Pore-Scale Simulation of Deep Shale Gas Flow Considering the Dual-Site Langmuir Adsorption Model Based on the Pore Network Model.

As a key resource in the oil and gas sector, shale gas development profoundly influences the advancement of the global energy industry. Deep shale gas reservoirs, typically found at depths exceeding 3500 m, represent a significant portion of total shale gas reserves. Currently, pore network models primarily simulate middle and shallow shale gas, insufficiently addressing the unique challenges posed by high-temperature and high-pressure conditions in deep shale gas formations. There is an urgent need to explore the microscale flow dynamics of deep shale gas. In this work, we use the pore network model to simulate the flow dynamics of deep shale gas, particularly under nanoconfinement conditions. The simulation integrates adsorption, slip flow, Knudsen diffusion, and bulk flow phenomena. Utilizing the dual-site Langmuir adsorption model tailored for high-temperature and high-pressure conditions enhances the accuracy of gas conductivity calculations for the adsorbed phase, thereby reflecting the specific characteristics of deep shale gas reservoirs. Moreover, this research investigates the flow characteristics of deep shale gas under varying sensitivity parameters, such as water saturation, temperature, and pressure. It explores methane flow dynamics, focusing on effective diffusion coefficients and permeability. The modified approach to calculating adsorption phase conductivity using the dual-site Langmuir adsorption model accurately captures the adsorption behaviors and characteristics of deep shale gas reservoirs.

MiCOL6, MiCOL7A and MiCOL7B isolated from mango regulate flowering and stress response in transgenic Arabidopsis.

The CONSTANS/CONSTANS-Like (CO/COL) family has been shown to play important roles in flowering, stress tolerance, fruit development and ripening in higher plants. In this study, three COL genes, MiCOL6, MiCOL7A and MiCOL7B, which each contain only one CCT domain, were isolated from mango (Mangifera indica), and their functions were investigated. MiCOL7A and MiCOL7B were expressed mainly at 20 days after flowering (DAF), and all three genes were highly expressed during the flowering induction period. The expression levels of the three genes were affected by light conditions, but only MiCOL6 exhibited a clear circadian rhythm. Overexpression of MiCOL6 promoted earlier flowering, while overexpression of MiCOL7A or MiCOL7B delayed flowering compared to that in the control lines of Arabidopsis thaliana under long-day (LD) and short-day (SD) conditions. Overexpressing MiCOL6, MiCOL7A or MiCOL7B in transgenic plants increased superoxide dismutase (SOD) and proline levels, decreased malondialdehyde (MAD) levels, and improved survival under drought and salt stress. In addition, yeast two-hybrid (Y2H) and bimolecular fluorescence complementation (BiFC) analyses showed that the MiCOL6, MiCOL7A and MiCOL7B proteins interact with several stress- and flower-related proteins. This work demonstrates the functions of MiCOL6, MiCOL7A and MiCOL7B and provides a foundation for further research on the role of mango COL genes in flowering regulation and the abiotic stress response.

Enzyme-Free Colorimetric Method for Fast Detection of PIK3CA Gene Mutation by Praseodymia Nanorods.

The frequently mutated phosphatidylinositol 3-kinase catalytic subunit alpha (PIK3CA) gene is associated with multiple tumors and endocytosis of viruses. Identification of muted nucleotides at the hotspot can help in finding the susceptible people who are vulnerable to cancers and viruses. Herein, a simple enzyme-free colorimetric method is developed for the quick detection of PIK3CA gene mutations. The main mechanism lies in the dissimilar interactions between praseodymia nanorods and different nucleotides, as well as the underlying oxidase-mimicking characteristics of praseodymia. With rational designs of probes and processes, this method has great potential for expanded applications in the screening of mutations in other genes of interest.

Engineering Support and Distribution of Palladium and Tin on MXene with Modulation of the d-Band Center for CO-resilient Methanol Oxidation.

The efficiency of direct methanol fuel cell (DMFC) is largely determined by the activity and durability of methanol oxidation reaction (MOR) catalysts. Herein, we present a CO-resilient MOR catalyst of palladium-tin nano-alloy anchored on Se-doped MXene (PdSn0.5 /Se-Ti3 C2 ) via a progressive one-step electrochemical deposition strategy. MOR mass activity resulting from Pd/Se-Ti3 C2 catalyst (1046.2 mA mg-1 ) is over 2-fold larger than that of Pd/Ti3 C2 , suggesting that the introduction of Se atoms on MXene might accelerate the reaction kinetics. PdSn0.5 /Se-Ti3 C2 with Se-doping progress of MXene and the cooperated Pd-Sn sites has a superior MOR mass activity (4762.8 mA mg-1 ), outperforming many other reported Pd-based catalysts. Both experimental results and theoretical calculation reveal that boosted electron interaction of metal crystals with Se-doped MXene and optimized distribution of Pd-Sn sites can modulate the d band center, reduce adsorption energies of CO* at Pd site and enhance OH* generation at Sn site, resulting in highly efficient removal of CO intermediates by reaction with neighboring OH species on adjacent Sn sites.

Exploring Anomalous Fluid Behavior at the Nanoscale: Direct Visualization and Quantification via Nanofluidic Devices.

Nanofluidics is the study of fluids under nanoscale confinement, where small-scale effects dictate fluid physics and continuum assumptions are no longer fully valid. At this scale, because of large surface-area-to-volume ratios, the fluid interaction with boundaries becomes more pronounced, and both short-range steric/hydration forces and long-range van der Waals forces and electrostatic forces dictate fluid behavior. These forces lead to a spectrum of anomalous transport and thermodynamic phenomena such as ultrafast water flow, enhanced ion transport, extreme phase transition temperatures, and slow biomolecule diffusion, which have been the subject of extensive computational studies. Experimental quantification of these phenomena was also enabled by the advent of nanofluidic technology, which has transformed challenging nanoscale fluid measurements into facile optical and electrical recordings. Our groups' focus is to investigate nanoscale (2 to 103 nm) fluid behaviors in the context of fluid mechanics and thermodynamics through the development of novel nanofluidic tools, to examine the applicability of classical equations at the nanoscale, to identify the source of deviations, and to explore new physics emerging at this scale. In this Account, we summarize our recent findings regarding liquid transport, vaporization, and condensation of nanoscale-confined liquids. Our study of nanoscale water transport identified an additional resistance in hydrophilic nanochannels, attributed to the reduced cross-sectional area caused by the formation of an immobile hydration layer on the surfaces. In contrast, a reduction in flow resistance was discovered in graphene-coated hydrophobic nanochannels, due to water slippage on the graphene surface. In the context of vaporization, the kinetic-limited evaporation flux was measured and found to exceed the classical theoretical prediction by an order of magnitude in hydrophilic nanochannels/nanopores as a result of the thin film evaporation outside of the apertures. This factor was eliminated by modifying the hydrophobicity of the aperture's exterior surface, enabling the identification of the true kinetic limits inside nanoconfinements and a crucial confinement-dependent evaporation coefficient. The transport-limited evaporation dynamics was also quantified, where experimental results confirmed the parallel diffusion-convection resistance model in both single nanoconduits and nanoporous systems at high accuracy. Furthermore, we have extended our studies to different aspects of condensation in nanoscale-confined spaces. The initiation of condensation for a single-component hydrocarbon was observed to follow the Kelvin equation, whereas for hydrocarbon mixtures it deviated from classical theory because of surface-selective adsorption, which has been corroborated by simulations. Moreover, the condensation dynamics deviates from the bulk and is governed by either vapor transport or liquid transport depending on the confinement scale. Overall, by using novel nanofluidic devices and measurement strategies, our work explores and further verifies the applicability of classical fluid mechanics and thermodynamic equations such as the Navier-Stokes, Kelvin, and Hertz-Knudsen equations at the nanoscale. The results not only deepen our understanding of the fundamental physical phenomena of nanoscale fluids but also have important implications for various industrial applications such as water desalination, oil extraction/recovery, and thermal management. Looking forward, we see tremendous opportunities for nanofluidic devices in probing and quantifying nanoscale fluid thermophysical properties and more broadly enabling nanoscale chemistry and materials science.

Implantable, Degradable, Therapeutic Terahertz Metamaterial Devices.

Metamaterial (MM) sensors and devices, usually consisting of artificially structured composite materials with engineered responses that are mainly determined by the unit structure rather than the bulk properties or composition, offer new functionalities not readily available in nature. A set of implantable and resorbable therapeutic MM devices at terahertz (THz) frequencies are designed and fabricated by patterning magnesium split ring resonators on drug-loaded silk protein substrates with controllable device degradation and drug release rates. To demonstrate proof-of-concept, a set of silk-based, antibiotics-loaded MM devices, which can serve as degradable antibacterial skin patches with capabilities to monitor drug-release in real time are fabricated. The extent of drug release, which correlates with the degradation of the MM skin patch, can be monitored by analyzing the resonant responses in reflection during degradation using a portable THz camera. Animal experiments are performed to demonstrate the in vivo degradation process and the efficacy of the devices for antibacterial treatment. Thus, the implantable and resorbable therapeutic MM devices do not need to be retrieved once implanted, providing an appealing alternative for in-vivo sensing and in situ treatment applications.

Nanoscale Phase Measurement for the Shale Challenge: Multicomponent Fluids in Multiscale Volumes.

Hydrocarbon recovery from shale reservoirs provides an increasing share of world energy. These resources are multicomponent fluid mixtures within multiscale geometries, and understanding their associated phase-change thermodynamics presents an array of challenges for experimentalists, theorists, operators, and policy makers. Here, we quantify hydrocarbon mixture phase behavior via direct imaging of connected channels spanning 4 orders of magnitude (10 nm to 10 µm) with supporting density functional theory. The methane/propane mixture dew point shifts, with early condensation of heavy components in nanopores because of a combination of capillarity and competitive surface adsorption. The bubble point in nanoconfinement is found to be deeply suppressed (∼3-fold), to below the bulk dew point of the original mixture, because of the exchange of mixture components with larger connected volumes. The trapping of the heaviest components of hydrocarbon mixtures within the smallest connected pores has implications for shale operations, reserve estimation, and ultimately energy security.

Bubble Point Pressures of Hydrocarbon Mixtures in Multiscale Volumes from Density Functional Theory.

Accurate characterization of the bubble point pressure of hydrocarbon mixtures under nanoconfinement is crucial to the prediction of ultimate oil recovery and well productivity of shale/tight oil reservoirs. Unlike conventional reservoirs, shale has an extensive network of tiny pores in the range of a few nanometers. In nanopores, the properties of hydrocarbon fluids deviate from those in bulk because of significant surface adsorption. Many previous theoretical works use a conventional equation of state model coupled with capillary pressure to study the nanoconfinement effect. Without including the inhomogeneous molecular density distributions in nanoconfinement, these previous approaches predict only slightly reduced bubble points. In this work, we use density functional theory to study the effect of nanoconfinement on the hydrocarbon mixture bubble point pressure by explicitly considering fluid-surface interactions and inhomogeneous density distributions in nanopores. We find that as system pressure decreases, while lighter components are continuously released from the nanopores, heavier components accumulate within. The bubble point pressure of nanoconfined hydrocarbon mixtures is thus significantly suppressed from the bulk bubble point to below the bulk dew point, in line with our previous experiments. When bulk fluids are in a two-phase, the confined hydrocarbon fluids are in a single liquid-like phase. As pore size increases, bubble point pressure of confined fluids increases and hydrocarbon average density in nanopores approaches the liquid-phase density in bulk when bulk is in a two-phase region. For a finite volume bulk bath, we find that because of the competitive adsorption in nanopores, the bulk bubble point pressure increases in line with a previous experimental work. Our work demonstrates how mixture dynamics and nanopore-bulk partitioning influence phase behavior in nanoconfinement and enables the accurate estimation of hydrocarbon mixture bubble point pressure in shale nanopores.

Bubble nucleation and growth in nanochannels.

We apply micro- and nanofluidics to study fundamental phase change behaviour at nanoscales, as relevant to shale gas/oil production. We investigate hydrocarbon phase transition in sub-100 nm channels under conditions that mimic the pressure drawdown process. Measured cavitation pressures are compared with those predicted from the nucleation theory. We find that cavitation pressure in the nanochannels corresponds closer to the spinodal limit than that predicted from classical nucleation theory. This deviation indicates that hydrocarbons remain in the liquid phase in nano-sized pores under pressures much lower than the saturation pressure. Depending on the initial nucleation location - along the channel or at the end - two types of bubble growth dynamics were observed. Bubble growth was measured experimentally at different nucleation conditions, and results agree with a fluid dynamics model including evaporation rate, instantaneous bulk liquid velocity, and bubble pressure. Collectively these results demonstrate, characterize, and quantify isothermal bubble nucleation and growth of a pure substance in nanochannels.

Cloning, Characterization and Expression Pattern Analysis of a Cytosolic Copper/Zinc Superoxide Dismutase (SaCSD1) in a Highly Salt Tolerant Mangrove (Sonneratia alba).

Mangroves are critical marine resources for their remarkable ability to tolerate seawater. Antioxidant enzymes play an especially significant role in eliminating reactive oxygen species and conferring abiotic stress tolerance. In this study, a cytosolic copper/zinc superoxide dismutase (SaCSD1) cDNA of Sonneratia alba, a mangrove species with high salt tolerance, was successfully cloned and then expressed in Escherichia coli Rosetta-gami (designated as SaCSD1). SaCSD1 comprised a complete open reading frame (ORF) of 459 bp which encoded a protein of 152 amino acids. Its mature protein is predicted to be 15.32 kDa and the deduced isoelectric point is 5.78. SaCSD1 has high sequence similarity (85%-90%) with the superoxide dismutase (CSD) of some other plant species. SaCSD1 was expressed with 30.6% yield regarding total protein content after being introduced into the pET-15b (Sma I) vector for expression in Rosetta-gami and being induced with IPTG. After affinity chromatography on Ni-NTA, recombinant SaCSD1 was obtained with 3.2-fold purification and a specific activity of 2200 U/mg. SaCSD1 showed good activity as well as stability in the ranges of pH between 3 and 7 and temperature between 25 and 55 °C. The activity of recombinant SaCSD1 was stable in 0.25 M NaCl, Dimethyl Sulphoxide (DMSO), glycerol, and chloroform, and was reduced to a great extent in ß-mercaptoethanol, sodium dodecyl sulfate (SDS), H2O2, and phenol. Moreover, the SaCSD1 protein was very susceptive to pepsin digestion. Real-time Quantitative Polymerase Chain Reaction (PCR) assay demonstrated that SaCSD1 was expressed in leaf, stem, flower, and fruit organs, with the highest expression in fruits. Under 0.25 M and 0.5 M salt stress, the expression of SaCSD1 was down-regulated in roots, but up-regulated in leaves.

Stereotactic radiosurgery with and without embolization for intracranial arteriovenous malformations: a systematic review and meta-analysis.

OBJECT: The effectiveness and risk of stereotactic radiosurgery (SRS) in the management of partially embolized intracranial arteriovenous malformations (AVMs) remain controversial. The aim of this analysis was to assess current evidence regarding the efficiency and safety of SRS for AVM patients with and without prior embolization. METHODS: To compare SRS in patients with and without embolization, the authors conducted a meta-analysis of studies by searching the literature via PubMed and EMBASE for the period between January 2000 and December 2013, complemented by a hand search. Primary outcome was the rate of AVM obliteration on a 3-year follow-up angiogram. Secondary outcome was the rate of hemorrhage at 3 years after SRS. Tertiary outcome was permanent neurological deficits related to radiation-induced changes. RESULTS: Ten studies eligible for analysis included 1988 patients: 593 had undergone embolization followed by SRS and 1395 had undergone SRS alone. The AVM obliteration rate was significantly lower in patients who had undergone embolization followed by SRS than in those who had undergone SRS alone (41.0% vs 59%, OR 0.46, 95% CI 0.37-0.56, p < 0.00001). However, the rates of hemorrhage (7.3% vs 5.6%, OR 1.17, 95% CI 0.74-1.83, p = 0.50) and permanent neurological deficits related to radiation-induced changes (3.3% vs 3.4%, OR 1.41, 95% CI 0.64-3.11, p = 0.39) were not significantly different between the two groups. CONCLUSIONS: Embolization before SRS significantly decreases the AVM obliteration rate. However, there is no significant difference in the risk of hemorrhage and permanent neurological deficits after SRS alone and following embolization. Further validation by well-designed prospective or randomized cohort studies is still needed.

Revolutionizing targeting precision: microfluidics-enabled smart microcapsules for tailored delivery and controlled release.

As promising delivery systems, smart microcapsules have garnered significant attention owing to their targeted delivery loaded with diverse active materials. By precisely manipulating fluids on the micrometer scale, microfluidic has emerged as a powerful tool for tailoring delivery systems based on potential applications. The desirable characteristics of smart microcapsules are associated with encapsulation capacity, targeted delivery capability, and controlled release of encapsulants. In this review, we briefly describe the principles of droplet-based microfluidics for smart microcapsules. Subsequently, we summarize smart microcapsules as delivery systems for efficient encapsulation and focus on target delivery patterns, including passive targets, active targets, and microfluidics-assisted targets. Additionally, based on release mechanisms, we review controlled release modes adjusted by smart membranes and on/off gates. Finally, we discuss existing challenges and potential implications associated with smart microcapsules.

Prediction and transmission analysis of bluetongue disease in China.

Bluetongue disease is an infectious disease transmitted by Culicoides as vectors, mainly infecting ruminants. Because ruminants play an important role in animal husbandry in China, the outbreak of bluetongue disease can cause serious economic losses. Maxent model was applied to predict the distribution of bluetongue in China based on the data derived from domestic and foreign academic literature databases including CNKI, Wanfang Database, PubMed, Web of Science and Google Scholar. The results showed that annual mean temperature (BIO1), precipitation in driest month (BIO14), sheep density (SD) and altitude (Elev) were the relevant variables of bioclimatic suitable zones for bluetongue disease. Precipitation in wettest month (BIO13), BIO1, BIO14, Elev were the main variables affecting the habitat of the bluetongue vector Culicoides. The most suitable climate for bluetongue infection occurs in southern China, central China and parts of Xinjiang. The suitable living areas of Culicoides are mainly located in southern, central and eastern China, and the overlap of the two suitable areas is high. The study suggested that southern, central, and eastern China are high-risk areas for bluetongue due to the significant overlap of suitable habitats for both the disease and its vector. Implementing effective surveillance and targeted control strategies in these regions is crucial for mitigating the impact of bluetongue disease.

Application and Progress of Machine Learning in Pesticide Hazard and Risk Assessment.

Long-term exposure to pesticides is associated with the incidence of cancer. With the exponential increase in the number of new pesticides being synthesized, it becomes more and more important to evaluate the toxicity of pesticides by means of simulated calculations. Based on existing data, machine learning methods can train and model the predictions of the effects of novel pesticides, which have limited available data. Combined with other technologies, this can aid the synthesis of new pesticides with specific active structures, detect pesticide residues, and identify their tolerable exposure levels. This article mainly discusses support vector machines, linear discriminant analysis, decision trees, partial least squares, and algorithms based on feedforward neural networks in machine learning. It is envisaged that this article will provide scientists and users with a better understanding of machine learning and its application prospects in pesticide toxicity assessment.

The extracellular matrix with a continuous gradient of SDF1αguides the oriented migration of human umbilical cord mesenchymal stem cells.

The extracellular matrix (ECM) plays a crucial role in maintaining cell morphology and facilitating intercellular signal transmission within the human body. ECM has been extensively utilized for tissue injury repair. However, the consideration of factor gradients during ECM preparation has been limited. In this study, we developed a novel approach to generate sheet-like ECM with a continuous gradient of stromal cell-derived factor-1 (SDF1α). Briefly, we constructed fibroblasts to overexpress SDF1αfused with the collagen-binding domain (CBD-SDF1α), and cultured these cells on a slanted plate to establish a gradual density cell layer at the bottom surface. Subsequently, excess parental fibroblasts were evenly distributed on the plate laid flat to fill the room between cells. Following two weeks of culture, the monolayer cells were lyophilized to form a uniform ECM sheet possessing a continuous gradient of SDF1α. This engineered ECM material demonstrated its ability to guide oriented migration of human umbilical cord mesenchymal stem cells on the ECM sheet. Our simple yet effective method holds great potential for advancing research in regenerative medicine.

Deep learning-based automated scan plane positioning for brain magnetic resonance imaging.

Background: Manual planning of scans in clinical magnetic resonance imaging (MRI) exhibits poor accuracy, lacks consistency, and is time-consuming. Meanwhile, classical automated scan plane positioning methods that rely on certain assumptions are not accurate or stable enough, and are computationally inefficient for practical application scenarios. This study aims to develop and evaluate an effective, reliable, and accurate deep learning-based framework that incorporates prior physical knowledge for automatic head scan plane positioning in MRI. Methods: A deep learning-based end-to-end automated scan plane positioning framework has been developed for MRI head scans. Our model takes a three-dimensional (3D) pre-scan image input, utilizing a cascaded 3D convolutional neural network to detect anatomical landmarks from coarse to fine. And then, with the determined landmarks, accurate scan plane localization can be achieved. A multi-scale spatial information fusion module was employed to aggregate high- and low-resolution features, combined with physically meaningful point regression loss (PRL) function and direction regression loss (DRL) function. Meanwhile, we simulate complex clinical scenarios to design data augmentation strategies. Results: Our proposed approach shows good performance on a clinically wide range of 229 MRI head scans, with a point-to-point absolute error (PAE) of 0.872 mm, a point-to-point relative error (PRE) of 0.10%, and an average angular error (AAE) of 0.502°, 0.381°, and 0.675° for the sagittal, transverse, and coronal planes, respectively. Conclusions: The proposed deep learning-based automated scan plane positioning shows high efficiency, accuracy and robustness when evaluated on varied clinical head MRI scans with differences in positioning, contrast, noise levels and pathologies.

Truncated Dyrk1A aggravates neuronal apoptosis by inhibiting ASF-mediated Bcl-x exon 2b inclusion.

AIM: Aggravated neuronal loss, caused mainly by neuronal apoptosis, is observed in the brain of patients with Alzheimer's disease (AD) and animal models of AD. A truncated form of Dual-specific and tyrosine phosphorylation-regulated protein kinase 1A (Dyrk1A) plays a vital role in AD pathogenesis. Downregulation of anti-apoptotic Bcl-xL is tightly correlated with neuronal loss in AD. However, the molecular regulation of neuronal apoptosis and Bcl-x expression by Dyrk1A in AD remains largely elusive. Here, we aimed to explore the role and molecular mechanism of Dyrk1A in apoptosis. METHODS: Cell Counting Kit-8 (CCK8), flow cytometry, and TdT-mediated dUTP Nick-End Labeling (TUNEL) were used to check apoptosis. The cells, transfected with Dyrk1A or/and ASF with Bcl-x minigene, were used to assay Bcl-x expression by RT-PCR and Western blots. Co-immunoprecipitation, autoradiography, and immunofluorescence were conducted to check the interaction of ASF and Dyrk1A. Gene set enrichment analysis (GSEA) of apoptosis-related genes was performed in mice overexpressing Dyrk1A (TgDyrk1A) and AD model 5xFAD mice. RESULTS: Dyrk1A promoted Bcl-xS expression and apoptosis. Splicing factor ASF promoted Bcl-x exon 2b inclusion, leading to increased Bcl-xL expression. Dyrk1A suppressed ASF-mediated Bcl-x exon 2b inclusion via phosphorylation. The C-terminus deletion of Dyrk1A facilitated its binding and kinase activity to ASF. Moreover, Dyrk1a1-483 further suppressed the ASF-mediated Bcl-x exon 2b inclusion and aggravated apoptosis. The truncated Dyrk1A, increased Bcl-xS, and enrichment of apoptosis-related genes was observed in the brain of 5xFAD mice. CONCLUSIONS: We speculate that increased Dyrk1A and truncated Dyrk1A may aggravate neuronal apoptosis by decreasing the ratio of Bcl-xL/Bcl-xS via phosphorylating ASF in AD.

Two new compounds from the capitula of Chrysanthemum morifolium cv. Fubaiju.

A new germacrane-type sesquiterpenoid (1) and a new alkamide (2), as well as six known compounds (3-8) were isolated from the capitula of Chrysanthemum morifolium cv. Fubaiju. The new structures were elucidated by comprehensive spectroscopic analysis and quantum chemical calculations. The known structures were characterised via 1D NMR data compared with the already existing literature data. Among the isolates, compound 5 showed inhibitory activity against human lung cancer A549 cells and human hepatoma HepG2 cells with the IC50 values of 19.50 ± 1.23 and 23.24 ± 1.30 µM, respectively, and compound 8 exhibited inhibitory effect on RSV infection with IC50 value of 12.50 ± 1.02 µM.

Quantitative risk assessments of Salmonella spp. in domestic pork in China.

Pork is one of the most commonly consumed meats, and its safety has always been a concern. Recently, safety incidents caused by chemical or biological contamination such as drug residues, heavy metals, and pathogenic microorganisms in pork have been reported, and the safety of pork is a cause for concern. Salmonella spp. is one of the important foodborne pathogens that threaten human health. Pork is a high-risk vector food for Salmonella spp. infection. The assessment of the safety risk of Salmonella spp. in pork is conducive to the prevention of related foodborne diseases. In this paper, risk assessment models for Salmonella spp. in meat were developed. The quantitative risk assessment model for Salmonella spp. based on the pork supply chain showed that the annual number of cases of salmonellosis due to pork consumption in China is approximately 27 per 10,000 males and 24 per 10,000 females. Sensitivity analysis showed that the main factors affecting the risk of Salmonella spp. in pork were the display temperature, display time, and Salmonella spp. contamination concentration in pork at the sale.

Engineering Symmetry-Breaking Centers and d-Orbital Modulation in Triatomic Catalysts for Zinc-Air Batteries.

Unraveling the configuration-activity relationship and synergistic enhancement mechanism (such as real active center, electron spin-state, and d-orbital energy level) for triatomic catalysts, as well as their intrinsically bifunctional oxygen electrocatalysis, is a great challenge. Here we present a triatomic catalyst (TAC) with a trinuclear active structure that displays extraordinary oxygen electrocatalysis for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), greatly outperforming the counterpart of single-atom and diatomic catalysts. The aqueous Zn-air battery (ZAB) equipped with a TAC-based cathode exhibits extraordinary rechargeable stability and ultrarobust cycling performance (1970 h/3940 cycles at 2 mA cm-2, 125 h/250 cycles at 10 mA cm-2 with negligible voltage decay), and the quasi-solid-state ZAB displays outstanding rechargeability and low-temperature adaptability (300 h/1800 cycles at 2 mA cm-2 at -60 °C), outperforming other state-of-the-art ZABs. The experimental and theoretical analyses reveal the symmetry-breaking CoN4 configuration under incorporation of neighboring metal atoms (Fe and Cu), which leads to d-orbital modulation, a low-shift d band center, weakened binding strength to the oxygen intermediates, and decreased energy barrier for bifunctional oxygen electrocatalysis. This rational tricoordination design as well as an in-depth mechanism analysis indicate that hetero-TACs can be promisingly applied in various electrocatalysis applications.