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Abstract Internationalisation at home (IaH) has gained prominence in higher education, emphasising the cosmopolitan aspects of curricula, teaching, and learning. This case study, grounded in the concept of cosmopolitan learning as a sociological approach, focuses on three dimensions—cosmopolitan engagement, critical reflections on global and local issues, and ethical judgements—made by 23 Chinese university students participating in IaH at a prestigious Chinese university. It explores these students’ cosmopolitan learning experiences through IaH and their gains and learning challenges. The results show that the student participants exhibited more cosmopolitan engagement through the IaH curricula. Cosmopolitan engagement also enabled them to reflect critically on global and local issues, such as inequality in access to cosmopolitan learning resources, the impact of the global social imaginaries, and asymmetrical geo-power relations on the situatedness of knowledge, people, and learning. Accordingly, they made judgements to pursue ethical and meaningful changes. The challenges identified by students in cosmopolitan learning emphasise the need to further develop IaH cosmopolitan curricula to promote equity among diverse students in cosmopolitan learning, support multilingual learning, and empower students through a plural, egalitarian, and critical epistemology in addressing ethical change. Consequently, comprehensive proposals for the construction of cosmopolitan IaH curricula are presented.

In order to clarify the pre-exist immunity background of different human coronaviruses (HCoV), this study investigated the positive rate of spike (S) protein antibodies of HCoV, including HCoV- severe acute respiratory syndrome (SARS) −associated coronavirus (SARS-CoV-1), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Middle East respiratory syndrome coronavirus (MERS-CoV), HCoV-229E, HCoV-NL63, HCoV-HKU1 and HCoV-OC43, before and after the Coronavirus Disease 2019 (COVID-19) outbreak. We utilized pseudotyped virus-based neutralization assays (PBNA) or enzyme-linked immunosorbent assays (ELISA) to detect antibody levels against HCoV in serum samples collected in 2009–2010 and 2023. The PBNA results showed that neutralizing antibodies against SARS-CoV-1 and the MERS-CoV were negative. In the serum samples from 2009 to 2010, neutralizing antibodies against SARS-CoV-2 (D614G) were negative, whereas in the serum samples from 2023, 73 samples (73 %) showed neutralizing reactions with the SARS-CoV-2 D614G strain, 96 samples (96 %) with the BA.5 strain, and 91 samples (91 %) with the BF.7 strain. Among pre-COVID-19 samples, 33 % (33/100) showed neutralizing reactions with HCoV-229E and 63 % (63/100) with HCoV-NL63. Among post-COVID-19 samples, 50 % (50/100) showed neutralizing reactions with HCoV-229E and 49 % (49/100) with HCoV-NL63. Due to the different receptors of alpha coronavirus genus compared to other beta coronavirus genus, neutralizing antibodies against HCoV-OC43 and HCoV-HKU1 virus cannot be detected by constructing corresponding pseudotyped virus. Binding antibodies against HCoV-OC43 and HCoV-HKU1 virus were detected using ELISA. The results revealed that among pre-COVID-19 samples, 83 % (83/100) and 45 % (45/100) had binding activity with HCoV-OC43 and HCoV-HKU1, respectively. Among post-COVID-19 samples, 100 % (100/100) and 81 % (81/100) had binding activity with HCoV-OC43 and HCoV-HKU1, respectively.

Based on drilling and logging data, as well as geological experiments, the geological characteristics and factors controlling high-yield and enrichment of hydrocarbons in ultra-deep clastic rocks in the Linhe Depression, Hetao Basin, are studied. The results are obtained in four aspects. First, the inland saline lacustrine high-quality source rocks developed in the Paleogene in the Linhe Depression have the characteristics of early maturity, early expulsion, high hydrocarbon yield, and continuous and efficient hydrocarbon generation, providing an important resource basis for the formation of ultra-high pressure and high-yield reservoirs. Second, the weak compaction, early charging, and weak cementation for pore-preserving, together with the ultra-high pressure for pore-preserving and fracture expansion to improve the permeability, leads to the development of high-quality reservoirs with medium porosity (greater than 15%) and medium permeability (up to 226×10−3 μm2) in the ultra-deep strata (deeper than 6 500 m), which represents a greatly expanded space for oil and gas exploration. Third, the Linhe Formation adjacent to the trough exhibits a low net-to-gross (NTG) and good reservoir-caprock assemblage, and it is overlaid by very thick high-quality mudstone caprock, which are conducive to the continuous and efficient hydrocarbon generation and pressurization and the formation of ultra-high pressure oil and gas reservoirs. Fourth, the most favorable targets for ultra-deep exploration are the zones adjacent to the hydrocarbon generating center of the Paleogene Linhe Formation and with good tectonic setting and structural traps, mainly including the Xinglong faulted structural zone and the Nalinhu faulted buried-hill zone. The significant breakthrough of ultra-deep oil and gas exploration in the Linhe Depression reveals the good potential of ultra-deep clastic rocks in this area, and provides valuable reference for oil and gas exploration of ultra-deep clastic rocks in other areas.

Abstract Objectives To investigate the feasibility of a deep learning-constrained compressed sensing (DL-CS) method in non-contrast-enhanced modified DIXON (mDIXON) coronary magnetic resonance angiography (MRA) and compare its diagnostic accuracy using coronary CT angiography (CCTA) as a reference standard. Methods Ninety-nine participants were prospectively recruited for this study. Thirty healthy subjects (age range: 20–65 years; 50% female) underwent three non-contrast mDIXON-based coronary MRA sequences including DL-CS, CS, and conventional sequences. The three groups were compared based on the scan time, subjective image quality score, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The remaining 69 patients suspected of coronary artery disease (CAD) (age range: 39–83 years; 51% female) underwent the DL-CS coronary MRA and its diagnostic performance was compared with that of CCTA. Results The scan time for the DL-CS and CS sequences was notably shorter than that of the conventional sequence (9.6 ± 3.1 min vs 10.0 ± 3.4 min vs 13.0 ± 4.9 min; p

Abstract Prohibited item detection is crucial for the safety of public places. Deep learning, one of the mainstream methods in prohibited item detection tasks, has shown superior performance far beyond traditional prohibited item detection methods. However, most neural network architectures in deep learning still lack sufficient local feature representation ability for overlapping and small targets, and ignore the problem of semantic conflicts caused by direct feature fusion. In this paper, we propose MFPIDet, a novel prohibited item detection neural network architecture based on improved YOLOV7 to achieve reliable prohibited item detection in complex environments. Specifically, a multi-scale attention module (MAM) backbone is proposed to filter the redundant information of target regions and further applied to enhance the local feature representation ability of overlapping objects. Here, to reduce the redundant information of target regions, a squeeze-excitation (SE) block is used to filter the background. Then, aiming at enhancing the feature expression ability of overlapping objects, a multi-scale feature extraction module (MFEM) is designed for local feature representation. In addition, to obtain richer context information, We design an adaptive fusion feature pyramid network (AF-FPN) to combine the adaptive context information fusion module (ACIFM) with the feature fusion module (FFM) to improve the neck structure of YOLOV7. The proposed method is validated on the PIDray dataset, and the tested results showed that our method obtained the highest mAP (68.7%), which is improved by 3.5% than YOLOV7 methods. Our approach provides a new design pattern for prohibited item detection in complex environments and shows the development potential of deep learning in related fields.

Abstract Objective Existing evidence suggests telomerase activation is a crucial step in tumorigenesis. The telomerase reverse transcriptase (TERT), encoded by the human TERT gene, is critical for telomerase expression. The TERT rs10069690 (C > T) variant was identified to be associated with the risk of cancer, however, there have been inconsistent results. Therefore, we performed a comprehensive meta-analysis aiming to clarify the association between this variant and cancer susceptibility. Methods We conducted literature search in PubMed, EMbase, MEDLINE and Cochrane Library up to April 30, 2024. Overall, there are 55 studies involving 334,196 patients with cancer and 741,187 controls included in the present study. All statistical analyses were performed by STATA software (version 11.0). Results The pooled results showed a significant association between rs10069690 and an increased risk of cancer under allele model (OR = 1.10, 95% CI: 1.07–1.13, P

Abstract. Background:. Although some well-established oncogenes are involved in cancer initiation and progression such as prostate cancer (PCa), the long tail of cancer genes remains to be defined. Goosecoid (GSC) has been implicated in cancer development. However, the comprehensive biological role of GSC in pan-cancer, specifically in PCa, remains unexplored. The aim of this study was to investigate the role of GSC in PCa development. Methods:. We performed a systematic bioinformatics exploration of GSC using datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, Gene Expression Omnibus, German Cancer Research Center, and our in-house cohorts. First, we evaluated the expression of GSC and its association with patient prognosis, and identified GSC-relevant genetic alterations in cancers. Further, we focused on the clinical characterization and prognostic analysis of GSC in PCa. To understand the transcriptional regulation of GSC by E2F transcription factor 1 (E2F1), we performed chromatin immunoprecipitation quantitative polymerase chain reaction (qPCR). Functional experiments were conducted to validate the effect of GSC on the tumor cellular phenotype and sensitivity to trametinib. Results:. GSC expression was elevated in various tumors and significantly correlated with patient prognosis. The alterations of GSC contribute to the progression of various tumors especially in PCa. Patients with PCa and high GSC expression exhibited worse progression-free survival and biochemical recurrence outcomes. Further, GSC upregulation in patients with PCa was mostly accompanied with higher Gleason score, advanced tumor stage, lymph node metastasis, and elevated prostate-specific antigen (PSA) levels. Mechanistically, the transcription factor, E2F1, stimulates GSC by binding to its promoter region. Detailed experiments further demonstrated that GSC acted as an oncogene and influenced the response of PCa cells to trametinib treatment. Conclusions:. GSC was highly overexpressed and strongly correlated with patient prognosis in PCa. We found that GSC, regulated by E2F1, acted as an oncogene and impeded the therapeutic efficacy of trametinib in PCa.

ABSTRACT Background and Aims Observational studies suggest that antidiabetic drugs may lower POAG risk; while the causal relationship remains unclear. Naturally occurring variation in genes encoding antidiabetics drug targets can be used as proxies to investigate long‐term therapeutic effect of these drugs on POAG risk. Methods We performed a two‐sample Mendelian randomization study to evaluate the potential effect of antidiabetic drug targets on POAG in Europeans and East Asians. To proxy antidiabetic drugs (ABCC8, PPARG, GLP1R, SLC5A2), we leveraged genetic variants located near or within drug target genes that were associated with HbA1c. The validity of our ancestry‐specific genetic instrument was checked with multipul positive control outcomes. Genetic summary statistics of POAG from the International Glaucoma Genetics Consortium, Global Biobank Meta‐analysis Initiative, and FinnGen consortia were analyzed for Europeans (38,164 cases and 1,576,179 controls) and East Asians (16,650 cases and 288,833 controls) separately. Inverse‐variance weighted random‐effects models were used as primary method. Results MR results provided consistent evidence of a protective effect of ABCC8 inhibition on POAG using data sets from IGG, GBMI, and FinnGen. Genetically predicted one‐standard deviation reduction in HbA1c from ABCC8 inhibition were significant associated with lower risk of POAG in Europeans (OR = 0.211, 95% CI: 0.133–0.333; p

Abstract Near‐infrared (NIR) light powdered CO2 photoreduction reaction is generally restricted to the separation efficiency of photogenerated carriers and the supply of active hydrogen (*H). Herein, the study reports a retrofitting hydrogenated MoO3‐x (H‐MoO3‐x) nanosheet photocatalysts with Ru single atom substitution (Ru@H‐MoO3‐x) fabricated by one‐step solvothermal method. Experiments together with theoretical calculations demonstrate that the synergistic effect of Ru substitution and oxygen vacancy can not only inhibit the recombination of photogenerated carriers, but also facilitate the CO2 adsorption/activation as well as the supply of *H. Compared with H‐MoO3‐x, the Ru@H‐MoO3‐x exhibit more favorable formation of *CHO in the process of *CO conversion due to the fast *H generation on electron‐rich Ru sites and transfer to *CO intermediates, leading to the preferential photoreduction of CO2 to CH4 with high selectivity. The optimized Ru@H‐MoO3‐x exhibits a superior CO2 photoreduction activity with CH4 evolution rate of 111.6 and 39.0 µmol gcatalyst−1 under full spectrum and NIR light irradiation, respectively, which is 8.8 and 15.0 times much higher than that of H‐MoO3‐x. This work provides an in‐depth understanding at the atomic level on the design of NIR responsive photocatalyst for achieving the goal of carbon neutrality.

Diatoms (> 2 μm) have traditionally been identified as the primary biological agents linking the carbon (C) and silicon (Si) cycles. However, recent research has shown that picophytoplankton species (< 2 μm) also play a crucial role in the intertwined Si-C biogeochemical cycling in marine ecosystems. In this study, we examined the spatial distribution and vertical variation of micro/nano-diatoms and picophytoplankton in the eastern Indian Ocean (EIO), aimed to differentiate the contributions of living carbon and biogenic silica (bSi) stocks between diatoms and picophytoplankton. The study revealed that the abundance of picophytoplankton surpasses that of diatoms by four to seven orders of magnitude. Synechococcus was predominantly presented in the upper layer, while Prochlorococcus, picoeukaryotes, and diatoms were primarily located in the middle layer. Aggregation Boosted Tree (ABT) and Generalized Additive Models (GAM) analyses revealed that temperature and silicate (DSi) levels strongly influenced the diatom and picophytoplankton communities in the EIO. The fractions smaller than 2 μm made substantial contributions of 86.20%, 55.69%, and 96.86% to chlorophyll a (Chl-a), particulate organic carbon (POC), and living carbon biomass, respectively, underscoring the ecological significance of picophytoplankton in the carbon cycle of oligotrophic regions. Picophytoplankton represented a 33.06% of bSi stocks in the area, comparable to the contribution of diatoms (> 20 μm). Moreover, estimated contributions of diatom living carbon and silicon quota averaged 0.47% and 0.66%, respectively, while that of Synechococcus stood at 2.58% and 1.77%, indicating the predominance of Synechococcus as a weakly siliceous organism with high cell abundance in oligotrophic seas. Overall, this study draws on data from diatom and picophytoplankton biomass in the EIO to offer insights into the disproportionate carbon and silicon budgets in oligotrophic oceans from a biological perspective.

Coal fine intrusion into hydraulic propped fractures of coal seam easily leads to the blockage of the fracture, resulting in the decrease of the conductivity and the reduction of coal reservoir permeability, which seriously affects the stable discharge and production of coalbed methane well. In this paper, the permeability dynamic evolution models of coal fine intrusion into propped fractures were established before the shutdown and after the restart of coalbed methane well, and the experiments of coal fine intrusion into propped fracture under continuous and intermittent flow conditions were carried out by using the coal-rock conductivity test system, which verified the correctness of the models and studied the influence of coalbed methane well stoppage and drainage velocity on the permeability spatial and temporal evolution laws. The results indicate that with the increase of coal fine migration time, the permeability of propped fracture decreases slowly after a sudden drop, and along the direction of coal fine migration, the spatial pore loss rate of propped fracture decreases gradually, resulting in the permeability of fracture decreases along the direction of coal fine migration. With the continuous coal fine intrusion into propped fracture, the propped fracture pore loss rate after the shut-in and restart of coalbed methane wells is larger than that before the shutdown, and the permeability cannot be restored to the level before the shutdown. The slower the flow rate of drainage, the slower the permeability attenuation rate of coal fine intrusion into propped fracture, and the higher the permeability. During the coal fine invasion into proppant fracture at the low drainage flow rate, the fracture permeability is more sensitive to the flow rate change, and the less damage to the propped fracture permeability caused by the well shutdown. In the process of coal fine intrusion, the larger the deposition coefficient of coal fine is, the smaller the proximal fracture permeability and the larger the distal fracture permeability. The larger the diffusion coefficient is, the smaller the distal fracture permeability of the propped fracture is. The permeability of the proximal fracture is very little affected by the diffusion coefficient, and the damage to the proximal fracture permeability is more serious. In the process of coal fine intrusion, the proximal fracture permeability declines faster, while the distal fracture permeability declines slowly. The deposition coefficient changes have a significant influence on the proximal fracture permeability, while the diffusion coefficient changes have a more significant influence on the distal fracture permeability.

Abstract In diabetes, macrophages and inflammation are increased in the islets, along with β-cell dysfunction. Here, we demonstrate that galectin-3 (Gal3), mainly produced and secreted by macrophages, is elevated in islets from both high-fat diet (HFD)-fed and diabetic db/db mice. Gal3 acutely reduces glucose-stimulated insulin secretion (GSIS) in β-cell lines and primary islets in mice and humans. Importantly, Gal3 binds to calcium voltage-gated channel auxiliary subunit gamma 1 (CACNG1) and inhibits calcium influx via the cytomembrane and subsequent GSIS. β-Cell CACNG1 deficiency phenocopies Gal3 treatment. Inhibition of Gal3 through either genetic or pharmacologic loss of function improves GSIS and glucose homeostasis in both HFD-fed and db/db mice. All animal findings are applicable to male mice. Here we show a role of Gal3 in pancreatic β-cell dysfunction, and Gal3 could be a therapeutic target for the treatment of type 2 diabetes.

The coalbed methane resource under goaf is rich, but has not been effectively developed for a long time. Hydraulic fracturing technology stands as an effective means to augment coalbed methane recovery. The extraction and re-compaction of overlying coal seam will directly affect the expansion behavior of hydraulic fractures in the underlying coal seam. Though the large-scale (300 mm×300 mm×300 mm) true triaxial hydraulic fracturing experiments, the mechanical and acoustic emission response characteristics of coal were analyzed under different levels of loading and unloading stress perturbations. The damage variable T was proposed to characterize the degree of coal damage, and the relationship between damage and the initiation and expansion patterns of hydraulic fractures was elucidated. The results revealed that, the damage induced by vertical stress loading in the underlying coal significantly exceeded that in the unloading stage. When the vertical loading stress was below 11 MPa, the coal remained in an elastic stage with minimal damage. Loading between 11~15 MPa corresponded to the yielding stage, witnessing a substantial increase in damage. Loading between 15~18 MPa led to the strengthening stage, the pores and fractures of coal were gradually compacted. Damage variables T can effectively characterize the degree of internal damage of coal. When T=Tc, the internal damage of coal was comparable to that of a coal that has not disturbed by loading and unloading stress.Tc is the damage variable of coal without loading and unloading stress disturbance. When T＞Tc , the coal exhibited a stress-damaged state, with higher values of T corresponding to increasing damage levels. Conversely, when T＜Tc, the coal demonstrated a stress-compacted state, with smaller values of T indicating higher compaction degrees. The degree of stress damage in coal was negatively correlated with the fracture pressure, a high degree of damage made coal more prone to fracture, and it was favor to form the primary hydraulic fractures near the wellbore, which was conducive to hydraulic fracturing. The degree of compaction of coal was positively correlated with fracture pressure. The high degree of compaction weakened the effect of horizontal stress difference on hydraulic fracture expansion, and the hydraulic fracture near the wellbore was more developed, which hindered the formation of primary hydraulic fractures. Based on the research results, the principle of hydraulic fracturing construction scheme optimization for underlying coal seam in goaf was formulated and applied in the field. The hydraulic fracturing ability of the optimized scheme was significantly improved.

The bioretention system is one of the most widely used low impact development (LID) facilities with efficient purification capacity for stormwater, and its planting design has been a hot spot for research at home and abroad. In this paper, ryegrass (Lolium perenne L.), bermuda (Cynodon dactylon Linn.), bahiagrass (Paspalum notatum Flugge), and green grass (Cynodon dactylon × C .transadlensis ‘Tifdwarf’) were chosen as plant species to construct a shallow bioretention system. The growth traits and nutrient absorption ability of four gramineous plants were analyzed. Their tolerance, enrichment, and transportation capacity were also evaluated to compare plant species and their absorptive capacity of heavy metals (Cu, Pb, and Zn). Results showed that the maximum absorption rate (Imax) ranged from 22.1 to 42.4 μg/(g·h) for P and ranged from 65.4 to 104.8 μg/(g·h) for NH4+-N; ryegrass had the strongest absorption capacity for heavy metals and the maximum removal rates of Cu, Pb, and Zn by four grasses were 78.4, 59.4, and 51.3%, respectively; the bioretention cell with ryegrass (3#) was significantly more effective in purifying than the unplanted bioretention cell (1#) during the simulated rainfall test. Overall, the system parameters were optimized to improve the technical application of gramineous plants in the bioretention system. HIGHLIGHTS Four kinds of gramineous plants were selected as plant species to construct shallow bioretention systems.; Ryegrass showed the strongest absorptive capacity for phosphorus, ammonia nitrogen, and heavy metals.; The bioretention cell with ryegrass (3#) was significantly more effective in purifying than the unplanted bioretention cell (1#) during the simulated rainfall test.;

Abstract Gastric cancer (GC) is a common malignant tumor worldwide, especially in East Asia, with high incidence and mortality rate. Epigenetic modifications have been reported to participate in the progression of gastric cancer, among which m6A is the most abundant and important chemical modification in RNAs. Fat mass and obesity-associated protein (FTO) is the first identified RNA demethylase but little is known about its role in gastric cancer. In our study, data from TCGA and clinical samples showed that FTO was highly expressed in gastric cancer tissues. Kaplan–Meier plotter suggested that patients with the high level of FTO had a poor prognosis. In vitro and in vivo experiments confirmed the role of FTO in promoting gastric cancer cell proliferation. Mechanistically, we found that FTO bound to circFAM192A at the specific site and removed the m6A modification in circFAM192A, protecting it from degradation. CircFAM192A subsequently interacted with the leucine transporter solute carrier family 7 member 5 (SLC7A5) and enhancing its stability. As a result, an increased amount of SLC7A5 was on the membrane, which facilitated leucine uptake and activated the mTOR signaling pathway. Therefore, our study demonstrated that FTO promoted gastric cancer proliferation through the circFAM192A/SLC7A5 axis in the m6A-dependent manner. Our study shed new light on the role of FTO in gastric cancer progression.

Objective Hair follicle stem cells (HFSCs) differentiation is a critical physiological progress in skin hair follicle (HF) formation. Goat HFSCs differentiation is one of the essential processes of superior-quality brush hair (SQBH) synthesis. However, knowledge regarding the functions and roles of miR-133a-3p and miR-145-5p in differentiated goat HFSCs is limited. Methods To examine the significance of chi-miR-133a-3p and chi-miR-145-5p in differentiated HFSCs, overexpression and knockdown experiments of miR-133a-3p and miR-145-5p (Mimics and Inhibitors) separately or combined were performed. NANOG, SOX9, and stem cell differentiated markers (β-catenin, C-myc, Keratin 6 [KRT6]) expression levels were detected and analyzed by using real-time quantitative polymerase chain reaction, western blotting, and immunofluorescence assays in differentiated goat HFSCs. Results miR-133a-3p and miR-145-5p inhibit NANOG (a gene recognized in keeping and maintaining the totipotency of embryonic stem cells) expression and promote SOX9 (an important stem cell transcription factor) expression in differentiated stem cells. Functional studies showed that miR-133a-3p and miR-145-5p individually or together overexpression can facilitate goat HFSCs differentiation, whereas suppressing miR-133a-3p and miR-145-5p or both inhibiting can inhibit goat HFSCs differentiation. Conclusion These findings could more completely explain the modulatory function of miR-133a-3p and miR-145-5p in goat HFSCs growth, which also provide more understandings for further investigating goat hair follicle development.

Abstract Visible‐infrared person re‐identification (VI‐ReID) aims to recognize images of the same person captured in different modalities. Existing methods mainly focus on learning single‐granularity representations, which have limited discriminability and weak robustness. This paper proposes a novel dual‐granularity feature fusion network for VI‐ReID. Specifically, a dual‐branch module that extracts global and local features and then fuses them to enhance the representative ability is adopted. Furthermore, an identity‐aware modal discrepancy loss that promotes modality alignment by reducing the gap between features from visible and infrared modalities is proposed. Finally, considering the influence of non‐discriminative information in the modal‐shared features of RGB‐IR, a greyscale conversion is introduced to extract modality‐irrelevant discriminative features better. Extensive experiments on the SYSU‐MM01 and RegDB datasets demonstrate the effectiveness of the framework and superiority over state‐of‐the‐art methods.

Staphylococcus aureus (S. aureus) infection is a primary cause of otitis media (OM), the most common disease for which children are prescribed antibiotics. However, the abuse of antibiotics has led to a global increase in antimicrobial resistance (AMR). Nanozymes, as promising alternatives to traditional antibiotics, are being extensively utilized to combat AMR. Here, we synthesize a series of single-atom nanozymes (metal-C3N4 SANzymes) by loading four metals (Ag, Fe, Cu, Ru) with antibacterial properties onto a crystalline g-C3N4. These metal-C3N4 display a rob-like morphology and well-dispersed metal atoms. Among them, Ru-C3N4 demonstrates the optimal peroxidase-like activity (285.3 U mg–1), comparable to that of horseradish peroxidase (267.7 U mg–1). In vitro antibacterial assays reveal that Ru-C3N4 significantly inhibits S. aureus growth compared with other metal-C3N4 even at a low concentration (0.06 mg mL–1). Notably, Ru-C3N4 acts as a narrow-spectrum nanoantibiotic with relative specificity against Gram-positive bacteria. Biofilms formed by S. aureus are easily degraded by Ru-C3N4 due to its high peroxidase-like activity. In vivo, Ru-C3N4 effectively eliminates S. aureus and relieves ear inflammation in OM mouse models. However, untreated OM mice eventually develop hearing impairment. Due to its low metal load, Ru-C3N4 does not exhibit significant toxicity to blood, liver, or kidney. In conclusion, this study presents a novel SANzyme-based antibiotic that can effectively eliminate S. aureus and treat S. aureus-induced OM.

Summary: This study aims to establish a scientific foundation for early detection and diagnosis of silicosis by conducting meta-analysis on the role of single biomarkers in independent diagnosis. The combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic score, and diagnostic odds ratio (DOR) were 0.84 (95% confidence interval (CI): 0.77–0.90), 0.83 (95% CI: 0.78–0.88), 5.08 (95% CI: 3.92–6.59), 0.19 (95% CI: 0.13–0.27), 3.31 (95% CI: 2.88–3.74) and 27.29 (95% CI: 17.77–41.91), respectively. The area under the curve (AUC) was 0.90 (95% CI: 0.88–0.93). The Fagan plot shows a positive posterior probability of 82% and a negative posterior probability of 15%. This study establishes an academic basis for the swift identification, mitigation, and control of silicosis through scientific approaches. The assessed biomarkers offer precision and dependability in silicosis diagnosis, opening novel paths for early detection and intervention, thereby mitigating the disease burden associated with silicosis.

Abstract Extractive approaches have been the mainstream paradigm for identifying overlapping entity–relation extraction. However, limited by their inherently methodological flaws, which hardly deal with three issues: hierarchical dependent entity–relations, implicit entity–relations, and entity normalization. Recent advances have proposed an effective solution based on generative language models, which cast entity–relation extraction as a sequence-to-sequence text generation task. Inspired by the observation that humans learn by getting to the bottom of things, we propose a novel framework, namely GenRE, Generative multi-turn question answering with contrastive learning for entity–relation extraction. Specifically, a template-based question prompt generation first is designed to answer in different turns. We then formulate entity–relation extraction as a generative question answering task based on the general language model instead of span-based machine reading comprehension. Meanwhile, the contrastive learning strategy in fine-tuning is introduced to add negative samples to mitigate the exposure bias inherent in generative models. Our extensive experiments demonstrate that GenRE performs competitively on two public datasets and a custom dataset, highlighting its superiority in entity normalization and implicit entity–relation extraction. (The code is available at https://github.com/lovelyllwang/GenRE ).

Abstract The Coronavirus Disease 2019 (COVID‐19) epidemic has constituted a Public Health Emergency of International Concern. Chest computed tomography (CT) can help early reveal abnormalities indicative of lung disease. Thus, accurate and automatic localisation of lung lesions is particularly important to assist physicians in rapid diagnosis of COVID‐19 patients. The authors propose a classifier‐augmented generative adversarial network framework for weakly supervised COVID‐19 lung lesion localisation. It consists of an abnormality map generator, discriminator and classifier. The generator aims to produce the abnormality feature map M to locate lesion regions and then constructs images of the pseudo‐healthy subjects by adding M to the input patient images. Besides constraining the generated images of healthy subjects with real distribution by the discriminator, a pre‐trained classifier is introduced to enhance the generated images of healthy subjects to possess similar feature representations with real healthy people in terms of high‐level semantic features. Moreover, an attention gate is employed in the generator to reduce the noise effect in the irrelevant regions of M. Experimental results on the COVID‐19 CT dataset show that the method is effective in capturing more lesion areas and generating less noise in unrelated areas, and it has significant advantages in terms of quantitative and qualitative results over existing methods.

Extreme precipitation events greatly threaten people's daily lives and safety, making accurate and timely precipitation estimation especially critical. However, common methods like radar and satellite remote sensing have limitations due to coverage and environmental factors. Existing deep learning models struggle with complex scenarios and multisource data correlations. These make the precipitation estimation tasks challenging. This article proposes a Multiscale Dual Cross-Attention UNet (MS-DCA-UNet) model for near-real-time precipitation estimation. It integrates Doppler weather radar and FY-4A satellite data to overcome single-source data limitations. To narrow the semantic gap among the encoder feature maps, the MS-DCA-UNet model introduces a dual-cross attention (DCA) module at the skip connections of the backbone network U-Net. The DCA module mainly employs a channel cross-attention and a spatial cross-attention to capture remote dependencies and enable multiscale feature fusion. A multiscale convolution module is designed to reduce the risk of the model falling into local optima. It is a multibranch upsampling strategy that runs parallel to the decoder. Experimental results show that the Critical Success Index (CSI), Root Mean Square Error (RMSE), and Pearson's Correlation Coefficient (CC) of MS-DCA-UNet are 0.6033, 0.5949 mm/h, and 0.8460, respectively, with the hourly CMPAS precipitation as the benchmark. These outperform the other comparisons, such as FY-4A QPE, GPM IMERG, U-Net, Attention-UNet, and DCA-UNet on the CSI, RMSE, and CC metrics. MS-DCA-UNet reduces the RMSE of Attention-UNet, UNet, and DCA-UNet by a margin of 34.68% (0.5949 mm/h versus 0.9107 mm/h), 10.24% (0.5949 mm/h versus 0.6628 mm/h), 6.96% (0.5949 mm/h versus 0.6394 mm/h), respectively.

Near-surface air temperature is a crucial weather parameter that significantly impacts human health and is widely utilized in numerical weather forecasting and climate prediction studies. However, the most common ground-based meteorological station observation and radar observation are often limited by geographic and natural constraints. With the advantages of global coverage and high spatiotemporal resolution, satellite remote sensing has become a valuable support in overcoming data scarcity issues related to ground-based station and radar observations in complex geographic and natural conditions. Although remote sensing indirectly reflects atmosphere variables (e.g., near-surface air temperature), accurately estimating the atmosphere variables through satellite remote sensing remains a significant challenge. This article introduces a deep learning transformer-based neural network (TaNet) for near-surface air temperature estimation. TaNet automatically extracts information from imageries captured by China's new-generation geostationary meteorological satellite FengYun-4A and generates grid near-surface air temperature data in near real time. Extensive experiments conducted using the state-of-the-art operational reanalysis product ERA5 and meteorological station observations as benchmark standards demonstrate the effectiveness and superiority of TaNet. It achieves an impressive Pearson's correlation coefficient (CC) of 0.990 with ERA5 and 0.959 with station observations, outperforming the other products, such as CFSv2, CRA, and U-Net, on root mean square error (RMSE) and Pearson's CC metrics. TaNet reduces the RMSE of CFSv2, CRA, and U-Net by a margin of 10.551$\%$ (2.594 $^{\circ }$C versus 2.900 $^{\circ }$C), 2.261$\%$ (2.594 $^{\circ }$C versus 2.654 $^{\circ }$C), and 5.535$\%$ (2.594 $^{\circ }$C versus 2.746 $^{\circ }$C), respectively, using station observations as the benchmark.

Abstract Coacervation, or liquid-liquid phase separation (LLPS) of biomacromolecules, is increasingly recognized to play an important role both intracellularly and in the extracellular space. Central questions that remain to be addressed are the links between the material properties of coacervates (condensates) and both the primary and the secondary structures of their constitutive building blocks. Short LLPS-prone peptides, such as GY23 variants explored in this study, are ideal model systems to investigate these links because simple sequence modifications and the chemical environment strongly affect the viscoelastic properties of coacervates. Herein, a systematic investigation of the structure/property relationships of peptide coacervates was conducted using GY23 variants, combining biophysical characterization (plate rheology and surface force apparatus, SFA) with secondary structure investigations by infrared (IR) and circular dichroism (CD) spectroscopy. Mutating specific residues into either more hydrophobic or more hydrophilic residues strongly regulates the viscoelastic properties of GY23 coacervates. Furthermore, the ionic strength and kosmotropic characteristics (Hofmeister series) of the buffer in which LLPS is induced also significantly impact the properties of formed coacervates. Structural investigations by CD and IR indicate a direct correlation between variations in properties induced by endogenous (peptide sequence) or exogenous (ionic strength, kosmotropic characteristics, aging) factors and the β-sheet content within coacervates. These findings provide valuable insights to rationally design short peptide coacervates with programmable materials properties that are increasingly used in biomedical applications.

Abstract Traffic time series anomaly detection has been intensively studied for years because of its potential applications in intelligent transportation. However, classical traffic anomaly detection methods often overlook the evolving dynamic associations between road network nodes, which leads to challenges in capturing the long-term temporal correlations, spatial characteristics, and abnormal node behaviors in datasets with high periodicity and trends, such as morning peak travel periods. In this paper, we propose a mirror temporal graph autoencoder (MTGAE) framework to explore anomalies and capture unseen nodes and the spatiotemporal correlation between nodes in the traffic network. Specifically, we propose the mirror temporal convolutional module to enhance feature extraction capabilities and capture hidden node-to-node features in the traffic network. Morever, we propose the graph convolutional gate recurrent unit cell (GCGRU CELL) module. This module uses Gaussian kernel functions to map data into a high-dimensional space, and enables the identification of anomalous information and potential anomalies within the complex interdependencies of the traffic network, based on prior knowledge and input data. We compared our work with several other advanced deep-learning anomaly detection models. Experimental results on the NYC dataset illustrate that our model works best compared to other models for traffic anomaly detection.

The reverse electrodialysis heat engine (REDHE) represents a transformative innovation that converts low-grade thermal energy into salinity gradient energy (SGE). This crucial form of energy powers reverse electrodialysis (RED) reactors, significantly changing wastewater treatment paradigms. This comprehensive review explores the forefront of this emerging field, offering a critical synthesis of key discoveries and theoretical foundations. This review begins with a summary of various oxidation degradation methods, including cathodic and anodic degradation processes, that can be integrated with RED technology. The degradation principles and characteristics of different RED wastewater treatment systems are also discussed. Then, this review examines the impact of several key operational parameters, degradation circulation modes, and multi-stage series systems on wastewater degradation performance and energy conversion efficiency in RED reactors. The analysis highlights the economic feasibility of using SGE derived from low-grade heat to power RED technology for wastewater treatment, offering the dual benefits of waste heat recovery and effective wastewater processing.

To address the issue of missing near-surface air temperature data caused by the uneven distribution of ground meteorological observation stations, we propose a method for near-surface air temperature estimation based on an improved conditional generative adversarial network (CGAN) framework. Leveraging the all-weather coverage advantage of Fengyun meteorological satellites, Fengyun-4A (FY-4A) satellite remote sensing data are utilized as conditional guiding information for the CGAN, helping to direct and constrain the near-surface air temperature estimation process. In the proposed network model of the method based on the conditional generative adversarial network structure, the generator combining a self-attention mechanism and cascaded residual blocks is designed with U-Net as the backbone, which extracts implicit feature information and suppresses the irrelevant information in the Fengyun satellite data. Furthermore, a discriminator with multi-level and multi-scale spatial feature fusion is constructed to enhance the network’s perception of details and the global structure, enabling accurate air temperature estimation. The experimental results demonstrate that, compared with Attention U-Net, Pix2pix, and other deep learning models, the method presents significant improvements of 68.75% and 10.53%, respectively in the root mean square error (RMSE) and Pearson’s correlation coefficient (CC). These results indicate the superior performance of the proposed model for near-surface air temperature estimation.

ObjectiveIn this work, we propose a novel method for constructing whole-brain spatio-temporal multilayer functional connectivity networks (FCNs) and four innovative rich-club metrics.MethodsSpatio-temporal multilayer FCNs achieve a high-order representation of the spatio-temporal dynamic characteristics of brain networks by combining the sliding time window method with graph theory and hypergraph theory. The four proposed rich-club scales are based on the dynamic changes in rich-club node identity, providing a parameterized description of the topological dynamic characteristics of brain networks from both temporal and spatial perspectives. The proposed method was validated in three independent differential analysis experiments: male–female gender difference analysis, analysis of abnormality in patients with autism spectrum disorders (ASD), and individual difference analysis.ResultsThe proposed method yielded results consistent with previous relevant studies and revealed some innovative findings. For instance, the dynamic topological characteristics of specific white matter regions effectively reflected individual differences. The increased abnormality in internal functional connectivity within the basal ganglia may be a contributing factor to the occurrence of repetitive or restrictive behaviors in ASD patients.ConclusionThe proposed methodology provides an efficacious approach for constructing whole-brain spatio-temporal multilayer FCNs and conducting analysis of their dynamic topological structures. The dynamic topological characteristics of spatio-temporal multilayer FCNs may offer new insights into physiological variations and pathological abnormalities in neuroscience.

Background: Resistance to oxaliplatin (L-OHP) is a major barrier in the treatment of colorectal cancer (CRC). Autophagy is the main cause of L-OHP tolerance in CRC cells. Method: The human colon cancer cell lines HCT116 and SW480 were treated with L-OHP to obtain the drug-resistant cell lines HCT116/L-OHP and SW480/L-OHP, respectively. To probe the relationship between autophagy and L-OHP tolerance of growth factor independent 1 (Gfi-1) and high-mobility group protein 1 (HMGB1) in CRC cells, gene knockout or overexpression was performed, and Western blotting was used to determine the levels of drug tolerance interrelated proteins. Transwell and CCK-8 assays were employed to analyze the proliferation of cancer cells. Immunofluorescence detection of LC3 reflected autophagy levels. Finally, the relationship between Gfi-1 and HMGB1 was detected by chromatin immunoprecipitation (ChIP). Result: Compared to normal CRC cells, L-OHP-tolerant CRC cells exhibited greater autophagy (8.2 times greater in HCT116/L-OHP cells and 7.4 times greater in SW480/L-OHP cells). In addition, we detected low levels of Gfi-1 (0.6-fold for HCT116/L-OHP cells and 0.4-fold for SW480/L-OHP cells), and OE-Gfi-1 decreased HMGB1 levels (0.6-fold for HCT116/L-OHP + OE-Gfi-1 cells and 0.5-fold for SW480/L-OHP + OE-Gfi-1 cells). The inhibition of Gfi-1 further enhanced cell viability (1.7 times in HCT116+sh-Gfi-1 cells and 1.2 times in SW480+sh-Gfi-1 cells) and invasion (1.8 times in HCT116+sh-Gfi-1 cells and 2.1 times in SW480+sh-Gfi-1 cells) in CRC cells, thus promoting oxaliplatin resistance in these cells. The autophagy inhibitor 3-MA reversed the above effects. Furthermore, we noted that Gfi-1 can restrain HMGB1 expression by binding to its promoter (0.5 times in HCT116+OE-Gfi-1 cells and 0.5 times in SW480+OE-Gfi-1 cells). The inhibitory influence of 3-MA on HMGB1 reversed the influence of Gfi-1 on autophagy and malignant progression in CRC cells. Conclusion: Our study suggested that Gfi-1 inhibited HMGB1 to reduce CRC autophagy levels, increasing CRC sensitivity to L-OHP.

IntroductionPostoperative delirium (POD) remains one of the most prevalent neuropsychiatric complications after deep brain stimulation (DBS) surgery. The fibrinogen-to-albumin ratio (FAR) has been shown to significantly correlate with the prognosis of many diseases related to inflammation. However, the association between FAR and POD remains unclear. We aimed to explore the association between POD and FAR in patients with Parkinson’s disease (PD) undergoing DBS surgery.MethodsPatients with PD who underwent DBS surgery in our hospital were included in this retrospective study. FAR was calculated from the blood sample collected on admission. The association between baseline FAR and delirium after surgery was assessed by binary logistic regression analysis, interaction analysis, and stratified analyses.ResultsOf 226 patients, 37 (16.4%) suffered from delirium after surgery. The average age of the participants was 63.3 ± 7.2 years, and 51.3% were male patients. Multivariate logistic regression analysis indicated that patients in the highest FAR tertile had a higher risk of POD compared with patients in the lowest FAR tertile (OR = 3.93, 95% CI: 1.24 ~ 12.67). Subgroup analysis demonstrated that FAR and the preoperative Mini-Mental State Examination score (p = 0.013) had an association with delirium after surgery.ConclusionOur data suggest that a higher preoperative FAR was significantly associated with delirium after DBS surgery. FAR on admission is a useful candidate biomarker to identify patients with PD who are at a high risk of delirium following DBS surgery.

Abstract Regarding the extensive global attention to severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) that constitutes an international public health emergency, pseudovirus neutralization assays have been widely applied due to their advantages of being able to be conducted in biosafety level 2 laboratories and having a high safety factor. In this study, by adding a blue fluorescent protein (AmCyan) gene to the HIV system pSG3‐△env backbone plasmid HpaI and truncating the C‐terminal 21 amino acids of the SARS‐CoV‐2 spike protein (S), high‐titer SARS‐CoV‐2‐Sdel21‐AmCyan fluorescent pseudovirus was successfully packaged. The fluorescent pseudovirus was used to establish a neutralization assay in a 96‐well plate using 293T cells stably transfected with the AF cells. Then, parameters such as the ratio of backbone and membrane plasmid, sensitive cells, inoculation of cells and virus, as well as incubation and detection time were optimized. The pseudovirus neutralization assay demonstrated high accuracy, sensitivity, repeatability, and a strong correlation with the luminescent pseudovirus neutralization assay. Additionally, we scaled up the neutralizing antibody determination method by increasing the plate size from 96 wells to 384 wells. We have established a robust fluorescent pseudotyped virus neutralization assay for SARS‐CoV‐2 using the HIV system, providing a foundation for serum neutralization antibody detection, monoclonal antibody screening, and vaccine development.

The Eastern Indian Ocean (EIO) is an ideal region to explore the variability and controlling mechanisms of the seawater carbonate system and their potential influence on global climate change due to the distinctive environmental features, while studies in the EIO is far from sufficient. The spatiotemporal distributions of pH, dissolved inorganic carbon (DIC), alkalinity (Alk), and partial pressure of carbon dioxide (pCO2) were investigated in the EIO during autumn 2020 and spring 2021. The respective quantitative contributions of different controlling processes to DIC were further delineated. Significant seasonal variations were observed in the study area. Overall, the surface pH was lower and DIC, Alk, and pCO2 were higher during spring 2021 than during autumn 2020. The pH generally decreased from east to west during autumn 2020, whereas it decreased from north to south during spring 2021. The low values of DIC and Alk that were detected in the Bay of Bengal in these two seasons were mainly attributed to the influence of river inputs. Coastal upwelling during monsoon periods led to higher pCO2 and DIC values near Sumatra and Sri Lanka during spring 2021. The relationships of carbonate system parameters with different types of nutrients and different sized chlorophyll-a in the two seasons indicated the shifts of nutrients utilized by the phytoplankton, and phytoplankton species dominated the carbonate system variabilities. In vertical profiles, carbonate system parameters showed strong correlations with other physical and biogeochemical parameters, and these correlations were more robust during spring 2021 than during autumn 2020. The average sea–air flux of CO2 was 10.00 mmol m−2 d−1 during autumn 2020 and was 16.00 mmol m−2 d−1 during spring 2021, which revealed that the EIO served as a CO2 source during the study period. In addition, the separation of different controlling processes of DIC indicated stronger mixing processes, less CaCO3 precipitation, more intensive sea–air exchange, and weaker photosynthesis during spring 2021 than during autumn 2020.

The Loess Plateau region is seriously affected by soil erosion, water scarcity, and fragile ecosystems, which severely hinder social and economic development in the region. There is currently a lack of quantitative analysis and research on how human activities will affect the changes in water and sediment on the Loess Plateau and how to allocate the areas for reforestation and grassland restoration. This study focuses on the Beiluo River Basin in the Loess Plateau, analyzing the spatiotemporal variations of precipitation, runoff, water resources, sediment yield and normalized difference vegetation index (NDVI) over the past 20 years. The study establishes a distributed hydrological model for the basin, quantitatively evaluates the impact of returning farmland to forests and grassland on water resources and sediment transport, and explores the optimal land retirement plan under different decision-making conditions. The results show that the total water resources, runoff, groundwater resources and sediment yield in the basin are decreasing, and the annual reductions are 7×108 m3, 1×108 m3, 1.2×108 m3, and 1.6×104 tons respectively. While NDVI and precipitation is increasing, and the annual increases are 0.0064 and 65×108 m3 respectively. The continuous increase in NDVI has resulted in a reduction in runoff volume and sediment transport. Returning farmland to forests and grassland or increasing vegetation density can reduce the amount of runoff and sediment transport, with sediment transport being more sensitive. Considering both the impact on runoff and sediment transport, based on multi-objective optimization, an optimal allocation proposal for the area of returning farmland to forest and grass is proposed. The optimal land retirement area is 28.1%. This study provides decision-making support for ecological environment construction, soil and water conservation, and rational utilization of water and sediment resources in the Loess Plateau region.

Abstract Background R189W and K193del of protein C (PC) were hotspot mutations in Chinese population with venous thromboembolism (VTE), but almost two-thirds of patients with above mutations coexisting with other genetically or aquiredly prothrombotic risk factors. The aim of this study is to clarify the independent contributions of R189W or K193del to VTE risk. Methods 490 unrelated patients with a personal history of VTE and 410 healthy participants were enrolled in this study. Data of their demographics, family history, genetic and acquired thrombosis risk factors were collected and statistically analyzed. Results PC R189W and K193del were identified in 3/410 (0.7%) and 7/410 (1.7%) healthy controls, and in 27/490 (5.5%) and 43/490 (8.8%) patients with VTE, respectively. Notably, about 70% of these mutant carriers combined with other genetic or acquired thrombophilic factors. After adjustment for age, gender, other inherited and acquired risk factors, we demonstrated that R189W and K193del were associated with 5.781-fold and 4.365-fold increased risk of VTE, respectively, which were significantly lower than the prothrombotic risk of anticoagulant deficiencies induced from rare mutations. Independent R189W or K193del mutation was not associated with earlier first-onset age as well as higher recurrent rate of VTE. However, combination of other genetic or acquired thrombophilic factors had supra-additive effects on those consequences. The more additional risk factors the patients had, the younger first-onset ages and higher risk of recurrence would be. Conclusions As the most frequent mutations for PC deficiency in Chinese population, both R189W and K193del mutations had limited independent contributions to VTE development compared with other rare mutations in PROC gene, but may act in concert with other genetic defects or acquired thrombotic risk factors to produce the final severe phenotype.

Abstract Series compensation grids connected with type-3 wind turbine generator (WTG)-based wind farms have suffered numerous subsynchronous oscillation (SSO) events worldwide. For early alerting of SSO and effective development of protection and control strategies, it is critical to monitor and identify SSO accurately and quickly. Ambient data is continuously available, which is useful for online monitoring. This paper proposes an ambient data-driven SSO online monitoring method based on the Kalman filter (KF) combined with the multi-model partitioning filter (MMPF). The KF is utilized to fit the measured ambient data with an auto regressive (AR) model. Then, the damping factor (or damping ratio) and frequency in the SSO mode can be acquired by solving the roots of the characteristic polynomial corresponding to the AR model. Moreover, the MMPF is an effective model order selection method applied to the KF for better identification. The performance of the MMPF-KF method is demonstrated by simulations and real-time experiments. The results of case studies validate the effectiveness of the proposed method under various conditions.

The mountainous regions of southwest China are recognized as pivotal centers for the origin and evolution of Osmanthus species. Baoxing Osmanthus (Osmanthus serrulatus Rehder), a rare and endemic species known for its spring blooms, is sparsely distributed within the high altitude evergreen broad-leaved forests surrounding the southwestern Sichuan Basin. However, persistent anthropogenic disturbances and habitat fragmentation have precipitated a significant decline in its natural population size, leading to the erosion of genetic resources. To assess the genetic status of O. serrulatus and formulate effective conservation strategies, we conducted sampling across ten wild populations, totaling 148 individuals in their natural habitats. We employed two cpDNA fragments (matK and trnS-trnG) to elucidate the phylogeographic structure and historical population dynamics. The results revealed low species-level genetic diversity, alongside pronounced regional differentiation among populations (FST = 0.812, p < 0.05) and a notable phylogeographic structure (NST = 0.698 > GST = 0.396, p < 0.05). Notably, genetic variation was predominantly observed among populations (81.23%), with no evidence of recent demographic expansion across the O. serrulatus distribution range. Furthermore, divergence dating indicated a timeline of approximately 4.85 Mya, corresponding to the late Miocene to early Pleistocene. This temporal correlation coincided with localized uplift events in the southwestern mountains and heightened Asian monsoons, suggesting pivotal roles for these factors in shaping the current phylogeographic pattern of O. serrulatus. These findings support the effective conservation of O. serrulatus germplasm and offer insights into the impact of Quaternary climate oscillations on companion species within evergreen broad-leaved forests. They also enhance our understanding of the origin and evolution of these forests in the southwestern mountains, aiding biodiversity conservation efforts in the region.

Abstract Ionic liquids provide versatile pathways for controlling the structures and properties of quantum materials. Previous studies have reported electrostatic gating of nanometer-thick flakes leading to emergent superconductivity, insertion or extraction of protons and oxygen ions in perovskite oxide films enabling the control of different phases and material properties, and intercalation of large-sized organic cations into layered crystals giving access to tailored superconductivity. Here, we report an ionic-liquid gating method to form three-dimensional transition metal monochalcogenides (TMMCs) by driving the metals dissolved from layered transition metal dichalcogenides (TMDCs) into the van der Waals gap. We demonstrate the successful self-intercalation of PdTe2 and NiTe2, turning them into high-quality PdTe and NiTe single crystals, respectively. Moreover, the monochalcogenides exhibit distinctive properties from dichalcogenides. For instance, the self-intercalation of PdTe2 leads to the emergence of superconductivity in PdTe. Our work provides a synthesis pathway for TMMCs by means of ionic liquid gating driven self-intercalation.

Abstract Tumor initiation, progression, and response to therapies depend to a great extent on interactions between malignant cells and the tumor microenvironment (TME), which denotes the cancerous/non-cancerous cells, cytokines, chemokines, and various other factors around tumors. Cancer cells as well as stroma cells can not only obtain adaption to the TME but also sculpt their microenvironment through a series of signaling pathways. The post-translational modification (PTM) of eukaryotic cells by small ubiquitin-related modifier (SUMO) proteins is now recognized as a key flexible pathway. Proteins involved in tumorigenesis guiding several biological processes including chromatin organization, DNA repair, transcription, protein trafficking, and signal conduction rely on SUMOylation. The purpose of this review is to explore the role that SUMOylation plays in the TME formation and reprogramming, emphasize the importance of targeting SUMOylation to intervene in the TME and discuss the potential of SUMOylation inhibitors (SUMOi) in ameliorating tumor prognosis.

The unmanned undersea vehicle(UUV) cluster will become important in future underwater operations. The task allocation of the UUV cluster is a key problem in the application of the UUV cluster, and it can be regarded as a weapon–target assignment problem and a multiconstraint and multiobjective optimization problem. Therefore, considering factors such as the detection probability, ammunition load, ammunition cost, kill probability, target value of enemy ships, and interception probabilities of torpedoes around the UUV, two objective functions for the attack income and ammunition consumption cost are established, and a UUV cluster strike task allocation model is constructed. A multiobjective optimization algorithm, i.e., the non-dominated sorting genetic algorithm-III(NSGA-III), is introduced to solve the model. The coding strategy, constraint processing method, process, and key steps of NSGA-III are analyzed. Simulation results indicate that this algorithm outperforms NSGA-II and AGE-multi-objective evolutionary algorithms(AGE-MOEA) in terms of the running time and inverted generational distance and thus can support effective decision making.

Introduction Quitting smoking, the critical path to reach the global targets of reducing tobacco use, can bring major and immediate health benefits to smokers. Exploring factors that help individuals to quit smoking is of great importance. The present study explored influencing factors on smoking cessation, in order to provide comprehensive reference for tobacco control policies. Methods Ex-smokers and current smokers were recruited online in this crosssectional survey, from 1 October to 31 November 2022, in China. The observational data were collected using a questionnaire to collect information with respect to sociodemographic characteristics of smokers, attitudes towards smoking cessation, details of smoking cessation, and different potential factors related to smoking cessation through open-ended questions. Results A total of 638 smokers from 30 provinces were recruited as eligible respondents, with a mean age of 37.3 ± 11.7 years and a mean smoking history of 15.9 ± 13.7 years. The percentage of males was 92.3%. Of the 638 respondents, only 3.9% had no intention to stop smoking. Among 155 subjects who had quitted smoking successfully, willpower (55.5%) was considered as the most important contributing factor. Among 365 subjects who tried to quit but failed, lack of willpower (28.2%), tobacco dependence (16.2%), influence of surrounding smokers or smoking environments (15.9%), bad moods (9.9%), stress from work or life (7.9%), habits (7.1%), socialization (4.1%), and easy availability of tobacco (2.7%) were considered as the adverse factors leading to failure in quitting smoking. Conclusions Willpower and support from family members were the vital factors that lead to successful smoking cessation. Future tobacco control policies should also focus on addressing withdrawal symptoms and creating smoke-free environments as well as other factors.

Abstract Purpose To compare the degree of myopia between the dominant and non-dominant eyes in teenagers with intermittent exotropia (IXT) in China. Methods A total of 199 IXT patients with myopia were included in this retrospective study and were divided into two groups according to the difference between near and distance exodeviation: basic IXT and convergence insufficiency (CI) IXT. Refractive errors were analyzed by spherical equivalent (SE) values. Patients were further stratified into anisometropia group and non-anisometropia group based on binocular SE values difference greater than 1.0D or not. Results There were 127 patients in the CI IXT group, with a near deviation of 46.94 ± 20.53 prism diopters (PD) and a distance deviation of 28.36 ± 14.34 PD, and there were 72 (36.2%) patients in the basic IXT group, with a near deviation of 37.68 ± 22.21 PD and a distance deviation angle of 33.21 ± 23.96 PD. The near exodeviation was significantly larger in the CI group than in the basic IXT group(P

Abstract Forest musk deer (Moschus berezovskii) are currently a threatened species under conservation, and the development of captive populations is restricted by health problems. To evaluate the application potential of interferon (IFN)-ω in the prevention and control of forest musk deer disease, 5 forest musk deer IFN-ω (fmdIFNω) gene sequences were successfully obtained by homologous cloning method for the first time. FmdIFNω5 was selected and recombinant fmdIFNω protein (rIFNω) was successfully expressed by pGEX-6P-1 plasmid and E. coli expression system. The obtained protein was used to stimulate forest musk deer lung fibroblasts cells FMD-C1 to determine its regulatory effect on interferon-stimulated genes (ISGs). In addition, an indirect ELISA method based on anti-rIFNω serum was established to detect endogenous IFN-ω levels in 8 forest musk deer. The results showed that there were 18 amino acid differences among the 5 fmdIFNω subtypes, all of which had the basic structure to exert the activity of type I IFN and were close to Cervus elaphus IFN-ω in the phylogenetic tree. The protein expressed was 48 kDa, and the transcription levels of all ISGs were increased in FMD-C1 cells stimulated by rIFNω, and the amount of transcription accumulation was time-dependent. Meanwhile, Anti-rIFNω serum of mice could react with both rIFNω and forest musk deer serum, and the OD450nm value of forest musk deer serum with the most obvious symptoms was the highest, suggesting that the level of natural IFN-ω in different forest musk deer could be monitored by the rIFNω-based ELISA method. These results indicate that fmdIFNω has the potential as an antiviral drug and an early indication of innate immunity, which is of great significance for the prevention and control of forest musk deer diseases.

In the context of multi-vehicle formation, obstacle avoidance in unknown environments presents a number of challenges, including obstacles near the target, susceptibility to local minima, and dynamic obstacle avoidance. To address these issues in multi-vehicle formation control and obstacle avoidance within unknown environments, this paper uses PID control to optimize the potential field function of the artificial potential field method and conducts simulation experiments. The results demonstrate that the proposed algorithm achieves reductions of 39.7%, 41.9%, 24.8% and 32.0% in four efficiency functions (total iteration times, formation efficiency function value, energy consumption and standard deviation of iteration times) compared to other algorithms. The improved algorithm more effectively addresses the challenge of slow obstacle avoidance when vehicles approach the target and can handle unexpected situations such as local minima and dynamic obstacles. It achieves energy-efficient optimization for multi-vehicle obstacle avoidance in complex environments.

The global outbreak of COVID-19 has caused a severe threat to human health; therefore, simple, high-throughput neutralization assays are desirable for developing vaccines and drugs against COVID-19. In this study, a high-titre SARS-CoV-2 pseudovirus was successfully packaged by truncating the C-terminus of the SARS-CoV-2 spike protein by 21 amino acids and infecting 293 T cells that had been stably transfected with the angiotensin-converting enzyme 2 (ACE2) receptor and furin (named AF cells), to establish a simple, high-throughput, and automated 384-well plate neutralization assay. The method was optimized for cell amount, virus inoculation, incubation time, and detection time. The automated assay showed good sensitivity, accuracy, reproducibility, Z’ factor, and a good correlation with the live virus neutralization assay. The high-throughput approach would make it available for the SARS-CoV-2 neutralization test in large-scale clinical trials and seroepidemiological surveys which would aid the accelerated vaccine development and evaluation.

Little is known about whether preventative practices for post-contrast acute kidney injury (PC-AKI) recommended in guidelines have been adopted in clinical practice and translated into a lower incidence of PC-AKI. The aim of this study was to examine the yearly trends in the incidence of PC-AKI, and comorbidities and care practices associated with PC-AKI in hospitalized patients who received intravenous administration of iodinated contrast medium (ICM). Adult patients receiving intravenous ICM at the Second Xiangya Hospital of Central South University in China between 2015 and 2021 were included. Temporal trends in the incidence and risk factors for PC-AKI were evaluated using logistic regression analyses with adjustments for relevant variables. The incidence of PC-AKI has declined significantly from 5.3% in 2015 to 4.1% in 2021 (p 1000 mL on the day of ICM administration or using iso-osmolar ICM increased. In conclusion, a declining trend in PC-AKI incidence was observed in patients receiving intravenous ICM between 2015 and 2021, which may be related to increased awareness and efforts to prevent PC-AKI.

Background Brachial-ankle pulse wave velocity (baPWV) is an important clinical indicator of aortic stiffness and a risk predictor of cardiovascular disease and associated with obesity. However, whether body mass index (BMI) is associated with baPWV remains controversial. In our study, body fat-related indicators, including BMI, body fat rate (BFR), body fat volume (BFV), waist circumference (WC) were examined from healthy volunteers. We investigated the correlation of baPWV with these indicators and also assessed whether baPWV has the potential to predict these indicators. Methods A total of 429 healthy participants were enrolled in this study. Body fat indices, blood pressures, baPWV and blood metabolic indices were measured and recorded. The association of baPWV and indices reflecting body fat and blood pressure, as well as mediation effect were analyzed. Results Three different types of baPWV values were significantly correlated. Mean level of baPWV was an independent risk factor for WC, BMI, BFR, and BFV (exp(β) = 1.011, 1.004, 1.010 and 1.009, respectively, P

AbstractContrast-induced acute kidney injury (CI-AKI), which occurs after the use of iodinated contrast media, has become the third leading cause of hospital-acquired acute kidney injury (AKI). It is associated with prolonged hospitalization and increased risks of end-stage renal disease and mortality. The pathogenesis of CI-AKI is unclear and effective treatments are lacking. By comparing different post-nephrectomy times and dehydration times, we constructed a new, short-course CI-AKI model using dehydration for 24 h two weeks after unilateral nephrectomy. We found that the low-osmolality contrast media iohexol caused more severe renal function decline, renal morphological damage, and mitochondrial ultrastructural alterations compared to the iso-osmolality contrast media iodixanol. The shotgun proteomics based on Tandem Mass Tag (TMT) was used to conduct proteomics research on renal tissue in the new CI-AKI model, and 604 distinct proteins were identified, mainly involving complement and coagulation cascade, COVID-19, PPAR signalling pathway, mineral absorption, cholesterol metabolism, ferroptosis, staphylococcus aureus infection, systemic lupus erythematosus, folate biosynthesis, and proximal tubule bicarbonate reclamation. Then, using parallel reaction monitoring (PRM), we validate 16 candidate proteins, of which five were novel candidates (Serpina1, Apoa1, F2, Plg, Hrg) previously unrelated to AKI and associated with an acute response as well as fibrinolysis. The pathway analysis and 16 candidate proteins may help to discover new mechanisms in the pathogenesis of CI-AKI, allowing for early diagnosis and outcome prediction.

AbstractContrast-induced acute kidney injury (CI-AKI) is a severe complication associated with significant morbidity and mortality, and effective therapeutic strategies are still lacking. Apelin is an endogenous physiological regulator with antioxidative, anti-inflammatory and antiapoptotic properties. However, the role of apelin-13 in CI-AKI remains unclear. In our study, we found that the protein expression levels of apelin were significantly downregulated in rat kidney tissues and HK-2 cells during contrast media treatment. Moreover, we explored the protective effect of apelin-13 on renal tubule damage using in vitro and in vivo models of CI-AKI. Exogenous apelin-13 ameliorated endoplasmic reticulum stress, reactive oxygen species and apoptosis protein expression in contrast media-treated cells and rat kidney tissues. Mechanistically, the downregulation of endoplasmic reticulum stress contributed critically to the antiapoptotic effect of apelin-13. Collectively, our findings reveal the inherent mechanisms by which apelin-13 regulates CI-AKI and provide a prospective target for the prevention of CI-AKI.

Bidens pilosa L. 1753 is a perennial herbaceous flowering plant, traditionally used in foods and medicines. In this study, we sequenced, assembled, and characterized the complete plastome of B. pilosa from Beijing, China. The plastome (MN385242) is circularized with a conservative quadripartite structure. Its length is 150,524 bp, including a large single-copy region (83,535 bp), a small single-copy region (17,627 bp), and a pair of inverted repeat regions (each 24,681 bp). The plastome consists of 128 genes, including 78 unique protein-coding, 28 unique tRNA, and 4 unique rRNA genes. Phylogenetic analyses showed all five B. pilosa plants couldn’t form a monophyletic clade and were separated into three clades. The results of K2P distance and molecular markers were all consistent with those of phylogenetic analysis, revealing high genetic diversity and even possible misidentifications of the B. pilosa. Our results highlighted the importance of correct species identification of materials in medicinal products.