The Silkworm () Neuropeptide Orcokinin's Efficiency in Whitening and Skincare.

The silkworm neuropeptide Orcokinin (abbreviated as BommoOK) is equipped with multiple biological functions, one of which acts as a pigmentation inhibitor. To explore the whitening efficiency of BommoOK, the inhibitory effects on tyrosinase and its adaptability on the cell for six mature peptides of BommoOK were investigated in this paper. At the same time, BommoOKA_type4, the peptide with the best melanin inhibition effect, was used as an additive to prepare a whitening cream, and the effects on skin moisture, oil content, fine lines, skin glossiness, pores, and pigment depth were determined.

Deciphering the complex molecular architecture of the genetically modified soybean FG72 through paired-end whole genome sequencing.

The clear molecular characterization of genetically modified (GM) plants and animals is a prerequisite for obtaining regulatory approval and safety certification for commercial cultivation. This characterization includes the identification of the transferred DNA (T-DNA) insertion site, its flanking sequences, the copy number of inserted genes, and the detection of any unintended genomic alterations accompanying the transformation process. In this study, we performed a comprehensive molecular characterization of the well-known GM soybean event FG72 using paired-end whole-genome sequencing (PE-WGS).

Innovations in Transgene Integration Analysis: A Comprehensive Review of Enrichment and Sequencing Strategies in Biotechnology.

Understanding the integration of transgene DNA (T-DNA) in transgenic crops, animals, and clinical applications is paramount for ensuring the stability and expression of inserted genes, which directly influence desired traits and therapeutic outcomes. Analyzing T-DNA integration patterns is essential for identifying potential unintended effects and evaluating the safety and environmental implications of genetically modified organisms (GMOs). This knowledge is crucial for regulatory compliance and fostering public trust in biotechnology by demonstrating transparency in genetic modifications.

Effects of dietary glucosamine sulfate sodium on early laying performance and eggshell quality of laying hens.

This study was conducted to determine the influence of dietary glucosamine sulfate sodium (GSS) on laying performance, blood profiles, eggshell and inner quality of eggs and relative expression of the genes related to eggshell in laying hens at early stage. A total of 640 twenty-weeks-old Lohmann laying hens were randomly allotted to 4 treatments with 10 replicates of 16 hens each. The experiment lasted for 8 wk, and dietary treatments were: 1) CON, basal diet; 2) G1, CON + 0.

Effect of Perilla seeds inclusion on the performance, egg quality characteristics, biochemical parameters and egg yolk fatty acid composition of laying hens.

This study investigates the effect of supplementation of Perilla seeds (PS) on the performance, egg quality, blood biochemical parameters, and egg yolk fatty acids composition in the diet of egg-laying chicken. A total of 1600 Lohmann laying hens were randomly assigned to four different groups with 4 replicates each (100 chickens/replicate) and were subjected to varying PS concentrations (PS0, PS6, PS12, and PS18; 0%, 6%, 12%, and 18%, respectively) for four weeks, including an acclimation period of one week. The results showed no significant differences among the groups for average egg weight (P > 0.

Maximizing light-driven CO and N fixation efficiency in quantum dot-bacteria hybrids.

Integrating light-harvesting materials with microbial biochemistry is a viable approach to produce chemicals with high efficiency from the air, water, and sunlight. Yet it remains unclear whether all absorbed photons in the materials can be transferred through the material-biology interface for solar-to-chemical production and whether the presence of materials beneficially affect the microbial metabolism. Here we report a microbe-semiconductor hybrid by interfacing CO/N-fixing bacterium with CdTe quantum dots for light-driven CO and N fixation with internal quantum efficiencies of 47.

Machine learning-based inverse design for electrochemically controlled microscopic gradients of O and HO.

A fundamental understanding of extracellular microenvironments of O and reactive oxygen species (ROS) such as HO, ubiquitous in microbiology, demands high-throughput methods of mimicking, controlling, and perturbing gradients of O and HO at microscopic scale with high spatiotemporal precision. However, there is a paucity of high-throughput strategies of microenvironment design, and it remains challenging to achieve O and HO heterogeneities with microbiologically desirable spatiotemporal resolutions. Here, we report the inverse design, based on machine learning (ML), of electrochemically generated microscopic O and HO profiles relevant for microbiology.

Ternary Deep Eutectic Solvent (DES) with a Regulated Rate-Determining Step for Efficient Recycling of Lithium Cobalt Oxide.

Deep eutectic solvents (DESs) have attracted extensive research for their potential applications as leaching solvent to recycle valuable metal elements from spent lithium ion batteries (LIBs). Despite various advantages like being economical and green, the full potential of conventional binary DES has not yet been harnessed because of the kinetics during leaching. Herein, we consider the fundamental rate-determining-step (RDS) in conventional binary DES and attempt to design ternary DES, within which the chemical reaction kinetics and diffusion kinetics can be regulated to maximize the overall leaching rate.

Perfluorocarbon Nanoemulsions Create a Beneficial O Microenvironment in N-fixing Biological | Inorganic Hybrid.

Powered by renewable electricity, biological | inorganic hybrids employ water-splitting electrocatalysis and generate H as reducing equivalents for microbial catalysis. The approach integrates the beauty of biocatalysis with the energy efficiency of inorganic materials for sustainable chemical production. Yet a successful integration requires delicate control of the hybrid's extracellular chemical environment.

Machine-Learning-Enabled Exploration of Morphology Influence on Wire-Array Electrodes for Electrochemical Nitrogen Fixation.

Neural networks, trained on data generated by a microkinetic model and finite-element simulations, expand explorable parameter space by significantly accelerating the predictions of electrocatalytic performance. In addition to modeling electrode reactivity, we use micro/nanowire arrays as a well-defined, easily tuned, and experimentally relevant exemplary morphology for electrochemical nitrogen fixation. This model system provides the data necessary for training neural networks which are subsequently exploited for electrocatalytic material morphology optimizations and explorations into the influence of geometry on nitrogen fixation electrodes, feats untenable without large-scale simulations, on both a global and a local basis.

Electricity-powered artificial root nodule.

Root nodules are agricultural-important symbiotic plant-microbe composites in which microorganisms receive energy from plants and reduce dinitrogen (N) into fertilizers. Mimicking root nodules using artificial devices can enable renewable energy-driven fertilizer production. This task is challenging due to the necessity of a microscopic dioxygen (O) concentration gradient, which reconciles anaerobic N fixation with O-rich atmosphere.

Solution Catalytic Cycle of Incompatible Steps for Ambient Air Oxidation of Methane to Methanol.

Direct chemical synthesis from methane and air under ambient conditions is attractive yet challenging. Low-valent organometallic compounds are known to activate methane, but their electron-rich nature seems incompatible with O and prevents catalytic air oxidation. We report selective oxidation of methane to methanol with an O-sensitive metalloradical as the catalyst and air as the oxidant at room temperature and ambient pressure.

Lipopolysaccharide-affinity copolymer senses the rapid motility of swarmer bacteria to trigger antimicrobial drug release.

An intelligent drug release system that is triggered into action upon sensing the motion of swarmer P. mirabilis is introduced. The rational design of the drug release system focuses on a pNIPAAm-co-pAEMA copolymer that prevents drug leakage in a tobramycin-loaded mesoporous silica particle by covering its surface via electrostatic attraction.

Nontoxic colloidal particles impede antibiotic resistance of swarming bacteria by disrupting collective motion and speed.

A monolayer of swarming B. subtilis on semisolid agar is shown to display enhanced resistance against antibacterial drugs due to their collective behavior and motility. The dynamics of swarming motion, visualized in real time using time-lapse microscopy, prevents the bacteria from prolonged exposure to lethal drug concentrations.

Loss of collective motion in swarming bacteria undergoing stress.

The collective motion of Bacillus subtilis in the presence of a photosensitizer is disrupted by reactive oxygen species when exposed to light of sufficient dosages and is partially recovered when light irradiation is suspended. The transition from a highly collective to a more random motion is modeled using an improved self-propelled model with alignment rule. The increment in noise level describes the enhanced uncertainty in the motion of swarming bacteria under stress as observed experimentally.