Results 131 to 140 of about 9,181 (247)

Human Urine Stem Cells Alleviate Pulmonary Fibrosis via Inhibiting Macrophage‐Myofibroblast Transition

Advanced Science, EarlyView.
Therapeutic role and mechanism of human urine stem cells (hUSCs) in pulmonary fibrosis. hUSCs alleviated pulmonary fibrosis by selectively inhibiting macrophage‐myofibroblast transition (MMT) in two ways: on one hand, hUSCs inhibited mitochondrial reactive oxygen species (mtROS) production and apoptosis/senescence of epithelial cells in pulmonary ...
Zhou‐Hang Zhang, Guan‐Lin Guo, Xiao‐Hui Guan, Min Hu, Qi‐Ming Huang, Ding‐Wen Guo, Hao‐Cheng Gu, You‐Qiong Zhuo, Ning Li, Hong‐Bo Xin, Ke‐Yu Deng   +10 more
wiley   +1 more source

Analyzing the performance of multimodal large language models on visually-based questions in the Japanese National Examination for Dental Technicians. [PDF]

J Dent Sci
Mine Y, Taji T, Okazaki S, Takeda S, Peng TY, Shimoe S, Kaku M, Nikawa H, Kakimoto N, Murayama T.   +9 more
europepmc   +1 more source

From Materials to Medical Images: Translating Perovskite‐Based X‐Ray Detectors Toward Clinical Imaging

Advanced Science, EarlyView.
This review examines perovskite‐based X‐ray detectors from a materials‐to‐medical‐images perspective. Recent progress in perovskite‐based X‐ray detectors is discussed with emphasis on their relevance to clinical imaging. The key barriers to clinical implementation are analyzed.
Sibin Wang, Yongrui Yang, Kun Zhang, Xiaojuan Lu, Hong Yin, Yali Qiao, Xiaojia Zheng, Xiao Zhang, Yanlin Song   +8 more
wiley   +1 more source

A Blood‐Derived Double‐Network Hydrogel with Robust Wet Adhesion for Keratinized Mucosa Regeneration via Neutrophil Phenotype Reprogramming and Mechanophysical Niche Modulation

Advanced Science, EarlyView.
The iPRF‐MA/Alg‐NHS/Lut@EGCG (PGAE) double‐network hydrogel achieves durable wet adhesion in the oral environment. It simultaneously reprograms neutrophils from NETosis to phagocytosis for biofilm clearance, and activates the FAK‐RhoA‐YAP mechanotransduction pathway in gingival fibroblasts to drive extracellular matrix remodeling, thereby promoting ...
Sicong Ren, Xinting Yang, Jingxia Chen, Yihan Wang, Jian Feng, Jing Zhou, Jiaxin Luo, Jingjie Zhai, Quan Lin, Yanmin Zhou   +9 more
wiley   +1 more source

The current considerations in the fabrication of implant prostheses and the state of prosthetic complications: A survey among the dental technicians. [PDF]

Saudi Dent J, 2018
Al Dosari AAF, Habib SR, Alnassar T, Alshihri A, Kamalan R.   +4 more
europepmc   +1 more source

Annual Report of the 2022 National Clinical Database: Decade‐Long Trends and Current Status of Gastroenterological Surgery in Japan

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim The National Clinical Database (NCD) of Japan is the largest nationwide registry, covering over 95% of surgeries in the country. This 2022 annual report summarizes the short‐term outcomes of gastroenterological surgeries and discusses trends and insights over the past decade.
Koshi Kumagai, Arata Takahashi, Hideki Ueno, Naoki Hiki, Yoshiki Kajiwara, Tomoki Ebata, Takao Otsuka, Taro Oshikiri, Yoshihiro Kakeji, Takanori Goi, Akio Saiura, Hiroshi Saeki, Chie Tanaka, Masanori Tokunaga, Tsutomu Fujii, Satoru Matsuda, Tsunekazu Mizushima, Hiroyuki Yamamoto, Yuko Kitagawa, Ken Shirabe   +19 more
wiley   +1 more source

Survival Outcomes of Gemcitabine–Cisplatin–S‐1 Versus Gemcitabine–Cisplatin in Unresectable Biliary Tract Cancer: A Multicenter Retrospective Study With a Focus on Conversion Surgery

Annals of Gastroenterological Surgery, EarlyView.
In this multicenter retrospective study conducted by the Biliary Tract Club, we compared survival outcomes between gemcitabine–cisplatin–S‐1 (GCS) and gemcitabine–cisplatin (GC) in patients with unresectable biliary tract cancer, with a particular focus on conversion surgery. GCS was associated with longer overall and progression‐free survival compared
Hisashi Kosaka, Masahiko Kinoshita, Satoshi Yasuda, Satoru Kakizaki, Rie Sugimoto, Jun Sakata, Kiyonori Yamai, Takeshi Hatanaka, Yusuke Yamamoto, Toshifumi Sato, Toru Ishikawa, Takanori Morikawa, Jun Hanaoka, Haruki Mori, Hidenori Toyoda, Tsuyoshi Sanuki, Misaki Yokoi, Hiroyuki Shibata, Koji Fukuda, Kazuhito Kawata, Koji Amaya, Takashi Ito, Masaaki Hidaka, Atsushi Naganuma, Keishi Sugimachi, Satoshi Toshiyama, Makoto Yamasaki, Masaki Kaibori   +27 more
wiley   +1 more source

Rethinking Perioperative Corticosteroids in Esophageal Cancer Surgery: Evidence From an Integrative Meta‐Analysis

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Esophagectomy remains a highly invasive procedure associated with substantial postoperative morbidity. Pulmonary complications, anastomotic leakage, and in‐hospital mortality are of particular concern. Perioperative corticosteroids are often administered to attenuate excessive inflammatory responses; however, the clinical impact in ...
Tomohiko Yasuda, Akihisa Matsuda, Nobutoshi Hagiwara, Yoshiharu Nakamura, Hiroshi Yoshida   +4 more
wiley   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source