Hurdles in translating science from lab to market in delivery systems for Cosmetics: An industrial perspective.

In recent decades, a sweeping technological wave has reshaped the global economic landscape. Fueled by the unceasing forces of digital innovation and venture capital investment, this transformative machine has left a significant mark across numerous economic sectors. More recently, the emergence of 'deep tech' start-ups, focusing on areas such as artificial intelligence, nanotechnology, and biotechnology, has infused a fresh wave of innovation into various sectors, including the pharmaceutical and cosmetic industry. This review explores the significance of innovation within the cosmetics sector, with a particular emphasis on delivery systems. It assesses the crucial process of bridging the gap between research and the market, particularly in the translation of nanotechnology into tangible real-world applications. With the rise of nanotechnology-based beauty ingredients, we can anticipate groundbreaking advancements that promise to surpass consumer expectations, ushering in a new era of unparalleled innovation in beauty products.

A cyclic learning approach for improving pre-stack seismic processing.

Current seismic processing workflows in the oil and gas industry involve several interactions between different experts to optimize the overall data quality in various tasks, such as noise attenuation, velocity analysis and horizon picking. While many machine learning-based approaches have been proposed to support each of those steps, most of them disregard expert interactions to guide the overall optimization. This paper presents geocycles, a cyclic learning approach that mimics this iterative process, which can be applied to different pre-stack seismic processing tasks. Our method refactor these processes considering training, testing, and evaluation sub-tasks, which allow the selection of samples for greedy sequential processes targeting an overall optimum quality for very large seismic datasets. We present encouraging results showing that a cyclic structure and efficient quality metrics improved overall outcomes in up to 128% for two different seismic processing tasks in comparison to a 1-cycle machine learning approach.

Biotechnological Potential of Araucaria angustifolia Pine Nuts Extract and the Cysteine Protease Inhibitor AaCI-2S.

Protease inhibitors are involved in the regulation of endogenous cysteine proteases during seed development and play a defensive role because of their ability to inhibit exogenous proteases such as those present in the digestive tracts of insects. Araucaria angustifolia seeds, which can be used in human and animal feed, were investigated for their potential for the development of agricultural biotechnology and in the field of human health. In the pine nuts extract, which blocked the activities of cysteine proteases, it was detected potent insecticidal activity against termites (Nasutitermes corniger) belonging to the most abundant termite genus in tropical regions. The cysteine inhibitor (AaCI-2S) was purified by ion-exchange, size exclusion, and reversed-phase chromatography. Its functional and structural stability was confirmed by spectroscopic and circular dichroism studies, and by detection of inhibitory activity at different temperatures and pH values. Besides having activity on cysteine proteases from C. maculatus digestive tract, AaCI-2S inhibited papain, bromelain, ficin, and cathepsin L and impaired cell proliferation in gastric and prostate cancer cell lines. These properties qualify A. angustifolia seeds as a protein source with value properties of natural insecticide and to contain a protease inhibitor with the potential to be a bioactive molecule on different cancer cells.

The effects of Enterolobium contortisiliquum serine protease inhibitor on the survival of the termite Nasutitermes corniger, and its use as affinity adsorbent to purify termite proteases.

The immobilization of Enterolobium contortisiliquum protease inhibitor, EcTI-Sepharose, as an affinity chromatography matrix is a powerful biotechnological tool to purify targets from Nasutitermes corniger in the investigation of insecticidal properties of natural compounds.