Supersonic gas jet subsoiler experiment. by Xia Li (14984)

“…Furthermore, the subsoiling effect was further improved as the working speed decreased and the frequency of air blasts increased, satisfying the subsoiling operation assessment standards. …”

TNFAIP9 expression was increased in mice with chronic kidney disease (CKD) induced by 5/6 nephrectomy (Nx). by Ying Chen (9697)

Differences in glenohumeral joint stability (A) and muscle force of the infraspinatus (B), and subscapularis (C) in models with and without cuff tears. by Shobu Nakashima (22537717)

“…<p>The black bar indicates a significant increase compared with the Intact model, and the gray bar indicates a significant decrease compared with the Intact model.…”

Behaviour and significance of reservoir evaporation and seepage losses – an experience of four reservoirs in Damodar River Valley, India by Dipankar Chaudhuri (498103)

“…Frequency of seepage varied significantly with the season or month. It increased noticeably with rise of operating level. …”

Schematic presentation <i>M</i>. <i>bovis</i> PG45 5′ nucleotidase and phylogenetic tree of its homologs. by Aga E. Gelgie (17661720)

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<i>In vitro</i> characterization of the mnuA::Tn and 0690::Tn mutants. by Aga E. Gelgie (17661720)

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Loss of mammary fitness and virulence by <i>M</i>. <i>bovis</i> 0690::Tn mutant. by Aga E. Gelgie (17661720)

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<i>M</i>. <i>bovis</i> 0690::Tn mutant failed to elicit the recruitment of neutrophils into milk spaces. by Aga E. Gelgie (17661720)

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Data supporting the findings of this study. by Aga E. Gelgie (17661720)

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Oligonucleotides used in this study. by Aga E. Gelgie (17661720)

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Impact of 5′ nucleotidase disruption on <i>M</i>. <i>bovis</i> growth phenotype in axenic conditions. by Aga E. Gelgie (17661720)

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Inactivation of MnuA and 5′-NT reduced bacterial fitness and virulence of <i>M</i>. <i>bovis</i> PG45 in mammary glands. by Aga E. Gelgie (17661720)

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Mapping of transposon insertions in the selected mutants of <i>M</i>. <i>bovis</i> PG45. by Aga E. Gelgie (17661720)

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Effect of alkali-stress (NaHCO₃ (250 mmol·L⁻¹)) on SGAT activity, Rubico activity, glycine (Gly), and serine (Ser) content in hemp seedling leaves grown under... by Zeyu Jiang (5094320)

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Table 2_Prognostic significance of collagen content in solitary fibrous tumors of the central nervous system.docx by Xiaoling Li (129705)

“…Additionally, the signal intensity of SFTs on T2-weighted imaging (T2WI) decreased with increasing collagen content. Radiomics analysis identified 1,702 features from each patient’s region of interest, with 12 features showing significant differences between the high and low collagen content groups. …”

Table 4_Prognostic significance of collagen content in solitary fibrous tumors of the central nervous system.docx by Xiaoling Li (129705)

“…Additionally, the signal intensity of SFTs on T2-weighted imaging (T2WI) decreased with increasing collagen content. Radiomics analysis identified 1,702 features from each patient’s region of interest, with 12 features showing significant differences between the high and low collagen content groups. …”

Table 3_Prognostic significance of collagen content in solitary fibrous tumors of the central nervous system.docx by Xiaoling Li (129705)

“…Additionally, the signal intensity of SFTs on T2-weighted imaging (T2WI) decreased with increasing collagen content. Radiomics analysis identified 1,702 features from each patient’s region of interest, with 12 features showing significant differences between the high and low collagen content groups. …”

Table 1_Prognostic significance of collagen content in solitary fibrous tumors of the central nervous system.docx by Xiaoling Li (129705)

“…Additionally, the signal intensity of SFTs on T2-weighted imaging (T2WI) decreased with increasing collagen content. Radiomics analysis identified 1,702 features from each patient’s region of interest, with 12 features showing significant differences between the high and low collagen content groups. …”

Minimal data set. by Pornpan Chalermkitpanit (22110121)

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Univariate and multivariate analysis of variables associated with good and poor responders to TFESI. by Pornpan Chalermkitpanit (22110121)

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