Data from: Large subsurface carbon stocks in a long-term no-tillage site are vulnerable to potential mineralization by Qiuping Peng (20147290)

“…Alternative fitting methods were also considered, including fitting a single set of transit times (k-values) to all samples, versus fitting a unique set of turnover times for each samples. …”

Cyclization Decoded: Engineering Amylomaltase for Efficient α‑Glucan Transformations by Han Liu (288039)

Supplementary Material for: Hidradenitis Suppurativa in a Large Cohort of Italian Patients: Evaluation of the Burden of Disease by Fabbrocini G. (7463126)

Development of quality of life during the COVID-19 pandemic in the Netherlands. by C. A. Robert Warmerdam (12568808)

The life cycle of intensifiers, with empirical examples. by Madison S. Krieger (4487053)

Study group background characteristics. by Zicheng Hu (3825313)

“…The dashed horizontal lines in <b>Fig 1K</b>–<b>1O</b> indicate the mean +2 SD of the uninfected, seronegative (<b><i>HIV-</i></b>) control group in the measured variable as a rough estimate of their upper normal limit and as a visual guide to compare groups; this convention is also used in the Olink CSF protein measurement figures showing the group profiles in subsequent figures. …”

Table1_Expression, Prognosis and Gene Regulation Network of NFAT Transcription Factors in Non-Small Cell Lung Cancer.XLSX by Jin Ma (335456)

“…In lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), NFAT1/2/4/5 mRNA expression levels were significantly decreased and NFAT3 mRNA expression level was significantly increased. …”

Table1_Sensitivity of the Cervical Disc Loads, Translations, Intradiscal Pressure, and Muscle Activity Due to Segmental Mass, Disc Stiffness, and Muscle Strength in an Upright Neut... by Rizwan Arshad (12465345)

“…A head–neck complex with nine segments (head, C1–T1) was developed with joints having three rotational and three translational degrees of freedom, 517 nonlinear ligament fibers, and 258 muscle fascicles. …”

STMs for speech in impaired listeners (Venezia et al., 2019) by Jonathan H. Venezia (425218)

“…Ordinal regression was used to estimate weights showing which regions of the STM spectrum were associated with good performance (a “classification image” or CImg).</div><div><b>Results: </b>The results indicated that (a) large-scale CImg patterns did not differ between the 3 groups; (b) weights in a small region of the CImg decreased systematically as hearing loss increased; (c) CImgs were also nonsystematically distorted in OHI listeners, and the magnitude of this distortion predicted speech recognition performance even after accounting for audibility; and (d) YNH listeners performed better overall than the older groups.…”