Cu/TiO2 adsorbents modified by air plasma for adsorption-oxidation of H2S.

In this study, non-thermal plasma (NTP) was employed to modify the Cu/TiO2 adsorbent to efficiently purify H2S in low-temperature and micro-oxygen environments. The effects of Cu loading amounts and atmospheres of NTP treatment on the adsorption-oxidation performance of the adsorbents were investigated. The NTP modification successfully boosted the H2S removal capacity to varying degrees, and the optimized adsorbent treated by air plasma (Cu/TiO2-Air) attained the best H2S breakthrough capacity of 113.29 mg H2S/gadsorbent, which was almost 5 times higher than that of the adsorbent without NTP modification. Further studies demonstrated that the superior performance of Cu/TiO2-Air was attributed to increased mesoporous volume, more exposure of active sites (CuO) and functional groups (amino groups and hydroxyl groups), enhanced Ti-O-Cu interaction, and the favorable ratio of active oxygen species. Additionally, the X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) results indicated the main reason for the deactivation was the consumption of the active components (CuO) and the agglomeration of reaction products (CuS and SO42-) occupying the active sites on the surface and the inner pores of the adsorbents.

Nonmetal Doping Modulates Fe Single-Atom Catalysts for Enhancement in Peroxidase Mimicking via Symmetry Disruption, Distortion, and Charge Transfer.

Developing biomimetic catalysts with excellent peroxidase (POD)-like activity has been a long-standing goal for researchers. Doping nonmetallic atoms with different electronegativity to boost the POD-like activity of Fe-N-C single-atom catalysts (SACs) has been successfully realized. However, the introduction of heteroatoms to regulate the coordination environment of the central Fe atom and thus influence the activation of the H2O2 molecule in the POD-like reaction has not been extensively explored. Herein, the effect of different doping sites and numbers of heteroatoms (P, S, B, and N) on the adsorption and activation of H2O2 molecules of Fe-N sites is thoroughly investigated by density functional theory (DFT) calculations. In general, alternation in the catalytic efficiency directly depends on the transfer of electrons and the geometrical shifts near the Fe-N site. First, the symmetry disruption of the Fe-N4 site by P, S, and B doping is beneficial to the activation of H2O2 due to a significant reduction in the adsorption energies. In some cases, without Fe-N4 site disruption, the configurations fail to modulate the adsorption behavior of H2O2. Second, Fe-N-P/S configurations exhibit a stronger affinity for H2O2 molecules due to the significant out-of-plane distortions induced by larger atomic radii of P and S. Moreover, the synergistic effects of Fe and doping atoms P, S, and B with weaker electronegativity than that of N atoms promote electron donation to generated oxygen-containing intermediates, thus facilitating subsequent electron transfer with other substrates. This work demonstrates the critical role of tuning the coordinating environment of Fe-N active centers by heteroatom doping and provides theoretical guidance for controlling the types by breaking the symmetry of SACs to achieve optimal POD-like catalytic activity and selectivity.

Practical and regioselective halonitrooxylation of olefins to access ß-halonitrates.

Organic nitrates, as effective donors of the signaling molecule nitric oxide, are widely applied in the pharmaceutical industry. However, practical and efficient methods for accessing organic nitrates are still scarce, and achieving high regiocontrol in unactivated alkene difunctionalization remains challenging. Here we present a simple and practical method for highly regioselective halonitrooxylation of unactivated alkenes. The approach utilizes TMSX (X: Cl, Br, or I) and oxybis(aryl-λ3-iodanediyl) dinitrates (OAIDN) as sources of halogen and nitrooxy groups, with 0.5 mol % FeCl3 as the catalyst. Remarkably, high regioselectivity in the halonitrooxylation of aromatic alkenes can be achieved even without any catalyst. This protocol features easy scalability and excellent functional group compatibility, providing a range of ß-halonitrates (127 examples, up to 99% yield, up to >20:1 rr). Notably, 2-iodoethyl nitrate, a potent synthon derived from ethylene, reacts smoothly with a variety of functional units to incorporate the nitrooxy group into the desired molecules.

RegionSizeR- A Novel App for Regional Sample Size Planning in MRCTs.

In multi-regional clinical trials, planning the sample size for participating regions is essential for the evaluation of the treatment effect consistency across regions. Based on the MRCT design and sample size allocation to regions, consistency probability is usually used to predict the consistent trend between regions and the overall population, while preserving a certain proportion of the overall treatment effect. Specific enrollment characteristics in a region of interest should also be considered during the time of the sample size planning. To facilitate efficient and harmonized regional sample size planning, we have developed RegionSizeR, a comprehensive and user-friendly interactive web-based R shiny application that can be obtained from https://github.com/rsr-ss/RegionSizeR . This simulation-based app can serve as an initial point for discussions on sample size allocation plans, following preservation of treatment effect method in ICH E17. The app accommodates various types of endpoints and designs, including continuous, binary, and time-to-event endpoints, for superiority, non-inferiority, and MCP-Mod designs. To ensure the validity of this app, independent testing is conducted allowing a discrepancy of no more than 1% across all results considering various scenarios.

PIEZO1 targeting in macrophages boosts phagocytic activity and foam cell apoptosis in atherosclerosis.

The rising incidences of atherosclerosis have necessitated efforts to identify novel targets for therapeutic interventions. In the present study, we observed increased expression of the mechanosensitive calcium channel Piezo1 transcript in mouse and human atherosclerotic plaques, correlating with infiltration of PIEZO1-expressing macrophages. In vitro administration of Yoda1, a specific agonist for PIEZO1, led to increased foam cell apoptosis and enhanced phagocytosis by macrophages. Mechanistically, PIEZO1 activation resulted in intracellular F-actin rearrangement, elevated mitochondrial ROS levels and induction of mitochondrial fragmentation upon PIEZO1 activation, as well as increased expression of anti-inflammatory genes. In vivo, ApoE-/- mice treated with Yoda1 exhibited regression of atherosclerosis, enhanced stability of advanced lesions, reduced plaque size and necrotic core, increased collagen content, and reduced expression levels of inflammatory markers. Our findings propose PIEZO1 as a novel and potential therapeutic target in atherosclerosis.

Design Strategies for High-Performance NH3-SCO Catalysts: Identifying and Modulating Direct Anchoring Sites for Ag on TiO2.

Ammonia (NH3) slip from diesel vehicle aftertreatment systems and internal combustion engines fueled by NH3 or NH3/H2 poses serious environmental problems. Ag-based catalysts are widely used for the selective catalytic oxidation of NH3 to N2 (NH3-SCO), and their performance is greatly dependent on the state of Ag, which is influenced by the anchoring sites on the support. Despite efforts to identify the direct anchoring sites of metal atoms on TiO2, conflicting views persist. Here, we compared the correlation between Ag dispersion and the content of hydroxyl (OH) groups or defects on TiO2 and conducted density functional theory (DFT) calculations, and the results confirmed that the surface OH groups of TiO2 serve as the direct anchoring sites for Ag. By modulating the OH group content through thermal induction, the optimal OH group content on TiO2-800 resulted in more metallic Ag nanoparticles (Ag0 NPs) in larger sizes, leading to the development of an excellent NH3-SCO catalyst. Moreover, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), kinetic studies, and DFT calculations suggested that more Ag0 NPs in larger sizes on 10Ag/TiO2-800 were conducive to O2 activation and NH3 dissociation. Our findings provide new insights for designing efficient NH3-SCO catalysts, and OH groups as direct anchoring sites could be extended to other metals and supports for the rational design of catalysts.

Controlled interconversion of macrocyclic atropisomers via defined intermediates.

Macrocyclic conformations play a crucial role in regulating their properties. Our understanding of the determinants to control macrocyclic conformation interconversion is still in its infancy. Here we present a macrocycle, octamethyl cyclo[4](1,3-(4,6)-dimethylbenzene)[4]((4,6-benzene)(1,3-dicarboxylate) (OC-4), that can exist at 298 K as two stable atropisomers with C2v and C4v symmetry denoted as C2v-OC-4 and C4v-OC-4, respectively. Heating induces the efficient stepwise conversion of C2v- to C4v-OC-4 via a Cs-symmetric intermediate (Cs-OC-4). It differs from the typical transition state-mediated processes of simple C-C single bond rotations. Hydrolysis and further esterification with a countercation dependence promote the generation of C2v- and Cs-OC-4 from C4v-OC-4. In contrast to C2v-OC-4, C4v-OC-4 can bind linear guests to form pseudo-rotaxans, or bind C60 or C70 efficiently. The present study highlights the differences in recognition behavior that can result from conformational interconversion, as well as providing insights into the basic parameters that govern coupled molecular rotations.

A Bayesian bias-adjusted random-effects model for synthesizing evidence from randomized controlled trials and nonrandomized studies of interventions.

OBJECTIVE: An important consideration when combining RCTs and NRSIs is how to address their potential biases in the pooled estimates. This study aimed to propose a Bayesian bias-adjusted random effects model for the synthesis of evidence from RCTs and NRSIs. METHODS: We present a Bayesian bias-adjusted random effects model based on power prior method, which combines the likelihood contribution of the NRSIs, raised to the power parameter of alpha, with the likelihood of the RCT data, modeled with an additive bias. The method was illustrated using a meta-analysis on the association between low-dose methotrexate exposure and melanoma. We also combined RCTs and NRSIs using the naïve data synthesis. RESULTS: The results including only RCTs has a posterior median and 95% credible interval (CrI) of 1.18 (0.31-4.04), the posterior probability of any harm (> 1.0) and a meaningful association (> 1.15) were 0.61 and 0.52, respectively. The posterior median and 95% CrI based on the naïve data synthesis resulted in 1.17 (0.96-1.47), and the posterior probability of any harm and a meaningful association were 0.96 and 0.60, respectively. For the Bayesian bias-adjusted analysis, the median OR was 1.16 (95% CrI: 0.83-1.71), and the posterior probabilities of any and a meaningful clinical association were 0.88 and 0.53, respectively. CONCLUSIONS: The results indicated that integrating NRSIs into meta-analysis could increase the certainty of the body of evidence. However, directly combining RCTs and NRSIs in the same meta-analysis without distinction may lead to misleading conclusions.

Nitrite-oxidizing bacteria adapted to low oxygen conditions dominate nitrite oxidation in marine oxygen minimum zones.

Nitrite is a central molecule in the nitrogen cycle because nitrite oxidation to nitrate (an aerobic process) retains fixed nitrogen in a system and its reduction to dinitrogen gas (anaerobic) reduces the fixed nitrogen inventory. Despite its acknowledged requirement for oxygen, nitrite oxidation is observed in oxygen-depleted layers of the ocean's oxygen minimum zones (OMZs), challenging the current understanding of OMZ nitrogen cycling. Previous attempts to determine whether nitrite-oxidizing bacteria in the anoxic layer differ from known nitrite oxidizers in the open ocean were limited by cultivation difficulties and sequencing depth. Here, we construct 31 draft genomes of nitrite-oxidizing bacteria from global OMZs. The distribution of nitrite oxidation rates, abundance and expression of nitrite oxidoreductase genes, and relative abundance of nitrite-oxidizing bacterial draft genomes from the same samples all show peaks in the core of the oxygen-depleted zone (ODZ) and are all highly correlated in depth profiles within the major ocean oxygen minimum zones. The ODZ nitrite oxidizers are not found in the Tara Oceans global dataset (the most complete oxic ocean dataset), and the major nitrite oxidizers found in the oxygenated ocean do not occur in ODZ waters. A pangenomic analysis shows the ODZ nitrite oxidizers have distinct gene clusters compared to oxic nitrite oxidizers and are microaerophilic. These findings all indicate the existence of nitrite oxidizers whose niche is oxygen-deficient seawater. Thus, specialist nitrite-oxidizing bacteria are responsible for fixed nitrogen retention in marine oxygen minimum zones, with implications for control of the ocean's fixed nitrogen inventory.

Guidance of development, validation, and evaluation of algorithms for populating health status in observational studies of routinely collected data (DEVELOP-RCD).

BACKGROUND: In recent years, there has been a growing trend in the utilization of observational studies that make use of routinely collected healthcare data (RCD). These studies rely on algorithms to identify specific health conditions (e.g. diabetes or sepsis) for statistical analyses. However, there has been substantial variation in the algorithm development and validation, leading to frequently suboptimal performance and posing a significant threat to the validity of study findings. Unfortunately, these issues are often overlooked. METHODS: We systematically developed guidance for the development, validation, and evaluation of algorithms designed to identify health status (DEVELOP-RCD). Our initial efforts involved conducting both a narrative review and a systematic review of published studies on the concepts and methodological issues related to algorithm development, validation, and evaluation. Subsequently, we conducted an empirical study on an algorithm for identifying sepsis. Based on these findings, we formulated specific workflow and recommendations for algorithm development, validation, and evaluation within the guidance. Finally, the guidance underwent independent review by a panel of 20 external experts who then convened a consensus meeting to finalize it. RESULTS: A standardized workflow for algorithm development, validation, and evaluation was established. Guided by specific health status considerations, the workflow comprises four integrated steps: assessing an existing algorithm's suitability for the target health status; developing a new algorithm using recommended methods; validating the algorithm using prescribed performance measures; and evaluating the impact of the algorithm on study results. Additionally, 13 good practice recommendations were formulated with detailed explanations. Furthermore, a practical study on sepsis identification was included to demonstrate the application of this guidance. CONCLUSIONS: The establishment of guidance is intended to aid researchers and clinicians in the appropriate and accurate development and application of algorithms for identifying health status from RCD. This guidance has the potential to enhance the credibility of findings from observational studies involving RCD.

A robust ensemble deep learning framework for accurate diagnoses of tuberculosis from chest radiographs.

Introduction: Tuberculosis (TB) stands as a paramount global health concern, contributing significantly to worldwide mortality rates. Effective containment of TB requires deployment of cost-efficient screening method with limited resources. To enhance the precision of resource allocation in the global fight against TB, this research proposed chest X-ray radiography (CXR) based machine learning screening algorithms with optimization, benchmarking and tuning for the best TB subclassification tasks for clinical application. Methods: This investigation delves into the development and evaluation of a robust ensemble deep learning framework, comprising 43 distinct models, tailored for the identification of active TB cases and the categorization of their clinical subtypes. The proposed framework is essentially an ensemble model with multiple feature extractors and one of three fusion strategies-voting, attention-based, or concatenation methods-in the fusion stage before a final classification. The comprised de-identified dataset contains records of 915 active TB patients alongside 1,276 healthy controls with subtype-specific information. Thus, the realizations of our framework are capable for diagnosis with subclass identification. The subclass tags include: secondary tuberculosis/tuberculous pleurisy; non-cavity/cavity; secondary tuberculosis only/secondary tuberculosis and tuberculous pleurisy; tuberculous pleurisy only/secondary tuberculosis and tuberculous pleurisy. Results: Based on the dataset and model selection and tuning, ensemble models show their capability with self-correction capability of subclass identification with rendering robust clinical predictions. The best double-CNN-extractor model with concatenation/attention fusion strategies may potentially be the successful model for subclass tasks in real application. With visualization techniques, in-depth analysis of the ensemble model's performance across different fusion strategies are verified. Discussion: The findings underscore the potential of such ensemble approaches in augmenting TB diagnostics with subclassification. Even with limited dataset, the self-correction within the ensemble models still guarantees the accuracies to some level for potential clinical decision-making processes in TB management. Ultimately, this study shows a direction for better TB screening in the future TB response strategy.

A novel peptide encoded by circ-SLC9A6 promotes lipid dyshomeostasis through the regulation of H4K16ac-mediated CD36 transcription in NAFLD.

BACKGROUND: As the leading cause of end-stage liver disease, nonalcoholic fatty liver disease (NAFLD) is mainly induced by lipid dyshomeostasis. The translation of endogenous circular RNAs (circRNAs) is closely related to the progression of various diseases, but the involvement of circRNAs in NAFLD has not been determined. METHODS: Combined high-throughput circRNA profiles were used to identify circRNAs with translational potential. The underlying molecular mechanisms were investigated by RNA sequencing, pull-down/MS and site-specific mutagenesis. RESULTS: In this study, we focused on circ-SLC9A6, an abnormally highly expressed circRNA in human and mouse liver tissue during NAFLD development that exacerbates metabolic dyshomeostasis in hepatocytes by encoding a novel peptide called SLC9A6-126aa in vivo and in vitro. YTHDF2-mediated degradation of m6A-modified circ-SLC9A6 was found to be essential for the regulation of SLC9A6-126aa expression. We further found that the phosphorylation of SLC9A6-126aa by AKT was crucial for its cytoplasmic localization and the maintenance of physiological homeostasis, whereas high-fat stress induced substantial translocation of unphosphorylated SLC9A6-126aa to the nucleus, resulting in a vicious cycle of lipid metabolic dysfunction. Nuclear SLC9A6-126aa promotes transcriptional activation of the target gene CD36 and enhances its occupancy of the CD36 promoter locus by regulating MOF-mediated histone H4K16 acetylation. Hepatic CD36 depletion significantly ameliorated hyperactivated MAPK signalling and lipid disturbance in SLC9A6-126aa transgenic mice. Clinically, increasing levels of SLC9A6-126aa were observed during NAFLD progression and were found to be positively correlated with the CD36 and MAPK cascades. CONCLUSION: This study revealed the role of circ-SLC9A6-derived SLC9A6-126aa in the epigenetic modification-mediated regulation of lipid metabolism. Our findings may provide promising therapeutic targets for NAFLD and new insights into the pathological mechanisms of metabolic diseases. HIGHLIGHTS: Under normal circumstances, driven by m6A modification, YTHDF2 directly recognizes and degrades circ-SLC9A6, thereby inhibiting the translation of SLC9A6-126aa. Additionally, AKT1 phosphorylates and inhibits the nuclear translocation of SLC9A6-126aa. In NAFLD, lipid overload leads to YTHDF2 and AKT1 deficiency, ultimately increasing the expression and nuclear import of SLC9A6-126aa. Nuclear SLC9A6-126aa binds directly to the CD36 promoter and initiates CD36 transcription, which induces lipid dyshomeostasis.

Catalpol attenuates hepatic glucose metabolism disorder and oxidative stress in triptolide-induced liver injury by regulating the SIRT1/HIF-1α pathway.

Triptolide (TP), known for its effectiveness in treating various rheumatoid diseases, is also associated with significant hepatotoxicity risks. This study explored Catalpol (CAT), an iridoid glycoside with antioxidative and anti-inflammatory effects, as a potential defense against TP-induced liver damage. In vivo and in vitro models of liver injury were established using TP in combination with different concentrations of CAT. Metabolomics analyses were conducted to assess energy metabolism in mouse livers. Additionally, a Seahorse XF Analyzer was employed to measure glycolysis rate, mitochondrial respiratory functionality, and real-time ATP generation rate in AML12 cells. The study also examined the expression of proteins related to glycogenolysis and gluconeogenesis. Using both in vitro SIRT1 knockout/overexpression and in vivo liver-specific SIRT1 knockout models, we confirmed SIRT1 as a mechanism of action for CAT. Our findings revealed that CAT could alleviate TP-induced liver injury by activating SIRT1, which inhibited lysine acetylation of hypoxia-inducible factor-1α (HIF-1α), thereby restoring the balance between glycolysis and oxidative phosphorylation. This action improved mitochondrial dysfunction and reduced glucose metabolism disorder and oxidative stress caused by TP. Taken together, these insights unveil a hitherto undocumented mechanism by which CAT ameliorates TP-induced liver injury, positioning it as a potential therapeutic agent for managing TP-induced hepatotoxicity.

Ischemic core volume is associated with hemorrhagic transformation post endovascular thrombectomy.

INTRODUCTION: Symtomatic hemorrhagic transformation(sHT) was defined as any intracerebral hemorrhage that combined with clinical deterioration. While recent studies showed low rates of sHT in large core ischemic strokes treated with endovascular thrombectomy (EVT), the specific impact of core size on overall hemorrhagic transformation (HT) remains unclear. We aim to investigate the relationship between ischemic core size and development of HT post thrombectomy. METHODS: This prospective study enrolled acute ischemic stroke (AIS) patients with anterior large vessel occlusion undergoing EVT who had baseline MRI from 2017-2019. Pre-EVT Arterial Spin Labeling (ASL) and Diffusion-Weighted Imaging (DWI) scans were performed for volume calculations. Primary outcome was HT assessed within 72 hours post EVT. Multivariable logistic regression was used to analyze the associations between baseline DWI and ASL volumes and HT occurrence. Discriminative ability for HT was compared using receiver operating curve analysis (c-statistic). RESULTS: We included 101 patients (median age: 64 [IQR 56-74] years, baseline NIHSS 13 [IQR 9-16]). Median DWI and ASL volume were 21.0 ml [IQR 8.3-47.2] and 105ml [59.5-172.9], respectively. 36.8% recieved intravenous thrombolysis before EVT. HT occurred in 36.6% of patients, including 16.8% with sHT. Baseline DWI volume was independently associated with HT (OR=1.030, 95% CI 1.008 to 1.053, P=0.009), while ASL volume wasn't statistically significant(P=0.330). The DWI model was superior to ASL model in predicting HT within 72 hours (c-statistic, 0.787).Neither DWI (P=0.149) nor ASL volume (P=0.834) effectively indicated sHT. CONCLUSIONS: DWI-based ischemic core volume correlates significantly with HT within 72 hours post successful thrombectomy. This highlights the potential clinical utility of DWI in guiding treatment decisions for this population.

Polycyclic aromatic hydrocarbon and its adducts in peripheral blood: Gene and environment interaction among Chinese population.

BACKGROUND: Benzo(a)pyrene (B[a]P) is the most widely concerned polycyclic aromatic hydrocarbons (PAHs), which metabolizes benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide (BPDE) in vivo to produce carcinogenic effect on the body. Currently, there is limited research on the role of the variation of metabolic enzymes in this process. METHODS: We carried out a study including 752 participants, measured the concentrations of 16 kinds PAHs in both particle and gaseous phases, urinary PAHs metabolites, leukocyte BPDE-DNA adduct and serum BPDE- Albumin (BPDE-Alb) adduct, and calculated daily intake dose (DID) to assess the cumulative exposure of PAHs. We conducted single nucleotide polymorphism sites (SNPs) of metabolic enzymes, explored the exposure-response relationship between the levels of exposure and BPDE adducts using multiple linear regression models. RESULT: Our results indicated that an interquartile range (IQR) increase in B[a]P, PAHs, BaPeq, 1-hydroxypyrene (1-OHP), 1-hydroxynaphthalene (1-OHNap) and 2-hydroxynaphthalene (2-OHNap) were associated with 26.53 %, 24.24 %, 28.15 %, 39.15 %, 12.85 % and 14.09 % increase in leukocyte BPDE-DNA adduct (all P < 0.05). However, there was no significant correlation between exposure with serum BPDE-Alb adduct (P > 0.05). Besides, we also found the polymorphism of CYP1A1(Gly45Asp), CYP2C9 (Ile359Leu), and UGT1A1(downstream) may affect BPDE adducts level. CONCLUSION: Our results indicated that leukocyte BPDE-DNA adduct could better reflect the exposure to PAHs. Furthermore, the polymorphism of CYP1A1, CYP2C9 and UGT1A1affected the content of BPDE adducts.

Turning Waste into Treasure: Invasive Plant Ambrosia trifida L Leaves as a High-Efficiency Inhibitor for Steel in Simulated Pickling Solutions.

High toxicity is the main reason for the limited application of traditional corrosion inhibitors. Herein, it is critical to find a green, efficient, and long-term stable alternative substitute for the hazardous and conventional corrosion inhibitor. Ambrosia trifida L is widely distributed in fields and riverside wetlands as an invasive plant in China. According to the concept of turning waste into treasure, the extract of Ambrosia trifida L leaves (ATL) has the potential to address this issue due to its natural origin and abundant presence of heterocyclic organics. Therefore, ATL, as a green corrosion inhibitor, is prepared for the first time via a simple water-based extraction method. FT-IR (Fourier transform infrared spectroscopy) and UV-Vis (UV-visible) indicate that ATL extract contains abundant heterocyclic organics with conjugated structures, which exhibit the potential to become a high-efficiency inhibitor. Notably, the active sites of ATL molecules and their interaction with Q235 steel at the molecular/atomic level are revealed via theoretical calculations. The highest Ebinding value observed for the major components in the ATL extract is 259.66 kcal/mol, implying a significant adsorption capacity. The electrochemical results verify that microdose ATL extract can prominently inhibit steel corrosion, and the highest inhibition efficiency (η) is 97.5% (1000 mg/L). Following immersion for 24 h, the η value is enhanced to 99.0%, indicating a reliable and long-term ATL extract protection film is formed on the steel surface in harsh acidic solutions. The results of the weight loss, SEM (scanning electron microscope), and LSCM (laser scanning confocal microscopy) are consistent with the above conclusions. Finally, this study anticipates providing theoretical support for developing novel green plant extract inhibitors and aiding in their application in industrial pickling environments.

Modulation of Interlayer Nanochannels via the Moderate Heat Treatment of Graphene Oxide Membranes.

In response to the phenomenon of interlayer transport channel swelling caused by the hydration of oxygen-containing functional groups on the GO membrane surface, a moderate heat treatment method was employed to controllably reduce the graphene oxide (GO) membrane and prepare a reduced GO composite nanofiltration membrane (mixed cellulose membrane (MCE)/ethylenediamine (EDA)/reduced GO-X (RGO-X)). The associations of different heat treatment temperatures with the hydrophilicity, interlayer structure, permeability and dye/salt rejection properties of GO membranes were systematically explored. The results indicated that the oxygen-containing groups of the GO membrane were partially eliminated after heat treatment, and the hydrophilicity was weakened. This effectively weakened the hydration between the GO membrane and the water molecules and inhibited the swelling of the oxidized graphene membrane. In the dye desalination test, the MCE/EDA/RGO membrane exhibited an ultra-high rejection rate of over 97% for methylene blue (MB) dye molecules. In addition, heat treatment increased the structural defects of the GO membrane and promoted the fast passage of water molecules via the membrane. In pure water flux testing, the water flux of the membrane remained above 46.58 Lm-2h-1bar-1, while the salt rejection rate was relatively low.

The preventative effects of Lactococcus Lactis metabolites against LPS-induced sepsis.

Introduction: Sepsis is a syndrome of organ dysfunction caused by a dysregulated host response to infection and septic shock. Currently, antibiotic therapy is the standard treatment for sepsis, but it can lead to drug resistance. The disturbance of the gut microbiota which is affected by sepsis could lead to the development of organ failure. It is reported that probiotics could shape the gut microbiota, potentially controlling a variety of intestinal diseases and promoting whole-body health. Methods: In this study, we evaluated the preventive effects of intra- and extracellular products of probiotics on sepsis. The extracellular products of Lactococcus lactis (L. lactis) were identified through the in vivo cell experiments. The preventive effect and mechanism of L. lactis extracellular products on mouse sepsis were further explored through HE staining, mouse survival rate measurement, chip analysis, etc. Results: L. lactis extracellular products increase cell survival and significantly reduce inflammatory factors secreted in a cellular sepsis model. In in vivo experiments in mice, our samples attenuated sepsis-induced pulmonary edema and inflammatory infiltrates in the lungs of mice, and reduced mortality and inflammatory factor levels within the serum of mice. Finally, the mechanism of sepsis prevention by lactic acid bacteria is suggested. Extracellular products of L. lactis could effectively prevent sepsis episodes. Discussion: In animal experiments, we reported that extracellular products of L. lactis can effectively prevent sepsis, and preliminarily discussed the pathological mechanism, which provides more ideas for the prevention of sepsis. In the future, probiotics may be considered a new way to prevent sepsis.