Chromosome-level genome assembly of Hippophae tibetana provides insights into high-altitude adaptation and flavonoid biosynthesis.

BACKGROUND: As an endemic shrub of the Qinghai-Tibetan Plateau (QTP), the distribution of Hippophae tibetana Schlecht. ranges between 2800 and 5200 m above sea level. As the most basal branch of the Hippophae genus, H. tibetana has an extensive evolutionary history. The H. tibetana is a valuable tree for studying the ecological evolution of species under extreme conditions. RESULTS: Here, we generated a high-quality chromosome-level genome of H. tibetana. The total size of the assembly genome is 917 Mb. The phylogenomic analysis of 1064 single-copy genes showed a divergence between 3.4 and 12.8 Mya for H. tibetana. Multiple gene families associated with DNA repair and disease resistance were significantly expanded in H. tibetana. We also identified many genes related to DNA repair with signs of positive selection. These results showed expansion and positive selection likely play important roles in H. tibetana's adaptation to comprehensive extreme environments in the QTP. A comprehensive genomic and transcriptomic analysis identified 49 genes involved in the flavonoid biosynthesis pathway in H. tibetana. We generated transgenic sea buckthorn hairy root producing high levels of flavonoid. CONCLUSIONS: Taken together, this H. tibetana high-quality genome provides insights into the plant adaptation mechanisms of plant under extreme environments and lay foundation for the functional genomic research and molecular breeding of H. tibetana.

A regularized orthogonal activated inverse-learning neural network for regression and classification with outliers.

A novel regularized orthogonal activated inverse-learning (ROAIL) neural network is proposed and investigated for reducing the impact of outliers in regression and classification fields. The proposed ROAIL network does not require extensive iterative computations. Instead, it can achieve the desired results with a single step of computation, allowing for the efficient acquisition of network weights. By extending the Gegenbauer polynomials to a multi-variate version, and integrating the ℓ2 regularization and Welsch loss function into the orthogonal activated inverse-learning framework, two forms of ROAIL are obtained, i.e., ℓ2 norm ROAIL (ℓ2-ROAIL) and Welsch-ROAIL (W-ROAIL). ℓ2-ROAIL neural network is proposed to minimize the empirical and structural risk simultaneously since taking the structural risk as a part of loss function can effectively reduce the complexity of the model and thus improve the generalization ability. W-ROAIL neural network further improves the robustness of the ℓ2-ROAIL neural network by replacing the original two-norm in loss function with Welsch function. The Welsch function can determine the weights of each sample according to its output error, and influence of outliers could be weakened since the weights of outliers would be reduced. Both regression and classification experiments show that W-ROAIL neural network has strong ability to suppress the influence of outliers.

Genome-wide identification of the walnut MYC gene family and functional characterization of Xinjiang wild walnut under low-temperature stress.

Introduction: MYC transcription factors are the basic regulators of the jasmonic acid signaling pathway and play important roles in plant growth and development and the response to adverse stress. In recent years, severe winter freezing and late spring frost in the main planting area of walnut in Xinjiang have affected the growth and development of walnut, which has become a prominent problem restricting walnut production. Xinjiang wild walnut is the only remaining wild species of walnuts in China, which contains a lot of genes with excellent traits, and is important for the cultivation and breeding. Methods: In this paper, the physicochemical properties and bioinformatics of MYC transcription factor members in walnut were analyzed, and the nine MYC were screened from the transcriptome data under low temperature stress. At last, we study the subcellular localizations and the expression patterns of the nine MYC members in Xinjiang wild walnut. Results: The results revealed that 30 MYC members were identified from published walnut whole-genome data, and their evolutionary relationships with Arabidopsis and poplar were divided into six groups according to clustering analysis, among which JrMYC22 and JrMYC23 had high homology with PtrMYC2b, which is induced by jasmonic acid in response to low-temperature stress. Walnut MYC members are unevenly distributed on 12 chromosomes. The prediction of promoter cis-acting elements of walnut MYC transcription factor family members revealed that cis-acting elements related to jasmonic acid and lowtemperature stress were the ones with the greatest number of members, with 12. In addition, all nine MYC family members in Xinjiang wild walnut plants responding to low-temperature stress exhibited strong fluorescence responses in the nucleus. The expression levels of these members in response to low-temperature stress revealed that JrMYC28, JrMYC31, JrMYC33, JrMYC34, and JrMYC35 were highly expressed, and it was hypothesized that JrMYC28, JrMYC31, JrMYC33, JrMYC34, and JrMYC35 might play a key role in the response to lowtemperature stress. Discussion: The results of this study provide a theoretical basis for further research on the functional mechanisms of the MYC transcription factor family members in walnut.

The influencing factors of participation in time banking volunteer service for older adults among university students in Nanjing, China.

Objective: This study aims to identify factors influencing university students' participation in time banking volunteer services for older adults and provides evidence to promote the involvement. Methods: Conducted in November 2022, we utilized a convenience sampling method to recruit students from the School of Aging Service and Management at Nanjing University of Chinese Medicine, China. Data was collected through an online questionnaire focusing on various aspects related to time banking volunteer services for older adults. Factor analysis was employed to extract variables, and logistic regression was applied to identify key determinants. Results: A significant majority (82.67%) of participants expressed willingness to engage in volunteer services for older adults. Factor analysis uncovered six influential factors explaining 62.55% of the variance. Logistic regression highlighted four key determinants of students' willingness: value judgment (OR = 4.392, CI = 2.897-6.658), social support (OR = 1.262, CI = 0.938-1.975), social influence (OR = 1.777, CI = 1.598-3.799), and socioeconomic conditions (OR = 1.174, CI = 1.891-3.046). Conclusion: To foster sustainability and continuous time banking among university students majoring in aging service and management, a multifaceted support involving governmental, social, and university is recommended.