Article
Oncology
Yen-Yun Wang, Pen-Tzu Fang, Chang-Wei Su, Yuk-Kwan Chen, Joh-Jong Huang, Ming-Yii Huang, Shyng-Shiou F. Yuan
Summary: Oral cancer is the fourth most common cancer among males in Taiwan, with poor prognosis for advanced-stage oral squamous cell carcinoma. Research found that high expression of ERCC2 may be a risk factor for OSCC recurrence, and high levels of XRCC1, ERCC1, and ERCC2 proteins are associated with lower survival rates.
Review
Medicine, Research & Experimental
Qiang Liu, Qiu Peng, Bin Zhang, Yueqiu Tan
Summary: Genomic instability is a common feature of tumors, and the XRCC gene family plays an important role in tumor development and therapeutic sensitivity. Studying XRCC can help us better understand the mechanisms of tumor formation and potential treatments.
JOURNAL OF TRANSLATIONAL MEDICINE
(2023)
Article
Biotechnology & Applied Microbiology
Yongfei Fan, Zhaojia Gao, Xinwei Li, Shuzhang Wei, Kai Yuan
Summary: The XRCC4/5/6 genes were found to be overexpressed and associated with poor prognosis in lung adenocarcinoma and lung squamous cell carcinoma. They were also identified as independent risk factors in lung adenocarcinoma. Genetic alterations, methylation, and immune cell infiltration further demonstrated the association of XRCC4/5/6 with poor prognosis. Additionally, KEGG-enriched and NHEJ pathways were shown to be associated with XRCC4/5/6.
Review
Genetics & Heredity
Hamid Reza Mozaffari, Maryam Rostamnia, Roohollah Sharifi, Mohsen Safaei, Elisa Zavattaro, Santosh Kumar Tadakamadla, Mohammad Moslem Imani, Masoud Sadeghi, Amin Golshah, Hedaiat Moradpoor, Farzad Rezaei, Neda Omidpanah, Masoud Hatami
Summary: The meta-analysis found that the T allele and CT genotype of XRCC1 rs1799782 polymorphism were associated with an increased risk of oral cancer, while the G allele and GG genotype of XRCC2 rs2040639 polymorphism were protective against oral cancer.
Review
Oncology
Nawar Al Nasrallah, Benjamin M. Wiese, Catherine R. Sears
Summary: XPC is not only important in skin cancer, but also plays a protective role in non-dermatologic cancers. In addition to its involvement in GG-NER, XPC also participates in other DNA repair pathways, DNA damage response, and transcriptional regulation. XPC expression levels and polymorphisms may impact development and could serve as predictive and therapeutic biomarkers for non-dermatologic cancers.
FRONTIERS IN ONCOLOGY
(2022)
Article
Oncology
Miao Li, Rong Chen, Baoyan Ji, Chunmei Fan, Guanying Wang, Chenli Yue, Guoquan Jin
Summary: This study found that certain single nucleotide polymorphisms within the ERCC5 gene were associated with the risk of non-small cell lung cancer, response to chemotherapy, and risk of toxicity.
Article
Health Care Sciences & Services
Matthew P. Deek, Nikhil Yegya-Raman, Parima Daroui, Sairam Balasubramanian, Jyoti Malhotra, Dirk Moore, Malini Patel, Shang-Jui Wang, Joseph Aisner, Salma K. Jabbour
Summary: In patients with locally advanced NSCLC treated with CRT, higher tumoral ERCC1 expression is associated with worse progression free survival. Additionally, factors such as increasing tumor volume, squamous cell, and poorly differentiated histology may also correlate with worse overall survival. Larger studies are needed to confirm these findings and integrate molecular biomarkers for treatment optimization.
ANNALS OF PALLIATIVE MEDICINE
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Zixing Wang, Cuihong Yang, Wei Han, Xin Sui, Fuling Zheng, Fang Xue, Xiaoli Xu, Peng Wu, Yali Chen, Wentao Gu, Wei Song, Jingmei Jiang
Summary: This study validates the clinical value of promising radiomic features in decoding lung cancer heterogeneity. The features were robust and associated with patient long-term prognosis, cancer profiles, and could predict survival and death risk better than routine characteristics.
INSIGHTS INTO IMAGING
(2022)
Article
Biochemistry & Molecular Biology
Ankita Shukla, Mohammad Afsar, Taran Khanam, Nelam Kumar, Faiz Ali, Sanjay Kumar, Farheen Jahan, Ravishankar Ramachandran
Summary: A novel tri-component BER complex composed of Mtb beta-clamp, MtbXthA, and MtbLigA has been discovered. In the apo complex, MtbXthA binds simultaneously to subsite-I of Mtb beta-clamp through the 239QLRFPKK245 motif and to MtbLigA through the 104DGQPSWSGKP113 motif. However, in the presence of substrate DNA, the complex adopts a less-extended conformation, and MtbXthA interactions switch from predominantly subsite-I to subsite-II of Mtb beta-clamp. This novel tri-component complex prevents futile ligation activity of MtbLigA on the product of MtbXthA and ensures productive mycobacterial BER interactions.
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
(2023)
Article
Crystallography
Andrei Rogalev, Fabrice Wilhelm, Elena Ovchinnikova, Aydar Enikeev, Roman Bakonin, Ksenia Kozlovskaya, Alexey Oreshko, Dai Aoki, Vladimir E. Dmitrienko
Summary: The absorption spectra of a single CeCoGe3 crystal under two orthogonal linearly polarized X-rays near the K-edges of Ge, Co, and the L-23 edges of Ce were measured at the ID12 beamline of the ESRF. X-ray natural linear dichroism (XNLD) was observed near all absorption edges, indicating a splitting of electronic states in a crystalline field. Mathematical modeling and comparison with experimental data allowed determination of the isotropic and anisotropic parts of atomic absorption cross section in CeCoGe3 near all measured absorption edges, showing different anisotropic contributions from Ge atoms in two different Wyckoff positions.
Article
Biochemical Research Methods
Xuechen Li, Linlin Shen, Zhihui Lai, Zhongliang Li, Juan Yu, Zuhui Pu, Lisha Mou, Min Cao, Heng Kong, Yingqi Li, Weicai Dai
Summary: This study aims to solve the cross-domain problem in medical image classification by designing a self-supervised feature-standardization block. The experimental results showed that the feature-standardization block improved the network's domain adaptation performance.
Review
Biochemistry & Molecular Biology
Scarlett Acklin, Fen Xia
Summary: Platinum-based chemotherapy-induced peripheral neuropathy (CIPN) is a common and debilitating complication in cancer treatment, with dorsal root ganglia sensory neurons playing a key role in symptom development. Nucleotide excision repair is crucial for repairing platinum adducts and may serve as potential targets for future therapeutics.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Oncology
Yansong Zheng, Hengce Zhang, Yueting Guo, Yuan Chen, Hanglong Chen, Yingchun Liu
Summary: The study found that knockdown of XRCC1 significantly increased beta-lap-induced DNA double-strand breaks, comet tail lengths, and cell death in PDA cells. Furthermore, combining XRCC1 knockdown with beta-lap treatment switched programmed necrosis with beta-lap monotherapy to caspase-dependent apoptosis.
Article
Biochemistry & Molecular Biology
Jennifer Le, Jung-Hyun Min
Summary: Xeroderma pigmentosum C (XPC) is an important factor in the genome nucleotide excision repair pathway. Mutations in the XPC gene can lead to XP cancer predisposition syndrome, increasing susceptibility to sunlight-induced cancers. The lack of a high-resolution 3D structure for human XPC makes it challenging to assess the impact of mutations/variations on its structure.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Computer Science, Artificial Intelligence
Faizan Karim, Munam Ali Shah, Hasan Ali Khattak, Zoobia Ameer, Umar Shoaib, Hafiz Tayyab Rauf, Fadi Al-Turjman
Summary: Machine learning and computer vision have played important roles in fighting against the COVID-19 pandemic. Radiology has significantly improved the diagnosis of diseases, especially lung diseases. Chest X-rays have become commonly used to detect and diagnose various lung diseases. However, identifying lung disease through X-rays is a challenging task that relies on skilled radiologists. Recent attention has been focused on Convolution Neural Networks (CNN) models for lung disease classification. CNN requires a large amount of training data, but it struggles with translation and rotation inputs. Capsule Networks (CapsNets) have been proposed as a solution to this problem, as they can handle rotation and complex translation. They require less training data, which is beneficial for medical image datasets like chest X-rays. This research explores the adoption and integration of CapsNets in chest X-ray classification, aiming to design a deep model that improves classification accuracy.
APPLIED SOFT COMPUTING
(2022)
