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1.
J Environ Manage ; 351: 119977, 2024 Feb.
Article in English | MEDLINE | ID: mdl-38160549

ABSTRACT

Moso bamboo (Phyllostachys edulis) is a valuable nontimber forestry product with a biennial cycle, producing abundant bamboo shoots within one year (on-year) and few shoots within the following year (off-year). Moso bamboo plants undergo clonal reproduction, resulting in similar genetic backgrounds. However, the number of moso bamboo shoots produced each year varies. Despite this variation, the impact of soil nutrients and the root microbiome on the biennial bearing of moso bamboo is poorly understood. We collected 139 soil samples and determined 14 major physicochemical properties of the rhizosphere, rhizoplane, and bulk soil in different seasons (i.e., the growing and deciduous seasons) and different years (i.e., on- and off-years). Based on 16S rRNA and metagenomic sequencing, major variations were found in the rhizospheric microbial composition during different seasons and years in the moso bamboo forest. Environmental driver analysis revealed that essential nutrients (i.e., SOC, TOC, TN, P, and NH4+) were the main drivers of the soil microbial community composition and were correlated with the on- and off-year cycles. Moreover, 19 MAGs were identified as important biomarkers that could distinguish on- and off-years. We found that both season and year influenced both the microbial community structure and functional pathways through the biosynthesis of nutrients that potentially interact with the moso bamboo growth rhythm, especially the on-year root-associated microbiome, which had a greater abundance of specific nutrients such as gibberellins and vitamin B6. This work provides a dynamic perspective of the differential responses of various on- and off-year microbial communities and enhances our understanding of bamboo soil microbiome biodiversity and stability.


Subject(s)
Poaceae , Rhizosphere , RNA, Ribosomal, 16S/genetics , Forests , Soil/chemistry
2.
Gigascience ; 112022 10 30.
Article in English | MEDLINE | ID: mdl-36310246

ABSTRACT

Bamboo, the fast-growing grass plant, and rattan, the spiky climbing palm, are both essential forest resources that have been closely linked with human lives, livelihoods and material culture since ancient times. To promote genetic and genomic research in bamboo and rattan, a comprehensive and coordinated international project, the Genome Atlas of Bamboo and Rattan (GABR), was launched in 2017. GABR achieved great success during Phase I (2017-2022). We will focus on investigating and protecting bamboo and rattan germplasm resources in Phase II ( 2022-2027). Here, we briefly review the achievements of Phase I and introduce the goals of Phase II.


Subject(s)
Forests , Sustainable Development , Humans , Poaceae/genetics
3.
J Healthc Eng ; 2019: 5647078, 2019.
Article in English | MEDLINE | ID: mdl-31534646

ABSTRACT

In China, emergency room residents (EMRs) generally face high working intensity. It is particularly important to arrange the working shifts of EMRs in a scientific way to balance their work and rest time. However, in existing studies, most of the scheduling models are based on the individual doctor or nurse as a unit, less considering the actuality of operation and management of emergency department (ED) in large public hospitals in China. Besides, the depiction of the hard and soft constraints of EMR scheduling in China is insufficient. So in order to obtain the scientific and reasonable scheduling shifts, this paper considers various management rules in a hospital, physicians' personal preferences, and the time requirements of their personal learning and living and takes the minimum deviation variables from the soft constraints as the objective function to construct a mixed integer programming model with the doctor group as the scheduling unit. The analytic hierarchy process (AHP) is used to determine the weights of deviation variables. Then, IBM ILOG CPLEX 12.8 is used to solve the model. The feasibility and effectiveness of the scheduling method are verified by the actual case from West China Hospital of Sichuan University. The scheduling results can meet the EMRs' flexible work plans and the preferences of the doctor teams for the shifts and rest days. Compared with the current manual scheduling, the proposed method can greatly improve the efficiency and rationality of shift scheduling. In addition, the proposed scheduling method also provides a reference for EMR scheduling in other China's high-grade large public hospitals.


Subject(s)
Academic Medical Centers/organization & administration , Emergency Medicine/methods , Emergency Medicine/organization & administration , Personnel Staffing and Scheduling , Physicians , Algorithms , China , Electronic Health Records , Emergency Service, Hospital , Hospitals , Humans , Learning , Models, Statistical , Software , Work Schedule Tolerance
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