State-of-the-art production chains for peas, beans and chickpeas\u2014valorization of agro-industrial residues and applications of derived extracts

The world is confronted with the depletion of natural resources due to their unsustainable use and the increasing size of populations. In this context, the efficient use of by-products, residues and wastes generated from agro-industrial and food processing opens the perspective for a wide range of benefits. In particular, legume residues are produced yearly in very large amounts and may represent an interesting source of plant proteins that contribute to satisfying the steadily increasing global protein demand. Innovative biorefinery extraction cascades may also enable the recovery of further bioactive molecules and fibers from these insufficiently tapped biomass streams. This review article gives a summary of the potential for the valorization of legume residual streams resulting from agro-industrial processing and more particularly for pea, green bean and chickpea by-products/wastes. Valuable information on the annual production volumes, geographical origin and state-of-the-art technologies for the extraction of proteins, fibers and other bioactive molecules from this source of biomass, is exhaustively listed and discussed. Finally, promising applications, already using the recovered fractions from pea, bean and chickpea residues for the formulation of feed, food, cosmetic and packaging products, are listed and discussed

Models predicting the growth response to growth hormone treatment in short children independent of GH status, birth size and gestational age

<p>Abstract</p> <p>Background</p> <p>Mathematical models can be used to predict individual growth responses to growth hormone (GH) therapy. The aim of this study was to construct and validate high-precision models to predict the growth response to GH treatment of short children, independent of their GH status, birth size and gestational age. As the GH doses are included, these models can be used to individualize treatment.</p> <p>Methods</p> <p>Growth data from 415 short prepubertal children were used to construct models for predicting the growth response during the first years of GH therapy. The performance of the models was validated with data from a separate cohort of 112 children using the same inclusion criteria.</p> <p>Results</p> <p>Using only auxological data, the model had a standard error of the residuals (SD_res), of 0.23 SDS. The model was improved when endocrine data (GH_maxprofile, IGF-I and leptin) collected before starting GH treatment were included. Inclusion of these data resulted in a decrease of the SD_resto 0.15 SDS (corresponding to 1.1 cm in a 3-year-old child and 1.6 cm in a 7-year old). Validation of these models with a separate cohort, showed similar SD_resfor both types of models. Preterm children were not included in the Model group, but predictions for this group were within the expected range.</p> <p>Conclusion</p> <p>These prediction models can with high accuracy be used to identify short children who will benefit from GH treatment. They are clinically useful as they are constructed using data from short children with a broad range of GH secretory status, birth size and gestational age.</p

Evidence for Protein Leverage in Children and Adolescents with Obesity

Objective The aim of this study was to test the protein leverage hypothesis in a cohort of youth with obesity.Methods A retrospective study was conducted in a cohort of youth with obesity attending a tertiary weight management service. Validated food questionnaires revealed total energy intake (TEI) and percentage of energy intake from carbohydrates (ì), fats (ï), and proteins (%EP). Individuals with a Goldberg cutoff >= 1.2 of the ratio of reported TEI to basal metabolic rate from fat-free mass were included. A subgroup had accelerometer data. Statistics included modeling of percentage of energy from macronutrients and TEI, compositional data analysis to predict TEI from macronutrient ratios, and mixture models for sensitivity testing.Results A total of 137 of 203 participants were included (mean [SD] age 11.3 [2.7] years, 68 females, BMI z score 2.47 [0.27]). Mean TEI was 10,330 (2,728) kJ, mean ì was 50.6% (6.1%), mean ï was 31.6% (4.9%), and mean %EP was 18.4% (3.1%). The relationship between %EP and TEI followed a power function (L coefficient -0.48; P Conclusions In youth with obesity, protein dilution by either carbohydrates or fats increases TEI. Assessment of dietary protein may be useful to assist in reducing TEI and BMI in youth with obesity.</p

Plant cell culture technology in the cosmetics and food industries : current state and future trends

The production of drugs, cosmetics, and food which are derived from plant cell and tissue cultures has a long tradition. The emerging trend of manufacturing cosmetics and food products in a natural and sustainable manner has brought a new wave in plant cell culture technology over the past 10 years. More than 50 products based on extracts from plant cell cultures have made their way into the cosmetics industry during this time, whereby the majority is produced with plant cell suspension cultures. In addition, the first plant cell culture-based food supplement ingredients, such as Echigena Plus and Teoside 10, are now produced at production scale. In this mini review, we discuss the reasons for and the characteristics as well as the challenges of plant cell culture-based productions for the cosmetics and food industries. It focuses on the current state of the art in this field. In addition, two examples of the latest developments in plant cell culture-based food production are presented, that is, superfood which boosts health and food that can be produced in the lab or at home

Teaching and Generative AI

With the rapid development of generative AI, teachers are experiencing a new pedagogical challenge, one that promises to forever change the way we approach teaching and learning. As a response to this unprecedented teaching context, this collection—Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions—provides interdisciplinary teachers, librarians, and instructional designers with practical and thoughtful pedagogical resources for navigating the possibilities and challenges of teaching in an AI era. Because our goal with this edited collection is to present nuanced discussions of AI technologies across disciplines, the chapters collectively acknowledge or explore both possibilities and tensions—including the strengths, limitations, ethical considerations, and disciplinary potential and challenges—of teaching in an AI era. As such, the authors in this collection do not simply praise or criticize AI, but thoughtfully acknowledge and explore its complexities within educational settings

A review of bioanalytical techniques for evaluation of cannabis (Marijuana, weed, Hashish) in human hair

Cannabis products (marijuana, weed, hashish) are among the most widely abused psychoactive drugs in the world, due to their euphorigenic and anxiolytic properties. Recently, hair analysis is of great interest in analytical, clinical, and forensic sciences due to its non-invasiveness, negligible risk of infection and tampering, facile storage, and a wider window of detection. Hair analysis is now widely accepted as evidence in courts around the world. Hair analysis is very feasible to complement saliva, blood tests, and urinalysis. In this review, we have focused on state of the art in hair analysis of cannabis with particular attention to hair sample preparation for cannabis analysis involving pulverization, extraction and screening techniques followed by confirmatory tests (e.g., GC–MS and LC–MS/MS). We have reviewed the literature for the past 10 years’ period with special emphasis on cannabis quantification using mass spectrometry. The pros and cons of all the published methods have also been discussed along with the prospective future of cannabis analysis