The clinical course of cirrhosis has been typically described by a compensated and a decompensated state based on the absence or, respectively, the presence of any of bleeding, ascites, encephalopathy or jaundice. More recently, it has been recognized that increasing portal hypertension and several major clinical events are followed by a marked worsening in prognosis, and disease states have been proposed accordingly in a multistate model. The development of multistate models implies the assessment of the probabilities of more than one possible outcome from each disease state. This requires the use of competing risks analysis which investigates the risk of several competing outcomes. In such a situation, the Kaplan-Meier risk estimates and the Cox regression may be not appropriate. Clinical states of cirrhosis presently considered as suitable for a comprehensive multistate model include: in compensated cirrhosis, early (mild) portal hypertension with hepatic venous pressure gradient (HVPG) >5 and <10 mmHg, clinically significant portal hypertension (HVPG ≥ 10 mmHg) without gastro-esophageal varices (GEV), and GEV; in decompensated cirrhosis, a first variceal bleeding without other decompensating events, any first non-bleeding decompensation and any second decompensating event; and in a late decompensation state, refractory ascites, sepsis, renal failure, recurrent encephalopathy, profound jaundice, acute on chronic liver failure, all predicting a very short survival. In this review, we illustrate how competing risks analysis and multistate models may be applied to cirrhosis.
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Sci Rep
December 2024
School of Pharmacy, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.
Cuproptosis, a newly identified form of cell death, has drawn increasing attention for its association with various cancers, though its specific role in colorectal cancer (CRC) remains unclear. In this study, transcriptomic and clinical data from CRC patients available in the TCGA database were analyzed to investigate the impact of cuproptosis. Differentially expressed genes linked to cuproptosis were identified using Weighted Gene Co-Expression Network Analysis (WGCNA).
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December 2024
Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut Medical Center, Riad El-Solh, PO Box 11-0236, 1107 2020, Beirut, Lebanon.
Fatigue is one of the most prevalent and disabling symptoms among patients with MS, but there is limited research investigating the longitudinal determinants of fatigue progression. This study aims to identify the sociodemographic, behavioral and clinical characteristics, and therapeutic regimens that are correlated with worsening fatigue over time in patients diagnosed with MS. This is a retrospective chart review of 483 patients.
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December 2024
Institute of Pathology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Pathogenic activating mutations in the fibroblast growth factor receptor 3 (FGFR3) drive disease maintenance and progression in urothelial cancer. 10-15% of muscle-invasive and metastatic urothelial cancer (MIBC/mUC) are FGFR3-mutant. Selective targeting of FGFR3 hotspot mutations with tyrosine kinase inhibitors (e.
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December 2024
Department of Orthopaedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Accumulating evidence indicates that cellular senescence is closely associated with osteoarthritis. However, there is limited research on the mechanisms underlying fibroblast-like synoviocyte senescence and its impact on osteoarthritis progression. Here, we elucidate a positive correlation between fibroblast-like synoviocyte senescence and osteoarthritis progression and reveal that GATD3A deficiency induces fibroblast-like synoviocyte senescence.
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December 2024
GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Laboratory, Guangzhou Medical University, Guangzhou, China.
Cell type deconvolution methods can impute cell proportions from bulk transcriptomics data, revealing changes in disease progression or organ development. But benchmarking studies often use simulated bulk data from the same source as the reference, which limits its application scenarios. This study examines batch effects in deconvolution and introduces SCCAF-D, a computational workflow that ensures a Pearson Correlation Coefficient above 0.
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