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Abstract Emerged evidence has indicated that immunosuppression is involved in the occurrence and development of sepsis. To provide clinical practice recommendations on the immune function in sepsis, an expert consensus focusing on the monitoring and treatment of sepsis-induced immunosuppression was developed. Literature related to the immune monitoring and treatment of sepsis were retrieved from PubMed, Web of Science, and Chinese National Knowledge Infrastructure to design items and expert opinions were collected through an online questionnaire. Then, the Delphi method was used to form consensus opinions, and RAND appropriateness method was developed to provide consistency evaluation and recommendation levels for consensus opinions. This consensus achieved satisfactory results through two rounds of questionnaire survey, with 2 statements rated as perfect consistency, 13 as very good consistency, and 9 as good consistency. After summarizing the results, a total of 14 strong recommended opinions, 8 weak recommended opinions and 2 non-recommended opinions were produced. Finally, a face-to-face discussion of the consensus opinions was performed through an online meeting, and all judges unanimously agreed on the content of this consensus. In summary, this expert consensus provides a preliminary guidance for the monitoring and treatment of immunosuppression in patients with sepsis.

Subsequent findings reveal the combination characteristics and spatial patterns of plant functional traits, and their response and adaptation to environmental changes in the Qinghai-Tibet Plateau. We analyzed the variation in characteristics and the influence of environmental factors on leaf functional traits from 78 quadrats in July 2021, using: one-way ANOVA, Tukey’s Honest Significant Difference (HSD) post hoc test, Pearson correlation coefficient (r) analysis, and redundancy analysis (RDA) in the Qilian Mountains. Only the leaf carbon content (LCC) of arbors was a weak variation indicator in leaf function traits of different plant types, whereas other leaf function traits including: the LCC of herbaceous plants (herbs) and shrub plants (shrubs), and the leaf nitrogen content (LNC) and carbon to nitrogen (C/N) ratio of arbors were medium variation indicators. The LNC, leaf phosphorus content (LPC), C/N ratio(C/N), C/P ratio(C/P), and N/P ratio (N/P)of herbs and shrubs, and the LPC, C/P, and N/P of arboreal plants (arbors) were strong variation indicators. Altitude was also one of the main factors affecting functional traits of plants in cold regions. Electrical conductivity (EC) and soil phosphorus content (SPC) were the main factors affecting changes in the leaf functional traits of herbs. Soil bulk density (SBD) and Soil salinity (SAL) were the main factors affecting changes in the leaf functional traits of shrubs. Soil nitrogen content (SNC) and soil temperature (ST) were the main factors affecting changes in the leaf functional traits of arbors.

With the rapid development of Internet of Things(IoT),various IoT mobile devices(IMDs) need to process more and more computing-intensive and delay-sensitive tasks,which puts forward new challenges for the mobile edge networks.To address these challenges,the MEC-equipped ultra-dense IoT has emerged.In such networks,IMDs can save their computation resources and reduce their energy consumption by offloading computing-intensive tasks to edge computing servers for processing.However,it will result in additional transmission time and higher delay.In view of this,an optimization problem is formulated for finding the trade-off between energy consumption and delay,which jointly considers the user(IMD) association,computation offloading and resource allocation for ultra-dense MEC-enabled IoT.To further balance the network load and fully utilize the computation resources,the optimization problem is finally modeled as multi-step computation offloading one.At last,an intelligent algorithm,adaptive particle swarm optimization(PSO),is utilized to solve the proposed problem.Compared with traditional PSO,the total cost of adaptive PSO reduces by 20%~65%.

Selenium (Se) is essential for successful male reproduction. However, the association of Se status with human semen quality remains controversial and the underlying mechanisms are poorly understood. We measured seminal plasma Se concentrations, sperm mitochondrial DNA copy number (mtDNAcn), and sperm quality parameters among healthy Chinese men screened as potential sperm donors. Linear mixed-effects models were used to investigate the associations of within-subject pooled seminal plasma Se concentrations (n = 1159) with repeated sperm quality parameters (n = 5617); mediation analyses were applied to evaluate the mediating role of sperm mtDNAcn (n = 989). Seminal plasma Se concentrations were positively associated with sperm concentration and total count (both P for trend < 0.001). In adjusted models, men in the top vs. bottom quartiles of seminal plasma Se concentrations had 70.1 % (95 % CI: 53.3 %, 88.9 %) and 59.1 % (95 % CI: 40.5 %, 80.2 %) higher sperm concentration and total count, respectively. Meanwhile, we observed inverse associations between seminal plasma Se concentrations and sperm mtDNAcn, and between sperm mtDNAcn and sperm motility, concentration, and total count (all P for trend < 0.05). Mediation analyses suggested that sperm mtDNAcn mediated 19.7 % (95 % CI: 15.9 %, 25.3 %) and 23.1 % (95 % CI: 17.4 %, 33.4 %) of the associations between seminal plasma Se concentrations and sperm concentration and total count, respectively. Our findings suggest that Se is essential for male spermatogenesis, potentially by affecting sperm mtDNAcn.