Digital economy, resource distortion and low-carbon inclusive development-Evidence from the perspectives of a threshold effect and knowledge spillover effect.

The low-carbon economy represents a global transformation that encompasses production methods, lifestyles, values, national interests, and the destiny of humanity. As a significant contributor to carbon emissions, China has made a momentous strategic decision on carbon peaking and neutralization, infusing momentum into the global effort to address climate change. The rapid growth of the digital economy offers a fresh approach to achieving the "double carbon" objective and advancing the development of low-carbon transformation. Based on the panel data of 30 provinces in China, this paper uses the least square method to investigate the impact of digital economy development on regional low-carbon inclusive development. It is found that there is a significant inverted U shape in the impact of the digital economy on low-carbon inclusive development and the mechanism is resource allocation and ecological inequality. The threshold test found that the role of the digital economy in promoting low-carbon inclusive development shows a marginal decreasing trend. The inverted U-shaped impact of the digital economy on low-carbon inclusive development in the eastern and coastal areas and areas with a low level of factor productivity is more significant. Based on the knowledge factor spillover perspective, we found that the impact of the digital economy on low-carbon inclusive development has a spatial spillover effect, and this effect is more obvious under the role of R&D personnel mobility.

Thermal Effect Management via Entropy Variation Strategy to Improve the Catalyst Stability in Acetylene Hydrogenation.

The dynamic structure evolution of heterogeneous catalysts during reaction has gained great attention recently. However, controllably manipulating dynamic process and then feeding back catalyst design to extend the lifetime remains challenging. Herein, we proposed an entropy variation strategy to develop a dynamic CuZn-Co/HEOs catalyst, in which the non-active Co nano-islands play a crucial role in controlling thermal effect via timely capturing and utilizing reaction heat generated on the adjacent active CuZn alloys, thus solving the deactivation problem of Cu-based catalysts. Specifically, heat sensitive Co nano-islands experienced an entropy increasing process of slowly redispersion during the reaction. Under such heat dissipation effect, the CuZn-Co/HEOs catalyst exhibited 95.7% ethylene selectivity and amazing long-term stability (>530 h) in the typical exothermic acetylene hydrogenation. Aiming at cultivating it as a catalyst with promising industrial potential, we proposed a simple regeneration approach via an entropy decreasing process.

Document-level biomedical relation extraction via hierarchical tree graph and relation segmentation module.

MOTIVATION: Biomedical relation extraction at the document level (Bio-DocRE) involves extracting relation instances from biomedical texts that span multiple sentences, often containing various entity concepts such as genes, diseases, chemicals, variants, etc. Currently, this task is usually implemented based on graphs or transformers. However, most work directly models entity features to relation prediction, ignoring the effectiveness of entity pair information as an intermediate state for relation prediction. In this article, we decouple this task into a three-stage process to capture sufficient information for improving relation prediction. RESULTS: We propose an innovative framework HTGRS for Bio-DocRE, which constructs a hierarchical tree graph (HTG) to integrate key information sources in the document, achieving relation reasoning based on entity. In addition, inspired by the idea of semantic segmentation, we conceptualize the task as a table-filling problem and develop a relation segmentation (RS) module to enhance relation reasoning based on the entity pair. Extensive experiments on three datasets show that the proposed framework outperforms the state-of-the-art methods and achieves superior performance. AVAILABILITY AND IMPLEMENTATION: Our source code is available at https://github.com/passengeryjy/HTGRS.

Premature Ovarian Insufficiency Is Associated with Increased Risk of Depression, Anxiety, and Poor Life Quality: A Systematic Review and Meta-analysis.

Background: Premature ovarian insufficiency (POI) seriously affects the reproductive health of women. Several studies have been conducted to show that POI appears to be associated with psychological and psychosocial problems, but whether POI increases the risk of mental health problems has not been identified. Therefore, this meta-analysis provides a preliminary systematic assessment of the studies published to date on the impact of POI on women's mental health. Methods: We implemented a systematic search for studies on this topic up to October 2022. Pooled odds ratios (ORs) and 95% confident intervals (CIs) of prevalence were used to assess the impacts of POI on various psychological factors, and the publication bias was assessed by Egger's test. Results: A total of 15 articles comprising 5820 participants were included in this meta-analysis. POI was found to be related to higher risk of 13 psychological and psychosocial problems identified and classified into 3 domains: depression (OR = 1.61; 95% CI: 1.11-2.33), anxiety (OR = 3.74; 95% CI: 1.78-7.87), and poor life quality (OR = 2.55, 95% CI: 1.63-3.97). Conclusion: This meta-analysis reveals that women with POI have an increased risk of depression, anxiety, and poor life quality. The marital status of POI may be a possible influencing factor for depression, meaning that the unmarried status in POI is at high risk of psychological and psychosocial problems. We should pay attention to the mental health of women with POI who were unmarried.

Nanobody in a Double "Y"-Shaped Assembly: A Promising Candidate for Lateral Flow Immunoassays.

Derived from camelid heavy-chain antibodies, nanobodies (Nbs) are the smallest natural antibodies and are an ideal tool in biological studies because of their simple structure, high yield, and low cost. Nbs possess significant potential for developing highly specific and user-friendly diagnostic assays. Despite offering considerable advantages in detection applications, knowledge is limited regarding the exclusive use of Nbs in lateral flow immunoassay (LFIA) detection. Herein, we present a novel double "Y" architecture, achieved by using the SpyTag/SpyCatcher and Im7/CL7 systems. The double "Y" assemblies exhibited a significantly higher affinity for their epitopes, as particularly evident in the reduced dissociation rate. An LFIA employing double "Y" assemblies was effectively used to detect the severe acute respiratory syndrome coronavirus-2 N protein, with a detection limit of at least 500 pg/mL. This study helps broaden the array of tools available for the development of Nb-based diagnostic techniques.

Periostin is associated with prognosis and immune cell infiltration in pancreatic adenocarcinoma based on integrated bioinformatics analysis.

BACKGROUND: Pancreatic cancer is one of the most aggressive human malignancies. Previous research has shown that periostin (POSTN) promotes pancreatic cancer cell proliferation, migration, and invasion. Further, POSTN is involved in tumor microenvironment remodeling during tumor progression. However, the relationship between POSTN expression, immune cell infiltration, and the efficacy of immunotherapy in pancreatic cancer is unclear. METHODS: We conducted a comprehensive evaluation of POSTN differential expression, examining mRNA and protein levels. To gather data, we utilized various databases including gene expression profiling interactive analysis 2 (GEPIA2), gene expression omnibus (GEO), and the human protein atlas (HPA). To investigate the correlation between POSTN expression and clinical characteristics, we analyzed data from the Kaplan-Meier plotter database and clinical data sourced from the cancer genome atlas (TCGA). Furthermore, we performed gene ontology (GO) analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and gene set enrichment analysis (GSEA). Additionally, we explored the relationship between POSTN expression and immune cell infiltration, as well as the immunophenoscore (IPS), by leveraging the cancer immunome atlas (TCIA) database. Lastly, we examined the tumor mutational burden (TMB) in pancreatic cancer in relation to POSTN expression. RESULTS: When compared with healthy pancreatic tissues, pancreatic cancer tissues displayed significantly higher levels of POSTN, which was indicative of a worse prognosis. POSTN expression was closely associated with extracellular matrix (ECM) organization, ECM-receptor interaction, and focal adhesion by GO, KEGG pathway, and GSEA analyses. Higher expression of POSTN was associated with increased infiltration of M2 macrophages. Additionally, increased IPS was linked to lower POSTN expression. IPS scores for CTLA4, PD-1/PDL1, and CTLA4/PD-1/PDL1 immune checkpoint inhibitors were also higher in the POSTN-low expression group, suggesting that lower expression of POSTN is associated with a better outcome with checkpoint inhibitor treatment. CONCLUSION: POSTN is related to pancreatic cancer prognosis, and may influence immune cell infiltration. High expression of POSTN is predicted to correlate with lower sensitivity to immunotherapy with checkpoint inhibitors in pancreatic cancer.

The dynamic-process characterization and prediction of synthetic gene circuits by dynamic delay model.

Differential equation models are widely used to describe genetic regulations, predict multicomponent regulatory circuits, and provide quantitative insights. However, it is still challenging to quantitatively link the dynamic behaviors with measured parameters in synthetic circuits. Here, we propose a dynamic delay model (DDM) which includes two simple parts: the dynamic determining part and the doses-related steady-state-determining part. The dynamic determining part is usually supposed as the delay time but without a clear formula. For the first time, we give the detail formula of the dynamic determining function and provide a method for measuring all parameters of synthetic elements (include 8 activators and 5 repressors) by microfluidic system. Three synthetic circuits were built to show that the DDM can notably improve the prediction accuracy and can be used in various synthetic biology applications.

Electrochemical reduction of nitrite to ammonia on amorphous MoO3 nanosheets.

Electrocatalytic NO2- reduction to NH3 (NO2RR) is an appealing approach for mitigating NO2- pollution and for the synthesis of valuable NH3, and so the exploration for high-performance NO2RR catalysts is pivotal yet remains challenging. Herein, amorphous MoO3 nanosheets (am-MoO3) were designed as a high-performance NO2RR electrocatalyst, delivering a maximum NO2--to-NH3 faradaic efficiency of 94.8% and NH3 yield rate of 480.4 µmol h-1 cm-2 at -0.6 V vs. RHE. Theoretical computations revealed that the largely enhanced NO2RR activity of am-MoO3 originated from the amorphization-induced O-vacancies, which could enhance the NO2--to-NH3 reaction energetics and hamper the competitive hydrogen evolution.

Genetic components of Escherichia coli involved in its complex prey-predator interaction with Myxococcus xanthus.

Myxococcus xanthus and Escherichia coli represent a well-studied microbial predator-prey pair frequently examined in laboratory settings. While significant progress has been made in comprehending the mechanisms governing M. xanthus predation, various aspects of the response and defensive mechanisms of E. coli as prey remain elusive. In this study, the E. coli MG1655 large-scale chromosome deletion library was screened, and a mutant designated as ME5012 was identified to possess significantly reduced susceptibility to predation by M. xanthus. Within the deleted region of ME5012 encompassing seven genes, the significance of dusB and fis genes in driving the observed phenotype became apparent. Specifically, the deletion of fis resulted in a notable reduction in flagellum production in E. coli, contributing to a certain level of resistance against predation by M. xanthus. Meanwhile, the removal of dusB in E. coli led to diminished inducibility of myxovirescin A production by M. xanthus, accompanied by a slight decrease in susceptibility to myxovirescin A. These findings shed light on the molecular mechanisms underlying the complex interaction between M. xanthus and E. coli in a predatory context.