Article
Engineering, Biomedical
Samira Aghlara-Fotovat, Elena Musteata, Michael D. Doerfert, Moshe Baruch, Maya Levitan, Jeffrey J. Tabor, Omid Veiseh
Summary: Researchers have discovered that encapsulating bacteria in alginate core-shell particles enhances their survival ability in vivo, enabling them to sense and report disease biomarkers in the gastro-intestinal tract. This study holds promise for the development of next-generation smart therapeutics and non-invasive monitoring of various diseases.
Article
Cell Biology
Ria Uhlig, David Dum, Natalia Gorbokon, Anne Menz, Franziska Buescheck, Andreas M. Luebke, Claudia Hube-Magg, Andrea Hinsch, Doris Hoeflmayer, Christoph Fraune, Katharina Moeller, Christian Bernreuther, Patrick Lebok, Soren Weidemann, Maximilian Lennartz, Frank Jacobsen, Till S. Clauditz, Guido Sauter, Waldemar Wilczak, Stefan Steurer, Eike Burandt, Rainer Krech, Till Krech, Andreas H. Marx, Ronald Simon, Sarah Minner
Summary: The expression of neuroendocrine markers synaptophysin and chromogranin A was examined in various tumor types. These markers were found to be positive in a high percentage of neuroendocrine neoplasms. However, their expression in non-neuroendocrine tumors was less common. Neuroendocrine differentiation was most commonly observed in certain adenocarcinomas, such as those in the female genital tract, pancreatico-/hepato-/biliary tract, and the prostate. The presence of neuroendocrine markers did not seem to correlate with tumor aggressiveness in several types of cancers.
MOLECULAR AND CELLULAR ENDOCRINOLOGY
(2022)
Article
Pharmacology & Pharmacy
L. Romano, A. Giuliani, V. Vicentini, M. Schietroma, F. Carlei
Summary: Pancreatic neuroendocrine tumors are primarily found in the pancreas and upper small intestine. Most pNETs are non-functional, and immunohistochemistry is essential for diagnosis, with Chromogranin A and synaptophysin considered the most specific markers.
EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES
(2021)
Review
Chemistry, Analytical
Mai Tharwat, Nehal A. A. Sakr, Shaker El-Sappagh, Hassan Soliman, Kyung-Sup Kwak, Mohammed Elmogy
Summary: The diagnosis and treatment of colon cancer pose significant social and economic challenges. This article provides a comprehensive survey on the diagnosis of colon cancer, covering aspects such as symptoms, grades, imaging modalities, and diagnosis systems. Deep-learning and machine-learning techniques are highlighted for their potential in early cancer detection and reducing mortality rates. Screening tests and polyp removal are also discussed as preventive measures. Challenges and future research directions are identified.
Article
Medicine, General & Internal
Pedro Guimaraes, Helen Finkler, Matthias Christian Reichert, Vincent Zimmer, Frank Gruenhage, Marcin Krawczyk, Frank Lammert, Andreas Keller, Markus Casper
Summary: This study developed AI-based algorithms to differentiate inflammatory bowel disease (IBD) from other colitis types using endoscopic images and clinical data. The image-based algorithm had lower accuracy compared to the clinical data-based algorithm, suggesting the need for larger image datasets for better performance.
EUROPEAN JOURNAL OF CLINICAL INVESTIGATION
(2023)
Article
Biology
Tao Jiang, Xiao-jing Guo, Li-ping Tu, Zhou Lu, Ji Cui, Xu-xiang Ma, Xiao-juan Hu, Xing-hua Yao, Long-tao Cui, Yong-zhi Li, Jing-bin Huang, Jia-tuo Xu
Summary: The study developed models for early diagnosis of NAFLD using computer tongue image analysis technology and machine learning methods, achieving high accuracy and sensitivity in diagnosis.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Immunology
Zhen Ye, Huanhuan Zhang, Jianwei Liang, Shuying Yi, Xianquan Zhan
Summary: This study aimed to identify prognostic biomarkers of colon cancer and establish a logistic regression scoring model to predict its prognosis. Results showed that ULBP2 was significantly overexpressed in colon cancer tissues and cell lines. The logistic regression scoring model, based on six statistically significant features, effectively predicted the 3-year survival time. The high-risk score group had a poorer prognosis, higher tumor mutation burden, lower M0 macrophage infiltration score, and higher IC50 value of oxaliplatin.
FRONTIERS IN IMMUNOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Hend Okasha, Safia Samir, Sami Mohamed Nasr
Summary: This study successfully expressed the recombinant human CGA-N46 peptide with wide-spectrum antibacterial, fungal, and anticancer activities. The purified rhCGA-N46 peptide showed safety on normal cells and significant anticancer effects on colon cancer cells, potentially through regulating apoptotic signal pathways.
BIOORGANIC CHEMISTRY
(2021)
Article
Biochemistry & Molecular Biology
Mayidili Nijiati, Renbing Zhou, Miriguli Damaola, Chuling Hu, Li Li, Baoxin Qian, Abudukeyoumujiang Abulizi, Aihemaitijiang Kaisaier, Chao Cai, Hongjun Li, Xiaoguang Zou
Summary: An artificial intelligence model for differential diagnosis of active pulmonary tuberculosis (ATB) has been developed, utilizing computer tomography (CT) scans and deep learning models. The 3D ResNet-50 model outperformed other models and achieved higher diagnostic accuracy than experienced radiologists, with a reading and diagnosing speed 10 times faster than human experts. The model is also capable of visualizing clinician interpretable lung lesion regions important for differential diagnosis.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Quentin Fillias, Ingrid Millet, Boris Guiu, Celine Orliac, Fernanda Curros Doyon, Lucie Gamon, Nicolas Molinari, Patrice Taourel
Summary: This study developed a simple risk scoring system to predict the risk of severe ischemic colitis. The scoring system showed good discrimination capability in both internal and external validation and can stratify patients into different prognosis groups, optimizing patient management.
EUROPEAN RADIOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Frederico Barbosa Muniz, Matheus de Freitas Oliveira Baffa, Sergio Britto Garcia, Luciano Bachmann, Joaquim Cezar Felipe
Summary: This study investigates the possibility of using hyperspectral images acquired over micro-FTIR absorbance spectroscopy to characterize healthy, inflammatory, and tumor colon tissues. The results show that deep learning and hyperspectral images can accurately characterize such tissues, indicating that the infrared spectrum contains relevant information.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Oncology
Katharina Kriegsmann, Christiane Zgorzelski, Thomas Muley, Petros Christopoulos, Michael Thomas, Hauke Winter, Martin Eichhorn, Florian Eichhorn, Moritz von Winterfeld, Esther Herpel, Benjamin Goeppert, Albrecht Stenzinger, Felix J. F. Herth, Arne Warth, Mark Kriegsmann
Summary: A study of 1170 cases found that neuroendocrine markers synaptophysin, chromogranin, and CD56 are commonly expressed in pulmonary adenocarcinoma and squamous cell carcinoma, but their expression does not impact survival outcomes, aligning with current best practice guidelines.
Article
Oncology
Rayed AlGhamdi, Turky Omar Asar, Fatmah Y. Assiri, Rasha A. Mansouri, Mahmoud Ragab
Summary: This article presents a transfer learning approach for lung and colon cancer detection using histopathological image analysis. The experimental results demonstrate the promising performance of the proposed model in diagnosing lung and colon cancer.
Article
Oncology
Hanan Abdullah Mengash, Mohammad Alamgeer, Mashael Maashi, Mahmoud Othman, Manar Ahmed Hamza, Sara Saadeldeen Ibrahim, Abu Sarwar Zamani, Ishfaq Yaseen
Summary: The timely and initial diagnosis of cancer is crucial for reducing the possibility of death. Deep learning and machine learning methods can accelerate cancer recognition and provide a cost-effective way for examination. This study introduces a technique called MPADL-LC3 which uses a marine predator's algorithm with deep learning to properly classify different types of lung and colon cancer based on histopathological images.
Article
Endocrinology & Metabolism
Stefanie Parisien-La Salle, Mathieu Provencal, Isabelle Bourdeau
Summary: The study found that CgA is a sensitive marker for diagnosing PHEO and thoracoabdominal paragangliomas. Additionally, CgA may have potential in monitoring nonfunctional PGLs as a tumor marker, as well as complementary role in early detection of recurrence in secreting PPGLs.
ENDOCRINE PRACTICE
(2021)