Evidence for neoadjuvant chemotherapy combined with targeted therapy for locally advanced esophageal squamous cancer (ESCC) is inadequate. We conducted a single-arm phase II trial to evaluate the efficacy and safety of apatinib combined with taxol and cisplatin (ATP) for locally advanced ESCC. All patients were cT3-4aN0-3 M0 (IIIb-IVa) stage, which were confirmed by histopathology. Apatinib was taken orally (425 mg/d) for two cycles, followed by one cycle of rest. Taxol was administered at 135 mg/m intravenously on day 1, and cisplatin was administered at 20 mg/m intravenously on day 1 to day 3. Radical ESCC resection was performed 4 weeks after ATP. The primary endpoint was pathological response rate (pCR). Secondary endpoints were pathologic response rate (MPR), disease-free survival (DFS), overall survival (OS), R0 resection rate, and safety profile. This trial was registered. We evaluated 41 patients for screening from Oct 2018 to July 2020, of whom 39 were enrolled in the study, with a median age of 65 years (range 49-75 years), and 29 (74.4%) were male. Among the 39 patients, 1 was considered unresectable by the multidisciplinary team due to tumor progression, and 38 patients underwent surgery eventually. The median follow-up was 22 months (range 5-29 months), and the follow-up rate was 100%. The 1-year and 2-year OS was 95% and 95%, and the 1-year and 2-year DFS was 85% and 82%, respectively. Thirty-eight (97.3%) successfully underwent R0 resection. Of the 38 evaluable patients, 9 (23.6%) were pCR, and 15 (39.5%) were MPR. The most common ATP-related AEs were nausea (76.9%), leucopenia (53.8%), neutropenia (51.2%) and vomit (51.2%), anemia (41.0%), and hypertension (25.6%). The most frequent grade 3-4 events included leucopenia (15.3%), neutropenia (15.3%), nausea (12.8%), vomit (12.8%), and hypertension (10.2%). No treatment-related death occurred. Neoadjuvant apatinib combined with taxol and cisplatin for locally advanced ESCC showed favorable activity and manageable safety.
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http://dx.doi.org/10.1155/2022/4727407 | DOI Listing |
J Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
View Article and Find Full Text PDFMed Mol Morphol
January 2025
Faculty of Advanced Techno-Surgery (FATS), Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, 8-1 Kawada-Cho, Shinjuku, Tokyo, 162-8666, Japan.
This study evaluates the effects of different high-intensity focused ultrasound irradiation (HIFU) methods on local tumor suppression and systemic antitumor effects, including the abscopal effect, in a mouse model of pancreatic cancer. To ascertain the efficacy of the treatment, pancreatic cancer cells were injected into the thighs of mice and HIFU was applied on one side using continuous waves or trigger pulse waves. Then, tumor volume, tissue changes, and immune marker levels were analyzed.
View Article and Find Full Text PDFNat Methods
January 2025
Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
Teravoxel-scale, cellular-resolution images of cleared rodent brains acquired with light-sheet fluorescence microscopy have transformed the way we study the brain. Realizing the potential of this technology requires computational pipelines that generalize across experimental protocols and map neuronal activity at the laminar and subpopulation-specific levels, beyond atlas-defined regions. Here, we present artficial intelligence-based cartography of ensembles (ACE), an end-to-end pipeline that employs three-dimensional deep learning segmentation models and advanced cluster-wise statistical algorithms, to enable unbiased mapping of local neuronal activity and connectivity.
View Article and Find Full Text PDFInt J Biometeorol
January 2025
University College of Applied Sciences in Chełm, Pocztowa 54, Chełm, 22-100, Poland.
In this study, a relationship between climate indices (local - air temperatures, and wide-scale - North Atlantic Oscillation) and first arrival dates (FAD) of a short-distant migratory bird, the Common Wood Pigeon (Columba palumbus) at a breeding site in SE Poland (Lublin) was investigated. Temporal patterns of FAD on a multi-year scale (20 years within 39 years between 1982 and 2020) were also studied. Additionally, correlations between mean air temperature at Lublin and sites along the spring migration route with various distances from the breeding site and various time lags were searched for.
View Article and Find Full Text PDFActa Pharmacol Sin
January 2025
Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
Computational target identification plays a pivotal role in the drug development process. With the significant advancements of deep learning methods for protein structure prediction, the structural coverage of human proteome has increased substantially. This progress inspired the development of the first genome-wide small molecule targets scanning method.
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