Shiying Tang
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Multimodal deep learning model for AI-based functional prognostic risk stratification in patients undergoing radical nephrectomy
Abstract Making the decision between technically challenging partial nephrectomy (PN) and radical nephrectomy (RN) in patients with complex renal cell carcinoma (RCC) remains a significant challenge for urologists. Rapid glomerular filtration rate (GFR) decline (annual decline >3 mL/min/1.73 m²) after RN is considered an abnormal renal function state, and if this risk can be predicted preoperatively, PN may be pursued even when technically demanding.
The mannose receptor on sinusoidal lining cells mediates two-step bacterial clearance in the human spleen
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Abstract The human spleen plays a critical role in clearing bacteria from the bloodstream, particularly during septicaemia; yet the cellular mechanisms underlying this function remain poorly defined. Using a dual translational approach including ex vivo perfusion of human spleens and splenic primary cell cultures, we identify a previously unrecognised division of tasks in splenic antibacterial defence.
By Tareq Al Saoudi, Giulia Cattabriga, Daniele Ghezzi, Ryan G Hames, John Isherwood, Trisha Kanani, Zydrune Jasiunaite, Shiying Tang, Giuliana Germinario, Giorgia Radi, Francesca M. Rizzo, Katrin Schilcher, Christopher Bayliss, Romina Camilli, Marco Caprini, Carola Parolin, Wen Y Chung, Giuseppe Garcea, Enrico Giampieri, Gastone Castellani, Kornelis R Straatman, Stefano Bruno, Claudia Trappetti, Matteo Ravaioli, Ashley Dennison, Luisa Martinez-Pomares, Marco R. Oggioni, Neama Alnabati, Francesco Flandi, Talia Richardson, Alessia Gennai, Stefano Fedi
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Nature
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T-bet+CD8+ T cells govern anti-PD-1 responses in microsatellite-stable gastric cancers - Nature Communications
Abstract More than 90% of advanced gastric cancers (GC) are microsatellite-stable (MSS). Compared to the high response rate of immune checkpoint inhibitors (ICI) in microsatellite-instability-high (MSI-H) GCs, only 10% of unstratified MSS GCs respond to ICIs. In this study, we apply semi-supervised learning to stratify potential ICI responders in MSS GCs, achieving high accuracy, quantified by an area under the curve of 0.924.
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