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Background: Time elapsed from stroke onset and baseline infarct volume is influential on endovascular thrombectomy (EVT) outcomes. Objectives: This study aimed to explore the utility of early infarct growth rate (EIGR) measured by apparent diffusion coefficient (ADC) in predicting symptomatic intracranial hemorrhage (sICH) of ischemic stroke patients after EVT. Methods: We retrospectively analyzed patients from the prospectively maintained stroke registry admitted between January 2019 and March 2023, presenting with large vessel occlusive stroke in the anterior circulation. EIGR was defined as ischemic core volume on magnetic resonance perfusion imaging (ADC ⩽620 × 10 −6 mm 2 /s) divided by the time from stroke onset to imaging. sICH was diagnosed according to the Heidelberg Bleeding Classification within 72 h after the procedure. Results: A total of 315 patients met the inclusion criteria. We observed sICH in 36 (11.4%) patients. After adjusting for the potential confounders, increased EIGR was confirmed to be independently associated with a higher risk of sICH (adjusted odds ratio, 1.033; 95% confidence interval (CI), 1.018–1.048; p = 0.001). Similar results were also confirmed when EIGR was analyzed as a categorical variable. Using a logistic regression model with restricted cubic splines, we found a linear correlation between EIGR and sICH risk ( p = 0.001 for linearity). Furthermore, adding EIGR to a model containing conventional risk factors significantly improved risk reclassification for sICH (category-free net reclassification index, 0.393; 95% CI, 0.227–0.560; p = 0.001; integrated discrimination improvement, 0.245; 95% CI, 0.146–0.343; p = 0.001). Conclusion: Increased EIGR may predict the sICH in ischemic stroke patients who receiving EVT.

Refueling decisions of liner ships are facing challenges from both fuel price fluctuations and carbon emission constraints. This paper proposes a multistage stochastic programming model to tackle the refueling problem for dual-fuel ships under carbon intensity indicator (CII) rating limit and carbon tax costs. The model also takes into account various factors, including fuel consumption of main and auxiliary engines, fuel availability at ports of call, and fuel price fluctuations. The proposed model is solved using scenario size selection and moment matching methods, and a greedy heuristic algorithm is adopted to speed up the process. Managerial insights are obtained from multinomial logistic regression and sensitivity analyses. Our numerical results reveal that low sulfur fuel oil (LSFO) refueling decisions are closely linked to the difference of LSFO and liquefied natural gas (LNG) fuel prices and that LSFO becomes more attractive when the variance of LSFO fuel price or the LNG availability decreases. Besides, carbon emission costs are found to become a true consideration when carbon taxes exceed a certain threshold. These insights can help practitioners better understand the coupling influence of carbon emissions and fuel price fluctuations on the ship refueling problem.

Ships are traditionally powered by fossil fuels such as heavy fuel oil (HFO) and marine diesel oil (MDO), where the emissions, such as particulates, hydrocarbons (HC), carbon monoxide (CO), nitrogen oxides (NOX) and carbon dioxide (CO2), negatively affect the environment and human health. The International Maritime Organization (IMO) encourages shipping companies to use liquefied natural gas (LNG), which is a green fuel source to power shipping activities and is easy to store, to replace traditional marine fuels. There are three common methods of LNG bunkering: ship-to-ship, truck-to-ship, and port-to-ship. The objective of this study is to determine the optimal bunkering method at a port using an integer linear programming (ILP) model considering three kinds of costs: fixed, variable, and extra. To find the optimal bunkering method, the three methods and their related constraints are modeled into the ILP model. The results indicate that ship-to-ship is the optimal bunkering method for LNG under the scenario of the port considered. Numerical experiments are conducted to validate model performance and generate managerial insights.

Surface shortwave radiation (SSR) plays an important role in global energy systems. The new generation of geostationary meteorological satellite Himawari-8, with higher spatiotemporal and spectral resolution, offers a new opportunity to retrieve SSR with higher accuracy. In this study, an improved algorithm was applied to estimate instantaneous, hourly, and daily mean SSR using cloud products from the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite. The validation against Baseline Surface Radiation Network (BSRN) stations showed a root mean square error (RMSE) of 95.8 W m−2 for instantaneous SSR, 82.4 W m−2 for hourly SSR, and 22.8 W m−2 for daily SSR and mean bias error (MBE) of −15.8 W m−2, −14.1 W m−2, and −6.6 W m−2. The validation against China Meteorological Administration (CMA) stations showed a RMSE of 99.5 W m−2 and MBE of −8.2 W m−2 for hourly SSR and RMSE of 27.7 W m−2 and MBE of −3.9 W m−2 for daily SSR, which are generally better than the Himawari-8 SSR product. Overall, the improved algorithm performed well on the new-generation geostationary satellite, with high accuracy and efficiency, and would contribute to surface process research and photovoltaic engineering applications.

Double-layer heat tubes have been designed to effectively reduce the occurrence of heat pipe rupture accidents. However, inter-tube thermal contact resistance can decrease heat transfer efficiency, thus hampering the heat dissipation in the primary loop system of lead-bismuth reactors. Therefore, optimizing the design of double-layer heat tubes is necessary. This work focuses on the double-layer heat exchanger of a lead-bismuth reactor and utilizes gallium-based graphene nanofluids as a thermal interface material to fill the gap between the heat tubes. Furthermore, the impact of the length, wall thickness, outer diameter, and spacing of heat tubes on the heat transfer performance of the double-layer heat exchanger with and without the nanofluids has been analyzed. The study aims to optimize the JF factor and cost-effectiveness ratio (CER). Genetic algorithms are employed to optimize and evaluate the heat transfer performance of the main heat exchanger based on the four aforementioned parameters. Consequently, a new design scheme is obtained for the double-layer heat exchanger, which increases the optimized overall heat transfer coefficient of the main heat exchanger by 5.79%, pressure drop in the primary loop by 2.32%, JF factor by 5%, and CER by 24.62%. These results demonstrate that the gallium-based graphene nanofluids can effectively enhance the heat transfer performance of the double-layer heat exchanger while reducing the likelihood of steam generator tube rupture accidents.

A rising volume of vessel traffic increases navigation density, which leads to an increasing risk of vessel collisions in navigation channels. Navigation safety issues have been widely studied with the aim of reducing such collisions. Intelligent navigation channels, which involve deploying remote-sensing radars on buoys, are an effective method of tackling vessel collisions. This paper investigates the problem of radar deployment in navigation channels, aiming to expand the radar coverage area and effectively detect vessel locations. A mixed-integer linear programming model is formulated to determine the optimal deployment of radars in navigation channels under a given budget, where radars with different coverage radii and different types of buoys are introduced. Then, sensitivity analyses involving the impacts of budgets, the coverage radii of the radars, the distance between adjacent discrete locations, and the distribution of the existing buoys on the radar deployment plan are conducted. The computational results indicate that the coverage ratio of the navigation channel can be improved by reasonably deploying the different types of radars on the existing and new buoys under a given budget.

With the rising environmental consciousness, emission pollution has become one of the major concerns of the maritime industry, which is the artery of international trade. To handle the significant cost increase resulting from stringent emission regulations, ship operators have adopted multiple methods, including operational and technical methods. Scrubbers are a mature and effective technology that can reduce sulfur dioxide and particulate matter emissions by cleaning the exhaust gases before emitting them. However, the existing literature regarding the operation of scrubbers does not consider the prohibition of open scrubber usage in the vicinity of certain ports or the variable costs of using scrubbers. Therefore, this study explores the fleet scrubber installation and utilization problem, considering sulfur emission control areas, marine fuel switching, and open-scrubber-prohibited areas. A mixed-integer nonlinear model was developed to formulate and address the problem. Numerical experiments and sensitive analyses based on practical data were conducted to validate the originally proposed model and show the effectiveness of this technology under various scenarios. The results indicated that the operational cost was effectively reduced by using scrubbers, compared to not using them. Additionally, the disparity between total costs with and without scrubbers was significant, regardless of the sailing speed and proportion of the regulation areas. It was also proven that spreading the scrubber installation work over several years will relieve financial pressures due to scrubber investment and thus obtain a better installation plan.

Ferry shipping is an indispensable method of public transportation, especially in areas with well-developed river systems or coastal areas. The increasing demand for transport requires additional visits and introduces the problem of ship visit schedule engineering at ferry terminals with stochastic servicing time. In this paper, we propose a ferry visit planning problem to maximize the total profit, in which the berthing time, berthing location, and servicing time for each ferry visit are optimized. Then, a mixed-integer nonlinear programming model is proposed to formulate the focal problem. We propose a tailored solution method to convert the mixed-integer nonlinear programming model to a mixed-integer linear programming model. We further devise an inserting algorithm to test the performance of our model. A comparison between the results of the basic instance yielded by our model and those of the inserting algorithm validates our model and solution method. We then conduct sensitivity analyses of the impacts of different numbers of existing ferry visits and added ferry visits, different expectations of the real time taken by all the ferry visits, and different distribution patterns of existing ferry visits, to further validate the performance of our model.

Liquefied natural gas (LNG) is a promising measure to reduce shipping emissions and alleviate air pollution problem, especially in coastal areas. Currently, the lack of a complete infrastructure system is preventing the extensive application of dual-fueled ships that are mainly LNG-powered. Given that groups of LNG bunkering stations are under establishment in various countries and areas, the construction plan becomes critical. In this paper, we focus on the LNG bunkering station deployment problem, which identifies the locations of the stations to be built. A large-scale case study of China’s container shipping network was conducted. The problem scale of this case paper exceeds those in previous academic studies. Thus, this study better validates the model and solution method proposed than numerical experiments that are randomly generated. Sensitive analyses on the LNG price, bunkering station construction costs, and total budget were carried out. The results yielded provide practical suggestions and managerial insights for the competent department. In addition to building a complete bunkering system, subsidies to ship operators for consuming LNG and higher production efficiency in bunkering station construction also help promote the application of LNG as marine fuel.

Ship air emissions are recognized as one of the key concerns of the maritime industry. Competent authorities have issued various regulations to manage air emissions from ships. Although the authorities are policy makers, the effectiveness of policies is up to the shipping industry who operates the vessels and terminals to fulfill maritime transportation works. Given this characteristic, bi-level optimization model has been widely adopted in studies that optimize policy design or evaluate its effectiveness. The framework of a typical bi-level optimization model for ship emission management problem is given to show the basic structure of similar issues. A series of applications of bi-level optimization model in managing ship emissions is reviewed, including cases of Energy Efficiency Design Index, Emissions Control Area, Market Based Measure, Carbon Intensity Indicator, and Vessel Speed Reduction Incentive Program. We hope this paper can enlighten scholars interested in this area and provide help for them.

The 76th session of the Marine Environment Committee (MEPC 76) of the International Maritime Organization adopted several mandatory measures in June 2021 to reduce carbon emissions from ships. One of the measures is the carbon intensity indicator (CII), which is the carbon emissions per unit transport work for each ship. Several options of CIIs are available and none of them is chosen to be applied yet. We prove that, at least in theory, requiring the attained annual CII of a ship to be less than a reference value, no matter which CII option is applied, may increase its carbon emissions. Therefore, more elaborate models, combined with real data, should be developed to analyze the effectiveness of each CII option and possibly to design a new CII.

BackgroundMismatch repair proficient colorectal cancer (pMMR CRC) lacks effective treatments and has a poor prognosis, which can be attributed to the complexity of tumor microenvironment. The coordinated function of immune cells is vital to anti-tumor immunity. However, the spatial characteristics of immune cells in the pMMR CRC immune microenvironment and their relationship with clinical prognosis are not fully understood. Meanwhile, the immune modulatory effect of neoadjuvant chemotherapy (NCT), which is the first-line treatment of pMMR CRC, needs further investigation. Therefore, this study aims to explore the spatial dynamics of immune cells and its prognostic value in pMMR CRC.MethodsWe analyzed the various immune cells in formalin-fixed, paraffin-embedded tumor tissues which were collected from 77 patients with stage II/III of pMMR CRC, including 39 non-NCT treated and 38 NCT treated patients. We used the optimized multiplex immunohistochemistry (mIHC) to identify and quantify the density, type and location of immune cells in pMMR CRC. Multivariate survival analysis was performed to assess the relationship of immune profiles and clinical prognosis of pMMR CRC patients.ResultsThe densities of most T cell subsets, B cells and macrophages were higher in the central region of the pMMR CRC than in the invasion margin. Tumor infiltrating lymphocytes (TILs), especially the infiltration of CD4+ GzmB+ T cells in the central region of the tumor was identified to be positively correlated with the prognosis of the patients. Multivariate analysis confirmed that CD4+ GzmB+ T cells population was an independent predictor of disease-free survival (DFS) in non-NCT group. Meanwhile, NCT enhanced the infiltration of CD4+ GzmB+ T cells in the central region of the pMMR CRC, which was also identified as an independent protective factor of overall survival (OS) and DFS in NCT group.ConclusionWe demonstrated that the level of CD4+ GzmB+ T cells located in the center of tumor could provide great prognostic value for pMMR CRC patients. And the application of neoadjuvant chemotherapy further improves the infiltration of CD4+ GzmB+ T cells in the central compartment. Further studies into the application of CD4+ GzmB+ T cells in tumor immunotherapy are needed.

Due to the gradual increase in maritime cargo volume, exhaust fumes from the maritime industry have become a concern of various sectors of society. In particular, because of their proximity to human habitation, emissions from docked ships are a serious health hazard. Shore power, as a promising approach to reducing ship emissions in port areas, has drawn attention from governments, industries, and academia. This paper reviews studies of shore power's economic challenges from the perspective of ship owners, port authorities, and governments. The basic models roughly summarize the costs of shore power for different interested parties. In addition, some technical reports and governmental studies of shore power are reviewed. This paper provides scholars interested in this area with a systematic review of current research on shore power. Research opportunities that are worth investigating and the potential forces driving the popularization of shore power are identified. We hope that the review helps to increase research on this topic.

Abstract Background The latest evidence on health literacy in China revealed that only 8% of individuals aged 65–69 years, a segment of the geriatric population, possess adequate health literacy levels, indicating a low level in China. Studies have demonstrated that improving the organizational health literacy of healthcare institutions is a crucial approach to addressing low health literacy among older patients. Objective To explore the obstacles hindering the advancement of organizational health literacy in healthcare institutions in meeting the needs of older patients. Design A mixed-methods approach was employed to investigate both the status and barriers to the establishment of organizational health literacy within two healthcare institutions. Participants Participants included older individuals aged over 60, clinical staff, and managerial personnel from these two health institutions. Methods This research utilized the social-ecological model as its theoretical foundation and utilized a mixed-methods approach to examine the current status and challenges in developing organizational health literacy within healthcare institutions. Initially, a survey using a questionnaire (n = 178) was conducted among older patients to evaluate the establishment of organizational health literacy from their perspective. Following this, interviews (n = 22) were carried out with administrators, clinical personnel, and elderly patients to identify the barriers hindering the development of organizational health literacy within healthcare institutions. Results Quantitative research indicates that health institutions have been less accommodating to the requirements of older patients, with health information dissemination and communication emerging as the weakest areas. Qualitative investigations revealed three key influencing factors: patient-related factors, including physiological and cognitive decline, as well as low educational attainment among older patients; organizational factors, including inadequate clinical staff numbers, deficient long-term systematic training, and a digital divide resulting from health institutions’ digital advancements; and policy-related factors indicating a lack of regulations governing the establishment of organizational health literacy within healthcare institutions. Conclusion The two most vulnerable aspects of OHL in medical institutions regarding the needs of older patients are health information and communication. The factors influencing the construction of OHL in medical institutions are multifaceted, encompassing micro, meso, and macro levels. At the macro level, it is essential for medical institutions to enhance leadership awareness of OHL and to incorporate its development into institutional strategic plans. At the meso-level, medical institutions should be made to optimize the medical environment for elderly patients and to prioritize health literacy training for medical staff. At the micro level, attention must be given to the characteristics and needs of elderly patients. Ultimately, by implementing a comprehensive construction of intervention strategies, the response ability of medical institutions to the needs of elderly patients can be enhanced.

The lack of long-term and high-quality solar radiation data has been an obstacle for scientific and industrial fields. In this study, a dense station-based long term and high-accuracy dataset of daily surface solar radiation was developed using two surface radiation models. One is the model developed by Yang et al. (2006) for global radiation estimation, and the other is the model developed by Tang et al. (2018) for direct radiation estimation. The main inputs for the development of the dataset are surface pressure, air temperature, relative humidity, horizontal visibility, and sunshine duration, which are the routine meteorological variables observed at the 2743 China Meteorological Administration (CMA) weather stations. Validation against in-situ observations and comparisons with two satellite-based radiation products show that our station-based radiation dataset clearly outperforms the satellite-based radiation products at both daily and monthly scales. In addition, our dataset is available for more than 60 years and includes three radiation components of global, direct and diffuse radiation, which is not possible with satellite products. This station-based radiation dataset will contribute to the climate change research and solar energy engineering applications in the future. [ABSTRACT FROM AUTHOR]

The biology of natural killer (NK) cells in commonly used mouse models is discussed in this review, along with their crucial function in a variety of immunological responses. It has been demonstrated that the formation, maturation, subtype variety, and immunological recognition mechanisms of NK cells from various mice strains exhibit notable differences. These variations shed light on the intricacy of NK cell function and offer crucial information regarding their possible uses in treating human illnesses. The application of flow cytometry in mouse NK cell research is also covered in the article. Improved knowledge of the biology of NK cells across species may facilitate the development of new NK cell-based therapeutic approaches.

BackgroundEmergence delirium (ED) is a widely recognized issue that prolongs mechanical ventilation and post-anesthesia care unit (PACU) resuscitation time, consequently increasing hospital costs and mortality. Postoperative disturbance in circadian rhythms, commonly leading to sleep disorders, has been identified as a significant risk factor for ED. However, the influence of surgery timing (morning vs. afternoon) on the incidence of ED in pediatric patients undergoing general anesthesia remains unknown.MethodsPatients aged 2–6 years who were operated on under general anesthesia with a bispectral index value between 50 and 60 were categorized based on anesthesia start time into either the morning surgery group (Group M, 8:00–12:00) or the afternoon surgery group (Group A, 13:00–17:00). The primary outcome was the post-extubation incidence of ED assessed by the Cornell Assessment of Pediatric Delirium (CAPD) score. Secondary outcomes included extubation time, duration of PACU stay, and adverse postoperative events and complications.ResultsWe recruited a total of 560 patients, 280 in group M and 280 in group A. Compared to Group M, Group A exhibited a significantly higher incidence of ED (p

Abstract Background In recent years, the prevalence and mortality rates of diabetes have been rising continuously, posing a significant threat to public health and placing a heavy burden on the population. This study was conducted to describe and analyze the burden of diabetes in China from 1990 to 2021 and its attributable risk factors. Methods Utilizing data from the Global Burden of Disease Study 2021, we analyzed the incidence, prevalence, and disability‐adjusted life years (DALYs) of type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in China from 1990 to 2021. We extracted sex‐ and age‐specific data on diabetes, focusing on DALYs, years lived with disability, and years of life lost. Bayesian meta‐regression and spatiotemporal Gaussian process regression were used to estimate disease parameters. Age‐standardized rates (ASRs) and estimated annual percentage changes (EAPC) were calculated using direct standardization and log‐linear regression. The population‐attributable fractions were also determined for each risk factor. Results In 2021, the absolute number of incident diabetes mellitus (DM) cases was estimated at 4003543.82, including 32 000 T1DM and 3971486.24 T2DM cases. The ASRs were 244.57 for DM, 2.67 for T1DM, and 241.9 for T2DM (per 100 000 population). The absolute number of prevalent DM cases was 117288553.93, including 1442775.09 T1DM and 115845778.84 T2DM cases. The ASRs were 6142.29 for DM, 86.78 for T1DM, and 6055.51 for T2DM (per 100 000 population). In 2021, there were 178475.73 deaths caused by DM, with an ASR of mortality of 8.98 per 100 000 population. The DALYs due to DM in 2021 were 11713613.86, with an ASR of 585.43 per 100 000 population and an EAPC of 0.57. This increase can be attributed to several factors, including high body mass index, air pollution, and dietary habits. Conclusions The burden of diabetes is considerable, with high prevalence and incidence rates, highlighting the urgent need for public health interventions. Addressing factors like high fasting plasma glucose, body mass index, air pollution, and dietary risks through effective interventions is critical.

Abstract Background Nucleotide-binding oligomerization domain-containing protein 1 (NOD1) plays a pivotal role in inducing metabolic inflammation in diabetes. Additionally, the NOD1 ligand disrupts the equilibrium of bone marrow-derived hematopoietic stem/progenitor cells, a process that has immense significance in the development of diabetic retinopathy (DR). We hypothesized that NOD1 depletion impedes the advancement of DR by resolving bone marrow dysfunction. Methods We generated NOD1−/−-Akita double-mutant mice and chimeric mice with hematopoietic-specific NOD1 depletion to study the role of NOD1 in the bone marrow–retina axis. Results Elevated circulating NOD1 activators were observed in Akita mice after 6 months of diabetes. NOD1 depletion partially restored diabetes-induced structural changes and retinal electrical responses in NOD1−/−-Akita mice. Loss of NOD1 significantly ameliorated the progression of diabetic retinal vascular degeneration, as determined by acellular capillary quantification. The preventive effect of NOD1 depletion on DR is linked to bone marrow phenotype alterations, including a restored HSC pool and a shift in hematopoiesis toward myelopoiesis. We also generated chimeric mice with hematopoietic-specific NOD1 ablation, and the results further indicated that NOD1 had a protective effect against DR. Mechanistically, loss of hematopoietic NOD1 resulted in reduced bone marrow-derived macrophage infiltration and decreased CXCL1 and CXCL2 secretion within the retina, subsequently leading to diminished neutrophil chemoattraction and NETosis. Conclusions The results of our study unveil, for the first time, the critical role of NOD1 as a trigger for a hematopoietic imbalance toward myelopoiesis and local retinal inflammation, culminating in DR progression. Targeting NOD1 in bone marrow may be a potential strategy for the prevention and treatment of DR.

BackgroundHypercholesterolemia, a critical contributor to cardiovascular disease, is not fully understood in terms of its relationship with serum metabolites and their role in disease pathogenesis.MethodsThis study leveraged GWAS data to explore the relationship between serum metabolites and hypercholesterolemia, pinpointing significant metabolites via Mendelian Randomization (MR) and KEGG pathway enrichment analysis. Data on metabolites were sourced from a European population, with analysis focusing on individuals diagnosed with hypercholesterolemia.ResultsOut of 486 metabolites analyzed, ten showed significant associations with hypercholesterolemia, categorized into those enhancing risk and those with protective effects. Specifically, 2-methoxyacetaminophen sulfate and 1-oleoylglycerol (1-monoolein) were identified as risk-enhancing, with odds ratios (OR) of 1.545 (95% CI: 1.230–1.939; P_FDR = 3E−04) and 1.462 (95% CI: 1.036–2.063; P_FDR = 0.037), respectively. On the protective side, 3-(cystein-S-yl)acetaminophen, hydroquinone sulfate, and 2-hydroxyacetaminophen sulfate demonstrated ORs of 0.793 (95% CI: 0.735–0.856; P_FDR = 6.18E−09), 0.641 (95% CI: 0.423–0.971; P_FDR = 0.042), and 0.607 (95% CI: 0.541–0.681; P_FDR = 5.39E−17), respectively. In addition, KEGG pathway enrichment analysis further revealed eight critical pathways, comprising “biosynthesis of valine, leucine, and isoleucine”, “phenylalanine metabolism”, and “pyruvate metabolism”, emphasizing their significant role in the pathogenesis of hypercholesterolemia.ConclusionThis study underscores the potential causal links between particular serum metabolites and hypercholesterolemia, offering innovative viewpoints on the metabolic basis of the disease. The identified metabolites and pathways offer promising targets for therapeutic intervention and warrant further investigation.

The purple nonsulfur bacteria, Rhodospirillum rubrum, is recognized as a potential strain for PHAs bioindustrial processes since they can assimilate a broad range of carbon sources, such as syngas, to allow reduction of the production costs. In this study, we comparatively analyzed the biomass and PHA formation behaviors of R. rubrum under 100% CO and 50% CO gas atmosphere and found that pure CO promoted the PHA synthesis (PHA content up to 23.3% of the CDW). Hydrogen addition facilitated the uptake and utilization rates of CO and elevated 3-HV monomers content (molar proportion of 3-HV up to 9.2% in the presence of 50% H2). To elucidate the genetic events culminating in the CO assimilation process, we performed whole transcriptome analysis of R. rubrum grown under 100% CO or 50% CO using RNA sequencing. Transcriptomic analysis indicated different CO2 assimilation strategy was triggered by the presence of H2, where the CBB played a minor role. An increase in BCAA biosynthesis related gene abundance was observed under 50% CO condition. Furthermore, we detected the α-ketoglutarate (αKG) synthase, converting fumarate to αKG linked to the αKG-derived amino acids synthesis, and series of threonine-dependent isoleucine synthesis enzymes were significantly induced. Collectively, our results suggested that those amino acid synthesis pathways represented a key way for carbon assimilation and redox potential maintenance by R. rubrum growth under syngas condition, which could partly replace the PHA production and affect its monomer composition in copolymers. Finally, a fed-batch fermentation of the R. rubrum in a 3-l bioreactor was carried out and proved H2 addition indeed increased the PHA accumulation rate, yielding 20% ww-1 PHA production within six days.

The catalytic performance and the stability of the water electrolysis system have perplexed the practical splitting water. Herein, 3D‐printed metallic electrodes with Janus porosity are reported, which can achieve the efficient bubble emission and provide high surface area. After a further one‐step treatment, the catalysts of Ru–Ni(OH)2 and Fe–Ni(OH)2 nanoarrays are in situ grown on the electrodes. Theoretical calculations and systematical experiments confirm the synergistic effect of the gradient morphology and the in situ grown catalysts. The electrolyzer shows unprecedented activity with an overpotential of 98 mV for hydrogen evolution reaction and 343 mV for oxygen evolution reaction at the current density of 500 mA cm−2 and outperformed stability, which can deliver 500 mA cm−2 at the voltage of 1.638 V for 2100 h with no significant decay, far exceedingly most state‐of‐the‐art electrolyzers. This 3D electrode with controllable bubble motions offers a viable solution for future industrial sustainable hydrogen production technology.

BackgroundElderly patients have a high risk of developing postoperative cognitive dysfunction (POCD). Gastrointestinal disorders, such as constipation, in the elderly population may be involved in the pathogenesis of neurological disorders by promoting inflammatory responses due to a ‘leaky gut’. General anesthetic sevoflurane may impair gastrointestinal function in elderly patients to trigger neurological complications following surgery. Therefore, we hypothesized that elderly individuals with gastrointestinal dysfunction may be more vulnerable to sevoflurane and consequently develop POCD.MethodsAged mice were randomly divided into four groups: control (CTRL), CTRL+sevoflurane (Sev), slow transit constipation (STC), and STC + Sev. Mice in the STC and STC + Sev groups were intra-gastrically administrated loperamide (3 mg/kg, twice a day for 7 days) to induce a slow transit constipation (STC) model determined with fecal water content and the time of first white fecal pellet, whereas mice in the other groups received the similar volume of saline. One week later, mice in the CTRL+Sev group and STC + Sev group received 2% sevoflurane for 2 h. The gut permeability evaluated with 4-kDa fluorescein isothiocyanate (FITC)-dextran, serum cytokines, microglia density, TLR4/NF-κB signaling expression, and POCD-like behavioral changes were determined accordingly.ResultsThe loperamide-induced STC mice had decreased fecal water content and prolonged time of first white fecal pellet. Sevoflurane exposure caused significantly increased gut permeability and serum cytokines, as well as the activation of microglia and the TLR4/NF-κB signaling pathway in the prefrontal cortex of the aged STC mice. Sevoflurane also caused cognitive impairment and emotional phenotype abnormality in aged STC mice.ConclusionAged STC mice were more vulnerable to sevoflurane anesthesia and consequently developed POCD-like behavioral changes. Our data suggest that gastrointestinal disorders including constipation may contribute to the development of POCD.

Abstract An effective systemic mechanism regulates tumor development and progression; thus, a rational design in a one‐stone‐two‐birds strategy is meant for cancer treatment. Herein, a hollow Fe3O4 catalytic nanozyme carrier co‐loading lactate oxidase (LOD) and a clinically‐used hypotensor syrosingopine (Syr) are developed and delivered for synergetic cancer treatment by augmented self‐replenishing nanocatalytic reaction, integrated starvation therapy, and reactivating anti‐tumor immune microenvironment. The synergetic bio‐effects of this nanoplatform stemmed from the effective inhibition of lactate efflux through blocking the monocarboxylate transporters MCT1/MCT4 functions by the loaded Syr as a trigger. Sustainable production of hydrogen peroxide by catalyzation of the increasingly residual intracellular lactic acid by the co‐delivered LOD and intracellular acidification enabled the augmented self‐replenishing nanocatalytic reaction. Large amounts of produced reactive oxygen species (ROS) damaged mitochondria to inhibit oxidative phosphorylation as the substituted energy supply upon the hampered glycolysis pathway of tumor cells. Meanwhile, remodeling anti‐tumor immune microenvironment is implemented by pH gradient reversal, promoting the release of proinflammatory cytokines, restored effector T and NK cells, increased M1‐polarize tumor‐associated macrophages, and restriction of regulatory T cells. Thus, the biocompatible nanozyme platform achieved the synergy of chemodynamic/immuno/starvation therapies. This proof‐of‐concept study represents a promising candidate nanoplatform for synergetic cancer treatment.

Sodium butyrate (SB) is a histone deacetylase inhibitor that can induce changes in gene expression and secondary metabolite titers by inhibiting histone deacetylation. Our preliminary analysis also indicated that SB significantly enhanced the biosynthesis of carotenoids in the Rhodotorula glutinis strain YM25079, although the underlying regulatory mechanisms remained unclear. Based on an integrated analysis of transcriptomics and metabolomics, this study revealed changes in cell membrane stability, DNA and protein methylation levels, amino acid metabolism, and oxidative stress in the strain YM25079 under SB exposure. Among them, the upregulation of oxidative stress may be a contributing factor for the increase in carotenoid biosynthesis, subsequently enhancing the strain resistance to oxidative stress and maintaining the membrane fluidity and function for normal cell growth. To summarize, our results showed that SB promoted carotenoid synthesis in the Rhodotorula glutinis strain YM25079 and increased the levels of the key metabolites and regulators involved in the stress response of yeast cells. Additionally, epigenetic modifiers were applied to produce fungal carotenoid, providing a novel and promising strategy for the biosynthesis of yeast-based carotenoids.

Probiotics play beneficial roles in improving the host intestinal microecological balance and improving the host health level and health state. It mainly affects the host health by regulating the intestinal microbiota and participating in the immune regulation of various diseases, thus improving the gastrointestinal physiology. Probiotics have considerable potential in the prevention and treatment of gastrointestinal diseases, and a deeper understanding of the mechanisms of their interaction with gut flora and immune regulation are needed. In this paper, the distribution and colonization of probiotics in the intestinal tract, the regulation of probiotics on intestinal flora and intestinal function, and the relationship between probiotics and immune regulation are briefly discussed, in order to provide reference for the future research on the interaction between probiotics and intestinal flora and the clinical application of probiotics.