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Colorectal cancer (CRC) is a common malignant tumor worldwide. The solute carrier family 25 member 18 (SLC25A18) transports glutamate across the inner mitochondrial membrane and involves some non-tumor diseases, yet little is known about its role in malignancy. Here, we studied the function and mechanism of SLC25A18 in CRC. We conducted a bioinformatic analysis of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify the correlation of SLC25A18 expression with clinic-pathological characteristics. Function experiments were implemented to estimate the variation of aerobic glycolysis and cell proliferation due to in vitro and in vivo up- or down-regulation of SLC25A18. Immunohistochemical staining of SLC25A18 was performed on a tissue microarray of 106 patients with primary or metastatic CRC to evaluate its predictive and prognostic value. SLC25A18 expression was low in the CRC samples and was negatively correlated with stage, age and serum carcinoembryonic antigen levels. High expression of SLC25A18 indicated longer disease-free survival time after surgery. Exogenous overexpression of SLC25A18 decreased glucose consumption, lactate production, intracellular ATP concentration and cell proliferation and abrogated expression of CTNNB1, PKM2, LDHA and MYC. Inhibition of Wnt/β-catenin restored SLC25A18-repressed cellular activities. SLC25A18 clinically predicted a longer survival time after surgery or medicine treatment. These results showed that increased SLC25A18 expression inhibits Warburg effect and cell proliferation via Wnt/β-catenin cascade, and suggest a better prognosis after treatment.

We propose a single-stage Human-Object Interaction (HOI) detection method that has outperformed all existing methods on HICO-DET dataset at 37 fps on a single Titan XP GPU. It is the first real-time HOI detection method. Conventional HOI detection methods are composed of two stages, i.e., human-object proposals generation, and proposals classification. Their effectiveness and efficiency are limited by the sequential and separate architecture. In this paper, we propose a Parallel Point Detection and Matching (PPDM) HOI detection framework. In PPDM, an HOI is defined as a point triplet < human point, interaction point, object point>. Human and object points are the center of the detection boxes, and the interaction point is the midpoint of the human and object points. PPDM contains two parallel branches, namely point detection branch and point matching branch. The point detection branch predicts three points. Simultaneously, the point matching branch predicts two displacements from the interaction point to its corresponding human and object points. The human point and the object point originated from the same interaction point are considered as matched pairs. In our novel parallel architecture, the interaction points implicitly provide context and regularization for human and object detection. The isolated detection boxes are unlikely to form meaning HOI triplets are suppressed, which increases the precision of HOI detection. Moreover, the matching between human and object detection boxes is only applied around limited numbers of filtered candidate interaction points, which saves much computational cost. Additionally, we build a new application-oriented database named HOI-A, which severs as a good supplement to the existing datasets. The source code and the dataset will be made publicly available to facilitate the development of HOI detection., Accepted to CVPR 2020. Code is available at https://github.com/YueLiao/PPDM

Short‐chain fatty acids (SCFAs), produced from fermentation of dietary fibre by the gut microbiota, have been suggested to modulate energy metabolism. Previous work using rodent models has demonstrated that oral supplementation of the SCFA propionate raises resting energy expenditure (REE) by promoting lipid oxidation. The objective of the present study was to investigate the effects of oral sodium propionate on REE and substrate metabolism in humans. Eighteen healthy volunteers (9 women and 9 men; age 25 ± 1 years; body mass index 24.1 ± 1.2 kg/m2) completed 2 study visits following an overnight fast. Tablets containing a total of 6845 mg sodium propionate or 4164 mg sodium chloride were provided over the 180‐minute study period in random order. REE and substrate oxidation were assessed by indirect calorimetry. Oral sodium propionate administration increased REE (0.045 ± 0.020 kcal/min; P = .036); this was accompanied by elevated rates of whole‐body lipid oxidation (0.012 ± 0.006 g/min; P = .048) and was independent of changes in glucose and insulin concentrations. Future studies are warranted to determine whether the acute effects of oral sodium propionate on REE translate into positive improvements in long‐term energy balance in humans.

Background: Manganese (Mn) stress is an important reason for forming tobacco ( Nicotiana tobacum L. ) leaf browning, leading to low yield and quality of tobacco leaves. The mechanism of flue-cured tobacco varieties, Honghuadajinyuan (Hongda) and K326 tobacco leaves browning by Mn were explored. The two tobacco varieties were planted in red soil and sandy soil and Mn concentration of 0, 250, 500, 750 and 1000 mg/kg were applied. The research investigate the traits of agronomic, physiological and economic of flue-cured tobacco. Results: As Mn application rate increased, browning scale increased while plant height, root, stem and total weight, content of chlorophyll decreased. Activities of superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX) showed a rising parabolic formation. As Mn application rate increased, the content of malondialdehyde (MDA) and relative conductivity increased. Peroxidase (POD) activity continually increased with Mn application rate in K326 variety, while in Hongda variety, POD activity first increased and then decreased in sandy soil, while it continuously rose in red soil. Mn concentration and browning scale were significantly and negatively correlated with height, soil and plant analysis development (SPAD), CAT, total weight, average priceand yield, but significantly positively correlated with total plant Mn content, POD and MDA. Plant Mn concentration was significantly and positively correlated with browning scale. This study founded that SOD, CAT, APX, POD enzyme activity and MDA content in tobacco leaves affected by Mn concentration in soils, cause the change of chlorophyll content, agronomic and economic traits of flue-cured tobaccos. Conclusion: The mechanism of Mn stress to the physio-biochemical of tobacco varieties would be useful for controlling browning tobacco leaves by agronomic strategies and regarding as markers for Mn tolerance in breeding.

In this study, a mimotope peptide-based non-toxic photoelectrochemical (PEC) competitive enzyme-linked immunoassay (ELISA) was established for ultrasensitive detection of zearalenone (ZEN) with dual-signal readout. Using the phage display technique (PDT), a mimotope peptide of ZEN could be harvested by selecting a peptide from a phage-display peptide library, which avoided using mycotoxin itself and minimized potential damage to operators. The tyramine-modified rutile TiO2 mesocrystals (Tyr-RMC) with outstanding PEC properties were utilized as reporter units to label the mimotope peptide. The fabricated peptide@Tyr-RMC probe could anchor on the antibody-modified electrode via competitive immune recognition of free target ZEN. When subjected to catalysis of HRP-H2O2, the Tyr-RMC composite was deposited at the enzyme reaction site, causing rolling circle extension of the reporter unit chains. By merit of the brilliant signal amplification effect of tyramine signal amplification (TSA), dramatically enhanced photocurrent response and enormously increased electrochemical impedance could be determined. Combining all of these advantages, the developed dual-signal readout non-toxicity immunoassay could effectively decrease environmental interference. Also, the designed dual-signal readout biosensor demonstrated a wide linear range between 10-6 and 1 ng mL-1 with a low detection limit of 1 × 10-6 ng mL-1, which provides a valuable reference for developing highly efficient, secure and sensitive detection methods and indicates promising applicability in food testing.

Referring expression comprehension aims to localize the object instance described by a natural language expression. Current referring expression methods have achieved good performance. However, none of them is able to achieve real-time inference without accuracy drop. The reason for the relatively slow inference speed is that these methods artificially split the referring expression comprehension into two sequential stages including proposal generation and proposal ranking. It does not exactly conform to the habit of human cognition. To this end, we propose a novel Realtime Cross-modality Correlation Filtering method (RCCF). RCCF reformulates the referring expression comprehension as a correlation filtering process. The expression is first mapped from the language domain to the visual domain and then treated as a template (kernel) to perform correlation filtering on the image feature map. The peak value in the correlation heatmap indicates the center points of the target box. In addition, RCCF also regresses a 2-D object size and 2-D offset. The center point coordinates, object size and center point offset together to form the target bounding box. Our method runs at 40 FPS while achieving leading performance in RefClef, RefCOCO, RefCOCO+ and RefCOCOg benchmarks. In the challenging RefClef dataset, our methods almost double the state-of-the-art performance (34.70% increased to 63.79%). We hope this work can arouse more attention and studies to the new cross-modality correlation filtering framework as well as the one-stage framework for referring expression comprehension., Accepted by CVPR 2020

Herein, a photothermal triggered multi-signal readout (MSR) system was innovatively established with great convenience for low-cost and sensitive point-of-care testing (POCT). In this sensing system, an intelligent multi-signal readout interface (MSRI) with multidimensional response-ability to thermal stimulus was developed and utilized as a sensing element. A bio-bar-code photothermal probe peptides@H2N-HCNTs acted as a target associated photothermal agent anchored on MSRI via competitive reaction. The multi-signal assay of target was realized under the driven of 808 nm laser, photo-to-thermal conversion effect of photothermal probe caused dramatically thermal energy increase on MSRI. As a result, the competitive recognition events were translated into several detectable signals on MSRI, including a local temperature elevation, a visual color change from blue to green as well as weight loss on MSRI, all of these signals were proportional to the target concentration. This assay has been successfully applied in field work for detecting zearalenone (ZEN), a common mycotoxin in grain food, with linear ranger from 10−7 ng/mL to 10−1 ng/mL and detection limits of 1.06 × 10−7 ng/mL. Combination of the different signal principles was expected to result in more reliable and precise results. Accordingly, this creatively designed MSR-system not only provided a platform for sensitive monitor of mycotoxin but also offered new method for reliable and affordable personal assays in daily life and low-resource setting.

This paper concentrates on the global predefined-time synchronization of delayed memristive neural networks with external unknown disturbance via an observer-based active control. First, a global predefined-time stability theorem based on a non-negative piecewise Lyapunov function is proposed, which can obtain more accurate upper bound of the settling time estimation. Subsequently, considering the delayed memristive neural networks with disturbance, a disturbance-observer is designed to approximate the external unknown disturbance in the response system with a Hurwitz theorem and then to eliminate the influence of the unknown disturbance. With the help of global predefined-time stability theorem, the predefined-time synchronization is achieved between two delayed memristive neural networks via an active control Lyapunov function design. Finally, two numerical simulations are performed, and the results are given to show the correctness and feasibility of the predefined-time stability theorem.