Multi-authority ABS supporting dendritic access structure

National Natural Science Foundation of Chin

Unlocking drought-induced tree mortality : physiological mechanisms to modeling

Drought-related tree mortality has become a major concern worldwide due to its pronounced negative impacts on the functioning and sustainability of forest ecosystems. However, our ability to identify the species that are most vulnerable to drought, and to pinpoint the spatial and temporal patterns of mortality events, is still limited. Model is useful tools to capture the dynamics of vegetation at spatiotemporal scales, yet contemporary land surface models (LSMs) are often incapable of predicting the response of vegetation to environmental perturbations with sufficient accuracy, especially under stressful conditions such as drought. Significant progress has been made regarding the physiological mechanisms underpinning plant drought response in the past decade, and plant hydraulic dysfunction has emerged as a key determinant for tree death due to water shortage. The identification of pivotal physiological events and relevant plant traits may facilitate forecasting tree mortality through a mechanistic approach, with improved precision. In this review, we (1) summarize current understanding of physiological mechanisms leading to tree death, (2) describe the functionality of key hydraulic traits that are involved in the process of hydraulic dysfunction, and (3) outline their roles in improving the representation of hydraulic function in LSMs. We urge potential future research on detailed hydraulic processes under drought, pinpointing corresponding functional traits, as well as understanding traits variation across and within species, for a better representation of drought-induced tree mortality in models

Optimizing DUS testing for Chimonanthus praecox using feature selection based on a genetic algorithm

Chimonanthus praecox is a famous traditional flower in China with high ornamental value. It has numerous varieties, yet its classification is highly disorganized. The distinctness, uniformity, and stability (DUS) test enables the classification and nomenclature of various species; thus, it can be used to classify the Chimonanthus varieties. In this study, flower traits were quantified using an automatic system based on pattern recognition instead of traditional manual measurement to improve the efficiency of DUS testing. A total of 42 features were quantified, including 28 features in the DUS guidelines and 14 new features proposed in this study. Eight algorithms were used to classify wintersweet, and the random forest (RF) algorithm performed the best when all features were used. The classification accuracy of the outer perianth was the highest when the features of the different parts were used for classification. A genetic algorithm was used as the feature selection algorithm to select a set of 22 reduced core features and improve the accuracy and efficiency of the classification. Using the core feature set, the classification accuracy of the RF model improved to 99.13%. Finally, K-means was used to construct a pedigree cluster tree of 23 varieties of wintersweet; evidently, wintersweet was clustered into a single class, which can be the basis for further study of genetic relationships among varieties. This study provides a novel method for DUS detection, variety identification, and pedigree analysis

Picturing Electron Capture to the Continuum in the Transfer Ionization of Intermediate-Energy He²⁺ Collisions with Argon

Electron emission occurring in transfer ionization for He2+ collisions with argon has been investigated using cold target recoil ion momentum spectroscopy. The double differential cross sections for electron capture to the continuum of the projectile (cusp-shaped electrons) are presented for collision energies from 17.5 to 75 keV/u. For an energy of 30 keV/u, we find a maximum in the experimental ratio of the cusp-shaped electron yield to the total electron yield. This result is explained in terms of the velocity matching between the projectile ion and the electron initially bound to the target. One of the important issues for double electron transitions is the role of electron-electron correlation. If this correlation is weak, then the transfer-ionization process can be viewed as two separate sequential processes. If this correlation is strong, then the transfer-ionization process would happen simultaneously and not sequentially. Our experimental and theoretical results indicate that correlation is weak and that the first step is target ionization followed by charge capture

Genome-wide identification of resistance genes and response mechanism analysis of key gene knockout strain to catechol in Saccharomyces cerevisiae

Engineering Saccharomyces cerevisiae for biodegradation and transformation of industrial toxic substances such as catechol (CA) has received widespread attention, but the low tolerance of S. cerevisiae to CA has limited its development. The exploration and modification of genes or pathways related to CA tolerance in S. cerevisiae is an effective way to further improve the utilization efficiency of CA. This study identified 36 genes associated with CA tolerance in S. cerevisiae through genome-wide identification and bioinformatics analysis and the ERG6 knockout strain (ERG6Δ) is the most sensitive to CA. Based on the omics analysis of ERG6Δ under CA stress, it was found that ERG6 knockout affects pathways such as intrinsic component of membrane and pentose phosphate pathway. In addition, the study revealed that 29 genes related to the cell wall-membrane system were up-regulated by more than twice, NADPH and NADP+ were increased by 2.48 and 4.41 times respectively, and spermidine and spermine were increased by 2.85 and 2.14 times, respectively, in ERG6Δ. Overall, the response of cell wall-membrane system, the accumulation of spermidine and NADPH, as well as the increased levels of metabolites in pentose phosphate pathway are important findings in improving the CA resistance. This study provides a theoretical basis for improving the tolerance of strains to CA and reducing the damage caused by CA to the ecological environment and human health

Cyclin‐dependent kinase subunit2 (CKS2) promotes malignant phenotypes and epithelial‐mesenchymal transition‐like process in glioma by activating TGFβ/SMAD signaling

Abstract Background Gliomas are a group of primary intracranial tumors with high morbidity and mortality. The previous researches indicated a crucial role of CKS2 (cyclin‐dependent kinases regulatory subunit 2) in hepatocellular carcinoma and breast cancer; however, little is known about the molecular mechanism of CKS2 in the tumorigenesis and epithelial‐mesenchymal transition‐like (EMT) process in glioma. Methods Datasets for bioinformatics analysis were obtained from the GEO, TCGA and CGGA databases. qRT‐PCR, western blotting (WB), and immunohistochemistry (IHC) assays were used to investigate the expression patterns of CKS2 among glioma and brain tissues. Glioma cells were transfected with small interfering RNA/overexpression plasmid against CKS2, then clone formation assay, CCK‐8, wound healing, Transwell assay, and flow cytometry were performed to detect changes in cell viability, invasiveness, and the apoptosis rate. Markers of cell invasion, apoptosis, EMT and TGFβ/SMAD signaling were evaluated by WB and immunofluorescence (IF) assays. Results We found that CKS2 overexpression correlates with poor prognosis in human glioma and knockdown of CKS2 could inhibit cell proliferation, migration, invasion, and induced apoptosis in glioma cells. Besides, we also found that knockdown of CKS2 could reverse the EMT process via modulating EMT‐related molecules. Glioma cells with overexpression of CKS2 were constructed to confirmed the fact that CKS2 induced nucleocytoplasmic translocation of SMAD2/3 and activated TGFβ/SMAD pathway, then upregulated its downstream targets expression, while inhibition of TGFβ/SMAD (by TGFβ inhibitor LY2157299 or SMAD4 siRNA) could reverse the tumor‐promoting effects and malignant phenotype caused by CKS2 overexpression. Conclusions We identified CKS2 as a critical contributor to the gliomagenesis, which might provide a novel therapeutic target for inhibiting the spread and infiltration of glioma

Evolution as a Service: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization

Evolutionary algorithms (EAs), such as the genetic algorithm (GA), offer an elegant way to handle combinatorial optimization problems (COPs). However, limited by expertise and resources, most users do not have enough capability to implement EAs to solve COPs. An intuitive and promising solution is to outsource evolutionary operations to a cloud server, whilst it suffers from privacy concerns. To this end, this paper proposes a novel computing paradigm, evolution as a service (EaaS), where a cloud server renders evolutionary computation services for users without sacrificing users' privacy. Inspired by the idea of EaaS, this paper designs PEGA, a novel privacy-preserving GA for COPs. Specifically, PEGA enables users outsourcing COPs to the cloud server holding a competitive GA and approximating the optimal solution in a privacy-preserving manner. PEGA features the following characteristics. First, any user without expertise and enough resources can solve her COPs. Second, PEGA does not leak contents of optimization problems, i.e., users' privacy. Third, PEGA has the same capability as the conventional GA to approximate the optimal solution. We implements PEGA falling in a twin-server architecture and evaluates it in the traveling salesman problem (TSP, a widely known COP). Particularly, we utilize encryption cryptography to protect users' privacy and carefully design a suit of secure computing protocols to support evolutionary operators of GA on encrypted data. Privacy analysis demonstrates that PEGA does not disclose the contents of the COP to the cloud server. Experimental evaluation results on four TSP datasets show that PEGA is as effective as the conventional GA in approximating the optimal solution

Two-Phase Fermentation Systems for Microbial Production of Plant-Derived Terpenes

Microbial cell factories, renowned for their economic and environmental benefits, have emerged as a key trend in academic and industrial areas, particularly in the fermentation of natural compounds. Among these, plant-derived terpenes stand out as a significant class of bioactive natural products. The large-scale production of such terpenes, exemplified by artemisinic acid—a crucial precursor to artemisinin—is now feasible through microbial cell factories. In the fermentation of terpenes, two-phase fermentation technology has been widely applied due to its unique advantages. It facilitates in situ product extraction or adsorption, effectively mitigating the detrimental impact of product accumulation on microbial cells, thereby significantly bolstering the efficiency of microbial production of plant-derived terpenes. This paper reviews the latest developments in two-phase fermentation system applications, focusing on microbial fermentation of plant-derived terpenes. It also discusses the mechanisms influencing microbial biosynthesis of terpenes. Moreover, we introduce some new two-phase fermentation techniques, currently unexplored in terpene fermentation, with the aim of providing more thoughts and explorations on the future applications of two-phase fermentation technology. Lastly, we discuss several challenges in the industrial application of two-phase fermentation systems, especially in downstream processing