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Objective: Accurate preoperative prediction of sinonasal inverted papilloma (SNIP) malignant transformation is essential and challenging. In this study, 3.0T magnetic resonance was used for qualitative, quantitative, and multi-parametric analysis to evaluate the predictive value of magnetic resonance imaging (MRI) in malignant transformation. Methods: The data of patients with SNIP (n=83) or SNIP-transformed squamous cell carcinoma (SNIP-SCC) (n=21) were analysed retrospectively. Univariate analysis and multivariate logistic regression were used to establish models to predict the risk factors for the malignant transformation of SNIP. Receiver operating characteristic (ROC) curves were used to evaluate the ability of independent risk factors and related combination models to predict malignant transformation of SNIP. Result: Convoluted cerebriform pattern (CCP) mutation, apparent diffusion coefficient ratio (ADCr), and wash-in index (WII) 2 and 3 were independent risk factors for predicting malignant transformation of SNIP, with area under the ROC curve (AUC) values of 0.845, 0.862, 0.727, and 0.704, respectively. The AUC of the quantitative parameter model combined with ADCr and WII 2 and 3 was 0.910 for diagnosing malignant transformation. The AUC of the comprehensive model comprising all independent risk factors was 0.937, with a sensitivity, specificity, and accuracy of 90.48%, 90.36%, and 92.31%, respectively. Conclusion: Compared with assessing independent risk factors of CCP mutation, ADCr and WII, and the quantitative parameter model, the comprehensive model could improve the differential diagnosis ability of SNIP and SNIP-SCC, which provides an important imaging basis for the possible accurate preoperative evaluation of malignant transformation of SNIP.

The entire Arctic is rapidly warming, which brings in a multitude of environmental consequences far beyond the northern high-latitude limits. Land cover maps offer biophysical insights into the terrestrial environment and are therefore essential for understanding the transforming Arctic in the context of anthropogenic activity and climate change. Satellite remote sensing has revolutionized our ability to capture land cover information over large areas. However, circumpolar Arctic-scale fine-resolution land cover mapping has so far been lacking. Here, we utilize a combination of multimode satellite observations and topographic data at 10 m resolution to provide a new baseline land cover product (CALC-2020) across the entire terrestrial Arctic for circa 2020. Accuracy assessments suggest that the CALC-2020 product exhibits satisfactory performances, with overall accuracies of 79.3 % and 67.3 %, respectively, at validation sample locations and field/flux tower sites. The derived land cover map displays reasonable agreement with pre-existing products, meanwhile depicting more subtle polar biome patterns. Based on the CALC-2020 dataset, we show that nearly half of the Arctic landmass is covered by graminoid tundra or lichen/moss. Spatially, the land cover composition exhibits regional dominance, reflecting the complex suite of both biotic and abiotic processes that jointly determine the Arctic landscape. The CALC-2020 product we developed can be used to improve Earth system modelling and benefit the ongoing efforts on sustainable Arctic land management by public and non-governmental sectors. The CALC-2020 land cover product is freely available on Science Data Bank: https://doi.org/10.57760/sciencedb.01869 (Xu et al., 2022a).

The electro-hydraulic servo system is widely used in industrial automation fields for its merits of the high force to weight ratio, compact size, and fast response. However, the parameter uncertainties and external disturbances of the electro-hydraulic servo system significantly deteriorate the control performance of conventional linear controller in practice. To deal with this problem, sliding mode controller (SMC) that incorporates high gain observer (HGO) is proposed in this paper. HGO is used to obtain the accurate time derivative of position signal for sliding mode controller design. The stability of the control system is guaranteed by Lyapunov stability theory. Comparation simulation is conducted to validate the effectiveness of the presented control scheme.

Exogenous chemotaxis under the concentration gradient of growth factors (CGGF) is demonstrated as a mechanism of hematogenous metastasis. A bionic microfluidic device inspired by the leaky tumor vessels is proposed to study the mechanism.

The strongest formation of oxygenated organic molecules occurs when PM2.5 and O3 are co-enhanced.

Inspired by siderophores, a new two-dimensional MOF with homoleptic Fe-tri(hydroxamate) nodes is reported, featuring chemical stability and electrochemical H2O2-sensing potentials.

Visual retrieval tasks such as image retrieval and person re-identification (Re-ID) aim at effectively and thoroughly searching images with similar content or the same identity. After obtaining retrieved examples, re-ranking is a widely adopted post-processing step to reorder and improve the initial retrieval results by making use of the contextual information from semantically neighboring samples. Prevailing re-ranking approaches update distance metrics and mostly rely on inefficient crosscheck set comparison operations while computing expanded neighbors based distances. In this work, we present an efficient re-ranking method which refines initial retrieval results by updating features. Specifically, we reformulate re-ranking based on Graph Convolution Networks (GCN) and propose a novel Graph Convolution based Re-ranking (GCR) for visual retrieval tasks via feature propagation. To accelerate computation for large-scale retrieval, a decentralized and synchronous feature propagation algorithm which supports parallel or distributed computing is introduced. In particular, the plain GCR is extended for cross-camera retrieval and an improved feature propagation formulation is presented to leverage affinity relationships across different cameras. It is also extended for video-based retrieval, and Graph Convolution based Re-ranking for Video (GCRV) is proposed by mathematically deriving a novel profile vector generation method for the tracklet. Without bells and whistles, the proposed approaches achieve state-of-the-art performances on seven benchmark datasets from three different tasks, i.e., image retrieval, person Re-ID and video-based person Re-ID., Code is publicly available: https://github.com/WesleyZhang1991/GCN_rerank

[Cu75(S-Adm)32]2+ was constructed by 12 distorted octahedra and face centered cubic Cu15 core, and contains the shortest Cu–Cu bond length (2.166(7) Å), indicating the strong cuprophilic interactions in the Cu75 nanocluster.

Compartmentalization of catalysts has potential to become a powerful synthetic tool, however, further work in understanding its fundamental principles is required. Herein, those principles are elucidated through the lens of biomimicry.

We show that every ℝd-valued Sobolev path with regularity a and integrability p can be lifted to a Sobolev rough path provided 1/2 > α > 1/p> ⋁ 1/3. The novelty of our approach is its use of ideas underlying Hairer’s reconstruction theorem generalized to a framework allowing for Sobolev models and Sobolev modelled distributions. Moreover, we show that the corresponding lifting map is locally Lipschitz continuous with respect to the inhomogeneous Sobolev metric.

Conventional drug delivery systems have been applied to a myriad of active ingredients but may be difficult to tailor for a given drug. Herein, we put forth a new strategy, which designs and selects the drug delivery material by considering the properties of encapsulated drugs (even multiple drugs, simultaneously). Specifically, through an in-silico screening process of 5109 MOFs using grand canonical Monte Carlo simulations, a customized MOF (referred as BIO-MOF-100) was selected and experimentally verified to be biologically stable, and capable of loading 3 anti-Tuberculosis drugs Rifampicin+Isoniazid+Pyrazinamide at 10% + 28% + 23% wt/wt (total 50% by weight). Notably, the customized BIO-MOF-100 delivery system cleared naturally Pyrazinamide-resistant Bacillus Calmette-Guérin, reduced growth of virulent Erdman infection in macaque macrophages 10-100-fold compared to soluble drugs in vitro and was also significantly reduced Erdman growth in mice. These data suggest that the methodology of identifying-synthesizing materials can be used to generate solutions for challenging applications such as simultaneous delivery of multiple, small hydrophilic and hydrophobic molecules in the same molecular framework.

The water-selective channel protein aquaporin-4 (AQP4) contributes to the migration and proliferation of gliomas, and to their resistance to therapy. Here we show, in glioma cell cultures, in subcutaneous and orthotopic gliomas in rats, and in glioma tumours in patients, that transmembrane water-efflux rate is a sensitive biomarker of AQP4 expression and can be measured via conventional dynamic-contrast-enhanced magnetic resonance imaging. Water-efflux rates correlated with stages of glioma proliferation as well as with changes in the heterogeneity of intra-tumoural and inter-tumoural AQP4 in rodent and human gliomas following treatment with temozolomide and with the AQP4 inhibitor TGN020. Regions with low water-efflux rates contained higher fractions of stem-like slow-cycling cells and therapy-resistant cells, suggesting that maps of water-efflux rates could be used to identify gliomas that are resistant to therapies.

Integrating light-harvesting materials with microbial biochemistry is a viable approach to produce chemicals with high efficiency from the air, water, and sunlight. Yet it remains unclear whether all absorbed photons in the materials can be transferred through the material-biology interface for solar-to-chemical production and whether the presence of materials beneficially affect the microbial metabolism. Here we report a microbe-semiconductor hybrid by interfacing CO(2)/N(2)-fixing bacterium Xanthobacter autotrophicus with CdTe quantum dots for light-driven CO(2) and N(2) fixation with internal quantum efficiencies of 47.2 ± 7.3% and 7.1 ± 1.1%, respectively, reaching the biochemical limits of 46.1% and 6.9% imposed by the stoichiometry in biochemical pathways. Photophysical studies suggest fast charge-transfer kinetics at the microbe-semiconductor interfaces, while proteomics and metabolomics indicate a material-induced regulation of microbial metabolism favoring higher quantum efficiencies compared to the biological counterparts alone.

Membrane bioreactor (MBR) is an attractive option method for treating azo dye wastewater under extreme conditions. The present study assessed the effect of salinity on the performance of anaerobic MBR in treating azo dye wastewater. Increased salinity showed adverse effects on the decolorization efficiency and chemical oxygen demand (COD) removal efficiency. The decolorization efficiency decreased from 95.8% to 82.3% and 73.1% with a stepwise increasing of salinity from 0 to 3% and 5%, respectively. The COD removal efficiency decreased from 80.7% to 71.3% when the salinity increased from 0 to 3% and then decreased to 58.6% at 5% salinity. The volatile fatty acids (VFAs) concentration also increased as the salinity increased. Furthermore, increased salinity led to the elevated production of soluble microbial products (SMP) and extracellular polymeric substances (EPS), which can provide a protective barrier against harsh environments. More serious membrane fouling was observed as the SMP and EPS concentrations increased. The concentration of loosely bound EPS (LB-EPS), tightly bound EPS (TB-EPS), and the polysaccharide/protein (PS/PN) ratios in LB-EPS and TB-EPS all increased when the salinity was elevated. The production of SMP and EPS was caused by the generation of PS in response to the saline environment. Lactobacillus, Lactococcus, Anaerosporobacter, and Pectinatus were the dominant bacteria, and Lactobacillus and Lactococcus were the decolorization bacteria in the MBR. The lack of halophilic bacteria was the main reason for the decreased decolorization efficiency in the salinity environment.

Stimulator of interferon genes (STING) functions downstream of cyclic GMP-AMP synthase in DNA sensing or as a direct receptor for bacterial cyclic dinucleotides and small molecules to activate immunity during infection, cancer and immunotherapy1–10. Precise regulation of STING is essential to ensure balanced immune responses and prevent detrimental autoinflammation11–16. After activation, STING, a transmembrane protein, traffics from the endoplasmic reticulum to the Golgi, where its phosphorylation by the protein kinase TBK1 enables signal transduction17–20. The mechanism that ends STING signalling at the Golgi remains unknown. Here we show that adaptor protein complex 1 (AP-1) controls the termination of STING-dependent immune activation. We find that AP-1 sorts phosphorylated STING into clathrin-coated transport vesicles for delivery to the endolysosomal system, where STING is degraded21. We identify a highly conserved dileucine motif in the cytosolic C-terminal tail (CTT) of STING that, together with TBK1-dependent CTT phosphorylation, dictates the AP-1 engagement of STING. A cryo-electron microscopy structure of AP-1 in complex with phosphorylated STING explains the enhanced recognition of TBK1-activated STING. We show that suppression of AP-1 exacerbates STING-induced immune responses. Our results reveal a structural mechanism of negative regulation of STING and establish that the initiation of signalling is inextricably associated with its termination to enable transient activation of immunity.

Microfluidic devices have developed a wide range of applications in the fields of biomedicine, chemistry, and analytical science. But it is easy to form and accumulate bubbles in microfluidic devices. These bubbles could decrease the detection sensitivity, cause inaccurate analysis results, and even damage the functional region of the device. Inspired by the embolism repair mechanism of angiosperms and the permeability of gas permeable materials, this work proposes a bioinspired permeation-enhanced degassing method. Bionic redundant pits are used in this method to keep bubbles from spreading between microchannels and maintain the continuity of the flow. A hydrophobic gas permeable material is used to enhance the bubble capture capability and accelerate the degassing process. This method can eliminate bubbles automatically and continuously in real time without auxiliary equipment. Compared to the bubble removal only depending on solution in water, the degassing effect of the permeation-enhanced degassing method shows about 1.6 times improvement in the same conditions, and the capability of trapping bubbles is improved by 1.33 times. In this paper, this method was integrated into a concentration gradient generator and a cell culture device. The results show that the concentration gradient generator with degassing structures can dissolve bubbles in a rapid way and reach the stability of the concentration gradient within 5-15 min. The degassing method can run for a long time and improve the cell density and cell viability of HeLa cells up to 2.64 and 1.12 times, respectively. The method has a broad application prospect in microfluidic fields including biomedical fluid processing, virus detection, and microscale reactor operation.

Zbtb34 is a novel zinc finger protein, which is revealed by biological software analysis to have 3 zinc fingers, but its functions remain unknown. In this study, mouseiZbtb34/icDNA was amplified by PCR and inserted into the plasmid pEGFP-N1 to generate Zbtb34-EGFP fusion protein. The upregulation of Zbtb34 in mouse embryonic stem cells promoted telomere elongation and increased cell proliferation. In order to understand the above phenomena, the telomere co-immunoprecipitation technique was employed to investigate the relationship between Zbtb34 and telomeres. The results indicated that Zbtb34 could bind to the DNA sequences of the telomeres. Alanine substitution of the third zinc finger abolished such binding. Since Pot1 is the only protein binding to the single-stranded DNA at the end of the telomeres, we further investigated the relationship between Zbtb34 and Pot1. The results revealed that the upregulation of Zbtb34 decreased the binding of Pot1b to the telomeres. Through the upregulation of Pot1b, the binding of Zbtb34 to the telomeres was also reduced. In conclusion, we showed that the main biological function of Zbtb34 was to bind telomere DNA via its third ZnF, competing with Pot1b for the binding sites, resulting in telomere elongation and cell proliferation.

To investigate the correlation between circulating microRNAs and liver injury indexes in drug-induced liver injury (DILI). We collected data on 72 DILI patients and 150 healthy subjects undergoing physical examination at our hospital from January 2021 to February 2022. From the diagnostic results, they were divided into a DILI group and a control group. Nano-magnetic beads were used to extract nucleic acid from serum, then qPCR was used to determine circulating microRNA levels, and the results were analyzed. Meanwhile, the serum liver function index levels before and after treatment were determined, and the correlations between circulating microRNA and these indexes were analyzed. We analyzed microRNA expression and found that miR-122-3p, miR-92a-3p, and miR-192-5p expression was consistent with a database, all of which were highly expressed in DILI. Moreover, after a period of treatment, their levels in circulation significantly decreased. ALT, ALP, GGT, AST, and TBIL also all decreased to different degrees after treatment. Multivariate analysis showed that the correlations between miR-122-3p and miR-92a-3p expression and ALT/AST index change were significant, as were the correlations between miR-192-5p expression and ALP/ALT/AST index change. This study showed that circulating microRNA expression levels in serum of DILI significantly increased and were positively correlated with the AST, ALP, and ALT expression levels. Circulating miRNA expression in serum can be used as a predictor and therapeutic index of DILI, which has high clinical value.

This study focuses on dissipativity-based fault detection for multiple delayed uncertain switched Takagi-Sugeno fuzzy stochastic systems with intermittent faults and unmeasurable premise variables. Nonlinear dynamics, exogenous disturbances, and measurement noise are also considered. In contrast to the existing study works, there is a wider range of applications. An observer is explored to detect faults. A controller is studied to stabilize the considered system. A piecewise fuzzy Lyapunov function is collected to obtain delay-dependent sufficient conditions by means of linear matrix inequalities. The designed observer has less conservatism. In addition, the strict (Q, S,R)-e-dissipativity performance is achieved in the residual dynamic. Besides, the elaborate H∞ performance and the elaborate H performance are also acquired. Finally, the availability of the method in this study is verified through two simulation examples.

Based on a rough path foundation, we develop a model-free approach to stochastic portfolio theory (SPT). Our approach allows to handle significantly more general portfolios compared to previous model-free approaches based on Föllmer integration. Without the assumption of any underlying probabilistic model, we prove a pathwise formula for the relative wealth process, which reduces in the special case of functionally generated portfolios to a pathwise version of the so-called master formula of classical SPT. We show that the appropriately scaled asymptotic growth rate of a far reaching generalization of Cover's universal portfolio based on controlled paths coincides with that of the best retrospectively chosen portfolio within this class. We provide several novel results concerning rough integration, and highlight the advantages of the rough path approach by showing that (nonfunctionally generated) log-optimal portfolios in an ergodic Itô diffusion setting have the same asymptotic growth rate as Cover's universal portfolio and the best retrospectively chosen one.

Parkinson’s disease (PD) is the second most common neurodegenerative disease; it mainly occurs in the elderly population. Cuproptosis is a newly discovered form of regulated cell death involved in the progression of various diseases. Combining multiple GEO datasets, we analyzed the expression profile and immunity of cuproptosis-related genes (CRGs) in PD. Dysregulated CRGs and differential immune responses were identified between PD and non-PD substantia nigra. Two CRG clusters were defined in PD. Immune analysis suggested that CRG cluster 1 was characterized by a high immune response. The enrichment analysis showed that CRG cluster 1 was significantly enriched in immune activation pathways, such as the Notch pathway and the JAK-STAT pathway. KIAA0319, AGTR1, and SLC18A2 were selected as core genes based on the LASSO analysis. We built a nomogram that can predict the occurrence of PD based on the core genes. Further analysis found that the core genes were significantly correlated with tyrosine hydroxylase activity. This study systematically evaluated the relationship between cuproptosis and PD and established a predictive model for assessing the risk of cuproptosis subtypes and the outcome of PD patients. This study provides a new understanding of PD-related molecular mechanisms and provides new insights into the treatment of PD.

For decades, employing cyclic voltammetry for mechanistic investigation demands manual inspection of voltammograms. Here we report a deep-learning-based algorithm that automatically analyzes cyclic voltammograms and designates a electrochemical probable mechanism among five of the most common ones in homogenous molecular electrochemistry. The reported algorithm will aid researchers’ mechanistic analysis, utilize otherwise elusive features in voltammograms, and experimentally observe the gradual mechanism transitions encountered in electrochemistry. An automated voltammogram analysis will aid the analysis of complex electrochemical systems and promise autonomous high-throughput research in electrochemistry with minimal human interference.

Background In September 2015, the State Council of China issued guidelines on building a hierarchical medical system, stating that the first visit rate to primary healthcare (PHC) facilities should be increased to 70% for all medical facilities by 2017. This meta-analysis aims to estimate the willingness of the first visit to PHC services in China after the year 2015 and identify its determinants. Methods A meta-analysis was conducted. Results The combined estimate from 23 studies in China for the willingness rate of the first visit to PHC services was 56% (95% CI: 47–65). Chronic diseases may be one source of heterogeneity. We identified five main associated factors with the pooled odds ratio ranging from 1.39 to 10.28, including fair self-reported health status; high understanding of service content; good service attitude; solid expertise and advanced diagnostic methods; and a good medical environment. Conclusion In comparison with China’s State Council recommendations, the willingness rate for the first visit to PHC services was significantly lower. The Government should develop strategies to facilitate the implementation of a hierarchical system for diagnosis and treatment.