The regulation of AsfR on tmRNA expression mediates bacterial motility and virulence by Huimin Chang (21142907)

“…Consistently, the transcription level of tmRNA was significantly decreased in Δ<i>asfR</i> compared with WT of <i>A. veronii </i>by quantitative real-time PCR (RT-qPCR) analyses. …”

Table 2_The hemoglobin, albumin, lymphocyte, and platelet score as a useful predictor for mortality in older patients with hip fracture.docx by Zhicong Wang (810566)

“…For each unit increase in the HALP score, there was a significant decrease in 90-day mortality by 1.1% and in overall mortality by 1.0% (all p < 0.05). …”

Table 3_The hemoglobin, albumin, lymphocyte, and platelet score as a useful predictor for mortality in older patients with hip fracture.docx by Zhicong Wang (810566)

“…For each unit increase in the HALP score, there was a significant decrease in 90-day mortality by 1.1% and in overall mortality by 1.0% (all p < 0.05). …”

Table 4_The hemoglobin, albumin, lymphocyte, and platelet score as a useful predictor for mortality in older patients with hip fracture.docx by Zhicong Wang (810566)

“…For each unit increase in the HALP score, there was a significant decrease in 90-day mortality by 1.1% and in overall mortality by 1.0% (all p < 0.05). …”

Image 2_The hemoglobin, albumin, lymphocyte, and platelet score as a useful predictor for mortality in older patients with hip fracture.jpeg by Zhicong Wang (810566)

“…For each unit increase in the HALP score, there was a significant decrease in 90-day mortality by 1.1% and in overall mortality by 1.0% (all p < 0.05). …”

Image 7_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

“…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”

Image 2_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

“…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”

Image 3_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

“…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”

Image 4_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

“…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”

Image 5_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

“…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”

Image 6_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

“…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”

Octβ2R and cAMP underlie the Brp compartmental heterogeneity. by Hongyang Wu (8856740)

“…Pseudo color range: −1.2 to 1.2. Mann–Whitney <i>U</i>-test. Ctrl (<i>n</i> = 10 brains) vs. …”

Table 2_Genomic characterization and antibiotic susceptibility of biofilm-forming Borrelia afzelii and Borrelia garinii from patients with erythema migrans.pdf by Giorgia Fabrizio (19022288)

“…Core genome analysis showed 38.9% of genes were shared between B. afzelii and B. garinii, decreasing to 26.1% with B. burgdorferi. The cloud genome expanded from 34.4% to 53.4% with the addition of B. burgdorferi. …”

Image 8_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

“…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”

Image 7_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

“…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”

Data Sheet 2_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.zip by Minyong Choi (22465405)

“…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”

Image 4_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

“…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”

Image 3_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

“…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”

Image 2_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

“…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”

Image 5_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

“…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”