Identification of potential PIM-2 inhibitors via ligand-based generative models, molecular docking and molecular dynamics simulations.

Proviral Integrations of Moloney-2 (PIM-2) kinase is a promising target for various cancers and other diseases, and its inhibitors hold potential for treating related diseases. However, there is currently no clinically available PIM-2 inhibitor. In this study, we constructed a generative model for de novo PIM-2 inhibitor design based on artificial intelligence, performed molecular docking and molecular dynamics (MD) simulations to develop an efficient PIM-2 inhibitor generative model and discover potential PIM-2 inhibitors. First, we designed a generative model based on a Bi-directional Long Short-Term Memory (BiLSTM) framework combined with a transfer learning strategy and generated a new PIM-2 small molecule library using existing active drug databases. The generated compound library was then virtually screened by molecular docking and scaffold similarity comparison, identifying 10 initial hit compounds with better performance. Next, using the inhibitor in the crystal structure as a positive control, we performed two rounds of MD simulations, with lengths of 100 ns and 500 ns, respectively, to study the dynamic stability of the protein-ligand systems of the 10 compounds with PIM-2. Analyzed the interactions with key hinge region residues, binding free energies, and changes in the ATP pocket size. The generative model demonstrates good molecular generation capability and can generate efficient novel molecules with similar physicochemical properties as active PIM-2 drugs. Among the 10 initially selected hit compounds, 5 compounds C3 (- 29.69 kcal/mol), C4 (- 33.31 kcal/mol), C5 (- 28.59 kcal/mol), C8 (- 34.68 kcal/mol), and C9 (- 25.88 kcal/mol) have higher binding energies with PIM-2 than the positive drug 3YR (- 26.18 kcal/mol). The MD simulation results are consistent with the docking analysis, these compounds have lower and more stable RMSD values for the complex systems with the reported positive drug 3YR and PIM-2 complex system. They can form long-term stable interactions with active site and the hinge region of PIM-2, which suggests these compounds are likely to have potent inhibitory effects on PIM-2. This study provides an efficient generative model for PIM-2 inhibitor research and discovers 5 potential novel PIM-2 inhibitors.

Enhancing the CO2 Adsorption of the Cobalt-Free Layered Perovskite Cathode for Solid-Oxide Electrolysis Cells Gains Excellent Stability under High Voltages via Oxygen-Defect Adjustment.

Solid-oxide electrolysis cells are a clean energy conversion device with the ability to directly electrolyze the conversion of CO2 to CO efficiently. However, their practical applications are limited due to insufficient CO2 adsorption performance of the cathode materials. To overcome this issue, the A-site cation deficiency strategy has been applied in a layered perovskite PrBaFe1.6Ni0.4O6-δ (PBFN) cathode for direct CO2 electrolysis. The introduction of 5% deficiency at the Pr/Ba site leads to a significant increase in the concentration of oxygen vacancies (nonstoichiometric number δ of oxygen vacancies increased from 0.093 to 0.132), which greatly accelerates the CO2 adsorption performance as well as the O2- transport capacity toward the CO2 reduction reaction (CO2RR). CO2 temperature-programmed desorption indicates that A-site cation-deficient (PrBa)0.95Fe1.6Ni0.4O6-δ (PB95FN) shows a larger desorption peak area and a higher desorption temperature. PB95FN also exhibits a greater presence of carbonate in Fourier transform infrared (FT-IR) spectroscopy. The electrical conductivity relaxation test shows that the introduction of the 5% A-site deficiency effectively improves the surface oxygen exchange and diffusion kinetics of PB95FN. The current density of the electrolysis cell with the (PrBa)0.95Fe1.6Ni0.4O6-δ (PB95FN) cathode reaches 0.876 A·cm-2 under 1.5 V at 800 °C, which is 41% higher than that of PB100FN. Moreover, the PB95FN cathode demonstrates excellent long-term stability over 100 h and better short-term stability than PB100FN under high voltages, which can be ascribed to the enhanced CO2 adsorption performance. The PB95FN cathode maintains a porous structure and tightly binds to the electrolyte after stability testing. This study highlights the potential of regulating oxygen defects in layered perovskite PrBaFe1.6Ni0.4O6-δ cathode materials via incorporation of cation deficiency toward high-temperature CO2 electrolysis.

Effects of esketamine on postoperative fatigue syndrome in patients after laparoscopic resection of gastric carcinoma: a randomized controlled trial.

BACKGROUND: Despite the implementation of various postoperative management strategies, the prevalence of postoperative fatigue syndrome (POFS) remains considerable among individuals undergoing laparoscopic radical gastrectomy. While the N-methyl-D-aspartic acid receptor antagonist esketamine has demonstrated efficacy in enhancing sleep quality and alleviating postoperative pain, its impact on POFS remains uncertain. Consequently, the objective of this study is to ascertain whether perioperative administration of esketamine can effectively mitigate the occurrence of POFS in patients undergoing laparoscopic radical gastrectomy. METHODS: A total of 133 patients diagnosed with gastric cancer were randomly assigned to two groups, namely the control group (Group C) (n = 66) and the esketamine group (Group E) (n = 67), using a double-blind method. The Group C received standardized anesthesia, while the Group E received esketamine in addition to the standardized anesthesia. The primary outcome measure assessed was the Christensen fatigue score at 3 days after the surgical procedure, while the secondary outcomes included the disparities in postoperative fatigue, postoperative pain, sleep quality, and adverse reactions between the two groups. RESULTS: In the group receiving esketamine, the fatigue scores of Christensen on the third day after surgery were significantly lower compared to the Group C (estimated difference, -0.70; 95% CI, -1.37 to -0.03; P = 0.040). Additionally, there was a significant decrease in the occurrence of fatigue in the Group E compared to the Group C on the first and third days following surgery (P < 0.05). Also, compared to individuals who had distal gastrectomy, those who had entire gastrectomy demonstrated a higher degree of postoperative tiredness reduction with esketamine. Furthermore, the Group E exhibited reduced postoperative pain and improved sleep in comparison to the Group C. Both groups experienced similar rates of adverse events. CONCLUSIONS: The use of esketamine during the perioperative period can improve POFS after laparoscopic radical gastrectomy, without adverse reactions. TRIAL REGISTRATION: Registered in the Chinese Clinical Trial Registry (ChiCTR2300072167) on 05/06 /2023.

Self-Report Amphiphilic Polymer-Based Drug Delivery System with ROS-Triggered Drug Release for Osteoarthritis Therapy.

The development of drug delivery systems with real-time cargo release monitoring capabilities is imperative for optimizing nanomedicine performance. Herein, we report an innovative self-reporting drug delivery platform based on a ROS-responsive random copolymer (P1) capable of visualizing cargo release kinetics via the activation of an integrated fluorophore. P1 was synthesized by copolymerization of pinacol boronate, PEG, and naphthalimide monomers to impart ROS-sensitivity, hydrophilicity, and fluorescence signaling, respectively. Detailed characterization verified that P1 self-assembles into 11 nm micelles with 10 µg mL-1 CMC and can encapsulate hydrophobic curcumin with 79% efficiency. Fluorescence assays demonstrated H2O2-triggered disassembly and curcumin release with concurrent polymer fluorescence turn-on. Both in vitro and in vivo studies validated the real-time visualization of drug release and ROS scavenging, as well as the therapeutic effect on osteoarthritis (OA). Overall, this nanotheranostic polymeric micelle system enables quantitative monitoring of drug release kinetics for enhanced treatment optimization across oxidative stress-related diseases.

Development of sensitive and stable electrochemical impedimetric biosensor based on T1R1 receptor and its application to detection of umami substances.

Umami substances can provide a palatable flavour for food. In this study, an electrochemical impedimetric biosensor was developed for detecting umami substances. This biosensor was fabricated by immobilising T1R1 onto AuNPs/reduced graphene oxide/chitosan which was in advance electro-deposited onto a glassy carbon electrode. The evaluation by the electrochemical impedance spectrum method showed that the T1R1 biosensor performed well with low detection limits and wide linear ranges. Under the optimised incubation time (60 s), the electrochemical response was linearly related to the concentrations of the detected targets monosodium glutamate and inosine-5'-monophosphate within their respective linear range of 10-14 to 10-9 M and 10-16 to 10-13 M. The low detection limit of monosodium glutamate and inosine-5'-monophosphate was 10-15 M and 10-16 M, respectively. Moreover, the T1R1 biosensor exhibited high specificity to umami substances even in the real food sample. The developed biosensor still retained 89.24% signal intensity after 6-day storage, exhibiting a desirable storability.

Progresses, Challenges, and Prospects of CRISPR/Cas9 Gene-Editing in Glioma Studies.

Glioma refers to a tumor that is derived from brain glial stem cells or progenitor cells and is the most common primary intracranial tumor. Due to its complex cellular components, as well as the aggressiveness and specificity of the pathogenic site of glioma, most patients with malignant glioma have poor prognoses following surgeries, radiotherapies, and chemotherapies. In recent years, an increasing amount of research has focused on the use of CRISPR/Cas9 gene-editing technology in the treatment of glioma. As an emerging gene-editing technology, CRISPR/Cas9 utilizes the expression of certain functional proteins to repair tissues or treat gene-deficient diseases and could be applied to immunotherapies through the expression of antigens, antibodies, or receptors. In addition, some research also utilized CRISPR/Cas9 to establish tumor models so as to study tumor pathogenesis and screen tumor prognostic targets. This paper mainly discusses the roles of CRISPR/Cas9 in the treatment of glioma patients, the exploration of the pathogenesis of neuroglioma, and the screening targets for clinical prognosis. This paper also raises the future research prospects of CRISPR/Cas9 in glioma, as well as the opportunities and challenges that it will face in clinical treatment in the future.

Overexpression of Pleckstrin Homology Domain-Containing Family A Member 4 Is Correlated with Poor Prognostic Outcomes and Immune Infiltration in Lower-Grade Glioma.

Introduction: The global incidence of brain tumors, the most common of which is lower grade glioma (LGG), remains high. Pleckstrin homology domain-containing family A member 4 (PLEKHA4) has been reported to be related to tumor invasion and growth. However, its role and correlation with immunity in LGG remain elusive. Methods: We evaluated the expression pattern, prognostic value, biological functions, and immune effects of PLEKHA4 in LGG. We also analyzed the association between PLEKHA4 levels in different tumors, patient prognosis, and its role in tumor immunity. Depending on the type of research data, we used statistical methods such as Student's t-tests, Mann-Whitney U tests one-way ANOVA tests Kruskal-Wallis tests Pearson's or Spearman's correlation analysis Chi-square and Fisher's exact tests in this paper. Results and Conclusions. The results revealed that PLEKHA4 levels were markedly elevated in most tumors (such as LGG). High PLEKHA4 levels are associated with poor overall survival (OS), progression-free interval (PFI) rates, and disease-specific survival (DSS) in LGG patients. Cox regression analysis and nomograms showed that PLEKHA4 levels are independent prognostic factors for LGG patients. According to functional enrichment analysis, PLEKHA4 levels in LGG are associated with immune infiltration and immunotherapy. In conclusion, PLEKHA4 is a potential prognostic marker and immunotherapy target for LGG.

Kinetics of a new porcine taste-bud tissue biosensor for the detection of umami substances and their synergistic effect.

Umami substances are nutrients to humans, and their synergistic effect is associated with food acceptance. In this study, a new biosensor was developed to detect umami substances, their synergistic effect, and detection kinetics. Porcine taste-bud tissues were used as the sensing element, and the umami substance signals were characterized using an electrochemical workstation. The responses of taste-bud tissue sensors to monosodium L-glutamate (MSG) were compared based on different tongue sites. The interaction law between MSG and receptors in the taste-bud tissues of the three sensors conforms to enzymatic-reaction kinetics, where rectangular hyperbola curves in the Michaelis-Menten equation were followed with fitting coefficients (>0.91). However, the taste-bud sensors respond differently to MSG stimuli, with those based on a tip and mediolateral tongue, producing the lowest detection limit of 10-16 mol/L. The number of receptors required for a single cell to achieve maximum output signal is 3.68, 30.42, and 7.27, respectively. Moreover, the taste-bud tissue sensors identified the synergistic effect of umami substances. In addition, they were sensitive to umami variations in soy sauce and mandarin fish. The developed porcine taste-bud tissue biosensor revealed the interaction law between umami substances and receptors, providing a new idea for umami evaluation.

Adaptive Local Aspect Dictionary Pair Learning for Synthetic Aperture Radar Target Image Classification.

In this paper, a new target classification algorithm based on adaptive local aspect dictionary pair learning for synthetic aperture radar (SAR) images is developed. To that end, first, the aspect sector of one testing sample is determined adaptively by a regularized non-negative sparse learning method. Second, a synthesis dictionary and an analysis dictionary are jointly learned from the corresponding training subset located in the aspect sector. By doing so, the local aspect dictionary pair is obtained. Finally, the class label of the testing sample is inferred by a use of the minimum reconstruction residual under the representation with the local aspect dictionary pair. Using the local aspect sector training subset rather than the global aspect training set reduces the interference of a large amount of unrelated training samples, which leads to a more discriminative local aspect dictionary pair for target classification. The experiments are conducted with the Moving and Stationary Target Acquisition and Recognition (MSTAR) database, and the results demonstrate that the proposed approach is effective and superior to the state-of-the-art methods.

Two-Stage Multi-Task Representation Learning for Synthetic Aperture Radar (SAR) Target Images Classification.

In this paper, we propose a two-stage multi-task learning representation method for the classification of synthetic aperture radar (SAR) target images. The first stage of the proposed approach uses multi-features joint sparse representation learning, modeled as a ℓ 2 , 1 -norm regularized multi-task sparse learning problem, to find an effective subset of training samples. Then, a new dictionary is constructed based on the training subset. The second stage of the method is to perform target images classification based on the new dictionary, utilizing multi-task collaborative representation. The proposed algorithm not only exploits the discrimination ability of multiple features but also greatly reduces the interference of atoms that are irrelevant to the test sample, thus effectively improving classification performance. Conducted with the Moving and Stationary Target Acquisition and Recognition (MSTAR) public SAR database, experimental results show that the proposed approach is effective and superior to many state-of-the-art methods.

Determination of bifendate in human plasma by HPLC-MS and bioequivalence on bifendate pills in healthy volunteers.

A sensitive and specific method for the determination of bifendate in human plasma was developed, based on high-performance liquid chromatography (HPLC)-mass spectrometry (MS). The samples were extracted from plasma with diethyl ether, followed by separation and evaporation after addition of internal standard diazepam. The residue was reconstituted in methanol and injected into the HPLC-MS. Chromatography was performed on an Inertsil ODS column with a mobile phase consisting of methanol-distilled water (70/30, v/v) at a flow rate of 0.3 mL/min. Quantitative analysis was achieved by MS detection, using a mass spectrometer equipped with an electrospray ionization interface (ESI) and operated in selected ion monitoring (SIM) and positive-ionization mode using target ions at m/z 419 for bifendate and m/z 285 for internal standard, respectively. The linearity was confirmed in the concentration range of 2-200 ng/mL in human plasma and the precision of this assay was not more than 6.79% over the entire concentration range. The method was sensitive and repeatable enough to be used in pharmacokinetic and bioavailability studies.