal efficiency and TEM images. Further, the optimal ST time can be inferred by the polarization parameters. These results demonstrate that polarized light scattering can be a potentially powerful tool to explore suitable times for sonication treatment of cyanobacteria blooms.Circulating tumor cells (CTCs) are an indicator of metastatic progression and relapse. Since non-CTC cells such as red blood cells outnumber CTCs in the blood, the separation and enrichment of CTCs is key to improving their detection sensitivity. The ATP luminescence assay can measure intracellular ATP to detect cells quickly but has not yet been used for CTC detection in the blood because extracellular ATP in the blood, derived from non-CTCs, interferes with the measurement. Herein, we report on the improvement of the ATP luminescence assay for the detection of CTCs by separating and concentrating CTCs in the blood using a 3D printed immunomagnetic concentrator (3DPIC). Because of its high-aspect-ratio structure and resistance to high flow rates, 3DPIC allows cancer cells in 10 mL to be concentrated 100 times within minutes. This enables the ATP luminescence assay to detect as low as 10 cells in blood, thereby being about 10 times more sensitive than when commercial kits are used for CTC concentration. This is the first time that the ATP luminescence assay was used for the detection of cancer cells in blood. These results demonstrate the feasibility of 3DPIC as a concentrator to improve the detection limit of the ATP luminescence assay for the detection of CTCs.The impaired blood flow to the brain causes a decrease in the supply of oxygen that can result in cerebral ischemia; if the blood flow is not restored quickly, neuronal injury or death will occur. link3 Under hypoxic conditions, the production of nitric oxide (●NO), via the classical L-arginine-●NO synthase pathway, is reduced, which can compromise ●NO-dependent vasodilation. However, the alternative nitrite (NO2-) reduction to ●NO, under neuronal hypoxia and ischemia conditions, has been viewed as an in vivo storage pool of ●NO, complementing its enzymatic synthesis. Brain research is thus demanding suitable tools to probe nitrite's temporal and spatial dynamics in vivo. In this work, we propose a new method for the real-time measurement of nitrite concentration in the brain extracellular space, using fast-scan cyclic voltammetry (FSCV) and carbon microfiber electrodes as sensing probes. In this way, nitrite was detected anodically and in vitro, in the 5-500 µM range, in the presence of increasing physiological concentrations of ascorbate (100-500 µM).
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