Results 171 to 180 of about 12,612 (291)

Optimized machine learning mechanism for big data healthcare system to predict disease risk factor. [PDF]

open access: yesSci Rep
Thatha VN   +7 more
europepmc   +1 more source

Microbial Contribution to Soiling and Its Impact on Photovoltaic Module Soiling in Arid Zones of the Atacama Desert

open access: yesAdvanced Sustainable Systems, EarlyView.
Microorganisms colonizing photovoltaic surfaces in the Atacama desert form biofilms that enhance particle adhesion and reduce energy yield. This study identifies UV‐resistant bacteria and carotenoid‐producing strains that interfere with PV performance.
Douglas Olivares   +8 more
wiley   +1 more source

Pre‐Administration of Akkermansia Muciniphila Prevents the Development of Severe Acute Graft‐Versus‐Host Disease in Systemic Organs

open access: yesAdvanced Science, EarlyView.
Akkermansia muciniphila, a next‐generation probiotic, alleviates acute graft‐versus‐host disease (aGvHD) following allogeneic hematopoietic stem cell transplantation (HSCT) by providing protective effects across multiple organs. Pre‐colonization with A.
Jeong‐Eun Han   +9 more
wiley   +1 more source

Indole‐3‐Propionic Acid Improves Alveolar Development Impairment via Targeting VAMP8‐mediated SNAREs Complex Formation in Bronchopulmonary Dysplasia

open access: yesAdvanced Science, EarlyView.
This study aims to evaluate the impact of the tryptophan‐derived metabolite indole‐3‐propionic acid (IPA) on lung development and autophagic flux. IPA alleviates hyperoxia‐induced alveolar arrest by promoting autophagosome‐lysosome fusion via inhibition of VAMP8 phosphorylation, which is suggestive of a promising therapeutic target of BPD.
Beibei Wang   +14 more
wiley   +1 more source

Professional Fulfillment, Burnout, and Turnover Intention Among US Dialysis Patient Care Technicians: A National Survey. [PDF]

open access: yesAm J Kidney Dis, 2023
Plantinga LC   +7 more
europepmc   +1 more source

Multi‐Site Transfer Classification of Major Depressive Disorder: An fMRI Study in 3335 Subjects

open access: yesAdvanced Science, EarlyView.
The study proposes graph convolution network with sparse pooling to learn the hierarchical features of brain graph for MDD classification. Experiment is done on multi‐site fMRI samples (3335 subjects, the largest functional dataset of MDD to date) and transfer learning is applied, achieving an average accuracy of 70.14%.
Jianpo Su   +14 more
wiley   +1 more source

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