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Increasing exposure to heatwaves threatens public health, challenging various socioeconomic sectors in the coming decades. Prior studies mostly concentrated on the heatwaves occurring in specific regions by examining temperature durations, ignoring the fact that heatwaves typically swept across a large area. To comprehensively assess the effects of heatwaves, we jointly analyzed public attention to heatwaves using a dataset of over 10 million geo-located Weibo tweets across 321 cities in China. By considering spatial disparities, two kinds of public attention at city level, namely the number of heat-related tweets (NHTs) and the ratio of heat-related tweets (RHTs), were designed to indicate the severity and location of heatwave impacts, respectively. The heat cumulative intensity was used as a proxy for heatwaves, which exhibited more significant correlations with RHTs than NHTs. The multiscale geographically weighted regression (MGWR) model was employed to investigate the spatiotemporal variations of environment, demographic, and economic-social factors. Six city groups were clustered with MGWR coefficients that were consistent with the seven geographic subregions of China. This research provides a new perspective and methodology for public attention to heatwaves using geo-located social sensing data and highlights the need for actions to mitigate future heatwave stress in sensitive cities.

ABSTRACTMegaregion has emerged as a global urban form, typically based on the polycentric strategy to enhance regional development. How to measure megaregional spatial structure and discriminate different roles of cities has become increasingly important to enrich the knowledge of the formation of a megaregion. Meanwhile, various indices have been used to identify vital nodes in the field of complex network. Which indices, however, are suitable for megaregion analysis remain unsolved. To address this requirement, this study first reviewed the typical indices for identifying vital nodes in the complex network theory, and pointed out that in a weighted city network scenario, weighted degree centrality, hub & authority score, and S-core decomposition (which represent network centrality, connectivity, and structures, respectively) are suitable for analyzing megaregional spatial structures. Then, we explored the city hierarchies and spatial structure in Guangdong Province, China, using the three indices. The hierarchical structure of the weighted city network in Guangdong Province had been identified using S-core decomposition. From the perspective of polycentric structure, Guangzhou and Shenzhen have the strongest node degrees and strength of mobility flows, while the Guangzhou-Dongguan-Shenzhen corridor has been identified via the hub & authority score which is designed to evaluate the connectivity in a weighted network. Moreover, we conducted a comparison analysis of three indices. The findings of this study not only enrich the understanding of city hierarchies and the structure of a megaregion, but also highlight that although various indices are available, they should be applied selectively in accordance with the study context.

Station-level ridership is an important indicator for understanding the relationship between land use and rail transit, which is crucial for building more sustainable urban mobility systems. However, the nonlinear effects of the built environment on metro ridership, particularly concerning temporal heterogeneity, have not been adequately explained. To address this gap, this study proposes a versatile methodology that employs the eXtreme gradient boosting (XGBoost) tree to analyze the effects of factors on station-level ridership variations and compares these results with those of a multiple regression model. In contrast to conventional feature interpretation methods, this study utilized Shapley additive explanations (SHAP) to detail the nonlinear effects of each factor on station-level ridership across temporal dimensions (weekdays and weekends). Using Shanghai as a case study, the findings confirmed the presence of complex nonlinear and threshold effects of land-use, transportation, and station-type factors on station-level ridership in the association. The factor “Commercial POI” represents the most significant influence on ridership changes in both the weekday and weekend models; “Public Facility Station” plays a role in increasing passenger flow in the weekend model, but it shows the opposite effect on the change in ridership in the weekday model. This study highlights the importance of explainable machine learning methods for comprehending the nonlinear influences of various factors on station-level ridership.

Esters can be used as fuels and specialty chemicals for food flavoring, cosmetic and pharmaceutical industries. Here, the authors systematically engineer clostridia, including discovery and deletion of prophages to increase strain stability, for the production of butyl acetate and butyl butyrate from corn stover at low cost.

Abstract Background The treatment of hepatic injury can be complex. Medical clinical centers are often the first line hospitals for the diagnosis and treatment of hepatic trauma in China. The aim of the study is to summarize the experience in the diagnosis and treatment of hepatic trauma in one medical clinical center in China. Methods This retrospective study included patients with hepatic trauma admitted between January 2002 and December 2019 at the Xishan People’s Hospital of Wuxi. The outcomes were cure rate and death within 14 days post-discharge. Results Among the 318 patients with hepatic trauma, 146 patients underwent surgical treatment, and 172 received conservative treatment; three patients were transferred to other hospitals for further treatment; 283 patients were cured, and 35 died. Severe hepatic trauma occurred in 74 patients, with a mortality rate of 31.1% and accounting for 65.7% of total mortality. American Association for the Surgery of Trauma (AAST) grading ≥ III (OR = 3.51, 95%CI: 1.32–9.37, P = 0.012) and multiple organ injury (OR = 7.51, 95%CI: 2.51–22.46, P

Abstract Protein homeostasis is critical for maintaining eukaryotic cell function as well as responses to intrinsic and extrinsic stress. The proteasome is a major portion of the proteolytic machinery in mammalian cells and plays an important role in protein homeostasis. Multiple myeloma (MM) is a plasma cell malignancy with high production of immunoglobulins and is especially sensitive to treatments that impact protein catabolism. Therapeutic agents such as proteasome inhibitors have demonstrated significant benefit for myeloma patients in all treatment phases. Here, we demonstrate that the 11S proteasome activator PA28α is upregulated in MM cells and is key for myeloma cell growth and proliferation. PA28α also regulates MM cell sensitivity to proteasome inhibitors. Downregulation of PA28α inhibits both proteasomal load and activity, resulting in a change in protein homeostasis less dependent on the proteasome and leads to cell resistance to proteasome inhibitors. Thus, our findings suggest an important role of PA28α in MM biology, and also provides a new approach for targeting the ubiquitin-proteasome system and ultimately sensitivity to proteasome inhibitors.

Abstract Background Clostridium saccharoperbutylacetonicum N1-4 (HMT) is a strictly anaerobic, spore-forming Gram-positive bacterium capable of hyper-butanol production through the well-known acetone–butanol–ethanol fermentation process. Recently, five putative RRNPP-type QSSs (here designated as QSS1 to QSS5) were predicted in this bacterial strain, each of which comprises a putative RRNPP-type regulator (QssR1 to QssR5) and a cognate signaling peptide precursor (QssP1 to QssP5). In addition, both proteins are encoded by the same operon. The functions of these multiple RRNPP-type QSSs are unknown. Results To elucidate the function of multiple RRNPP-type QSSs as related to cell metabolism and solvent production in N1-4 (HMT), we constructed qssR-deficient mutants ΔR1, ΔR2, ΔR3 and ΔR5 through gene deletion using CRISPR–Cas9 and N1-4-dcas9-R4 (with the QssR4 expression suppressed using CRISPR–dCas9). We also constructed complementation strains by overexpressing the corresponding regulator gene. Based on systematic characterization, results indicate that QSS1, QSS2, QSS3, and QSS5 positively regulate the sol operon expression and thus solvent production, but they likely negatively regulate cell motility. Consequently, QSS4 might not directly regulate solvent production, but positively affect cell migration. In addition, QSS3 and QSS5 appear to positively regulate sporulation efficiency. Conclusions Our study provides the first insights into the roles of multiple RRNPP-type QSSs of C. saccharoperbutylacetonicum for the regulation of solvent production, cell motility, and sporulation. Results of this study expand our knowledge of how multiple paralogous QSSs are involved in the regulation of essential bacterial metabolism pathways.

Fine-grained subjective partitioning of urban space using human activity flows reveals actual human activity spaces with high resolution, which has great implications for the development and validation of planning strategies. This paper presents a new method for fine-grained subjective partitioning of urban space based on the combination of network analysis and human interactions from social media. Three main procedures are involved in this method: 1) a cut-off point for hierarchical partitioning is determined by fitting the probability distribution function of human activity patterns; 2) based on this cut-off point, improved hierarchical weighted-directed spatial networks are constructed by incorporating a gravity model into conventional spatial networks to take into account the importance of the attraction of nodes in shaping urban space; and 3) the hierarchical and fine-grained partitioning results, which reveal the actual human activity spaces with high resolution at multiscale are obtained by implementing a spatial community detection algorithm in these networks. A case study, using a real-world dataset from the capital of China validates the effectiveness of the proposed method. By analyzing the results from Beijing, we concluded that the social media, a gravity model, and the hierarchical subjective communities detected from the hierarchical human activity networks are all outstanding contributors to the fine-grained subjective partitioning of urban spaces.

In recent years, deploying Internet of Things (IoT) in electronic healthcare systems (EHS) has made great progress in healthcare detection. It is extremely important to reduce the cost of communication and ensure the authenticity and integrity of data. A linearly homomorphic signature scheme can solve the above problems. However, when the scale of EHS is too large, the transmission, storage and verification of signatures need a high cost. An aggregate signature can combine many signatures generated by many different users into a short one. Therefore, only one aggregate signature needs to be processed during verification, transmission and storage. Combining the advantages of aggregate signature and linearly homomorphic signature, this paper proposes an aggregate signature scheme based on a linearly homomorphic signature for EHS, which has both linear homomorphism and aggregation, and realizes double data compression. Moreover, our scheme can resist a potential real attack, named a coalition attack. The security of this scheme is rigorously demonstrated based on the computational Diffie–Hellman assumption in the random oracle model.

Transit-oriented development (TOD) is among the most feasible strategies for relieving urban issues caused by the unbalanced development of transportation and land use. This study proposes a multiobjective TOD land use design framework for the optimization of the land use layout in station catchments. Given the high density and diverse development in Chinese megacities, a planning model that considers nonlinear impacts on ridership, land use efficiency, quality of life, and the environment is constructed. The model applies fine-grained geo-big data to fill gaps in the empirical and statistical data and improve practicability. A genetic multiobjective optimization approach without reliance on objective weighting is used to generate alternative land use schemes. A metro station in Shanghai is applied as a case study. The results indicate that the proposed ridership objective outperforms the commonly used linear function, and the optimization method has superior extreme optima and convergence to baseline models. We also discuss the consistencies and conflicts in the objectives and provide a balanced land use scheme considering local policies. This work provides suggestions for sustainable urban design with coordinated land use and transportation.

Although immune checkpoint inhibitors (ICIs) have shown remarkable benefit for treatment of advanced non-small lung cancer (NSCLC), only a minority of patients can achieve durable responses and the most patients produce an ultra-rapid progressive disease. Here, we collected the availably published datasets and mined the determinants of response to immunotherapy on pathway levels. One hundred six NSCLC patients treated with immunotherapy were combined from Rizvi et al. and Hellman et al. studies (whole exon sequencing). Two independent validation datasets consisted of the MSKCC cohort (targeted sequencing) and data by Anagnostou and colleagues (whole exon sequencing). The Cancer Genome Atlas (TCGA) somatic mutation and gene expression data were applied to explore the immunobiology features. In the first combined cohort, we detected NOTCH pathway altered in 71% patients with durable clinical benefit (DCB) while only 36% among no durable benefit (NDB) (p = 0.005). Compared to NDB group, co-occurrence of NOTCH and at least two DDR (co-DDR) pathway was discovered in DCB group and contributed to a prolonged progression-free survival (PFS) [22.1 vs 3.6 months, p < 0.0001, HR, 0.34, 95% confidence interval (CI), 0.2–0.59]. In two independent datasets, co-occurrence of NOTCH+/co-DDR+ was also validated to be a better immunotherapy efficacy [Cohort 2: 13 vs 6 months, p = 0.034, HR, 0.55, 95% CI, 0.31–0.96; Cohort 3: 21 vs 11 months, p = 0.067, HR, 0.45, 95% CI, 0.18–1.1]. By analyzing TCGA cohort, we found patients with coexisting NOTCH+/co-DDR+ pathway had a higher TMB, more infiltration of CD4+T cells. Overall, co-occurrence of NOTCH and co-DDR pathway reflect a better immunotherapy efficacy in advanced NSCLC. This genomic predictor show promise in stratifying patients that suit for immunotherapy for future clinical practice.

The turning points of housing prices play a significant role in the real estate market and economy. However, because multiple factors impact the market, the prediction of the turning points of housing prices faces significant challenges. To solve this problem, in this study, a historical data-based model that incorporates a multi-population genetic algorithm with elitism into the log-periodic power law model is proposed. This model overcomes the weaknesses of multivariate and univariate methods that it does not require any external factors while achieving excellent interpretations. We applied the model to the case study collected from housing prices in Wuhan, China, from December 2016 to October 2018. To verify its reliability, we compared the results of the proposed model to those of the log-periodic power law model optimized by the standard genetic algorithm and simulated annealing, the results of which indicate that the proposed model performs best in terms of prediction. Efficiently predicting and analyzing the housing prices will help the government promulgate effective policies for regulating the real estate market and protect home buyers.

Abstract Background Sucrose is an naturally abundant and easily fermentable feedstock for various biochemical production processes. By now, several sucrose utilization pathways have been identified and characterized. Among them, the pathway consists of sucrose permease and sucrose phosphorylase is an energy-conserving sucrose utilization pathway because it consumes less ATP when comparing to other known pathways. Bacillus amyloliquefaciens NK-1 strain can use sucrose as the feedstock to produce poly-γ-glutamic acid (γ-PGA), a highly valuable biopolymer. The native sucrose utilization pathway in NK-1 strain consists of phosphoenolpyruvate-dependent phosphotransferase system and sucrose-6-P hydrolase and consumes more ATP than the energy-conserving sucrose utilization pathway. Results In this study, the native sucrose utilization pathway in NK-1 was firstly deleted and generated the B. amyloliquefaciens 3Δ strain. Then four combination of heterologous energy-conserving sucrose utilization pathways were constructed and introduced into the 3Δ strain. Results demonstrated that the combination of cscB (encodes sucrose permease) from Escherichia coli and sucP (encodes sucrose phosphorylase) from Bifidobacterium adolescentis showed the highest sucrose metabolic efficiency. The corresponding mutant consumed 49.4% more sucrose and produced 38.5% more γ-PGA than the NK-1 strain under the same fermentation conditions. Conclusions To our best knowledge, this is the first report concerning the enhancement of the target product production by introducing the heterologous energy-conserving sucrose utilization pathways. Such a strategy can be easily extended to other microorganism hosts for reinforced biochemical production using sucrose as substrate.

Abstract Background Poly-γ-glutamic acid (γ-PGA) is a valuable polymer with glutamate as its sole precursor. Enhancement of the intracellular glutamate synthesis is a very important strategy for the improvement of γ-PGA production, especially for those glutamate-independent γ-PGA producing strains. Corynebacterium glutamicum has long been used for industrial glutamate production and it exhibits some unique features for glutamate synthesis; therefore introduction of these metabolic characters into the γ-PGA producing strain might lead to increased intracellular glutamate availability, and thus ultimate γ-PGA production. Results In this study, the unique glutamate synthesis features from C. glutamicum was introduced into the glutamate-independent γ-PGA producing Bacillus amyloliquefaciens NK-1 strain. After introducing the energy-saving NADPH-dependent glutamate dehydrogenase (NADPH-GDH) pathway, the NK-1 (pHT315-gdh) strain showed slightly increase (by 9.1%) in γ-PGA production. Moreover, an optimized metabolic toggle switch for controlling the expression of ɑ-oxoglutarate dehydrogenase complex (ODHC) was introduced into the NK-1 strain, because it was previously shown that the ODHC in C. glutamicum was completely inhibited when glutamate was actively produced. The obtained NK-PO1 (pHT01-xylR) strain showed 66.2% higher γ-PGA production than the NK-1 strain. However, the further combination of these two strategies (introducing both NADPH-GDH pathway and the metabolic toggle switch) did not lead to further increase of γ-PGA production but rather the resultant γ-PGA production was even lower than that in the NK-1 strain. Conclusions We proposed new metabolic engineering strategies to improve the γ-PGA production in B. amyloliquefaciens. The NK-1 (pHT315-gdh) strain with the introduction of NADPH-GDH pathway showed 9.1% improvement in γ-PGA production. The NK-PO1 (pHT01-xylR) strain with the introduction of a metabolic toggle switch for controlling the expression of ODHC showed 66.2% higher γ-PGA production than the NK-1 strain. This work proposed a new strategy for improving the target product in microbial cell factories.

Alleviating public traffic congestion is an efficient and effective way to improve the travel time reliability and quality of public transport services. The existing public network optimization models usually ignored the essential impact of public traffic congestion on the performance of public transport service. To address this problem, this study proposes a data-based methodology to estimate the traffic congestion of road segments between bus stops (RSBs). The proposed methodology involves two steps: 1) Extracting three traffic indicators of the RSBs from smart card data and bus trajectory data; 2) The self-organizing map (SOM) is used to cluster and effectively recognize traffic patterns embedded in the RSBs. Furthermore, a congestion index for ranking the SOM clusters is developed to determine the congested RSBs. A case study using real-world datasets from a public transport system validates the proposed methodology. Based on the congested RSBs, an exploratory example of public transport network optimization is discussed and evaluated using a genetic algorithm. The clustering results showed that the SOM could suitably reflect the traffic characteristics and estimate traffic congestion of the RSBs. The results obtained in this study are expected to demonstrate the usefulness of the proposed methodology in sustainable public transport improvements.

In this study, the complete sequence of the mitochondrial DNA (mtDNA) of Ctenolepisma villosa was obtained using next-generation sequencing approaches and de novo assembly. The molecule was found to be 15,488 bp in length. It is the fourth complete mt genome sequence from the Zygentoma. The mt genomes are circular and encode 37 genes and a large non-coding region. The overall structure (gene number, orientation, and order) of the mt genomes is the same as that found in three other sequenced species. All protein-coding sequences except cox1 start with the typical ATN codon. Cox1 begins with TTG, which may be a common codon in Zygentoma insects. Stem-loop structure can be observed in the largest non-coding region thought to be involved in the regulation of replication and transcription of the mitochondrial genome.

The spatial structures of cities have changed dramatically with rapid socio-economic development in ways that are not well understood. To support urban structural analysis and rational planning, we propose a framework to identify urban functional regions and quantitatively explore the intensity of the interactions between them, thus increasing the understanding of urban structures. A method for the identification of functional regions via spatial semantics is proposed, which involves two steps: (1) the study area is classified into three types of functional regions using taxi origin/destination (O/D) flows; and (2) the spatial semantics for the three types of functional regions are demonstrated based on point-of-interest (POI) categories. To validate the existence of urban functional regions, we explored the intensity of interactions quantitatively between them. A case study using POI data and taxi trajectory data from Beijing validates the proposed framework. The results show that the proposed framework can be used to identify urban functional regions and promotes an enhanced understanding of urban structures.

Abstract Long-read sequencing, exemplified by PacBio, revolutionizes genomics, overcoming challenges like repetitive sequences. However, the high DNA requirement ( > 1 µg) is prohibitive for small organisms. We develop a low-input (100 ng), low-cost, and amplification-free library-generation method for PacBio sequencing (LILAP) using Tn5-based tagmentation and DNA circularization within one tube. We test LILAP with two Drosophila melanogaster individuals, and generate near-complete genomes, surpassing preexisting single-fly genomes. By analyzing variations in these two genomes, we characterize mutational processes: complex transpositions (transposon insertions together with extra duplications and/or deletions) prefer regions characterized by non-B DNA structures, and gene conversion of transposons occurs on both DNA and RNA levels. Concurrently, we generate two complete assemblies for the endosymbiotic bacterium Wolbachia in these flies and similarly detect transposon conversion. Thus, LILAP promises a broad PacBio sequencing adoption for not only mutational studies of flies and their symbionts but also explorations of other small organisms or precious samples.

Understanding the precise mechanism of BMSC (bone marrow mesenchymal stem cell) osteogenesis is critical for metabolic bone diseases and bone reconstruction. The histone-lysine N-methyltransferase 2D (KMT2D) acts as an important methyltransferase related with congenital skeletal disorders, yet the function of KMT2D in osteogenesis was unclear. Here we found that KMT2D expression was decreased in BMSCs collected from ovariectomized mice. Moreover, during human BMSC differentiation under mineralization induction, the mRNA level of KMT2D was gradually elevated. After KMT2D knockdown, the in vitro osteogenic differentiation of BMSCs was inhibited, while the in vivo bone formation potential of BMSCs was attenuated. Further, in BMSCs, KMT2D knockdown reduced the level of phosphorylated protein kinase B (p-AKT). SC-79, a common activator of AKT signaling, reversed the suppressing influence of KMT2D knockdown on BMSCs differentiation towards osteoblast. These results indicate that the KMT2D-AKT pathway plays an essential role in the osteogenesis process of human BMSCs (hBMSCs), which might provide new avenues for the molecular medicine of bone diseases and regeneration.

At night, clear pavement markings are essential for driver safety. Currently, markings visibility evaluation relies on the retroreflectivity, but the impact of line width is unclear. To quantify the impact of line width on visibility and to refine visibility evaluation methods, a driver visual detection experiment was designed using both qualitative and quantitative approaches. Twenty-four drivers of small vehicles were randomly recruited to participate in visual detection tests of a total of 54 white pavement markings (comprising 6 widths and 9 retroreflectivity levels) under the illumination of high beams, following the principle of using the “emergence point” as the critical state for assessing pavement marking visibility. This study indicated that widening pavement markings significantly enhances their visibility, particularly for markings with low retroreflectivity. A visibility evaluation model was established to quantify the impact of width and retroreflectivity on the visual distance of markings. The model confirms that widening markings can improve visibility, thereby reducing the required level of retroreflectivity. The research methodology and findings provide technical support for managers to more accurately assess nighttime safety visibility during pavement marking operation and maintenance.

Guipi wan (GPW) is a traditional Chinese medicine commonly used in clinical practice, typically to treat neurological diseases such as neurasthenia and traumatic brain injury. It may have positive effects on cerebral ischemia‒reperfusion injury (cI/R). This study aimed to assess the effects of GPW in a mouse model of cI/R and find its possible targets. C57BL/6J mice were used to establish the cI/R model, and the laser speckle doppler was used to determine the success of the model. GPW was administered intragastrically for 7 days, brain tissue sections were stained with TTC, HE, and TUNEL, Western blot assay was performed to detect the effect of apoptosis-related proteins. Furthermore, we screened active ingredients from the TCM Database and constructed a compound‒target network using the Cytoscape 3.8.0 software. Moreover, we employed protein‒protein interaction and component‒target‒pathway network analyses to determine the potential components of GPW and its target genes, the key target was verified through molecular docking. Finally, we detected the influence of the downstream signaling pathway of the target through Western blot. The results showed that GPW decreased the cerebral infarction area, neurological function scores, and neuronal apoptosis in mice by regulating PI3K/AKT signaling pathway. Network analysis indicated that gamma-aminobutyric acid B receptor 1 (GABBR1) might be a potential target for the treatment of cI/R. Molecular docking indicated that 9 active components in GPW could bind to GABBR1 with desirable binding energy. This study represented the demonstratable effect of GPW in the treatment of cI/R injury and suggested GABBR1 as a potential target using network analysis.