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Streptomyces can produce secondary metabolites with a wide range of activities and is often used in agriculture as a biocontrol strain to control soil-borne diseases. Screening and isolation from infected soil is an effective method to obtain active strains. In this study, the best antagonistic inter-root growth-promoting bacteria were isolated from grapevine inter-root soil samples, and strain F2 was identified as Streptomyces sp. based on morphological, physiological, and biochemical characteristics as well as 16S rDNA sequencing results. The results showed that the fermentation broth/liquid and sterile filtrate of strain F2 exhibited antagonistic effects against 10 plant pathogens, with an inhibition rate reaching up to 80%. Notably, two of them exhibited remarkable inhibitory effects against Phytophthora capsici with inhibition rates of 80.58% and 87.71%, respectively. The P. capsici leaf control experiment revealed that the control effect of strain F2 fermentation liquid on P. capsici filaments was 61.09%. Furthermore, indoor pot experiments demonstrated that the fermentation liquid of strain F2 had a significant inhibitory effect on pepper blight, with a maximum inhibition of 83.31%. Antagonistic factor analysis indicated that strain F2 had specific organophosphorus hydrolysis, nitrogen fixation, extracellular protease secretion, and IAA production capabilities. Additionally, root treatment with strain F2’s fermentation liquid significantly enhanced capsicum growth. Taking together, Streptomyces F2 not only exhibits a wide-spectrum antagonistic effect against plant pathogens but also promotes plant growth, which suggests that Streptomyces F2 can be used as an effective biological control resource and provides important theoretical support for the application of Streptomyces F2.

For multi-level spondylolysis patients, surgeons commonly choose to fix all the segments with pars interarticularis defect even those without slippage and not responsible for clinical symptoms. In this study, we tried to study the necessity of the preventative long-segment surgery for the defected segment without slippage in treatment of multi-level spondylolysis patients from a biomechanical perspective.We established a bi-level spondylolysis model with pars defects at L4 and L5 segments, and simulated posterior lumbar interbody fusion (PLIF) and pedicle screw fixation at L5-S1 level. Then we compared the biomechanical changes at L4 segment before and after surgery in neutral, flexion, extension, lateral bending and axial rotation position.The stress on L4 pars interarticularis was very similar before and after surgery, and reached the highest in axial rotation. The L3-L4 intradiscal pressure was almost the same, while L4-L5 intradiscal pressure changed a little in lateral bending (increase from 1.993 to 2.160 MPa) and axial rotation (decrease from 1.639 to 1.307 MPa) after surgery. The PLIF surgery caused a little increase of range of motion at adjacent L4-L5 and L3-L4 levels, but the change is very tiny (1 degree).The PLIF surgery will not cause significant biomechanical change at adjacent segment with pars defect in multi-level spondylolysis. On the contrary, excessive long-segment surgery will damage surrounding soft tissues which are important for maintaining the stability of spine. So a preventative long-segment surgery is not necessary for multi-level spondylolysis as long as there are no soft tissue degeneration signs at adjacent level.

Demand control ventilation (DCV) is a high energy efficiency ventilation strategy with control input from carbon dioxide (CO2) sensors. The measurement data quality of CO2 sensors plays a critical role in accurate determination of the indoor air quality (IAQ) and actual ventilation rate in implementation of the DCV. In this paper, the airflow field and CO2 spatial distribution in an indoor space of a seminar room seated with breathing occupants was modelled and simulated utilizing computational fluid dynamics (CFD) analysis. The airflow streamlines, airflow pressure and velocity, turbulence kinematic energy, as well as the CO2 spatial distribution in the seminar room were investigated. The locations for proper placement of the CO2 sensors in the seminar room were identified, for assuring the measurement data quality and effective DCV to achieve high energy efficiency.

Chordoma is a rare aggressive bone tumor arising from remnants of the notochord, and patients with chordoma have a poor prognosis. However, the unique expression profiles of microRNAs (miRNAs/miRs) and their downstream signaling pathways in chordoma remain incompletely characterized. The aim of the present study was to delineate the global miRNA expression profile and associated signaling networks in chordoma. miRNA profiling was performed on chordoma and fetal notochord tissues. Differentially expressed miRNAs in chordoma were analyzed using microarrays with hierarchical clustering analysis. The target genes of the differentially expressed miRNAs were predicted, and Gene Ontology (GO) and pathway analyses were performed for the intersecting genes. A total of 42 miRNAs were signifi- cantly dysregulated in chordoma compared with that in fetal nucleus pulposus tissues. The expression of hsa-miR-21-3p, hsa-miR-150-5p, hsa-miR-1290 and hsa-miR-623 were validated using the reverse transcription-quantitative polymerase chain reaction. On the basis of the intersection predicted by three databases (Targetscan, microRNA.org and PITA), 10,292 potential miRNA targets were identified. Bioinformatic analyses suggested that these dysregulated miRNAs and their predicted targets were functions of signaling pathways in cancer, the mitogen-activated protein kinase signaling pathway, regulation of actin cytoskeleton, focal adhesion and endocytosis. In particular, human (hsa-)miR-185-5p was identified as a crucial miRNA in chordoma development via the Wnt signaling pathway. The results of the present study provide a comprehensive expression and functional profile of differentially expressed miRNAs associated with chordoma. This profile may serve as a potential tool for biomarker and therapeutic target identification in patients with chordoma. [ABSTRACT FROM AUTHOR]

The measurement data quality of CO2 sensors plays a critical role in the implementation of the demand control ventilation (DCV) using a network of CO2 sensors. In this paper, the airflow field and spatial distribution of CO2 in an indoor space such as a seminar room was investigated utilizing computational fluid dynamics (CFD) analysis. The locations in the seminar room for proper placement of the CO2 sensors are identified, for assuring the measurement data quality and effective DCV to achieve high energy efficiency.