Publications by authors named "Shi-Fu Chen"
Article Synopsis
- Patients with polymerase epsilon/polymerase delta mutations showed some positive responses to toripalimab, an immune checkpoint inhibitor, with a 21.4% overall response rate and a 57.1% disease control rate in a small clinical trial.
- * The trial included 15 patients with advanced solid tumors, out of which 14 were evaluated, revealing differing response rates based on the type of mutation — 66.7% for exonuclease domain mutations compared to 9.1% for non-exonuclease domain mutations.
- * The presence of PBRM1 gene mutations correlated with a high response rate (75.0%), indicating that more research is needed to better understand how different mutations affect the effectiveness of
Article Synopsis
- The study investigated genetic changes in rare pancreatic tumors like schwannoma and neurofibroma using tumor samples from three patients who had surgery.
- Exome sequencing of one schwannoma revealed a potentially harmful MUTYH variant along with notable changes in NF2 and NOTCH1 genes, whereas the other schwannoma showed issues related to DNA repair and cell cycle processes.
- The neurofibroma presented different genetic alterations, including deletions and amplifications in NF1, TP53, and ERBB3, indicating that these genetic variants might contribute significantly to the development of these pancreatic tumors.
Article Synopsis
- The study investigates the separation mechanisms of photoexcited carriers in composite photocatalysts, focusing on Ag3PO4/g-C3N4 nanocomposites synthesized through a simple precipitation method.
- The photocatalysts were characterized using various techniques, and their effectiveness was tested by degrading methylene blue under visible light; results showed that the composition of the nanocomposite affects its photocatalytic activity.
- When g-C3N4 is the main component, a Z-scheme mechanism enhances photocatalytic performance, while Ag3PO4 as the main part leads to reduced activity; the study aims to provide insights for designing efficient photocatalysts.
Profile distribution characteristics of organic carbon (C), total nitrogen (N), total phosphorus (P) and total sulfur (S) were studied in two typical marshes including Carex lasiocarpa marsh and Phragmites australis marsh in the Sanjiang Plain. Sedimentary characteristics of typical mashes were analyzed. The results showed that vertically these soil chemical elements also varied, showing obvious stratification and enrichment.
View Article and Find Full Text PDFThe best performance of the phosphor Li(2)SrSiO(4): Eu(2+), Ce(3+) in terms of luminescence efficiency (LE), color rendering index (CRI) and color temperature (Tc) for light-emitting diode application was optimized with combinatorial approach. The combinatorial libraries were synthesized with solution-based method and the scale-up samples were synthesized with conventional solid-reaction method. Crystal structure was investigated by using the X-ray diffraction spectrometer.
View Article and Find Full Text PDF[Seasonal dynamics of hydrochemical characteristics of streams under different forest types].
Ying Yong Sheng Tai Xue Bao
April 2008
Article Synopsis
- Stream water samples were collected monthly from March to October 2006 in Liangshui Nature Reserve to study hydrochemical characteristics across different forest types.
- Major cations found were ranked as Ca2+ > Na+ > K+ > Mg2+, while anions followed the order HCO3(-) > SO4(2-) > NO3(-) > Cl(-).
- The spruce-fir forest had higher average contents of Na+, Ca2+, Mg2+, Fe2+, and Fe3+, while K+ was highest in the larch plantation, which also showed the highest average monthly anion content.
[Implementation and application of a digital cytopathological lung cancer diagnosing system].
Zhonghua Wai Ke Za Zhi
October 2007
Objective: To evaluate the efficacy of the digital cytopathological lung cancer diagnosing system (DCLCDS) utilizing the latest computer technologies (including reinforcement learning, image segmentation and classifier) and the cytopathological knowledge on lung cancer cells.
Methods: Separate the overlapped lung cancer cells in a slice image applying the improved deBoor-Cox B-Spline algorithm; Segment cell regions in a slice image using an image segmentation algorithm based on reinforcement learning; Ensemble different classifiers, including Decision Tree classifier, Support Vector Machine (SVM) classifier and Bayesian classifier, to achieve an accurate result of cytopathological lung cancer diagnosis.
Results: The accurate diagnosis rate for lung cancer identification of 224 images of small lung lesions aspiration biopsy from 120 cases randomly selected was 92.
The study on the profile distribution and accumulation characteristics of organic carbon (C) and total nitrogen (N) in two typical marshes in Sanjiang Plain showed that on the sediment profiles of Carex lasiocarpa marsh and Phragmites communis marsh, there existed distinct deposition horizon and illuviation horizon. In deposition horizon (0-60 cm), the average contents of organic C and total N were about 96 and 184 g x kg(-1), and 7.4 and 17.
View Article and Find Full Text PDFTiO2/beads as a photocatalyst for the degradation of X3B azo dye.
J Environ Sci (China)
January 2003
The feasibility of photocatalytic degradation of X3B azo dye by TiO2/beads photocatalyst was studied. The effects of parameters such as the amount of TiO2/beads, airflow, as well as the concentrations of H2O2, Fe3+, Mg2+ and Na+ on the photocatalytic degradation of X3B azo dye were also studied. The results showed that 25 mg/dm3 X3B azo dye can be photocatalytically degraded completely by 30 min illumination with a 375W medium pressure mercury lamp.
View Article and Find Full Text PDFLung cancer cell identification based on artificial neural network ensembles.
Artif Intell Med
January 2002
Article Synopsis
- An artificial neural network ensemble uses multiple networks to solve problems, and in this paper, it’s applied to detect lung cancer in biopsy images.
- The proposed method, Neural Ensemble-based Detection (NED), employs a two-level architecture where the first level confidently identifies normal versus cancer cells.
- The second level further classifies detected cancer cells into specific lung cancer types while prioritizing accuracy to minimize missed diagnoses, thus enhancing patient outcomes.