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Abstract Background Ferroptosis, a non-apoptotic form of regulated cell death, plays a critical role in the suppression of various tumor types, including ovarian cancer. Artesunate (ART), a derivative of artemisinin, exhibits extensive antitumor effects and is associated with ferroptosis. This study aimed to investigate the mechanisms through which ART induces ferroptosis to inhibit ovarian cancer. Methods RNA sequencing was conducted to identify differentially expressed genes associated with ART-induced ferroptosis. Dual-luciferase reporter assays and electrophoretic mobility shift assays were performed to confirm the interaction between Homeobox C11 (HOXC11) and the Prominin 2 (PROM2) promoter. Cell Counting Kit-8 (CCK-8) assays, flow cytometry, and wound healing assays were used to analyze the antitumor effects of ART. Western blot, biochemical assays and transmission electron microscope were utilized to further characterize ART-induced ferroptosis. In vivo, the effects of ART on ferroptosis were examined using a xenograft mouse model. Results RNA sequencing analysis revealed that the HOXC11, PROM2 and Phosphatidylinositol 3-Kinase/ Protein Kinase B (PI3K/AKT) pathways were downregulated by ART. HOXC11 was found to regulate PROM2 expression by binding to its promoter directly. HOXC11 overexpression reversed ART-induced effects on ovarian cancer cell proliferation, migration, apoptosis and ferroptosis by activating the PROM2/PI3K/AKT signaling axis. Conversely, silencing PROM2 in HOXC11-overexpressing cells restored ART-induced ferroptosis and its associated antitumor effects by inhibiting the PI3K/AKT pathway. Consistently, in vivo studies using a xenograft mouse model confirmed that ART-induced tumor inhibition was mediated by ferroptosis through the suppression of the HOXC11/PROM2/PI3K/AKT pathway. Conclusion This study identifies the HOXC11/PROM2/PI3K/AKT axis as a novel regulatory mechanism underlying ART-induced ferroptosis in ovarian cancer. Targeting the HOXC11/PROM2 axis may represent a promising therapeutic strategy for enhancing ferroptosis, offering new insights for the treatment of ovarian cancer.

Skeletal muscle disorders have posed great threats to health. Selective delivery of drugs and oligonucleotides to skeletal muscle is challenging. Aptamers can improve targeting efficacy. In this study, for the first time, the human skeletal muscle-specific ssDNA aptamers (HSM01, etc.) were selected and identified with Systematic Evolution of Ligands by Exponential Enrichment (SELEX). The HSM01 ssDNA aptamer preferentially interacted with human skeletal muscle cells in vitro. The in vivo study using tree shrews showed that the HSM01 ssDNA aptamer specifically targeted human skeletal muscle cells. Furthermore, the ability of HSM01 ssDNA aptamer to target skeletal muscle cells was not affected by the formation of a disulfide bond with nanoliposomes in vitro or in vivo, suggesting a potential new approach for targeted drug delivery to skeletal muscles via liposomes. Therefore, this newly identified ssDNA aptamer and nanoliposome modification could be used for the treatment of human skeletal muscle diseases.

Structure from Motion (SfM) is a series of methods for reconstructing scene structure (i.e.three-dimensional space points) and camera motion (i.e.camera pose) from an image set. In this paper, aimed at the low accuracy of the global reconstruction, the robustness to external points and the time-consuming incremental reconstruction, a fast, closed-loop and high precision reconstruction method is proposed. The method is based on the SIFT matching algorithm GeoMatch, which is constrained by geometric structure of the scene and by numerical and statistical characteristics of feature invariant scale transformation. Experiments show that GeoMatch outperforms both traditional tree-based and hash-based matching methods in terms of time and accuracy.

In this paper, we integrate the advantages of convolutional neural network (CNN) and bidirectional recurrent neural network (BiRNN) with attention mechanism, and propose a CNN-BiRNN based method to recognize the individual high resolution range profile (HRRP). In the proposed method, the CNN is utilized to explore the spatial correlation of raw HRRP data and extract expressive features followed by a BiRNN taking the full consideration of temporal dependence between range cells. Furthermore, in order to enhance the robustness to misalignment, an attentional mechanism is employed after BiRNN to allow the CNN-BiRNN model to focus on the discriminative target area. The combination of CNN and BiRNN with attention mechanism makes the extracted features are not only efficient, but also strongly resistant to the time-shift sensitivity. Experimental results on measured HRRP data demonstrate the effectiveness and the robustness to misalignment of the proposed method.

Microplastics (MPs), a kind of novel contaminant, have potential to concentrate and transport heavy metals in the aquatic environment. This feature may affect the distribution and bioavailability of heavy metals. In order to determine the sorption behaviors of heavy metals onto the MPs, the sorption kinetics and mechanisms were investigated between the MPs (polyvinylchloride PVC, polyethylene PE, polystyrene PS) and Pb(II). The results suggested that the Pb(II) sorption onto the MPs were pH- and ionic strength-dependent. The sorption processes were best fitted by the pseudo-second-order model, and the rate-limiting steps were the intraparticle diffusion and final equilibrium process. The maximum sorption capacities of PVC, PE and PS were 483.1 μg/g, 416.7 μg/g and 128.5 μg/g under the condition of 0.01 M NaCl, pH 6.0, T = 298 K. The sorption rate constants were in the following order: PVC

A long-range surface plasmon polariton (SPP) waveguide, composed of double-layer graphene, can be pivotal in transferring and handling mid-infrared electromagnetic waves. However, one of the key challenges for this type of waveguide is how to excite the SPP modes through an incident light beam. In this study, our proposed design of a novel grating, consisting of a graphene-based cylindrical long-range SPP waveguide array, successfully addresses this issue using finite-difference time-domain simulations. The results show that two types of symmetric coupling modes (SCMs) are excited through a normal incident light. The transmission characteristics of the two SCMs can be manipulated by changing the interaction of the double-layer gratings of graphene as well as by varying various parameters of the device. Similarly, four SCMs can be excited and controlled by an oblique incident light because this light source is equivalent to two orthogonal beams of light. Furthermore, this grating can be utilized in the fabrication of mid-infrared optical devices, such as filters and refractive index sensors. This grating, with double-layer graphene arrays, has the potential to excite and manipulate the mid-infrared electromagnetic waves in future photonic integrated circuits.

Abstract In order to reveal the role of phytoplankton in the spatio-temporal distribution of alkaline phosphatase activity (APA), monthly investigations were conducted in the Xiaojiang River, a tributary of the Three Gorges Reservoir in China. Different APA fractions, environmental parameters, and phytoplankton communities were followed. High spatio-temporal variations of APA were observed, with the highest value in summer and the lowest in winter. The annual average APAT (total alkaline phosphatase activity) ranged from 7.78–14.03 nmol∙L−1∙min−1 with the highest in the midstream and the lowest in the estuary. The dominant phytoplankton phyla in summer and winter were Cyanophyta and Bacillariophyta, respectively. The mean cell density in the midstream and in the estuary was 5.2 × 107 cell∙L−1 and 1.4 × 107 cell∙L−1, respectively. That APA>3.0 μm was significantly higher than APA0.45-3 μm indicating phytoplankton was the main contributor to alkaline phosphatase. Correlation analysis indicated the dominant species and cell density could determine the distribution pattern of APA. Turbidity, total phosphorus, chemical oxygen demand, water temperature (WT), pH and chlorophyll a were proved to be positively correlated with APA; soluble reactive phosphorus, conductivity, transparency and water level(WL) were negatively correlated with APA. It was concluded that spatio-temporal heterogeneity of APA determined by phytoplankton communities was related to WT and WL.

Low molecular weight metabolites are important plant hormones and signaling molecules, and play an important part among the processes of plant development. Their activities may also be affected by the chemical modifications of methylation performed by SABATH. In this study, a total of 24 and 21 SABATH genes in Arabidopsis and rice, respectively, were identified and taken a comprehensive study. Phylogenetic analysis showed that AtSABATH and OsSABATH genes could be classified into 4 major groups and 6 subgroups. Gene expansion analysis showed that the main expansion mechanism of SABATH gene family in Arabidopsis and rice was tandem duplication and segmental duplication. The ratios of nonsynonymous (Ka) and synonymous (Ks) substitution rates of 12 pairs paralogous of AtSABATH and OsSABATH genes indicated that the SABATH gene family in Arabidopsis and rice had gone through purifying selection. Positive selection analysis with site models and branch-site models revealed that AtSABATH and OsSABATH genes had undergone selective pressure for adaptive evolution. Motif analysis showed that certain motifs only existed in specific subgroups or species, which indicated that the SABATH proteins of Arabidopsis and rice appear divergence in different species and subgroups. Functional divergence analysis also suggested that the AtSABATH and OsSABATH subgroup genes had functional differences, and the positive selection sites which contributed to functional divergence among subgroups were detected. These results provide insights into functional conservation and diversification of SABATH gene family, and are useful information for further elucidating SABATH gene family functions.

Descriptors play an important role in point cloud registration. The current state-of-the-art resorts to the high regression capability of deep learning. However, recent deep learning-based descriptors require different levels of annotation and selection of patches, which make the model hard to migrate to new scenarios. In this work, we learn local registration descriptors for point clouds in a self-supervised manner. In each iteration of the training, the input of the network is merely one unlabeled point cloud. Thus, the whole training requires no manual annotation and manual selection of patches. In addition, we propose to involve keypoint sampling into the pipeline, which further improves the performance of our model. Our experiments demonstrate the capability of our self-supervised local descriptor to achieve even better performance than the supervised model, while being easier to train and requiring no data labeling.

WRI1 is a plant-specific transcription factor that enhances the accumulation of oils through the upregulation of the expression of genes involved in glycolysis and fatty acid biosynthesis. In this study, the EgWRI1 promoter from oil palm was isolated and characterized in transgenic Arabidopsis. The sequence analysis results revealed that various putative plant regulatory elements are present in the EgWRI1 promoter region. The EgWRI1 promoter and beta-glucuronidase (GUS) reporter gene were transcriptionally fused and transformed into Arabidopsis thaliana. Histochemical analysis revealed that GUS staining was very strong in whole seedlings, especially the stems, leaves, and siliques. Moreover, GUS staining was strong in the silique coats but weak in the seeds. Furthermore, to detect whether EgWRI1 was induced by environmental stress, we detected the expression efficiency of the EgWRI1 promoter in transgenic Arabidopsis treated with low temperature, darkness, and exogenous ethylene. The results showed that the activity of the EgWRI1 promoter was induced by darkness but suppressed significantly when exposed to exogenous ethylene. When treated with low temperature, the activity of the EgWRI1 promoter was first reduced after 24 hours but recovered after 48 hours. Taken together, these results reveal the features of the EgWRI1 promoter from oil palm, which will be helpful for improving oil accumulation in oil palm via reasonable cultivation methods.

In higher plants, ω-3 fatty acid desaturases are the key enzymes in the biosynthesis of alpha-linolenic acid (18:3), which plays key roles in plant metabolism as a structural component of both storage and membrane lipids. Here, the first ω-3 fatty acid desaturase gene was identified and characterized from oil palm. The bioinformatic analysis indicated it encodes a temperature-sensitive chloroplast ω-3 fatty acid desaturase, designated as EgFAD8. The expression analysis revealed that EgFAD8 is highly expressed in the oil palm leaves, when compared with the expression in the mesocarp. The heterologous expression of EgFAD8 in yeast resulted in the production of a novel fatty acid 18:3 (about 0.27%), when fed with 18:2 in the induction culture. Furthermore, to detect whether EgFAD8 could be induced by the environment stress, we detected the expression efficiency of the EgFAD8 promoter in transgenic Arabidopsis treated with low temperature and darkness, respectively. The results indicated that the promoter of EgFAD8 gene could be significantly induced by low temperature and slightly induced by darkness. These results reveal the function of EgFAD8 and the feature of its promoter from oil palm fruits, which will be useful for understanding the fuction and regulation of plastidial ω-3 fatty acid desaturases in higher plants.

Oil palm (Elaeis guineensis Jacq.) is the highest oil-yielding plant in the world, storing 90 and 60% (dry weight) oil in its mesocarp and kernel, respectively. To gain insights into the oil accumulation mechanism, one of the key enzymes involved in triacylglycerol (TAG) biosynthesis, a Type 2 diacylglycerol acyltransferase (DGAT2) from oil palm, was characterized for its in vivo activity. EgDGAT2 is highly expressed in mesocarp during the last two developmental stages while large amounts of oil are accumulated at the highest rate during ripening. Heterologous expression of EgDGAT2 in mutant yeast H1246 restored TAG biosynthesis with substrate preference toward unsaturated fatty acids (FAs) (16:1 and 18:1). Furthermore, seed-specific overexpression of EgDGAT2 in Arabidopsis thaliana enhanced the content of polyunsaturated FAs 18:2 and 18:3 (each by 6 mol%) in seed TAGs, when compared to that from wild-type Arabidopsis. In turn, the proportion of 18:0 and 20:0 FAs in seed TAGs from EgDGAT2 transgenic lines decreased accordingly. These results provide new insights into understanding the in vivo activity of EgDGAT2 from oil palm mesocarp, which will be of importance for metabolic enhancement of unsaturated FAs production.

Pericallis hybrida is a very prevalent decorative plant worldwide. Here, we report the assembly of the complete nucleotide sequence of the P. hybrida chloroplast genome using the program MITObim v1.7 after whole genome shotgun sequencing. The complete chloroplast genome of P. hybrida (GenBank accession number: KT285537) consists of 151,267 bp and includes a pair of inverted repeats (IR) of 23,595 bp separated by one small and one large single copy region (SSC and LSC) of 18,330 bp and 85,747 bp, respectively. The genome has a 37.3% GC content and contains 132 genes coding for 87 proteins. Phylogenetic analyses using complete chloroplast genome revealed that P. hybrida belongs to the Senecioneae of Asteraceae family, which is conformed to the traditional classification.