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Abstract The increasing mortality rate of pancreatic cancer globally necessitates the urgent identification for novel therapeutic targets. This study investigated the expression, functions, and mechanistic insight of G protein inhibitory subunit 3 (Gαi3) in pancreatic cancer. Bioinformatics analyses reveal that Gαi3 is overexpressed in human pancreatic cancer, correlating with poor prognosis, higher tumor grade, and advanced classification. Elevated Gαi3 levels are also confirmed in human pancreatic cancer tissues and primary/immortalized cancer cells. Gαi3 shRNA or knockout (KO) significantly reduced cell viability, proliferation, cell cycle progression, and mobility in primary/immortalized pancreatic cancer cells. Conversely, Gαi3 overexpression enhanced pancreatic cancer cell growth. RNA-sequencing and bioinformatics analyses of Gαi3-depleted cells indicated Gαi3’s role in modulating the Akt-mTOR and PKA-Hippo-YAP pathways. Akt-S6 phosphorylation was decreased in Gαi3-depleted cells, but was increased with Gαi3 overexpression. Additionally, Gαi3 depletion elevated PKA activity and activated the Hippo pathway kinase LATS1/2, leading to YAP/TAZ inactivation, while Gαi3 overexpression exerted the opposite effects. There is an increased binding between Gαi3 promoter and the transcription factor TCF7L2 in pancreatic cancer tissues and cells. Gαi3 expression was significantly decreased following TCF7L2 silencing, but increased with TCF7L2 overexpression. In vivo, intratumoral injection of Gαi3 shRNA-expressing adeno-associated virus significantly inhibited subcutaneous pancreatic cancer xenografts growth in nude mice. A significant growth reduction was also observed in xenografts from Gαi3 knockout pancreatic cancer cells. Akt-mTOR inactivation and increased PKA activity coupled with YAP/TAZ inactivation were also detected in xenograft tumors upon Gαi3 depletion. Furthermore, bioinformatic analysis and multiplex immunohistochemistry (mIHC) staining on pancreatic cancer tissue microarrays showed a reduced proportion of M1-type macrophages and an increase in PD-L1 positive cells in Gαi3-high pancreatic cancer tissues. Collectively, these findings highlight Gαi3’s critical role in promoting pancreatic cancer cell growth, potentially through the modulation of the Akt-mTOR and PKA-Hippo-YAP pathways and its influence on the immune landscape.

Kiwifruit bacterial canker, caused by Pseudomonas syringae pv. actinidiae (PSA), poses a grave threat to the global kiwifruit industry. In this study, we examined the role of microRNAs (miRNAs) in kiwifruit’s response to PSA. Kiwifruit seedlings subjected to PSA treatment showed significant changes in both miRNA and gene expression compared to the control group. We identified 364 differentially expressed miRNAs (DEMs) and 7170 differentially expressed genes (DEGs). Further analysis revealed 180 miRNAs negatively regulating 641 mRNAs. Notably, two miRNAs from the miRNA482 family, miRNA-215-3p and miRNA-29-3p, were found to increase kiwifruit’s sensitivity to PSA when overexpressed. These miRNAs were linked to the regulation of NBS-LRR target genes, shedding light on their role in kiwifruit’s defence against PSA. This study offers insights into the miRNA482-NBS-LRR network as a crucial component in enhancing kiwifruit bioresistance to PSA infestation and provides promising candidate genes for further research.

This manuscript introduces an improved Cuckoo Search (CS) algorithm, known as BASCS, designed to address the inherent limitations of CS, including insufficient search space coverage, premature convergence, low search accuracy, and slow search speed. The proposed improvements encompass four main areas: the integration of tent chaotic mapping and random migration in population initialization to reduce the impact of random errors, the guidance of Levy flight by the directional determination strategy of the Beetle Antennae Search (BAS) algorithm during the global search phase to improve search accuracy and convergence speed, the adoption of the Sine Cosine Algorithm for local exploitation in later iterations to enhance local optimization and accuracy, and the adaptive adjustment of the step-size factor and elimination probability throughout the iterative process to convergence. The performance of BASCS is validated through ablation experiments on 10 benchmark functions, comparative experiments with the original CS and its four variants, and application to a robot path planning problem. The results demonstrate that BASCS achieves higher convergence accuracy and exhibits faster convergence speed and superior practical applicability compared to other algorithms. [ABSTRACT FROM AUTHOR]

After hydraulic fracturing, unconventional reservoirs frequently encounter challenges related to limited effective proppant support distance and suboptimal proppant placement. Due to the strong heterogeneity of offshore reservoirs, which causes varying fracture roughnesses depending on different lithologies, a systematic study of the relationship between roughness and proppant transport could optimize operational parameters. This study incorporates the box dimension method for fractal dimension analysis to quantify roughness in auto-correlated Gaussian distributed surfaces created by true triaxial tests. Combined with the numerical analysis of (computational fluid dynamics) CFD-DEM (discrete element method) for bidirectional coupling, the laws of proppant deposition and transport processes within fractures with different roughnesses are obtained through comparative verification simulations. The results show that for rougher fractures of shale, the proppants are transported farther, but at JRC_52, (joint roughness coefficient), where there may be plugging in curved areas, there is a risk of near-well blockages. Compared to the smooth model, fluctuations in JRC_28 (tight sandstone) drastically increase turbulent kinetic energy within the fracture, altering particle transport dynamics. Moreover, smaller proppants (d/w ≤ 0.3) exhibit better transport capacity due to gravity, but the conductivity of the proppant is limited when the particles are too small. A d/w of 0.4 is recommended to guarantee transport capacity and proppant efficiency near the well. Additionally, proppants injected sequentially from small to large in shale fractures offer optimal propping effects, and can take advantage of the better transport capacity of smaller proppants in rough fractures. The large proppant (d/w = 0.8) is primarily deposited by gravity and forms a sloping sand bed, which subsequently ensures the aperture of the fractures. This research provides a fresh perspective on the influence of fracture roughness on proppant transport in offshore unconventional reservoirs and offers valuable considerations for the order of proppant injection. [ABSTRACT FROM AUTHOR]

Human pose estimation is an important task in computer vision, which can provide key point detection of human body and obtain bone information. At present, human pose estimation is mainly utilized for detection of large targets, and there is no solution for detection of small targets. This paper proposes a multi-channel spatial information feature based human pose (MCSF-Pose) estimation algorithm to address the issue of medium and small targets inaccurate detection of human key points in scenarios involving occlusion and multiple poses. The MCSF-Pose network is a bottom-up regression network. Firstly, an UP-Focus module is designed to expand the feature information while reducing parameter computation during the up-sampling process. Then, the channel segmentation strategy is adopted to cut the features, and the feature information of multiple dimensions is retained through different convolutional groups, which reduces the parameter lightweight network model and makes up for the loss of the feature information associated with the depth of the network. Finally, the three-layer PANet structure is designed to reduce the complexity of the model. With the aid of the structure, it also to improve the detection accuracy and anti-interference ability of human key points. The experimental results indicate that the proposed algorithm outperforms YOLO-Pose and other human pose estimation algorithms on COCO2017 and MPII human pose datasets. [ABSTRACT FROM AUTHOR]

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The navigation signals can be blocked, faded and interfered, when a satellite navigation receiver is carried by high dynamic vehicles and working in complex environments. Besides, the carrier Doppler measurements in the navigation receiver will rapidly change due to high dynamics. As a result, the algorithms of smoothing the pseudorange measurements with the carrier-phase measurements are no longer applicable. Furthermore, the conventional techniques of smoothing the pseudo-range measurements with the integral of carrier Doppler measurements, generally use a fixed window for calculating the initial value of pseudoranges, and then can cause a large error in the initial value if the measurements with significant biases or the outliers are involved in the fixed window. In addition, the error in the integral of carrier Doppler measurements is accumulated over the smoothing time. Therefore, an improved algorithm of smoothing the pseudo-range measurements with the integral of carrier Doppler measurements is proposed. By employing a sliding window to replace the fixed window for calculating the initial value of pseudoranges, more accurate initial values for smoothing can be estimated. And the changes in pseudorange are calculated based on the weighted accumulation of carrier Doppler measurements. In consideration of the ionospheric variations, accumulated error and other factors, the lengths of the sliding window and the consequent smoothing window are chosen. The experimental results in both the static positioning and the simulated flight navigation show that the positioning accuracy is improved. Moreover, the estimation error in the initial value of pseudoranges and the accumulated error in the integral of carrier Doppler measurements are efficiently reduced.

Water-induced mechanically adaptive rubber nanocomposites were prepared by mixing bacterial cellulose whiskers (BCWs) suspension with carboxylated acerlonitrilebutadiene rubber (XNBR) latex, followed by latex blending method. The introduction of BCWs into XNBR enhanced the tensile storage modulus (F) significantly, which originated from the formation of a rigid 3D filler network within matrix as well as the interfacial interaction between filler and matrix. The water uptake ratio of nanocomposite films increased with BCWs content, from 5.5% for neat XNBR to 54% for nanocomposite with 20 phr (parts per hundred rubber) BCWs. Upon submersed in water, the nanocomposite films showed dramatic decrease in E', especially for which filled with high BCWs loadings. For example, E of nanocomposite with 20 phr BCWs was decreased by 98.04% after equilibrium swelling compared with only 52.02% for nanocomposite with 3 phr BCWs. The remarkable watertriggered modulus changes are attributed to the disentanglement of BCWs network after swelling. The prepared XNBR-BCWs nanocomposites with mechanically adaptive properties could contribute to develop the new type of rubber-based smart materials. POLYM. ENG. SCI., 59:58-65, 2019., INTRODUCTION Functional polymer nanocomposites which associate desirable nanofiller with polymer matrix and possess a broad range of properties (e.g., mechanics, electricity, thermology, and impermeability) have been devoted into academia and [...]