Transcriptomic analyses of Vibrio parahaemolyticus under the phenyllactic acid stress.

Phenyllactic acid (PLA) generally recognized as a natural organic acid shows against Vibrio parahaemolyticus activity. In this study, V. parahaemolyticus ATCC17802 (Vp17802) was cultured under the stress of 1/2MIC PLA, and then the antibacterial mechanisms were explored via transcriptomics. The minimum inhibitory concentration (MIC) of PLA against Vp17802 was 3.2 mg/mL, and the time-kill analysis resulted that Vp17802 was inhibited. PLA was able to destroy the bacterial membrane, leading to the leakage of intracellular substances and decline of ATP levels. The RNA-sequencing analysis results indicated that 1616 significantly differentially expressed genes were identified, among which 190 were up-regulated and 1426 were down-regulated. Down-regulation of the icd2 gene in the TCA cycle mediates blockage of tyrosine metabolic, arginine biosynthesis, and oxidative phosphorylation, causing insufficient energy supply of Vp17802. Moreover, PLA could cause amino acids, metal ions, and phosphate transporters to be blocked, affecting the acquisition of nutrients. The treatment by PLA altered the expression of genes encoding functions involved in quorum sensing, flagellar assembly, and cell chemotaxis pathway, which may be interfering with the biofilm formation in Vp17802, reducing cell motility. Overall, 1.6 mg/mL PLA inhibited the growth of Vp17802 by disrupting to uptake of nutrients, cell metabolism, and the formation of biofilms. The results suggested a new direction for exploring the activity of PLA against Vp17802 and provided a theoretical basis for bacterial pathogen control in the food industry. KEY POINTS: •RNA sequencing was carried out to indicate the antibacterial mechanism of Vp17802. •The icd2 gene in the TCA cycle mediates blockage of metabolic of Vp17802. •The biofilm formation has interfered with 1.6 mg/mL PLA, which could reduce cell motility and virulence.

Lycium barbarum Is a New Host of Botryosphaeria dothidea Associated with Soft Rot Disease in China.

Goji berry (Lycium barbarum) is a plant of the Solanaceae family that is cultivated in the Chinese provinces of Xinjiang, Ningxia, Gansu, and Qinghai, and its fruit is used as a traditional Chinese medicine (Yossa Nzeuwa et al. 2019). In July 2019, fruit rot was observed at an incidence of 20 to 25% on the Goji berry at a fruit market in Yinchuan, Ningxia, China. The fruit symptoms began as slightly shriveled areas on fruit peel, with noticeable softening of the infested portion of the tissue, followed by rotting and a sour odor. To isolate the pathogen, ten symptomatic tissues were randomly collected from different boxes, surface-sterilized for 30 s with 75% ethanol, followed by 0.1% mercuric chloride, then rinsed in sterile distilled water three times and plated onto PDA. The plates were incubated at 25°C in the dark for 7 days. Five purified fungal isolates from different fruit were obtained and single-spores. Emergent fungal colonies were white with 1 to 3 mm white margins and abundant aerial hyphae, 1 to 6 mm high, that became dark gray after 4 to 5 days. Conidia were hyaline, unicellular, fusiform, and measured 19.3 to 28.2 µm× 3.8 to 6.4 µm (n=50). All the morphological characteristics were consistent with Botryosphaeria spp. (Slippers et al. 2004). Five representative isolates, BJN1-BJN5, were selected for molecular identification. Total genomic DNA of the isolates was extracted with a Plant/Fungi DNA Isolation Kit. Translation elongation factor 1-alpha (EF1) gene and internal transcribed spacer (ITS) regions were amplified with primers EF1-728F/986R (Carbone and Kohn 1999) and ITS1/ITS4, respectively. The sequencing results of the five isolates were consistent, and those of the isolate BJN1 we deposited in the NCBI GeneBank database for EF1 (MK733274) and ITS (MK359291). A BLAST search of the GenBank database indicated that the EF1 and ITS sequences had 100% and 99% similarity, respectively, to B. dothidea ex-type strain (AY236898 and KF766151). A phylogenetic tree was constructed using maximum parsimony methods in MEGA11 and BJN1 isolate clustered with the reference sequence of B. dothidea. Pathogenicity tests were performed, inoculating healthy fruit with both mycelial plugs (7 days old) and conidial suspension (1 × 106 conidia/ml), repeated three times. Mycelial plugs of five isolates (BJN1-BJN5) growing on PDA with a colony diameter of 4 mm were placed on the sterilized surface of 20 Goji berry fruit. Sterile PDA plugs were placed on 12 healthy fruit as a control. In a second test, conidial suspensions of five isolates were sprayed on the surface of 20 healthy fruit and sterilized distilled water was used as a control. The inoculated fruits were maintained in an artificial climate chamber at 25°C and 80% to 85% relative humidity with a 12-h photoperiod for 7 days. The development of soft rot, similar to that observed on the original samples, was observed on inoculated fruit while control fruits remained asymptomatic. The pathogen was reisolated from infected fruit and confirmed as B. dothidea based on morphological characteristics and molecular sequences. To our knowledge, this is the first report of B. dothidea causing postharvest fruit rot of Goji berry, and this pathogen has been reported to cause fruit rot in Kiwifruit (Li et al. 2016) and Yellowhorn (Liu et al. 2018). This study provides information on a new postharvest fruit rot of Goji berry in China that has the potential to cause economic losses.

Occurrence of Leaf Spot on Elaeocarpus decipiens Caused by Alternaria alternata, a new disease in China.

Elaeocarpus decipiens is widely cultivated as an ornamental tree of commercial importance in southern China. During March 2018 to March 2021, leaf spot disease was observed in about 40% of E. decipiens on the campus of Jiangnan University in Wuxi, Jiangsu, China (31.48°N, 120.46°E). Leaf symptoms began as small, light brown lesions that enlarged, turned olive brown in color and then became necrotic. Ten symptomatic leaves were collected from five different trees on the Jiangnan University campus and surface sterilized with 75% ethanol for 30 seconds, followed by 1% sodium hypochlorite for 1 minute, and rinsed three times with sterile distilled water before being cultured onto potato dextrose agar and incubated in the dark at 25°C for 5 days. Five purified fungal isolates were obtained by the single spore isolation method. Emergent fungal colonies were olive-green in color with 1 to 3 mm white margins and abundant aerial hyphae. Conidia were borne in chains or singly and were obclavate or obpyriform and measured 6.5 to 17.4 × 21.3 to 32.8 µm (n=50) with one to seven transverse septa and zero to three longitudinal septa. Based on morphological characteristics, the pathogen was identified as Alternaria spp.(Simmons 2007). Three representative isolates, At1, At2 and At3, were selected for molecular identification, total genomic DNA of the fungus isolates were extracted with Plant/Fungi DNA Isolation Kit (Sigma-Aldrich, Ontario, Canada). Plasma membrane ATPase (ATP) gene, chitin synthase (CHS) gene and translation elongation factor 1-alpha (EF1) gene were amplified with primers ATPDF1/ATPDR1, CHS-79F/CHS-345R (Lawrence et al. 2013) and EF1-728F/EF1-986R (Carbone and Kohn 1999). The amplification results of the three isolate genes were consistent, and we deposited the results of the ATP (MN046377), CHS (MN046378) and EF1 (MN046379) sequences of At1 in the NCBI GeneBank. The ATPase gene from the representative isolate At1 shared 99.83% similarity to A. alternata causing leaf Spot of Codonopsis pilosula in China (OM362504, Shi et al. 2022), the CHS gene shared 100% similarity to A. alternata causing brown leaf spot on Paris polyphylla var. chinensis in China (MK391053, Fu et al. 2019), and the EF1 gene shared 100% similarity to A. alternata CBS 916.96 ex-type on Arachis hypogaea in India (KC584634). A phylogenetic tree constructed with the EF1 gene using the neighbor-joining algorithm in MEGA 11 software with 1,000 bootstrap replicates revealed that the examined isolate, At1, belongs to the fungus A. alternata. For pathogenicity tests, 10 leaves of five healthy plants were sprayed with spore suspensions (1 × 107 conidia/ml) of the 10-day-old isolates (At1, At2 and At3, respectively). As a control, five plants were sprayed with sterile distilled water. After inoculation, use the bags to moisturize for 48 hours. Pathogenicity tests were conducted three times. Fourteen days after inoculation, olive brown necrotic lesions developed on inoculated leaves while control leaves remained symptomless. The pathogen was reisolated from infected leaves and confirmed as A. alternata based on morphological characteristics and molecular markers. To date, A. alternata has been reported to cause leaf spot disease on many plants inculuding Ficus religiosa (Du et al. 2022), Tilia miqueliana (Yue et al. 2023), Ligustrum japonicum (Fang et al. 2023) and so on. To our knowledge, this is the first report of the occurrence of A. alternata causing leaf spot on E. decipiens in China. The increasing area of E. decipiens cultivation and global climate change have led to an increase in the incidence of E. decipiens diseases, which should be taken into account by forest conservationists.

Non-Metallic NH4 + /H+ Co-Storage in Organic Superstructures for Ultra-Fast and Long-Life Zinc-Organic Batteries.

Compared with Zn2+ storage, non-metallic charge carrier with small hydrated size and light weight shows fast dehydration and diffusion kinetics for Zn-organic batteries. Here we first report NH4 + /H+ co-storage in self-assembled organic superstructures (OSs) by intermolecular interactions of p-benzoquinone (BQ) and 2, 6-diaminoanthraquinone (DQ) polymer through H-bonding and π-π stacking. BQ-DQ OSs exhibit exposed quadruple-active carbonyl motifs and super electron delocalization routes, which are redox-exclusively coupled with high-kinetics NH4 + /H+ but exclude sluggish and rigid Zn2+ ions. A unique 4e- NH4 + /H+ co-coordination mechanism is unravelled, giving BQ-DQ cathode high capacity (299 mAh g-1 at 1 A g-1 ), large-current tolerance (100 A g-1 ) and ultralong life (50,000 cycles). This strategy further boosts the capacity to 358 mAh g-1 by modulating redox-active building units, giving new insights into ultra-fast and stable NH4 + /H+ storage in organic materials for better Zn batteries.

Accelerating the Reaction Kinetics of CO2 Reduction to Multi-Carbon Products by Synergistic Effect between Cation and Aprotic Solvent on Copper Electrodes.

Improving the selectivity of electrochemical CO2 reduction to multi-carbon products (C2+ ) is an important and highly challenging topic. In this work, we propose and validate an effective strategy to improve C2+ selectivity on Cu electrodes, by introducing a synergistic effect between cation (Na+ ) and aprotic solvent (DMSO) to the electrolyte. Based on constant potential ab initio molecular dynamics simulations, we first revealed that Na+ facilitates C-C coupling while inhibits CH3 OH/CH4 products via reducing the water network connectivity near the electrode. Furthermore, the water network connectivity was further decreased by introducing an aprotic solvent DMSO, leading to suppression of both C1 production and hydrogen evolution reaction with minimal effect on *OCCO* hydrogenation. The synergistic effect enhancing C2 selectivity was also experimentally verified through electrochemical measurements. The results showed that the Faradaic efficiency of C2 increases from 9.3 % to 57 % at 50 mA/cm2 under a mixed electrolyte of NaHCO3 and DMSO compared to a pure NaHCO3 , which can significantly enhance the selectivity of the C2 product. Therefore, our discovery provides an effective electrolyte-based strategy for tuning CO2 RR selectivity through modulating the microenvironment at the electrode-electrolyte interface.

RNF106 aggravates esophageal squamous cell carcinoma progression through LATS2/YAP axis.

Esophageal squamous cell carcinoma (ESCC) is one of the most lethal solid tumors in China, with the 5-year overall survival rate less than 20%. Although the carcinogenic process of ESCC is still not clear, recent studies using whole genomic profiling revealed that dysregulation of Hippo signaling pathway might play important roles in ESCC progression. The ubiquitin-like with PHD and RING finger domain 1 (RNF106) was a modifier of DNA methylation and histone ubiquitination. In this study, we evaluate the oncogenic function of RNF106 in ESCC both in vitro and in vivo. Wound healing and transwell data showed that RNF106 was required for ESCC cell migration and invasion. RNF106 depletion dramatically restrained Hippo signaling targeted gene expression. The bioinformatics analysis displayed that RNF106 was increased in ESCC tumor tissues and related with poor survival in ESCC patients. Mechanistic studies demonstrated that RNF106 was associated with LATS2 and facilitate LATS2 K48-linked ubiquitination and degradation, which subsequently inhibited YAP phosphorylation and promoted YAP oncogenic function in ESCC. Taken together, our study revealed a novel link between RNF106 and Hippo signaling in ESCC, suggesting that RNF106 could be a promising target for ESCC therapy.

Population pharmacokinetics and pharmacogenetics of apatinib in adult cancer patients.

AIMS: Apatinib is widely used in Chinese cancer patients. As the in vivo drug disposition of apatinib has large individual differences, adverse events are prone to occur. Cytochrome P450 (CYP)3A5 and cancer types maybe the main factors affecting this individual differences. The objective of our study was to establish a population pharmacokinetics (PK) model of apatinib in adult cancer patients, and to explore optimal dosage regimens for individualized treatment. METHODS: Adult patients with various types of cancer treated with apatinib were enrolled. The concentration of apatinib in plasma was determined by high-performance liquid chromatography-tandem mass spectrometry. CYP3A5 genotype was determined using TaqMan allelic discrimination technique. The population PK model was developed by NONMEM V7.4. The dosing regimen was optimized based on Monte Carlo simulations. RESULTS: A population PK model of apatinib in adult cancer patient was established. CYP3A5 genotype and systemic cancer type (digestive system cancers, nondigestive system cancers) were the most significant covariates for PK parameters. Patients with CYP3A5*1 expressers (CYP3A5*1/*1 and CYP3A5*1/*3) had lower apparent clearance and apparent volume of distribution than patients who do not express CYP3A5*1 (CYP3A5*3/*3). Patients with nondigestive system cancer had higher apparent volume of distribution and absorption rate constant than digestive system cancer. The results of dose simulation suggest that the apatinib dose in patients who do not express CYP3A5*1 should be 33.33-50.00% higher than that in CYP3A5*1 expressers. CONCLUSIONS: A population PK model of apatinib in adult cancer patients was established. CYP3A5 genotype and systemic cancer type had concurrent effects on PK parameters. CYP3A5 patients who do not express CYP3A5*1 required higher doses.

Influence of Organic-Cation Defects on Optoelectronic Properties of ASnI3 Perovskites A=HC(NH2 )2 , CH3 NH3.

Tin organic-inorganic halide perovskites (tin OIHPs) possess a desirable band gap and their power conversion efficiency (PCE) has reached 14 %. A commonly held view is that the organic cations in tin OIHPs would have little impact on the optoelectronic properties. Herein, we show that the defective organic cations with randomly dynamic characteristics can have marked effect on optoelectronic properties of the tin OIHPs. Hydrogen vacancies originated from the proton dissociation from FA [HC(NH2 )2 ] in FASnI3 can induce deep transition levels in the band gap but yield relatively small nonradiative recombination coefficients of 10-15  cm3 s-1 , whereas those from MA (CH3 NH3 ) in MASnI3 can yield much larger nonradiative recombination coefficients of 10-11  cm3 s-1 . Additional insight into the "defect tolerance" is gained by disentangling the correlations between dynamic rotation of organic cations and charge-carrier dynamics.

A Universal Descriptor for Complicated Interfacial Effects on Electrochemical Reduction Reactions.

Supported catalysts have exhibited excellent performance in various reactions. However, the rational design of supported catalysts with high activity and certain selectivity remains a great challenge because of the complicated interfacial effects. Using recently emerged two-dimensional materials supported dual-atom catalysts (DACs@2D) as a prototype, we propose a simple and universal descriptor based on inherent atomic properties (electronegativity, electron type, and number), which can well evaluate the complicated interfacial effects on the electrochemical reduction reactions (i.e., CO2, O2, and N2 reduction reactions). Based on this descriptor, activity and selectivity trends in CO2 reduction reaction are successfully elucidated, in good agreement with available experimental data. Moreover, several potential catalysts with superior activity and selectivity for target products are predicted, such as CuCr/g-C3N4 for CH4 and CuSn/N-BN for HCOOH. More importantly, this descriptor can also be extended to evaluate the activity of DACs@2D for O2 and N2 reduction reactions, with very small errors between the prediction and reported experimental/computational results. This work provides feasible principles for the rational design of advanced electrocatalysts and the construction of universal descriptors based on inherent atomic properties.

Dynamic Stability of Copper Single-Atom Catalysts under Working Conditions.

The long-term stability of single-atom catalysts is a major factor affecting their large-scale commercial application. How to evaluate the dynamic stability of single-atom catalysts under working conditions is still lacking. Here, taking a single copper atom embedded in N-doped graphene as an example, the "constant-potential hybrid-solvation dynamic model" is used to evaluate the reversible transformation between copper single atoms and clusters under realistic reaction conditions. It is revealed that the adsorption of H is a vital driving force for the leaching of the Cu single atom from the catalyst surface. The more negative the electrode potential, the stronger the adsorption of H. As a result, the competitive hydrogen evolution reaction is inhibited, and Cu-N bonds are weakened, resulting in some Cu atoms being tethered on the catalyst surface and some being dissolved in the aqueous solution. The collision of the Cu atoms in the two states forms a transient Cu cluster structure as a true catalytic active site to promote CO2 reduction to ethanol. As the applied potential is released or switched to a positive value, hydroxyl radicals (OH•) play a dominant role in the oxidation process of the Cu cluster, and then Cu returns to the initial atomic dispersion state by redeposition, completing the reconstruction cycle of the copper catalyst. Our work provides a fundamental understanding of the dynamic stability of Cu single-atom catalysts under working conditions at the atomic level and calls for a reassessment of the stability of currently reported single-atom catalysts considering realistic reaction conditions.

Ferroelastic-switching-driven large shear strain and piezoelectricity in a hybrid ferroelectric.

Materials that can produce large controllable strains are widely used in shape memory devices, actuators and sensors1,2, and great efforts have been made to improve the strain output3-6. Among them, ferroelastic transitions underpin giant reversible strains in electrically driven ferroelectrics or piezoelectrics and thermally or magnetically driven shape memory alloys7,8. However, large-strain ferroelastic switching in conventional ferroelectrics is very challenging, while magnetic and thermal controls are not desirable for practical applications. Here we demonstrate a large shear strain of up to 21.5% in a hybrid ferroelectric, C6H5N(CH3)3CdCl3, which is two orders of magnitude greater than that in conventional ferroelectric polymers and oxides. It is achieved by inorganic bond switching and facilitated by structural confinement of the large organic moieties, which prevents undesired 180° polarization switching. Furthermore, Br substitution can soften the bonds, allowing a sizable shear piezoelectric coefficient (d35 ≈ 4,830 pm V-1) at the Br-rich end of the solid solution, C6H5N(CH3)3CdBr3xCl3(1-x). The electromechanical properties of these compounds suggest their potential in lightweight and high-energy-density devices, and the strategy described here could inspire the development of next-generation piezoelectrics and electroactive materials based on hybrid ferroelectrics.

Icariin Ameliorates Alzheimer's Disease Pathology by Alleviating Myelin Injury in 3 × Tg-AD Mice.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by excessive deposition of ß amyloid (Aß), hyperphosphorylation of tau protein, and neuronal cell death. Recent studies have shown that myelin cell damage, which leads to cognitive dysfunction, occurs before AD-related pathological changes. Here, we examine the effect of icariin (ICA), a prenylated flavonol glycoside, in improving cognitive function in AD model mice. ICA has been reported to exhibit cardiovascular protective functions and antiaging effects. In this study, we used 3 × Tg-AD mice as an AD model. The Morris water maze and Y maze tests were performed to assess the learning and memory of the mice. Immunofluorescence analysis of Aß1-42 deposition and myelin basic protein (MBP) expression in the mouse hippocampus was performed. Tau protein phosphorylation and MBP protein expression in the hippocampus were further analyzed by Western blotting. Myelin damage in the mouse optic nerve was evaluated by electron microscopy, and LFB staining was performed to assess myelin morphology in the mouse corpus callosum. MBP, Mpp5, and Egr2 transcript levels were quantified by qPCR. We observed that ICA treatment improved the learning and memory of 3 × Tg-AD mice and reduced Aß deposition and tau protein phosphorylation in the hippocampus. Moreover, this treatment protocol increased myelin-related gene expression and reduced myelin damage.

In situ monitoring of silver adsorption on assembled gold nanorods by surface-enhanced Raman scattering.

Self-assembly of metal nanocrystals is able to create a gap of sub-nanometer distance for concentrating incoming light by the strong coupling of surface plasmon resonance, known as a 'hot spot'. Although the plasmonic property of silver is better than other metals in the visible range, the superior Raman enhancement of silver compared to gold is still under debate. To provide direct evidence, in this work, we studied the silver adsorption on assembled gold nanorods (AuNRs) using in situ surface-enhanced Raman scattering (SERS) measurements. The self-assembled AuNR multimers were used as the SERS substrate, where the 4-mercaptophenol (MPh) molecules in our experiment played dual roles as both probe molecules for the Raman scattering and linking molecules for the AuNR assembly in a basic environment. Silver atoms were adsorbed on the surface of gold nanorod assemblies by reduction of Ag+ anions. The stability of the adsorbed silver was guaranteed by the basic environment. We monitored the SERS signal during the silver adsorption with a home-built in situ Raman spectroscope, which was synchronized by recording the UV-vis absorption spectra of the reaction solution to instantly quantify the plasmonic effect of the silver adsorption. Although a minor change was found in the plasmonic resonance wavelength or intensity, the measured SERS signal at specific modes faced a sudden increase by 2.1 folds during the silver adsorption. The finite element method (FEM) simulation confirmed that the silver adsorption corresponding to the plasmonic resonance variation gave little change to the electric field enhancement. We attributed the mode-specific enhancement mechanism of the adsorption of silver to the chemical enhancement from charge transfer (CT) for targeting molecules with a specific orientation. Our findings provided new insights to construct SERS substrates with higher enhancement factor (EF), which hopefully would encourage new applications in the field of surface-enhanced optical spectroscopies.

Acori tatarinowii rhizoma extract ameliorates Alzheimer's pathological syndromes by repairing myelin injury and lowering Tau phosphorylation in mice.

It has been shown that Acori tatarinowii rhizoma (ATR) extract can improve cognitive functions in Alzheimer Diseas (AD) patients or animal models. In this study, we have examined the activity of ATR in 3×Tg-AD model mice with different comprehensive behavioral tests like the Morris water maze and Y-maze test assay for behavior. Moreover, we performed LFB staining for myelin determination in the AD model mouse. By analyzing different pathways, we determined key proteins that are beneficial for ameliorating AD syndrome in the mouse. Periluminally, ATR treatment improved the learning and memory ability that was determined by comprehensive behavioral tests. Moreover, treatment reduces the p-Tau accumulation in the 3×Tg-AD mouse and the level of p-Tau accumulation was at per with the wildtype control mouse and improves the myelin lining in 3×Tg-AD mouse. In conclusion, our results indicate that ATR-treatment can improve the learning ability of AD model mice and the hyperphosphorylation of Tau protein was decreased. ATR can protect myelin lining from damage in AD syndrome.

New Mechanism for N2 Reduction: The Essential Role of Surface Hydrogenation.

Electrocatalytic N2 reduction is one of the most promising ways for green and sustainable production of NH3. However, a mechanistic understanding of the N2 reduction process remains very limited. Herein, a surface-hydrogenation mechanism for the N2 reduction reaction is proposed, which can well address the recently emerged sharp discrepancies between experiments and computations. Our results reveal that surface hydrogenation can drive N2 reduction reaction on catalysts with weak N2-binding strength (i.e., noble-metal catalysts) at low potentials. Instead of N2 adsorption, the reduction of H+ is found to be the first step, which is also the potential determining step of the whole process. N2 can be activated and reduced into *N2H2 subsequently by overcoming relatively high energy barriers, which determines the total reaction rate. Moreover, the cooperative effect of surface *H and the catalysts plays a key role in the activation of N2. Our work not only provides new insights into the N2 reduction reaction, but also paves a promising way for advancing sustainable NH3 production.

Self-Template Synthesis of Ag-Pt Hollow Nanospheres as Electrocatalyst for Methanol Oxidation Reaction.

Ag-Pt bimetallic hollow nanospheres have been prepared through a one-pot, wet-chemical route. The formation of the hollow nanostructure can be explained by a self-template mechanism in which initially formed silver nanoparticles serve as the template. The Ag-Pt hollow nanospheres with an Ag/Pt ratio of 0.89:1 show the best electrochemical catalytic performances in the methanol oxidation reaction. Furthermore, the catalytic activity of the Ag-Pt hollow nanospheres is also much better than that of commercial Pt/C catalyst. The superior electrochemical performance of the Ag-Pt hollow nanospheres can be ascribed to the hollow nanostructure and the synergistic effect of Ag and Pt.

[Analysis of tobacco site features using near-infrared spectroscopy and projection model].

In this paper, total of 5170 flue-cured tobacco samples collected from 2003 to 2012 in the domestic and foreign origin by Shanghai Tobacco Group Technical Center were tested by near infrared spectroscopy, including the typical upper leaves 1394, central 2550, the lower part of 1226. Using projection model of based on principal component and Fisher criterion (PPF), follow the projected results to get no statistically significant differences at adjacent principal components, and the number of principal components as little as possible, in this paper, four main components to build projection analysis model, the model results show that: the near-infrared spectral characteristics of the upper and lower leaves have a significant difference that can be achieved almost entirely distinguished; while the middle leaves with upper and lower have a certain degree of overlap, which is consistent to the actual situation of the continuity of tobacco leaf. At the same time, Euclidean distance between the predicted sample projection values and the mean projection values of each class in the model, a description is given for the prediction samples to quantify the extent of the site features, and its first and second close categories. Using the dispersion of projected values in model and the given threshold value, prediction results can be refined into typically upper, upper to central, central to upper, typical central, central to the lower, the lower to central, typically the lower, or super-model range. The model was validated by 34 tobacco samples obtained from the re-drying process in 2012 with different origins and parts. This kind of analysis methods, not only can achieve discriminant analysis, and get richer feature attribute information, can provide guidance on the raw tobacco processing and formulations.

The antibacterial mechanism of (-)-epigallocatechin-3-gallate (EGCG) against Campylobacter jejuni through transcriptome profiling.

(-)-Epigallocatechin-3-gallate (EGCG) has been shown antibacterial activity against Campylobacter jejuni; however, the relevant antibacterial mechanism is unknown. In this study, phenotypic experiments and RNA sequencing were used to explore the antibacterial mechanism. The minimum inhibitory concentration of EGCG on C. jejuni was 32 µg/mL. EGCG-treated was able to increase intracellular reactive oxygen species levels and decline bacterial motility. The morphology and cell membrane of C. jejuni after EGCG treatment were observed collapsed, broken, and agglomerated by field emission scanning electron microscopy and fluorescent microscopy. The RNA-seq analysis presents that there are 36 and 72 differential expressed genes after C. jejuni was treated by EGCG with the concentration of 16 and 32 µg/mL, respectively. EGCG-treated increased the thioredoxin expression, which was a critical protein to resist oxidative stress. Moreover, downregulation of the flgH and flgM gene in flagellin biosynthesis of C. jejuni was able to impair the flagella, reducing cell motility and virulence. The primary antibacterial mechanism revealed by RNA-seq is that EGCG with iron-chelating activity competes with C. jejuni for iron, causing iron deficiency in C. jejuni, which potentially impacts the survival and virulence of C. jejuni. The results suggested a new direction for exploring the activity of EGCG against C. jejuni in the food industry. PRACTICAL APPLICATION: A deeper understanding of the antibacterial mechanism of EGCG against C. jejuni was more beneficial in improving the food safety, eliminating concerns about human health caused by C. jejuni in future food, and promoting the natural antibacterial agent EGCG application in the food industry.

Machine Learning Accelerates Precise Excited-State Potential Energy Surface Calculations on a Quantum Computer.

Electronically excited-state problems represent a crucial research field in quantum chemistry, closely related to numerous practical applications in photophysics and photochemistry. The emerging of quantum computing provides a promising computational paradigm to solve the Schrödinger equation for predicting potential energy surfaces (PESs). Here, we present a deep neural network model to predict parameters of the quantum circuits within the framework of variational quantum deflation and subspace search variational quantum eigensolver, which are two popular excited-state algorithms to implement on a quantum computer. The new machine learning-assisted algorithm is employed to study the excited-state PESs of small molecules, achieving highly accurate predictions. We then apply this algorithm to study the excited-state properties of the ArF system, which is essential to a gas laser. Through this study, we believe that with future advancements in hardware capabilities, quantum computing could be harnessed to solve excited-state problems for a broad range of systems.