A New Type of Compositive Information Entropy for IvIFS and Its Applications

We first show the interval-valued intuitionistic fuzzy entropy which reflects intuitionism and fuzziness of interval-valued intuitionistic fuzzy set (IvIFS) based on interval-valued intuitionistic fuzzy cross-entropy. As for intuitionism and fuzziness of IvIFS, we propose interval-valued intuitionistic entropy and interval-valued fuzzy entropy, respectively. Furthermore, we establish the interval-valued span entropy describing the uncertainty of membership degree and nonmembership degree and show some concrete measure formulas. Combining intuitionistic factor, fuzzy factor, and span factor, we ultimately put forward the axiomatic definition of the compositive entropy and give a measure formula of compositive entropy. In addition, the effectiveness of the compositive entropy measure is illuminated by comparison with other entropy measures. Furthermore, the compositive entropy is applied to multiple attributes’ decision-making by using the weighted correlation coefficient between IvIFSs and pattern recognition by a similarity measure transformed from the compositive entropy

Eriodictyol attenuates spinal cord injury by activating Nrf2/HO-1 pathway and inhibiting NF-κB pathway

Purpose: To investigate the effect of eriodictyol on spinal cord injury (SCI) and its underlying mechanism of action.Methods: Thirty Sprague-Dawley rats were assigned to sham, SCI, and eriodictyol-treated groups (SCI + Eri; 10, 20, and 50 mg/kg). Moderate spinal cord contusion injury was induced to model SCI. Locomotor recovery was assessed based on Basso, Beattie, and Bresnahan (BBB) score. Pain wasevaluated by paw withdrawal threshold (PWT) and latency (PWL), and spinal cord water content was measured. Tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6) expression were determined by enzyme-linked immunosorbent assay (ELISA) and reverse transcriptase quantitative polymerase chain reaction (RT-qPCR). Immunoassay was used to determine malondialdehyde (MDA), superoxide dismutase (SOD), glutathione (GSH), and glutathione peroxidase (GSH-PX) levels while Western blotting was employed to evaluate nuclear factor erythroid 2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), nuclear factor-kappa B (NF-κB), and phosphorylated NF-κB (p-NF-κB) levels.Results: Eriodictyol elevated BBB score, PWT, and PWL in SCI rats but reduced spinal cord water content (p < 0.05). Eriodictyol treatment down-regulated TNF-α, IL-1β, IL-6, and MDA, whereas SOD, GSH, and GSH-PX levels were elevated (p < 0.05). Eriodictyol administration increased Nrf2 and HO-1 levels but reduced p-NF-κB/NF-κB.Conclusion: This study provides a potential therapy to promote long-term functional recovery following SCI. Keywords: Spinal cord injury, Eriodictyol, Nrf2/HO-1 pathway, NF-κB signaling pathway, Polymerase chain reaction, Basso, Beattie and Bresnahan scor

Identifying the proton loading site cluster in the ba₃ cytochrome c oxidase that loads and traps protons

Cytochrome c Oxidase (CcO) is the terminal electron acceptor in aerobic respiratory chain, reducing O₂ to water. The released free energy is stored by pumping protons through the protein, maintaining the transmembrane electrochemical gradient. Protons are held transiently in a proton loading site (PLS) that binds and releases protons driven by the electron transfer reaction cycle. Multi-Conformation Continuum Electrostatics (MCCE) was applied to crystal structures and Molecular Dynamics snapshots of the B-type Thermus thermophilus CcO. Six residues are identified as the PLS, binding and releasing protons as the charges on heme b and the binuclear center are changed: the heme a₃ propionic acids, Asp287, Asp372, His376 and Glu126B. The unloaded state has one proton and the loaded state two protons on these six residues. Different input structures, modifying the PLS conformation, show different proton distributions and result in different proton pumping behaviors. One loaded and one unloaded protonation states have the loaded/unloaded states close in energy so the PLS binds and releases a proton through the reaction cycle. The alternative proton distributions have state energies too far apart to be shifted by the electron transfers so are locked in loaded or unloaded states. Here the protein can use active states to load and unload protons, but has nearby trapped states, which stabilize PLS protonation state, providing new ideas about the CcO proton pumping mechanism. The distance between the PLS residues Asp287 and His376 correlates with the energy difference between loaded and unloaded states

Modeling the protein binding non-linearity in population pharmacokinetic model of valproic acid in children with epilepsy: a systematic evaluation study

Background: Several studies have investigated the population pharmacokinetics (popPK) of valproic acid (VPA) in children with epilepsy. However, the predictive performance of these models in the extrapolation to other clinical environments has not been studied. Hence, this study evaluated the predictive abilities of pediatric popPK models of VPA and identified the potential effects of protein binding modeling strategies.Methods: A dataset of 255 trough concentrations in 202 children with epilepsy was analyzed to assess the predictive performance of qualified models, following literature review. The evaluation of external predictive ability was conducted by prediction- and simulation-based diagnostics as well as Bayesian forecasting. Furthermore, five popPK models with different protein binding modeling strategies were developed to investigate the discrepancy among the one-binding site model, Langmuir equation, dose-dependent maximum effect model, linear non-saturable binding equation and the simple exponent model on model predictive ability.Results: Ten popPK models were identified in the literature. Co-medication, body weight, daily dose, and age were the four most commonly involved covariates influencing VPA clearance. The model proposed by Serrano et al. showed the best performance with a median prediction error (MDPE) of 1.40%, median absolute prediction error (MAPE) of 17.38%, and percentages of PE within 20% (F20, 55.69%) and 30% (F30, 76.47%). However, all models performed inadequately in terms of the simulation-based normalized prediction distribution error, indicating unsatisfactory normality. Bayesian forecasting enhanced predictive performance, as prior observations were available. More prior observations are needed for model predictability to reach a stable state. The linear non-saturable binding equation had a higher predictive value than other protein binding models.Conclusion: The predictive abilities of most popPK models of VPA in children with epilepsy were unsatisfactory. The linear non-saturable binding equation is more suitable for modeling non-linearity. Moreover, Bayesian forecasting with prior observations improved model fitness

Evaluation of log P, pKa, and log D predictions from the SAMPL7 blind challenge

The Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges focuses the computational modeling community on areas in need of improvement for rational drug design. The SAMPL7 physical property challenge dealt with prediction of octanol-water partition coefficients and pKa for 22 compounds. The dataset was composed of a series of N-acylsulfonamides and related bioisosteres. 17 research groups participated in the log P challenge, submitting 33 blind submissions total. For the pKa challenge, 7 different groups participated, submitting 9 blind submissions in total. Overall, the accuracy of octanol-water log P predictions in the SAMPL7 challenge was lower than octanol-water log P predictions in SAMPL6, likely due to a more diverse dataset. Compared to the SAMPL6 pKa challenge, accuracy remains unchanged in SAMPL7. Interestingly, here, though macroscopic pKa values were often predicted with reasonable accuracy, there was dramatically more disagreement among participants as to which microscopic transitions produced these values (with methods often disagreeing even as to the sign of the free energy change associated with certain transitions), indicating far more work needs to be done on pKa prediction methods