Large inter-city inequality in consumption-based CO₂ emissions for China's pearl river basin cities

Cities are leading carbon mitigation but are heterogeneous in their mitigation policies due to different socioeconomic backgrounds. Given that cities are increasingly inextricably linked, formulating mitigation policies of different cities cannot be easily achieved without comprehensive carbon inventories, who taking the inter-city supply chains into account. The Pearl River Basin is one of the important economic zones in China, with huge disparity in its cities, but very limited information is available on their consumption-based CO2 emissions. To fill this gap, we compiled a consumption-based inventory of 47 cities in the Basin for 2012. We found that the total consumption-based emissions of 47 cities was 933.8 Mt, accounting for 13.1% of China's emissions. There were huge differences in the consumption-based emissions, ranging from 3.6 Mt (Heyuan City) to 153.1 Mt (Shenzhen City). The consumption-based emissions were highly concentrated in the largest seven cities, which accounted for 52.8% of the total emissions of the Basin. The consumption-based emissions per capita also varied greatly, from 1.2 to 14.5 tons per capita. Large scale infrastructure was the biggest driving force for most cities, resulting in 42.1% to 75.6% of the emissions. At sector-level, construction, heavy industry and services were leading in emissions, contributing more than 80% of emissions. The major inter-city carbon transfers occurred within upstream cities in the developing regions and downstream cities in the Pearl River Delta respectively, instead of the transfers between upstream and downstream cities. The findings highlight that the regional mitigation strategies could mainly focus on cities in intra-province boundary, rather than inter-province boundary, and also the city-level mitigation strategies should pay attention to the key emission sectors and drivers in respect of the heterogeneity of cities

D-2-hydroxyglutarate is essential for maintaining oncogenic property of mutant IDH-containing cancer cells but dispensable for cell growth

Cancer-associated isocitrate dehydrogenase (IDH) 1 and 2 mutations gain a new activity of reducing α-KG to produce D-2-hydroxyglutarate (D-2-HG), which is proposed to function as an oncometabolite by inhibiting α-KG dependent dioxygenases. We investigated the function of D-2-HG in tumorigenesis using IDH1 and IDH2 mutant cancer cell lines. Inhibition of D-2-HG production either by specific deletion of the mutant IDH1-R132C allele or overexpression of D-2-hydroxyglutarate dehydrogenase (D2HGDH) increases α-KG and related metabolites, restores the activity of some α-KG-dependent dioxygenases, and selectively alters gene expression. Ablation of D-2-HG production has no significant effect on cell proliferation and migration, but strongly inhibits anchorage independent growth in vitro and tumor growth in xenografted mouse models. Our study identifies a new activity of oncometabolite D-2-HG in promoting tumorigenesis

NeuroSeg-II: A deep learning approach for generalized neuron segmentation in two-photon Ca2+ imaging

The development of two-photon microscopy and Ca2+ indicators has enabled the recording of multiscale neuronal activities in vivo and thus advanced the understanding of brain functions. However, it is challenging to perform automatic, accurate, and generalized neuron segmentation when processing a large amount of imaging data. Here, we propose a novel deep-learning-based neural network, termed as NeuroSeg-II, to conduct automatic neuron segmentation for in vivo two-photon Ca2+ imaging data. This network architecture is based on Mask region-based convolutional neural network (R-CNN) but has enhancements of an attention mechanism and modified feature hierarchy modules. We added an attention mechanism module to focus the computation on neuron regions in imaging data. We also enhanced the feature hierarchy to extract feature information at diverse levels. To incorporate both spatial and temporal information in our data processing, we fused the images from average projection and correlation map extracting the temporal information of active neurons, and the integrated information was expressed as two-dimensional (2D) images. To achieve a generalized neuron segmentation, we conducted a hybrid learning strategy by training our model with imaging data from different labs, including multiscale data with different Ca2+ indicators. The results showed that our approach achieved promising segmentation performance across different imaging scales and Ca2+ indicators, even including the challenging data of large field-of-view mesoscopic images. By comparing state-of-the-art neuron segmentation methods for two-photon Ca2+ imaging data, we showed that our approach achieved the highest accuracy with a publicly available dataset. Thus, NeuroSeg-II enables good segmentation accuracy and a convenient training and testing process

Use of nanomaterials in the pretreatment of water samples for environmental analysis

The challenge of providing clean drinking water is of enormous relevance in today’s human civilization, being essential for human consumption, but also for agriculture, livestock and several industrial applications. In addition to remediation strategies, the accurate monitoring of pollutants in water sup-plies, which most of the times are present at low concentrations, is a critical challenge. The usual low concentration of target analytes, the presence of in-terferents and the incompatibility of the sample matrix with instrumental techniques and detectors are the main reasons that renders sample preparation a relevant part of environmental monitoring strategies. The discovery and ap-plication of new nanomaterials allowed improvements on the pretreatment of water samples, with benefits in terms of speed, reliability and sensitivity in analysis. In this chapter, the use of nanomaterials in solid-phase extraction (SPE) protocols for water samples pretreatment for environmental monitoring is addressed. The most used nanomaterials, including metallic nanoparticles, metal organic frameworks, molecularly imprinted polymers, carbon-based nanomaterials, silica-based nanoparticles and nanocomposites are described, and their applications and advantages overviewed. Main gaps are identified and new directions on the field are suggested.publishe

PLEKHA4 is Associated with Tumour Microenvironment, Stemness, Proliferation and Poor Prognosis of Gliomas

Background: Glioma is the most common intracranial malignancy. Immune-infiltration and tumour stemness are associated with the prognosis of glioma. Although pleckstrin homology containing family A, number 4 (PLEKHA4) is widely expressed in various human cancers, its role in glioma remains unclear. Methods: We examined the features and clinical significance of PLEKHA4 in gliomas by analysing relevant data from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. Gene set enrichment analysis (GSEA) was performed to determine the possible functions and pathways involving PLEKHA4 in glioma. The relationship between PLEKHA4 expression and the degree of oncogenic dedifferentiation was analysed using stemness scores (ss) calculated from epigenetic and transcriptomic features. We also explored the relationship between PLEKHA4 expression and immune cell infiltration in gliomas using the CIBERSORT databases. Furthermore, drug sensitivity analysis was performed using datasets from the GDSC and GTRP databases. In addition, we performed relevant in vitro experimental studies. Results: PLEKHA4 DNA hypomethylation status was associated with its high expression in glioma tissues as well as poor prognoses. Univariate and multivariate Cox analyses indicated that PLEKHA4 expression may be considered as an independent prognostic factor in patients with glioma. GSEA indicated that high PLEKHA4 expression was associated with Janus kinase (JAK)/signal transducer and activator of transcription (STAT), Wingless-Type MMTV Integration Site Family (Wnt), JUN N-terminal kinase (JNK) signalling pathways and involved in apoptotic, cytoskeletal, and cell adhesion biological processes (BPs). In addition, increased PLEKHA4 expression was associated with higher glioma stemness scores than lower PLEKHA4 expression levels. Furthermore, the expression of PLEKHA4 was shown to be associated with glioma infiltration by CD4+ T cells, B cells, neutrophils, macrophages, and dendritic cells. Drug sensitivity analysis also showed that PLEKHA4 expression was negatively correlated with the sensitivity of several small molecule kinase inhibitors. Furthermore, in vitro experiments confirmed that PLEKHA4 knockdown inhibited the proliferation of glioma cells. Conclusions: PLEKHA4 is highly expressed in glioma tissues and correlated with tumour stemness, immune cell infiltration and proliferation, suggesting its potential as a novel prognostic biomarker and therapeutic target in glioma

Seismic Response Analysis and Connection Performance Evaluation of a Hybrid Coupled PEC Wall System

This paper proposes a hybrid coupled partially encased composite (PEC) wall system, obtained through the connection of two PEC walls by means of the shear critical steel coupling beams with an innovative welded connection. This structural solution is designed to take advantage of both the stiffness of the PEC walls (required to limit building damage under frequent earthquakes) and the ductility of the steel coupling beams (necessary to dissipate energy under medium-intensity and high-intensity earthquakes). The connection performance of an innovative rigid joint with different configurations in this system is studied through pseudostatic analysis, and the seismic performance of the proposed hybrid coupled PEC wall system is evaluated through multirecord nonlinear dynamic analysis of a set of case studies. Adopted finite element models are developed and validated against the available experimental results. A summary of the results is presented and discussed to highlight the potential of the proposed hybrid coupled PEC wall systems. The key feature of this system is development of a reasonable two-level yielding mechanism (the first level is the yielding of the coupling beams, and the second level is the yielding of the PEC wall) without damage to the welded joints

Table_1_The use of generalized synthetic control method to evaluate air pollution control measures of G20 Hangzhou Summit.DOCX

The traditional campaign-style enforcement in environmental governance has been debated whether its rebound effect is likely to eat away the short-term environmental benefits and subsequently bring about severer pollution. There are methodological challenges in assessing the effect of temporary environmental intervention. By applying the generalized synthetic control method (GSCM), we quantified and characterized the effectiveness of environmental regulations implemented for the G20 Hangzhou Summit held on 4–5 September, 2016. The summit was successful in reducing Air Quality Composite Index by 17.40% (95% CI: 9.53%, 24.60%), 13.30% (95% CI: 4.23%, 21.50%), and 10.09% (95% CI: 2.01%, 17.51%) in the core, strictly-regulated and regulated areas respectively, comparing with the index expected under a “No-G20” scenario during the preparatory period and the summit period (July–September 2016), and the reduction of the levels in specific pollutants (PM10, PM2.5, NO2, and CO) was also observed. Besides, the environmental benefits lasted for at least 3 months after the summit. This study demonstrates that the pollution control measures during the G20 Hangzhou Summit improved air quality immediately and continuously, and the GSCM provides a useful tool for evaluating the intervention effects of environmental regulations.</p

Resection of high-grade glioma involving language areas assisted by multimodal techniques under general anesthesia: a retrospective study

Abstract Background Multimodal techniques-assisted resection of glioma under general anesthesia (GA) has been shown to achieve similar clinical outcomes as awake craniotomy (AC) in some studies. In this study, we aim to validate the use of multimodal techniques can achieve the maximal safe resection of high-grade glioma involving language areas (HGILAs) under GA. Methods HGILAs cases were reviewed and collected between January 2009 and December 2020 in our center. Patients were separated into multimodal group (using neuronavigation, intraoperative MRI combined with direct electrical stimulation [DES] and neuromonitoring [IONM]) and conventional group (neuronavigation alone) and clinical outcomes were compared between groups. Studies of HGILAs were reviewed systematically and the meta-analysis results of previous (GA or AC) studies were compared with our results. Results Finally, there were 263 patients in multimodal group and 137 patients in conventional group. Compared to the conventional group, the multimodal group achieved the higher median EOR (100% versus 94.32%, P < 0.001) and rate of gross total resection (GTR) (73.8% versus 36.5%, P < 0.001) and the lower incidence of permanent language deficit (PLD) (9.5% versus 19.7%, P = 0.004). The multimodal group achieved the longer median PFS (16.8 versus 10.3 months, P < 0.001) and OS (23.7 versus 15.7 months, P < 0.001) than the conventional group. The multimodal group achieved a higher rate of GTR than the cohorts in previous multimodal studies under GA and AC (73.8% versus 55.7% [95%CI 32.0–79.3%] versus 53.4% [35.5–71.2%]). The multimodal group had a lower incidence of PLD than the cohorts in previous multimodal studies under GA (9.5% versus 14.0% [5.8–22.1%]) and our incidence of PLD was a little higher than that of previous multimodal studies under AC (9.5% versus 7.5% [3.7–11.2%]). Our multimodal group also achieved a relative longer survival than previous studies. Conclusions Surgery assisted by multimodal techniques can achieve maximal safe resection for HGILAs under GA. Further prospective studies are needed to compare GA with AC for HGILAs