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By defining the nature of legal representation as a public service, this profession has distanced itself from the private initiative of individuals (lawyers and clients), and the role of a third party, namely the government, has become prominent with the aim of ensuring public benefit and protecting consumers of legal services. This research, through a library study and adopting an analytical-descriptive approach, aims to elucidate the components of the New Zealand government's intervention in regulating the legal services market, particularly the profession of law. It concludes that in this country, the government's efforts have focused on establishing a perspective that goes beyond private contracts and defining the profession as a public service. The most important law governing the profession of law in New Zealand is the Lawyers and Conveyancers Act 2006. This law grants the New Zealand government extensive authority over the supervision of lawyers; issues ranging from setting fees to overarching policy-making in this profession are under the government's oversight. The conditions for practicing this profession are also determined by government authorities. Despite some criticism regarding these extensive powers, the positive outcomes of regulating this profession, including increased public satisfaction, elimination of monopolies, enhancing competition in the legal profession, and easier access to legal services, have further highlighted the necessity of government intervention in the regulation of this profession. [ABSTRACT FROM AUTHOR]

Protein-rich diets often contain high quantities of biogenic amines (BAs), notably histamine and tyramine, which pose substantial health hazards owing to their toxicity. BAs are primarily produced by the microbial decarboxylation of free amino acids. Lactic acid bacteria (LAB) can either produce BAs using substrate-specific decarboxylase enzymes or degrade them into non-toxic compounds using amine-degrading enzymes such as amine oxidase and multicopper oxidase. Furthermore, LAB may inhibit BA-producing microbes by generating bioactive metabolites, including organic acids and bacteriocins. This paper thoroughly explores the processes underlying BA production and degradation in LAB, with a focus on the diversity of enzymes involved. Metabolic mapping of LAB strains at the genus and species levels reveals their involvement in BA metabolism, from production to degradation. The phylogenetic-based evolutionary relatedness of BA-producing and BA-degrading enzymes among LAB strains sheds light on their functional adaptability to various metabolic needs and ecological settings. These findings have significant practical implications for establishing better microbial management strategies in food production, particularly through strategically using starter or bioprotective cultures to reduce BA buildup. By highlighting the evolutionary and metabolic diversity of LAB, this review helps to optimize industrial fermentation processes, improve food safety protocols, and advance future research and innovation in BA management, ultimately protecting consumer health and supporting regulatory compliance. • Biogenic amines (BAs) in protein-rich foods pose health risks due to potential toxicity. • LAB strains can produce BAs from amino acid precursors using decarboxylase enzymes. • The LAB strain degrades BAs via enzymes like amine oxidase, dehydrogenase, and multicopper oxidase. • Phylogenetic analysis shows conservation and divergence of BAs-related enzymes in LAB strains. • Metabolic mapping of LAB strains reveals their roles in BA metabolism. [ABSTRACT FROM AUTHOR]

Health experts and consumer protection agencies have been expressing concerns about the nutritional quality and marketing of child-oriented food products for years, and political debates on child-targeted food marketing are currently happening around the world. At the same time, systematic research on laypeople's views on the topic is still scarce. However, knowing what these consumers think is highly important, as lay beliefs can affect food decision-making and consumption. We address this gap with two online studies. In Study 1 (N = 444 parents and non-parents), we develop an instrument measuring lay beliefs about child-oriented food products consisting of three scales: Nutrition-Related Concerns, Convenience, and Healthiness. We find small effects of socio-demographic factors on beliefs and observe meaningful relationships between beliefs and (i) thinking style and (ii) food purchase motives (e.g., visual appeal and convenience). In Study 2 (N = 571 parents), we validate the factor structure of the instrument by means of CFA and find that lay beliefs about Healthiness and Convenience predict self-reported purchase of child-oriented food products. With our research, we extend current knowledge on laypeople's perceptions of child-oriented food products and provide an instrument with good psychometric properties that can be applied in future studies. Our research offers valuable insights for policymakers and producers who wish to meet the actual demands of consumers. [ABSTRACT FROM AUTHOR]

[Display omitted] • An innovative variant of GAN named regression GAN was proposed. • The regression GAN was used to extend the spectral and physicochemical data. • The performance of regression models was improved by data augmentation. • VNIR-HSI and SWIR-HSI were used to detect acetamiprid residue of Hami melon. The rapid and non-destructive detection of pesticide residues in Hami melons plays substantial importance in protecting consumer health. However, the investment of time and resources needed to procure sample data poses a challenge, often resulting in limited data set and consequently leading insufficient accuracy of the established models. In this study, an innovative variant based on generative adversarial network (GAN) was proposed, named regression GAN (RGAN). It was used to synchronically extend the visible near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral data and corresponding acetamiprid residue content data of Hami melon. The support vector regression (SVR) and partial least squares regression (PLSR) models were trained using the generated data, and subsequently validate them with real data to assess the reliability of the generated data. In addition, the generated data were added to the real data to extend the dataset. The SVR model based on SWIR-HSI data achieved the optimal performance after data augmentation, yielding the values of R p 2 , RMSEP and RPD were 0.8781, 0.6962 and 2.7882, respectively. The RGAN extends the range of GAN applications from classification problems to regression problems. It serves as a valuable reference for the quantitative analysis of chemometrics. [ABSTRACT FROM AUTHOR]

Rapid and sensitive methods to detect allergenic proteins in foods at the point-of-need could help to protect allergic consumers from life-threatening accidental exposure. In this context, the development of a label-free optical immunosensor for detecting hazelnut proteins in cookies is presented. The sensor is based on silicon photonic chips containing two integrated Mach-Zehnder interferometers (MZI) with light input and output on one side of the chip, and sensing window openings on the other side. Coupling with a white-light LED and a spectrometer for signal recording is achieved via a bifurcated fiber. The sensing window of one of the MZIs is modified with a mouse monoclonal antibody against hazelnut proteins, while the other sensing window is modified with bovine serum albumin to serve as blank. The assay follows a two-step sandwich immunoassay format, involving a 10-min reaction with the hazelnut proteins calibrator or cookie sample, followed by a 2-min reaction with a mixture of monoclonal antibodies. All reactions were performed by immersing the chip side where the MZIs windows are located into the solutions. The recorded spectrum is processed in real-time to transform the spectrum shifts due to immunoreactions taking place on the sensing windows of the two MZIs into phase shifts. The developed assay detects hazelnut proteins at concentrations as low as 25 ng/mL in calibrators prepared in buffer or in aqueous extract of hazelnut-free cookies. Additionally, cookies containing hazelnuts were analyzed demonstrating the sensor ability for fast and sensitive detection of the hazelnut proteins in commercial products. • Rapid and sensitive detection of hazelnut proteins with a silicon photonic sensor. • Photonic sensor chips containing two integrated Mach-Zehnder interferometers (MZI). • One MZI monitors the specific reaction the other the non-specific signal. • The detection limit in cookie matrix is 0.25 mg/kg for a 13-min assay. • Instrument suitable for point-of-need applications. [ABSTRACT FROM AUTHOR]