Data Sheet 1_Global, regional, and national burden of IHD attributable to PM pollution aged 70 and above: an age-period-cohort modeling and frontiers analysis study.csv by Ke-Jie He (13239966)

“…Background<p>Particulate matter (PM) pollution is a significant risk factor for ischemic heart disease (IHD). …”

Table 1_Global, regional, and national burden of IHD attributable to PM pollution aged 70 and above: an age-period-cohort modeling and frontiers analysis study.docx by Ke-Jie He (13239966)

“…Background<p>Particulate matter (PM) pollution is a significant risk factor for ischemic heart disease (IHD). …”

Table 1_Characterization of the airway microbiome in preterm infants with bronchopulmonary dysplasia.doc by Zhidan Bao (22418314)

“…Previous studies have indicated a significant association between the pulmonary microbiome and various respiratory diseases. …”

Data Sheet 6_Global, regional, and national burden of IHD attributable to PM pollution aged 70 and above: an age-period-cohort modeling and frontiers analysis study.csv by Ke-Jie He (13239966)

“…Background<p>Particulate matter (PM) pollution is a significant risk factor for ischemic heart disease (IHD). …”

Video 1_Efficacy of P62-expressing plasmid in treatment of canine osteoarthritis pain: a pilot study.mp4 by Vladimir Gabai (38129)

“…Traditional OA management consist of non-steroidal anti-inflammatory drugs and remains challenging because of significant side effects, thus there is an urgent need for new effective and safe therapeutics for OA.…”

Table 1_Unpacking the cost implications of diagnosis-related groups reform for lumbar disc herniation patients in Chinese medicine: a closer look at evidence from China.xls by Meng-en Chen (22274533)

“…Objectives<p>Lumbar disc herniation (LDH) presents a significant economic burden globally, worsening in China due to an aging population. …”

Predicting brown planthopper populations in diverse agro-climatic zones of India: a comparative study of statistical and machine learning models by Kiran Gandhi Bapatla (21542016)

“…Among the models, LSTM outperformed MLP and SARIMAX, achieving higher accuracy (85.4%–98.5%), but requiring greater computational resources. In machine learning models, the previous week’s BPH count and current week’s total rainfall were the most significant features for predicting BPH populations across agro-climatic zones of India.…”

Supplementary Material for: High expression of tetraspanin CD63 predicts poor prognosis in esophageal squamous cell carcinoma by Matsumoto Y. (2866151)

“…Herein, we report the significance of CD63 expression by analyzing ESCC patient samples and ESCC cell lines. …”

Image 3_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Table 3_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Table 8_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Table 2_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Table 1_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Image 2_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Table 6_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Table 5_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Image 5_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Image 1_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tiff by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”

Figure 1 from Tracking Nongenetic Evolution from Primary to Metastatic ccRCC: TRACERx Renal by Ángel Fernández-Sanromán (20814476)

“…Variables in blue and gray bars display significant (FDR < 0.05) and nonsignificant associations, respectively. …”

Table 7_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx by Bin He (75597)

“…These subtypes exhibited significantly different distributions between AF and SR. …”