The prognosis of hepatocellular carcinoma (HCC) remains poor. Vascular invasion, tumour multiplicity and large tumour size are the conventional poor prognostic indicators related to early recurrence. However, it is difficult to predict prognosis of each HCC in the absence of these indicators. The purpose of this study is to predict early recurrence of HCC after radical resection based on whole human gene expression profiling. Microarray analyses were performed in 139 HCC primary tumours. A total of 88 cases lacking the conventional poor prognostic indicators were analysed to establish a molecular prediction system characteristic for early recurrence in 42 training cases with two polarised prognoses, and to test its predictive performance in 46 independent cases (group C). Subsequently, this system was applied to another 51 independent cases with some poor prognostic indicators (group D). The molecular prediction system accurately differentiated HCC cases into poor and good prognoses in both the independent group C (disease-free survival [DFS]: p=0.029, overall survival [OS]: p=0.0043) and independent group D (DFS: p=0.0011, OS, p=0.035). Multivariate Cox regression analysis indicated that the clinical value of molecular prediction system was an independent prognostic factor (p<0.0001, hazard ratio=3.29). Gene expression pattern related to early intrahepatic recurrence inherited in the primary HCC tumour can be useful for the prediction of prognosis.
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http://dx.doi.org/10.1016/j.ejca.2008.12.019 | DOI Listing |
J Am Chem Soc
January 2025
Tsung-Dao Lee Institute, Shanghai Jiao Tong University, Shanghai 201210, China.
The emergence of spinon quasiparticles, which carry spin but lack charge, is a hallmark of collective quantum phenomena in low-dimensional quantum spin systems. While the existence of spinons has been demonstrated through scattering spectroscopy in ensemble samples, real-space imaging of these quasiparticles within individual spin chains has remained elusive. In this study, we construct individual Heisenberg antiferromagnetic spin-1/2 chains using open-shell [2]triangulene molecules as building blocks.
View Article and Find Full Text PDFJ Phys Chem A
January 2025
Department of Chemistry and Biochemistry, Shahrood Branch, Islamic Azad University, 36714 Shahrood, Iran.
This study investigates the nature and interplay of noncovalent interactions (NCIs)─tetrel bonds (TB), hydrogen bonds (HB), and halogen bonds (XB)─in molecular assemblies formed between trifluorogermyl hypochlorite (FGeOCl) and hydrogen cyanide (HCN). Using a combination of high-level computational methods, we explored the geometric, energetic, and electronic properties of dimers, trimers, and tetramers formed in different molar ratios of interacting reagents. Various analyses reveal a significant cooperativity between TB and HB, which mutually reinforce each other, while XB interactions are diminished in the presence of TB and HB.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Geneis (Beijing) Co. Ltd., Beijing 100102, China.
Identification of potential drug-target interactions (DTIs) is a crucial step in drug discovery and repurposing. Although deep learning effectively deciphers DTIs, most deep learning-based methods represent drug features from only a single perspective. Moreover, the fusion method of drug and protein features needs further refinement.
View Article and Find Full Text PDFPLoS One
January 2025
The Key Laboratory of Cyber-Physical Power System of Yunnan Universities, Yunnan Minzu University, Kunming, Yunnan Province, China.
Current researches on sodium penetration in electrolytic aluminum cathode carbon blocks primarily measure cathode expansion curves, showing mostly macroscopic characteristics. However, the microscopic structure is often underexplored. As a porous medium, the diffusion performance of cathode carbon blocks is closely tied to their internal pore structure.
View Article and Find Full Text PDFEur Heart J Acute Cardiovasc Care
January 2025
Department of Heart Disease, Haukeland University Hospital, Bergen, Norway.
Background: This prospective, two-centre study derived and validated predictive algorithms for the Siemens Atellica IM high-sensitivity cardiac troponin I (hs-cTnI) assay in the emergency department (ED).
Methods: Algorithms for predicting 30-day myocardial infarction type 1 and 2 (MI) and death or non-ST-elevation myocardial infarction (NSTEMI, type 1 and 2) at index admission were developed from a derivation cohort of 1896 patients and validated using a synthetic dataset with nearly 1 million patient cases. Performance was compared to the European Society of Cardiology algorithms for hs-cTnT (Roche Diagnostics) and hs-cTnI (Abbott Diagnostics).
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