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"Li, Qiang"
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Revisiting the determinants of CO2 emissions: The role of higher education under the extended STIRPAT model
This study directly aligns with Sustainable Development Goals (SDGs), i.e., SDG-13 and SDG-4. Carbon emissions (CO2e) are primarily addressed under SDG-13: Climate Action, which aims to combat climate change and its impacts. CO2e reduction efforts contribute to achieving this goal by mitigating greenhouse gas emissions. SDG 4: Quality Education aims to ensure inclusive and equitable quality education for all. It emphasizes explicitly lifelong learning opportunities and targets higher education (HE) access to improve skills for sustainable development. Therefore, the current study aims to examine the determinants of CO2e in China and the role of HE under the extended STIRPAT model. This study utilizes the Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) methods using the time series data from 1985 to 2023. The finding shows that total population, GDP, and industry positively affect CO2e, while technological innovation and higher education negatively affect CO2e in China.
Journal Article
Spatial epidemiological analysis based on township scale and analysis of influencing factors of pulmonary tuberculosis cure of Changshu city from 2015 to 2022
This study aimed to enhance the prevention and control of pulmonary tuberculosis (PTB) and provide more effective and accurate methods in Changshu City.
The PTB patients' information came from the China Information System for Disease Control and Prevention (CISDCP). The demographic data for Changshu city and towns came from the Suzhou Statistical Yearbook and the LandScan platform. ArcGIS was used for global spatial autocorrelation analysis and local spatial autocorrelation analysis. Univariate logistic regression and multivariate logistic regression were used to analyze the influencing factors of cured PTB patients. The receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to analyze the predictive efficacy and clinical benefit of the indicators. XGBoost analysis was performed to explore the feature importance of key metrics for PTB outcome.
A total of 3943 PTB cases were included. The annual incidence rate of new PTB in Changshu city was 27.081 per 100,000. Changshu High-tech Industrial Development Zone in Jiangsu Province and Shajiabang town were the high-high aggregation areas and hot spot areas. Diagnosis delay, TB strain types, and drug sensitivity were independent predictors of the cure of new PTB patients.
The central and southern areas of Changshu were the high-high cluster areas and hot spots for PTB. Shorter diagnosis delay days and mycobacterium tuberculosis (MTB) promote the cure of tuberculosis, while drug sensitivity was a risk factor for its cure.
Journal Article
Cryo-EM structure of an amyloid fibril formed by full-length human prion protein
Prion diseases are caused by the misfolding of prion protein (PrP). Misfolded PrP forms protease-resistant aggregates in vivo (PrPSc) that are able to template the conversion of the native form of the protein (PrPC), a property shared by in vitro–produced PrP fibrils. Here we produced amyloid fibrils in vitro from recombinant, full-length human PrPC (residues 23–231) and determined their structure using cryo-EM, building a model for the fibril core comprising residues 170−229. The PrP fibril consists of two protofibrils intertwined in a left-handed helix. Lys194 and Glu196 from opposing subunits form salt bridges, creating a hydrophilic cavity at the interface of the two protofibrils. By comparison with the structure of PrPC, we propose that two α-helices in the C-terminal domain of PrPC are converted into β-strands stabilized by a disulfide bond in the PrP fibril. Our data suggest that different PrP mutations may play distinct roles in modulating the conformational conversion.A cryo-EM structure of amyloid fibrils formed in vitro with recombinant human PrP provides insights into fibril architecture and the potential role of disease mutations.
Journal Article
Comprehensive metabolomics expands precision medicine for triple-negative breast cancer
Metabolic reprogramming is a hallmark of cancer. However, systematic characterizations of metabolites in triple-negative breast cancer (TNBC) are still lacking. Our study profiled the polar metabolome and lipidome in 330 TNBC samples and 149 paired normal breast tissues to construct a large metabolomic atlas of TNBC. Combining with previously established transcriptomic and genomic data of the same cohort, we conducted a comprehensive analysis linking TNBC metabolome to genomics. Our study classified TNBCs into three distinct metabolomic subgroups: C1, characterized by the enrichment of ceramides and fatty acids; C2, featured with the upregulation of metabolites related to oxidation reaction and glycosyl transfer; and C3, having the lowest level of metabolic dysregulation. Based on this newly developed metabolomic dataset, we refined previous TNBC transcriptomic subtypes and identified some crucial subtype-specific metabolites as potential therapeutic targets. The transcriptomic luminal androgen receptor (LAR) subtype overlapped with metabolomic C1 subtype. Experiments on patient-derived organoid and xenograft models indicate that targeting sphingosine-1-phosphate (S1P), an intermediate of the ceramide pathway, is a promising therapy for LAR tumors. Moreover, the transcriptomic basal-like immune-suppressed (BLIS) subtype contained two prognostic metabolomic subgroups (C2 and C3), which could be distinguished through machine-learning methods. We show that N-acetyl-aspartyl-glutamate is a crucial tumor-promoting metabolite and potential therapeutic target for high-risk BLIS tumors. Together, our study reveals the clinical significance of TNBC metabolomics, which can not only optimize the transcriptomic subtyping system, but also suggest novel therapeutic targets. This metabolomic dataset can serve as a useful public resource to promote precision treatment of TNBC.
Journal Article
Phase-only transmissive spatial light modulator based on tunable dielectric metasurface
Rapidly developing augmented reality, solid-state light detection and ranging (LIDAR), and holographic display technologies require spatial light modulators (SLMs) with high resolution and viewing angle to satisfy increasing customer demands. Performance of currently available SLMs is limited by their large pixel sizes on the order of several micrometers. Here, we propose a concept of tunable dielectric metasurfaces modulated by liquid crystal, which can provide abrupt phase change, thus enabling pixel-size miniaturization. We present a metasurface-based transmissive SLM, configured to generate active beam steering with >35% efficiency and a large beam deflection angle of 11°. The high resolution and steering angle obtained provide opportunities to develop the next generation of LIDAR and display technologies.
Journal Article
Observation of inhomogeneous plasmonic field distribution in a nanocavity
The progress of plasmon-based technologies relies on an understanding of the properties of the enhanced electromagnetic fields generated by the coupling nanostrucutres1–6. Plasmon-enhanced applications include advanced spectroscopies7–10, optomechanics11, optomagnetics12 and biosensing13–17. However, precise determination of plasmon field intensity distribution within a nanogap remains challenging. Here, we demonstrate a molecular ruler made from a set of viologen-based, self-assembly monolayers with which we precisely measures field distribution within a plasmon nanocavity with ~2-Å spatial resolution. We observed an unusually large plasmon field intensity inhomogeneity that we attribute to the formation of a plasmonic comb in the nanocavity. As a consequence, we posit that the generally adopted continuous media approximation for molecular monolayers should be used carefully.The strength of the plasmonic field between a plasmonic particle and a Au surface can be measured at ~2-Å resolution by following the Raman peaks of a suitably labelled self-assembly monolayer.
Journal Article