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In this paper, a novel model predictive control (MPC) method based on the population normal probability division genetic algorithm and ant colony optimization (GA-ACO) method is proposed to optimally solve the problem of standard MPC with constraints that generally cannot yield global optimal solutions when using quadratic programming (QP). Combined with dynamic sliding mode control (SMC), this model is applied to the dynamic trajectory tracking control of autonomous underwater vehicles (AUVs). First, the computational fluid dynamics (CFD) simulation platform ANSYS Fluent is used to solve for the main hydrodynamic coefficients required to establish the AUV dynamic model. Then, the novel model predictive controller is used to obtain the desired velocity command of the AUV. To reduce the influence of external interference and realize accurate velocity tracking, dynamic SMC is used to obtain the control input command. In addition, stability analysis based on the Lyapunov method proves the asymptotic stability of the controller. Finally, the trajectory tracking performance of the AUV in an underwater, three-dimensional environment is verified by using the MATLAB/Simulink simulation platform. The results verify the effectiveness and robustness of the proposed control method.

Due to the importance of underwater exploration in the development and utilization of deep-sea resources, underwater autonomous operation is more and more important to avoid the dangerous high-pressure deep-sea environment. For underwater autonomous operation, the intelligent computer vision is the most important technology. In an underwater environment, weak illumination and low-quality image enhancement, as a preprocessing procedure, is necessary for underwater vision. In this paper, a combination of max-RGB method and shades of gray method is applied to achieve the enhancement of underwater vision, and then a CNN (Convolutional Neutral Network) method for solving the weakly illuminated problem for underwater images is proposed to train the mapping relationship to obtain the illumination map. After the image processing, a deep CNN method is proposed to perform the underwater detection and classification, according to the characteristics of underwater vision, two improved schemes are applied to modify the deep CNN structure. In the first scheme, a 1∗1 convolution kernel is used on the 26∗26 feature map, and then a downsampling layer is added to resize the output to equal 13∗13. In the second scheme, a downsampling layer is added firstly, and then the convolution layer is inserted in the network, the result is combined with the last output to achieve the detection. Through comparison with the Fast RCNN, Faster RCNN, and the original YOLO V3, scheme 2 is verified to be better in detecting underwater objects. The detection speed is about 50 FPS (Frames per Second), and mAP (mean Average Precision) is about 90%. The program is applied in an underwater robot; the real-time detection results show that the detection and classification are accurate and fast enough to assist the robot to achieve underwater working operation.

Natural killer (NK) cells, initially identified for their rapid virus-infected and leukemia cell killing and tumor destruction, are pivotal in immunity. They exhibit multifaceted roles in cancer, viral infections, autoimmunity, pregnancy, wound healing, and more. Derived from a common lymphoid progenitor, they lack CD3, B-cell, or T-cell receptors but wield high cytotoxicity via perforin and granzymes. NK cells orchestrate immune responses, secreting inflammatory IFNγ or immunosuppressive TGFβ and IL-10. CD56 dim and CD56 bright NK cells execute cytotoxicity, while CD56 bright cells also regulate immunity. However, beyond the CD56 dichotomy, detailed phenotypic diversity reveals many functional subsets that may not be optimal for cancer immunotherapy. In this review, we provide comprehensive and detailed snapshots of NK cells’ functions and states of activation and inhibitions in cancer, autoimmunity, angiogenesis, wound healing, pregnancy and fertility, aging, and senescence mediated by complex signaling and ligand-receptor interactions, including the impact of the environment. As the use of engineered NK cells for cancer immunotherapy accelerates, often in the footsteps of T-cell-derived engineering, we examine the interactions of NK cells with other immune effectors and relevant signaling and the limitations in the tumor microenvironment, intending to understand how to enhance their cytolytic activities specifically for cancer immunotherapy.

Seabed fishing depends on humans in common, for instance, the sea cucumber, sea urchin, and scallop fishing, which is always a very dangerous task. Considering the underwater complex environment conditions such as low temperature, dim vision, and high pressure, collecting the marine products using underwater robots is commonly regarded as a feasible solution. The key technique of the underwater robot development is to detect and locate the main target from underwater vision. This research is based on the deep convolutional neural network (CNN) to realize the target recognition from underwater vision. The RPN (Region Proposal Network) is used to optimize the feature extraction capability. Deep learning dataset is prepared using an underwater video obtained from a sea cucumber fishing ROV (Remote Operated Vehicle). The inspiration of the network structure and the improvements come from the Faster RCNN and Hypernet method, and for the underwater dataset, the method proposed in this paper shows a good performance of recall and object detection accuracy. The detection runs with a speed of 17 fps on a GPU, which is applicable to be used for real-time processing.

Ferroptosis, a form of iron-dependent cell death driven by cellular metabolism and iron-dependent lipid peroxidation, has been implicated as a tumor-suppressor function for cancer therapy. Recent advance revealed that the sensitivity to ferroptosis is tightly linked to numerous biological processes, including metabolism of amino acid and the biosynthesis of glutathione. Here, by using a high-throughput CRISPR/Cas9-based genetic screen in HepG2 hepatocellular carcinoma cells to search for metabolic proteins inhibiting ferroptosis, we identified a branched-chain amino acid aminotransferase 2 (BCAT2) as a novel suppressor of ferroptosis. Mechanistically, ferroptosis inducers (erastin, sorafenib, and sulfasalazine) activated AMPK/SREBP1 signaling pathway through iron-dependent ferritinophagy, which in turn inhibited BCAT2 transcription. We further confirmed that BCAT2 as the key enzyme mediating the metabolism of sulfur amino acid, regulated intracellular glutamate level, whose activation by ectopic expression specifically antagonize system Xc– inhibition and protected liver and pancreatic cancer cells from ferroptosis in vitro and in vivo. On the contrary, direct inhibition of BCAT2 by RNA interference, or indirect inhibition by blocking system Xc– activity, triggers ferroptosis. Finally, our results demonstrate the synergistic effect of sorafenib and sulfasalazine in downregulating BCAT2 expression and dictating ferroptotic death, where BCAT2 can also be used to predict the responsiveness of cancer cells to ferroptosis-inducing therapies. Collectively, these findings identify a novel role of BCAT2 in ferroptosis, suggesting a potential therapeutic strategy for overcoming sorafenib resistance.

Conventional cancer treatments, such as surgical resection, radiotherapy, and chemotherapy, have achieved significant progress in cancer therapy. Nevertheless, some limitations (such as toxic side effects) are still existing for conventional therapies, which motivate efforts toward developing novel theranostic avenues. Owning many merits such as easy surface modification, unique optical properties, and high biocompatibility, gold nanoparticles (AuNPs and GNPs) have been engineered to serve as targeted delivery vehicles, molecular probes, sensors, and so on. Their small size and surface characteristics enable them to extravasate and access the tumor microenvironment (TME), which is a promising solution to realize highly effective treatments. Moreover, stimuli-responsive properties (respond to hypoxia and acidic pH) of nanoparticles to TME enable GNPs’ unrivaled control for effective transport of therapeutic cargos. In this review article, we primarily introduce the basic properties of GNPs, further discuss the recent progress in gold nanoparticles for cancer theranostics, with an additional concern about TME stimuli-responsive studies.

Xiangdong Fu and colleagues map variants in OsSPL16 that influence grain width and yield in a cross between a slender-grain Basmati and a wide-grain indica variety of rice. The authors show that higher expression of OsSPL16 promotes cell division and grain filling and can lead to improvements in grain quality and yield. Grain size and shape are important components of grain yield and quality and have been under selection since cereals were first domesticated. Here, we show that a quantitative trait locus GW8 is synonymous with OsSPL16 , which encodes a protein that is a positive regulator of cell proliferation. Higher expression of this gene promotes cell division and grain filling, with positive consequences for grain width and yield in rice. Conversely, a loss-of-function mutation in Basmati rice is associated with the formation of a more slender grain and better quality of appearance. The correlation between grain size and allelic variation at the GW8 locus suggests that mutations within the promoter region were likely selected in rice breeding programs. We also show that a marker-assisted strategy targeted at elite alleles of GS3 and OsSPL16 underlying grain size and shape can be effectively used to simultaneously improve grain quality and yield.

In this article, carbon black nanofluids were prepared by dispersing the pretreated carbon black powder into distilled water. The size and morphology of the nanoparticles were explored. The photothermal properties, optical properties, rheological behaviors, and thermal conductivities of the nanofluids were also investigated. The results showed that the nanofluids of high-volume fraction had better photothermal properties. Both carbon black powder and nanofluids had good absorption in the whole wavelength ranging from 200 to 2,500 nm. The nanofluids exhibited a shear thinning behavior. The shear viscosity increased with the increasing volume fraction and decreased with the increasing temperature at the same shear rate. The thermal conductivity of carbon black nanofluids increased with the increase of volume fraction and temperature. Carbon black nanofluids had good absorption ability of solar energy and can effectively enhance the solar absorption efficiency.

To investigate the exact role of GRP78 in artesunate-induced ferroptosis in mutant pancreatic cancer cells. Artesunate-induced mutant human pancreatic cancer cells (AsPC-1 and PaTU8988) ferroptosis was confirmed by fluorescent staining experiments and CCK8. Western blot and short-hairpin RNA-based knockdown assays were conducted to detect GRP78 activity and its role in artesunate-induced ferroptosis. Artesunate induced AsPC-1 and PaTU8988 cell death in ferroptosis manner, rather than necrosis or apoptosis. In addition, artesunate increased the mRNA and protein levels of GRP78 in a concentration-dependent manner in AsPC-1 and PaTU8988 cells. Knockdown GRP78 enhanced artesunate-induced ferroptosis of pancreatic cancer cells in vitro and in vivo. Combining artesunate with GRP78 inhibition may be a novel maneuver for effective killing of mutant pancreatic ductal adenocarcinoma cells.