Results 251 to 260 of about 2,170,450 (367)

RADA16 and SAAP148 Peptide‐Modified Collagen Self‐Assembled Hydrogels for Accelerated Healing of Infected Wounds

Advanced Science, EarlyView.
Collagen type I (Col I) is integrated with self‐assembling peptide RADA16 and loaded with anti‐bacterial peptide SAAP148 to develop a self‐assembled nano‐microstructure hydrogel (Col I‐RADA16‐SAAP148, CRS) without chemical cross‐linkers. CRS exhibits excellent mechanical properties, sustained SAAP148 release to inhibit bacterial infection, macrophage ...
Qian Liu, Jiawei Wu, Ho‐Pan Bei, Yufei Chen, Yifan Zhang, Xueliang Peng, Fulin Chen, Xin Zhao, Zhuoyue Chen   +8 more
wiley   +1 more source

Kidney transplantation and statins effects on dyslipidemia in kidney transplant recipients. [PDF]

Ann Med Surg (Lond)
Arabi Z, Tawhari M, Arabi T, Alaklabi A, Fallatah W, Sabbah B, Alghamdi A, Alnasrullah A, Shafqat A.   +8 more
europepmc   +1 more source

Guillain-Barré Syndrome Secondary to Cytomegalovirus Infection in a Pediatric Kidney Transplant Patient

D. Lopes, Iracy de Oliveira Araújo, Rodrigo Melo Gallindo, Cassio Tâmara Ribeiro, Paula Andréa dos Santos Genesio   +4 more
openalex   +1 more source

All Nanozyme‐Based Cascade Reactions for Biomedical Applications: from Self‐Cascading Nanozyme to Immobilized Cascade Nanozyme

Advanced Science, EarlyView.
This review introduces the development and classification of all‐nanozyme cascade reaction systems, highlighting mechanistic insights and research methods for understanding catalytic features and design principles. It provides detailed classifications, surveys recent applications in biosensing and therapy, and discusses the challenges that all‐nanozyme
Caixia Zhu, Congcong Jiang, Hian Kee Lee, Yuanjian Zhang, Sheng Tang   +4 more
wiley   +1 more source

Immune Monitoring Goes Viral - Torque Teno Virus for Immunologic Risk Stratification After Kidney Transplantation. [PDF]

Transpl Int
Doberer K, Kapps S, Haupenthal F, Bond G.   +3 more
europepmc   +1 more source

Pregnancy in chronic kidney disease and kidney transplantation.

Kidney International, 2017
P. Webster, L. Lightstone, D. McKay, M. Josephson   +3 more
semanticscholar   +1 more source

Colorectal Cancer Cell's Weapon: RNF32 Engages SPP1+ Macrophages to Foster Liver Metastasis, Targeted by Indole‐3‐Acetic Acid

Advanced Science, EarlyView.
Cytoplasmic RNF32 fuels CRC liver metastasis by degrading GSK3β, which stabilizes β‐catenin and activates Wnt/EMT. Moreover, RNF32 rewires the metastatic niche: it depletes CD8+/CD4+ T and NK cells while recruiting SPP1+ macrophages (which boost tumor stemness via CD44), fibroblasts, and immunosuppressive monocytes to aid colonization.
Hongyu Wang, Shipeng Dai, Yuchen Xie, Pengyu Chen, Yue Chai, Chongyu Wang, Xueying Huang, Xiao Dong, Junfeng Shi, Yongxiang Xia, Xiaofeng Qian, Weiwei Tang, Yichan Zhou   +12 more
wiley   +1 more source

Rituximab in antibody-mediated rejection following kidney transplantation: clinical and pathological outcomes. [PDF]

BMC Nephrol
Yilmaz B, Uslu A, Taşli F, Durusoy R, Doğan SM, Okut G, Uğur MA, Kocabaş E.   +7 more
europepmc   +1 more source

Assessing antiviral treatment efficacy and risk factors for severe COVID-19 in kidney transplant recipients during the Omicron subvariant-dominant period: a retrospective study [PDF]

Takashi Sakaguchi, Akihiko Mitsuke, Yoichi Osako, Yasutoshi Yamada, Himawari Takeyama, Risako Ogawa, Katsuya Takahashi, Yukiko Hirohata, Sayuri Yamamoto, Junya Arima, Wataru Fukumoto, Satoshi Sugita, Satoru Inoguchi, Ryosuke Matsushita, Hirofumi Yoshino, Shuichi Tatarano, Hideki Enokida   +16 more
openalex   +1 more source

Which Method Best Predicts Postoperative Complications: Deep Learning, Machine Learning, or Conventional Logistic Regression?

Annals of Gastroenterological Surgery, EarlyView.
Deep learning has shown promise in predicting postoperative complications, particularly when using image or time‐series data. However, on tabular clinical data such as the NCD, it often underperforms compared to conventional machine learning. Integrating multimodal data may enhance predictive accuracy and interpretability in surgical care.
Ryosuke Fukuyo, Masanori Tokunaga, Hiroyuki Yamamoto, Hideki Ueno, Yusuke Kinugasa   +4 more
wiley   +1 more source