With the exacerbating problem of antibiotic resistance, antibiotic resistance genes (ARGs) as emerging contaminants are found at elevated levels in inland aquatic environments, especially in regions ...of intensive agricultural and urban activity. However, little quantitative data exist on the migration and attenuation of ARGs in estuary ecosystem, which is central to predicting their fate after release into marine environment. Moreover, the relevance of multiple chemical contaminants and water quality constituents should be understood to amplify and attenuate antibiotic resistance levels. To determine the prevalence and examine the fate of sulfonamide ARGs (sul-ARGs) in two estuaries under different effects of anthropogenic activities, we analyzed the sul-ARGs (sul1, sul2, and sul3), class 1 integrons (int1), and bacterial biomass in surface water samples from Daliaohe and Liaohe river estuaries. We also evaluated five types of antibiotics, heavy metals, and various bulk water quality constituents. Results showed that sul-ARGs were widespread in Daliaohe and Liaohe river estuaries, but the distribution did not correlate with the concentration of sulfonamides. Significant reduction in the abundance of sul-ARGs was also observed with increased salinity. Nevertheless, the trend in the change of concentrations of sul-ARGs was different in the two estuaries. Statistical analysis of the results indicated that several metals were significantly and positively correlated with sul-ARGs. Pearson's correlation coefficients were higher than those determined between antibiotic residues and sul-ARGs. Furthermore, the relative abundance of sul-ARGs was significantly and positively correlated with the relative abundance of int1 which suggested that the propagation of sul-ARGs was facilitated by class 1 integrons in estuaries.
•Trends in sul-ARGs were investigated in estuaries under different anthropogenic effect.•Distribution of sul-ARGs did not correlate with the sulfonamides levels in estuary.•Significant reduction of sul-ARGs abundances were observed in estuary.•Fate of sul-ARGs were affected by ambient pressures from non-antibiotic contaminants.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
As a safety-related application, visual systems based on deep neural networks (DNNs) in modern unmanned aerial vehicles (UAVs) show adversarial vulnerability when performing real-time inference. ...Recently, deep ensembles with various defensive strategies against adversarial samples have drawn much attention due to the increased diversity and reduced variance for their members. Aimed at the recognition task of remote sensing images (RSIs), this paper proposes to use a reactive-proactive ensemble defense framework to solve the security problem. In reactive defense, we fuse scoring functions of several classical detection algorithms with the hidden features and average output confidences from sub-models as a second fusion. In terms of proactive defense, we attempt two strategies, including enhancing the robustness of each sub-model and limiting the transferability among sub-models. In practical applications, the real-time RSIs are first input to the reactive defense part, which can detect and reject the adversarial RSIs. The accepted ones are then passed to robust recognition with a proactive defense. We conduct extensive experiments on three benchmark RSI datasets (i.e., UCM, AID, and FGSC-23). The experimental results show that the deep ensemble method of reactive and proactive defense performs very well in gradient-based attacks. The analysis of the applicable attack scenarios for each proactive ensemble defense is also helpful for this field. We also perform a case study with the whole framework in the black-box scenario, and the highest detection rate reaches 93.25%. Most of the adversarial RSIs can be rejected in advance or correctly recognized by the enhanced deep ensemble. This article is the first one to combine reactive and proactive defenses with a deep ensemble against adversarial attacks in the context of RSI recognition for DNN-based UAVs.
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Deep neural networks (DNNs) have been widely utilized in automatic visual navigation and recognition on modern unmanned aerial vehicles (UAVs), achieving state-of-the-art performances. However, ...DNN-based visual recognition systems on UAVs show serious vulnerability to adversarial camouflage patterns on targets and well-designed imperceptible perturbations in real-time images, which poses a threat to safety-related applications. Considering a scenario in which a UAV is suffering from adversarial attack, in this paper, we investigate and construct two ensemble approaches with CNN and transformer for both proactive (i.e., generate robust models) and reactive (i.e., adversarial detection) adversarial defense. They are expected to be secure under attack and adapt to the resource-limited environment on UAVs. Specifically, the probability distributions of output layers from base DNN models in the ensemble are combined in the proactive defense, which mainly exploits the weak adversarial transferability between the CNN and transformer. For the reactive defense, we integrate the scoring functions of several adversarial detectors with the hidden features and average the output confidence scores from ResNets and ViTs as a second integration. To verify their effectiveness in the recognition task of remote sensing images, we conduct experiments on both optical and synthetic aperture radar (SAR) datasets. We find that the ensemble model in proactive defense performs as well as three popular counterparts, and both of the ensemble approaches can achieve much more satisfactory results than a single base model/detector, which effectively alleviates adversarial vulnerability without extra re-training. In addition, we establish a one-stop platform for conveniently evaluating adversarial robustness and performing defense on recognition models called AREP-RSIs, which is beneficial for the future research of the remote sensing field.
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This paper proposes two new extended recursive three-step filters for linear discrete systems with dual-unknown inputs, which can simultaneously estimate unknown input and state. Extended recursive ...three-step filter 1 (ERTSF1) introduces an innovation for obtaining the estimates of the unknown input in the measurement equation, then derives the estimates of the unknown input in the state equation. After that, it uses the already obtained estimates of the dual-unknown inputs to correct the one-step prediction of the state, and finally, it obtains the minimum-variance unbiased estimate of the system state. Extended recursive three-step filter 2 (ERTSF2) establishes a unified innovation feedback model, then applies linear minimum-variance unbiased estimation to obtain the estimates of the system state and the dual-unknown inputs to refine a more concise recursive filter. Numerical Simulation Ex-ample demonstrates the effectiveness and superiority of the two filters in this paper compared with the traditional method. The battery state of charge estimation results demonstrate the effectiveness of ERTSF2 in practical applications.
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Diabetic nephropathy (DN) is one of the serious microvascular complications of diabetes mellitus (DM). A growing body of research has demonstrated that the inflammatory state plays a critical role in ...the incidence and development of DN. Pyroptosis is a new way of programmed cell death, which has the particularity of natural immune inflammation. The inhibition of inflammatory cytokine expression and regulation of pathways related to pyroptosis may be a novel strategy for DN treatment. The aim of this study is to identify pyroptosis-related genes and potential drugs for DN.
DN differentially expressed pyroptosis-related genes were identified via bioinformatic analysis Gene Expression Omnibus (GEO) dataset GSE96804. Dataset GSE30528 and GSE142025 were downloaded to verify pyroptosis-related differentially expressed genes (DEGs). Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a pyroptosis-related gene predictive model. A consensus clustering analysis was performed to identify pyroptosis-related DN subtypes. Subsequently, Gene Set Variation Analysis (GSVA), Gene Ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to explore the differences between DN clusters. A protein-protein interaction (PPI) network was used to select hub genes and DGIdb database was utilized to screen potential therapeutic drugs/compounds targeting hub genes.
A total of 24 differentially expressed pyroptosis-related genes were identified in DN. A 16 gene predictive model was conducted via LASSO regression analysis. According to the expression level of these 16 genes, DN cases were divided into two subtypes, and the subtypes are mainly associated with inflammation, activation of immune response and cell metabolism. In addition, we identified 10 hub genes among these subtypes, and predicted 65 potential DN therapeutics that target key genes.
We identified two pyroptosis-related DN clusters and 65 potential therapeutical agents/compounds for DN, which might shed a light on the treatment of DN.
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A key requirement for the understanding of crystal growth is to detect how new layers form and grow at the nanoscale. Multistage crystallization pathways involving liquid-like, amorphous or ...metastable crystalline precursors have been predicted by theoretical work and have been observed experimentally. Nevertheless, there is no clear evidence that any of these precursors can also be relevant for the growth of crystals of organic compounds. Herein, we present a new growth mode for crystals of DL-glutamic acid monohydrate that proceeds through the attachment of preformed nanoscopic species from solution, their subsequent decrease in height at the surface and final transformation into crystalline 2D nuclei that eventually build new molecular layers by further monomer incorporation. This alternative mechanism provides a direct proof for the existence of multistage pathways in the crystallization of molecular compounds and the relevance of precursor units larger than the monomeric constituents in the actual stage of growth.
The environmental behaviors and migration patterns of antibiotic resistance genes (ARGs) have attracted considerable research interest. However, there has been little research concerning the effects ...of corresponding and non-corresponding contaminants on the fate of ARGs in coastal environments. In the present study, the distribution of intI1, sul1, sul2, qnrS and aac(6′)-Ib were analyzed in water and sediment samples of Laizhou Bay in the context of corresponding and non-corresponding contaminants. The abundance of intI1, sul1 and sul2 genes exhibited a clear decreasing trend extending from the inner estuary to the coastal area. Strong and positive correlations existed between sul1/sul2 and sulfonamide antibiotic residues in sediments, and between the abundances of intI1 and sul1/sul2. Statistical analyses indicated that non-corresponding contaminants were partially correlated with ARG abundances. These results suggest that non-corresponding contaminants may have direct or indirect influences on the abundances of ARGs and intI1 in the Laizhou Bay.
•The concentrations of ARGs exhibited a decreasing trend from estuary to coast.•Estuary environments played a natural attenuator role on the distribution of ARGs.•Non-corresponding contaminants may have influence on the abundances of ARGs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
For nonlinear discrete systems with dual unknown inputs, there are many limitations regarding previous nonlinear filters. This paper proposes two new, improved square-root cubature Kalman filtering ...(ISRCKF) algorithms to estimate system states and dual unknown inputs. Improved square-root cubature Kalman filtering 1 (ISRCKF1) introduces an innovation that first obtains the unknown input estimates from the measurement equation, then updates the innovation to derive the unknown input estimates from the state equation, then uses the already obtained estimates of the dual unknown inputs to correct the one-step estimate of the state, and finally the minimum variance unbiased estimate of the state is obtained. Improved square-root cubature Kalman filtering 2 (ISRCKF2) builds a unified innovation feedback model, then applies the minimum variance unbiased estimation (MVUE) criterion to obtain the estimates of system states and dual unknown inputs, refining a more concise recursive filter but requiring stronger assumptions. Finally, simulation results demonstrate that the above two algorithms can achieve the optimal estimates of system states and dual unknown inputs simultaneously, and ISRCKF2 further enhances the accuracy of both state and dual unknown inputs estimation, which verifies the validity of the proposed algorithms.
Abstract Background Pleural solitary fibrous tumors (pSFTs) are rare mesenchymal pleural tumors with rich vascularity. Surgical resection is the cornerstone of pSFTs treatment, requiring careful ...preoperative imaging to delineate lesion extent and vascular supply including contrast-enhanced computed tomography and other examinations depending on its size and characteristics. Case presentation The patient was a 34-year-old female with a mass measuring approximately 67 × 42 × 65 mm in the left posterior mediastinum. Intraoperatively, the mass demonstrated rich vascularity. Two veins originating from the abdominal cavity entered the lower pole, one converged from the superior pole, draining into the brachiocephalic vein. Additionally, two arteries arose directly from the descending aorta, while several veins drained into the intercostal veins. In response to unexpected intraoperative vascular findings, vascular clips and silk threads were used to ligate them. Subsequently, the tumor was successfully dissected, with approximately 600 ml of blood loss recorded during the 4-hour surgery. The patient exhibited a satisfactory postoperative recovery, and follow-up spanning over six months revealed no indications of recurrence or metastasis. Conclusions We firstly present a case of successful resection of a pSFT in a 34-year-old woman with a distinct feeding vessel arising from the descending aorta and describe the related surgical procedures. This case highlights preoperative evaluation of mass vascularity based on contrast-enhanced computed tomography. When blood supply is challenging to clarify, angiography can offer additional details, especially for giant pSFTs. Despite this, thorough intraoperative exploration remains essential to detect unexpected vessels. Appropriate interventions should be customized based on the vascular origins and the surrounding anatomical structures.
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ARGs concentrations (sul I and sul II) in surface water versus sediment. Genes and resistant bacteria. Display omitted
•First report of distribution characteristics of ARGs and its main sources in ...coastal environment of the Northern Yellow Sea.•There is strong relationship between sulfonamide and ARGs in coastal environments.•The gene int I may facilitate ARGs propagation as a major transmission mode of ARGs in marine environment.
Antibiotic resistance gene (ARG) residues and the mode of transmission in marine environments remain unclear. The sulfonamide (SAs) concentrations, different genes and total bacterial abundance in seawater and sediment of the Northern Yellow Sea were analyzed. Results showed the genes sul I and sul II were present at relatively high concentrations in all samples, whereas the gene sul III was detected fewer. The ARGs concentrations in the sediment were 103 times higher than those in water, which indicated sediment was essential ARG reservoir. Statistical analysis revealed the total antibiotic concentration was positively correlated with the relative abundance of the gene sul I and sul II. The relative abundances of the gene sul I and the gene sul II were also correlated positively with those of the gene int1. This correlation demonstrated that SAs exerted selective pressure on these ARGs, whereas the gene int1 could be implicated in the propagation of the genes sul I and sul II in marine environments.
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