Veratrum spp. grow throughout the world and are especially prevalent in high mountain meadows of North America. All parts of Veratrum plants have been used for the treatment of ailments including injuries, hypertension, and rheumatic pain since as far back as the 1600s. Of the 17–45 Veratrum spp., Veratrum californicum alkaloids have been proven to possess favorable medicinal properties associated with inhibition of hedgehog (Hh) pathway signaling. Aberrant Hh signaling leads to proliferation of over 20 cancers, including basal cell carcinoma, prostate and colon among others. Six of the most well-studied V. californicum alkaloids are cyclopamine (1), veratramine (2), isorubijervine (3), muldamine (4), cycloposine (5), and veratrosine (6). Recent inspection of the ethanolic extract from V. californicum root and rhizome via liquid chromatography–mass spectrometry has detected up to five additional alkaloids that are proposed to be verazine (7), etioline (8), tetrahydrojervine (9), dihydrojervine (10), 22-keto-26-aminocholesterol (11). For each alkaloid identified or proposed in V. californicum, this review surveys literature precedents for extraction methods, isolation, identification, characterization and bioactivity to guide natural product drug discovery associated with this medicinal plant.

Protein content variation in milk can impact the quality and consistency of dairy products, necessitating access to in-line real time monitoring. Here, we present a chemometric approach for the qualitative and quantitative monitoring of β-lactoglobulin and α-lactalbumin, using mid-infrared spectroscopy (MIR). In this study, we employed Hotelling T2 and Q-residual for outlier detection, automated preprocessing using nippy, conducted wavenumber selection with genetic algorithms, and evaluated four chemometric models, including partial least squares, support vector regression (SVR), ridge, and logistic regression to accurately predict the concentrations of β-lactoglobulin and α-lactalbumin in milk. For the quantitative analysis of these two whey proteins, SVR performed the best to interpret protein concentration from 197 MIR spectra originating from 42 Cornell University samples of preserved pasteurized modified milk. The R² values obtained for β-lactoglobulin and α-lactalbumin using leave one out cross-validation (LOOCV) are 92.8% and 92.7%, respectively, which is the highest correlation reported to date. Our approach introduced a combination of preprocessing automation, genetic algorithm-based wavenumber selection, and used Optuna to optimize the framework for tuning hyperparameters of the chemometric models, resulting in the best chemometric analysis of MIR data to quantitate β-lactoglobulin and α-lactalbumin to date.

The purpose of this experimental review was to detect acrylamide in French fries using methods most adaptable to the food process industry for quality control assessment of products. French fries were prepared at different cook times using the same fryer oil over a five-day period to assess the influence of oil degradation and monitor trends in acrylamide formation. Acrylamide detection was performed using LC-MS, GC-MS and FT-NIR. The low levels of acrylamide produced during frying, low molecular weight of the analyte, and complexity of the potato matrix make routine acrylamide measurement challenging in a well-outfitted analytical lab with trained personnel. The findings of this study are presented from the perspective of pros and cons of each acrylamide measurement method in enough detail for food processors to appraise the method that may work best for them based on their available instrumentation and extent of personnel training.