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Autor:
Kensuke Kojima, Hironobu Samejima, Takafumi Iguchi, Toshiteru Tokunaga, Kyoichi Okishio, Hyungeun Yoon
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Accurate prediction of postoperative recurrence is important for optimizing the treatment strategies for non-small cell lung cancer (NSCLC). Previous studies identified the PD-L1 expression in NSCLC as a risk factor for postoperative recurre
Externí odkaz:
https://doaj.org/article/f09de399764244939689da1d7cc5f55d
Autor:
Tian Shi, Jiahe Li, Na Li, Cheng Chen, Chen Chen, Chenjie Chang, Shenglong Xue, Weidong Liu, Ainur Maimaiti Reyim, Feng Gao, Xiaoyi Lv
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Celiac Disease (CD) is a primary malabsorption syndrome resulting from the interplay of genetic, immune, and dietary factors. CD negatively impacts daily activities and may lead to conditions such as osteoporosis, malignancies in the small i
Externí odkaz:
https://doaj.org/article/7cea09804e174416a3f6571b2e8c03c3
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract This study aimed to apply pathomics to predict Matrix metalloproteinase 9 (MMP9) expression in glioblastoma (GBM) and investigate the underlying molecular mechanisms associated with pathomics. Here, we included 127 GBM patients, 78 of whom w
Externí odkaz:
https://doaj.org/article/fe69e75ed1664e789d846cc438c3f42b
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Breast cancer is the most commonly diagnosed cancer among women worldwide. Breast cancer patients experience significant distress relating to their diagnosis and treatment. Managing this distress is critical for improving the lifespan and qu
Externí odkaz:
https://doaj.org/article/cbbb87fb16084d319dd0e3e237a5fbcd
Autor:
Hiroaki Yabuuchi, Makiko Fujiwara, Akihiko Shigemoto, Kazuhito Hayashi, Yuhei Nomura, Mayumi Nakashima, Takeshi Ogusu, Megumi Mori, Shin-ichi Tokumoto, Kazuyuki Miyai
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Plants are valuable resources for drug discovery as they produce diverse bioactive compounds. However, the chemical diversity makes it difficult to predict the biological activity of plant extracts via conventional chemometric methods. In th
Externí odkaz:
https://doaj.org/article/0ec939d20d114895a164dadbe8546229
Autor:
Shuangquan Qing, Chuanxi Li
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-24 (2024)
Abstract The present study introduces a novel approach utilizing machine learning techniques to predict the crucial mechanical properties of engineered cementitious composites (ECCs), spanning from typical to exceptionally high strength levels. These
Externí odkaz:
https://doaj.org/article/65261865f7e749e7a5f03a323962a07c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract Energy consumption of constructed educational facilities significantly impacts economic, social and environment sustainable development. It contributes to approximately 37% of the carbon dioxide emissions associated with energy use and proce
Externí odkaz:
https://doaj.org/article/8b907f2717b548ccae630e91819e55a9
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Predicting physical properties of complex multi-scale systems is a common challenge and demands analysis of various temporal and spatial scales. However, physics alone is often not sufficient due to lack of knowledge on certain details of th
Externí odkaz:
https://doaj.org/article/5b74438be157410abce20b73a90d2fae
Autor:
Sayed Gomaa, Mohamed Abdalla, Khalaf G. Salem, Karim Nasr, Ramadan Emara, Qingsheng Wang, A. N. El-hoshoudy
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-42 (2024)
Abstract The accurate estimation of gas viscosity remains a pivotal concern for petroleum engineers, exerting substantial influence on the modeling efficacy of natural gas operations. Due to their time-consuming and costly nature, experimental measur
Externí odkaz:
https://doaj.org/article/276309e49ec1445da40425975f7c28b6
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract In this work, we combine the advantages of virtual Small Angle Neutron Scattering (SANS) experiments carried out by Monte Carlo simulations with the recent advances in computer vision to generate a tool that can assist SANS users in small an
Externí odkaz:
https://doaj.org/article/d3b8626e67524383b5bf2bef1cf34c04