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Prognostic value of the C-reactive protein to albumin ratio in patients with stroke: a meta-analysis
FDA approvals in 2024: new options for patients across cancer types and therapeutic classes
Correction for Maher et al., Intracranial substrates of meditation-induced neuromodulation in the amygdala and hippocampus
A bright future for topological acoustics
A near-threshold memristive computing-in-memory engine for edge intelligence
Dimetridazole potentiates cefotaxime against multidrug-resistant E. coli via membrane disruption and fatty acid composition
Interconnected four split rectangular ring resonator flexible metamaterial for microwave sensing application
GPS Galileo BDS3 LEO uncalibrated phase delays estimation and tight combination precise point positioning with ambiguity resolution
Predictive model on employee stock ownership impacting corporate performance
Life cycle cost of communication towers: identification and hierarchical classification of influencing factors
Effect of enhanced early life nutrition on the M. longissimus thoracis et lumborum transcriptome of crossbred beef heifer calves
Lactate-related lncRNAs assessment model predicts the prognosis of pancreatic ductal adenocarcinoma
Depression detection methods based on multimodal fusion of voice and text
Quantum emission from coupled spin pairs in hexagonal boron nitride
Abstract Optically addressable defect qubits in wide band gap materials are favorable candidates for room-temperature quantum information processing. Two-dimensional (2D) hexagonal boron nitride (hBN) is an attractive solid-state platform with great potential for hosting bright quantum emitters and quantum memories, leveraging the advantages of 2D materials for scalable preparation of defect qubits. Although room-temperature bright defect qubits have been recently reported in hBN, their microscopic origin, the nature of the optical transition, and the optically detected magnetic resonance (ODMR) have remained elusive. Here, we connect the variance in the optical spectra, optical lifetimes, and spectral stability of quantum emitters to donor-acceptor pairs (DAPs) in hBN through ab initio calculations. We find that DAPs can exhibit ODMR signals for the acceptor counterpart of the defect pair with an S = 1/2 ground state at non-zero magnetic fields, depending on the donor partner and dominantly mediated by the hyperfine interaction. The donor-acceptor pair model and its transition mechanisms provide a recipe for defect qubit identification and performance optimization in hBN for quantum applications.
Injectable magnesium-bisphosphonate MOF-based bone adhesive prevents excessive fibrosis for osteoporotic fracture repair
Hyperpolarization Modulation of the T‐Type hCa <sub>v</sub> 3.2 Channel by Human Synenkephalin [1–53], a Shrew Neurotoxin Analogue without Paralytic Effects
Abstract Mammalian secreted venoms mainly consist of peptides and proteases used for defense or predation. Blarina paralytic peptides (BPPs), mealworm‐targeting neurotoxins from shrew, are very similar to human synenkephalin. This peptide is released from proenkephalin in the brain along with opioid peptides that mediate analgesic and antidepressant effects, though its physiological function is unclear. Here, we synthesized and characterized human synenkephalin [1–53] (hSYN) and reveal its disulfide bond connectivity. Similar to BPP2, hSYN caused a hyperpolarizing shift in the human T‐type voltage‐gated calcium channel (hCa v 3.2) at 0.74 µM, but did not paralyze mealworms. Molecular docking and molecular dynamics simulations showed that hSYN and BPP2 interact with hCa v 3.2 channel differently, due to differences in polar residues. Since Ca v 3.2 channel regulates neuronal excitability and is implicated in conditions like autism and epilepsy, our findings on hSYN could provide insight into the channel gating and agonistic mechanisms, along with potential pathways for developing treatments for neurological disorders.
Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning model
Abstract This study presents a comprehensive methodology for implementing a unified knowledge-based planning model for RapidPlan™ (RP) to manage all 11 prostate cancer prescriptions used at our institution. Several RP configurations were evaluated to address different clinical scenarios. The initial models RP_46 and RP_30 involved the prostate, seminal vesicles, and lymph nodes treated with 46 Gy in 23 fractions and the prostate alone treated with 30 Gy in 15 fractions, respectively. These models were progressively expanded to incorporate all sequential boost treatment plans (RP_46 + 30), including those targeting the prostate bed (RP_Seq). Simultaneous integrated boost prescriptions were used to train the RP_SIB model, which was subsequently combined with the RP_Seq model to form the unified RP_UNI model. Each configuration was compared with the manual method using a cohort of 10–25 patients. All the models produced treatment plans that met the clinical requirements. An overall analysis revealed that the RP_UNI model significantly reduced the 45 Gy and 15 Gy volumes (cm3) in the peritoneal cavity by approximately 18%. The RP_UNI model was chosen for clinical implementation owing to its broader applicability compared with the other models, offering a 66% reduction in planning time with respect to the manual method. The unified model, derived from simpler RP configurations, successfully integrated all 11 prostate cancer prescriptions used at our institution. This model performed efficiently regardless of the complexity of the target volumes or whether the irradiation technique was a sequential or simultaneous integrated boost.