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TranscriptomicsTranscription profiling of soleus muscle from lean and obese Zucker rats following exercise training
Endurance exercise training has been shown to decrease whole-body and skeletal muscle insulin resistance and increase glucose tolerance in conditions of both pre-diabetes and overt type 2 diabetes. However, the adaptive responses in skeletal muscle at the molecular and genetic level for these benef...
ORGANISM(S): Rattus norvegicus 
2009-11-16 | E-TABM-213 | biostudies-arrayexpress
UnknownAssociation between trends in clinical variables and outcome in intensive care patients with faecal peritonitis: analysis of the GenOSept cohort.
Not available
S-EPMC4432819 | biostudies-literature
UnknownCOVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study.
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S-EPMC8231091 | biostudies-literature
UnknownTen months of temporal variation in the clinical journey of hospitalised patients with COVID-19: An observational cohort.
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S-EPMC8791638 | biostudies-literature
UnknownRespiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study.
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S-EPMC9469080 | biostudies-literature
UnknownAssociation of Country Income Level With the Characteristics and Outcomes of Critically Ill Patients Hospitalized With Acute Kidney Injury and COVID-19.
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S-EPMC10219675 | biostudies-literature
UnknownThrombotic and hemorrhagic complications of COVID-19 in adults hospitalized in high-income countries compared with those in adults hospitalized in low- and middle-income countries in an international registry.
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S-EPMC10439444 | biostudies-literature
UnknownImplementation of Recommendations on the Use of Corticosteroids in Severe COVID-19.
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S-EPMC10751594 | biostudies-literature
UnknownThe value of open-source clinical science in pandemic response: lessons from ISARIC.
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S-EPMC8489876 | biostudies-literature
UnknownAt-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.
Not available
S-EPMC11252333 | biostudies-literature
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