Data Sheet 1_Seven unique frequency profiles for scoring vigilance states in preclinical electrophysiological data.docx by Freja Gam Østergaard (19360470)

“…Based on these assumptions, a scoring method with a set frequency profile for each vigilance state, both in sleep and awake, was developed and validated. …”

Evaluation of PCR amplification bias and PCR amplification efficiency. by Trang Thi Quynh Tran (20485595)

“…(<b>C</b>) The ΔCt value, calculated by subtracting the CT value of the MSP primer set from that of the MIP primer set for each sample, proportionally increases as the DNA input decreases, indicating the Pfaffl formula to be suitable for relative quantification. …”

Impact of pathogen shedding characteristics on estimation accuracy. by Yun Lin (77976)

“…The violin plot represents the distribution of the detected Ct values for the 200 randomly selected individuals in each trajectory panel, and the horizontal dashed line represents the median Ct value at detection for individuals infected with each pathogen during the increasing epidemic as a reference for comparing the Ct distributions for each pathogen during different epidemic periods. …”

What matters in conversational recast treatment? (Choi-Tucci et al., 2025) by Alexander Tucci (16463756)

“…</p><p dir="ltr"><b>Conclusions:</b> These results suggest that different variations of conversational recasting facilitate or diminish learning by children with DLD and that clinicians’ attention to the form and structure of treatment delivery is necessary to implement best practice for this treatment method. …”

Ambulatory modeling of vocal hyperfunction (Parra et al., 2025) by Jesús A. Parra (20677929)

“…</p><p dir="ltr"><b>Results: </b>Results showed significant differences between the PVH and control groups in key parameters, including statistical moments of H1–H2, SPL, PS, and muscle activity of lateral cricoarytenoid (LCA) and cricothyroid (CT) muscles. Higher DPI values, reflecting more severe PVH, were associated with increased mean LCA activation and decreased LCA variability, along with decreased mean CT activation and increased median PS. …”

Table 1_Effects of Tanreqing injection on the gut microbiota in healthy volunteers.docx by Shiyu Li (144475)

“…Gut microbial structure was stable (weighted and unweighted Unifrac). Using a machine learning method based on PLS-DA analysis, the separation trend on D7 at the genus level was found, returning to baseline two days after discontinuation. …”

Supplementary Material for: Case Report of Myeloproliferative Neoplasm Complicated with Hepatic Sinusoidal Obstruction Syndrome and Focal Segmental Glomerulosclerosis by figshare admin karger (2628495)

“…Diagnostic investigations included a renal biopsy, which confirmed focal segmental glomerulosclerosis, and an abdominal enhanced CT scan, suggesting hepatic sinusoidal obstruction syndrome. …”

Data Sheet 2_An intricate relationship: stress markers and associative memory in a laboratory experiment in older adults.pdf by Luisa Knopf (22518134)

“…Such anecdotal experiences raise the question of whether the affective or physiological response of older participants to psychological laboratory experiments differs to that of young adults, who might be less motivated but also less nervous, as they may be more used to the environment and to learning and memory tests.</p>Methods<p>In the present study, we collected saliva samples and subjective affective ratings during an EEG experiment on memory, and at home, in young and older adults, while also taking into account sex effects.…”

Data Sheet 1_An intricate relationship: stress markers and associative memory in a laboratory experiment in older adults.pdf by Luisa Knopf (22518134)

“…Such anecdotal experiences raise the question of whether the affective or physiological response of older participants to psychological laboratory experiments differs to that of young adults, who might be less motivated but also less nervous, as they may be more used to the environment and to learning and memory tests.</p>Methods<p>In the present study, we collected saliva samples and subjective affective ratings during an EEG experiment on memory, and at home, in young and older adults, while also taking into account sex effects.…”

Supplementary Material for: Exploring the ability of novel choroidal biomarkers in predicting treatment outcomes of polypoidal choroidal vasculopathy by Zhang Y. (2828780)

“…Using ROC curves, we found that the CVI value demonstrated superior predictive ability compared to the CT value, with AUC of 0.842 and the best cut-off value of 0.445. …”

Table 3_Engineered spermidine-secreting Saccharomyces boulardii enhances olfactory memory in Drosophila melanogaster.xlsx by Florance Parweez (22534262)

“…The intracellular levels of polyamines, especially spermidine, decrease in aging. Oral spermidine supplementation has been reported to alleviate aspects of aging-related disease in animal models, including decline in learning and memory. …”

Table 1_Engineered spermidine-secreting Saccharomyces boulardii enhances olfactory memory in Drosophila melanogaster.xlsx by Florance Parweez (22534262)

“…The intracellular levels of polyamines, especially spermidine, decrease in aging. Oral spermidine supplementation has been reported to alleviate aspects of aging-related disease in animal models, including decline in learning and memory. …”

Table 2_Engineered spermidine-secreting Saccharomyces boulardii enhances olfactory memory in Drosophila melanogaster.xlsx by Florance Parweez (22534262)

“…The intracellular levels of polyamines, especially spermidine, decrease in aging. Oral spermidine supplementation has been reported to alleviate aspects of aging-related disease in animal models, including decline in learning and memory. …”

<b>Mystery of Deep Soil Organic Carbon Dynamics Uncovered through Long-term Conservation Tillage Experiments</b> by Jianye Li (8914520)

“…</a> Plant-derived carbon showed increased stability in the deep soil, as evidenced by decreased (Ac/Al)s values (-58%) and (Ac/Al)v values (-28%) and a 84% rise in V-type phenols under NT. …”

Clustering and heatmap of samples and genes. by Mojdeh Akbarzadeh Lelekami (21144101)

“…Red and green colors indicate increased and decreased expression in response to stress, respectively. …”

Image 6_Divergent B-cell and cytotoxic TNK cell activation signatures in HLA-B27-associated ankylosing spondylitis and acute anterior uveitis.jpeg by Eisa Mahyari (9681962)

“…Furthermore, we employed sparse decomposition of arrays (SDA) analysis, an unsupervised machine learning method, to examine the high-dimensional transcriptional landscape of our data and identify complex and nonlinear relationships. …”

Image 9_Divergent B-cell and cytotoxic TNK cell activation signatures in HLA-B27-associated ankylosing spondylitis and acute anterior uveitis.jpeg by Eisa Mahyari (9681962)

“…Furthermore, we employed sparse decomposition of arrays (SDA) analysis, an unsupervised machine learning method, to examine the high-dimensional transcriptional landscape of our data and identify complex and nonlinear relationships. …”

Data Sheet 1_Divergent B-cell and cytotoxic TNK cell activation signatures in HLA-B27-associated ankylosing spondylitis and acute anterior uveitis.docx by Eisa Mahyari (9681962)

“…Furthermore, we employed sparse decomposition of arrays (SDA) analysis, an unsupervised machine learning method, to examine the high-dimensional transcriptional landscape of our data and identify complex and nonlinear relationships. …”

Image 5_Divergent B-cell and cytotoxic TNK cell activation signatures in HLA-B27-associated ankylosing spondylitis and acute anterior uveitis.jpeg by Eisa Mahyari (9681962)

“…Furthermore, we employed sparse decomposition of arrays (SDA) analysis, an unsupervised machine learning method, to examine the high-dimensional transcriptional landscape of our data and identify complex and nonlinear relationships. …”

Data Sheet 2_Divergent B-cell and cytotoxic TNK cell activation signatures in HLA-B27-associated ankylosing spondylitis and acute anterior uveitis.xlsx by Eisa Mahyari (9681962)

“…Furthermore, we employed sparse decomposition of arrays (SDA) analysis, an unsupervised machine learning method, to examine the high-dimensional transcriptional landscape of our data and identify complex and nonlinear relationships. …”