Novel strategy for oncogenic alteration-induced lipid metabolism reprogramming in pancreatic cancer

The pathogenesis of pancreatic cancer involves substantial metabolic reprogramming, resulting in abnormal proliferation of tumor cells. This tumorigenic reprogramming is often driven by genetic mutations, such as activating mutations of the KRAS oncogene and inactivating or deletions of the tumor suppressor genes SMAD4, CDKN2A, and TP53, which play a critical role in the initiation and development of pancreatic cancer. As a normal cell gradually develops into a cancer cell, a series of signature characteristics are acquired: activation of signaling pathways that sustain proliferation; an ability to resist growth inhibitory signals and evade apoptosis; and an ability to generate new blood vessels and invade and metastasize. In addition to these features, recent research has revealed that metabolic reprogramming and immune escape are two other novel characteristics of tumor cells. The effect of the interactions between tumor and immune cells on metabolic reprogramming is a key factor determining the antitumor immunotherapy response. Lipid metabolism reprogramming, a feature of many malignancies, not only plays a role in maintaining tumor cell proliferation but also alters the tumor microenvironment by inducing the release of metabolites that in turn affect the metabolism of normal immune cells, ultimately leading to the attenuation of the antitumor immune response and resistance to immunotherapy. Pancreatic cancer has been found to have substantial lipid metabolism reprogramming, but the mechanisms remain elusive. Therefore, this review focuses on the mechanisms regulating lipid metabolism reprogramming in pancreatic cancer cells to provide new therapeutic targets and aid the development of new therapeutic strategies for pancreatic cancer

A Novel Target Detection Method of the Unmanned Surface Vehicle under All-Weather Conditions with an Improved YOLOV3

The USV (unmanned surface vehicle) is playing an important role in many tasks such as marine environmental observation and maritime security, for the advantages of high autonomy and mobility. Detecting the targets on the surface of the water with high precision ensures the subsequent task implementation. However, the changes from the lights and the surface environment influence the performance of the target detecting method in a long-term task with USV. Therefore, this paper proposed a novel target detection method by fusing DenseNet in YOLOV3 to improve the stability of detection to decrease the feature loss, while the target feature is transmitted in the layers of a deep neural network. All the image data used to train and test the proposed method were obtained in the real ocean environment with a USV in the South China Sea during a one month sea trial in November 2019. The experiment results demonstrate the performance of the proposed method is more suitable for the changed weather conditions though comparing with the existing methods, and the real-time performance is available in practical ocean tasks for USV

Concurrent Determination of Tigecycline, Tetracyclines and Their 4-Epimer Derivatives in Chicken Muscle Isolated from a Reversed-Phase Chromatography System Using Tandem Mass Spectrometry

A quantitative and qualitative method using a high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS) detection approach was developed and validated for the analysis of tigecycline, four tetracyclines and their three 4-epimer derivatives in chicken muscle. Samples were extracted repeatedly with 0.1 mol/L Na2EDTA–McIlvaine buffer solution. After vortexing, centrifugation, solid-phase extraction, evaporation and reconstitution, the aliquots were separated using a C8 reversed-phase column (50 mm × 2.1 mm, 5 µm) with a binary solvent system consisting of methanol and 0.01 mol/L trichloroacetic acid aqueous solution. The typical validation parameters were evaluated in accordance with the acceptance criteria detailed in the guidelines of the EU Commission Decision 2002/657/EC and the U.S. Food and Drug Administration Bioanalytical Method Validation 05/24/18. The matrix-matched calibration curve was linear over the concentration range from the limit of quantitation (LOQ) to 400 μg/kg for doxycycline, and the calibration graphs for tetracycline, chlortetracycline, oxytetracycline, their 4-epimer derivatives and tigecycline showed a good linear relationship within the concentration range from the LOQ to 200 μg/kg. The limits of detection (LODs) for the eight targets were in the range of 0.06 to 0.09 μg/kg, and the recoveries from the fortified blank samples were in the range of 89% to 98%. The within-run precision and between-run precision, which were expressed as the relative standard deviations, were less than 5.0% and 6.9%, respectively. The applicability was successfully demonstrated through the determination of residues in 72 commercial chicken samples purchased from different sources. This approach provides a novel option for the detection of residues in animal-derived food safety monitoring

Using Reinforcement Learning to Minimize the Probability of Delay Occurrence in Transportation

10.1109/TVT.2020.29647846932424 - 243

An embedded vertical‐federated feature selection algorithm based on particle swarm optimisation

Abstract In real life, a large amount of data describing the same learning task may be stored in different institutions (called participants), and these data cannot be shared among participants due to privacy protection. The case that different attributes/features of the same instance are stored in different institutions is called vertically distributed data. The purpose of vertical‐federated feature selection (FS) is to reduce the feature dimension of vertical distributed data jointly without sharing local original data so that the feature subset obtained has the same or better performance as the original feature set. To solve this problem, in the paper, an embedded vertical‐federated FS algorithm based on particle swarm optimisation (PSO‐EVFFS) is proposed by incorporating evolutionary FS into the SecureBoost framework for the first time. By optimising both hyper‐parameters of the XGBoost model and feature subsets, PSO‐EVFFS can obtain a feature subset, which makes the XGBoost model more accurate. At the same time, since different participants only share insensitive parameters such as model loss function, PSO‐EVFFS can effectively ensure the privacy of participants' data. Moreover, an ensemble ranking strategy of feature importance based on the XGBoost tree model is developed to effectively remove irrelevant features on each participant. Finally, the proposed algorithm is applied to 10 test datasets and compared with three typical vertical‐federated learning frameworks and two variants of the proposed algorithm with different initialisation strategies. Experimental results show that the proposed algorithm can significantly improve the classification performance of selected feature subsets while fully protecting the data privacy of all participants

Effects of Acremonium terricola Culture on the Growth, Slaughter Yield, Immune Organ, Serum Biochemical Indexes, and Antioxidant Indexes of Geese

Acremonium terricola culture (ATC) is a new type of green feed additive, and its main components include cordycepin, adenosine, and ergosterol. In this study, the Hortobagy geese were used as the experimental animals to explore the effects of ATC addition to the basal diet. Seven hundred and twenty 1-day-old Hortobagy geese were randomly divided into four treatment groups, each with 180 geese divided into six pens equally. The four treatments included the control group and three experimental treatments. Half of the geese in each group were males and half were females. All geese were offered the same basal diet with ATC supplementation at 0, 3, 5, and 7 g/kg. The results showed that basal diet supplementation with 7 g/kg ATC reduced the feed conversion rate (FCR) of Hortobagy geese in a highly significant manner (p < 0.01). When the dosage of ATC was 3 g/kg, the breast muscle rate and leg muscle rate of female geese were significantly increased (p < 0.05). ATC supplementation in the basal diet had no significant effect on the immune organ index of Hortobagy geese (p > 0.05). Basal diet supplementation with 3 g/kg and 5 g/kg ATC significantly reduced the alanine aminotransferase (ALT) content in the serum of female geese, significantly increased the total antioxidant capacity (T-AOC) of the serum, and significantly reduced the malondialdehyde (MDA) content in the serum (p < 0.05). The addition of 5 g/kg and 7 g/kg ATC to the basal diet reduced the blood glucose (GLU) content in male geese in a highly significant manner (p < 0.01). A basal diet supplemented with 3 g/kg and 7 g/kg ATC significantly reduced the MDA content in geese breast muscles (p < 0.05). Basal diet supplementation with 3 g/kg ATC highly significantly improved the T-AOC of female geese breast muscles (p < 0.01). Basal diet supplementation with 5 g/kg ATC significantly improved the T-AOC of female geese leg muscles (p < 0.01). In summary, basal diet supplementation with ATC enhances the growth performance and antioxidant properties of Hortobagy geese

Simultaneous Determination of Tetracyclines and Fluoroquinolones in Poultry Eggs by UPLC Integrated with Dual-Channel-Fluorescence Detection Method

An innovative, rapid and stable method for simultaneous determination of three tetracycline (oxytetracycline, tetracycline and doxycycline) and two fluoroquinolone (ciprofloxacin and enrofloxacin) residues in poultry eggs by ultra-high performance liquid chromatography–fluorescence detection (UPLC-FLD) was established and optimized. The samples were homogenized and extracted with acetonitrile/ultrapure water (90:10, v/v) and then purified by solid-phase extraction (SPE). LC separation was achieved on an ACQUITY UPLC BEH C18 column (1.7 µm, 2.1 mm × 100 mm), and the mobile phase was composed of acetonitrile and a 0.1 mol/L malonic acid solution containing 50 mmol/L magnesium chloride (the pH was adjusted to 5.5 with ammonia). When the five target drugs were spiked at the limit of quantification, 0.5 times the maximum residue limit (MRL), 1.0 MRL and 2.0 MRL, the recoveries were above 83.5% and the precision ranged from 1.99% to 6.24%. These figures of merit complied with the parameter validation regulations of the EU and U.S. FDA. The limits of detection and quantifications of the targets were 0.1–13.4 µg/kg and 0.3–40.1 µg/kg, respectively. The proposed method was easily extended to quantitative analyses of target drug residues in 85 egg samples, thus demonstrating its reliability and applicability