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Minimum Energy Conical Intersection Optimization Using DFT/MRCI(2).
J Chem Theory Comput
January 2025
Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa K1N 6N5,Canada.
The combined density functional theory and multireference configuration interaction (DFT/MRCI) method is a semiempirical electronic structure approach that is both computationally efficient and has predictive accuracy for the calculation of electronic excited states and for the simulation of electronic spectroscopies. However, given that the reference space is generated via a selected-CI procedure, a challenge arises in the construction of smooth potential energy surfaces. To address this issue, we treat the local discontinuities that arise as noise within the Gaussian progress regression framework and learn the surfaces by explicitly incorporating and optimizing a white-noise kernel.
View Article and Find Full Text PDFNDUFA11 may be the disulfidptosis-related biomarker of ischemic stroke based on integrated bioinformatics, clinical samples, and experimental analyses.
Front Neurosci
January 2025
Department of Geriatric Rehabilitation, Jiangbin Hospital, Nanning, China.
Background: Programmed cell death plays an important role in neuronal injury and death after ischemic stroke (IS), leading to cellular glucose deficiency. Glucose deficiency can cause abnormal accumulation of cytotoxic disulfides, resulting in disulfidptosis. Ferroptosis, apoptosis, necroptosis, and autophagy inhibitors cannot inhibit this novel programmed cell death mechanism.
View Article and Find Full Text PDFImplementation of a Cost and Variation Reduction Program for Hemostasis Products at a Large Academic Medical Center: A Multi-Stakeholder Perspective.
Med Devices (Auckl)
January 2025
Department of Orthopaedics, Sports Medicine Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Goal: Cost-saving initiatives targeting surgical supplies management have become increasingly common to address rising healthcare costs. However, few studies provide details on hospital stakeholder experiences or learnings from implementing such initiatives. Thus, we sought to evaluate hospital stakeholder satisfaction with conversion to a sole supplier for hemostasis products, in addition to economic and clinical impacts, to help develop best practices for implementation.
View Article and Find Full Text PDFThe role of intraoperative monitoring in target selection in deep brain stimulation: A single centre study.
Clin Park Relat Disord
January 2025
Department of Neurology, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia.
Introduction: Intraoperative microelectrode recording (MER) and intraoperative test stimulation may provide vital information for optimal electrode placement and clinical outcome in movement disorders patients treated with deep brain stimulation (DBS). The aims of this retrospective study were to determine (i) how often the planned (imaging based) placements of electrodes were changed due to MER and intraoperative test stimulation in Parkinson's disease (PD), dystonia and essential tremor (ET) patients; (ii) whether the frequency of repositioning changed over time; (iii) whether patients' age or disease duration (in PD) influenced the frequency of repositioning.
Methods: Data on the planned and the final placement of 141 electrodes in 72 consecutive DBS treated patients (52 PD, 11 dystonia, 9 ET) was collected over the first 8 years of DBS implementation in a single center.
Epigenetic profiling for prognostic stratification and personalized therapy in breast cancer.
Front Immunol
January 2025
Research Laboratory Center, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Background: The rising incidence of breast cancer and its heterogeneity necessitate precise tools for predicting patient prognosis and tailoring personalized treatments. Epigenetic changes play a critical role in breast cancer progression and therapy responses, providing a foundation for prognostic model development.
Methods: We developed the Machine Learning-derived Epigenetic Model (MLEM) to identify prognostic epigenetic gene patterns in breast cancer.
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