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Hypertension is a chronic condition with multiple drug regimens. Limiting these medicines is critical to patient compliance. Therefore, bisoprolol and telmisartan were recently developed in a fixed-dose combination to control blood pressure. The UV absorption spectra of bisoprolol and telmisartan overlapped significantly. Thus, three spectrophotometric methods have been developed for simultaneous determination of bisoprolol and telmisartan without prior separation. Method A is ratio difference of ratio spectra (RD), which measures the amplitude difference between (210–224) nm for bisoprolol and between (255–365) nm for telmisartan. Method B, the first derivative of ratio spectra ( 1 DD), measures amplitude signals at 232 and 243 nm for bisoprolol and telmisartan, respectively. Method C is the mean centering of ratio spectra (MC), which measures the mean-centered ratio spectra's values at 223 nm for bisoprolol and 245 nm for telmisartan. The applied methods showed good linearity 2–20 µg/mL for bisoprolol, 4–32 µg/mL for telmisartan, with sufficient accuracy and precision. The methods were sensitive, with LOD values of 0.243 µg/mL and 0.596 µg/mL in RD method, 0.313 µg/mL and 0.914 µg/mL in 1 DD method, and 0.406 and 0.707 µg/mL in MC method for bisoprolol and telmisartan, respectively, the methods were validated per ICH criteria. The novel methods are precise and accurate and can be used for routine analysis and quality control of bisoprolol and telmisartan in pure and dosage form. Furthermore, the greenness of the approaches was evaluated using Analytical Greenness assessment (AGREE), and the suggested method received a high greenness score.

We report a miniature, visible to near infrared G-Fresnel spectrometer that contains a complete spectrograph system, including the detection hardware and connects with a smartphone through a microUSB port for operational control. The smartphone spectrometer is able to achieve a resolution of ~5 nm in a wavelength range from 400 nm to 1000 nm. We further developed a diffuse reflectance spectroscopy system using the smartphone spectrometer and demonstrated the capability of hemoglobin measurement. Proof of concept studies of tissue phantoms yielded a mean error of 9.2% on hemoglobin concentration measurement, comparable to that obtained with a commercial benchtop spectrometer. The smartphone G-Fresnel spectrometer and the diffuse reflectance spectroscopy system can potentially enable new point-of-care opportunities, such as cancer screening.

Though the Lovibond colorimetric method is effective for determining oil colour, it is a visual comparison method which relies on manual visual reading. As a result, this method is vulnerable to the influence of subjective factors of testers and is of low accuracy. In this paper, the original index of oil colour grading based on Lovibond colour space is changed to the index of oil colour grading based on uniform colour space, and a new method is proposed to determine oil colour by spectrophotometry. The experimental results show that there is a strong correlation between Lovibond red value and the chroma index a *, and a strong correlation between Lovibond yellow value and the chroma index b *. So the method greatly improves the detection efficiency and avoids a series of disadvantages of the visual method.

A simple, accurate, precise, rapid, economical UV spectrophotometry method namely first order derivative spectrophotometry have been developed and validated for estimation of Indapamide (IND) and Amlodipine besylate (AML) in combined tablet dosage form, and can be used in routine analysis. In this method, the absorbance at 237.4 nm (ZCP of AML) and 241 nm (ZCP of IND) were used for estimation of IND and AML respectively. The method was found to be linear in the concentration range of 1.5-9 μg/ml for IND (r^SUP 2^=0.99983) and 5-30 μg/ml for AML (r^SUP 2^=0.99966). Mean assay was found to be 99.72%, and 100.28% for IND and AML respectively.

Colorectal cancer (CRC) is the third most common type of cancer worldwide and the second most deadly. Recent research efforts have focused on developing non-invasive techniques for CRC detection. In this study, we evaluated the diagnostic capabilities of diffuse reflectance spectroscopy (DRS) for CRC detection by building 6 classification models based on support vector machines (SVMs). Our dataset consists of 2889 diffuse reflectance spectra collected from freshly excised ex vivo tissues of 47 patients over wavelengths ranging from 350 and 1919 nm with source-detector distances of 630-µm and 2500-µm to probe different depths. Quadratic SVMs were used and performance was evaluated using twofold cross-validation on 10 iterations of randomized training and test sets. We achieved (93.5 ± 2.4)% sensitivity, (94.0 ± 1.7)% specificity AUC by probing the superficial colorectal tissue and (96.1 ± 1.8)% sensitivity, (95.7 ± 0.6)% specificity AUC by sampling deeper tissue layers. To the best of our knowledge, this is the first DRS study to investigate the potential of probing deeper tissue layers using larger SDD probes for CRC detection in the luminal wall. The data analysis showed that using a broader spectrum and longer near-infrared wavelengths can improve the diagnostic accuracy of CRC as well as probing deeper tissue layers.

In this study, we describe the synthesis and characterization of silver nanoparticles (Ag-NPs) of different sizes and evaluated their antibacterial activity. Particles size and morphology were characterized by transmission electron microscopy. Evaluation of the bacteriostatic effects was performed by ultraviolet-visible spectrophotometry and comet assays. The smaller the particle size of Ag-NPs, the smaller the value of the minimum inhibitory concentration (MIC) and minimum bactericidal concentrations (MBC), indicating the greater the antibacterial activity. The antibacterial activity was determined by the generation of reactive oxygen species (ROS) by bacteria and by bacterial membrane damage. In this study, we determined ROS-induced damage of bacteria caused by Ag-NPs. In conclusion, our findings indicated that Ag-NPs were effective at different particle sizes and concentrations and that the smaller the particle size of Ag-NPs, the greater the antibacterial activity.

Reactive oxygen species (ROS) are reactive compounds derived from oxygen. In biological systems, an excessive amount of ROS can cause oxidative damage to biological macromolecules being involved in different diseases. Several assays have been developed in the last 30 years for ROS evaluation. The objective of this article will be to provide an update about the spectrophotometric methods currently used in the assessment of ROS in serum. The chemical basis of four different techniques will be reviewed, and examples of their possible applications will be provided. A particular emphasis about the practical applications of these assays in the dog will be made, but selected information about their use in humans will also be presented for comparative purposes, following a One-Health approach. The information about the spectrophotometric assays presented in this paper should be interpreted with caution once limited information about them is available yet, and further studies should be performed to clarify what they measure and their clinical application. Ideally, when applied to evaluate a sample’s oxidative status, they should be incorporated in a panel of analytes where other oxidants, antioxidants, and biomarkers of inflammation were also included.

Accurate DNA quantification is key for downstream application including library preparations for whole genome sequencing (WGS) and the quantification of standards for quantitative PCR. Two commonly used technologies for nucleic acid quantification are based on spectrometry, such as NanoDrop, and fluorometry, such as Qubit. The DS–11+ Series spectrophotometer/fluorometer (DeNovix) is a UV spectrophotometry-based instrument and is a relatively new spectrophotometric method but has not yet been compared to established platforms. Here, we compared three DNA quantification platforms, including two UV spectrophotometry-based techniques (DeNovix and NanoDrop) and one fluorometry-based approach (Qubit). We used genomic prokaryotic DNA extracted from Streptococcus pneumoniae using a Roche DNA extraction kit. We also evaluated purity assessment and effect of a single freeze-thaw cycle. Spectrophotometry-based methods reported 3 to 4-fold higher mean DNA concentrations compared to Qubit, both before and after freezing. The ratio of DNA concentrations assessed by spectrophotometry on the one hand, and Qubit on the other hand, was function of the A 260/280 . In case DNA was pure (A 260/280 between 1.7 and 2.0), the ratio DeNovix or Nanodrop vs. Qubit was close or equal to 2, while this ratio showed an incline for DNA with increasing A 260/280 values > 2.0. The A 260/280 and A 260/230 purity ratios exhibited negligible variation across spectrophotometric methods and freezing conditions. The comparison of DNA concentrations from before and after freezing revealed no statistically significant disparities for each technique. DeNovix exhibited the highest Spearman correlation coefficient (0.999), followed by NanoDrop (0.81), and Qubit (0.77). In summary, there is no difference between DeNovix and NanoDrop in estimated gDNA concentrations of S . pneumoniae , and the spectrophotometry methods estimated close or equal to 2 times higher concentrations compared to Qubit for pure DNA.

Leaf hyperspectral reflectance can be used by the wheat physiology and breeding communities to rapidly estimate Rubisco activity, electron transport rate, leaf nitrogen, leaf dry mass per area, and relative chlorophyll content. Abstract Improving photosynthesis to raise wheat yield potential has emerged as a major target for wheat physiologists. Photosynthesis-related traits, such as nitrogen per unit leaf area (Narea) and leaf dry mass per area (LMA), require laborious, destructive, laboratory-based methods, while physiological traits underpinning photosynthetic capacity, such as maximum Rubisco activity normalized to 25 °C (Vcmax25) and electron transport rate (J), require time-consuming gas exchange measurements. The aim of this study was to assess whether hyperspectral reflectance (350-2500 nm) can be used to rapidly estimate these traits on intact wheat leaves. Predictive models were constructed using gas exchange and hyperspectral reflectance data from 76 genotypes grown in glasshouses with different nitrogen levels and/or in the field under yield potential conditions. Models were developed using half of the observed data with the remainder used for validation, yielding correlation coefficients (R2 values) of 0.62 for Vcmax25, 0.7 for J, 0.81 for SPAD, 0.89 for LMA, and 0.93 for Narea, with bias <0.7%. The models were tested on elite lines and landraces that had not been used to create the models. The bias varied between −2.3% and −5.5% while relative error of prediction was similar for SPAD but slightly greater for LMA and Narea.