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The decline of endothelial autophagy is closely related to vascular senescence and disease, although the molecular mechanisms connecting these outcomes in vascular endothelial cells (VECs) remain unclear. Here, we identify a crucial role for CD44, a multifunctional adhesion molecule, in controlling autophagy and ageing in VECs. The CD44 intercellular domain (CD44ICD) negatively regulates autophagy by reducing PIK3R4 and PIK3C3 levels and disrupting STAT3-dependent PtdIns3K complexes. CD44 and its homologue clec-31 are increased in ageing vascular endothelium and Caenorhabditis elegans , respectively, suggesting that an age-dependent increase in CD44 induces autophagy decline and ageing phenotypes. Accordingly, CD44 knockdown ameliorates age-associated phenotypes in VECs. The endothelium-specific CD44ICD knock-in mouse is shorter-lived, with VECs exhibiting obvious premature ageing characteristics associated with decreased basal autophagy. Autophagy activation suppresses the premature ageing of human and mouse VECs overexpressing CD44ICD, function conserved in the CD44 homologue clec-31 in C. elegans . Our work describes a mechanism coordinated by CD44 function bridging autophagy decline and ageing. Mechanisms underlying the connection between autophagy decline and vascular endothelial cell (VEC) ageing remain unclear. Here, the authors identify a key role for CD44 in controlling autophagy and ageing in VECs, and this function is conserved in nematodes.

The chloroplast genomes of wild loquat can help to determine their place in the history of evolution. Here, we sequenced and assembled two novel wild loquat’s chloroplast genomes, one is Eriobotrya elliptica , and the other is an unidentified wild loquat, which we named “YN-1”. Their sizes are 159,471 bp and 159,399 bp, respectively. We also assembled a cultivated loquat named ‘JFZ’, its chloroplast genome size is 159,156 bp. A comparative study was conducted with six distinct species of loquats, including five wild loquats and one cultivated loquat. The results showed that both E. elliptica and “YN-1” have 127 genes, one gene more than E. fragrans, which is psbK . Regions trnF-GAA - ndhJ, petG - trnP-UGG , and rpl32 - trnL-UAG were found to exhibit high variability. It was discovered that there was a positive selection on rpl22 and rps12 . RNA editing analysis found several chilling stress-specific RNA editing sites, especially in rpl2 gene. Phylogenetic analysis results showed that “YN-1” is closely related to E. elliptica , E. obovata and E. henryi .

In situ heat injection is a suitable technique for extracting shale oil from reservoirs with high organic matter content but insufficient thermal maturation. To optimize the stimulation process and to avoid unnecessary energy consumption, understanding the thermal process and the effects of thermal parameters is crucial. This research employs a self-developed simulator to build a 2D numerical model of the in situ conversion process of kerogen with electric heaters. A benchmark model is first established to determine the effects of heat injection on crude oil production and kerogen decomposition. Subsequently, this study analyzes the evolution of shale oil within the reservoir, identifying the role of thermal and physical properties in crude oil production and kerogen decomposition during the stimulation treatment. A sensitivity analysis of the thermal properties of the reservoir is also carried out, which allows for defining the role of the thermal conductivity of the rock during the stimulation process. Finally, it is observed that, when using the injection at a constant power, the injection time to achieve a suitable large rate of decomposition is shorter than at a constant temperature—consequently, it has a higher economic advantage.

China’s landslide disasters are serious, and regional landslide disaster early-warning is one of the important means of disaster prevention and mitigation. The traditional regional landslide disaster early-warning model, however, is limited by the complex landslide induction mechanism, limited data accumulation, and insufficient big data analysis methods, and has problems such as limited early-warning accuracy and insufficient refinement. In this paper, a machine learning method was introduced into the field of regional landslide disaster warning. From the model construction process of training sample-set construction, sample learning and training, model parameter optimization, model preservation, warning output, and so on, a method for constructing a regional landslide early-warning model based on machine learning was systematically proposed. In the sample learning and training, 80% of the training sample-set was used as the training set, and 20% was used as the test set for five-fold cross validation. The Bayesian Optimization algorithm was used to optimize the model parameters, and the accuracy, ROC curve, and AUC value were used to verify the model accuracy and model generalization ability. With China’s Fujian province as an example, based on nine years of geological and meteorological data (2010–2018), geological environment factors, factors of hazard-affected bodies and historical disaster situations, and rainfall-induced factors in four categories, a total of 26 indicators were used as input characteristic parameters. Six machine learning algorithms were adopted to improve model training; the results showed that the Random Forest algorithm performed the best, giving an accuracy of 92.3%, and was the model with the best generalization ability (AUC was 0.955). The second best was the Artificial Neural Network model, with an accuracy of 0.937 and an AUC of 0.935. Next were the Nearest Neighbor model, the Logistic Regression model, and the Support Vector Machine; the poorest results were from the Decision Tree model. Finally, the typical rainfall-type landslide disaster process in Fujian Province was selected as an example to verify the Random Forest algorithm model. The results showed that compared with the early-warning results of the original explicit statistical model, the hit rate of the new model was 6 times, or equal to that of the original model, and the landslide density in the early-warning area of the new model was 1.6–1.7 times that of the original model. Preliminary verification showed that the new model based on the Random Forest method has obvious advantages, a higher hit rate and a smaller warning area, and can achieve more accurate warnings. The follow-up will continue to track the new landslide disaster situation in the study area and carry out model verification and correction.

Tar content in gasification products is a serious problem for fuel gas utilization in downstream applications. Catalytic steam reforming of tar to syngas is a promising way for the removal of tar from the gas products. Nickel-based catalysts, dolomite, and olivine have been widely investigated for tar cracking and reforming by various researchers. This paper presents a review of biomass gasification, tar composition, and its elimination process by using the above three catalysts. This paper summarizes the knowledge in the published literature associated with tar elimination during the biomass gasification including discussion on the effects of different support, promoter on the catalytic performance. The aim of this paper is to collect information on the performance of above catalysts to make them accessible to readers within one paper. Comparative studies on these catalysts carried out by some researchers have also been presented here which show that the nickel-based catalyst is much more active than dolomite and olivine, but they are more expensive and can be also deactivated. Compared to olivine, the dolomite shows better catalytic performance with much higher gas yield and H2. Calcination of these catalysts improves the catalytic activities but the amount of coke deposited on the surface of the dolomite is reported higher than that of the olivine, which may be resulted from the different Fe amount of the catalyst.

Farmland boundary data, an important basic data for the operation of agricultural automation equipment, has been widely studied by scholars from all over the world. However, the common methods of farmland boundary acquisition through sensors such as LiDAR and vision cameras combined with complex algorithms suffer from problems such as serious data drift, difficulty in eliminating noise, and inaccurate plot boundary data. In order to solve this problem, this study proposes a method for estimating the orientation dimensions of farmland based on the seeding trajectory. The method firstly calculates the curvature of the discrete data of the seeding trajectory; secondly, we innovatively use a low-pass filter and integral clustering to filter the curvature values and distinguish between straight lines and curves; and finally, the straight-line portion located at the edge of the seeding trajectory is fitted with a univariate linear fit to calculate the estimation of the farmland size orientation. As verified by the field experiments, the minimum linear error of the vertices is only 0.12m, the average error is 0.315m, and the overlapping rate of the plot estimation is 98.36% compared with the real boundary of the plot. Compared with LiDAR mapping, the average linear error of the vertices’ position is reduced by 50.2%, and the plot estimation overlap rate is increased by 2.21%. The experimental results show that this method has the advantage of high accuracy, fast calculation speed, and small calculation volume, which provides a simple and accurate method for constructing farmland maps, provides the digital data support for the operation of agricultural automation equipment, and has significance for farm digital mapping.

Oil shale, as a vast potential resource, is considered an important alternative energy source, and its effective development and economic utilization are of significant importance in alleviating the contradiction between energy supply and demand. Presently, the in situ conversion technology for oil shale has gained significant global attention, with numerous extraction methods undergoing active research and development. One of these methods is the in situ conversion of oil shale based on the hydration reaction of calcium-oxide-based composite material (CaO-CM). This approach harnesses the heat produced by the reaction between CaO-CM and water as a heat source for the pyrolysis of oil shale. This paper conducted experiments to assess the feasibility of temperature associated with this method. The feasibility study mainly includes two aspects: First, it is necessary to investigate whether the temperature generated by the hydration reaction of CaO-CM can meet the temperature requirements for the pyrolysis of oil shale. Through pyrolysis experiments of Xinjiang oil shale, the minimum temperature required for oil shale pyrolysis was determined to be 330 °C. High-temperature and high-pressure reaction vessels were employed to explore the temperature generated by the hydration reaction of CaO-CM. The results show that with the increase in environment pressure, environment temperature, and reaction mass, the maximum temperature generated by the hydration reaction of CaO-CM also increases (reach 455.5 °C), meeting the temperature requirements for the pyrolysis of oil shale. Second, the study evaluates whether the hydration reaction of CaO-CM can induce pyrolysis hydrocarbons of the oil shale. Through the pyrolysis experiments of oil shale based on the hydration reaction of CaO-CM, the changes in the content of pyrolysis hydrocarbons (S2) in oil shale before and after pyrolysis are measured. The results show that under 10 MPa pressure, the content of pyrolysis hydrocarbons in the oil shale decreased from 40.96 mg/g to 0.08 mg/g after pyrolysis. This confirms the feasibility of the temperature conditions for the in situ conversion of oil shale based on the hydration reaction of CaO-CM.

Porcine epidemic diarrhea virus (PEDV) mainly infects the intestinal epithelial cells of pigs, causing porcine epidemic diarrhea (PED). In particular, the virus causes severe diarrhea, dehydration, and death in neonatal piglets. Maternal immunity effectively protects neonatal piglets from PEDV infection; however, maternal antibodies can only prevent PEDV attachment and entry into target cells, but have no effects on intracellular viruses. Intracellular antibodies targeting virus-encoded proteins are effective in preventing viral infection. We previously identified four single chain variable fragments (scFvs), ZW1-16, ZW3-21, ZW1-41, and ZW4-16, which specifically targeted the PEDV N protein and significantly inhibited PEDV replication and up-regulated interferon-λ1 (IFN-λ1) expression in host cells. In our current study, the four scFvs were subcloned into replication-defective adenovirus vectors to generate recombinant adenoviruses rAdV-ZW1-16, rAdV-ZW3-21, rAdV-ZW1-41, and rAdV-ZW4-16. ScFvs were successfully expressed in Human Embryonic Kidney 293 (HEK293) cells and intestinal porcine epithelial cell line J2 (IPEC-J2) and were biosafe for piglets as indicated by body temperature and weight, scFv excretion in feces, IFN-γ and interleukin-4 (IL-4) expression in jejunum, and pathological changes in porcine tissue after oral administration. Western blotting, immunofluorescence, and immunohistochemical analyses showed that scFvs were expressed in porcine jejunum. The prophylactic effects of rAdV-ZW, a cocktail of the four rAdV-scFvs, on piglet diarrhea caused by PEDV was investigated. Clinical symptoms in piglets orally challenged with PEDV, following a two-time treatment with rAdV-ZW, were significantly reduced when compared with PEDV-infected piglets treated with phosphate buffered saline (PBS) or rAdV-wild-type. Also, no death and jejunal lesions were observed. ScFv co-localization with the PEDV N protein in vivo was also observed. Next, the expression of pro-inflammatory serum cytokines such as tumor necrosis factor-α (TNF-α), IL-6, IL-8, IL-12, and IFN-λ was assessed by enzyme-linked immunosorbent assay (ELISA), which showed that scFvs significantly suppressed PEDV-induced pro-inflammatory cytokine expression and restored PEDV-inhibited IFN-λ expression. Therefore, our study supported a promising role for intracellular scFvs targeting the PEDV N protein to prevent and treat diarrhea in PEDV-infected piglets.

Zircon U-Pb geochronology, Hf isotope and whole-rock geochemistry were performed on the tuffs of the Yeba Formation in the Gangdese magmatic belt, South Tibet. The results are used to detail the age, source nature and tectonic processes that led to the formation of the Gangdese belt. Dating results indicate that the rhyolitic-andesitic tuffs were formed at 174–170 Ma. Positive and variable zircon ε_（Hf）（t） values of the rhyolitic tuffs reveal that the source was dominated by juvenile material, however, experienced crustal contamination. The basaltic tuffs have low HREEs, high contents of compatible elements（V and Cr） and no Eu anomaly. In contrast, the rhyolitic-andesitic tuffs show low compatible trace elements, depletion in Eu but enrichment in incompatible elements（Rb, Zr and Hf）. According to the discrimination diagrams of P_2O_5-SiO_2 and Th-Rb, the rhyolitic-andesitic tuffs show a close affinity to Ⅰ-type granitoids. Moreover, these tuffs are marked by significant depletion in Nb, Ta and Ti, plotted in calc-alkaline field, and with the andesitic-rhyolitic tuffs falling into an active continental margin setting. We suggest that these tuffs of the Yeba Formation were probably generated in an active continental margin above the northward subduction of the Neo-Tethyan oceanic lithosphere.

Some members of the Rosaceae family, particularly pear, contain stone cells in their fruits. Although stone cells in pear fruits are well studied, relatively little attention has been given to loquat stone cells. Only a few reports have suggested a relationship between stone cell traits and storage and transport tolerance of loquat fruits. Previously, we generated the variety JT8 from the interspecific hybrid of the loquat cultivar Jiefangzhong (JFZ; Eriobotrya japonica Lindl. cv. Jiefangzhong, female parent) and wild Taiwanese loquat (TL; E. deflexa Nakai, male parent). The JT8 fruits had a granular feel, similar to that of pear fruits, due to the presence of stone cells. In this study, the shape, size, development, and distribution dynamics of stone cells of Eriobotrya plants were thoroughly investigated. The results showed that loquat stone cells are brachysclereids and often contain typical branching pits. Loquat stone cells were distributed as both single stone cells and in stone cell clusters (SCCs), and the density of the stone cells near the core was higher than that near the peel. Stone cell density first increased and then decreased during fruit development. These traits noted in Eriobotrya were very similar to those observed in pear, indicating a close relationship between loquat and pear. Moreover, the contents, density dynamics, and aggregation traits of stone cells of the interspecific hybrid JT8 were derived from the male parent (TL). Transgressive segregation was likely exhibited in the content of stone cells and the size of the SCCs. More specifically, the content of stone cells reached 1.61% (w/w). In extreme cases, SCCs of JT8 exceeded 1,000 μm in length and 500 μm in width. This demonstrated that stone cell traits could be transmitted from parent to progeny through interspecific hybridization. The density dynamics of stone cells in two loquat cultivars with different storage and transport tolerances were also investigated, which indicated that the cultivar with more stone cells was more tolerant to storage and transport. We suggest that wild loquat genetic resources containing stone cells in Eriobotrya plants can be used to gradually improve the storage and transport tolerance of loquat fruits.