OBJECTIVE: Food forensics is an emerging field and the initial part of this review showcases the toxic effects and the instrumental methods applied for the detection of the most commonly used azo dyes. Electrochemical detection has a lot of advantages and hence the significance of the most important techniques used in the electrochemical detection is discussed. The major part of this review highlights the surface modified electrodes, utilized for the detection of the most important azo dyes to achieve low detection limit (LOD).
METHODS: A thorough literature study was conducted using scopus, science direct and other scientific databases using specific keywords such as toxic azo dyes, electrochemical detection, modified electrodes, LOD etc. The recent references in this field have been included.
RESULTS: From the published literature, it is observed that with the growing interests in the field of electrochemical techniques, a lot of importance have been given in the area of modifying the working electrodes. The results unambiguously show that the modified electrodes outperform bare electrodes and offer a lower LOD value.
CONCLUSIONS: According to the literature reports it can be concluded that, compared to other detection methods, electrochemical techniques are much dependable and reproducible. The fabrication of the electrode material with the appropriate modifications is the main factor that influences the sensitivity. Electrochemical sensors can be designed to be more sensitive, more reliable, and less expensive. These sensors can be effectively used by toxicologists to detect trace amounts of harmful dyes in food samples.

In the Japanese official detection method for unauthorized genetically modified (GM) papayas, one of two types of real-time PCR reagents with DNA polymerase (TaqMan Gene Master Mix [TaqMan Gene] or FastGene QPCR Probe Mastermix w/ROX [FastGene]) is primarily used for measurement. In 2022, we conducted a laboratory performance study on the unauthorized GM papaya line PRSV-YK, and the results revealed that high threshold cycle (Cq) values for the PRSV-YK detection test were obtained using TaqMan Gene with the 7500 Fast & 7500 Real-Time PCR System (ABI7500) and QuantStudio 12K Flex (QS12K), indicating the possibility of false negatives. The possibility of similar problems with all unauthorized GM papaya lines detection tests needs to be evaluated. In this study, we performed detection tests on unauthorized GM papaya lines (PRSV-YK, PRSV-SC, and PRSV-HN), the cauliflower mosaic virus 35S promotor (CaM), and a papaya positive control (Chy), and examined how the limits of detection (LOD) for each test are affected by two types of DNA polymerases (TaqMan Gene and FastGene) and three types of real-time PCR instruments (ABI7500, QS12K, and LightCycler 480 Instrument II [LC480]). In the PRSV-YK and PRSV-SC detection tests using ABI7500 and QS12K, measurement with TaqMan Gene showed a higher LOD than FastGene. In this case, an exponential amplification curve was confirmed on the amplification plot; however, the amplification curve did not cross the ΔRn threshold line and the correct Cq value was not obtained with a threshold line=0.2. The other tests (PRSV-HN, CaM, and Chy with ABI7500 and QS12K, and all detection tests with LC480) showed no important differences in the LOD for each test using either DNA polymerase. Therefore, when performing PRSV-YK and PRSV-SC detection tests with the ABI7500 or QS12K, FastGene should be used to avoid false negatives for foods containing GM papaya lines PRSV-YK and PRSV-SC at low mixing levels.

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Soybean is scientifically known as Glycine max. It belongs to the Fabaceae family. It consists of a lot of bioactive phytochemicals like saponin, phenolic acid, flavonoid, sphingolipids and phytosterols. It also owns excellent immune-active effects in the physiological system. Soy and its phytochemicals have been found to have pharmacological properties that include anticancer, antioxidant, anti-hypercholesterolaemic, anti-diabetic, oestrogenic, anti-hyperlipidaemic, anti-inflammatory, anti-obesity, anti-hypertensive, anti-mutagenic, immunomodulatory, anti-osteoporotic, antiviral, hepatoprotective, antimicrobial, goitrogenic anti-skin ageing, wound healing, neuroprotective and anti-photoageing activities. Present study has been designed to set standard pharmacognostical extraction method, complexation of compounds, qualitative evaluation through phytochemical screening, identification by TLC, physicochemical properties, solubility profile, total phenolic, flavonoid content as well as analytical evaluation or characterisation like UV and FT-IR of methanolic extract of G. max. The final observations like physicochemical properties such as total ash value, LOD and pH were recorded. Phytochemical screenings show the presence of flavonoid, alkaloid, saponin, carbohydrate, tannins, protein, gums and mucilage, fixed oils and fats. The results were found significant. Further in silico studies proved creatinine and euparin to be potent wound healing agents.

Fluoride detection has been playing an important role in chemical, biological, and medicinal field, especially for keeping physical health and resisting environmental pollution. Herein, a urolithin B fluorescent probe has been successfully developed with good sensitivity, selectivity, anti-interference ability. The low limit of detection (LOD) refers to 0.156 μM, and the instant response time to F- is less than 1 s. The probe is suitable for quantitatively and qualitatively ratiometric detection for F- in solution with two distinct emission bands at 425 (blue) and 566 nm (orange), with the coordinate change of CIE from (0.38, 0.41) to (0.22, 0.11). Urolithin B displayed a remarkable ratiometric fluorescence response towards F-. The detection mechanistic was further proposed by NMR and electronic spectroscopic experiments combining with time-dependent density functional theoretical calculation.

Soil-transmitted helminth (STH) infections are caused by roundworms, hookworms, whipworms, and thread worms. Accurate diagnosis is essential for effective treatment, prevention, and control of these infections. This study evaluates a new diagnostic method called Single-image Parasite Quantification (SIMPAQ), which uses a lab-on-a-disc (LoD) technique to isolate STH eggs into a single imaging zone for digital analysis. The study evaluates the purification performance of the SIMPAQ technique for detecting STH eggs in animal samples. This was a cross-sectional study conducted among 237 pigs and 281 dogs in the Morogoro region in Tanzania. Faecal samples were collected and processed with the LoD technique, as well as flotation and McMaster (McM) methods for comparison purposes. The overall prevalence of STH infections was high as per the LoD technique (74%), followed by McM (65.44%) and flotation (65.04%). Moreover, the overall performance of the LoD technique, using McM as the gold standard, was 93.51% (sensitivity), 60.89% (specificity), 81.91% (PPV), and 83.21% (NPV). The LoD technique exhibited high prevalence, sensitivity, and NPV, which demonstrates its value for STH egg detection and its crucial role in the era of accurate STH diagnosis, promoting proper management of the infection.

Lipidomic data often exhibit missing data points, which can be categorized as missing completely at random (MCAR), missing at random, or missing not at random (MNAR). In order to utilize statistical methods that require complete datasets or to improve the identification of potential effects in statistical comparisons, imputation techniques can be employed. In this study, we investigate commonly used methods such as zero, half-minimum, mean, and median imputation, as well as more advanced techniques such as k-nearest neighbor and random forest imputation. We employ a combination of simulation-based approaches and application to real datasets to assess the performance and effectiveness of these methods. Shotgun lipidomics datasets exhibit high correlations and missing values, often due to low analyte abundance, characterized as MNAR. In this context, k-nearest neighbor approaches based on correlation and truncated normal distributions demonstrate best performance. Importantly, both methods can effectively impute missing values independent of the type of missingness, the determination of which is nearly impossible in practice. The imputation methods still control the type I error rate.

Type 2 diabetes (T2D) is a global public health issue characterized by excess weight, abdominal obesity, dyslipidemia, hyperglycemia, and a progressive increase in insulin resistance. Human population studies of T2D development and its effects on systemic metabolism are confounded by many factors that cannot be controlled, complicating the interpretation of results and the identification of early biomarkers. Aged, sedentary, and overweight/obese non-human primates (NHPs) are one of the best animal models to mimic spontaneous T2D development in humans. We sought to identify and distinguish a set of plasma and/or fecal metabolite biomarkers, that have earlier disease onset predictability, and that could be evaluated for their predictability in subsequent T2D studies in human cohorts. In this study, a single plasma and fecal sample was collected from each animal in a colony of 57 healthy and dysmetabolic NHPs and analyzed for metabolomics and lipidomics. The samples were comprehensively analyzed using untargeted and targeted LC/MS/MS. The changes in each animal\'s disease phenotype were monitored using IVGTT, HbA1c, and other clinical metrics, and correlated with their metabolic profile. The plasma and fecal lipids, as well as bile acid profiles, from Healthy, Dysmetabolic (Dys), and Diabetic (Dia) animals were compared. Following univariate and multivariate analyses, including adjustments for weight, age, and sex, several plasma lipid species were identified to be significantly different between these animal groups. Medium and long-chain plasma phosphatidylcholines (PCs) ranked highest at distinguishing Healthy from Dys animals, whereas plasma triglycerides (TG) primarily distinguished Dia from Dys animals. Random Forest (RF) analysis of fecal bile acids showed a reduction in the secondary bile acid glycoconjugate, GCDCA, in diseased animals (AUC 0.76[0.64, 0.89]). Moreover, metagenomics results revealed several bacterial species, belonging to the genera Roseburia, Ruminococcus, Clostridium, and Streptococcus, to be both significantly enriched in non-healthy animals and associated with secondary bile acid levels. In summary, our results highlight the detection of several elevated circulating plasma PCs and microbial species associated with fecal secondary bile acids in NHP dysmetabolic states. The lipids and metabolites we have identified may help researchers to differentiate individual NHPs more precisely between dysmetabolic and overtly diabetic states. This could help assign animals to study groups that are more likely to respond to potential therapies where a difference in efficacy might be anticipated between early vs. advanced disease.

Mustard (Brassica spp.) is one of the world\'s oldest condiments in the food basket, which holds a significant place in the global culinary landscape due to historical prominence and perceived health benefits. This study explores the extraction of oils from Mustard seeds by employing traditional \'Kolhu\' method, modern supercritical fluid, and solvent extraction techniques. This study, for the first-time, identified Aurantiamide acetate, a potent anti-cancer dipeptide in Mustard seeds using ultra-performance liquid chromatography-mass spectrometry coupled with quadrupole time-of-flight (UPLC/MS-QToF) analytical platform. The analytical methodology was meticulously validated encompassing optimal parameters such as limit of detection, limit of quantification, precision, accuracy, linearity and robustness, within the range. Interestingly, \'Kolhu\' method of oil extraction exhibited better yield of Aurantiamide acetate, suggesting superior efficiency of traditional methods. This study accentuates the importance of classical extraction methods, used traditionally, and emphasizes that naturally occurring substances indeed could be harnessed for better health.

In the pharmaceutical industry, the unexpected appearance of crystalline forms could impact the therapeutic efficacy of an Active Pharmaceutical Ingredient (API). For quality control, a thorough qualitative and quantitative monitoring of pharmaceutical solid forms is essential to ensure the detection and the quantification of crystalline forms, wither different or with the same chemical composition (polymorphs) at a low detection level. The purpose of this paper was to review and highlight the importance of choosing adequate solid-state techniques for detection and quantification APIs that present polymorphism - based on limits of detection (LOD) and quantification (LOQ), pharmacopeias specifications, international guidelines and studies reported in the literature. To this study, the powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), Infrared and Raman spectroscopies and solid-state nuclear magnetic resonance (NMR) were the solid-state techniques analyzed. Additionally, the Argentine, Brazilian, British, European, International, Japanese, Mexican and the United States of America pharmacopeias were reviewed. Based on the analysis performed, the advantages and disadvantages of these techniques, as well as the LOD and LOQ values of APIs were reported. In comparison to these solid-state techniques, reference material used for identification analyses should be previously identified with the corresponding polymorph. Without this previous procedure, the patterns, the spectra, and DSC curves of the reference material can only be used to confirm the mixture of solid forms, not being able to specify which polymorphs are contained in the sample. A major advantage of PXRD is the use of the calculated diffraction patterns obtained from the Crystallographic Information Frameworks (CIFs) files which could be used as a reference pattern without any other information, assistance technique, or physical standards. Regarding the quantification aspect, different pharmacopeias suggest various methods such as the PXRD combining with Rietveld method, which can be used to obtain lower LOD values for minority phases in the mixture of different substances without the need for a calibration curve. Raman spectroscopy can detect polymorphs in small particles and solid-state NMR spectroscopy is a powerful technique for quantification not only crystalline but also crystalline-amorphous mixtures. Finally, this review intends to be a useful tool to control, with efficiency and accuracy, the polymorphism of APIs in pharmaceutical compounds.