Generalized pustular psoriasis (GPP) is a life-threatening condition; however, little is known about the factors that can predict GPP patients manifesting a deteriorating course. To investigate the demographics and clinical features of adult inpatient GPP and propose a prediction model for detecting fatal GPP (fGPP) and GPP requiring intensive care unit admission (iGPP) patients, a nationwide population-based retrospective cohort study was conducted. The adult inpatients with GPP from January 2007 to December 2020 were assessed. The 800 cases were aged 51.0 years (median [interquartile range, 37.0-64.0]). Overall, 21 iGPP (64.0 years [54.0-77.0]) and 17 fGPP (75.0 years [68.0-77.0]) cases were identified as deteriorating GPP. Renal disease (odds ratio [OR], 7.31), myocardial infarction history (OR, 4.29), liver disease (OR, 2.82), and diabetes mellitus (OR, 2.34) were identified as predictors for iGPP. For fGPP, myocardial infarction history (OR, 5.10) and psoriasis history (OR, 3.13) were established as predictors. A prediction model with scores ranging 0-11 points showed a reliable diagnostic value in detecting deteriorating GPP (area under the curve = 0.75 for iGPP and 0.83 for fGPP). In conclusion, this study provides the clinical features of deteriorating GPP. A prediction model may help physicians to identify patients with deteriorating GPP.
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http://dx.doi.org/10.1111/1346-8138.16383 | DOI Listing |
J Agric Food Chem
January 2025
UA MBG-UVIGO, Misión Biológica de Galicia (CSIC), Pazo de Salcedo, Pontevedra 36143, España.
Hydroxycinnamates, like ferulate (FA) and -coumarate (CA), are important components of maize cell walls, which influence pest resistance, ruminal digestibility, and biofuel production. Increasing their concentration has been linked to increased pest resistance, but also may lead to a decrease in nutritional value or bioethanol production efficiency. Therefore, improving forage quality or biofuel production without compromising plant resistance and a thorough understanding of the biosynthesis and deposition of these compounds is necessary, especially in stover, which is the feedstock for second-generation biofuel production and determines animal forage quality.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Knight Foundation of Computing & Information Sciences, Florida International University, Miami, FL, United States.
Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech.
View Article and Find Full Text PDFJMIR Public Health Surveill
January 2025
Faculty of Human-Environment Studies, Kyushu University, Fukuoka, Japan.
Background: The effects of physical activity (PA) across different domains and intensities on depressive symptoms remain inconclusive. Incorporating the community-built environment (CBE) into longitudinal analyses of PA's impact on depressive symptoms is crucial.
Objective: This study aims to examine the effects of PA at different intensities-low-intensity PA (eg, walking activities) and moderate-to-vigorous-intensity PA (eg, activities requiring substantial effort and causing faster breathing or shortness of breath)-across leisure-time and occupational domains on depressive symptom trajectories among middle-aged and older adults.
Bioinformatics
January 2025
Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, 1004, Philippines.
Motivation: Recent computational approaches for predicting phage-host interaction have explored the use of sequence-only protein language models to produce embeddings of phage proteins without manual feature engineering. However, these embeddings do not directly capture protein structure information and structure-informed signals related to host specificity.
Results: We present PHIStruct, a multilayer perceptron that takes in structure-aware embeddings of receptor-binding proteins, generated via the structure-aware protein language model SaProt, and then predicts the host from among the ESKAPEE genera.
Bioinformatics
January 2025
School of Artificial Intelligence, Jilin University, Jilin, China.
Motivation: Predicting RNA-binding proteins (RBPs) is central to understanding post-transcriptional regulatory mechanisms. Here, we introduce EnrichRBP, an automated and interpretable computational platform specifically designed for the comprehensive analysis of RBP interactions with RNA.
Results: EnrichRBP is a web service that enables researchers to develop original deep learning and machine learning architectures to explore the complex dynamics of RNA-binding proteins.
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