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IntroductionGelidocalamus Wen is a small yet taxonomically challenging genus within the Arundinarieae tribe. Recent molecular studies have suggested it may not be monophyletic. However, limited species sampling and insufficient molecular marker information have resulted in poorly resolved phylogenetic relationships within this genus.MethodsThe complete chloroplast genomes covering all 16 species and one variant of Gelidocalamus were sequenced, and comparative analyses were conducted. Phylogenetic analyses were performed using different molecular markers, including chloroplast data, the nuclear ribosomal DNA (nrDNA) repeats region, and 29 mitochondrial protein-coding genes. Additionally, the divergence times of Gelidocalamus were estimated to reveal their evolutionary history.ResultsThe plastomes of Gelidocalamus ranged in size from 139,500 bp to 139,801 bp, with a total of 137 identified genes, including 90 protein-coding genes, 39 tRNA genes, and 8 rRNA genes. The size of the nrDNA repeats ranged from 5,802 bp to 5,804 bp. Phylogenetic analysis based on chloroplast data revealed that Gelidocalamus is polyphyletic, with different subclades distributed within the IV and V clades. However, phylogenetic analysis based on nrDNA and mitochondrial genes did not effectively resolve the relationships within the genus.DiscussionComparative analysis of chloroplast genomes indicated that Gelidocalamus shares a high degree of similarity with closely related genera in terms of chloroplast genome collinearity, codon usage bias, and repetitive sequences. Divergence time estimation suggests that it is a relatively young group, with all members appearing successively over the past four million years. The complex phylogenetic patterns may arise from the rapid radiation of Arundinarieae. This study provides a preliminary foundation for further in-depth research on the phylogeny, genomic structural features, and divergence times of this genus.

Water inrush disaster is one of the most severe problems during the construction of sea tunnels, primarily due to faults, karst, and weathered zones. Once a water inrush disaster occurs, it can lead to construction delays, traffic disruptions, and major economic losses, as well as potential consequences such as seawater intrusion, casualties, project suspension, and tunnel closure. Thus, advanced geological prediction is indispensable. During the construction of the Shantou Bay subsea tunnel, a sudden water inrush accident occurred in the sea–land transition section. To prevent such incidents and ensure safety, an integrated approach was employed. Firstly, the cross-hole resistivity method was used to predict water content in front of the tunnel, as it is highly sensitive to water. Subsequently, borehole ground-penetrating radar was applied to finely characterize the geological structure. By combining these two methods, the size, scale, location, water content, and spatial distribution of water-bearing structures in front of the tunnel were identified. With the above measures, the Shantou Bay subsea tunnel passed through the detection section successfully. Herein, we present a case study and offer a valuable reference for similar projects concerning subsea tunnel construction.

Background: Gastric cancer is one of the cancers with wide incidence, difficult treatment and high mortality in the world, especially in Asia and Africa. In our previous work, a novel o-aminobenzamide analogue F8 was identified as an early preclinical candidate for treatment of undifferentiated gastric cancer (IC50 of 0.26 μM for HGC-27). However, the poor water solubility of compound F8 prevents its further progress in preclinical studies.Aim: To improve the water solubility and drug-likeness of F8 via salt formation.Method: Different acids and F8 were reacted to obtain different salt forms. Physicochemical property screening, pharmacokinetic property research, and antitumor biological activity evaluation in vitro and in vivo were used to obtain the optimal salt form with the best druggability.Results: our continuous efforts have finally confirmed F8·2HCl as the optimal salt form with maintained in vitro antitumor activity, improved water solubility and pharmacokinetic properties. Importantly, the F8·2HCl displayed superior in vivo antitumor efficacy (TGI of 70.1% in 75 mg/kg) in HGC-27 xenograft model. The further immunohistochemical analysis revealed that F8·2HCl exerts an antitumor effect through the regulation of cell cycle-related protein (CDK2 and p21), apoptosis-related protein Cleaved Caspase-3, proliferation marker Ki67, and cell adhesion molecule E-cadherin. In addition, F8·2HCl showed acceptable safety in the in vivo acute toxicity assay.Conclusion: Salting is an effective means to improve the drug-like properties of compound F8, and F8·2HCl can serve as a promising therapeutic agent against undifferentiated gastric cancer.

Abstract Epstein Barr-virus (EBV) is related to several cancers. Long non-coding RNAs (lncRNAs) act by regulating target genes and are involved in tumourigenesis. However, the role of lncRNAs in EBV-associated cancers is rarely reported. Understanding the role and mechanism of lncRNAs in EBV-associated cancers may contribute to diagnosis, prognosis and clinical therapy in the future. EBV encodes not only miRNAs, but also BART lncRNAs during latency and the BHLF1 lncRNA during both the latent and lytic phases. These lncRNAs can be targeted regulate inflammation, invasion, and migration and thus tumourigenesis. The products of EBV also directly and indirectly regulate host lncRNAs, including LINC00312, NORAD CYTOR, SHNG8, SHNG5, MINCR, lncRNA-BC200, LINC00672, MALATI1, LINC00982, LINC02067, IGFBP7‐AS1, LOC100505716, LOC100128494, NAG7 and RP4-794H19.1, to facilitate tumourigenesis using different mechanisms. Additionally, lncRNAs have been previously validated to interact with microRNAs (miRNAs), and lncRNAs and miRNAs mutually suppress each other. The EBV-miR-BART6-3p/LOC553103/STMN1 axis inhibits EBV-associated tumour cell proliferation. Additionally, H. pylori–EBV co-infection promotes inflammatory lesions and results in EMT. HPV–EBV co-infection inhibits the transition from latency to lytic replication. KSHV–EBV co-infection aggravates tumourigenesis in huNSG mice. COVID-19–EBV co-infection may activate the immune system to destroy a tumour, although this situation is rare and the mechanism requires further confirmation. Hopefully, this information will shed some light on tumour therapy strategies tumourigenesis. Additionally, this strategy benefits for infected patients by preventing latency to lytic replication. Understanding the role and expression of lnRNAs in these two phases of EBV is critical to control the transition from latency to the lytic replication phase. This review presents differential expressed lncRNAs in EBV-associated cancers and provides resources to aid in developing superior strategies for clinical therapy.

Abstract Epstein-Barr virus (EBV) is closely associated with multiple human cancers. EBV-associated cancers are mainly lymphomas derived from B cells and T cells (Hodgkin lymphoma, Burkitt lymphoma, NK/T-cell lymphoma, and posttransplant lymphoproliferative disorder (PTLD)) and carcinomas derived from epithelial cells (nasopharyngeal carcinoma and gastric carcinoma). EBV can induce oncogenesis in its host cell by activating various signaling pathways, such as nuclear factor-κB (NF-κB), phosphoinositide-3-kinase/protein kinase B (PI3K/AKT), Janus kinase/signal transducer and transcription activator (JAK/STAT), mitogen-activated protein kinase (MAPK), transforming growth factor-β (TGF-β), and Wnt/β-catenin, which are regulated by EBV-encoded proteins and noncoding RNA. In this review, we focus on the oncogenic roles of EBV that are mediated through the aforementioned signaling pathways.

The development of CRISPR-based gene-editing technologies has brought an unprecedented revolution in the field of genome engineering. Cas12a, a member of the Class 2 Type V CRISPR-associated endonuclease family distinct from Cas9, has been repurposed and developed into versatile gene-editing tools with distinct PAM recognition sites and multiplexed gene targeting capability. However, with current CRISPR/Cas12a technologies, it remains a challenge to perform efficient and precise genome editing of long sequences in mammalian cells. To address this limitation, we utilized phage recombination enzymes and developed an efficient CRISPR/Cas12a tool for multiplexed precision editing in mammalian cells. Through protein engineering, we were able to recruit phage recombination proteins to Cas12a to enhance its homology-directed repair efficiencies. Our phage-recombination-assisted Cas12a system achieved up to 3-fold improvements for kilobase-scale knock-ins in human cells without compromising the specificity of the enzyme. The performance of this system compares favorably against Cas9 references, the commonly used enzyme for gene-editing tasks, with improved specificity. Additionally, we demonstrated multi-target editing with similar improved activities thanks to the RNA-processing activity of the Cas12a system. This compact, multi-target editing tool has the potential to assist in understanding multi-gene interactions. In particular, it paves the way for a gene therapy method for human diseases that complements existing tools and is suitable for polygenic disorders and diseases requiring long-sequence corrections.

Few studies deal with the application of crop growth models to fruit trees. This research focuses on simulating the growth process, yield and soil moisture assessment of pear trees, considering pruning with a modified WOrld FOod Studies (WOFOST) model. Field trials (eight pruning treatments) were conducted in pear orchards in Alaer and Awat in Xinjiang, China and data were measured to calibrate and evaluate the modified model. In two pear orchards, the simulated total dry weight of storage organs (TWSO) and leaf area index (LAI) were in good agreement with the field measurements of each pruning intensity treatment, indicating that the R2 values of TWSO ranged from 0.899 to 0.976, and the R2 values of LAI ranged from 0.849 to 0.924. The modified model also showed high accuracy, with a normalized root mean square error (NRMSE) ranging from 12.19% to 26.11% for TWSO, and the NRMSE values for LAI were less than 10%. The modified model also had a good simulation performance for the soil moisture (SM) under all eight pruning intensity treatments, showing good agreement (0.703 ≤ R2 ≤ 0.878) and low error (NRMSE ≤ 7.47%). The measured and simulated results of different pruning intensities showed that the highest yield of pear trees was achieved when the pruning intensity was about 20%, and the yield increased and then decreased with the increase in pruning intensity. In conclusion, the modified WOFOST model can better describe the effects of summer pruning on pear tree growth, yield and soil moisture than the unmodified model, providing a promising quantitative analysis method for the numerical simulation and soil moisture assessment of fruit tree growth.

Planting with non-film mulching is the fundamental means to eliminate the pollution of residual film in cotton fields. However, this planting approach should have regional adaptability. Therefore, the calibrated WOFOST model and an early mature cultivar CRI619 (Gossypium hirsutum Linn) were employed to simulate the cotton growth, and regions were then evaluated for planting in Xinjiang. A field experiment was conducted in 2019–2020 at the experimental irrigation station of Alar City, and the data were used to calibrate and validate the WOFOST model. The field validation results showed that the errors of the WOFOST simulation for emergence, flowering, and maturity were +1 day, +2 days, and +1 day, respectively, with good simulation accuracy of phenological development time. The simulated WLV, WST, WSO, and TAGP agreed well with measured values, with R2 = 0.96, 0.97, 0.99, and 0.99, respectively. The RMSE values of simulated versus measured WLV, WST, WSO, and TAGP were 175, 210, 199, and 251 kg ha−1, and showed high accuracy. The simulated soil moisture (SM) agreed with the measured value, with R2 = 0.87. The calibration model also showed high SM simulation accuracy, with RMSE = 0.022 (cm3 cm−3). Under all treatments, the simulated TAGP and yield agreed well with the measured results, with R2 of 0.76 and 0.70, respectively. RMSE of simulated TAGP and yield was 465 and 200 kg ha−1, and showed high accuracy. The percentage RMSE values (ratio of RMSE to the average measured value, NRMSE) of ETa and WUE were 9.8% and 11.7%, indicating extremely high precision (NRMSE < 10%) and high precision (10% < NRMSE ≤ 20%), respectively. The simulated results for phenology length at the regional scales showed that the effective accumulation temperature in counties such as Yingjisha and Luntai was not enough for the phenological maturity of the studied cotton cultivar. The southern area of Xinjiang had a generally higher yield than the northern area but required more irrigation. This research can provide a method for evaluating the adaptability of filmless cultivation techniques for cotton in different counties.

Accurate cotton maps are crucial for monitoring cotton growth and precision management. The paper proposed a county-scale cotton mapping method by using random forest (RF) feature selection algorithm and classifier based on selecting multi-features, including spectral, vegetation indices, and texture features. The contribution of texture features to cotton classification accuracy was also explored in addition to spectral features and vegetation index. In addition, the optimal classification time, feature importance, and the best classifier on the cotton extraction accuracy were evaluated. The results showed that the texture feature named the gray level co-occurrence matrix (GLCM) is effective for improving classification accuracy, ranking second in contribution among all studied spectral, VI, and texture features. Among the three classifiers, the RF showed higher accuracy and better stability than support vector machines (SVM) and artificial neural networks (ANN). The average overall accuracy (OA) of the classification combining multiple features was 93.36%, 7.33% higher than the average OA of the single-time spectrum, and 2.05% higher than the average OA of the multi-time spectrum. The classification accuracy after feature selection by RF can still reach 92.12%, showing high accuracy and efficiency. Combining multiple features and random forest methods may be a promising county-scale cotton classification method.

The toxicity of engineered nanoparticles remains a concern. The knowledge of biohazards associated with particular nanoparticles is crucial to make this cutting-edge technology more beneficial and safe. Here, we evaluated the toxicity of Ga2O3 nanoparticles (NPs), which are frequently used to enhance the performance of metal catalysts in a variety of catalytic reactions. The potential inflammatory signaling associated with the toxicity of HA/β-Ga2O3:Cr3+ NPs in primary cortical neurons was examined. We observed a dose-dependent decrease in cell viability and an increase in apoptosis in neurons following various concentrations (0, 1, 5, 25, 50, 100 µg/ml) of HA/β-Ga2O3:Cr3+ NPs treatment. Consistently, constitutively active forms of calcineurin (48 kDa) were significantly elevated in cultured primary cortical neurons, which was consistent with calpain activation indicated by the breakdown products of spectrin. Moreover, HA/β-Ga2O3:Cr3+ NPs result in the elevation of LC3-II formation, SQSTM/p62, and Cathepsin B, whereas phosphorylation of CaMKII (Thr286) and Synapsin I (Ser603) were downregulated in the same context. Taken together, these results demonstrate for the first time that calpain activation and a disturbance of autophagy signaling are evoked by exposure to HA/β-Ga2O3:Cr3+ NPs, which may contribute to neuronal injury in vitro.

miRNAs have been proposed to be key regulators of progression and metastasis in cancer. However, an understanding of their roles and molecular mechanisms is needed to provide deeper insights for better therapeutic opportunities. In this study we investigated the role and mechanism of miR-493 in the development and progression of nonsmall-cell lung cancer (NSCLC). Our data indicated that the expression of miR-493 was markedly reduced in pulmonary carcinoma. The ectopic expression of miR-493 impaired cell growth and invasion in vitro and in vivo. Mechanically, miR-493 commonly directly targeted E2F1, which resulted in a robust reduction of the expression of mRNA and protein. This effect, in turn, decreased the growth, invasion and metastasis of lung cancer cells. Our findings highlight the importance of miR-493 dysfunction in promoting tumor progression, and implicate miR-493 as a potential therapeutic target in lung cancer.