Results 221 to 230 of about 1,033,712 (285)

Prognostic Significance of Portal Vein Tumor Thrombus in Pancreatic Ductal Adenocarcinoma Treated With Chemoradiotherapy

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim To examine the significance of portal vein tumor thrombus (PVTT) as a prognostic factor for patients with pancreatic ductal adenocarcinoma (PDAC) treated with chemoradiotherapy (CRT) followed by surgery. Methods The study retrospectively examined 313 patients with borderline resectable (BR) or locally advanced (LA) PDAC who underwent CRT ...
Aoi Hayasaki, Motonori Nagata, Miki Usui, Hiroshi Imai, Yusuke Iizawa, Akihiro Tanemura, Yasuhiro Murata, Naohisa Kuriyama, Masashi Kishiwada, Shugo Mizuno   +9 more
wiley   +1 more source

Mirror Effect of Parvalbumin and Connexin 43 Expression in the Acute and Subacute Phases After Penetrating Traumatic Brain Injury Reveals a Non-Canonical Interaction. [PDF]

Molecules
Kit O, Kirichenko E, Bachurin S, Nabiullina R, Nwosu C, Sakun P, Rodkin S.   +6 more
europepmc   +1 more source

“Intrapericardial Approach” for Venous Outflow Reconstruction in Living‐Donor Liver Transplantation for Budd‐Chiari Syndrome: Surgical Techniques and LongTerm Outcomes

Annals of Gastroenterological Surgery, EarlyView.
Unlike deceased‐donor liver transplantation, living‐donor liver transplantation (LDLT) for Budd‐Chiari Syndrome (BCS) presents distinctive challenges in hepatic venous (HV)‐outflow reconstruction because diseased HV–inferior vena cava (IVC) cannot be entirely replaced with healthy donor vessels.
Koichiro Hata, Tetsuya Tajima, Satoshi Ogiso, Shinji Uemoto, Etsuro Hatano   +4 more
wiley   +1 more source

Optimizing the Functional and Safety Properties of a Marine Allergen: Maillard-Induced Conjugation of Chitosan and Saccharides Attenuates the Allergenicity of Turbot (<i>Scophthalmus maximus</i>) Parvalbumin. [PDF]

Foods
Dzadu L, Han Q, Yin S, Liu M, Han S, Che H.   +5 more
europepmc   +1 more source

Organization of PV System with Dispersed PV Array

IEEJ Transactions on Power and Energy, 1999
openaire   +2 more sources

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Orbitofrontal PV interneurons modulate social interaction via default mode network dynamics. [PDF]

Commun Biol
Khatamsaz E, Ionescu TM, Keppler K, Stoller F, Kätzel D, Marston HM, Hengerer B.   +6 more
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Gene-Specific Outcomes After Central Nervous System Metastases in Germline BRCA1- and BRCA2-Associated Breast Cancer. [PDF]

Cancers (Basel)
Decaminada A, Sunder-Plassmann R, Ho WK, Muhr D, Starzer AM, Berghoff AS, Bartsch R, Singer CF, kConFab Investigators, Tan YY.   +9 more
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source