A disposable DNA methylation sensor based on the printable graphene field effect transistor

The detection of DNA methylation is necessary for the research of epigenetics. In this work we would like to propose a disposable DNA methylation sensor by using graphene field effect transistor (GFET) as the sensing platform. In this component, the liquid-phase exfoliated graphene (LEG) nanosheets were drop-coated on the flexible substrates of polyethylene terephthalate (PET) films. Then, the interdigital structured electrodes (named as source and drain) were printed on the LEG coated PET films to form the expected GFETs. Thirdly, the carbon dots (CDs) decoration was conducted and examined on the asprepared GFETs to evaluate the influence of CDs, as well as optimize CDs’ concentration. At last, the immune identification-based sensing strategy was utilized on the CDs modified GFETs to develop the concerned DNA methylation sensor. The experimental data indicate the proposed sensors could be a potential experimental tool for epigenetic research

Towards Generalizable Referring Image Segmentation via Target Prompt and Visual Coherence

Referring image segmentation (RIS) aims to segment objects in an image conditioning on free-from text descriptions. Despite the overwhelming progress, it still remains challenging for current approaches to perform well on cases with various text expressions or with unseen visual entities, limiting its further application. In this paper, we present a novel RIS approach, which substantially improves the generalization ability by addressing the two dilemmas mentioned above. Specially, to deal with unconstrained texts, we propose to boost a given expression with an explicit and crucial prompt, which complements the expression in a unified context, facilitating target capturing in the presence of linguistic style changes. Furthermore, we introduce a multi-modal fusion aggregation module with visual guidance from a powerful pretrained model to leverage spatial relations and pixel coherences to handle the incomplete target masks and false positive irregular clumps which often appear on unseen visual entities. Extensive experiments are conducted in the zero-shot cross-dataset settings and the proposed approach achieves consistent gains compared to the state-of-the-art, e.g., 4.15\%, 5.45\%, and 4.64\% mIoU increase on RefCOCO, RefCOCO+ and ReferIt respectively, demonstrating its effectiveness. Additionally, the results on GraspNet-RIS show that our approach also generalizes well to new scenarios with large domain shifts.Comment: 7 pages, 4 figure

Nano-Porous Light-Emitting Silicon Chip as a Potential Biosensor Platform

Nano-porous silicon (PS) offers a potential platform for biosensors with benefits both in terms of light emission and the large functional surface area. A light emitting PS chip with a stable and functional surface was fabricated in our laboratory. When protein was deposited on it, the light emission was reduced in proportion to the protein concentration. Based on this property, we developed a rudimentary demonstration of a label-free sensor to detect bovine serum albumin (BSA). A serial concentration of BSA was applied to the light chip and the reduction in light emission was measured. The reduction of the light intensity was linearly related to the concentration of the BSA at concentrations below 10-5 M. The detection limit was 8×10-9 M

Fatty acid metabolites of Dendrobium nobile were positively correlated with representative endophytic fungi at altitude

IntroductionAltitude, as a comprehensive ecological factor, regulates the growth and development of plants and microbial distribution. Dendrobium nobile (D. nobile) planted in habitats at different elevations in Chishui city, also shows metabolic differences and endophytes diversity. What is the triangular relationship between altitude, endophytes, and metabolites?MethodsIn this study, the diversity and species of endophytic fungi were tested by ITS sequencing and metabolic differences in plants were tested by UPLC–ESI–MS/MS. Elevation regulated the colonization of plant endophytic fungal species and fatty acid metabolites in D. nobile.ResultsThe results indicate that and high altitude was better for the accumulation of fatty acid metabolites. Therefore, the high-altitude characteristic endophytic floras were screened, and the correlation with fatty acid metabolites of plants was built. The colonization of T. rubrigenum, P. Incertae sedis unclassified, Phoma. cf. nebulosa JZG 2008 and Basidiomycota unclassified showed a significantly positive correlation with fatty acid metabolites, especially 18-carbon-chain fatty acids, such as (6Z,9Z,12Z)-octadeca-6,9,12-trienoic acid, 3,7,11,15-tetramethyl-12-oxohexadeca-2,4-dienoic acid and Octadec-9-en-12-ynoic acid. What is more fascinating is these fatty acids are the essential substrates of plant hormones.DiscussionConsequently, it was speculated that the D. nobile- colonizing endophytic fungi stimulated or upregulated the synthesis of fatty acid metabolites and even some plant hormones, thus affecting the metabolism and development of D. nobile

A disposable DNA methylation sensor based on the printable graphene field effect transistor

The detection of DNA methylation is necessary for the research of epigenetics. In this work we would like to propose a disposable DNA methylation sensor by using graphene field effect transistor (GFET) as the sensing platform. In this component, the liquid-phase exfoliated graphene (LEG) nanosheets were drop-coated on the flexible substrates of polyethylene terephthalate (PET) films. Then, the interdigital structured electrodes (named as source and drain) were printed on the LEG coated PET films to form the expected GFETs. Thirdly, the carbon dots (CDs) decoration was conducted and examined on the asprepared GFETs to evaluate the influence of CDs, as well as optimize CDs’ concentration. At last, the immune identification-based sensing strategy was utilized on the CDs modified GFETs to develop the concerned DNA methylation sensor. The experimental data indicate the proposed sensors could be a potential experimental tool for epigenetic research

Hyper α2,6‐Sialylation Promotes CD4+ T‐Cell Activation and Induces the Occurrence of Ulcerative Colitis

Abstract α2,6‐sialylation, catalyzed by α2,6‐sialyltransferase (ST6GAL1), plays a pivotal role in immune responses. However, the role of ST6GAL1 in the pathogenesis of ulcerative colitis (UC) remains unknown. ST6GAL1 mRNA is highly expressed in UC tissues compared with the corresponding adjacent normal tissues, and α2,6‐sialylation is significantly increased in the colon tissues of patients with UC. The expression of ST6GAL1 and proinflammatory cytokines, such as interleukin (IL)‐2, IL‐6, IL‐17, and interferon‐gamma, is also increased. The number of CD4+ T cells increases in UC patients. St6gal1 gene knockout (St6gal1−/‐) rats are established by clustered regularly interspaced short palindromic repeats (CRISPR)‐associated gene knockout system. St6gal1 deficiency reduces the levels of pro‐inflammatory cytokines and alleviates colitis symptoms in UC model rats. Ablation of α2,6‐sialylation inhibits the transport of the TCR to lipid rafts and suppresses CD4+ T‐cell activation. The attenuation of TCR signaling downregulates the expression of NF‐κB in ST6GAL1‐/‐ CD4+ T‐cells. Moreover, NF‐κB could bind to the ST6GAL1 promoter to increase its transcription. Ablation of ST6GAL1 downregulates the expression of NF‐κB and reduces the production of proinflammatory cytokines to relieve UC pathogenesis, which is a potential novel target for the clinical treatment of UC

Detection of Abnormal Data in GNSS Coordinate Series Based on an Improved Cumulative Sum

The global navigation satellite system (GNSS), as a high-time resolution and high-precision measurement technology, has been widely used in the field of deformation monitoring. Owing to the influence of uncontrollable factors, there are inevitably some abnormal data in the GNSS monitoring series. Thus, it is necessary to detect and identify abnormal data in the GNSS monitoring series to improve the accuracy and reliability of the deformation disaster law analysis and warning. Many methods can be used to detect abnormal data, among which the statistical process control theory, represented by the cumulative sum (CUSUM), is widely used. CUSUM usually constructs statistics and determines control limits based on the threshold criteria of the average run length (ARL) and then uses the control limits to identify abnormal data in CUSUM statistics. However, different degrees of the ‘trailing’ phenomenon exist in the interval of abnormal data identified by the algorithm, leading to a higher false alarm rate. Therefore, we propose an improved CUSUM method that uses breaks for additive season and trend (BFAST) instead of ARL-based control limits to identify abnormal data in CUSUM statistics to improve the accuracy of identification. The improved CUSUM method is used to detect abnormal data in the GNSS coordinate series. The results show that compared with CUSUM, the improved CUSUM method shows stronger robustness, more accurate detection of abnormal data, and a significantly lower false alarm rate

Low Conservative Criteria for Robust Consensus of Multiagent Systems with Delays, Disturbances, and Topologies Uncertainties

Considering the limited communications conditions such as delays, disturbances, and topologies uncertainties, the stability criteria for robust consensus of multiagent systems are proposed in this paper. Firstly, by using the idea of state decomposition and space transformation, the condition for guaranteeing consensus is converted into verifying the robust stability of the disagreement system. In order to deal with multiple time-varying delays and switching topologies, jointly quadratic common Lyapunov-Krasovskii (JQCLK) functional is built to analyze the robust stability. Then, the numerical criterion can be obtained through solving the corresponding feasible nonlinear matrix inequality (NLMI); at last, nonlinear minimization is used like solving cone complementarity problem. Therefore, the linear matrix inequality (LMI) criterion is obtained, which can be solved by mathematical toolbox conveniently. In order to relax the conservativeness, free-weighting matrices (FWM) method is employed. Further, the conclusion is extended to the case of strongly connected topologies. Numerical examples and simulation results are given to demonstrate the effectiveness and the benefit on reducing conservativeness of the proposed criteria

The effect of explosive percentage on underwater explosion energy release of hexanitrohexaazaisowurtzitane and octogen based aluminized explosives

To control the explosion energy output by optimizing explosive components is a key requirement in a number of different application areas. The effect of different Al/O Ratio on underwater explosion of aluminized explosives has been studied detailedly. However, the effect of explosive percentage in the same Al/O Ratio is rarely researched, especially for Hexanitrohexaazaisowurtzitane (CL-20) based aluminized explosives. In this study, we performed the underwater explosion experiments with 1.2-kilogram explosives in order to investigate the explosion energy released from CL-20 and Octogen (HMX) based aluminized explosives. The percentage of the explosive varied from 5% to 30% and it is shown that: the shockwave peak pressure (pm) grows gradually; shock wave energy (Es) continues increasing, bubble energy (Eb) increases then decreases peaking at 15% for both formulas, and the total energy (E) and energy release rate (η) peak at 20% for CL-20 and 15% for HMX. This paper outlines the physical mechanism of Eb change under the influence of an aluminium initial reaction temperature and reaction active detonation product percentage coupling. The result shows that CL-20 is superior as a new high explosive and has promising application prospects in the regulation of explosive energy output for underwater explosives