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 > 0.005). The laying rate (%), feed conversion ratio (FCR) and average feed intake (AFI) decreased significantly for birds fed on 18% PS as compared to the other treatments (P < 0.005). Haugh unit, albumin height, egg-shape index and eggshell thickness among hens fed PS diets were greater averaging 80.53, 7.00, 1.29, 0.34 compared to 76.84, 6.86, 1.25 and 0.32 from Control hen eggs (P < 0.05). Serum analysis showed a trend towards elevated levels of glucose (Glu), total protein (TP) and aspartate aminotransferase (AST) among treatments. Total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) decreased for the birds fed on 6% PS. The fatty acid composition of egg yolk showed a substantial reduction for α-linolenic acid and docosahexaenoic acid increased significantly by the incorporating PS in the diet (P < 0.001). PS incorporation in diets resulted in significant improvements in both performance indicators and greater amounts of α-linolenic acid and DHA in egg yolks. These findings indicate that PS at 6% inclusion has the potential to improve fatty acid profiles of egg yolk without any adverse effect on performance of egg quality.

Machine learning-based inverse design for electrochemically controlled microscopic gradients of O2 and H2O2.

A fundamental understanding of extracellular microenvironments of O2 and reactive oxygen species (ROS) such as H2O2, ubiquitous in microbiology, demands high-throughput methods of mimicking, controlling, and perturbing gradients of O2 and H2O2 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 O2 and H2O2 heterogeneities with microbiologically desirable spatiotemporal resolutions. Here, we report the inverse design, based on machine learning (ML), of electrochemically generated microscopic O2 and H2O2 profiles relevant for microbiology. Microwire arrays with suitably designed electrochemical catalysts enable the independent control of O2 and H2O2 profiles with spatial resolution of ∼101 µm and temporal resolution of ∼10° s. Neural networks aided by data augmentation inversely design the experimental conditions needed for targeted O2 and H2O2 microenvironments while being two orders of magnitude faster than experimental explorations. Interfacing ML-based inverse design with electrochemically controlled concentration heterogeneity creates a viable fast-response platform toward better understanding the extracellular space with desirable spatiotemporal control.

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. As a proof of concept, we show that the ternary choline chloride/succinic acid/ethylene glycol (ChCl/SA/EG) type ternary DES can completely dissolve LCO powder at 140 °C in 16 h. By systematically studying the leaching process at various conditions, the energy barrier during leaching can be calculated to be 11.77 kJ/mol. Furthermore, we demonstrate that the extraction of the cobalt ions from the leaching solution can be directly achieved by adding oxalic ions without neutralizing the solution. The precipitate can be used to regenerate LCO with high purity. The recycled materials show comparable electrochemical performance with commercial LCO. Our design strategy of ternary DES with regulated RDS is expected to have both scientific and technological significance in the field of hydrometallurgical recycling of LIBs.

Maximizing light-driven CO2 and N2 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 CO2/N2-fixing bacterium Xanthobacter autotrophicus with CdTe quantum dots for light-driven CO2 and N2 fixation with internal quantum efficiencies of 47.2 ± 7.3% and 7.1 ± 1.1%, respectively, reaching the biochemical limits of 46.1% and 6.9% imposed by the stoichiometry in biochemical pathways. Photophysical studies suggest fast charge-transfer kinetics at the microbe-semiconductor interfaces, while proteomics and metabolomics indicate a material-induced regulation of microbial metabolism favoring higher quantum efficiencies compared to the biological counterparts alone.

Perfluorocarbon Nanoemulsions Create a Beneficial O2 Microenvironment in N2-fixing Biological | Inorganic Hybrid.

Powered by renewable electricity, biological | inorganic hybrids employ water-splitting electrocatalysis and generate H2 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. Such an argument is evident in the exemplary case of O2 because biocatalysis has a stringent requirement of O2 but the electrocatalysis may inadvertently perturb the oxidative pressure of biological moieties. Here we report the addition of perfluorocarbon (PFC) nanoemulsions promote a biocompatible O2 microenvironment in a O2-sensitive N2-fixing biological | inorganic hybrid. Langmuir-type nonspecific binding between bacteria and nanoemulsions facilitates O2 transport in bacterial microenvironment and leads to a 250% increase in efficiency for organic fertilizers within 120 hours. Controlling the biological microenvironment with nanomaterials heralds a general approach accommodating the compatibility in biological | inorganic hybrids.

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 (N2) 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 (O2) concentration gradient, which reconciles anaerobic N2 fixation with O2-rich atmosphere. Here we report our designed electricity-powered biological|inorganic hybrid system that possesses the function of root nodules. We construct silicon-based microwire array electrodes and replicate the O2 gradient of root nodules in the array. The wire array compatibly accommodates N2-fixing symbiotic bacteria, which receive energy and reducing equivalents from inorganic catalysts on microwires, and fix N2 in the air into biomass and free ammonia. A N2 reduction rate up to 6.5 mg N2 per gram dry biomass per hour is observed in the device, about two orders of magnitude higher than the natural counterparts.

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 O2 and prevents catalytic air oxidation. We report selective oxidation of methane to methanol with an O2-sensitive metalloradical as the catalyst and air as the oxidant at room temperature and ambient pressure. The incompatibility between C-H activation and O2 oxidation is reconciled by electrochemistry and nanomaterials, with which a concentration gradient of O2 within the nanowire array spatially segregated incompatible steps in the catalytic cycle. An unexpected 220 000-fold increase of the apparent reaction rate constants within the nanowire array leads to a turnover number up to 52 000 within 24 h. The synergy between nanomaterials and organometallic chemistry warrants a new catalytic route for CH4 functionalization.

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. The copolymer chains are also conjugated to peptide ligands YVLWKRKRKFCFI-NH2 that display affinity to Gram-negative bacteria. When swarmer P. mirabilis cells approach and come in contact with the particle, the copolymer-YVLWKRKRKFCFI-NH2 binds to the lipopolysaccharides on the outer membrane of motile P. mirabilis and are stripped off the particle surface when the cells move away; hence releasing tobramycin into the swarmer colony and inhibiting its expansion. The release mechanism is termed Motion-Induced Mechanical Stripping (MIMS). For swarmer B. subtilis, the removal of copolymers from particle surfaces via MIMS is not apparent due to poor adherence between bacteria and copolymer-YVLWKRKRKFCFI-NH2 system.

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. The elevated drug resistance is significantly reduced when the collective motion of bacteria is judiciously disrupted using nontoxic polystyrene colloidal particles immobilized on the agar surface. The colloidal particles block and hinder the motion of the cells, and force large swarming rafts to break up into smaller packs in order to maneuver across narrow spaces between densely packed particles. In this manner, cohesive rafts rapidly lose their collectivity, speed, and group dynamics, and the cells become vulnerable to the drugs. The antibiotic resistance capability of swarming B. subtilis is experimentally observed to be negatively correlated with the number density of colloidal particles on the engineered surface. This relationship is further tested using an improved self-propelled particle model that takes into account interparticle alignment and hard-core repulsion. This work has pertinent implications on the design of optimal methods to treat drug resistant bacteria commonly found in swarming colonies.

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.