CRISPR screens reveal convergent targeting strategies against evolutionarily distinct chemoresistance in cancer.

Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.

Can fintech pave the way for a transition towards low-carbon economy? Examination based on machine learning algorithm.

Realizing the coordination between the economic and environmental systems through a green growth model is an important goal for China to enter the high-quality development stage. Meanwhile, financial technology (fintech) is rapidly developing in China. To explore the relationship between the two, this research uses panel data from 276 cities in China from 2011 to 2022 and empirically tests through constructing econometric models and machine learning algorithms. The empirical result shows that fintech has an impact on green growth. Specifically, there is a U-shaped relationship between fintech and green growth, meaning that before a certain stage, fintech may have a certain inhibitory effect on green growth. After fintech exceeds a certain development level, it will promote the improvement of green growth. Further mediation tests show that innovation plays a mediating role in the impact of fintech on green growth. Additionally, this research also conducts consistency tests based on different criteria including the location, scale, and financial development level of cities. Based on the research findings, policy suggestions are proposed in this paper to promote the development of fintech and stimulate the growth of the green economy. Overall, our research sheds more light on the fintech-green growth linkage and provides new insights into comprehending the role of fintech in advancing towards a low-carbon economy.

A step toward inclusive green growth: can digital finance be the main engine?

Inclusive green growth (IGG) has become a worldwide consensus to achieve the target of sustainable development goals. Although the prominent role of digital finance (DF) against the pandemic has drawn considerable attention from policymakers, its plausible effect on IGG and underlying mechanisms have not been distinctly explored in academia. The aim of the study is to explore the causal effect of DF on IGG based on prefecture city-level data from 2011 to 2019 in China. To this end, we employed the non-radial direction distance function approach within the global production technology to evaluate the aggregate IGG performance and its three sub-dimensions. The empirical results demonstrate that DF exerts a significant promotional effect on urban IGG. This finding continues to survive in an extensive set of robustness checks using an alternative dependent variable, model specifications, instrumental variable, and difference-in-difference approaches to address the endogeneity concerns. Meanwhile, sub-dimensional regressions show that this positive effect is driven predominantly by the scale economy of DF, while the depth of usage and digitalization playing a minor role. Moreover, we uncover that DF enhances IGG by leveraging greater marginal product of labor rather than capital, improving environmental externalities, increasing fuller employment, and reducing rural-urban income inequality. However, we also reveal the dark side of DF on imbalanced regional development. The promotional effect of DF on IGG is only prominent for cities with better inherent comparative advantages, and we are thus likely to see a widening digital divide resulting from the "Matthew effect" on regional disparity without timely policy interventions.

Does the Pro-Environmental Behavior of Household PV Installation Contribute to the Shaping of Users' Green Purchasing Behavior?-Evidence from China.

In order to achieve the "dual carbon goal", the Chinese government is actively encouraging the adoption of household photovoltaic (PV) systems. While there has been considerable research on residents' inclination to install PV, limited attention has been given to understanding how the installation and utilization of PV systems influence pro-environmental behaviors. Therefore, this paper aims to investigate the potential impact of pro-environmental behavior resulting from household PV installation on users' green purchasing behavior. Based on the "learning by doing" theory, a survey was conducted with 1249 participants, and the generalized structural equation model was employed as our analytical approach. The findings of this research indicate that the adoption and utilization of household photovoltaic (PV) systems have a positive impact on green consumption. The test results demonstrate that the overall effect coefficient is 0.03, indicating that current PV promotion policies have an indirect impact on green consumption. Moreover, economic incentive policies have a more substantial influence than environmental publicity policies, with total indirect effect coefficients of 0.005 and 0.002, respectively. Based on the findings above, the following recommendations are proposed: (1) It is recommended to maintain stable economic incentives to promote the adoption of household PV systems. (2) Emphasizing the dissemination of knowledge and skills for promoting environmental protection should be prioritized. (3) Efforts should be made to align personal interests and societal interests with low-carbon policies.

Towards inclusive green growth: does digital economy matter?

In this decade, China has been pursuing an inclusive green growth strategy. Concurrently, the digital economy, which relies on the Internet of Things, big data, and artificial intelligence, has experienced explosive growth in China. The digital economy's capacity to optimize resource allocation and reduce energy consumption potentially makes it a conducive channel towards sustainability. Using the panel data of 281 cities in China from 2011 to 2020, we theoretically and empirically explore the impact of the digital economy on inclusive green growth. Firstly, we theoretically analyze the potential impact of the digital economy on inclusive green growth using two hypotheses: accelerating green innovation and promoting the industrial upgrading effect. Subsequently, we measure the digital economy and inclusive green growth of Chinese cities using Entropy-TOPSIS and DEA approaches, respectively. Then, we apply traditional econometric estimation models and machine learning algorithms to our empirical analysis. The results show that China's high-powered digital economy significantly promotes inclusive green growth. Moreover, we analyze the internal mechanisms behind this impact. We find that innovation and industrial upgrading are two plausible channels that explain this effect. Additionally, we document a nonlinear feature of diminishing marginal effects between the digital economy and inclusive green growth. The heterogeneity analysis shows that the contribution weight of the digital economy to inclusive green growth is more remarkable in eastern region cities, large and medium-sized cities, and cities with high marketization. Overall, these findings shed more light on the digital economy-inclusive green growth nexus and provide new insights into understanding the real effects of the digital economy on sustainable development.

B7-H3 chimeric antigen receptor-modified T cell shows potential for targeted treatment of acute myeloid leukaemia.

BACKGROUND AND AIMS: Chimeric antigen receptor (CAR)-T cell therapy is a novel type of immunotherapy. However, the use of CAR-T cells to treat acute myeloid leukaemia (AML) has limitations. B7-H3 is expressed in several malignancies, including some types of AML cells. However, its expression in normal tissues is low. Therefore, B7-H3 is ideal for targeted AML therapy. MATERIALS AND METHODS: First, we constructed B7-H3 CAR that can target B7-H3, and then constructed B7-H3-CAR-T cells in vitro, which were co-incubated with six AML cell lines expressing different levels of B7-H3, respectively. The toxicity and cytokines were detected by flow cytometry. In vivo, AML model was established in B-NSG mice to study the toxicity of B7-H3-CAR T on AML cells. RESULTS: In vitro functional tests showed that B7-H3-CAR-T cells were cytotoxic to B7-H3-positive AML tumor cells and had good scavenging effect on B7-H3-expressing AML cell lines, and the cytokine results were consistent. In vivo, B7-H3-CAR-T cells significantly inhibited tumor cell growth in a mouse model of AML, prolonging mouse survival compared with controls. CONCLUSION: B7-H3-CAR-T cells may serve as a novel therapeutic method for the targeted treatment of AML.

Inclusive green growth for sustainable development of cities in China: spatiotemporal differences and influencing factors.

Inclusive green growth (IGG) based on coordinating the society, economy, and environment is a new way to reach sustainable development. However, there is a lack of relevant research in developing countries. To bridge this gap, based on a comprehensive index that includes economy, social, and environment, this study evaluates the urban inclusive green growth index (IGGI) of 282 in China from 2003 to 2020 and analyzes the spatiotemporal dynamics and regional differences. Moreover, the spatial Durbin model is employed to explore the plausible influencing factors of urban IGGI in China. The main results show an increasing trend of IGGI in Chinese cities and imbalanced spatiotemporal dynamics. Furthermore, the econometric regress results show that upgrade of industrial structure, opening up, human capital, and urban innovation have significant positive impact on urban IGGI, while the administrative capacity of the government and urban industrialization show negative impact on urban IGGI; human capital not only affects the local IGGI but also has significant spatial spillover effects to the surrounding cities. This finding provides new evidence for China to achieve its 2030 sustainable development goals and sheds lights on how policy can be improved to boost IGGI levels and achieve carbon neutrality in 2060.

Study on the Drivers of Inclusive Green Growth in China Based on the Digital Economy Represented by the Internet of Things (IoT).

With the vigorous development of digital economy based on digital technologies such as Internet of things (IoT), big data, and artificial intelligence, new vitality has been injected into China's economic model. Inclusive green growth (IGG) supports the transformation of society towards a better quality of life and well-being, as well as environmental protection. Therefore, it is crucial to identify the main drivers of IGG. However, IGG is subject to a variety of interpretations and lacks definitional clarity. To brigade this gap, this study primarily evaluates the performance of IGG and explores the key drivers on IGG in China. Specifically, the data envelopment analysis (DEA) model is employed to calculate IGG for 281 cities in China during 2005-2020. Subsequently, we take advantage of a nest of machine learning (ML) algorithm to demonstrate the vital drivers of urban IGG, which avoids the defects of endogenous linear hypothesis of traditional econometric methods. The results indicate that digitization represented by the IoT and other digital technology is the core drivers of the urban IGG in the overall sample, accounting for about 50% among all of drivers. This finding provides new evidence supporting the "high-quality development" strategy in China, as well as shedding light on grasping the principal fulcrum to achieve the transformation towards IGG in developing economies similar to China.

Does Human Capital Matter for China's Green Growth?-Examination Based on Econometric Model and Machine Learning Methods.

To tackle the increasingly severe environmental challenges, including climate change, we should pay more attention to green growth (GG), a path to realize sustainability. Human capital (HC) has been considered a crucial driving factor for developing countries to move towards GG, but the impact and mechanisms for emerging economies to achieve GG need to be further discussed. To bridge this gap, this paper investigates the relation between HC and GG in theory and demonstration perspective. It constructs a systematic theoretical framework for their relationship. Then, it uses a data envelopment analysis (DEA) model based on the non-radial direction distance function (NDDF) to measure the GG performance of China's 281 prefecture level cities from 2011 to 2019. Ultimately, it empirically tests the hypothesis by using econometric model and LightGBM machine learning (ML) algorithm. The empirical results indicate that: (1) There is a U-shaped relationship between China's HC and GG. Green innovation and industrial upgrading are transmission channels in the process of HC affecting GG. (2) Given other factors affecting GG, HC and economic growth contribute equally to GG (17%), second only to city size (21%). (3) China's HC's impact on GG is regionally imbalanced and has city size heterogeneity.

Evaluating the Performance of Inclusive Growth Based on the BP Neural Network and Machine Learning Approach.

In this paper, we use the panel data of 281 cities in China from 2005 to 2020 for capturing the factors driving urban inclusive growth (IG). In doing this, we employ the BP neural network algorithm combined with the DEA model to measure the urban inclusive growth efficiency (IGE). Furthermore, a nest of machine learning (ML) algorithms are introduced to explore the drivers of urban IGE, which overcomes the defects of endogeneity and multicollinearity of traditional econometric methods. We find for the overall sample that entrepreneurship and innovation contribute the most to IGE, accounting for about 35%, respectively, and they are the most critical drivers, while the heterogeneity test results reveal that the contribution of influencing factors has changed for different regions such as the eastern region, the central region, and the western region. Based on the experimental results of the ML model, we provide some policy suggestions for China and similar developing countries and emerging economies to promote IG.

Novel Ba2+ and Pb2+ metal-organic frameworks based on a semi-rigid tetracarboxylic acid: syntheses, structures, topologies and luminescence properties.

Multidentate carboxylate ligands have been widely used in the construction of metal-organic frameworks (MOFs) owing to the rich variety of their coordination modes, which can lead to crystalline products with interesting structures and properties. Two new main-group MOFs, namely, poly[[di-µ-aqua-diaqua(dimethylformamide)[µ7-5,5'-methylenebis(2,4,6-trimethylbenzene-1,3-dicarboxylato)]dibarium(II)] trihydrate], {[Ba2(C23H20O8)(C3H7NO)(H2O)4]·3H2O}n or {[Ba2(BTMIPA)(DMF)(H2O)4]·3H2O}n (1), and poly[[diaqua[µ6-5,5'-methylenebis(2,4,6-trimethylbenzene-1,3-dicarboxylato)]dilead(II)] 2.5-hydrate], {[Pb2(C23H20O8)(H2O)2]·2.5H2O}n or {[Pb2(BTMIPA)(H2O)2]·2.5H2O}n (2), were prepared by the self-assembly of metal salts with the semi-rigid tetracarboxylic acid ligand 5,5'-methylenebis(2,4,6-trimethylisophthalic acid) (H4BTMIPA). Both structures were characterized by elemental analysis (EA), single-crystal X-ray diffraction, powder X-ray diffraction (PXRD), IR spectroscopy and thermogravimetric analysis (TGA). Complex 1 reveals a three-dimensional (3D) flu network formed via bridging tetranuclear secondary building units (SBUs) and complex 2 displays a 3D framework with an sqp topology based on one-dimensional metal chains. The BTMIPA4- ligands adopt a rare coordination mode in 2, although the ligands in both 1 and 2 are X-shaped. The luminescence properties of both complexes were investigated in the solid state.

MUC1-Tn-targeting chimeric antigen receptor-modified Vγ9Vδ2 T cells with enhanced antigen-specific anti-tumor activity.

Chimeric antigen receptor (CAR) αß T cell adoptive immunotherapy has shown great promise for improving cancer treatment. However, there are several hurdles to overcome for the wide clinical application of CAR-αß T cells therapy, including side effects and a limited T cells source from cancer patients. Therefore, we sought to identify an alternative T cell subset that could avoid these limitations and improve the effectiveness of CAR-T immunotherapy. γδ T cells are a minor subset of T cells, which share the characteristic of innate immune cells and adaptive immune cells. Vγ9Vδ2 T cells are a predominant γδ T subset in the circulating peripheral blood. In this study, we investigated the antigen-specific antitumor activity of CAR-Vγ9Vδ2 T cells targeting MUC1-Tn antigen. Vγ9Vδ2 T cells were expanded from peripheral blood mononuclear cells of healthy volunteers with zoledronic acid and interleukin-2. CAR-Vγ9Vδ2 T cells were generated by transfection of lentivirus encoding MUC1-Tn CAR. Cytotoxicity assays with various cancer cell lines revealed that CAR-Vγ9Vδ2 T cells could effectively lyse tumor cells in an antigen-specific manner, with similar or stronger effects than CAR-αß T cells. However, CAR-Vγ9Vδ2 T cells had shorter persistence, which could be improved with the addition of IL-2 to maintain the function of CAR-Vγ9Vδ2 T cells with consecutive stimulation of tumor cells. Using a xenograft mouse model, we further showed that CAR-Vγ9Vδ2 T cells more effectively suppressed tumor growth in vivo than Vγ9Vδ2 T cells. Therefore, MUC1-Tn CAR-modified Vγ9Vδ2 T cells may represent a novel, promising ready-to-use product for cancer allogeneic immunotherapy.

REV7 is required for processing AID initiated DNA lesions in activated B cells.

Activation-induced cytidine deaminase (AID) initiates both antibody class switch recombination (CSR) and somatic hypermutation (SHM) in antibody diversification. DNA double-strand break response (DSBR) factors promote rearrangement in CSR, while translesion synthesis (TLS) polymerases generate mutations in SHM. REV7, a component of TLS polymerase zeta, is also a downstream effector of 53BP1-RIF1 DSBR pathway. Here, we study the multi-functions of REV7 and find that REV7 is required for the B cell survival upon AID-deamination, which is independent of its roles in DSBR, G2/M transition or REV1-mediated TLS. The cell death in REV7-deficient activated B cells can be fully rescued by AID-deficiency in vivo. We further identify that REV7-depedent TLS across UNG-processed apurinic/apyrimidinic sites is required for cell survival upon AID/APOBEC deamination. This study dissects the multiple roles of Rev7 in antibody diversification, and discovers that TLS is not only required for sequence diversification but also B cell survival upon AID-initiated lesions.

Research progression on the first-line biological target therapy of advanced / 中国肿瘤生物治疗杂志

@#[Abstract] Objective: To develop a new type of CD7 chimeric antigen receptor modified T cell (CD7-CAR-T) for the treatment of CD7 positive acute myeloid leukemia (AML), and to observe its killing effect on CD7 positive AML cells. Methods: The CD7-CAR lentiviral vector was constructed based on the CD7 Nanobody sequence and costimulatory domain sequence of CD28 and 4-1BB. The lentiviral particles were packaged and used to co-transfect human T cells with protein expression blocker (PEBL), so as to prepare CD7- CAR-T cells. Real time cellular analysis (RTCA) was used to monitor the cytotoxicity of CD7-CAR-T cells on CD7 overexpressed 293T cells. Flow cytometry assay was used to detect the effect of CD7-CAR-T cells on proliferation and cytokine secretion of AML cells with high, medium and low CD7 expressions (KG-1, HEL and Kasumi-1 cells, respectively). Results: CD7-CAR-T cell was successfully constructed and its surface expression of CD7 was successfully blocked. Compared with T cells, CD7-CAR-T cells could significantly inhibit the proliferation of CD7-293T cells and promote the release of TNF, Granzyme B and INF-γ; in addition, CD7-CAR-T cells also significantly promoted the apoptosis (t=147.1, P<0.01; t=23.57, P<0.01) and cytokine release (P<0.05 or P<0.01) in CD7 positive KG-1 and HEL cells, but had little effect on Kasumi-1 cells that only expressed minimal CD7 antigen (t=0.7058, P>0.05). Conclusion: CD7-CAR-T cells can specifically kill CD7-positive AML cells in vitro.

Intrinsic Nucleotide Preference of Diversifying Base Editors Guides Antibody Ex Vivo Affinity Maturation.

Base editors (BEs) are emerging tools used for precision correction or diversifying mutation. It provides a potential way to recreate somatic hypermutations (SHM) for generating high-affinity antibody, which is usually screened from antigen-challenged animal models or synthetic combinatorial libraries. By comparing somatic mutations in the same genomic context, we screened engineered deaminases and CRISPR-deaminase coupling approaches and updated diversifying base editors (DBEs) to generate SHM. The deaminase used in DBEs retains its intrinsic nucleotide preference and mutates cytidines at its preferred motifs. DBE with AID targets the same hotspots as physiological AID does in vivo, while DBE with other deaminases generates distinct mutation profiles from the same DNA substrate. Downstream DNA repair pathways further diversified the sequence, while Cas9-nickase restricted mutation spreading. Finally, application of DBE in an antibody display system achieved antibody affinity maturation ex vivo. Our findings provide insight of DBE working mechanism and an alternative antibody engineering approach.

PKM2 knockdown influences SREBP activation and lipid synthesis in bovine mammary-gland epithelial MAC-T cells.

OBJECTIVE: The purpose of the article is to evaluate the changes in lipid metabolism in bovine mammary-gland epithelial MAC-T cells after PKM2 knockdown. RESULTS: MAC-T cells stably expressing low levels of PKM2 were established with lentivirus-mediated small hairpin RNA. Although the knockdown of PKM2 had no effect on MAC-T cell growth, the reduced expression of PKM2 attenuated the mRNA and protein expression of key enzymes involved in sterol synthesis through the SREBP pathway. CONCLUSIONS: The downregulation of PKM2 significantly influenced lipid synthesis in bovine mammary-gland epithelial MAC-T cells. These findings extend our understanding of the crosstalk between glycolysis and lipid metabolism in bovine mammary-gland epithelial cells.

Molecular cloning and functional characterization of porcine cyclic GMP-AMP synthase.

Cyclic GMP-AMP synthase (cGAS), which belongs to the nucleotidyltransferase family, recognizes cytosolic DNA and induces the type I interferon (IFN) pathway through the synthesis of the second messenger cGAMP. In this study, porcine cGAS (p-cGAS) was identified and its tissue distribution, subcellular localization, and functions in innate immunity were characterized. The coding sequence of p-cGAS is 1494 bp long, encodes 497 amino acids, and is most similar (74%) to Bos taurus cGAS. p-cGAS mRNA is abundant in the spleen, duodenum, jejunum, and ileum. The subcellular distribution of p-cGAS is not only in the cytosol, but also on the endoplasmic reticulum (ER) membrane. The overexpression of wild-type p-cGAS in porcine kidney epithelial cells, but not its catalytically inactive mutants, induced IFN-ß expression, which was dependent on STING and IRF3. However, the downregulation of p-cGAS by RNA interference markedly reduced IFN-ß expression after pseudorabies virus (PRV) infection or poly(dA:dT) transfection. These results demonstrate that p-cGAS is an important DNA sensor, required for IFN-ß activation.