Understanding and treating diabetic foot ulcers: Insights into the role of cutaneous microbiota and innovative therapies.

Background: Notoriously known as the silent pandemic, chronic, non-healing diabetic foot ulcers (DFUs), pose a significant rate of incidence for amputation and are a major cause of morbidity. Alarmingly, the treatment and management strategies of chronic wounds represent a significant economic and health burden as well as a momentous drain on resources with billions per annum being spent in the US and UK alone. Defective wound healing is a major pathophysiological condition which propagates an acute wound to a chronic wound, further propelled by underlying conditions such as diabetes and vascular complications which are more prevalent amongst the elderly. Chronic wounds are prone to infection, which can exacerbate the condition, occasionally resulting in amputation for the patient, despite the intervention of modern therapies. However, amputation can only yield a 5-year survival rate for 50% of patients, highlighting the need for new treatments for chronic wounds. Findings: The dynamic cutaneous microbiota is comprised of diverse microorganisms that often aid wound healing. Conversely, the chronic wound microbiome consists of a combination of common skin commensals such as Staphylococcus aureus and Staphylococcus epidermidis, as well as the opportunistic pathogen Pseudomonas aeruginosa. These bacteria have been identified as the most prevalent bacterial pathogens isolated from chronic wounds and contribute to prolific biofilm formation decreasing the efficiency of antimicrobials and further perpetuating a hyper-inflammatory state. Discussion and Conclusion: Here, we review recent advances and provide a new perspective on alternative treatments including phage and microbiome transplant therapies and how the definitive role of the cutaneous microbiota impacts the aetiology of DFUs.

Digital economy, resource distortion and low-carbon inclusive development-Evidence from the perspectives of a threshold effect and knowledge spillover effect.

The low-carbon economy represents a global transformation that encompasses production methods, lifestyles, values, national interests, and the destiny of humanity. As a significant contributor to carbon emissions, China has made a momentous strategic decision on carbon peaking and neutralization, infusing momentum into the global effort to address climate change. The rapid growth of the digital economy offers a fresh approach to achieving the "double carbon" objective and advancing the development of low-carbon transformation. Based on the panel data of 30 provinces in China, this paper uses the least square method to investigate the impact of digital economy development on regional low-carbon inclusive development. It is found that there is a significant inverted U shape in the impact of the digital economy on low-carbon inclusive development and the mechanism is resource allocation and ecological inequality. The threshold test found that the role of the digital economy in promoting low-carbon inclusive development shows a marginal decreasing trend. The inverted U-shaped impact of the digital economy on low-carbon inclusive development in the eastern and coastal areas and areas with a low level of factor productivity is more significant. Based on the knowledge factor spillover perspective, we found that the impact of the digital economy on low-carbon inclusive development has a spatial spillover effect, and this effect is more obvious under the role of R&D personnel mobility.

The effects of meteorological factors and air pollutants on the incidence of tuberculosis in people living with HIV/AIDS in subtropical Guangxi, China.

BACKGROUND: Previous studies have shown the association between tuberculosis (TB) and meteorological factors/air pollutants. However, little information is available for people living with HIV/AIDS (PLWHA), who are highly susceptible to TB. METHOD: Data regarding TB cases in PLWHA from 2014 to2020 were collected from the HIV antiviral therapy cohort in Guangxi, China. Meteorological and air pollutants data for the same period were obtained from the China Meteorological Science Data Sharing Service Network and Department of Ecology and Environment of Guangxi. A distribution lag non-linear model (DLNM) was used to evaluate the effects of meteorological factors and air pollutant exposure on the risk of TB in PLWHA. RESULTS: A total of 2087 new or re-active TB cases were collected, which had a significant seasonal and periodic distribution. Compared with the median values, the maximum cumulative relative risk (RR) for TB in PLWHA was 0.663 (95% confidence interval [CI]: 0.507-0.866, lag 4 weeks) for a 5-unit increase in temperature, and 1.478 (95% CI: 1.116-1.957, lag 4 weeks) for a 2-unit increase in precipitation. However, neither wind speed nor PM10 had a significant cumulative lag effect. Extreme analysis demonstrated that the hot effect (RR = 0.638, 95%CI: 0.425-0.958, lag 4 weeks), the rainy effect (RR = 0.285, 95%CI: 0.135-0.599, lag 4 weeks), and the rainless effect (RR = 0.552, 95%CI: 0.322-0.947, lag 4 weeks) reduced the risk of TB. Furthermore, in the CD4(+) T cells < 200 cells/µL subgroup, temperature, precipitation, and PM10 had a significant hysteretic effect on TB incidence, while temperature and precipitation had a significant cumulative lag effect. However, these effects were not observed in the CD4(+) T cells ≥ 200 cells/µL subgroup. CONCLUSION: For PLWHA in subtropical Guangxi, temperature and precipitation had a significant cumulative effect on TB incidence among PLWHA, while air pollutants had little effect. Moreover, the influence of meteorological factors on the incidence of TB also depends on the immune status of PLWHA.

Large enhancement of red upconversion luminescence in beta Ba2Sc0.67Yb0.3Er0.03AlO5 phosphor via Mn2+ ions doping for thermometry.

Here, this study reports single-band red upconversion emission in ß-Ba2ScAlO5: Yb3+/Er3+ phosphor by doping Mn2+. The optimum concentration of Mn2+ ions in ß-Ba2ScAlO5: Yb3+/Er3+ phosphor was 0.20. The intensity of red and green emissions is increased by 27.4 and 19.3 times, respectively. Compared with the samples without Mn2+ ions, the red-green integral strength ratio of ß-Ba2ScAlO5: Yb3+/Er3+/Mn2+ sample was significantly increased by 28.4 times, reaching 110.9. The UCL mechanism was explored by analyzing the down-conversion luminescence spectra, absorption spectra, UCL spectra, and upconversion fluorescence lifetime decay curves of Yb3+/Er3+/Mn2+ co-doped ß-Ba2ScAlO5. The enhancement of upconversion red light is achieved through energy transfer between defect bands and Er3+ ions, as well as energy transfer between Mn2+ ions and Er3+ ions. In addition, the Mn2+ doped ß-Ba2ScAlO5: Yb3+/Er3+ red UCL phosphors have great potential for ambient temperature sensing in the 298-523 K temperature range. The maximum sensitivity of ß-Ba2ScAlO5: Yb3+/Er3+/Mn2+ phosphor as a temperature sensor at 523 K is 0.0247 K-1.

A Manganese-Based Nanodriver Coordinates Tumor Prevention and Suppression through STING Activation in Glioblastoma.

Glioblastoma (GBM), the most prevalent and aggressive primary malignant brain tumor, exhibits profound immunosuppression and demonstrates a low response rate to current immunotherapy strategies. Manganese cations (Mn2+) directly activate the cGAS/STING pathway and induce the unique catalytic synthesis of 2'3'-cGAMP to facilitate type I IFN production, thereby enhancing innate immunity. Here, a telodendrimer and Mn2+-based nanodriver (PLHM) with a small size is developed, which effectively target lymph nodes through the blood circulation and exhibit tumor-preventive effects at low doses of Mn2+ (3.7 mg kg-1). On the other hand, the PLHM nanodriver also exhibits apparent antitumor effects in GBM-bearing mice via inducing in vivo innate immune responses. The combination of PLHM with doxorubicin nanoparticles (PLHM-DOX NPs) results in superior inhibition of tumor growth in GBM-bearing mice due to the synergistic potentiation of STING pathway functionality by Mn2+ and the presence of cytoplasmic DNA. These findings demonstrate that PLHM-DOX NPs effectively stimulate innate immunity, promote dendritic cell maturation, and orchestrate cascaded infiltration of CD8 cytotoxic T lymphocytes within glioblastomas characterized by low immunogenicity. These nanodivers chelated with Mn2+ show promising potential for tumor prevention and antitumor effects on glioblastoma by activating the STING pathway.

Towards zero-carbon cities: how does environmental information disclosure impact the risk of carbon locking?

Utilizing panel data from 119 cities spanning from 2013 to 2019, the study rigorously investigates the influence of environmental information disclosure (EID) on mitigating the risk of urban carbon lock-in through the application of both two-way fixed effects and spatial econometric models. The findings robustly indicate that EID plays a significant role in facilitating carbon unlocking within cities, a conclusion that remains steadfast even after addressing potential endogeneity issues. Mechanistically, it is revealed that EID can effectively decrease the risk of carbon lock-in by enhancing urbanization levels and reducing energy intensity. Furthermore, the study unveils that the efficacy of EID in curbing urban carbon lock-in risk is also contingent upon factors such as carbon intensity, population size, and environmental quality, highlighting the multifaceted nature of EID's impact on urban carbon management. Specifically, the increase in carbon intensity, the expansion of population size, and the deterioration of environmental quality will reduce the carbon unlocking effect, which may not be conducive to the achievement of the goal of "carbon neutrality" in cities. The spatial effect test found that EID and carbon locking risk are both spatially significant positive autocorrelation, the deepening of local EID can significantly cut the risk of carbon locking in neighboring cities, and the urbanization pathway and energy saving pathway exist both locally and in neighboring places.

A Study of Electroplated Nanoporous Copper Using Aberration-Corrected Transmission Electron Microscopy.

Nanoporous Cu foam is widely applied in many fields such as the packaging of electronic power devices. In this study, a sandwich-structured Cu-Zn eutectic alloy precursor composed of Cu0.53Zn0.47/Cu5Zn8/Cu0.53Zn0.47 is prepared through electroplating. The surface layer of the precursor, Cu0.53Zn0.47, has a flat surface with numerous grain boundaries, which effectively promotes its dealloying behavior. By contrast, Cu5Zn8 has a porous structure, which promotes the dealloying behavior at the center of the precursor. The dealloying of Cu0.53Zn0.47 is dominated by the coherent surface diffusion of Cu atoms, and the crystal lattice and orientation show no changes before and after dealloying. By contrast, the dealloying behavior of Cu5Zn8 requires the renucleation of Cu crystals; in this process, Cu atoms are transported to the surface of the layer by capillary forces to form clusters, which nucleate and grow.

The antifouling mechanism and application of bio-inspired superwetting surfaces with effective antifouling performance.

With the rapid development of industries, the issue of pollution on Earth has become increasingly severe. This has led to the deterioration of various surfaces, rendering them ineffective for their intended purposes. Examples of such surfaces include oil rigs, seawater intakes, and more. A variety of functional surface techniques have been created to address these issues, including superwetting surfaces, antifouling coatings, nano-polymer composite materials, etc. They primarily exploit the membrane's surface properties and hydration layer to improve the antifouling property. In recent years, biomimetic superwetting surfaces with non-toxic and environmental characteristics have garnered massive attention, greatly aiding in solving the problem of pollution. In this work, a detailed presentation of antifouling superwetting materials was made, including superhydrophobic surface, superhydrophilic surface, and superhydrophilic/underwater superoleophobic surface, along with the antifouling mechanisms. Then, the applications of the superwetting antifouling materials in antifouling domain were addressed in depth.

Causal relationship between gut microbiota and tuberculosis: a bidirectional two-sample Mendelian randomization analysis.

BACKGROUND: Growing evidence from observational studies and clinical trials suggests that the gut microbiota is associated with tuberculosis (TB). However, it is unclear whether any causal relationship exists between them and whether causality is bidirectional. METHODS: A bidirectional two-sample Mendelian randomization (MR) analysis was performed. The genome-wide association study (GWAS) summary statistics of gut microbiota were obtained from the MiBioGen consortium, while the GWAS summary statistics of TB and its specific phenotypes [respiratory tuberculosis (RTB) and extrapulmonary tuberculosis (EPTB)] were retrieved from the UK Biobank and the FinnGen consortium. And 195 bacterial taxa from phylum to genus were analyzed. Inverse variance weighted (IVW), MR-Egger regression, maximum likelihood (ML), weighted median, and weighted mode methods were applied to the MR analysis. The robustness of causal estimation was tested using the heterogeneity test, horizontal pleiotropy test, and leave-one-out method. RESULTS: In the UK Biobank database, we found that 11 bacterial taxa had potential causal effects on TB. Three bacterial taxa genus.Akkermansia, family.Verrucomicrobiacea, order.Verrucomicrobiales were validated in the FinnGen database. Based on the results in the FinnGen database, the present study found significant differences in the characteristics of gut microbial distribution between RTB and EPTB. Four bacterial taxa genus.LachnospiraceaeUCG010, genus.Parabacteroides, genus.RuminococcaceaeUCG011, and order.Bacillales were common traits in relation to both RTB and TB, among which order.Bacillales showed a protective effect. Additionally, family.Bacteroidacea and genus.Bacteroides were identified as common traits in relation to both EPTB and TB, positively associating with a higher risk of EPTB. In reverse MR analysis, no causal association was identified. No significant heterogeneity of instrumental variables (IVs) or horizontal pleiotropy was found. CONCLUSION: Our study supports a one-way causal relationship between gut microbiota and TB, with gut microbiota having a causal effect on TB. The identification of characteristic gut microbiota provides scientific insights for the potential application of the gut microbiota as a preventive, diagnostic, and therapeutic tool for TB.

Protective effects of puerarin on liver tissue in Salmonella-infected chicks: a proteomic analysis.

Salmonella enterica is a zoonotic bacterium that not only causes serious economic losses to the livestock and poultry industries but also seriously endangers human health. Long-term indiscriminate use of antibiotics has led to drug resistance in Salmonella, and thus the identification of alternatives to antibiotics is crucial. In this study, the effects of puerarin on the S. enterica-infected chickens were investigated. A total of 360 chicks were randomly assigned as the control group (CON), the S. enterica group (S), and puerarin-treatment group (P). Chicks in the P group were fed the basal diet supplemented with 50 (P50), 100 (P100), 200 (P200), and 400 (P400) mg/kg puerarin, respectively. It was found that puerarin treatment markedly altered the serum activities of aspartate aminotransferase (AST), alanine transaminase (ALT), and superoxide dismutase (SOD), together with the malondialdehyde (MDA) and total antioxidant capacity (T-AOC) contents in the serum. The mRNA expression of IL-6, IL-1ß, TNF-α, Bcl-2, and caspase-8 in the livers of S. enterica-infected chicks was increased after infection but significantly reduced after treatment with puerarin. Histologic analysis showed that puerarin effectively mitigated morphological damage in the liver caused by S. enterica. Proteomic analysis revealed that S. enterica infection led to metabolic disorders in the liver, resulting in oxidative stress, increased inflammation, and significantly elevated levels of hepatocellular carcinoma biomarkers. The findings of the filtered sequencing were verified by using quantitative PCR (qPCR). Treatment with 100 mg/mL puerarin thus effectively alleviated disordered liver metabolism, reduced inflammation and oxidative damage and significantly reduced the levels of hepatocellular carcinoma biomarkers in the liver. The results suggest that puerarin has the potential to replace antibiotics to control Salmonella infection in poultry and thus improve food safety.

Paper-Supported Photoelectrochemical Biosensor for Dual-Mode miRNA-106a Assay: Integration of Luminescence-Confined Upconversion-Actuated Fluorescent Resonance Energy Transfer and CRISPR/Cas13a-Powered Cascade DNA Circuits.

Near-infrared (NIR)-responsive bioassays based on upconversion nanoparticle (UCNP) incorporating high-performance semiconductors have been developed by researchers, but most lack satisfactory ultrasensitivity for exceedingly trace amounts of target. Herein, for the first time, the CRISPR/Cas13a system is combined with cascade DNA circuits, fluorescent resonance energy transfer (FRET) effect, and luminescence-confined UCNPs-bonded CuInS2/ZnO p-n heterostructures-functionalized paper-working electrode to construct dual-signal-on paper-supported NIR-irradiated photoelectrochemical (PEC) (NIR-PEC) and upconversion luminescence (UCL) bioassay for high-sensitive quantification of miRNA-106a (miR-106a). By constructing an ideal FAM-labeled aminating molecular beacon (FAM-H2) model, a relatively good FRET ratio between the UCNP and FAM (≈85.3%) can be achieved. In the existence of miR-106a, the hairpin-structure FAM-H2 was unwound, bringing about the distance increase of UCNP and FAM and the restraint of FRET. Accordingly, both the NIR-PEC signal and the UCL intensity gradually recovered distinctly. Unlike conventional single-mode PEC sensors, with NIR excitation, the designed dual-mode sensing system could implement minimized misdiagnose assay and quantitative miR-106a determination with low detection limits, that is, 76.54 and 51.36 aM for NIR-PEC and UCL detection, respectively. This work not only broadens the horizon of application of the CRISPR/Cas13a strategy toward biosensing but also constructs a new structure of the UCNP-semiconductor in the exploration of efficient NIR-responsive tools and inspires the construction of a no-misdiagnosed and novel biosensor for dual-mode liquid biopsy.

Activation of the JNK/COX-2/HIF-1α axis promotes M1 macrophage via glycolytic shift in HIV-1 infection.

Chronic inflammation is recognized as a major risk factor for the severity of HIV infection. Whether metabolism reprogramming of macrophages caused by HIV-1 is related to chronic inflammatory activation, especially M1 polarization of macrophages, is inconclusive. Here, we show that HIV-1 infection induces M1 polarization and enhanced glycolysis in macrophages. Blockade of glycolysis inhibits M1 polarization of macrophages, indicating that HIV-1-induced M1 polarization is supported by enhanced glycolysis. Moreover, we find that this immunometabolic adaptation is dependent on hypoxia-inducible factor 1α (HIF-1α), a strong inducer of glycolysis. HIF-1α-target genes, including HK2, PDK1, and LDHA, are also involved in this process. Further research discovers that COX-2 regulates HIF-1α-dependent glycolysis. However, the elevated expression of COX-2, enhanced glycolysis, and M1 polarization of macrophages could be reversed by inactivation of JNK in the context of HIV-1 infection. Our study mechanistically elucidates that the JNK/COX-2/HIF-1α axis is activated to strengthen glycolysis, thereby promoting M1 polarization in macrophages in HIV-1 infection, providing a new idea for resolving chronic inflammation in clinical AIDS patients.

Determination of multiclass contaminants in chilli powder based on magnetic multiwalled carbon nanotubes and UPLC-QTOF/MS.

A multiclass analysis approach was developed using magnetic multiwalled carbon nanotubes sorbents and ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) for the rapid screening and simultaneous determination of 216 contaminants including 15 mycotoxins, 9 synthetic colourants, and 192 pesticides in chilli powder. The sample preparation process was optimized. The optimal preparation procedure utilized NaCl and NaAc as the salting-out agents, and Fe3O4-MWCNTs as the sorbents, resulting in reduced chemical consumption, improved cleaning performance, and facilitated high-throughput analysis. The proposed method was validated, and satisfactory parameters were obtained. Approximately 85.6% of the target analytes exhibited a weak matrix effect, with the matrix effects falling within the range of 0.8 âˆ¼ 1.2. The method demonstrated acceptable recoveries of the analytes, falling within the range of 62.14%∼119.76% at three fortified levels with relative standard deviations (RSDs) of less than 20%. Additionally, the method's limit of quantification (LOQ) ranged from ranged from 0.50 µg·kg-1 to 49.56 µg·kg-1. The method was further applied for analysis of 27 chilli powder samples, demonstrating its potential for screening and quantification of multiclass contaminants for spices.

UPLC-Q-TOF/MS-based metabolomic analysis reveals the effects of asomate on the citrus fruit.

The regulation of the sugar-acid ratio is of great significance to the improvement of citrus fruit quality. The citric acid level in fruit is influenced by many factors. Among them, cultivar selection and production practices are the most important strategies under the grower's control. In recent years, an arsenic-containing preparation called "Tianmisu", with the main ingredient of asomate, has occasionally been reported to be used in citrus cultivation to improve the sweetness of fruits. In order to reveal the effects of the pesticide on citrus fruits, 'Harumi' tangor was treated with "Tianmisu", and the impact of this pesticide on fruit quality and metabolites was investigated through UPLC-Q-TOF/MS-based metabolomic analysis. Compared with the control, the concentration of titratable acidity, in particular citric acid, in the pulp of 'Harumi' tangor treated with the pesticide, was significantly reduced by 60.5%. The differences in metabolites between the pesticide-treated samples and the control were illustrated by Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA). The PLS-DA analysis demonstrated a clear discrimination, with R2Y and Q2 values of 0.982 and 0.933 in the positive mode and 0.984 and 0.900 in the negative mode, respectively. A total of 155 compounds were identified, and 63 characteristic components were screened out from the pesticide-treated samples compared to the control. Aside from the upregulation observed for a few metabolites, the majority of the compounds, including citric acid and various lipids, were down-regulated in the treated citrus fruits compared to the control. This study can serve as a basis for understanding the regulatory mechanism of organic acids in citrus and will be helpful in developing different strategies to improve citrus quality.

Exploring outdoor activity limitation (OAL) factors among older adults using interpretable machine learning.

BACKGROUND: The occurrence of outdoor activity limitation (OAL) among older adults is influenced by multidimensional and confounding factors associated with aging. AIM: The aim of this study was to apply interpretable machine learning (ML) to develop models for multidimensional aging constraints on OAL and identify the most predictive constraints and dimensions across multidimensional aging data. METHODS: This study involved 6794 community-dwelling participants older than 65 from the National Health and Aging Trends Study (NHATS). Predictors included related to six dimensions: sociodemographics, health condition, physical capacity, neurological manifestation, daily living habits and abilities, and environmental conditions. Multidimensional interpretable machine learning models were assembled for model construction and analysis. RESULTS: The multidimensional model demonstrated the best predictive performance (AUC: 0.918) compared to the six sub-dimensional models. Among the six dimensions, physical capacity had the most remarkable prediction (AUC: physical capacity: 0.895, daily habits and abilities: 0.828, physical health: 0.826, neurological performance: 0.789, sociodemographic: 0.773, and environment condition: 0.623). The top-ranked predictors were SPPB score, lifting ability, leg strength, free kneeling, laundry mode, self-rated health, age, attitude toward outdoor recreation, standing time on one foot with eyes open, and fear of falling. DISCUSSION: Reversible and variable factors, which are higher in the set of high-contribution constraints, should be prioritized as the main contributing group in terms of interventions. CONCLUSION: The integration of potentially reversible factors, such as neurological performance in addition to physical function into ML models, yields a more accurate assessment of OAL risk, which provides insights for targeted, sequential interventions for older adults with OAL.

Bismuth-Decorated Honeycomb-like Carbon Nanofibers: An Active Electrocatalyst for the Construction of a Sensitive Nitrite Sensor.

The existence of carcinogenic nitrites in food and the natural environment has attracted much attention. Therefore, it is still urgent and necessary to develop nitrite sensors with higher sensitivity and selectivity and expand their applications in daily life to protect human health and environmental safety. Herein, one-dimensional honeycomb-like carbon nanofibers (HCNFs) were synthesized with electrospun technology, and their specific structure enabled controlled growth and highly dispersed bismuth nanoparticles (Bi NPs) on their surface, which endowed the obtained Bi/HCNFs with excellent electrocatalytic activity towards nitrite oxidation. By modifying Bi/HCNFs on the screen-printed electrode, the constructed Bi/HCNFs electrode (Bi/HCNFs-SPE) can be used for nitrite detection in one drop of solution, and exhibits higher sensitivity (1269.9 µA mM-1 cm-2) in a wide range of 0.1~800 µM with a lower detection limit (19 nM). Impressively, the Bi/HCNFs-SPE has been successfully used for nitrite detection in food and environment samples, and the satisfactory properties and recovery indicate its feasibility for further practical applications.

Bio-inspired and metal-derived superwetting surfaces: Function, stability and applications.

Due to their exceptional anti-icing, anti-corrosion, and anti-drag qualities, biomimetic metal-derived superwetting surfaces, which are widely employed in the aerospace, automotive, electronic, and biomedical industries, have raised significant concern. However, further applications in other domains have been hampered by the poor mechanical and chemical durability of superwetting metallic surfaces, which can result in metal fatigue and corrosion. The potential for anti-corrosion, anti-contamination, anti-icing, oil/water separation, and oil transportation on surfaces with superwettability has increased in recent years due to the advancement of research in biomimetic superwetting interface theory and practice. Recent developments in functionalized biomimetic metal-derived superwetting surfaces were summarized in this paper. Firstly, a detailed presentation of biomimetic metal-derived superwetting surfaces with unique capabilities was made. The problems with the long-term mechanical and chemical stability of biomimetic metal-derived superwetting surfaces were then examined, along with potential solutions. Finally, in an effort to generate fresh concepts for the study of biomimetic metal-derived superwetting surfaces, the applications of superwetting metallic surfaces in various domains were discussed in depth. The future direction of biomimetic metal-derived superwetting surfaces was also addressed.

Structural characterization and partial properties of dextran produced by Leuconostoc mesenteroides RSG7 from pepino.

Exopolysaccharides (EPSs) produced by lactic acid bacteria possess various bioactivities and potential attractions for scientific exploration and commercial development. An EPS-producing bacterial strain, RSG7, was previously isolated from the pepino and identified as Leuconostoc mesenteroides. Based on the analyses of high-performance size exclusion chromatography, high-performance ion chromatography, Fourier transform infrared spectroscopy, nuclear magnetic resonance spectroscopy, and methylation, the RSG7 EPS was identified as a dextran with a molecular weight of 5.47 × 106 Da and consisted of α-(1→6) glycosidic linkages as backbone and α-(1→2), α-(1→3), α-(1→4), and α-(1→6) glycosidic linkages as side chains. Scanning electron microscopy observed a honeycomb-like porous structure of RSG7 dextran, and this dextran formed aggregations with irregular hill-shaped lumps according to atomic force microscopy analysis. Physical-chemical investigations suggested that RSG7 dextran possessed excellent viscosity at high concentration, low temperature, and high pH; showed a superior emulsifying capacity of tested vegetable oils than that of hydrocarbons; and owned the maximal flocculating activity (10.74 ± 0.23) and flocculating rate (93.46 ± 0.07%) in the suspended solid of activated carbon. In addition, the dextran could coagulate sucrose-supplemented milk and implied potential probiotics in vitro. Together, these results collectively describe a valuable dextran with unique characteristics for exploitation in food applications.

Impact of Digital Transformation on Enterprise Carbon Intensity: The Moderating Role of Digital Information Resources.

In the context of China's "digital power" strategy, the realization of a green and low-carbon shift in manufacturing has become a necessary condition to promote the economy, and the digital factor has increasingly become a new driving force. The text mining and IPCC methods were used to measure manufacturing enterprise digitalization and the level of enterprise carbon emission intensity from 2011 to 2021, respectively. This study then explored the impact of digitalization on manufacturing enterprise carbon emission intensity based on the least squares method model and instrumental variable method model. This research comes to three conclusions. (1) Digitalization can significantly reduce the enterprise carbon emission intensity of China's manufacturing industry, and the influence shows a "marginal increase." (2) Notably, a mechanism analysis indicates the intermediary effect sizes of four crucial intermediaries: green technology innovation > financing constraint > information asymmetry > energy use efficiency. Interestingly, digital information resources positively moderate the positive effect of digitalization on carbon emission intensity through three paths: financing constraints, green technology innovation, and information asymmetry. (3) The influence shows evident signs of heterogeneity-as environmental regulation, financial development, executive education, and R&D quality advance, the inhibiting effect of digitalization on enterprise carbon emission intensity becomes more pronounced. Finally, corresponding policy suggestions are proposed.

Towards high-quality development: how does digital economy impact low-carbon inclusive development?: mechanism and path.

High-quality development is the primary task of building a modern socialist country in an all-around way. Innovation, coordination, green development, openness, and sharing are the main connotations of high-quality development. Based on panel data from 286 cities in China, this paper empirically analyzes the impact of the digital economy on low-carbon inclusive development (hereinafter referred to as LIG). The results show that the digital economy has a salient promoting effect on LIG, and with the increase of quantile level, the promoting effect shows a marginal decreasing trend. Heterogeneity analysis found that the cities with low resource dependence and marketization of the digital economy and high environmental concern and competition have more salient promoting effects on LIG. The dimensionality reduction analysis shows that the impact of digital economy on economic growth, social inclusion, and low-carbon ecology gradually increases in turn. The mechanism test shows that R&D investment, green innovation, and market integration play a partial mediating role, while entrepreneurial activity, industrial upgrading, and development imbalance play a fully mediating role. Digital economy promotes urban economic growth and low-carbon ecological development through R&D investment and market integration and mainly promotes low-carbon ecological development through green innovation. The digital economy will promote low-carbon and inclusive urban development by stimulating entrepreneurship, promoting industrial upgrading, and alleviating development imbalances.