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China, the world leader in automobile production and sales, confronts the challenge of transportation emissions, which account for roughly 10% of its total carbon emissions. This study, utilizing real-world vehicle data from three major Chinese cities, assesses the impact of Battery Electric Vehicles (BEVs) on air quality. Our analysis reveals that BEVs, when replacing gasoline vehicles in their operational phase, significantly reduce emissions, with reductions ranging from 8.72 to 85.71 kg of CO 2 per vehicle monthly. The average monthly reduction rate is 9.47%, though this effect is less pronounced during winter. Advanced BEVs, characterized by higher efficiency and newer technology, exhibit greater emission reduction benefits. While private BEVs generally contribute positively to environmental outcomes, taxi BEVs, due to their intensive usage patterns, show less environmental advantage and may sometimes worsen air quality. Looking ahead, we project substantial emission reductions from the replacement of gasoline vehicles with electric alternatives over the next decade. Policymakers are urged to adopt proactive measures, focusing on promoting medium to large electric vehicles and fostering the use of private and ride-hailing electric vehicles.

On-road vehicle emissions are a major contributor to elevated air pollution levels in populous metropolitan areas. We developed a link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet), based on multiple datasets extracted from the extensive road traffic monitoring network that covers the entire municipality of Beijing, China (16 400 km2). We employed the EMBEV-Link model under various traffic scenarios to capture the significant variability in vehicle emissions, temporally and spatially, due to the real-world traffic dynamics and the traffic restrictions implemented by the local government. The results revealed high carbon monoxide (CO) and total hydrocarbon (THC) emissions in the urban area (i.e., within the Fifth Ring Road) and during rush hours, both associated with the passenger vehicle traffic. By contrast, considerable fractions of nitrogen oxides (NOx), fine particulate matter (PM2.5) and black carbon (BC) emissions were present beyond the urban area, as heavy-duty trucks (HDTs) were not allowed to drive through the urban area during daytime. The EMBEV-Link model indicates that nonlocal HDTs could account for 29 % and 38 % of estimated total on-road emissions of NOx and PM2.5, which were ignored in previous conventional emission inventories. We further combined the EMBEV-Link emission inventory and a computationally efficient dispersion model, RapidAir®, to simulate vehicular NOx concentrations at fine resolutions (10 m × 10 m in the entire municipality and 1 m × 1 m in the hotspots). The simulated results indicated a close agreement with ground observations and captured sharp concentration gradients from line sources to ambient areas. During the nighttime when the HDT traffic restrictions are lifted, HDTs could be responsible for approximately 10 µg m−3 of NOx in the urban area. The uncertainties of conventional top-down allocation methods, which were widely used to enhance the spatial resolution of vehicle emissions, are also discussed by comparison with the EMBEV-Link emission inventory.

Macrophage autophagy plays a major role in the control and elimination of invading Mycobacterium tuberculosis. However, the function and mechanism of circRNA on macrophage autophagy in tuberculosis remain unclear. Therefore, this study aimed to explore the role of circRNA underlying macrophage autophagy in tuberculosis. Quantitative real-time polymerase chain reaction was used to detect the expression of hsa_circ_0045474, miR-582-5p and TNKS2. Autophagy was detected by LC3B immunofluorescence and transmission electron microscopy. Dual-luciferase reporter assays were used to detect the relationship of miR-582-5p and hsa_circ_0045474 or TNKS2. Western blot was used to detect the expression of LC3-І and LC3-ІІ. The results showed that hsa_circ_0045474 was down-regulated in monocytes from patients with tuberculosis and induced autophagy in macrophages. hsa_circ_0045474 sponged miR-582-5p and negatively regulated miR-582-5p expression. Overexpression of miR-582-5p affected by hsa_circ_0045474 induced autophagy in macrophages. TNKS2 served as a target of miR-582-5p and down-regulation of TNKS2 induced autophagy in macrophages regulated by miR-582-5p. In conclusion, our results demonstrated that hsa_circ_0045474 down-regulation induced macrophage autophagy in tuberculosis via miR-582-5p/ TNKS2 axis, implying a novel strategy to treat the occurrence of active pulmonary tuberculosis caused by immune escape of M. tuberculosis.

We investigated if corilagin can ameliorate or reverse atherosclerotic development via the toll-like receptor 4 (TLR4) signaling pathway and . Ana-1 cells or mouse peritoneal macrophages (MPMs) were stimulated with oxidized low-density lipoprotein followed by corilagin treatment. TLR4 expression in Ana-1 cells was upregulated by lentiviral transduction and downregulated by small interfering RNA. Peripheral blood mononuclear cells (PBMCs), plasma samples, and femoral arteries were collected from rats exhibiting peripheral artery disease (PAD). mRNA and protein expression of TLR4 and downstream molecules were decreased significantly by corilagin treatment in Ana-1 cells, MPMs, and rat PBMCs, and the reduction remained irrespective of downregulation or upregulation of TLR4 expression in Ana-1 cells. Corilagin also exerted a prominent effect on changes in plasma levels of cytokines and the pathologic manifestation of atherosclerosis in femoral arteries. Corilagin could ameliorate the development of atherosclerotic plaques by inhibiting the TLR4 signaling pathway in monocyte/macrophages and reduce the release of proinflammatory cytokines. This study provides a new therapeutic target and new targeting drug to oppose atherosclerosis and reveals the enormous potential of corilagin for control of PAD in humans.

Parkinson's disease (PD) is a progressive, chronic, and neurodegenerative disorder that is primarily diagnosed by clinical examinations and magnetic resonance imaging (MRI). In this study, we proposed a machine learning based radiomics method to predict PD. Fifty healthy controls (HC) along with 70 PD patients underwent resting-state magnetic resonance imaging (rs-fMRI). For all subjects, we extracted five types of 6664 features, including mean amplitude of low-frequency fluctuation (mALFF), mean regional homogeneity (mReHo), resting-state functional connectivity (RSFC), voxel-mirrored homotopic connectivity (VMHC) and grey matter (GM) volume. After conducting dimension reduction utilizing Least absolute shrinkage and selection operator (LASSO), fifty-three radiomic features including 46 RSFCs, 1 mALFF, 3 mReHos, 1 VMHC, 2 GM volumes and 1 clinical factor were retained. The selected features also indicated the most discriminative regions for PD. We further conducted model fitting procedure for classifying subjects in the training set employing random forest and support volume machine (SVM) to evaluate the performance of the two methods. After cross-validation, both methods achieved 100% accuracy and area under curve (AUC) for distinguishing between PD and HC in the training set. In the testing set, SVM performed better than random forest with the accuracy, true positive rate (TPR) and AUC being 85%, 1 and 0.97, respectively. These findings demonstrate the radiomics technique has the potential to support radiological diagnosis and to achieve high classification accuracy for clinical diagnostic systems for patients with PD.

Tigecycline is regarded as the last line of defense to combat multidrug-resistant Klebsiella pneumoniae . However, increasing utilization has led to rising drug resistance and treatment failure. Here, we design a D-alpha tocopheryl polyethylene glycol succinate-modified and S-thanatin peptide-functionalized nanorods based on calcium phosphate nanoparticles for tigecycline delivery and pneumonia therapy caused by tigecycline-resistant Klebsiella pneumoniae . After incubation with bacteria, the fabricated nanorods can enhance tigecycline accumulation in bacteria via the inhibitory effect on efflux pumps exerted by D-alpha tocopheryl polyethylene glycol succinate and the targeting capacity of S-thanatin to bacteria. The synergistic antibacterial capacity between S-thanatin and tigecycline further enhances the antibacterial activity of nanorods, thus overcoming the tigecycline resistance of Klebsiella pneumoniae . After intravenous injection, nanorods significantly reduces the counts of white blood cells and neutrophils, decreases bacterial colonies, and ameliorates neutrophil infiltration events, thereby largely increasing the survival rate of mice with pneumonia. These findings may provide a therapeutic strategy for infections caused by drug-resistant bacteria. Overproduction of efflux pumps represents an important mechanism of Klebsiella pneumonia resistance to tigecycline. Here, the authors design TPGS- and S-thanatin functionalized nanorods loaded with tigecycline to increase drug accumulation inside bacteria and overcome bacterial resistance.

Structured exercise programs delivered via telemedicine have the potential to benefit patients with chronic low back pain (CLBP). However, evidence-practice gaps exist, such as low exercise adherence and lack of attention to the mental health of CLBP, so further research is needed to investigate the impact of telemedicine-supported structured exercise program on patients with CLBP. To compare the clinical outcomes of patients with CLBP following a telemedicine intervention versus usual care therapy. An open label, randomized controlled trial (RCT) was conducted over eight weekly sessions. Participants with CLBP were randomly assigned to either the Experimental Group (EG) or the Control Group (CG) in a 1:1 ratio, using a randomized numeric table. The EG received an intervention consisting of patient education, health coaching, and structured exercise program delivered through mobile health (mHealth) apps. The CG received usual care therapy, including patient education and paper handouts describing home exercises. The outcome measures included disability, pain intensity, mental health status, quality of life, walking ability, and exercise adherence. These were evaluated using the Roland Morris Disability Questionnaire (RMDQ), the Numerical Rating Scale (NRS), Depression-Anxiety-Stress Scale (DASS21), 12-item Short Form Health Survey (SF-12), Time Up and Go (TUG), and Exercise Adherence Rating Scale (EARS), respectively. Linear mixed-effects model analysis was conducted at baseline, after 4 weeks (during treatment), and after 8 weeks (post-treatment), adhering to the principles of intention-to-treat (ITT) analysis. The study included a total of 78 participants, with 39 randomly assigned to each group. Changes were significantly different between groups at 8 weeks in disability (estimated value: -3.96, 95% CI: -5.45 to -2.47, P < 0.001), pain (estimated value: -1.69, 95% CI: -2.14 to -1.24, P < 0.001) and the physical health dimensions of quality of life (estimated value: 4.5, 95% CI: 1.29 to 7.71, P = 0.006). However, there were only within-group differences at 8 weeks in mental health status (estimated value: -3.81, 95% CI: -4.99 to -2.63, P < 0.001), mental health dimensions of quality of life (estimated value: 5.01, 95% CI: 2.9 to 7.13, P < 0.001), walking ability (estimated value: -0.92, 95% CI: -1.17 to -0.68, P < 0.001), and exercise adherence (Z: 1.91, P = 0.06) over time. This study suggests that a telemedicine-based structured exercise program is more effective than usual care therapy in improving disability, pain, and physical health dimensions of quality of life in patients with CLBP. Furthermore, the telemedicine program is equally effective as usual care therapy in enhancing mental health status, mental health dimensions of quality of life, walking ability, and exercise adherence. These findings indicate that implementing such a program could reduce the burden on patients with CLBP. This trial was registered at China Clinical Trial Registration Center with the identifier ChiCTR2300071560.

Background Zinc (Zn) and iron (Fe) are essential micronutrients for plant growth and development, their deficiency or excess severely impaired physiological and biochemical reactions of plants. Therefore, a tightly controlled zinc and iron uptake and homeostasis network has been evolved in plants. The Zinc-regulated transporters, Iron-regulated transporter-like Proteins (ZIP) are capable of uptaking and transporting divalent metal ion and are suggested to play critical roles in balancing metal uptake and homeostasis, though a detailed analysis of ZIP gene family in maize is still lacking. Results Nine ZIP-coding genes were identified in maize genome. It was revealed that the ZmZIP proteins share a conserved transmembrane domain and a variable region between TM-3 and TM-4. Transiently expression in onion epidermal cells revealed that all ZmZIP proteins were localized to the endoplasmic reticulum and plasma membrane. The yeast complementation analysis was performed to test the Zn or Fe transporter activity of ZmZIP proteins. Expression analysis showed that the ZmIRT1 transcripts were dramatically induced in response to Zn- and Fe-deficiency, though the expression profiles of other ZmZIP changed variously. The expression patterns of ZmZIP genes were observed in different stages of embryo and endosperm development. The accumulations of ZmIRT1 and ZmZIP6 were increased in the late developmental stages of embryo, while ZmZIP4 was up-regulated during the early development of embryo. In addition, the expression of ZmZIP5 was dramatically induced associated with middle stage development of embryo and endosperm. Conclusions These results suggest that ZmZIP genes encode functional Zn or Fe transporters that may be responsible for the uptake, translocation, detoxification and storage of divalent metal ion in plant cells. The various expression patterns of ZmZIP genes in embryo and endosperm indicates that they may be essential for ion translocation and storage during differential stages of embryo and endosperm development. The present study provides new insights into the evolutionary relationship and putative functional divergence of the ZmZIP gene family during the growth and development of maize.

The prognosis of patients with peripheral T‐cell lymphoma (PTCL) depends on bone marrow involvement (BMI). The bone marrow (BM) tumor microenvironment in PTCL remains unclear. We performed single‐cell RNA sequencing (scRNA‐seq) on 11 fresh BM samples from patients with BMI to reveal the associations of immune landscape and genetic variations with the prognosis of PTCL patients. Compared with PTCL not otherwise specified (NOS), angioimmunoblastic T‐cell lymphoma (AITL) had a higher number of T cells, lower number of lymphocytes, and greater inflammation. Immune heterogeneity in AITL is associated with prognosis. In particular, specific T‐cell receptor (TCR) T cells are enriched in patients with good response to anti‐CD30 therapy. We observed RhoA mutation‐associated neoantigens. Chidamide‐treated patients had a higher number of CD4+ regulatory cells and a better treatment response compared with other patients. In the nonresponder group, T‐cell enrichment progressed to secondary B‐cell enrichment and subsequently diffuse large B‐cell lymphoma. Moreover, AITL patients with lymphoma‐associated hemophagocytic syndrome had more T follicular helper (Tfh) cells with copy number variations in CHR5. To our knowledge, this study is the first to reveal the single‐cell landscape of BM microenvironment heterogeneity in PTCL patients with BMI. scRNA‐seq can be used to investigate the immune heterogeneity and genetic variations in AITL associated with prognosis. Based on single‐cell RNA sequencing (scRNA‐seq), we revealed the immune landscape and genetic variation at single‐cell resolution in peripheral T‐cell lymphoma (PTCL) with different prognoses. There were more effector T cells, inflammatory response, and exhausted lymphocyte cells enriched in angioimmunoblastic T‐cell lymphoma (AITL) compared with PTCL not otherwise specified (NOS). The immune heterogeneity in AITL was associated with prognosis.

Lack of digital skills among job applicants has been a significant factor that prevents them from taking advantage of many career opportunities in an increasingly digitalized economy. Knowing what digital skills are currently required by employers would be important for addressing the skill shortage. In this study, we apply the natural language processing techniques to analyze digital skill requirements in online job advertisements from three data sources. All three sources provide the full text of job advertisements in which employers describe the required skills or qualifications for the advertised positions. We observe consistent evidence on the demand for digital skills in all three samples in recent years: the percentage of jobs requiring digital skills typically ranges between 20% and 30%. A few digital skills are consistently in high demand through the study period. There are substantial overlaps but also clear differences in the digital skills that are required for accounting and finance professionals. We also find strong similarity and some differences in digital skill requirements between Singapore and Hong Kong. The findings from our study can provide valuable evidence to inform curriculum planning and career preparation for college education and professional training in accounting and finance disciplines in both economies. Digital technologies that appeared in the new millennium, such as artificial intelligence, blockchains, machine learning, robot advisors, robotic process applications, etc., are reshaping job scope and daily routines of accounting and finance professionals. Lack of digital skills among job applicants has been a significant factor that prevents them from taking advantage of many career opportunities in an increasingly digitalized economy. Knowing what digital skills are currently required by employers would be essential for addressing this skill shortage. In this study, we apply the natural language processing techniques to analyze digital skills that employers explicitly require in online job advertisements. We find that the percentage of jobs requiring digital skills ranges from 20% to 30% in recent years and a few digital skills are consistently in high demand through the study period. These findings can provide valuable evidence to inform curriculum planning and career preparation for college education and professional training.