The influence of drug-induced metabolic enzyme activity inhibition and CYP3A4 gene polymorphism on aumolertinib metabolism.

The purpose of this study is to clarify the drug interaction profile of aumolertinib, and the influence of CYP3A4 genetic polymorphism on aumolertinib metabolic characteristics. Through microsomal enzyme reactions, we screened 153 drugs and identified 15 that significantly inhibited the metabolism of aumolertinib. Among them, telmisartan and carvedilol exhibited potent inhibitory activities in rat liver microsomes (RLM) and human liver microsomes (HLM). In vivo, the pharmacokinetic parameters of aumolertinib, including AUC and Cmax, were significantly altered when co-administered with carvedilol, with a notable decrease in the clearance rate CLz/F. Interestingly, the pharmacokinetic parameters of the metabolite HAS-719 exhibited a similar trend as aumolertinib when co-administered. Mechanistically, both telmisartan and carvedilol exhibited a mixed-type inhibition on the metabolism of aumolertinib. Additionally, we used a baculovirus-insect cell expression system to prepare 24 recombinant CYP3A4 microsomes and obtained enzymatic kinetic parameters using aumolertinib as a substrate. Enzyme kinetic studies obtained the kinetic parameters of various CYP3A4 variant-mediated metabolism of aumolertinib. Based on the relative clearance rates, CYP3A4.4, 5, 7, 8, 9, 12, 13, 14, 17, 18, 19, 23, 24, 33, and 34 showed significantly lower clearance rates compared to the wild-type. Among the different CYP3A4 variants, the inhibitory potency of telmisartan and carvedilol on the metabolism of aumolertinib also varied. The IC50 values of telmisartan and carvedilol in CYP3A4.1 were 6.68 ± 1.76 µM and 0.60 ± 0.25 µM, respectively, whereas in CYP3A4.12, the IC50 exceeded 100 µM. Finally, we utilized adeno-associated virus to achieve liver-specific high expression of CYP3A4*1 and CYP3A4*12. In the group with high expression of the less active CYP3A4*12, the magnitude of the drug-drug interaction was significantly attenuated. In conclusion, CYP3A4 genetic polymorphism not only influences the pharmacokinetic characteristics of aumolertinib, but also the inhibitory potency of telmisartan and carvedilol on it.

Cyy-287, a novel pyrimidine-2,4-diamine derivative, efficiently mitigates inflammatory responses, fibrosis, and lipid synthesis in obesity-induced cardiac and hepatic dysfunction.

Background: Inflammation and metabolic disorders are important factors in the occurrence and development of obesity complications. In this study, we investigated the protective effect and underlying mechanism of a novel pyrimidine-2,4-diamine derivative, Cyy-287, on mice fed a high-fat diet (HFD). Methods: The mice were randomly separated into four groups (n ≥ 7): control (regular diet), HFD, HFD with Cyy-287 (5 mg/kg), and HFD with Cyy-287 (20 mg/kg) following HFD feeding for 10 weeks. After a 10-week administration, ALT and AST enzymes, echocardiography, immunohistochemical (IHC), Western blot (WB), Masson and Sirius Red staining were used to evaluate functional and morphological changes to the heart and liver. Microsomes from the mouse liver were extracted to quantify the total amount of CYP450 enzymes after drug treatment. Results: Cyy-287 decreased the levels of serum glucose, LDL, TC, ALT, and AST activities in HFD-treated mice. However, Cyy-287 administration increased ejection fraction (EF) and fractional shortening (FS) index of the heart. Cyy-287 inhibited histopathological changes in the heart and liver; decreased inflammatory activity; significantly diminished p38 mitogen-activated protein kinase (MAPK), the nuclear factor-kappa B (NF-κB) axis, and sterol regulatory element-binding protein-1c (SREBP-1c); and upregulated the AMP-activated protein kinase (AMPK) pathway in HFD-treated mice. Cyy-287 restored the content of hepatic CYP450 enzymes. Conclusion: These findings demonstrated that Cyy-287 protected heart and liver cells from obesity-induced damage by inhibiting inflammation, fibrosis, and lipid synthesis.

Gene Polymorphisms and Drug-Drug Interactions Determine the Metabolic Profile of Blonanserin.

This study aimed to evaluate the effects of cytochrome P450 3A4 (CYP3A4) gene polymorphism and drug interaction on the metabolism of blonanserin. Human recombinant CYP3A4 was prepared using the Bac-to-Bac baculovirus expression system. A microsomal enzyme reaction system was established, and drug-drug interactions were evaluated using Sprague-Dawley rats. Ultra-performance liquid chromatography-tandem mass spectrometry was used to detect the concentrations of blonanserin and its metabolite. Compared with wild type CYP34A, the relative clearance of blonanserin by CYP3A4.29 significantly increased to 251.3%, while it decreased notably with CYP3A4.4, 5, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 23, 24, 28, 31, 33, and 34, ranging from 6.09% to 63.34%. Among 153 tested drugs, nimodipine, felodipine, and amlodipine were found to potently inhibit the metabolism of blonanserin. Moreover, the inhibitory potency of nimodipine, felodipine, and amlodipine varied with different CYP3A4 variants. The half-maximal inhibitory concentration and enzymatic kinetics assay demonstrated that the metabolism of blonanserin was noncompetitively inhibited by nimodipine in rat liver microsomes and was inhibited in a mixed manner by felodipine and amlodipine in both rat liver microsomes and human liver microsomes. When nimodipine and felodipine were coadministered with blonanserin, the area under the blood concentration-time curve (AUC)(0-t), AUC(0-∞), and C max of blonanserin increased. When amlodipine and blonanserin were combined, the C max of blonanserin C increased remarkably. The vast majority of CYP3A4 variants have a low ability to catalyze blonanserin. With combined administration of nimodipine, felodipine, and amlodipine, the elimination of blonanserin was inhibited. This study provides the basis for individualized clinical use of blonanserin. SIGNIFICANCE STATEMENT: The enzyme kinetics of novel CYP3A4 enzymes for metabolizing blonanserin were investigated. Clearance of blonanserin by CYP3A4.4, 5, 7-10, 12-14, 16-18, 23-24, 28, 31, 33, and 34 decreased notably, but increased with CYP3A4.29. Additionally, we established a drug interaction spectrum for blonanserin, in which nimodipine, felodipine, and amlodipine kinetics exhibited mixed inhibition. Moreover, their inhibitory potencies decreased with CYP3A4.4 and 5 compared to CYP3A4.1. This study provides essential data for personalized clinical use of blonanserin.

Functional evaluation of CYP2C19 and CYP3A4 gene polymorphism on ibuprofen metabolism.

AIM: Ibuprofen is the most commonly used analgesic. CYP polymorphisms are mainly responsible for the differences in drug metabolism among individuals. Variations in the ability of populations to metabolize ibuprofen can lead to drug exposure events. The aim of this study was to evaluate the effects of CYP2C19 and CYP3A4 polymorphisms on ibuprofen metabolism in a Chinese population. METHODS: First, 31 CYP2C19 and 12 CYP3A4 microsomal enzymes were identified using an insect expression system. Then, variants were evaluated using a mature incubation system. Moreover, ibuprofen metabolite content was determined via ultra-performance liquid chromatography-tandem mass spectrometry analysis. Finally, kinetic parameters of CYP2C19 and CYP3A4 genotypes were determined via Michaelis-Menten curve fitting. RESULTS: Most variants exhibited significantly altered intrinsic clearance compared to the wild type. In the CYP2C19 metabolic pathway, seven variants exhibited no significant alterations in intrinsic clearance (CLint), six variants exhibited significantly high CLint (121-291%), and the remaining 15 variants exhibited substantially reduced CLint (1-71%). In the CYP3A4 metabolic pathway, CYP3A4*30 was not detected in the metabolite content due to the absence of activity, and 10 variants exhibited significantly reduced CLint. CONCLUSION: To the best of our knowledge, this is the first study to assess the kinetic characteristics of 31 CYP2C19 and 12 CYP3A4 genotypes on ibuprofen metabolism. However, further studies are needed on poor metabolizers as they are more susceptible to drug exposure. Our findings suggest that the kinetic characteristics in combination with artificial intelligence to predict the toxicity of ibuprofen and reduce any adverse drug reactions.

Untangling the causal mechanisms and spatial dynamics of digital financial development's impact on energy intensity: insights from panel data of Chinese provinces.

The prime focus of the present investigation delves into the linkage between digital financial services and energy intensity within the geographic confines of China, utilizing provincial-level panel data spanning from 2011 to 2021. Digital finance has rapidly developed due to changes in information technology, and its role in achieving green transformation, reducing energy consumption, and lowering energy intensity in Chinese society is critical. By conducting empirical analysis utilizing diverse models, we have tested our hypotheses and found that digital finance's improvement can contribute to the reduction in energy intensity at the regional level while still considering endogeneity concerns. This effect is mediated by the promotion of technological innovation and the facilitation of green development in industries. Digital finance's impact on energy intensity is contingent upon resource endowments, such as the level of traditional financial development and the degree of information. Moreover, digital finance's adverse impact on energy intensity becomes more pronounced beyond certain threshold values. However, digital finance can increase energy intensity in neighboring regions through spatial spillover effects. Drawing upon our findings, we recommend bolstering the development of digital finance, augmenting the capability for autonomous innovation, and devising specialized strategies for digital finance advancement to fully harness the potential of digital finance in curbing energy intensity. This study interprets the value of digital finance from the new perspective of energy intensity. By exploring the internal links between digital finance and energy intensity, the study enriches the research results on the impact of digital finance on energy intensity.

Variation of digital economy's effect on carbon emissions: improving energy efficiency and structure for energy conservation and emission reduction.

The significance of accurately assessing the influence of digital economy growth upon reducing emission of carbon in the context of worldwide climate governance cannot be overstated. This is crucial in encouraging low-carbon economic advancement at national level, achieving carbon peak and neutrality as soon as possible, and creating a shared future for humanity. A mediating effect model is established using cross-country panel data from 100 countries, ranging from 1990 to 2019, to assess the influence of digital economy development upon emission of carbon and to explore its underlying mechanism. The study found that: the growth of national emission of carbon can be considerably suppressed by digital economy development, and the reduction of emissions is positively associated to each country's level of economic advancement. Digital economy growth influences regional emission of carbon via intermediary channels like energy structure and efficiency, with energy intensity having a particularly noticeable intermediary impact. The inhibitory influence of digital economy development upon emission of carbon differs among countries with different levels of income, and improvements in energy structure and efficiency can precede to energy savings and emission reduction in both middle- and high-income countries. The above findings offer policy guidance for harmoniously advancing the growth of digital economy and climate management, hastening the low-carbon transformation of national economies, and implementing China's carbon peaking initiative.

Analyzing the mediating role of industrial structure in the spatial spillover effects of financial agglomeration on carbon emission and regional heterogeneity.

In China, achieving financial agglomeration necessitates both the gathering of financial resources and the reduction of carbon emissions and the interrelation between these two goals is significant. In this research, sophisticated econometric models are applied to examine the correlation between financial agglomeration and per capita carbon emissions in China, such as spatial econometric, mixed OLS, and stationary panel models. The research sample is composed of data from 30 provinces and cities in China from 2010 to 2020 and examines both temporal and spatial distributions of these two factors and how they influence each other. The direct effect of financial agglomeration on carbon emission is analyzed through spatial panel model, while indirect effect is analyzed by examining the role of industrial structure upgrading as a mediating variable through mediating effect model. This study also looks at how these effects vary regionally, both directly and indirectly. Generally, the study discovered that financial agglomeration and per capita carbon emissions have significantly positive spatial autocorrelation coefficient in all provinces and cities in China, indicating path dependence and spatial spillover. In terms of distribution trends, financial agglomeration shows an upward trend over time, while per capita carbon emissions grew faster in the early stage, but gradually achieves a steady decrease in recent years. In terms of the impact of financial agglomeration on carbon emissions, the relationship between financial agglomeration and per capita carbon emissions is in the form of "inverted U-shaped." Financial agglomeration indirectly influences the intensity of per capita carbon emissions through the advanced industrial structure, which acts as a mediator. In the test of industrial structure serving as a mediating variable, different regions exhibit different impacts due to regional heterogeneity, with a clear distinction between the central region and the eastern and western regions.

Role of agricultural credit guarantee policies in encouraging green agricultural development: farmers' perspectives and responses, and the regulatory function of household capital.

Green agriculture is anticipated to be the leading trend for achieving sustainable and high-quality development in the agricultural sector in the future. The success of credit guarantee policies in promoting green agricultural development is closely linked to the level of participation and response from farmers in securing agricultural credit guarantee loans. We examined how farmers in Xiji, Ningxia, perceive agricultural credit guarantee policies and their involvement in such loans by analyzing 706 survey responses. Our analysis utilized a combination of statistical techniques, including principal component analysis, Heckman's two-stage model, and moderating effect model. The results indicate that out of the 706 surveyed farmers, 29.32% of households (207 households) had knowledge of the agricultural credit guarantee policy. While 66.86% of households (472 households) expressed interest in participating in agricultural credit guarantee loans, only 23.65% of households actually took part or participated multiple times. The overall awareness of the agricultural credit guarantee policy among farmers and their participation rate are both low. An increase in farmers' awareness of the agricultural credit guarantee policy can have a significant impact on their willingness and frequency of participation. The farmer's understanding of the agricultural credit guarantee policy has a significant impact on their decision to participate in credit guarantee loans. However, this effect can vary based on the farmer's income level, household capital, and factors such as social security, personal characteristics, location, and type of household business. To improve the support provided to farmers, it is advised to increase their awareness and understanding of agricultural credit guarantee policies. Furthermore, loan products and services should be personalized according to the capital available to each farmer's household, and the agricultural credit guarantee system and process should be enhanced to provide better assistance.

Analysis of financial support efficiency and influencing factors of listed seed companies from the perspective of energy consumption and carbon emissions.

The seed industry has a prominent role in strengthening ecological stability and national food security as it provides the basic ground for agriculture sector. In the current research, the effectiveness of financial support provided to listed seed enterprises and its influencing factors from the perspectives of energy consumption and carbon emissions are examined using a three-stage DEA-Tobit model. The dataset for the underlined study variables mainly comes from the financial data published by 32 listed seed enterprises and the China Energy Statistical Yearbook from 2016 to 2021. In order to make the results more accurate, the influence of external environmental factors such as economic development level, total energy consumption, and total carbon emission on listed seed enterprises are excluded. The results revealed that the mean value of financial support efficiency of listed seed enterprises increased significantly after excluding the influence of external environmental and random factors. External environmental factors such as regional energy consumption and carbon dioxide emission played an important role in the process of the financial system supporting the development of listed seed enterprises. The development of some listed seed enterprises with high financial support efficiency came at the cost of high local carbon dioxide emission and high energy consumption. Internal factors such as operating profit, equity concentration, financial structure, and enterprise size are the key intra-firm factors that affect the efficiency of financial support for listed seed enterprises. Thus, it is suggested that enterprises must pay attention to the environmental performance to reach a win-win situation in reducing and improving the energy consumption and financial performance, respectively. Similarly, the improvement of energy use efficiency through endogenous and external innovation should be prioritized to achieve sustainable economic development.

Unlocking the effects and optimization path of financial support for improvement in environmental quality and rural revitalization development: an empirical analysis based on provincial data of Shaanxi province.

This study establishes an economic financial support model for the improvement of environmental quality through the development rural revitalization based on the extended Cobb-Douglas production function. Using statistical data from Shaanxi Province, China, from 2004 to 2019, a vector autoregressive (VAR) model is used to empirically analyze the development effect of financial support for rural revitalization and to give the focus points and optimization paths for financial support for environmental quality, rural revitalization and sustainable development. The research results show that financial support plays an active and long-term role in improving environmental quality and promoting rural revitalization and sustainable development. Specifically, the effect of financial instruments in supporting rural revitalization and sustainable development is continuous. In the insurance system, increasing the scale of agricultural insurance support and expanding the coverage of agricultural insurance are key to improving environmental quality and promoting rural revitalization and sustainable development. Therefore, financial policy makers should improve the targeting of financial instruments to provide the right guidance for improving the quality of rural environment and enhancing rural economy, so as to ultimately realize rural revitalization in China.

Does green finance promote agricultural green total factor productivity? Considering green credit, green investment, green securities, and carbon finance in China.

The Chinese government has proposed a "double carbon" target as a response to climate change and has been incorporated in the vision 2035. Agriculture's green development is intrinsically related to financial support, but conventional financial mechanisms fall short in their efforts to foster economic growth and curb environmental degradation. The current research examines the theoretical effects of green finance on agricultural green total factor productivity in the context of "double carbon." The mediating effect and moderating effect models are used to empirically examine this mechanism based on the panel data (2015-2019) of 30 provinces in China. The estimated results suggest that green finance development can significantly increase agricultural green total factor productivity, with an inverted U effect and an apparent regional heterogeneity. The eastern region has a stronger promotional effect than the central and western regions. The advanced industrial structure plays a mediating effect on the impact of green finance on agricultural green total factor productivity. Rural human capital can effectively mediate the mediating effect of advanced industrial structure on the impact of green finance on agricultural green total factor productivity. The aforementioned results offer fresh perspectives and empirical evidence for China's green finance policy improvement, harmonizing regional green finance development, promotion of industrial structure improvement, and rural human capital optimization.

Granulocyte-macrophage colony stimulating factor enhances efficacy of nimustine rendezvousing with temozolomide plus irradiation in patients with glioblastoma.

BACKGROUND: Glioblastoma is the most common and most aggressive type of primary brain tumor. OBJECTIVE: The aim of this study was to investigate the efficacy and safety of intranasal granulocyte-macrophage colony stimulating factor (GM-CSF) administration combined with chemoradiotherapy in patients with glioblastoma who underwent surgery. METHODS: Ninety-two patients were randomly divided into two groups: a control group (n= 46), who received radiotherapy with adjuvant local delivery of nimustine hydrochloride (ACNU) and systemic administration of temozolomide, and an intervention group (n= 46), who received intranasal GM-CSF prior to each cycle of adjuvant chemotherapy in addition to the treatment of the control group. Karnofsky performance status (KPS) scores, progression-free survival (PFS), overall survival (OS), and adverse effects were calculated and compared between the two groups. RESULTS: Compared with the control group, the intervention group had longer PFS (7.8 vs. 6.9 months, P= 0.016) and OS (19.2 vs. 17.1 months, P= 0.045, without adjustment for interim analyses). The KPS scores were also higher in the intervention group than in the control group after 6 months (84.35 ± 8.86 vs. 80.65 ± 7.72; t= 4.552, P= 0.036). Furthermore, the patients in the intervention group had lower incidence of neutropenia and thrombocytopenia (8.7% vs. 29.5%, P= 0.012; 8.7% vs. 18.2%, P= 0.186). Other adverse events were similar in both groups, and most adverse events were grade I/II and resolved spontaneously. CONCLUSION: Intranasal GM-CSF enhances the efficacy of the local ACNU administration combined with oral temozolomide chemotherapy. The survival and performance status were significantly improved in patients with glioblastoma after surgery. Additionally, the GM-CSF therapy was able to reduce the occurrence of chemotherapy-related neutropenia and thrombocytopenia.

An Estimation of the Effect of Green Financial Policies and Constraints on Agriculture Investment: Evidences of Sustainable Development Achievement in Northwest China.

Farming' community actively participating as micro-actors in green finance schemes is critical for regional planning and development. On the basis of the extent to which financial progress and sustainable development are coordinated, in a difference-in-differences approach, this article employed 2350 small investigations to estimate the influence of green-finance strategies on peasants' agriculture investment and developed a mediation effect method. It investigates the role of peasant managerial variability in mediating the influence of financial constraints. The results indicate that the introduction of a financial restriction variable reduces the positive impacts of green-finance regulations on peasants' agricultural investment. Moreover, peasants who participate in non-agricultural management exercises are more inclined to take advantage of green financing regulations and are affected via financial restrictions in mediate means. The building of a green-finance sector in remote regions should accomplish unique positioning and rapid growth.

Does farmers' agricultural investment is impacted by green finance policies and financial constraint? From the perspective of farmers' heterogeneity in Northwest China.

Green finance is a situation in which finance and environmental conservation are combined. Green credit management is a crucial green financial mechanism for achieving a win-win situation with economic development and environmental conservation through prudent credit resource allocation. Similarly, the continued involvement of farmers in green finance policies as micro-actors is critical to policy execution in rural regions. In current research, we utilized 2520 micro-surveys to measure the effects of green finance policies on agricultural investment of farmers in a difference-in-differences framework and developed a mediation effect model based on the degree of coupling coordination between financial development and environmental sustainability. It investigates the effects of heterogeneity in farmers' management on the mediating effect of financial restrictions. The study results show that, in comparison to the favorable effects of green finance policies on agricultural investment of farmers, the inclusion of a financial constraint variable reduces that benefit. Furthermore, farmers that engage in non-agricultural management practices are more likely to benefit from green finance policies and are impacted by the intermediate mechanism's financial restrictions. The construction of a rural green financial system should accomplish differentiated positioning and rapid development.

Comparative clinical studies of primary chemoradiotherapy versus S-1 and nedaplatin chemotherapy against stage IVb oesophageal squamous cell carcinoma: a multicentre open-label randomised controlled trial.

INTRODUCTION: Oesophageal squamous cell carcinoma (OSCC) is one of the most commonly occurring devastating tumours worldwide, including in China. To date, the standard care of patients with stage IV OSCC is systemic chemotherapy and palliative care, which results in poor prognosis. However, no consensus has been established regarding the role of radiotherapy in targeting the primary tumour in patients with stage IVa OSCC. Thus, the aim of this study is to assess the effectiveness of primary radiotherapy combined with S-1 and nedaplatin (NPD) chemotherapy in the patients with stage IV OSCC. METHODS AND ANALYSIS: The study is a multicentre, open-label, randomised controlled trial. A total of 180 eligible patients with stage IV OSCC will be randomised into a study group (90 patients) and a control group (90 patients). Patients in the study group will receive radiotherapy to the primary tumour at a dose of 50.4 Gy combined with 4-6 cycles of S-1 and NPD chemotherapy. In the control group, patients will only receive 4-6 cycles of S-1 and NPD chemotherapy. The primary and secondary outcomes will be measured. The differences between the two groups will be statistically analysed with regard to overall survival, the progression-free survival and safety. All outcomes will be ascertained before treatment, after treatment and after the follow-up period.The results of this study will provide evidence on the role of radiotherapy in patients with stage IV OSCC in China, which will show new options for patients with advanced oesophageal cancer. ETHICS AND DISSEMINATION: This study was approved by the Institutional Ethics Committee of The First Hospital Affiliated of Zhengzhou University (approval number: SS-2018-04). TRIAL REGISTRATION: The trial has been registered at the Chinese Clinical Trial Registry (ChiCTR1800015765) on 1 November 2018; retrospectively registered, http://www.chictr.org.cn/index.aspx.

Identifying impact of international trade and renewable energy consumption on environmental quality improvement and their role in global warming.

There is a lack of proper research that highlights the impact of institutional quality (IQ) and renewable energy consumption (REC) on the carbon emission (CE). The significance of IQ and REC in the achievement of zero CE is highlighted in this research. The current research reports the effects of these important factors on the consumption-based carbon emissions in the G-7 countries from 1995 to 2018. Based on the outcome of the cointegration test, the long-run connection is recognized between IQ, REC, GDP, exports, imports, and consumption-based CE. The findings also validated that there exist significant decrease and increase in the CE in both the short and long run; for instance, IQ, REC, and exports decrease the CE, while imports and GDP increase the CE. The estimates of causality test showed that policies aimed at improving IQ, REC, GDP, exports, and imports have a significant impact on the CE. Consequently, based on these results, policymakers in the G-7 must prioritize IQ and REC to enhance environmental quality and attain carbon neutrality.

Role of institutional quality and renewable energy consumption in achieving carbon neutrality: Case study of G-7 economies.

This research emphasized the significance of institutional quality and renewable energy consumption in achieving the desired objective of zero carbon emissions. Following the COP21 (Paris Conference), many countries have fixed their national level objectives for achieving the carbon neutrality and to tackle the problem of global warming. Many researchers have focused their efforts on the aspects that contribute to environmental degradation. Meanwhile, there is a scarcity of appropriate research that highlights the environmental implications of institutional quality and renewable energy consumption. Therefore, the current study examines the influence of these significant determinants on CCO2 emissions in the G-7 countries from 1990 to 2018. The long run relationship between institutional quality, renewable energy consumption, GDP, exports, imports, and CCO2 emissions is approved, based on the assessed results of cointegration test. Besides that, the estimated results have endorsed a considerable decrease and increase in carbon emission both in the short and long run, i.e., institutional quality, renewable energy consumption, and exports reduce emissions, while imports and GDP raise emissions. The Dumitrescu and Hurlin causality test results show that policies aiming at improving institutional quality, renewable energy consumption, GDP, exports, and imports have a significant effect on CO2 emissions. As a result of these findings which recommends that G-7 countries' policymakers should emphasize institutional quality and renewable energy consumption in order to improve environmental quality by reducing carbon emissions and to achieve carbon neutrality.

Do credit constraints affect the technical efficiency of Boro rice growers? Evidence from the District Pabna in Bangladesh.

This study analyzes the effects of credit constraints on technical efficiency of Boro rice growers in the district of Pabna in Bangladesh. Using a simple random sampling technique, the data was collected from 570 Boro rice growers from the Pabna district of Bangladesh. Before conducting a field survey, a theoretical model was designed to identify credit-constrained and non-constrained rice growers. We have analyzed the collected data in two phases: first, we investigated the technical efficiency of Boro rice growers using the stochastic frontier model (SFA); and second, we used an inefficiency effect model to estimate the influence of credit constraints on technical efficiency. Findings indicate that credit-constrained rice growers (CCRG) are 6.7% less technically efficient than credit non-constrained rice growers (CNRG). Findings further indicate that the education level of the household head, family size, certified seed, sowing time, access to extension services, off-farm income, and household savings have significant effects on the technical efficiency of both groups of rice growers. Furthermore, credit size has a significantly positive impact, whereas the interest rate imposed on the principal amount has a significantly negative impact.

An impact of climate change and groundwater salinity on shadow price of water, farmers' revenue, and socioeconomic and environmental indicators in district Kohat-Pakistan.

Globally, agricultural productivity is adversely impacted due to climatic changes as the temperatures rises and precipitation decreases, and especially in Pakistan, which ultimately enhanced groundwater salinity and harmed water quality in the country. However, the impacts of groundwater salinity and climate change on farmers' revenue have not been fully understood in Pakistan. Therefore, the focus of current research is the assessment of shadow price of water, farmers' revenue, and socioeconomic and environmental indicators affected by variations in groundwater salinity, precipitation, and temperature. The estimation of crop yield sensitivity to groundwater salinity, precipitation, and temperature and their prediction for 2030, 2040, and 2050 time periods was accomplished through the technique of General Maximum Entropy and Response-Yield function. Moreover, the assessment of groundwater quality and climate variable impacts on socioeconomic and environmental indicators was obtained through Target Motad-PMP model. In the end, the most suitable climate change scenario in the study area was established by applying a multi-criteria decision-making method. The results revealed that groundwater salinity and temperature expressed a significantly increasing trend with the Z values of 5.82 and 2.15, respectively. While the precipitation depicted a significantly decreasing trend (Z value = -3.37). The negative impact of climatic changes and groundwater salinity was revealed for revenue risk and shadow prices of water. The most negative impact on income risk and shadow prices is during 2050 horizon with a decrease by 11.4 and 19.4% respectively. The environmental index is the most important with a priority of 43.4% compared to the socio-economic indicators. The sub-index water use is also significant in the study area with a priority of 28.1%. A2 is the most appropriate climate scenario conferring to the TOPSIS ranking method. Therefore, the A2 scenario should be taken into account for the policy of adaptation to the climate change wonder in district Kohat.