Metabolomic profiles and differential metabolites of volatile components in Citrus aurantium Changshan-huyou pericarp during different growth and development stages.

Citrus fruits possess a distinctive aroma and flavor, with Citrus aurantium Changshan-huyou (CACH) standing out due to their considerable edible and medicinal value. However, the volatile components (VOCs) in the CACH pericarp (CP) remain underexplored. In this study, gas chromatography-mass spectrometry (GC-MS) was utilized to qualitatively analyze VOCs in 27 CP samples across different growth stages. A total of 544 VOCs were identified, including 91 terpenoids. The types, quantities and distributions of VOCs were conducted. Detailed discussions on the major terpenoids in CP were also presented. A metabolomics approach combining multivariate statistical analysis with univariate analysis was employed for screening the differential metabolites. The study provides comprehensive insights into the VOCs in CP and citrus plants. Moreover, it delivers the first in-depth analysis of differential metabolites in CP throughout the entire CACH growth and development process, laying a foundation for ongoing research and development of the VOCs in CP.

Global insights on the impact of digital infrastructure on carbon emissions: A multidimensional analysis.

With the swift expansion of global digital infrastructure, understanding its impact on carbon emissions is essential for addressing global warming. This study develops a digital infrastructure indicator system. We use panel data from 83 countries spanning 2005 to 2021 to thoroughly examine the effects and underlying mechanisms of digital infrastructure on carbon emissions. Our findings indicate that digital infrastructure contributes to an increase in carbon emissions worldwide. Mechanism tests suggest that this increase is facilitated by capital agglomeration and fossil energy consumption. However, the impact of digital infrastructure on carbon emissions shows regional variations. In the Arab region, digital infrastructure development seems to reduce carbon emissions, a trend also observed, albeit potentially, in the CIS, Africa, and the Americas. In contrast, Europe and the Asia-Pacific experience a significant surge in carbon emissions due to digital infrastructure. Population density and the proportion of renewable energy emerge as critical threshold variables. Beyond a certain population density, the impact on carbon emissions intensifies, whereas an increase in renewable energy share beyond a specific point mitigates this effect. Robustness tests confirm that digital infrastructure elevates both per capita carbon emissions and carbon intensity, with digital markets and technologies notably amplifying carbon emissions.

Traditional Use, Phytochemistry, Pharmacology, Toxicology and Clinical Applications of Persicae Semen: A Review.

Persicae Semen (Taoren), the seed of mature peaches consumed as both food and medicine, is native to the temperate regions of China, distributed in the provinces of North and East China, and currently cultivated worldwide. The primary components of Persicae Semen include volatile oil, protein, amino acids, amygdalin, and prunasin, all of which have pharmacological properties, such as anti-inflammatory, antioxidant, and immune regulatory effects, and are clinically used in the treatment of gynecological, cardiovascular, cerebrovascular, orthopedic, and digestive system diseases. This review provides a comprehensive perspective on the resource status, ethnopharmacology, phytochemistry, pharmacology, and toxicology, as well as the trend of Persicae Semen patent, global distribution, and clinical applications. This review will help facilitate the development and utilization of Persicae Semen in clinical settings.

Synthesis of non-modified near-infrared carbon dots for hypochlorite detection and cell membrane imaging.

Devising carbon dots with long wavelength emission (red light or near infrared), high selectivity and good bio-compatibility is critical in fluorescence detection and imaging, but achieving this goal remains a great challenge. Herein, near-infrared emissive carbon dots (NIR-CDs) with obvious emission characteristic of 653 nm were synthesized through hydrothermally treatment of toluidine bule and gallic acid. Noticeably, the NIR-CDs exhibited excellent selectivity and sensitivity to hypochlorite (ClO-), and the limit of detection is as low as 42.7 nM. The selective recognition reaction between ClO- and the surface functional groups of NIR-CDs inhibits the fluorescence from NIR-CDs. The quenching mechanism was confirmed by fluorescence lifetime decays, FT-IR spectroscopy and UV-vis absorption spectra. More remarkably, the NIR-CDs have rich hydrophilic groups showed lower cytotoxicity, excellent bio-compatibility and specific cell membrane localization ability. The established spectrofluorometric method based on NIR-CDs has been used to determination of ClO- level in tap water sample, the recoveries were 97.7 %-103.3 %. In addition, the NIR-CDs also has been successfully applied for the imaging of cell membrane. The study provides a novel idea for developing NIR ClO- probe as well as cell membrane localization probe based on CDs, which present bright prospects in real water samples monitoring and cell membrane imaging.

Does natural resource dependence restrict green development? An investigation from the "Belt and road" countries.

Addressing natural resource dependence is integral to achieving the Sustainable Development Goals by promoting economic diversification, environmental sustainability, and climate resilience. This study explores the effect of natural resource dependence on green development by adopting the balanced panel dataset from the "Belt and Road" countries from 2005 to 2019. Notably, the novelty of our analysis lies in the empirical analysis using instrument-based techniques that consolidate the "green development curse hypothesis" in the Belt and Road countries. The mechanism analysis reveals that natural resource dependence curbs green development by weakening innovative capability, disturbing institutional quality, reducing population density, and crowding out human capital. Further, the dynamic panel threshold model handling endogeneity verifies the nonlinear relationship between natural resource dependence and green development. Interestingly, digital trade offers greater "resilience" than traditional trade, correcting the resource curse dilemma. Finally, heterogeneity analyses indicate that the green development curse hypothesis only exists in countries with high-level environmental regulations and resource-based countries.

Interpretable machine learning-based clinical prediction model for predicting lymph node metastasis in patients with intrahepatic cholangiocarcinoma.

OBJECTIVE: Prediction of lymph node metastasis (LNM) for intrahepatic cholangiocarcinoma (ICC) is critical for the treatment regimen and prognosis. We aim to develop and validate machine learning (ML)-based predictive models for LNM in patients with ICC. METHODS: A total of 345 patients with clinicopathological characteristics confirmed ICC from Jan 2007 to Jan 2019 were enrolled. The predictors of LNM were identified by the least absolute shrinkage and selection operator (LASSO) and logistic analysis. The selected variables were used for developing prediction models for LNM by six ML algorithms, including Logistic regression (LR), Gradient boosting machine (GBM), Extreme gradient boosting (XGB), Random Forest (RF), Decision tree (DT), Multilayer perceptron (MLP). We applied 10-fold cross validation as internal validation and calculated the average of the areas under the receiver operating characteristic (ROC) curve to measure the performance of all models. A feature selection approach was applied to identify importance of predictors in each model. The heat map was used to investigate the correlation of features. Finally, we established a web calculator using the best-performing model. RESULTS: In multivariate logistic regression analysis, factors including alcoholic liver disease (ALD), smoking, boundary, diameter, and white blood cell (WBC) were identified as independent predictors for LNM in patients with ICC. In internal validation, the average values of AUC of six models ranged from 0.820 to 0.908. The XGB model was identified as the best model, the average AUC was 0.908. Finally, we established a web calculator by XGB model, which was useful for clinicians to calculate the likelihood of LNM. CONCLUSION: The proposed ML-based predicted models had a good performance to predict LNM of patients with ICC. XGB performed best. A web calculator based on the ML algorithm showed promise in assisting clinicians to predict LNM and developed individualized medical plans.

Balancing growth targets and environmental regulations: An empirical analysis of dual policy impact on corporate environmental responsibility-insights from China.

Balancing economic growth with environmental conservation poses a universal challenge for governments worldwide. This study investigates the intricate interplay between governments' economic-environmental trade-offs and their implementation of policies aimed at promoting Corporate Environmental Responsibility (CER). Given the discretion of Chinese local governments in economic and environmental policy, we take China as a case study. To conduct this research, we first merge critical data on China's economic growth targets and environmental regulations with information on listed enterprises. Then, we employ a "U-shaped" relationship model to examine the impact of these trade-offs on CER implementation. The results reveal that: (1)The effective fulfillment of CER by enterprises is primarily driven by stricter environmental regulations. (2) Economic growth targets can, to some extent, diminish the policy effect of environmental regulations on CER fulfillment. (3)The crowding-out effect of economic growth targets is particularly pronounced within specific subsets of enterprises, including state-owned enterprises, heavily polluting firms, and those facing high profit pressure. These findings imply that when local governments implement contradictory policies, they must consider not only enterprises' political connections and economic contributions but also pay close attention to the survival dilemma of enterprises. This balancing act aims to harmonize conflicting policy objectives. This research deepens the understanding of how institutional and policy frameworks impact enterprise engagement in CER, especially within the context of governments' economic-environmental trade-offs. It sheds light on the strategies employed by China and other emerging economies to effectively leverage contradictory policies to foster sustainable green growth.

The silencing of NREP aggravates OA cartilage damage through the TGF-ß1/Smad2/3 pathway in chondrocytes.

Background: Osteoarthritis (OA) is a common chronic degenerative joint disease. Due to the limited understanding of its complex pathological mechanism, there is currently no effective treatment that can alleviate or even reverse cartilage damage associated with OA. With improvement in public databases, researchers have successfully identified the key factors involved in the occurrence and development of OA through bioinformatics analysis. The aim of this study was to screen for the differentially expressed genes (DEGs) between the normal and OA cartilage through bioinformatics, and validate the function of the TGF-ß1/Smad2/3 pathway-related neuron regeneration related protein (NREP) in the articular cartilage. Methods: The DEGs between the cartilage tissues of OA patients and healthy controls were screened by bioinformatics, and functionally annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The expression levels of the DEG in human and murine OA cartilage was verified by reverse transcription-quantitative PCR (RT-qPCR), Western blotting and immunohistochemistry (IHC). RT-qPCR, Western-blotting, Cell Counting Kit-8(CCK8) and EdU assays were used to evaluate the effects of knocking down NREP in normal chondrocytes, and the molecular mechanisms were investigated by RT-qPCR, Western blotting and IHC. Results: In this study, we identified NREP as a DEG in OA through bioinformatics analysis, and found that NREP was downregulated in the damaged articular cartilage of OA patients and mouse model with surgically-induced OA. In addition, knockdown of NREP in normal chondrocytes reduced their proliferative capacity, which is the pathological basis of OA. At the molecular level, knock-down of NREP inactivated the TGF-ß1/Smad2/3 pathway, resulting in the downregulation of the anabolic markers Col2a1 and Sox9, and an increase in the expression of the catabolic markers MMP3 and MMP13. Conclusion: NREP plays a key role in the progression of OA by regulating the TGF-ß1/Smad2/3 pathway in chondrocytes, and warrants further study as a potential therapeutic target.

Enhancing New Zealand's emissions trading scheme: A comprehensive sector-level assessment for a stronger regulatory framework.

Certain nations have opted for stimulus-based regulations to curtail emissions, build a liveable, environmentally friendly setting, and work towards aspirational mitigation targets. New Zealand (NZ) prefers an Emission Trading Scheme (ETS) to taxation, mitigating emissions on one hand while retaining incentives for economic growth on the other. As a result, NZ has initiated a legal framework since 2008 to allow its economic sectors to engage in ETS and minimize emissions. Yet, selecting the appropriate sectors and effectively adjusting sector-specific regulations remain critical and complex challenges in the global design of ETS since both excessive and insufficient intervention can lead to inefficiencies in the system's functioning. Therefore, this study begins validating the NZ ETS's abatement potential regarding sectoral carbon intensity by executing the double machine learning techniques, consolidating the ETS efficacy that has robustly mitigated sectoral carbon intensity in NZ during 2006-2020. However, this conclusion seems invalid at the disaggregated level when focusing on forward-backward linkages, where NZ's input-output tables furnish a compelling scenario of sectoral dependencies and the products (residuals) they provide. Altogether, the regulatory requirements are either too strict or too lax, leaving out five of the 24 (as a whole) key sectors. Rather, the ETS could be powerful, providing these five key sectors are well tackled, necessitating a reformulation of the ongoing ETS regulatory regime.

Development and evaluation of short-form version of the Constitution in Chinese Medicine Questionnaire: study a new and best brief instrument of Chinese medicine for health management.

BACKGROUND: More efficient instruments for body constitution identification are needed for clinical practice. We aimed to develop the short-form version of the Constitution in Chinese Medicine Questionnaire (CCMQ) and evaluate for health management. METHODS: First, the short forms were developed through expert survey, classical test theory (CTT), and modern item response (IRT) based on the CCMQ. A combination of e-mail and manual methods was used in expert survey. Then, five indexes of CTT including criteria value-critical ratio, correlation coefficient, discrete tendency, internal consistency, and factor loading were used. And, IRT method was used through analyzing the discrimination and difficulty parameters of items. Second, the three top-ranked items of each constitution scale were selected for the simplified CCMQ, based on the three combined methods of different conditions and weights. Third, The psychometric properties such as completion time, validity (Construct, criterion, and divergent validity), and reliability (test-retest and internal consistency reliability) were evaluated. Finally, the diagnostic validity of the best short-form used receiver operating characteristic (ROC) curve. RESULTS: Three short-form editions were developed, and retained items 27, 23 and 27, which are named as WangQi nine body constitution questionnaire of Traditional Chinese Medicine (short-form) (SF-WQ9CCMQ)- A, B, and C, respectively. SF-WQ9CCMQ- A is showed the best psychometric property on Construct validity, Criterion validity, test-retest reliability and internal consistency reliability. The diagnostic validity indicated that the area under the ROC curve was 0.928 (95%CI: 0.924-0.932) for the Gentleness constitution scale, and were 0.895-0.969 and 0.911-0.981 for unbalance constitution scales using the cut-off value of the original CCMQ as 40 ("yes" standard) and 30 ("tendency" standard), respectively. CONCLUSIONS: Our study successfully developed a well short-form which has good psychometric property, and excellent diagnostic validity consistent with the original. New and simplified instrument and opportunity are provided for body constitution identification, health management and primary care implementation.

How financial clustering influences China's green development: Mechanism investigation and empirical discussion.

Understanding the significance of financial clustering in the context of green development holds immense importance for China as it strives towards achieving high-quality green development. Using a balanced panel dataset encompassing China's 283 cities from 2009 to 2020, we aim to explore the impact of financial clustering on green development from both linear and nonlinear perspectives. Empirical evidence suggests that when the level of financial clustering increases by 1%, the city-level green development increases by 0.1012%. A mediation effect model certifies that there are three essential channels through which financial clustering robustly boosts green development: technical, structural and scale effects. Subsequently, a novel program handling endogeneity is designed and verifies the nonlinear nexus between financial clustering and green development. Moreover, the spatial Durbin model demonstrates that financial clustering significantly sustains local green development, despite its relatively weak spill over effects. Heterogeneity analysis presents that the promoting effect is particularly predominant in Central China, as well as in cities characterized by high levels of financial clustering and large population sizes.

Appraising the role of the digital economy in global decarbonization: A spatial non-linear perspective on globalization.

In the context of globalization, the role of the digital economy in carbon emissions may generate spatial spill over effects. This study comprehensively applies a spatial model to understand the nexus between the digital economy and carbon emissions in 67 economies from 2010 to 2019. Specifically, this study contributes by introducing a spatial panel threshold model, which helps to present the new evidence regarding decarbonization process. Empirical findings exemplify that the digital economy remarkably reduces local carbon emissions, with the positive spatial spill over effects being salient. The spatial moderating effect model uncover that globalization positively affects the nexus between the digital economy and carbon emissions. Interestingly, the spatial panel threshold model designates that the digital economy's reduction effect on local carbon emissions will be tightened, whereas the positive spatial spill over effects turn negative only when globalization surpasses a threshold. Our model has the potential to explain some results that traditional models cannot reach.

Neurokinin-1 receptor drives PKCɑ-AURKA/N-Myc signaling to facilitate the neuroendocrine progression of prostate cancer.

The widespread application of antiandrogen therapies has aroused a significant increase in the incidence of NEPC, a lethal form of the disease lacking efficient clinical treatments. Here we identified a cell surface receptor neurokinin-1 (NK1R) as a clinically relevant driver of treatment-related NEPC (tNEPC). NK1R expression increased in prostate cancer patients, particularly higher in metastatic prostate cancer and treatment-related NEPC, implying a relation with the progression from primary luminal adenocarcinoma toward NEPC. High NK1R level was clinically correlated with accelerated tumor recurrence and poor survival. Mechanical studies identified a regulatory element in the NK1R gene transcription ending region that was recognized by AR. AR inhibition enhanced the expression of NK1R, which mediated the PKCα-AURKA/N-Myc pathway in prostate cancer cells. Functional assays demonstrated that activation of NK1R promoted the NE transdifferentiation, cell proliferation, invasion, and enzalutamide resistance in prostate cancer cells. Targeting NK1R abrogated the NE transdifferentiation process and tumorigenicity in vitro and in vivo. These findings collectively characterized the role of NK1R in tNEPC progression and suggested NK1R as a potential therapeutic target.

Impact of regional energy allocation distortion on carbon emission efficiency: Evidence from China.

The free flow of energy cannot be fully achieved in China's energy market because of incomplete market-oriented reform, resulting in energy allocation distortion, which has hampered carbon emissions reduction. However, the extent of energy allocation distortion and its role in carbon emission efficiency remain unexplored. Therefore, this study aims to measure energy allocation distortion and investigate its impact on carbon emission efficiency. For this purpose, first, we derive energy allocation distortion based on a production function and carbon emission efficiency using a meta-frontier non-radial Malmquist index. To effectively address the endogeneity issue, we use a generalized method of moments model to estimate the impact of energy allocation distortion on carbon emission efficiency. Second, we further explore the distortionary mechanism of carbon emission efficiency associated with energy allocation and analyze the asymmetric effect of energy allocation distortion on carbon emission efficiency. The results show a certain degree of energy allocation distortion throughout the country, and disparity exists among different regions. The average value of carbon emission efficiency in the eastern region is 1.0286, well ahead of the national average, demonstrating better performance than other regions. Energy allocation distortion negatively affects carbon emission efficiency, with a 1% increase in energy allocation distortion leading to a 0.251% decrease in carbon emission efficiency. Technological progress, the structure of energy consumption, and industrial structure are important transmission channels through which energy allocation affects carbon emission efficiency. The study contributes to uncovering regional energy allocation distortion and its impacts on carbon emission efficiency and providing strategic policy recommendations for improving energy allocation efficiency.

EphA2 is a functional entry receptor for HCMV infection of glioblastoma cells.

Human cytomegalovirus (HCMV) infection is associated with human glioblastoma, the most common and aggressive primary brain tumor, but the underlying infection mechanism has not been fully demonstrated. Here, we show that EphA2 was upregulated in glioblastoma and correlated with the poor prognosis of the patients. EphA2 silencing inhibits, whereas overexpression promotes HCMV infection, establishing EphA2 as a crucial cell factor for HCMV infection of glioblastoma cells. Mechanistically, EphA2 binds to HCMV gH/gL complex to mediate membrane fusion. Importantly, the HCMV infection was inhibited by the treatment of inhibitor or antibody targeting EphA2 in glioblastoma cells. Furthermore, HCMV infection was also impaired in optimal glioblastoma organoids by EphA2 inhibitor. Taken together, we propose EphA2 as a crucial cell factor for HCMV infection in glioblastoma cells and a potential target for intervention.

SOX2 downregulation of PML increases HCMV gene expression and growth of glioma cells.

The presence of human cytomegalovirus (HCMV) in glioblastoma (GBM) and improved outcomes of GBM patients receiving therapies targeting the virus have implicated HCMV in GBM progression. However, a unifying mechanism that accounts for the contribution of HCMV to the malignant phenotype of GBM remains incompletely defined. Here we have identified SOX2, a marker of glioma stem cells (GSCs), as a key determinant of HCMV gene expression in gliomas. Our studies demonstrated that SOX2 downregulated promyelocytic leukemia (PML) and Sp100 and consequently facilitated viral gene expression by decreasing the amount of PML nuclear bodies in HCMV-infected glioma cells. Conversely, the expression of PML antagonized the effects of SOX2 on HCMV gene expression. Furthermore, this regulation of SOX2 on HCMV infection was demonstrated in a neurosphere assay of GSCs and in a murine xenograft model utilizing xenografts from patient-derived glioma tissue. In both cases, SOX2 overexpression facilitated the growth of neurospheres and xenografts implanted in immunodeficient mice. Lastly, the expression of SOX2 and HCMV immediate early 1 (IE1) protein could be correlated in tissues from glioma patients, and interestingly, elevated levels of SOX2 and IE1 were predictive of a worse clinical outcome. These studies argue that HCMV gene expression in gliomas is regulated by SOX2 through its regulation of PML expression and that targeting molecules in this SOX2-PML pathway could identify therapies for glioma treatment.

Construction and characterization of a synthesized herpes simplex virus H129-Syn-G2.

Herpes simplex virus type 1 (HSV-1) causes lifelong infections worldwide, and currently there is no efficient cure or vaccine. HSV-1-derived tools, such as neuronal circuit tracers and oncolytic viruses, have been used extensively; however, further genetic engineering of HSV-1 is hindered by its complex genome structure. In the present study, we designed and constructed a synthetic platform for HSV-1 based on H129-G4. The complete genome was constructed from 10 fragments through 3 rounds of synthesis using transformation-associated recombination (TAR) in yeast, and was named H129-Syn-G2. The H129-Syn-G2 genome contained two copies of the gfp gene and was transfected into cells to rescue the virus. According to growth curve assay and electron microscopy results, the synthetic viruses exhibited more optimized growth properties and similar morphogenesis compared to the parental virus. This synthetic platform will facilitate further manipulation of the HSV-1 genome for the development of neuronal circuit tracers, oncolytic viruses, and vaccines.

Facile synthesis of non-modified yellow emission silicon quantum dots and their visualization of hydrogen sulfide in living cells and onion tissues.

Yellow fluorescent silicon quantum dots (y-SiQDs) with 22.2% fluorescence quantum yield were synthesized by a simple hydrothermal method using 3-glycidoxypropyl triethoxysilane (GOTS) and m-aminophenol. The excitation wavelength is 550 nm with an emission wavelength of 574 nm, which effectively avoids the interference of biological autofluorescence. Notably, the synthesis approach does not require any post-modification and the y-SiQDs can be directly used for hydrogen sulfide (H2S) quantification due to static quenching. It exhibits high sensitivity and excellent selectivity for H2S with a 0.2-10 µM (R2 = 0.9953) linear range and detection limit of 54 nM. y-SiQDs have excellent stability and biocompatibility and can be used for H2S imaging in living cells and onion tissues.

Human cytomegalovirus pUL97 upregulates SOCS3 expression via transcription factor RFX7 in neural progenitor cells.

Congenital human cytomegalovirus (HCMV) infection causes severe damage to the fetal brain, and the underlying mechanisms remain elusive. Cytokine signaling is delicately controlled in the fetal central nervous system to ensure proper development. Here we show that suppressor of cytokine signaling 3 (SOCS3), a negative feedback regulator of the IL-6 cytokine family signaling, was upregulated during HCMV infection in primary neural progenitor cells (NPCs) with a biphasic expression pattern. From viral protein screening, pUL97 emerged as the viral factor responsible for prolonged SOCS3 upregulation. Further, by proteomic analysis of the pUL97-interacting host proteins, regulatory factor X 7 (RFX7) was identified as the transcription factor responsible for the regulation. Depletion of either pUL97 or RFX7 prevented the HCMV-induced SOCS3 upregulation in NPCs. With a promoter-luciferase activity assay, we demonstrated that the pUL97 kinase activity and RFX7 were required for SOCS3 upregulation. Moreover, the RFX7 phosphorylation level was increased by either UL97-expressing or HCMV-infection in NPCs, suggesting that pUL97 induces RFX7 phosphorylation to drive SOCS3 transcription. We further revealed that elevated SOCS3 expression impaired NPC proliferation and migration in vitro and caused NPCs migration defects in vivo. Taken together, these findings uncover a novel regulatory mechanism of sustained SOCS3 expression in HCMV-infected NPCs, which perturbs IL-6 cytokine family signaling, leads to NPCs proliferation and migration defects, and consequently affects fetal brain development.