Machine learning-assisted aroma profile prediction in Jiang-flavor baijiu.

The complex flavor of Jiang-flavor Baijiu (JFB) arises from the interaction of hundreds of compounds at both physicochemical and sensory levels, making accurate perception challenging. Modern machine learning techniques offer precise and scientific approaches for predicting sensory attributes. This study applied flavoromics and sensory profiling to 27 representative JFB samples from main regions in China, integrating five machine learning algorithms to establish a novel strategy for predicting global aroma characteristics.

Study on the Influence of Microinjection Molding Processing Parameters on Replication Quality of Polylactic Acid Microneedle Array Product.

Biodegradable microneedles with a drug delivery channel have enormous potential for consumers, including use in chronic disease, vaccines, and beauty applications, due to being painless and scarless. This study designed a microinjection mold to fabricate a biodegradable polylactic acid (PLA) in-plane microneedle array product. In order to ensure that the microcavities could be well filled before production, the influences of the processing parameters on the filling fraction were investigated.

A Multiscale Simulation of Polymer Melt Injection Molding Filling Flow Using SPH Method with Slip-Link Model.

In this article, a multiscale simulation method of polymer melt injection molding filling flow is established by combining an improved smoothed particle hydrodynamics method and clustered fixed slip-link model. The proposed method is first applied to the simulation of HDPE melt in a classic Poiseuille flow case, and then two high-speed and high-viscosity injection molding flow cases in two simple long 2D rectangular cavities with and without a circular obstacle, respectively, are analyzed. For each case, the macro velocity results, and the micro average number of entanglements and orientation degree results are demonstrated and discussed, and the changing trends of and are analyzed.

Pressure Analysis of Dynamic Injection Molding and Process Parameter Optimization for Reducing Warpage of Injection Molded Products.

Plastic injection molding technology is one of the important technologies for the manufacturing industry. In this paper, a numerical dynamic injection molding technology (DIMT) is presented, which is based on the finite element (FE) method. This numerical simulation method introduces a vibrational force into the conventional injection molding technology (CIMT).

Multi-objective optimization of coronary stent using Kriging surrogate model.

Background: In stent design optimization, the functional relationship between design parameters and design goals is nonlinear, complex, and implicit and the multi-objective design of stents involves a number of potentially conflicting performance criteria. Therefore it is hard and time-consuming to find the optimal design of stent either by experiment or clinic test. Fortunately, computational methods have been developed to the point whereby optimization and simulation tools can be used to systematically design devices in a realistic time-scale.

Multi-Objective Optimizations of Biodegradable Polymer Stent Structure and Stent Microinjection Molding Process.

Biodegradable stents made of poly-l-lactic acid (PLLA) have a promising prospect thanks to high biocompatibility and a favorable biodegradation period. However, due to the low stiffness of PLLA, polymeric stents have a lower radial stiffness and larger foreshortening. Furthermore, a stent is a tiny meshed tube, hence, it is difficult to make a polymeric stent.

Design optimization of stent and its dilatation balloon using kriging surrogate model.

Background: Although stents have great success of treating cardiovascular disease, it actually undermined by the in-stent restenosis and their long-term fatigue failure. The geometry of stent affects its service performance and ultimately affects its fatigue life. Besides, improper length of balloon leads to transient mechanical injury to the vessel wall and in-stent restenosis.

Physicochemical stability of ternary admixtures of butorphanol, ketamine, and droperidol in polyolefin bags for patient-controlled analgesia use.

Background: Delivery of drug admixtures by intravenous patient-controlled analgesia is a common practice for the management of postoperative pain; however, analytical confirmation of the compatibility and stability of butorphanol tartrate, ketamine hydrochloride, and droperidol combined in ternary admixtures is not available.

Methods: Butorphanol tartrate, ketamine hydrochloride, and droperidol have been examined for compatibility and stability when combined with 0.9% sodium chloride injection stored at 4°C and 25°C with light protection for a total of 14 days.

A Self-Adaptive Steered Molecular Dynamics Method Based on Minimization of Stretching Force Reveals the Binding Affinity of Protein-Ligand Complexes.

Binding affinity prediction of protein-ligand complexes has attracted widespread interest. In this study, a self-adaptive steered molecular dynamics (SMD) method is proposed to reveal the binding affinity of protein-ligand complexes. The SMD method is executed through adjusting pulling direction to find an optimum trajectory of ligand dissociation, which is realized by minimizing the stretching force automatically.

Long-Term Stability of Tramadol and Ketamine Solutions for Patient-Controlled Analgesia Delivery.

Background: Subanesthetic doses of ketamine as an adjuvant to tramadol in patient-controlled analgesia (PCA) for postoperative pain have been shown to improve the quality of analgesia. However, there are no such commercially available drug mixtures, and the stability of the combination has rarely been assessed.

Material And Methods: Admixtures were assessed for periods of up to 14 days at 4°C and 25°C.

An accurate metalloprotein-specific scoring function and molecular docking program devised by a dynamic sampling and iteration optimization strategy.

Metalloproteins, particularly zinc metalloproteins, are promising therapeutic targets, and recent efforts have focused on the identification of potent and selective inhibitors of these proteins. However, the ability of current drug discovery and design technologies, such as molecular docking and molecular dynamics simulations, to probe metal-ligand interactions remains limited because of their complicated coordination geometries and rough treatment in current force fields. Herein we introduce a robust, multiobjective optimization algorithm-driven metalloprotein-specific docking program named MpSDock, which runs on a scheme similar to consensus scoring consisting of a force-field-based scoring function and a knowledge-based scoring function.

MoDock: A multi-objective strategy improves the accuracy for molecular docking.

Background: As a main method of structure-based virtual screening, molecular docking is the most widely used in practice. However, the non-ideal efficacy of scoring functions is thought as the biggest barrier which hinders the improvement of the molecular docking method.

Results: A new multi-objective strategy for molecular docking, named as MoDock, is presented to further improve the docking accuracy with available scoring functions.

The role of the GABA-A receptor of the adjacent intact dorsal root ganglion neurons in rats with neuropathic pain.

We aim to investigate the changes of The γ-aminobutyric acid (GABA) signals in the adjacent intact dorsal root ganglion (DRG) and the contribution of these changes to the development and maintenance of neuropathic pain (NPP). After establishment of neuropathic pain model with the lumbar 5 spinal nerve ligation (L5 SNL), the GABA-evoked currents were recorded in the acutely dissociated L4 DRG neurons using whole-cell patch clamp. Moreover, Muscimol or Bicuculline were respectively topically injected to the L4 DRG at the time of nerve injury and post-operative 5 days (POD5).

Neuroprotective effect of calcitriol on ischemic/reperfusion injury through the NR3A/CREB pathways in the rat hippocampus.

Calcitriol has been demonstrated to provide neuroprotection against ischemia/reperfusion (I/R) injury. However, the exact mechanism of this protection remains unknown. In the present study, the neuroprotective effect of calcitriol was investigated in rats exposed to cerebral I/R injury induced by middle cerebral artery occlusion (MCAO).

Free energy landscape for the binding process of Huperzine A to acetylcholinesterase.

Drug-target residence time (t = 1/k(off), where k(off) is the dissociation rate constant) has become an important index in discovering better- or best-in-class drugs. However, little effort has been dedicated to developing computational methods that can accurately predict this kinetic parameter or related parameters, k(off) and activation free energy of dissociation (ΔG(off)≠). In this paper, energy landscape theory that has been developed to understand protein folding and function is extended to develop a generally applicable computational framework that is able to construct a complete ligand-target binding free energy landscape.

A generic force field for protein coarse-grained molecular dynamics simulation.

Coarse-grained (CG) force fields have become promising tools for studies of protein behavior, but the balance of speed and accuracy is still a challenge in the research of protein coarse graining methodology. In this work, 20 CG beads have been designed based on the structures of amino acid residues, with which an amino acid can be represented by one or two beads, and a CG solvent model with five water molecules was adopted to ensure the consistence with the protein CG beads. The internal interactions in protein were classified according to the types of the interacting CG beads, and adequate potential functions were chosen and systematically parameterized to fit the energy distributions.

Optimizing energy potential for protein fold recognition with parametric evaluation function.

In this paper, a new optimization method is proposed to determine a simplified energy potential for protein fold recognition, which consists of the residue-residue contact, hydrophobicity, and pseudodihedral potentials. With a parametric evaluation function method, the Z-scores of all the proteins in a training set are optimized simultaneously to obtain the best parameter set of the potential. For this multi-objective and multi-constraint problem, the new optimization scheme is very effective.

A simple Calpha-SC potential with higher accuracy for protein fold recognition.

In this paper, an improved C(alpha)-SC energy potential designed for protein fold recognition was reported. It consists of three extremely simple interaction terms which are supposed to be the dominant interactions in protein folding: residue-residue contact, hydrophobicity and pseudodihedral potentials. The potential function only contains 210 contacts, one hydrophobic and one torsion parameters, which have been optimized using an interior point algorithm of linear programming.