Results 111 to 120 of about 11,536,029 (288)

Sensitivity, specificity, positive predictive value and negative predictive value of ApneaLink^TM autoscore compared with polysomnography.

, 2018
Sensitivity, specificity, positive predictive value and negative predictive value of ApneaLinkTM autoscore compared with polysomnography.
Sabrina Maier (5318102), Jörg Daniel Leuppi (2635099), Michel Hug (5318105), Stig Solbach (5318108), Stefanie Brighenti-Zogg (2635087), David Miedinger (330274), Katrin Uehli (5318099), Selina Dürr (5318111)   +7 more
core   +1 more source

Intussusception; deriving true prevalence, specificity and negative predictive value from the observed prevalence, sensitivity and positive predictive value.

, 2020
Intussusception; deriving true prevalence, specificity and negative predictive value from the observed prevalence, sensitivity and positive predictive value.
Rosa Gini (451348), Tom De Smedt (5400662), Kaatje Bollaerts (2266669), Caitlin Dodd (324051), Nick Andrews (151232), Alexandros Rekkas (8748450)   +5 more
core   +1 more source

The Shewanella oneidensis Fic enzyme SoFic targets the switch‐I region of EF‐Tu for AMPylation

FEBS Letters, EarlyView.
Fic enzymes mediate diverse post‐translational modifications across all domains of life, including AMPylation. Prokaryotic EF‐Tu can be AMPylated and deAMPylated by the conserved Fic enzyme SoFic. Structural and biochemical approaches were used to characterize the effect of AMPylation on EF‐Tu, SoFic's enzymatic activities, and the enzyme‐target ...
Svenja Runge, Vivian Pogenberg, Alexander Baumgart, Bente Siebels, Hartmut Schlüter, Michael Hecht‐Bucher, Aymelt Itzen   +6 more
wiley   +1 more source

Sensitivity, specificity, positive predictive value and negative predictive value of S₈ and S₂₄.

, 2018
Sensitivity, specificity, positive predictive value and negative predictive value of S8 and S24.
Paul Meyvisch (5537300), Koen Andries (346051), Chrispin Kambili (707561), Nacer Lounis (355090), Ariel Alonso (709471), Myriam Theeuwes (5537297), Brian Dannemann (5537303), Geert Molenberghs (43335), Wim Van der Elst (3824152), An Vandebosch (3741457)   +9 more
core   +1 more source

Prospecting the protein design landscape

FEBS Letters, EarlyView.
This review outlines the current state of various protein design approaches. We discuss the current possibilities enabled by recently released tools, highlight future avenues to pursue in protein design, and underscore the crucial role of key databases and resources for successful protein design workflows.
Jakob R. Riccabona, Katharina T. Stonig, Jens Meiler, Clara T. Schoeder, Monica L. Fernández‐Quintero   +4 more
wiley   +1 more source

Comparison of sensitivity, specificity, positive predictive value, and negative predictive value across different rater comparisons.

Comparison of sensitivity, specificity, positive predictive value, and negative predictive value across different rater comparisons.
Stefan Birkett (14526272), Simon Nichols (6836987), James Metcalfe (17286826), Stuart Ennis (5504579), Richard Powell (290871), Brian Begg (14526273), Prithwish Banerjee (583124), Thomas Nickolay (18121412), Gordon McGregor (5504588), Lee Ingle (21150), Angela Hoye (6988172), Rob Shave (11913643)   +11 more
core   +1 more source

The heterodimeric amino acid transporters (HAT) of the SLC7/SLC3 family: A structure−function relationships and relevance to human pathology

FEBS Letters, EarlyView.
Heterodimeric amino acid transporters consist of SLC7 and SLC3 family proteins arranged in a conserved structural organization. They regulate nutrient transport across cell membranes, supporting essential cellular functions. These transporters also contribute to xenobiotic/drug uptake and distribution.
Mariafrancesca Scalise, Tiziano Mazza, Raffaella Scanga, Lara Console, Michele Galluccio, Cesare Indiveri   +5 more
wiley   +1 more source

Metastatic niche shaped by host factors influences disseminated cancer cell fate

FEBS Letters, EarlyView.
Metastasis is shaped not only by cancer cells but also by the environments they encounter. This review explores how factors such as aging, diet, the microbiome, lifestyle, and environmental exposures remodel organ‐specific niches in the lung, liver, bone, and brain, influencing where metastatic cells survive, remain dormant, or grow, and ultimately ...
Gwennan Delyth Ward, Álvaro Ruiz‐Tabas, Patricia Altea‐Manzano   +2 more
wiley   +1 more source

Sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio of different cut-off values of PCT on SeptiFast results.

, 2013
PPV = positive predictive value.NPV = negative predictive value.LR+ = positive likelihood ratio.LR− = negative likelihood ratio.
Christian Leli (292048), Amedeo Moretti (292051), Angela Cardaccia (292049), Rita Pagliochini (292057), Francesco D'Alò (292053), Antonella Mencacci (292047), Mariella Barcaccia (292058), Francesco Bistoni (184196), Marta Meucci (292050), Senia Farinelli (292055)   +9 more
core   +1 more source

Smaller is better: nanobodies meet NMR

FEBS Letters, EarlyView.
Nanobodies are single‐domain antigen‐binding fragments derived from camelid heavy chain antibodies. Their small size, high stability, and exceptional specificity make nanobodies uniquely useful probes for NMR studies of protein dynamics, transient conformational states, and protein–protein interactions.
Oleg Y. Dmitriev
wiley   +1 more source