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Book
Paris Agreement climate proposals need a boost to keep warming well below 2 °C
The Paris climate agreement aims at holding global warming to well below 2 degrees Celsius and to “pursue efforts” to limit it to 1.5 degrees Celsius. To accomplish this, countries have submitted Intended Nationally Determined Contributions (INDCs) outlining their post-2020 climate action. Here we assess the effect of current INDCs on reducing aggregate greenhouse gas emissions, its implications for achieving the temperature objective of the Paris climate agreement, and potential options for overachievement. The INDCs collectively lower greenhouse gas emissions compared to where current policies stand, but still imply a median warming of 2.6–3.1 degrees Celsius by 2100. More can be achieved, because the agreement stipulates that targets for reducing greenhouse gas emissions are strengthened over time, both in ambition and scope. Substantial enhancement or over-delivery on current INDCs by additional national, sub-national and non-state actions is required to maintain a reasonable chance of meeting the target of keeping warming well below 2 degrees Celsius.
The objective of the Paris climate agreement is to limit global-average temperature increase to well below 2 degrees Celsius above pre-industrial levels and to further pursue limiting it to 1.5 degrees Celsius; here, the adequacy of the national plans submitted in preparation for this agreement is assessed, and it is concluded that substantial enhancement or over-delivery on these plans is required to have a reasonable chance of achieving the Paris climate objective.
Paris climate action plans assessed
The principal climate goal of the Paris Agreement of December 2015 is to hold the increase in the global average temperature to well below 2 degrees Celsius above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 degrees above pre-industrial levels. This Perspective assesses the national plans submitted to the Paris meeting for post-2020 action to reduce global greenhouse gas emission by 2030. It also provides projections for global mean temperature increase over the twenty-first century that would be consistent with the present national plans and discusses options that may help to reduce greenhouse gas emissions to levels that are more consistent with maintaining a reasonable chance of meeting the well below 2 degrees Celsius climate target.
Journal Article
Emissions: world has four times the work or one-third of the time
New synthesis shows what a wasted decade means for the climate pact made in Paris.
New synthesis shows what a wasted decade means for the climate pact made in Paris.
Journal Article
Artificial intelligence enables precision diagnosis of cervical cytology grades and cervical cancer
Cervical cancer is a significant global health issue, its prevalence and prognosis highlighting the importance of early screening for effective prevention. This research aimed to create and validate an artificial intelligence cervical cancer screening (AICCS) system for grading cervical cytology. The AICCS system was trained and validated using various datasets, including retrospective, prospective, and randomized observational trial data, involving a total of 16,056 participants. It utilized two artificial intelligence (AI) models: one for detecting cells at the patch-level and another for classifying whole-slide image (WSIs). The AICCS consistently showed high accuracy in predicting cytology grades across different datasets. In the prospective assessment, it achieved an area under curve (AUC) of 0.947, a sensitivity of 0.946, a specificity of 0.890, and an accuracy of 0.892. Remarkably, the randomized observational trial revealed that the AICCS-assisted cytopathologists had a significantly higher AUC, specificity, and accuracy than cytopathologists alone, with a notable 13.3% enhancement in sensitivity. Thus, AICCS holds promise as an additional tool for accurate and efficient cervical cancer screening.
Cervical screening is a key method for detecting cervical cancer, but is limited by pathologist detection. Here, the authors use artificial intelligence to predict cytology grades from whole slide images.
Journal Article
Contingency response decision of network public opinion emergencies based on intuitionistic fuzzy entropy and preference information of decision makers
A multi-attribute group decision-making (MAGDM) method based on intuitionistic fuzzy preference information is proposed for the multi-attribute intuitionistic fuzzy group decision-making problem where the decision-makers weight and attribute weight are completely unknown and the decision-maker has preference information for the scheme. Firstly, an intuitionistic fuzzy interval judgment matrix is established to describe the original data of the key decision indicators for multiple network public opinion emergencies that erupt simultaneously. Secondly, the attribute weights are determined based on the improved intuitionistic fuzzy entropy construction method, and the expert weights are determined by using objective decision information, taking into account the intuitionistic fuzzy entropy of decision matrix. MAGDM can not only synthesize experts' professional experience in different aspects, but also avoid experts' decision-making errors caused by insufficient domain knowledge. It is necessary to continuously adjust the expert weight based on decision-making information to make the comprehensive decision-making information more accurate. Thirdly, a scheme preference model and an attribute weight optimization model are established to determine the ranking method of intuitionistic fuzzy interval values. Then, a modified distance measure of intuitionistic fuzzy sets (IFSs) is introduced to make the evaluation result more accurate and reasonable when it comes to solving the deviation between the evaluation value and ideal solution of each scheme. Finally, the effectiveness and practicability of the proposed decision-making method are verified by an example of emergency crisis severity, It assists decision makers in selecting and implementing the optimal emergency response plan in a timely and efficient manner, which improves the emergency treatment efficiency of network public opinion crisis, helps emergency departments to better deal with the network public opinion crisis, improves the ability of public opinion guidance and control, and provides a new method and idea for multi-attribute intuitionistic fuzzy group decision-making problem.
Journal Article
Interval-valued intuitionistic fuzzy multi-attribute group decision-making method considering risk preference of decision-makers and its application
An improved interval-valued intuitionistic fuzzy multi-attribute group decision-making method considering the risk preference of decision-makers is proposed to solve the multi-attribute group decision-making problem with interval-valued intuitionistic fuzzy numbers and the condition that the attribute weight information is completely unknown. Firstly, the decision-maker weight of each attribute is determined by combining similarity and proximity. In order to consider the influence of the decision-maker's risk preference on the decision result and avoid the asymptotic behavior of interval-valued intuitionistic fuzzy matrix, the risk aversion coefficient of the decision-maker is introduced and combined with the determined decision-maker's weight aggregation to form a group decision matrix. Then, the information of group decision matrix is mined, and the interval-valued intuitionistic fuzzy entropy is used to determine the attribute weight and relative weight. Based on the interval-valued intuitionistic fuzzy distance measure formula and the TODIM method, the overall superiority of each scheme relative to other schemes is obtained by calculating the superiority between schemes, and the optimal scheme is determined by comparing and sequencing. Finally, the rationality and effectiveness of the proposed method are verified by an example of mechanical assembly supplier selection decision.
Journal Article
Efficiency of Agricultural Insurance in Facilitating Modern Agriculture Development: From the Perspective of Production Factor Allocation
Agricultural insurance is instrumental in consolidating the gains of poverty alleviation and advancing rural revitalization. It significantly aids in the efficient allocation of agricultural production factors, which in turn enhances agricultural output and bolsters the evolution of modern agriculture. Therefore, utilizing data from 583 household surveys and employing endogenous transformation and intermediary effect models, this paper analyzes the production factor allocation effect and specific mechanism of agricultural insurance. It focuses on small-scale farmers and new agricultural operators, exploring how insurance contributes to the advancement of modern agricultural practices. The results show the following: (1) Agriculture insurance can significantly affect the agricultural scale input behavior of farmers such as land input scale and input scale, agricultural machinery application behavior such as the degree of mechanization and water conservancy application, agricultural technology adoption behavior, and planting structure selection behavior, thereby helping to modernize agriculture. (2) There is heterogeneity in the impact of agriculture insurance on the allocation of production factors for small farmers and new agricultural operators. For small farmers, agriculture insurance has a significant promoting effect on their agricultural machinery application behavior, agricultural technology adoption behavior, and planting structure selection behavior. For new agricultural operators, agriculture insurance significantly promotes their agricultural scale input behavior, agricultural machinery application behavior, and agricultural technology adoption behavior. (3) In terms of the mechanism of action, agriculture insurance mainly promotes agricultural scale input behavior through land transfer, facilitates agricultural machinery application behavior by purchasing agricultural machinery equipment and services, encourages agricultural technology adoption behavior by strengthening agricultural technology training, and enhances professional production levels by increasing the scale of insured planting, thereby contributing to the development of modern agriculture. Based on this, several policy suggestions have been proposed. These include enhancing the directionality of agriculture insurance policies, improving the collaborative interaction mechanism between agriculture insurance and agricultural credit financing, and adopting certain reward and punishment measures to curb moral hazard.
Journal Article
Mitochondrial fission induces immunoescape in solid tumors through decreasing MHC-I surface expression
Mitochondrial dynamics can regulate Major Histocompatibility Complex (MHC)-I antigen expression by cancer cells and their immunogenicity in mice and in patients with malignancies. A crucial role in the mitochondrial fragmentation connection with immunogenicity is played by the IRE1α-XBP-1s axis. XBP-1s is a transcription factor for aminopeptidase TPP2, which inhibits MHC-I complex cell surface expression likely by degrading tumor antigen peptides. Mitochondrial fission inhibition with Mdivi-1 upregulates MHC-I expression on cancer cells and enhances the efficacy of adoptive T cell therapy in patient-derived tumor models. Therefore mitochondrial fission inhibition might provide an approach to enhance the efficacy of T cell-based immunotherapy.
Cancer cells downregulate surface expression of major histocompatibility complex I (MHC-I) for immune evasion. Here, the authors show that rapid mitochondrial fission activates the ER-stress response leading to reduced MHC-I complex formation and cell surface expression in solid cancer cells; moreover inhibition of mitochondrial fission increases the immune-mediated anticancer response in murine models.
Journal Article
The genomic landscape of Epstein-Barr virus-associated pulmonary lymphoepithelioma-like carcinoma
Pulmonary lymphoepithelioma-like carcinoma (LELC) is a rare and distinct subtype of primary lung cancer characterized by Epstein-Barr virus (EBV) infection. Herein, we reported the mutational landscape of pulmonary LELC using whole-exome sequencing, targeted deep sequencing and single-nucleotide polymorphism arrays. We identify a low degree of somatic mutation but widespread existence of copy number variations. We reveal predominant signature 2 mutations and frequent loss of type I interferon genes that are involved in the host-virus counteraction. Integrated analysis shows enrichment of genetic lesions affecting several critical pathways, including NF-κB, JAK/STAT, and cell cycle. Notably, multi-dimensional comparison unveils that pulmonary LELC resemble NPC but are clearly different from other lung cancers, natural killer/T-cell lymphoma or EBV-related gastric cancer in terms of genetic features. In all, our study illustrates a distinct genomic landscape of pulmonary LELC and provides a road map to facilitate genome-guided personalized treatment.
The rare lung cancer subtype pulmonary lymphoepithelioma-like carcinoma is linked to Epstein-Barr virus infection. Here, the authors provide a mutational landscape for this cancer, showing a low burden of somatic mutations and high prevalence of copy number variations.
Journal Article
Increased co-expression of PD1 and TIM3 is associated with poor prognosis and immune microenvironment heterogeneity in gallbladder cancer
Background
The effectiveness of immune checkpoint inhibitors in treating gallbladder cancer (GBC) remains unsatisfactory. Recently, several new immune checkpoints have been identified. However, investigations exploring these immune checkpoints in GBC are limited. In this study, we aim to investigate the expression patterns and clinical implications of various immune checkpoints, and further characterize the spatial and quantitative heterogeneity of immune components in GBC.
Methods
We employed single and multiplex immunohistochemistry to evaluate the expression of five immune checkpoint markers and four immune cell markers in the primary tumor core, hepatic invasion margin, and liver metastasis. Subsequently, we analyzed their interrelationships and their prognostic significance.
Results
We observed a robust positive correlation between PD1/TIM3 expression in GBC (R = 0.614, P < 0.001). The co-expression of PD1/TIM3 exhibited a synergistic effect in predicting poor prognosis among postoperative GBC patients. Further analysis revealed that the prognostic significance of PD1/TIM3 was prominent in the subgroup with high infiltration of CD8 + T cells (P < 0.001). Multiplex immunohistochemistry reveals that PD1 + TIM3 + FOXP3 + cells constitute a significant proportion of FOXP3 + TILs in GBC tissue. Moreover, the co-high expression of PD1 and TIM3 is positively correlated with the accumulation of CD8 + TILs at the hepatic invasion margin. Lastly, our findings indicated reduced expression levels of immune checkpoints and diminished immune cell infiltration in liver metastases compared to primary tumors.
Conclusions
Increased co-expression of PD1/TIM3 is associated with poor prognosis in GBC patients and is related to the heterogeneity of immune microenvironment between GBC primary tumor and its hepatic invasion margin or liver metastases, which may be a potential target for future immunotherapy of GBC.
Journal Article