Talanta Open最新文献

Global health is seriously threatened by an increase in antibiotic resistance among ESKAPE pathogens- E- E. faecium, S- S.aureus, K- K.pneumoniae, A-A.baumannii, P- P.aeruginosa, and E-Enterobacter. The resistance of many bacteria to traditional antibiotics is increasing, making the search for novel approaches critical. In order to minimize the effect of these diseases, early detection, diagnosis, and treatment are important. However, there are drawbacks to traditional detection techniques such molecular-based, biochemical, and microbiological assays. These include the inability to detect on-site, as well as their time-consuming, expensive, and labour-intensive nature. Viral agents that target bacteria exclusively, known as bacteriophages, have shown promise in combating over infections resistant to antibiotics. Bacteriophage-based biosensors are adaptable to many environmental conditions and offer special features such as host specificity and ability to identify active infections. They're very accurate, very specific, and have quick assay times, which makes them beneficial tools for detection. Also, phages are more easily produced than antibodies and can withstand high pH, temperature, and chemical solvents. The potential of bacteriophage-based biosensors in the fight against ESKAPE pathogens is highlighted by this review. Bacteriophage-based biosensors provide simplified detection processes in contrast to conventional approaches, which makes them invaluable in environmental and clinical situations. Numerous platforms, including electrochemical, magnetoelastic, quartz crystal microbalance, and surface plasmon resonance sensors, being investigated for their potential use to detect pathogenic bacteria in a range of sample types.

Potency testing in the cannabis industry is one of the most important tests currently performed. Due to its financial importance, there exists a lot of pressure to achieve potency values that are as high as possible, while staying within the realm of what is morally correct to perform. This paper explains how potency testing is achieved and how differences due to lack of standardization may exist. The paper then explores measurement error, or uncertainty, and suggests reference material may be the largest contributor to this uncertainty in the market today.

This comprehensive review investigates the dynamic landscape of trace elemental analysis methodologies applied to plants and food-based extracts. The exploration spans from the inception of techniques to the latest procedures, contributing to heightened precision and sensitivity in elemental detection. According to the WHO, herbal plants and medicine from varied soil compositions serve as crucial therapeutic agents for 70–80 % of the world's population. Yet, their susceptibility to trace element toxicity poses a significant risk to human health. Rising population and increased food demands have led to environmental pollution, contaminating the food chain through unintended activities like industrialization, mining, and pesticide production. The elemental composition of plants and derived extracts is central to comprehending nutritional profiles, evaluating product quality, and ensuring food safety. Methodological advancements, progressing from manual procedures to sophisticated technologies such as X-ray fluorescence (XRF), neutron activation analysis (NAA), inductively coupled plasma optical emission spectroscopy (ICP OES), and inductively coupled plasma mass spectrometry (ICP-MS), are delineated. Recent strides in paper-based electrochemical sensors are highlighted for their distinctive capabilities and elucidation of associated advantages and limitations.

Moreover, the review delves into innovative sample preparation methodologies, encompassing microwave-assisted digestion and solid-phase microextraction, to amplify the efficiency of elemental extraction and subsequent analysis. Integrating data analytics and machine learning in elucidating complex elementary datasets is explored, underscoring the potential for heightened accuracy and automation in trace elemental analysis. This review compiles literature data, summarizing sample preparation methods for various herbal parts (roots, soil, stems, bark, fruits, food). Standard protocols from WHO, United States Pharmacopeia-National Formulary (USP-FR), Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy (AYUSH) are considered. Lead, Cadmium, Mercury, and Arsenic are the primary toxic elements of concern in herbal medicines. This review furnishes valuable insights tailored for researchers, analysts, and policymakers actively involved in advancing the domain of trace elemental analysis in plants and food-based extract.

The false declaration of honey authenticity requires the use of rapid and efficient analytical tools in order to be detected. In this study, the use of a green, rapid and emerging approach for food authentication, FT-Raman spectroscopy, proved to obtain reliable and efficient honey botanical and harvesting year differentiation models, when the spectroscopic data was processed by employing a supervised statistical method, namely Partial Least Squares Discriminant Analysis (PLS-DA). The peaks and bands present in the Raman spectra were discussed based on honey composition. In order to increase the efficiency of the models, different preprocessing methods were used and a variable reduction step was employed. The new authentication approach is capable of distinguishing among four botanical sources and two harvesting periods of honey with a correct prediction rate higher than 97 %. The Raman markers that proved to contribute the most to the discrimination were correlated with the honey composition.

Background

Visceral Leishmaniasis is a neglected tropical disease with a high rate of infection and mortality in affected areas. Around 50,000 to 90,000 new cases of visceral leishmaniasis (VL) are estimated every year. Individuals asymptomatic for the disease should also be considered in epidemiological surveillance of the disease, as they can help spread the parasite. Thus, the development of low-cost diagnosis methods that allow the identification of infected and asymptomatic individuals is required, especially in developing countries where this disease is endemic.

Results

In this work, we developed an immunosensor for recognizing anti-Leishmania antibodies in asymptomatic individuals and avoiding cross-reaction with Chagas disease (CD). For that, we used carbon-based screen-printed electrodes, modified with graphene oxide and gold. Reproducibility was assessed by calculating the relative standard deviation (RSD < 5 %) from cyclic voltammograms of [Fe(CN)₆]^3-/4− using three different electrodes, screen-printed carbon electrodes (DPR-110) and graphene modified screen-printed electrodes (DPR-110 GPH) were purchased from DropSens (Oviedo, Asturias, Spain).

Significance

As an electrochemical methodology, we use cyclic voltammetry. After the tests were carried out, we considered that carbon electrodes adsorbed with reduced graphene oxide and modified with gold nanoparticles were the best platforms for detecting anti-Leishmania antibodies. In the study carried out, the limit of quantification (LOQ) for anti-Leishmania antibodies was established at 16.75 mg/mL, while the limit of detection (LOD) was 5.58 mg/mL. These limits indicate the minimum antibody concentration values that can be quantified and detected accurately and reliably in the analyzed sera.

Tin contamination in waters due to mining and natural activities in high concentrations can threaten human health. This research presents the development of a sensitive and selective colorimetric sensor in aqueous, paper, and gel-based to detect Sn²⁺. The development of such sensors is promising, with attractive advantages such as intense color, fast naked-eye response, and simple continuous fabrication. The addition of Sn²⁺ ions will change the color of the medium because curcumin (Cur) interacts with Sn²⁺, causing a decrease in free Cur, silver nanoparticles (AgNPs) becoming less stable, and a change in particle size. Colorimetric changes in Sn²⁺ were achieved by visual inspection within 10 min for aqueous-based and 20 min for paper and gel-based. The good linear relationship (R² = 0.9999) between Sn²⁺ and Δ absorption with a detection limit of up to 66.99 µg/L. This method is relatively scalable in determining Sn²⁺ and shows good recovery between 80 and 105 %. This colorimetric sensor gives good sensitivity to Sn²⁺ metal ions which is expected to become the basic technology for developing in-situ sensors to monitor Sn²⁺ levels in tin industrial waste.

With a rise in the prominence of cannabis usage, due to its widespread availability and varying legal status, there has been an increased emphasis on the differentiation of cannabinoids present within cannabis using various analytical techniques. The present study aimed to exploit the capability of Raman microscopy to collect high-quality spectra of seven cannabinoid analytical standards, followed by their classification using linear discriminant analysis (LDA) and a novel transfer learning approach. Additionally, the experimental Raman spectra of delta-9-tetrahydrocannabinol (Δ9-THC), cannabidiol (CBD), and cannabichromene (CBC) were compared to simulated spectra from density functional theory calculations (DFT) to connect the spectral features to the underlying vibrational motions. A microscopical approach enabled the determination of the optimal sampling areas to collect Raman spectra for the nonacidic and acidic cannabinoids. An initial visualization of the data using principal component analysis (PCA) confirmed the spectral differences observable by visual comparisons of the spectra of the cannabinoid standards. The application of LDA implemented with a 5-fold cross-validation with 10 repeats, resulted in a classification accuracy of 99.83 %. For the transfer learning approach, the artificial intelligence (AI) model training was conducted in less than 10 min in a graphical processing unit (GPU) environment. All seven cannabinoids were successfully classified into respective classes based on scalograms transformed from Raman spectra, with 100 % classification accuracy. The average prediction probability for correct classification was 99.31 %. The classification outcome provided by the AI model included both prediction labels and probability, which provided a comprehensive evaluation of the samples.

Paper-based analytical devices (PADs) are becoming increasingly popular for drug analysis in various matrices. These affordable, portable platforms come with a range of benefits, such as their user-friendly design, straightforward operation, and minimal need for sample preparation. This study evaluates the potential applications of PADs in drug testing with a particular emphasis on the adaptability of PADs in terms of their ability to handle various types of samples during the testing process. In this study, the design, manufacturing, and performance of PADs for drug detection, as well as the influence that different biological samples have on the performance of PAD performance were investigated. PADs are discussed in this paper, with respect to their applications in forensic sample analysis, point-of-care testing and illicit drug testing. The study demonstrates the flexibility of PADs as platforms for drug testing in varied matrices. The authors highlight the fact that PADs are inexpensive, portable, user-friendly, and need minimum sample preparation, which makes them effective instruments in a variety of situations, including research, law enforcement, and healthcare. On the whole, this paper highlights the versatility of PADs, emphasizing their role as adaptable platforms for drug testing within different matrices. Scientists and professionals can utilize these cutting-edge devices to improve the efficiency and accessibility of drug analysis.

To quantify phytocannabinoids in hemp, liquid chromatography diode array detector (LC-DAD) methods are favored, but their selectivity depends on baseline separation of all phytocannabinoids and unknown compounds in an extract. Therefore, development of a LC-DAD method with a different selectivity has become highly desirable. Currently, most LC-DAD methods use the water/acetonitrile eluting system, while this study aimed to use the water/methanol eluting system. A systematic investigation of various chromatographic parameters on LC separation of eighteen phytocannabinoids, the maximum number that has been quantified in hemp so far, plus two potential internal standards, led to a four-step isocratic mobile phase that was able to baseline separate the twenty compounds with a significantly different eluting order from published methods. Although changes in the mobile phase composition caused baseline drifts, consequent difficulty in quantification was avoided through detection at wavelengths longer than 230 nm. Subsequently, the method was validated according to the ISO 17025 guidelines, calibrated between 0.04 and 50 µg/mL, and used to analyze phytocannabinoids in nine strains of hemp flowers that were extracted using methanol between 0.04 and 50 % (w/w). Extraction recovery was tracked in real-time by spiking one of the two potential internal standards, i.e., abnormal cannabidiol (ACBD), a cannabinoid not naturally present in hemp. Method selectivity was further assessed by electrospray ionization time-of-flight mass spectrometry (ESI/TOFMS), indicating minimum interferences. In addition, five untargeted/unknown phytocannabinoids were identified by ESI/TOFMS, including two structural isomers of Δ⁹-tetrahydrocannabinol (Δ⁹-THC), two structural isomers of Δ⁹-tetrahydrocannabinolic acid (Δ⁹-THCA), and one structural isomer of Δ⁹-THC acetate.

Poisoning metabolites within mushrooms typically exert varying physiological and biological effects; however, their distributions within mushrooms are seldom investigated. This study focused on imaging illudin S, a representative poisoning metabolite within Omphalotus illudens mushroom, using desorption electrospray ionization–tandem mass spectrometry (DESI–MS/MS) coupled with liquid chromatography–electrospray ionization–tandem mass spectrometry (LC–ESI–MS/MS). Initially, LC–ESI–MS/MS conditions were established for the selective detection of illudin S (m/z 247→159, positive mode) from extracted mushroom. Based on this MS/MS condition, each mushroom was divided into nine sections, and each section was subjected to specific DESI–MS/MS mode imaging (pixel size: 200 × 200 μm). The results revealed high concentrations of illudin S in the stalks of the mushrooms growing on trees. Further, re-evaluations using the LC–MS/MS assay revealed a seven-fold difference in the illudin S between the stalk and other regions. This study marks the first attempt at assessing toxic metabolite distributions within poisonous mushrooms, thus offering valuable insights including the efficient utilization of illudin analogs in biological applications.