Social Influence and Trial Willingness of Pecan in China

In view of the recent trade war and the ongoing adversarial relationship between the US and China, it is critical to understand more about China's rising pecan market. The purpose of this research was to investigate factors influencing purchase intentions of pecans in the Chinese collective culture. The proposed research model was based on social influence theory and Hofstede's culture definition and was evaluated using regression analysis based on 441 respondents from an urban center in China. Study results suggest that perceived authority trust and social influence are the two most important variables affecting peoples’ intentions to purchase pecans in China. Study results also provide an applied understanding of the typical person that is most likely to purchase pecans in China

Carbohydrates generated via hot water as catalyst for CO2 reduction reaction

Combining terrestrial biomass with submarine-type hydrothermal environments for CO2 reduction is a possible approach for realizing new energies while achieving sustainable circulation of carbon. Herein, carbohydrateenabled CO2 reduction based on NaHCO3 conversion to formate revealed that hydrothermal environments facilitated direct hydrogen transfer from carbohydrates (glucose, cellulose) to CO2/NaHCO3 with hot water (250–300 °C, 5–20 MPa) acting as homogeneous catalyst in absence of any conventional catalysts giving CO2/ NaHCO3 reduction efficiencies as high as 76% for cellulose. Time-resolved operando hydrothermal DRIFTS spectra of glycolaldehyde in hot water (250 °C, autogenous pressure) verified that water catalyzed NaHCO3 reduction by converting the -CHO group in the carbohydrate to its hydrated state as -CH(OH)2, which enabled NaHCO3 reduction by direct hydrogen transfer and that the ratio of hydrogen transfer from water:- glycolaldehyde for NaHCO3 reduction was about 13:87 on an atom basis. For cellulose exploited as energy input, a greater than 3.4% solar-to-formate efficiency can be theoretically attained, which is unprecedented compared with present literature values. These findings provide basic data for future studies on biomass-enabled CO2 reduction and broaden the scope of hydrothermal chemistry for developing net-zero emission processes

A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer.

The objective of this research was to develop a robust gene expression-based prognostic signature and scoring system for predicting overall survival (OS) of patients with high-grade serous ovarian cancer (HGSOC). Transcriptomic data of HGSOC patients were obtained from six independent studies in the NCBI GEO database. Genes significantly deregulated and associated with OS in HGSOCs were selected using GEO2R and Kaplan-Meier analysis with log-rank testing, respectively. Enrichment analysis for biological processes and pathways was performed using Gene Ontology analysis. A resampling/cross-validation method with Cox regression analysis was used to identify a novel gene expression-based signature associated with OS, and a prognostic scoring system was developed and further validated in nine independent HGSOC datasets. We first identified 488 significantly deregulated genes in HGSOC patients, of which 232 were found to be significantly associated with their OS. These genes were significantly enriched for cell cycle division, epithelial cell differentiation, p53 signaling pathway, vasculature development, and other processes. A novel 11-gene prognostic signature was identified and a prognostic scoring system was developed, which robustly predicted OS in HGSOC patients in 100 sampling test sets. The scoring system was further validated successfully in nine additional HGSOC public datasets. In conclusion, our integrative bioinformatics study combining transcriptomic and clinical data established an 11-gene prognostic signature for robust and reproducible prediction of OS in HGSOC patients. This signature could be of clinical value for guiding therapeutic selection and individualized treatment

Effect of dynamic cerebral autoregulation on the association between deep medullary vein changes and cerebral small vessel disease

Changes in the deep medullary vein (DMV) are reported to be associated with cerebral small vessel disease (CSVD). While the mechanisms of this association are unclear, dynamic cerebral autoregulation (dCA) has been speculated to participate in this association. Thus, we aimed to verify the association between DMV changes and total CSVD burden and further investigate the effect of dCA function on this correlation. In this prospective study, 95 Asian patients aged ≥18 years were included in the final assessment. DMV scores and total CSVD burden were determined using magnetic resonance imaging sequences. Transfer function analysis was performed to analyze dCA function. Generalized linear regressions were used to assess the relationship between DMV changes and total CSVD burden as well as between DMV changes and dCA function. An interaction model was utilized to assess the effect of dCA function on the association between DMV changes and total CSVD burden. Generalized linear models showed a significant positive association between DMV changes and total CSVD burden (p = 0.039) and a significant negative association between DMV changes and dCA function (p = 0.018). The interaction model demonstrated a significant positive interaction of dCA impairment on the association between DMV changes and the total CSVD burden (p = 0.02). Thus, we came to the conclusion that changes in DMV were correlated independently with both CSVD and dCA impairment and furthermore, impaired dCA function play an interaction effect on the association between DMV changes and the total CSVD burden. Our results can help improve the understanding of the complex pathogenesis and progression of CSVD, thereby facilitating early intervention and treatment development

Gut-brain axis: Mechanisms and potential therapeutic strategies for ischemic stroke through immune functions

After an ischemic stroke (IS) occurs, immune cells begin traveling to the brain and immune system from the gut and gastrointestinal tract, where most of them typically reside. Because the majority of the body’s macrophages and more than 70% of the total immune cell pool are typically found within the gut and gastrointestinal tract, inflammation and immune responses in the brain and immune organs require the mobilization of a large number of immune cells. The bidirectional communication pathway between the brain and gut is often referred to as the gut-brain axis. IS usually leads to intestinal motility disorders, dysbiosis of intestinal microbiota, and a leaky gut, which are often associated with poor prognosis in patients with IS. In recent years, several studies have suggested that intestinal inflammation and immune responses play key roles in the development of IS, and thus may become potential therapeutic targets that can drive new therapeutic strategies. However, research on gut inflammation and immune responses after stroke remains in its infancy. A better understanding of gut inflammation and immune responses after stroke may be important for developing effective therapies. This review discusses the immune-related mechanisms of the gut-brain axis after IS and compiles potential therapeutic targets to provide new ideas and strategies for the future effective treatment of IS

DESIGN AND EXPERIMENT OF A COMBINED TYPE SPATIALLY LAYERED PROPORTIONAL FERTILIZATION DEVICE

ABSTRACT To solve the problems of low efficiency, poor fertilizer application, and low fertilizer utilization rate of existing wheat layered fertilization devices (LFD). This paper proposed a layered fertilization mode combining shallow fertilizer application based on rotary tillage and middle/deep fertilizer application of layered fertilizer shovel (LFS), and designed a combined spatial layered fertilization device with a fixed proportion. A discrete element simulation model consisting of soil, LFS and fertilizer was established. Taking the variation coefficients of fertilization amount as the evaluation indicator and changing the sidewall deflection angle, rear inclination angle, upper channel length of LFS, a three-factor three-level quadratic rotational orthogonal experiment was carried out. The optimal parameter combination was obtained: the deflection angle was 9.5°, the inclination angle was 57°, and the channel length was 280 mm. The corresponding variation coefficients of fertilizer application depth were 4.55%, 8.44%, and 6.93% while working stably under the optimal combination, which is consistent with the simulation results. The results showed that LFD can apply fertilizer underground in three layers: 0~10, 15, and 20 cm, with the proportion of shallow, middle, and deep fertilizers being 30%, 35%, and 35%, which can meet the agronomic requirements for winter wheat growth

Cuproptosis in glioblastoma: unveiling a novel prognostic model and therapeutic potential

Glioblastoma, a notably aggressive brain tumor, is characterized by a brief survival period and resistance to conventional therapeutic approaches. With the recent identification of “Cuproptosis,” a copper-dependent apoptosis mechanism, this study aimed to explore its role in glioblastoma prognosis and potential therapeutic implications. A comprehensive methodology was employed, starting with the identification and analysis of 65 cuproptosis-related genes. These genes were subjected to differential expression analyses between glioblastoma tissues and normal counterparts. A novel metric, the “CP-score,” was devised to quantify the cuproptosis response in glioblastoma patients. Building on this, a prognostic model, the CP-model, was developed using Cox regression techniques, designed to operate on both bulk and single-cell data. The differential expression analysis revealed 31 genes with distinct expression patterns in glioblastoma. The CP-score was markedly elevated in glioblastoma patients, suggesting an intensified cuproptosis response. The CP-model adeptly stratified patients into distinct risk categories, unveiling intricate associations between glioblastoma prognosis, immune response pathways, and the tumor’s immunological environment. Further analyses indicated that high-risk patients, as per the CP-model, exhibited heightened expression of certain immune checkpoints, suggesting potential therapeutic targets. Additionally, the model hinted at the possibility of personalized therapeutic strategies, with certain drugs showing increased efficacy in high-risk patients. The CP-model offers a promising tool for glioblastoma prognosis and therapeutic strategy development, emphasizing the potential of Cuproptosis in cancer treatment

Ξc−Ξc′\Xi_c-\Xi_c^{\prime} mixing From Lattice QCD

In heavy quark limit, the lowest-lying charmed baryons with two light quarks can form an SU(3) triplet and sextet. The $\Xi_c$ in the SU(3) triplet and $\Xi_c'$ in the sextet have the same $J^{PC}$ quantum number and can mix due to the finite charm quark mass and the fact the strange quark is heavier than the up/down quark. We explore the $\Xi_c$-$\Xi_c'$ mixing by calculating the two-point correlation functions of the $\Xi_c$ and $\Xi_c'$ baryons from lattice QCD. Based on the lattice data, we adopt two independent methods to determine the mixing angle between $\Xi_c$ and $\Xi_c'$. After making the chiral and continuum extrapolation, it is found that the mixing angle $\theta$ is $1.2^{\circ}\pm0.1^{\circ}$, which seems insufficient to account for the large SU(3) symmetry breaking effects found in weak decays of charmed baryons