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The aim of this study is to investigate the relationship between green technology R&D investment and corporate performance (ROA) of 44 Beijing-listed energy companies from 2016 to 2021 using a threshold regression model. The results show that there is an inverse W-shaped nonlinear relationship between green technology R&D investment and firm performance. This means that green technology R&D investments only have a positive effect on firm performance within an appropriate green technology R&D investment interval, and a negative effect occurs outside this interval. Additionally, the study analyses the influence of three threshold variables (firm size, capital structure and capital density) on the relationship between green technology R&D investment and firm performance. The results show that firm size has an inversely- U-shaped relationship, the capital structure has a negative nonlinear relationship and the capital density has an inversely N-shaped relationship. Optimal intervals are observed for all three threshold variables. Moreover, the study shows that the green technology R&D investment intensity has a lagged effect on firm performance. The positive influence weakens over time, and the negative influence becomes more pronounced. The findings of the study can help energy companies to develop green technology R&D innovation strategies, such as differentiating green technology R&D expenditures for companies in different development situations. It can also exploit the driving effect of green technology R&D investment on firm performance in the context of China’s energy sector restructuring.

Understanding how industrial agglomeration affects agricultural green production efficiency is essential for green agricultural development. This study uses the super-efficient Epsilon-Based Measure (EBM) model and Global Malmquist–Luenberger (GML) index to measure and analyze the spatial and temporal evolution characteristics and core sources of dynamics of agricultural green production efficiency in China by using panel data from 30 Chinese provinces from 2006 to 2020. It also empirically investigates the relationships between industrial agglomeration, land transfer, and agricultural production efficiency. By using fixed, intermediary, and threshold effect models, the internal links between industrial agglomeration, land transfer, and agricultural green production efficiency are examined. The findings indicate the following. (1) The green production efficiency of Chinese agriculture exhibits the regional characteristics of being “high in the west and low in the east, high in the south and low in the north” in terms of space; in terms of time, the overall trend is that green production technology efficiency is growing, with an average annual growth rate of 11.45%, and the growth primarily depends on the “single-track drive” of green technological progress. (2) Industrial agglomeration significantly affects agricultural green production efficiency, green technology efficiency, and green technology change; the corresponding coefficient values are 0.115, 0.093, and 0.022. (3) According to the mechanism-of-action results, land transfer mediates the effects of industrial agglomeration on agricultural green production efficiency, green technology efficiency, and green technology change. These effects have effect values of 28.48%, 27.91%, and 47.75%, respectively. (4) The threshold effect’s findings demonstrate a double threshold effect of industrial agglomeration on the green production efficiency of agriculture in terms of land transfer, with threshold values of 1.468 and 3.891, respectively. As a result, this study suggests adhering to the idea of synergistic development, promoting agricultural green development, strengthening the development of industrial agglomerations, promoting the quality and efficiency of industry, improving land-transfer mechanisms, and placing a focus on resource efficiency improvements, as well as other policy recommendations.

The achievement of China’s low-carbon development and carbon neutrality depends heavily on the decrease of manufacturing carbon emissions. From coagglomeration’s dynamic evolution perspective, by using panel-threshold-STIRPAT and mediation-STIRPAT models, this study examines the relationships among industrial coagglomeration, green innovation, and manufacturing carbon emissions and explores the direct and indirect function mechanisms. Panel data of China’s 30 provinces from 2010 to 2019 are employed. The results imply that, first, the impact of industrial coagglomeration on manufacturing carbon emissions is nonlinear and has significant threshold effects. Industrial coagglomeration negatively affects manufacturing carbon emissions, and as the coagglomeration level deepens, the negative effect has a diminishing trend in marginal utility. Once the coagglomeration degree exceeds a certain threshold, the negative impact becomes insignificant. At present, for 90% of China’s regions, an increase in industrial coagglomeration level can help reduce manufacturing carbon emissions. Second, green innovation is a vital intermediary between industrial coagglomeration and manufacturing carbon emissions. It is a partial intermediary when industrial coagglomeration is at a relatively lower-level stage and a complete intermediary when industrial coagglomeration is at a relatively higher-level stage. These findings reveal the significance of optimizing industrial coagglomeration and the level and efficiency of green innovation to decrease carbon emissions.

The impact of environmental regulations (ER) on haze pollution control has been continuously debated in the field of sustainable development. This paper explores the direct and indirect threshold effects of ER on haze pollution, and five underlying mechanisms—technological innovation (TI), industrial structure (IS), foreign direct investment (FDI), urbanization (UR), and electricity consumption (EC)—are adopted to investigate the indirect threshold effects. Panel data, over the period 2008–2018, of 284 Chinese cities were used and the threshold effects were predicted endogenously based on the panel smooth transition regression (PSTR) model. The results showed the following: (1) For the direct threshold effect, there exists a U-shaped relationship between ER and haze pollution. ER significantly reduced haze pollution when ER < 38.86 due to “cost effects”. However, ER increased haze pollution after the threshold owing to the “green paradox”, which was not significant. (2) For the indirect threshold effect, when TI = 0.37, IS = 39.61, FDI = 7.25, and UR = 42.86, the relationships between ER and haze pollution changed. The changes and corresponding reasons for the indirect threshold effects are discussed in detail. (3) After a comprehensive analysis, the threshold effects have obvious regional distribution characteristics and internal connections. Finally, based on the results, it is essential for governments to enact appropriate environmental regulatory policies and enhance inter-regional synergies in environmental governance.

Based on the 30-province panel data in China during 2005-2018, this paper uses the DEA-SBM model and DEA-Malmquist model to measure rural financial efficiency and agricultural technological progress respectively and then uses the mediating effect model to analyze the linear influence. The results show that rural financial efficiency and agricultural technological progress both can inhibit agricultural carbon emissions, while agricultural technological progress plays a mediating role when rural financial efficiency influences agricultural carbon emissions. What’s more, this paper uses the threshold effect model to analyze the non-linear influence. The findings reveal that when rural financial efficiency improves, the effects of rural financial efficiency and agricultural technology advances on agricultural carbon emissions shift from promoter to inhibitor.

Rationale Endogenous opioids inhibit nociceptive processing and promote the experience of pleasure. It has been proposed that pain and pleasure lie at opposite ends of an affective spectrum, but the relationship between pain and pleasure and the role of opioids in mediating this relationship has not been tested. Objectives Here, we used obese individuals as a model of a dysfunctional opioid system to assess the role of the endogenous opioid peptide, beta-endorphin, on pain and pleasure sensitivity. Methods Obese (10M/10F) and age- and gender-matched non-obese (10M/10F) controls were included in the study. Pain sensitivity using threshold, tolerance, and subjective rating assessments and perceived sweet pleasantness using sucrose solutions were assessed in two testing sessions with placebo or the opioid antagonist, naltrexone (0.7 mg/kg body weight). Beta-endorphin levels were assessed in both sessions. Results and conclusions Despite having higher levels of baseline beta-endorphin and altered beta-endorphin-reactivity to naltrexone, obese individuals reported a similar increase in pain and decrease in pleasantness following naltrexone compared to non-obese individuals. Beta-endorphin levels did not correlate with pain or pleasantness in either group, but naltrexone-induced changes in pain and pleasantness were mildly correlated. Moreover, naltrexone-induced changes in pain were related to depression scores, while naltrexone-induced changes in sweet pleasantness were related to anxiety scores, indicating that pain and pleasantness are related, but influenced by different processes.

Relevant studies have demonstrated that urban green spaces composed of various types of plants are able to alleviate the morbidity and mortality of respiratory diseases, by reducing air pollution levels. In order to explore the relationship between the spatial pattern of urban green spaces and air pollutant concentrations, this study takes 37 garden cities with subtropical monsoon climate in China as the research object and selects the urban air quality monitoring data and land use type data in 2019 to analyze the relationship between the spatial pattern and the air pollutant concentration through the landscape metrics model and spatial regression model. Moreover, the threshold effect of the impact of green space on air pollutant concentrations is estimated, as well. The results showed that the spatial pattern of urban green space was significantly correlated with the concentrations of PM2.5 (PM with aerodynamic diameters of 2.5 mmor less), NO2 (Nitrogen Dioxide), and SO2 (Sulfur dioxide) pollutants in the air, while the concentrations of PM10 (PM with aerodynamic diameters of 10 mmor less) pollutants were not significantly affected by the green space pattern. Among them, the patch shape index (LSI), patch density (PD) and patch proportion in landscape area (PLAND) of forest land can affect the concentration of PM2.5, NO2, and SO2, respectively. The PLAND, PD, and LSI of grassland and farmland can also have an additional impact on the concentration of SO2 pollutants. The study also found that there was a significant threshold effect within the impact mechanism of urban green space landscape pattern indicators (LSI, PD, PLAND) on the concentrations of PM2.5, NO2, and SO2 air pollutants. The results of this study not only clarified the impact mechanism of the spatial pattern of urban green space on air pollutant concentrations but also provided quantitative reference and scientific basis for the optimization and updating of urban green space to promote public health.

Natural genetic variation can have a pronounced influence on human taste perception, which in turn may influence food preference and dietary choice. Genome-wide association studies represent a powerful tool to understand this influence. To help optimize the design of future genome-wide-association studies on human taste perception we have used the well-known TAS2R38-PROP association as a tool to determine the relative power and efficiency of different phenotyping and data-analysis strategies. The results show that the choice of both data collection and data processing schemes can have a very substantial impact on the power to detect genotypic variation that affects chemosensory perception. Based on these results we provide practical guidelines for the design of future GWAS studies on chemosensory phenotypes. Moreover, in addition to the TAS2R38 gene past studies have implicated a number of other genetic loci to affect taste sensitivity to PROP and the related bitter compound PTC. None of these other locations showed genome-wide significant associations in our study. To facilitate further, target-gene driven, studies on PROP taste perception we provide the genome-wide list of p-values for all SNPs genotyped in the current study.

RationaleMinocycline, a tetracycline antibiotic, inhibits activation of microglia. In preclinical studies, minocycline prevented development of opioid tolerance and opioid-induced hyperalgesia (OIH). The goal of this study was to determine if minocycline changes pain threshold and tolerance in individuals with opioid use disorder who are maintained on agonist treatment.MethodsIn this double-blind, randomized human laboratory study, 20 participants were randomized to either minocycline (200 mg/day) or placebo treatment for 15 days. The study had three test sessions (days 1, 8, and 15 of treatment) and one follow-up visit 1 week after the end of treatment. In each test session, participants were assessed on several subjective and cognitive measures, followed by assessment of pain sensitivity using the Cold Pressor Test (CPT). Daily surveys and cognitive measures using Ecological Momentary Assessment (EMA) were also collected four times a day on days 8 through 14 of treatment, and proinflammatory serum cytokines were assessed before and on the last day of treatment.ResultsMinocycline treatment did not change pain threshold or tolerance on the CPT. Similarly, minocycline did not change severity of pain, opioid craving, withdrawal, or serum cytokines. Minocycline treatment increased accuracy on a Go/No-Go task.ConclusionsWhile these findings do not support minocycline’s effects on OIH, minocycline may have a potential use as a cognitive enhancer for individuals with opioid use disorder, a finding that warrants further systematic studies.

This trial assessed the efficacy of MR309 (a novel selective sigma-1 receptor ligand previously developed as E-52862) in ameliorating oxaliplatin-induced peripheral neuropathy (oxaipn). A discontinuous regimen of MR309 (400 mg/day, 5 days per cycle) was tested in patients with colorectal cancer receiving FOLFOX in a phase II, randomized, double-blind, placebo-controlled, multicenter clinical trial. Outcome measures included changes in 24-week quantitative measures of thermal sensitivity and total neuropathy score. In total, 124 patients were randomized (1:1) to MR309 or placebo. Sixty-three (50.8%) patients withdrew prematurely before completing 12 planned oxaliplatin cycles. Premature withdrawal because of cancer progression was less frequent in the MR309 group (7.4% vs 25.0% with placebo; p = 0.054). MR309 significantly reduced cold pain threshold temperature [mean treatment effect difference (SE) vs placebo: 5.29 (1.60)°C; p = 0.001] and suprathreshold cold stimulus-evoked pain intensity [mean treatment effect difference: 1.24 (0.57) points; p = 0.032]. Total neuropathy score, health-related quality-of-life measures, and nerve-conduction parameters changed similarly in both arms, whereas the proportion of patients with severe chronic neuropathy (National Cancer Institute Common Terminology Criteria for Adverse Events ≥ 3) was significantly lower in the MR309 group (3.0% vs 18.2% with placebo; p = 0.046). The total amount of oxaliplatin delivered was greater in the active arm (1618.9 mg vs 1453.8 mg with placebo; p = 0.049). Overall, 19.0% of patients experienced at least 1 treatment-related adverse event (25.8% and 11.9% with MR309 and placebo, respectively). Intermittent treatment with MR309 was associated with reduced acute oxaipn and higher oxaliplatin exposure, and showed a potential neuroprotective role for chronic cumulative oxaipn. Furthermore, MR309 showed an acceptable safety profile.