Table 7_Immunological reference intervals in pregnancy: longitudinal analysis of adaptive lymphocyte subsets.xlsx by Miguel Ângelo-Dias (20936444)

“…</p>Methods<p>A total of 50 pregnant and 30 age-matched non-pregnant women were recruited in a prospective cohort study. …”

Table 2_Immunological reference intervals in pregnancy: longitudinal analysis of adaptive lymphocyte subsets.xlsx by Miguel Ângelo-Dias (20936444)

“…</p>Methods<p>A total of 50 pregnant and 30 age-matched non-pregnant women were recruited in a prospective cohort study. …”

Table 4_Immunological reference intervals in pregnancy: longitudinal analysis of adaptive lymphocyte subsets.xlsx by Miguel Ângelo-Dias (20936444)

“…</p>Methods<p>A total of 50 pregnant and 30 age-matched non-pregnant women were recruited in a prospective cohort study. …”

Table 5_Immunological reference intervals in pregnancy: longitudinal analysis of adaptive lymphocyte subsets.xlsx by Miguel Ângelo-Dias (20936444)

“…</p>Methods<p>A total of 50 pregnant and 30 age-matched non-pregnant women were recruited in a prospective cohort study. …”

Table 3_Immunological reference intervals in pregnancy: longitudinal analysis of adaptive lymphocyte subsets.xlsx by Miguel Ângelo-Dias (20936444)

“…</p>Methods<p>A total of 50 pregnant and 30 age-matched non-pregnant women were recruited in a prospective cohort study. …”

Image 2_Immunological reference intervals in pregnancy: longitudinal analysis of adaptive lymphocyte subsets.tif by Miguel Ângelo-Dias (20936444)

“…</p>Methods<p>A total of 50 pregnant and 30 age-matched non-pregnant women were recruited in a prospective cohort study. …”

Table 6_Immunological reference intervals in pregnancy: longitudinal analysis of adaptive lymphocyte subsets.xlsx by Miguel Ângelo-Dias (20936444)

“…</p>Methods<p>A total of 50 pregnant and 30 age-matched non-pregnant women were recruited in a prospective cohort study. …”

Data Sheet 1_Immunological reference intervals in pregnancy: longitudinal analysis of adaptive lymphocyte subsets.pdf by Miguel Ângelo-Dias (20936444)

“…</p>Methods<p>A total of 50 pregnant and 30 age-matched non-pregnant women were recruited in a prospective cohort study. …”

Data Sheet 4_Immunological reference intervals in pregnancy: longitudinal analysis of adaptive lymphocyte subsets.pdf by Miguel Ângelo-Dias (20936444)

“…</p>Methods<p>A total of 50 pregnant and 30 age-matched non-pregnant women were recruited in a prospective cohort study. …”

Data Sheet 1_Thalamic functional dysconnectivity in patients with left-hemisphere chronic capsular and pontine stroke.pdf by Jun Guo (85069)

“…Finally, we found significant group x subfields interactions on thalamic functional connectivity, where capsular vs. pontine stroke demonstrate varied functional dysconnectivity with specific thalamic subfields. …”

SEAwise Report on improved predictive models of recruitment under different habitat scenarios and incorporating experimental results by Paco Melià (162862)

“…Climate conditions were less important than trophic linkages with processes during both the hatching year and the second year of life being significantly important. …”

Table2_Identification of telomere-related lncRNAs and immunological analysis in ovarian cancer.xlsx by Weina Xu (558990)

“…The mRNA levels of PTPRD-AS1, SPAG5-AS1, FAM27E3, and AC018647.3 were significantly over-expressed in OC cell lines (SKOV3, A2780, CAOV3) in comparison to normal IOSE-80 cells. …”

Table1_Identification of telomere-related lncRNAs and immunological analysis in ovarian cancer.docx by Weina Xu (558990)

“…The mRNA levels of PTPRD-AS1, SPAG5-AS1, FAM27E3, and AC018647.3 were significantly over-expressed in OC cell lines (SKOV3, A2780, CAOV3) in comparison to normal IOSE-80 cells. …”

DataSheet1_Identification of telomere-related lncRNAs and immunological analysis in ovarian cancer.docx by Weina Xu (558990)

“…The mRNA levels of PTPRD-AS1, SPAG5-AS1, FAM27E3, and AC018647.3 were significantly over-expressed in OC cell lines (SKOV3, A2780, CAOV3) in comparison to normal IOSE-80 cells. …”

Fig 3 - by Nehal Shawky Nagy (17721213)

“…<p>A) Pathologic assessment of H&E-stained sections of substantia nigra in different studied groups: control, DSMO, and gonadal extract groups show a compact cellular substania nigra in low power, high power shows viable neurons with large, rounded nuclei with open chromatin and a nucleolus (arrows). …”

Supplementary file 1_The effect of development on cortical auditory evoked potentials in normal hearing listeners and cochlear implant users.docx by Eun Kyung Jeon (2032222)

“…</p>Results<p>Both onset and ACC responses were present across groups, with P1 latency decreasing significantly with age in NH and CI listeners. …”

Supplementary file 1_Spatiotemporal monitoring in beidagang wetland using Landsat time-series images and Google Earth Engine during 2000–2022.docx by Xinyue Zhang (271120)

“…This study presents a promising method combining Landsat time-series images, DT and GEE for continuous land cover monitoring. …”

Table 1_Bone mineral content determined by energy X-ray absorptiometry correlates with handgrip strength in Latin American divers.docx by Alex Véliz (21709934)

“…Introduction<p>Although a lack of gravitational stimuli decreases bone mineral content in some populations, such as astronauts’ bone mineral content (BMC), little is known about the association of BMC with handgrip muscle strength (HGS) in divers of different years of diving experience.…”

Supplementary file 1_Spatial-temporal evolution characteristics and driving factors of carbon emission prediction in China-research on ARIMA-BP neural network algorithm.pdf by Sanglin Zhao (20915732)

“…The results show that: (1) From 2000 to 2035, China’s total carbon emissions increased year by year, but the growth rate of carbon emissions gradually decreased; The carbon emission structure is “secondary industry > residents’ life > tertiary industry > primary industry”, and the growth rate of carbon in secondary industry and residents’ life is faster, while the change trend of primary industry and tertiary industry is smaller; (2) The spatial distribution of carbon emissions in China’s provinces presents a typical pattern of “eastern > central > western” and “northern > southern”, and the carbon emission centers tend to move to the northwest; (3) The regions with high level of digital economy, advanced industrial structure and new quality productivity have relatively less carbon emissions, which has significant group difference effect; (4) The intensity effect of energy consumption is the main factor driving the continuous growth of carbon emissions, while the per capita GDP and the structure effect of energy consumption are the main factors restraining carbon emissions, while the effects of industrial structure and population size are relatively small. …”

Study group background characteristics. by Zicheng Hu (3825313)

“…<p>Except for the first panel (<b>Fig 1A</b>), the graphs (<b>Fig 1B</b>–<b>1O</b>) use the same format that is applied to subsequent figures showing the Olink-generated protein measurement profiles across the study groups. …”