Substituted phenols, including chlorophenols, are important analytes, particularly in the context of environmental analysis. Chlorophenols are formed during the disinfection of drinking water by chlorination and are important water pollutants. Gas chromatography–mass spectrometry (GC-MS) is an important method for the analysis of chlorophenols. Retention indices are used in GC-MS analysis to improve the accuracy of identification. Our research reveals that the retention indices currently available for substituted phenols are erroneous in a number of cases. We report reliable retention index values for pentafluorophenol, 5-methoxy-2-nitrophenol, 4-cyanophenol (stationary phase: 5%-phenyl-polymethylsiloxane), 3-methoxyphenol, 2-chlorophenol, 3-chlorophenol, 4-chlorophenol, 2,3-dichlorophenol, 2,5-dichlorophenol, 2,6-dichlorophenol, 3,4-dichlorophenol, 3,5-dichlorophenol, 2,3,5-trichlorophenol, 2,3,6-trichlorophenol, 2,4,5-trichlorophenol, and 2,4,6-trichlorophenol (stationary phase: polyethylene glycol modified with 2-nitroterephthalic acid). The structures of the standard samples were confirmed, and measurements were performed under various conditions. The analysis of the causes of the incorrect records appearing in the well-known NIST database was also carried out.

Addition of Two Authors [...]

Canine olfaction is a highly developed sense and is utilized for the benefit of detection applications, ranging from medical diagnostics to homeland security and defense prevention strategies. Instrumental validation of odor delivery methods is key to standardize canine olfaction research to establish baseline data for explosive detection applications. Solid-phase microextraction gas chromatography (SPME/GC-MS) was used to validate the odor delivery of an olfactometer. Three explosive classes were used in this study: composition C-4 (C-4), trinitrotoluene (TNT), and ammonium nitrate (AN). Dynamic airflow sampling yielded the successful detection of previously reported target volatile organic compounds (VOCs): 2,3-dimethyl-2,3-dinitrobutane (DMNB) in C-4 and 2-ethylhexan-1-ol (2E1H) in ammonium nitrate and TNT across odor dilutions of 80%, 50%, 25%, 12%, and 3%. C-4 highlighted the most reliable detection from the olfactometer device, depicting a response decrease as a function of dilution factor of its key odor volatile DMNB across the entire range tested. TNT only portrayed 2-ethylhexan-1-ol as a detected odor volatile with a detection response as a function of dilution from 80% down to 12%. Comparatively, ammonium nitrate also depicted 2-ethylhexan-1-ol as an odor volatile in the dynamic airflow sampling but with detection only within the upper scale of the dilution range (80% and 50%). The results suggest the importance of monitoring odor delivery across different dilution ranges to provide quality control for explosive odor detection using dynamic airflow systems.

Catechol (CT) is a phenolic compound widely used in various industrial sectors, but it is toxic; thus, there is a need for methods that aim to identify and quantify the existence of residues of this material in the environment. In this study a disposable printed electrochemical sensor was developed as an effective alternative for determining CT in water samples. The electrode, called SPEC, was manufactured using the screen-printing method using polyethylene terephthalate (PET) as a support, in which a conductive ink based on carbonaceous materials was used to print the working and auxiliary electrodes and a silver/silver chloride of ink on the reference electrode. The optimal ratio for the conductive ink was 6.25% carbon black, 35.42% graphite, and 58.33% nail polish. The ink obtained was characterized by scanning electron microscopy (SEM). The assessment of the effect of pH on the redox process showed Nernstian behavior (0.057 V pH−1), indicating that the process involves the same number of protons and electrons. Under optimized conditions, with 0.2 mol L−1 acetate buffer at pH 5.0, and by square wave voltammetry, the sensor presented sensitivity values of 0.31 μA L μmol−1, a detection limit of 5.96 μmol L−1, and a quantification limit of 19.87 μmol L−1. The sensor was applied to determine CT in tap water samples, and the results showed recoveries between 97.95 and 100.17%.

Gold nanoclusters are peculiar objects promising in view of qualitative and quantitative determination of various species, including heavy metal ions and biological molecules. We have recently discovered that introducing sodium azide in the reaction mixture during gold nanocluster synthesis in the presence of citrate and adenosine monophosphate can tune the product emission from blue to yellow. Taking advantage of the factorial design of the experiment, we have optimized the synthesis conditions to obtain pure blue and yellow emitters and investigate their sensitivity to a series of inorganic salts. The experiments have revealed selective quenching of the nanocluster’s fluorescence in the presence of mercury(II) ions.

The incidence of colorectal cancer (CRC) is increasing worldwide. It has variable signs and symptoms starting from changes in bowel habit to nausea and vomiting. Chemotherapeutic agents are often prescribed in CRC such as Capecitabine (CCB) and 5-Fluorouracil (FU). CCB is the prodrug of FU in oral dosage form, which makes it preferable by physicians, since no hospitalization is needed for drug administration. CCB is activated to FU in a three-step reaction producing 5′-deoxy-5-fluorocytidine (DFCR) (by carboxylesterase (CES) enzyme), then 5′-deoxy-5-fluorouridine (DFUR) (by cytidine deaminase (CDD) enzyme) and finally FU (by thymidine phosphorylase (TP) enzyme), the active form, which is later deactivated to give 5,6-dihydro-5-fluorouracil (DHFU). Different patients exhibit variable drug responses and adverse in response to CCB therapy, despite being treated by the same dose, which could be attributed to the occurrence of different possible enzyme single nucleotide polymorphisms (SNPs) along the activation and deactivation pathways of CCB. The most commonly occurring toxicities in CCB therapy are hand-foot syndrome and diarrhea. This study aims at developing and validating a new method for the simultaneous determination of CCB and its metabolites by HPLC-UV, followed by a correlation study with the toxicities occurring during therapy, where predictions of toxicity could be based on metabolites’ levels instead of the tedious process of genotyping. A new superior analytical method was optimized by a quality-by-design approach using DryLab® 2000 software achieving a baseline resolution of the six analytes within the least possible gradient time of 10 min. The method also showed linearity (in a range from 1 to 500 μg/mL), accuracy, precision and robustness upon validation: The LOD was found to be 3.0 ng/mL for DHFU and CCB, and 0.3 ng/mL for DFUR, DFCR and FU. The LOQ was found to be 10.0 ng/mL for DHFU and CCB, and 1.0 ng/mL for DFUR, DFCR and FU. The clinical results showed a positive correlation between the concentration of DFCR and mucositis and between the concentration of DFUR and hand-foot syndrome, confirming that this technique could be used for predicting such toxicities.

The metallome has been involved in the pathological investigation into ocular tissue for decades; however, as technologies advance, more information can be ascertained from individual tissue sections that were not previously possible. Herein, a demonstration of complementary techniques has been utilized to describe the distribution and concentrations of essential metals in both wildtype (WT) and rhodopsin (Rho−/−) ocular tissues. The multimodal approach described is an example of complementary datasets that can be produced when employing a multifaceted analytical approach. Heterogenous distributions of copper and zinc were observable within both WT and Rho−/− tissue by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), and the distributions of further trace elements notoriously problematic for ICP-MS analysis (phosphorous, Sulfur, chlorine, potassium, calcium, iron, and aluminum) were analysed by particle-induced X-ray emission (PIXE).

Raman spectroscopy (RS) is a spectroscopic method which indirectly measures the vibrational states within samples. This information on vibrational states can be utilized as spectroscopic fingerprints of the sample, which, subsequently, can be used in a wide range of application scenarios to determine the chemical composition of the sample without altering it, or to predict a sample property, such as the disease state of patients. These two examples are only a small portion of the application scenarios, which range from biomedical diagnostics to material science questions. However, the Raman signal is weak and due to the label-free character of RS, the Raman data is untargeted. Therefore, the analysis of Raman spectra is challenging and machine learning based chemometric models are needed. As a subset of representation learning algorithms, deep learning (DL) has had great success in data science for the analysis of Raman spectra and photonic data in general. In this review, recent developments of DL algorithms for Raman spectroscopy and the current challenges in the application of these algorithms will be discussed.

We determined the antifungal and antimicrobial sensitivity of Euphorbia tirucalli extracts in vitro. Antifungal and antibacterial activity was determined based on the M38-A and M26-A protocols, respectively. The methanolic and ethanolic partitions demonstrated antidermatophytic activity against Trichophyton rubrum (MIC 125 µg/mL for ethanol and MIC 125 µg/mL for methanol) and T. interdigitalis (MIC 500 µg/mL for ethanol; 125 µg/mL for methanol). These partitions also showed antibacterial activity—the ethanolic partition had an MIC of 1.56 ± 0.02 mg/mL against methicillin-resistant Staphylococcus aureus (clinical isolate), 6.25 ± 0.04 mg/mL against Staphylococcus aureus BAA-44, 3.13 ± 0.13 mg/mL against Pseudomonas aeruginosa 27853, and 3.13 ± 0.15 mg/mL against Escherichia coli ATCC 25922; the methanolic partition showed an MIC of 1.56 ± 0.02 mg/mL against P. aeruginosa 27853 and 1.56 ± 0.043 mg/mL against E. coli ATCC 25922. These partitions show promise as antimicrobial agents or adjuvants in the treatment of infections caused by these microorganisms.

Nonsteroidal anti-inflammatory drugs are the most commonly prescribed anti-inflammatory drugs worldwide. The most common side effects are gastrointestinal. Pantoprazole, a proton pump inhibitor (PPI), can be used to prevent these events from occurring. In this study, we attempt to develop and validate a novel method for determining and validating the fixed-dose combination of meloxicam and pantoprazole. A new method has been developed and validated to estimate pantoprazole and meloxicam in a fixed-dose combination using RP-HPLC. In order to separate the drugs, a mobile phase phosphate buffer/acetate was used (30:70, v/v), with a pH of 3.4 and a flow rate of 1.0 mL/min at 25 °C. The detection wavelength for the drugs was at a wavelength of 310 nm. The retention times for meloxicam and pantoprazole were 6 and 9 min, respectively. In concentrations ranging from 0.1 to 200 mg/L, the linearity of the detector was established. The r was 0.9998 for both drugs. Recovery rates ranged from 98 to 102% on average. According to the guidelines of the International Council on Harmonization, the results were satisfactory. Using the method presented herein, the pharmaceutical formulation of the combined meloxicam and pantoprazole can be routinely tested.