Results 191 to 200 of about 22,032 (297)

Carcinoembryonic Antigen Messenger RNA in Pelvic Lavage Fluid Predicts Local Recurrence After Curative‐Intent Resection of Rectal Cancer

Annals of Gastroenterological Surgery, EarlyView.
Pelvic lavage carcinoembryonic antigen (CEA) mRNA was quantified in 178 patients undergoing curative‐intent resection for rectal cancer. Positive pelvic lavage CEA mRNA was significantly associated with local recurrence and provided additional prognostic information beyond circumferential resection margin (CRM) status.
Hiroyuki Asai, Yushi Yamakawa, Kazuyoshi Shiga, Shuhei Uehara, Akira Kato, Takuya Suzuki, Hajime Ushigome, Hiroki Takahashi, Yoichi Matsuo, Shuji Takiguchi   +9 more
wiley   +1 more source

Synergistic bactericidal and anticancer potential of rubidium and silver-containing phosphate-based bioglasses. [PDF]

Sci Rep
Bosca M, Bolundut LC, Pop L, Lucacel-Ciceo R, Stiufiuc G, Badila RF, Lupan I, Koblicska OR, Onaciu A, Cenariu D, Țigu AB, Katona G, Simedru D, Pascuta P.   +13 more
europepmc   +1 more source

Interaction Between Operator and Assistant Certification Is Associated With Local Recurrence After Laparoscopic Rectal Cancer Surgery: An Ancillary Analysis of the EnSSURE Study

Annals of Gastroenterological Surgery, EarlyView.
A significant synergistic interaction between operator and assistant certification was associated with a lower risk of local recurrence after laparoscopic rectal cancer surgery. Patients treated by both ESSQS‐qualified operators and assistants had the lowest risk of local recurrence, whereas a single qualification alone was not associated with a ...
Yusuke Sakimura, Hiroyuki Bando, Koya Hida, Tatsunari Fukuoka, Tohru Funakoshi, Fuminori Teraishi, Kay Uehara, Yuji Inoue, Nobuaki Suzuki, Nobuki Ichikawa, Hiroaki Iijima, Akinobu Taketomi, Yoshiharu Sakai, Takeshi Naitoh, Ichiro Takemasa, the EnSSURE study group collaboratives within the Japan Society of Laparoscopic Colorectal Surgery, Akinobu Furutani, Akiyoshi Kanazawa, Akiyoshi Noda, Atsushi Ishibe, Chikayoshi Tani, Daisuke Yamamoto, Fumihiko Fujita, Fumio Ishida, Fumitaka Asahara, Heita Ozawa, Hideaki Karasawa, Hideki Osawa, Hiroaki Nagano, Hiroaki Takeshita, Hirofumi Ota, Hirokazu Suwa, Hiroki Ochiai, Hiroomi Ogawa, Hiroshi Saeki, Hirotoshi Hasegawa, Hisanaga Horie, Hisashi Nagahara, Jun Watanabe, Kaori Hayashibara, Kazuhiro Takehara, Ken Kojo, Ken Okamoto, Kenichiro Saito, Koji Ikeda, Koji Munakata, Koki Otsuka, Koki Goto, Kunihiko Nagakari, Mamoru Uemura, Manabu Shimomura, Manabu Shiozawa, Manabu Takata, Manabu Yamamoto, Masaaki Ito, Masafumi Inomata, Masahiko Watanabe, Masakatsu Numata, Masashi Miguchi, Masatsune Shibutani, Mayumi Ozawa, Mitsuhisa Takatsuki, Naoya Aisu, Naruhiko Sawada, Ryo Ikeshima, Ryo Inada, Ryuichi Oshima, Satoshi Maruyama, Shigehiro Kojima, Shigeki Yamaguchi, Shigenori Homma, Shiki Fujino, Shinichiro Mori, Shinobu Ohnuma, Sho Takeda, Shota Aoyama, Shuji Saito, Shunpei Mukai, Shusaku Takahashi, Takahiro Sasaki, Takahiro Yamanashi, Takeru Matsuda, Takuya Miura, Tatsunori Ono, Tatsuya Kinjo, Tatsuya Shonaka, Teni Godai, Tomohiro Adachi, Tomohiro Yamaguchi, Tomohisa Furuhata, Tomonori Akagi, Toshimoto Kimura, Toshisada Aiba, Toshiya Nagasaki, Toshiyoshi Fujiwara, Tsukasa Shimamura, Tsunekazu Mizushima, Yasuhito Iseki, Yasuo Sumi, Yasushi Rino, Yasuyuki Kamada, Yohei Kurose, Yoshiaki Kita, Yoshihiro Kakeji, Yoshihiro Takashima, Yoshihito Ide, Yoshinori Munemoto, Yoshito Akagi, Yoshiyuki Ishii, Yuki Kiyozumi, Yukihito Kokuba, Yukitoshi Todate, Yusuke Sakimura, Yusuke Shimodaira, Yusuke Suwa   +114 more
wiley   +1 more source

Severe Multivessel Coronary Artery Disease in an Adolescent With Genetic Dyslipidemia. [PDF]

JACC Case Rep
Thorsen V, Slim G, Saskikumar N, Bainey KR, Chan AYM, Hegele RA, Khoury M.   +6 more
europepmc   +1 more source

Machine learning–driven design of catalytic processes for sulfur dioxide oxidation: Lessons from the trenches

AIChE Journal, EarlyView.
Abstract Despite the growing use of ML in chemical engineering, the catalytic conversion of sulfur dioxide (SO2) to sulfur trioxide (SO3) remains underexplored from a data‐driven modeling perspective. This study evaluates an integrated workflow for literature‐derived SO2 oxidation data, combining data curation, preprocessing assessment, machine ...
Farough Agin, Jules Thibault, Clémence Fauteux‐Lefebvre   +2 more
wiley   +1 more source

Synthesis and crystal structure of NaRbB₅O₈(OH)·H₂O. [PDF]

Acta Crystallogr E Crystallogr Commun
Zhang XY, Xiao HL, Zhou XL, Zou MJ, Cheng JW, Wen YH.   +5 more
europepmc   +1 more source

Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring

Advanced Intelligent Discovery, EarlyView.
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira, Marcos de C. Leite, Pedro H. M. Zanineli, Juliana N. Y. Costa, Débora M. Cunha, Sophia P. Serra, Pedro H. Sophia, Flávio M. Shimizu, Yasmin W. Moura, Célio C. Oliveira, Gabriel R. Schleder, Gabriela F. Persinoti, Leandro Merces, Renato S. Lima   +13 more
wiley   +1 more source

Radiation stability and performance of TEHDGA resin for theranostic scandium radionuclide purification. [PDF]

EJNMMI Radiopharm Chem
Zabolockis RJ, Mamis E, Pakalniete LD, Avotina L, Bertins M, Sadauskis J, Semjonova A, Sadło J, Rzepna M, Proskurins J, Pajuste E.   +10 more
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source