Therapeutic effect of fecal microbiota transplantation on rats with liver cirrhosis and its influence on gut microbiota.

Objectives: This study aimed to explore the therapeutic effect of fecal microbiota transplantation (FMT) on liver cirrhosis-induced rat models by studying changes in intestinal flora distribution and liver pathology. Materials and Methods: Cirrhosis was induced in adult male Sprague-Dawley rats using carbon tetrachloride; successful establishment of the cirrhosis model was verified using hematoxylin and eosin (HE) staining. Rats were divided into normal control, cirrhosis model+normal saline, and cirrhosis model+FMT groups. Fecal intestinal flora was analyzed using 16S rRNA high-throughput sequencing for each group. Alpha diversity, beta diversity, and functional prediction analyses were performed. Additionally, rat liver tissue was subjected to HE staining to compare the degree of fibrosis and liver damage between the groups. Results: FMT significantly improved the diversity, richness, and uniformity of the intestinal flora in rats with liver cirrhosis. Notably, post-FMT, the abundance of lactobacillaceae, bacilli, and bacteroidia increased, while the abundance of clostridia decreased. Moreover, hepatic fibrosis improved after FMT. Conclusion: The dysbiosis of intestinal flora in rats with liver cirrhosis improved after FMT. Thus, FMT can regulate intestinal flora, reduce liver inflammation, and improve hepatic fibrosis and cirrhosis.

Mitochondrial-Targeted Copper Delivery for Cuproptosis-Based Synergistic Cancer Therapy.

Cuproptosis is dependent on mitochondrial respiration modulation by targeting lipoylated tricarboxylic acid cycle (TCA) cycle proteins, showing great potential in cancer treatment. However, the specific release of copper ions at mitochondrial is highly needed and still a major challenge to trigger cellular cuproptosis. Herein, a metal-organic framework-based nanoplatform (ZCProP) is designed for mitochondrial-targeted and ATP/pH-responsive Cu2+ and prodigiosin release. The released Cu2+ promotes aggregation of lipoylated protein and loss of Fe-S cluster protein, resulting in cell cuproptosis. In the meanwhile, Cu2+ can concert with prodigiosin to induce mitochondrial dysfunction and DNA damage and enhance cell cuproptosis. Furthermore, this nanoplatform has an ability to deplete glutathione, which not only further promotes cuproptosis but also triggers cell ferroptosis by the suppression of glutathione peroxidase 4, an anti-ferroptosis protein. Collectively, the designed ZCProP nanoplatform can responsively release cargos at mitochondrial and realize a conspicuous therapeutic efficacy through a cuproptosis-mediated concerted effect. Along with its excellent biocompatibility, this nanoplatform may provide a novel therapeutic modality paradigm to boost cancer therapeutic strategies based on cuproptosis.

Links among population aging, economic globalization, per capita CO2 emission, and economic growth, evidence from East Asian countries.

Population aging, economic globalization, and economic growth simultaneously cause changes in environmental quality, but so far no studies have integrated these key factors into the same environmental policy framework. Thus, this study uses the more robust Westerlund cointegration test and the augmented mean group (AMG) estimator (robust to cross-sectional dependence (CD), heterogeneity, and endogeneity) to estimate the long-term relationship between population aging, economic globalization, economic growth, and per capita carbon emissions in East Asian countries during the period 1975-2018. The analysis results reflect that population aging significantly reduces the long-term per capita carbon emissions of specific East Asian countries. However, energy generation and economic globalization make significant contributions to long-run per capita carbon emissions. Moreover, the impact of economic growth on long-term per capita carbon emissions is significantly positive, while the impact of square of economic growth on long-run per capita carbon emissions is significantly negative, thus validating the inverted U-shaped environmental Kuznets curve (EKC) hypothesis for specific East Asian countries. The results of the causality test indicated a two-way causality between energy generation and per capita carbon dioxide emission, supporting the feedback hypothesis. There is also a two-way causal relationship between aging population and per capita carbon dioxide emission. Policy recommendations are discussed in response to the empirical findings of this study.

Application of omics technology to investigate the mechanism underlying the role of San Hua Tang in regulating microglia polarization and blood-brain barrier protection following ischemic stroke.

ETHNOPHARMACOLOGY RELEVANCE: San Hua Tang (SHT) was first mentioned in the book "The Collection of Plain Questions about Pathogenesis, Qi, and Life." SHT has the effect of dispelling wind and dredging collaterals, dredging viscera, and guiding stagnation, and is used in the treatment of ischemic stroke (IS). SHT is composed of Rheum palmatum L., Magnolia officinalis Rehder & E.H.Wilson, Citrus assamensis S.Dutta & S.C.Bhattacharya, and Notopterygium tenuifolium M.L.Sheh & F.T.Pu, which is the traditional prescription of the Tongxia method for the treatment of stroke. Tongxia is one of the "eight methods" used in traditional Chinese medicine, which plays a role in treating diseases by promoting gastrointestinal peristalsis and defecation. Studies have demonstrated a close relationship between gut microbiota metabolism and cerebral stroke; however, the role of SHT in IS treatment through gut microbiota or intestinal metabolites is unclear. AIM OF THE STUDY: To explore the connotation of the Xuanfu theory and clarify the mechanism underlying SHT-mediated opening Xuanfu methods. Through metabolomics, 16S rRNA gene sequencing, and molecular biology techniques, research on the changes in the gut microbiota and blood-brain barrier (BBB) will highlight greater strategies for the treatment of stroke. MATERIALS AND METHODS: We used pseudo-germ-free (PGF) rats combined with an ischemia/reperfusion (I/R) rat model for the follow-up experimental research. PGF rats were prepared by the intragastric administration of an antibiotic cocktail for 6 days, following which SHT was administered for 5 consecutive days. The I/R model was performed 1 day following the concluding administration of SHT. We detected the neurological deficit score, cerebral infarct volume, serum inflammatory factor levels (interleukin IL-6, IL-10, IL-17, and tumor necrosis factor alpha), tight junction-related proteins (Zonula occludens-1, Occludin, and Claudin-5), and small glue plasma cell-associated proteins (Cluster of Differentiation 16/Cluster of Differentiation 206, Matrix metalloproteinase, ionized calcium-binding adapter molecule 1, and C-X3-C Motif Chemokine Ligand 1) 24 h following I/R. Using 16S rRNA gene sequencing and non-targeted metabolomics analysis, we explored the relationship between fecal microecology and serum metabolites. Eventually, we analyzed the correlation between the gut microbiota and plasma metabolic profile as well as the mechanism underlying the SHT-mediated regulation of gut microbiota to protect the BBB following stroke. RESULTS: In IS treatment, SHT is principally involved in reducing neurological injury and the volume of cerebral infarction; protecting the intestinal mucosal barrier; increasing the levels of acetic acid, butyric acid, and propionic acid; promoting the transformation of microglia to the M2 state; reducing inflammatory reactions; and enhancing tight junctions. These therapeutic effects were not observed in the group treated with antibiotics alone or that treated with SHT in combination with antibiotics, thereby indicating SHT plays a therapeutic role through the gut microbiota. CONCLUSION: SHT regulates the gut microbiota, inhibits pro-inflammatory factors in rats with IS, alleviates an inflammatory injury of the BBB, and plays a protective role in the brain.

An empirical analysis of the impact of renewable and non-renewable energy consumption on economic growth and carbon dioxide emissions: evidence from seven Northeast Asian countries.

Oil and natural consumption are non-renewable energy sources that are the main drivers of economic growth, but these energy sources are also the main causes of environmental degradation in Northeast Asian countries. The main objective of this study is to examine the impact of renewable energy consumption, non-renewable energy consumption on CO2 emissions, and economic growth in seven selected Northeast Asian countries during the period 1970-2020. First, the cross-sectional dependence test recommended by Pesaran, Ullah, and Yamagata (2008) concludes that there is no cross-sectional dependence in the panel data model, so it is feasible to use the first-generation panel data methods. Later, cointegration tests proposed by Pedroni (Oxford Bull Econ Stat 61:653-670, 1999, Economet Theor 20:597-625, 2004), Kao (J Econom 90:1-44, 1999), and Westerlund (2007) were adopted, revealing long-term cointegration relationships among model panel variables. Long-term variable coefficient elasticities were detected using the estimation techniques of panel fully modified ordinary least squares (FMOLS) and panel dynamic ordinary least squares (DOLS). Two-way causality of variables was detected using the Dumitrescue-Hurlin (Econ Model 29:1450-1460, 2012) panel causality test. The results of the analysis highlight the significant progressive effects of renewable energy consumption, nonrenewable energy consumption, employed labor force, and capital formation on long-run economic growth. The study also concluded that renewable energy consumption significantly reduced long-term CO2 emissions, while non-renewable energy consumption significantly contributed to long-term CO2 emissions. Estimates from the FMOLS technique reflect a significant progressive effect of GDP and GDP3 on CO2 emissions, while GDP2 has a significant adverse effect on CO2 emissions, thus validating the N-shaped EKC assumption in selected group of countries. Furthermore, the feedback hypothesis is supported based on the two-way causality between renewable energy consumption and economic growth. Strategically, this evidence-based empirical study demonstrates that renewable energy is a valuable process that can protect the environment and contribute to future economic growth in selected countries by addressing energy security and reducing carbon emissions.

The effect of transport infrastructure (road, rail, and air) investments on economic growth and environmental pollution and testing the validity of EKC in China, India, Japan, and Russia.

A key factor in social development and sustainable urban expansion is the establishment of sustainable and affordable transport systems. This study aims to investigate the impact of transport infrastructure investment on environmental degradation and economic growth and to test the validity of the EKC hypothesis in China, India, Russia, and Japan over the period 1995-2020. The results show that GDP has a significant positive effect, and GDP2 and GDP3 have significant adverse effects on environmental degradation, respectively. These results confirm the validity of the inverted U-shaped EKC hypothesis in selected emerging Asian economies. Rail infrastructure investment has significant adverse effects, while road infrastructure investment and aviation infrastructure investment have significant positive effects on environmental degradation. Likewise, the impact of investment in transport infrastructure system (roads, rail, and aviation) on economic growth is positive and statistically significant. Country-level estimates confirm the validity of the inverted U-shaped EKC hypothesis in China, India, and Russia, while the N-shaped EKC is only valid in Japan. Investments in rail infrastructure based on modern rail systems that run on electricity are believed to be less polluting in the transport mix, help create sustainable and safe transport systems, and reduce emissions at the urban and intercity levels in emerging Asian countries. In addition, the growing impact of free trade on environmental pollution should be strengthened to harmonize the strict enforcement of environmental conditions dominated by trade agreements.

Empirical analysis of the impact of China-Japan-South Korea transportation infrastructure investment on environmental degradation and the validity of the environmental Kuznets curve hypothesis.

Building sustainable and affordable transport systems is a key issue for social development and sustainable urban expansion. The study used dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) to examine the impact of transport infrastructure investment on environmental degradation in China, Japan, and South Korea over the period 1995-2020 and the validity of the EKC hypothesis. The results show that GDP has a significant positive effect, and GDP2 and GDP3 have significant adverse effects on environmental degradation, respectively. These results confirm the validity of the inverted U shaped EKC hypothesis in selected Asian countries. Road infrastructure investment has a significant positive effect, while railway infrastructure investment has a significant adverse effect on environmental degradation. Air infrastructure investment and trade opening have a progressive and statistically significant impact on environmental pollution. Modern rail systems that run on electricity are considered less polluting, so the share of rail infrastructure investment in the transport mix can help build sustainable and safe transport systems at the city Centre and intercity levels and reduce emissions in Asian countries. Moreover, strict enforcement of the prevailing environmental conditions of trade agreements should be encouraged to reduce the increasing impact of free trade on environmental pollution.

An empirical analysis of the impact of higher education on economic growth: The case of China.

China's domestic labor market has limited demand for tertiary graduates due to an unbalanced industrial structure, with a weak contribution to economic performance over the past decade. This study estimates the asymmetric effects of higher education progress (highly educated employed workforce), higher education utilization (highly educated unemployed workforce), and the separate effects of higher education utilization interactions with high-tech industries on economic growth in China from 1980 to 2020. Using a Nonlinear Autoregressive Distributed Lag (NARDL) model, this study finds that the expansion of higher education progress (the employed workforce with higher education) promotes economic growth, while contraction of higher education progress (employed workforce with higher education) reduces economic growth. Likewise, an increase in higher education utilization (the unemployed labor force with higher education) suppresses economic growth, while a decline in the higher education utilization (the unemployed labor force with higher education) promotes economic growth. The study also found that the expansion of high-tech industries and government spending on education significantly stimulate economic growth. The moderating role of higher education utilization (unemployed labor force with higher education) in the impact of high-tech industries on economic growth is significantly positive. This study strategically proposes that China's higher-educated unemployed labor force can be adjusted to high-tech industries, which need to be developed equally in all regions. Moreover, the country is required to invest more in higher education and the development of high technological industries across all regions, thus may lead to higher economic growth.

Diagnostic value of neutrophil CD64 combined with CRP for neonatal sepsis: A meta-analysis.

BACKGROUND: Sepsis is the leading cause of morbidity and mortality in newborns. CD64 combined with c-reactive protein (CRP) could improve the sensitivity and specificity of neonatal sepsis diagnosis, but the results were still controversial. Therefore, this meta-analysis was conducted to clarify the importance of CD64 combined with CRP in the diagnosis of neonatal sepsis. METHODS: The researches published as of December 24, 2018 were comprehensively searched in PubMed, Embase (included Embase and Medline), the Cochrane Library and Web of Science. Totally, 8 articles were included, involving 1114 objects. Statistical calculations were performed using Stata14.0 and Review Manager 5.3. RESULTS: The diagnostic accuracy of all included studies was pooled as follows: sensitivity, 0.95 (95% CI: 0.86-0.98); specificity, 0.86 (95% CI: 0.74-0.93); positive likelihood ratio (PLR), 6.8 (95% CI: 3.50-13.20); negative likelihood ratio (NLR), 0.06 (95% CI: 0.02-0.18); diagnostic odds ratio (DOR), 118.0 (95% CI: 25.00-549.00), and the area under the curve (AUC) was 0.96 (95% CI: 0.94-0.97). It was found that heterogeneity was not caused by threshold effect (P = 0.16), but the results of sensitivity (I2 = 87.57%) and specificity (I2 = 89.07%) analyses indicated significant heterogeneity between studies. CONCLUSIONS: The combined application of CD64 and CRP improved the accuracy of neonatal sepsis diagnosis.

A High-Precision Time-Frequency Entropy Based on Synchrosqueezing Generalized S-Transform Applied in Reservoir Detection.

According to the fact that high frequency will be abnormally attenuated when seismic signals travel across reservoirs, a new method, which is named high-precision time-frequency entropy based on synchrosqueezing generalized S-transform, is proposed for hydrocarbon reservoir detection in this paper. First, the proposed method obtains the time-frequency spectra by synchrosqueezing generalized S-transform (SSGST), which are concentrated around the real instantaneous frequency of the signals. Then, considering the characteristics and effects of noises, we give a frequency constraint condition to calculate the entropy based on time-frequency spectra. The synthetic example verifies that the entropy will be abnormally high when seismic signals have an abnormal attenuation. Besides, comparing with the GST time-frequency entropy and the original SSGST time-frequency entropy in field data, the results of the proposed method show higher precision. Moreover, the proposed method can not only accurately detect and locate hydrocarbon reservoirs, but also effectively suppress the impact of random noises.