Molecular Interactions Research Articles

An Alkyne-bridged Covalent Organic Framework Featuring Interactive Pockets for Bromine Capture.

The high degree of corrosivity and reactivity of bromine, which is released from various sources poses a serious threat to the environment. Moreover, its coexistence with iodine forming an equilibrium compound, iodine monobromide (IBr) necessitates the selective capture of bromine from halogen mixtures. The electrophilicity of halogens to π-electron rich structures enabled us to strategically design a covalent organic framework for halogen capture, featuring a defined pore environment with localized sorption sites. The higher capture capacity of bromine (4.6gg-1) over iodine by ~41% shows its potential in selective capture. Spectroscopic results uncovering the preferential interaction sites are supported by theoretical investigations. The alkyne bridge is a core functionality promoting the selectivity in capture by synergistic physisorption, rationalized by the higher orbital overlap of bromine due to its smaller atomic size as well as reversible chemical interactions. The slip stacking in the structure has further promoted this phenomenon by creating clusters of molecular interaction sites with bromine intercalated between the layers. The inclusion of unsaturated moieties, i.e. triple bonds and the complementary pore geometry offer a promising design strategy for the construction of porous materials for halogen capture.

Distance plus attention for binding affinity prediction

Protein-ligand binding affinity plays a pivotal role in drug development, particularly in identifying potential ligands for target disease-related proteins. Accurate affinity predictions can significantly reduce both the time and cost involved in drug development. However, highly precise affinity prediction remains a research challenge. A key to improve affinity prediction is to capture interactions between proteins and ligands effectively. Existing deep-learning-based computational approaches use 3D grids, 4D tensors, molecular graphs, or proximity-based adjacency matrices, which are either resource-intensive or do not directly represent potential interactions. In this paper, we propose atomic-level distance features and attention mechanisms to capture better specific protein-ligand interactions based on donor-acceptor relations, hydrophobicity, and π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document}-stacking atoms. We argue that distances encompass both short-range direct and long-range indirect interaction effects while attention mechanisms capture levels of interaction effects. On the very well-known CASF-2016 dataset, our proposed method, named Distance plus Attention for Affinity Prediction (DAAP), significantly outperforms existing methods by achieving Correlation Coefficient (R) 0.909, Root Mean Squared Error (RMSE) 0.987, Mean Absolute Error (MAE) 0.745, Standard Deviation (SD) 0.988, and Concordance Index (CI) 0.876. The proposed method also shows substantial improvement, around 2% to 37%, on five other benchmark datasets. The program and data are publicly available on the website https://gitlab.com/mahnewton/daap.Scientific Contribution StatementThis study innovatively introducesdistance-based features to predict protein-ligand binding affinity, capitalizing onunique molecular interactions. Furthermore, the incorporation of protein sequencefeatures of specific residues enhances the model’s proficiency in capturing intricatebinding patterns. The predictive capabilities are further strengthened through theuse of a deep learning architecture with attention mechanisms, and an ensembleapproach, averaging the outputs of five models, is implemented to ensure robustand reliable predictions.

Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality

BackgroundCharacterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell–cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality.MethodsCCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.ResultsA shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64–10.25]) and ovarian cancer in UKBB (5.53[2.08–8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97–2.96]) compared to females (1.84[1.44–2.37]).ConclusionWe identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.

Integrating spatial and single-cell transcriptomics reveals tumor heterogeneity and intercellular networks in colorectal cancer

Single cell RNA sequencing (scRNA-seq), a powerful tool for studying the tumor microenvironment (TME), does not preserve/provide spatial information on tissue morphology and cellular interactions. To understand the crosstalk between diverse cellular components in proximity in the TME, we performed scRNA-seq coupled with spatial transcriptomic (ST) assay to profile 41,700 cells from three colorectal cancer (CRC) tumor-normal-blood pairs. Standalone scRNA-seq analyses revealed eight major cell populations, including B cells, T cells, Monocytes, NK cells, Epithelial cells, Fibroblasts, Mast cells, Endothelial cells. After the identification of malignant cells from epithelial cells, we observed seven subtypes of malignant cells that reflect heterogeneous status in tumor, including tumor_CAV1, tumor_ATF3_JUN | FOS, tumor_ZEB2, tumor_VIM, tumor_WSB1, tumor_LXN, and tumor_PGM1. By transferring the cellular annotations obtained by scRNA-seq to ST spots, we annotated four regions in a cryosection from CRC patients, including tumor, stroma, immune infiltration, and colon epithelium regions. Furthermore, we observed intensive intercellular interactions between stroma and tumor regions which were extremely proximal in the cryosection. In particular, one pair of ligands and receptors (C5AR1 and RPS19) was inferred to play key roles in the crosstalk of stroma and tumor regions. For the tumor region, a typical feature of TMSB4X-high expression was identified, which could be a potential marker of CRC. The stroma region was found to be characterized by VIM-high expression, suggesting it fostered a stromal niche in the TME. Collectively, single cell and spatial analysis in our study reveal the tumor heterogeneity and molecular interactions in CRC TME, which provides insights into the mechanisms underlying CRC progression and may contribute to the development of anticancer therapies targeting on non-tumor components, such as the extracellular matrix (ECM) in CRC. The typical genes we identified may facilitate to new molecular subtypes of CRC.

Structural basis for pathogenic variants of GJB2 and hearing levels of patients with hearing loss

ObjectivesThe crystal structure of the six protomers of gap junction protein beta 2 (GJB2) enables prediction of the effect(s) of an amino acid substitution, thereby facilitating investigation of molecular pathogenesis of missense variants of GJB2. This study mainly focused on R143W variant that causes hearing loss, and investigated the relationship between amino acid substitution and 3-D structural changes in GJB2.MethodsPatients with nonsyndromic hearing loss who appeared to have two GJB2 pathogenic variants, including the R143W variant, were investigated. Because the X-ray crystal structure of the six protomers of the GJB2 protein is known, R143W and structurally related variants of GJB2 were modeled using this crystal structure as a template. The wild-type crystal structure and the variant computer-aided model were observed and the differences in molecular interactions within the two were analyzed.ResultsThe predicted structure demonstrated that the hydrogen bond between R143 and N206 was important for the stability of the protomer structure. From this prediction, R143W related N206S and N206T variants showed loss of the hydrogen bond.ConclusionInvestigation of the genotypes and clinical data in patients carrying the R143W variant on an allele indicated that severity of hearing loss depends largely on the levels of dysfunction of the pathogenic variant on the allele, whereas a patient with the homozygous R143W variant demonstrated profound hearing loss. We concluded that these hearing impairments may be due to destabilization of the protomer structure of GJB2 caused by the R143W variant.

THOC6 is a novel biomarker of glioma and a target of anti-glioma drugs: An analysis based on bioinformatics and molecular docking.

Glioma is a typical malignant tumor of the nervous system. It is of great significance to identify new biomarkers for accurate diagnosis of glioma. In this context, THOC6 has been studied as a highly diagnostic prognostic biomarker, which contributes to improve the dilemma in diagnosing gliomas. We used online databases and a variety of statistical methods, such as Wilcoxon rank sum test, Dunn test and t test. We analyzed the mutation, location and expression profile of THOC6, revealing the network of THOC6 interaction with disease. Wilcoxon rank sum test showed that THOC6 is highly expressed in gliomas (P < 0.001). Dunn test, Wilcoxon rank sum test and t test showed that THOC6 expression was correlated with multiple clinical features. Logistic regression analysis further confirmed that THOC6 gene expression was a categorical dependent variable related to clinical features of poor prognosis. Kaplan-Meier survival analysis showed that the overall survival (OS) of glioma patients with high expression of THOC6 was poor (P < 0.001). Both univariate (P < 0.001) and multivariate (P = 0.04) Cox analysis confirmed that THOC6 gene expression was an independent risk factor for OS in patients with glioma. ROC curve analysis showed that THOC6 had a high diagnostic value in glioma (AUC = 0.915). Based on this, we constructed a nomogram to predict patient survival. Enrichment analysis showed that THOC6 expression was associated with multiple signal pathways. Immuno-infiltration analysis showed that the expression of THOC6 in glioma was closely related to the infiltration level of multiple immune cells. Molecular docking results showed that THOC6 might be the target of anti-glioma drugs. THOC6 is a novel diagnostic factor and prognostic biomarker of glioma.

The role of platelets in central hubs of inflammation: A literature review.

Platelets are increasingly recognized for their multifaceted roles in inflammation beyond their traditional involvement in haemostasis. This review consolidates knowledge on platelets as critical players in inflammatory responses. This study did an extensive search of electronic databases and identified studies on platelets in inflammation, focusing on molecular mechanisms, cell interactions, and clinical implications, emphasizing recent publications. Platelets contribute to inflammation via surface receptors, release of mediators, and participation in neutrophil extracellular trap formation. They are implicated in diseases like atherosclerosis, rheumatoid arthritis, and sepsis, highlighting their interaction with immune cells as pivotal in the onset and resolution of inflammation. Platelets are central to regulating inflammation, offering new therapeutic targets for inflammatory diseases. Future research should explore specific molecular pathways of platelets in inflammation for therapeutic intervention.

Synergistic effect of stearic acid/bismuth oxychloride/cupric oxide for thermal storage applications: preparation, stability, rheological and thermophysical analysis

Abstract The present study reports the preparation of nanophase change materials (NPCMs) using a two-step method with an optimized ratio of 0.5 wt.% of nanoparticles for thermal storage applications. Bismuth oxychloride (BiOCl), cupric oxide (CuO), and a mixture of BiOCl/CuO (composite) were used as nanoparticles, and stearic acid was used as the PCM. The crystallography, chemical/functional groups and morphologies of the prepared NPCMs have been analysed by XRD, FT-IR and SEM, respectively. Observations revealed that the presence of nanoparticles in NPCMs did not affect crystal formation or chemical disruption of molecular interactions. TGA was used to analyse the thermal stability and rate of deterioration of the NPCMs. The deterioration of the PCM occurs at 243℃ with a weight loss of 1.3% while 0.5 wt.% concentrated BiOCl, CuO, and composite NPCMs exhibit weight losses of 1.8%, 2.3%, and 3.4%, respectively at 257℃, 262℃ and 258℃. In the DSC study, the phase-changing attributes of the NPCMs manifested in the onset temperature range between 53.4°C and 59.8°C. The potential enthalpy of the PCM is 209.1 kJ/kg, whereas those of the 0.5 wt.% concentrated BiOCl, CuO, and composite NPCMs are 204.6, 198.3, and 201.7 kJ/kg, respectively. However, the enhanced thermal conductivities of 0.5 wt.% concentrated BiOCl, CuO, and the composite NPCMs are 0.18, 0.22, and 0.20 W/(m.℃), respectively, which are 5.9%, 29.4% and 17.6% greater than that of PCM. Additionally, the congruent melting rate increased by 31% for 0.5 wt.% CuO concentrated NPCM; therefore, it is a potential candidate than other NPCMs/PCM. Cyclic tests were conducted to assess the reliability of the NPCMs, and compatible results were obtained even after 500 cycles. The findings of this work indicate that all the prepared NPCMs could be a viable option for practical applications, including thermal comfort buildings, solar heating, and electronic cooling.

Multi-Responsive Peptide-Based Ultrathin Nanosheets Prepared by a Horizontal Monolayer Assembly.

In this study, peptide-based self-assembled nanosheets with a thickness of approximately 1 nm were prepared using a hierarchical covalent physical fabrication strategy. The covalent alternating polymerization of helical peptide E3 with an azobenzene (AZO) structure yielded copolymers CoP(E3-AZO), which physically self-assembled into ultrathin nanosheets in an unanticipated two-dimensional horizontal monolayer arrangement. This special monolayer arrangement enabled the thickness of the nanosheets to be equal to the cross-sectional diameter of a single linear copolymer, which is a rare phenomenon. Molecular dynamics simulations suggested that the synergistic effect of multiple molecular interactions drives the self-assembly of CoP(E3-AZO) into nanosheets and that various methods, including phototreatment, pH adjustment, the addition of additives, and introduction of cosolvents, can alter the molecular interactions and modulate the self-assembly of CoP(E3-AZO), yielding diverse nanostructures. Remarkably, the ultrathin nanosheets selectively inhibited cancer cells at certain concentrations.

Efficient wastewater decontamination using magnetic bentonite-alginate beads: A comprehensive study of adsorption dynamics, regeneration, and molecular interactions

This study enhances wastewater treatment methodologies by developing magnetic bentonite-alginate beads (MBent-A beads) for adsorbing methylene blue (MB) from aqueous solutions. Experimental and computational analyses were employed to evaluate the beads' adsorption efficiency, utilizing characterization techniques including Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), point of zero charge (pHpzc), Brunauer-Emmett-Teller method (BET), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS) to examine the composite’s morphology and chemistry. Findings reveal a significant adsorption capacity with the beads' specific surface area at 3.94 m2/g and a maximum adsorption capacity of 774.32 mg/g. Adsorption kinetics adhered closely to the pseudo-second-order model, indicating a rapid adsorption process, while Langmuir isotherm analysis confirmed a uniform monolayer adsorption and temperature-dependent capacities. Thermodynamic analysis showed the adsorption process to be spontaneous and exothermic, reflecting a strong affinity between MB molecules and the bead surface. The beads demonstrated durability with more than 90% removal efficiency after five regeneration cycles, highlighting a minimal decrease from 98.54% to 90.60%. In-depth theoretical investigations using density functional theory (DFT), frontier molecular orbital (FMO), reduced density gradient (RDG), and quantum theory of atoms in molecules (QTAIM) analyses identified van der Waals forces and hydrogen bonding as primary interactions driving the adsorption. The synthesis of MBent-A beads and their confirmed efficacy in dye adsorption integrates experimental research with theoretical modeling, offering a robust solution for treating dye-contaminated wastewater and underlining the potential of MBent-A beads in environmental remediation.

Multi‐Responsive Peptide‐Based Ultrathin Nanosheets Prepared by a Horizontal Monolayer Assembly

In this study, peptide‐based self‐assembled nanosheets with a thickness of approximately 1 nm were prepared using a hierarchical covalent physical fabrication strategy. The covalent alternating polymerization of helical peptide E3 with an azobenzene (AZO) structure yielded copolymers CoP(E3–AZO), which physically self‐assembled into ultrathin nanosheets in an unanticipated two‐dimensional horizontal monolayer arrangement. This special monolayer arrangement enabled the thickness of the nanosheets to be equal to the cross‐sectional diameter of a single linear copolymer, which is a rare phenomenon. Molecular dynamics simulations suggested that the synergistic effect of multiple molecular interactions drives the self‐assembly of CoP(E3–AZO) into nanosheets and that various methods, including phototreatment, pH adjustment, the addition of additives, and introduction of cosolvents, can alter the molecular interactions and modulate the self‐assembly of CoP(E3–AZO), yielding diverse nanostructures. Remarkably, the ultrathin nanosheets selectively inhibited cancer cells at certain concentrations.

Alkyl Chains Tune Molecular Orientations to Enable Dual Passivation in Inverted Perovskite Solar Cells.

Nonradiative recombination losses occurring at the interface pose a significant obstacle to achieve high-efficiency perovskite solar cells (PSCs), particularly in inverted PSCs. Passivating surface defects using molecules with different functional groups represents one of the key strategies for enhancing PSCs efficiency. However, a lack of insight into the passivation orientation of molecules on the surface is a challenge for rational molecular design. In this study, aminothiol hydrochlorides with different alkyl chains but identical electron-donating (-SH) and electron-withdrawing (-NH3+) groups were employed to investigate the interplay between molecular structure, orientation, and interaction on perovskite surface. The 2-Aminoethane-1-thiol hydrochloride with shorter alkyl chains exhibited a preference of parallel orientations, which facilitating stronger interactions with the surface defects through strong coordination and hydrogen bonding. The resultant perovskite films following defect passivation demonstrate reduced ion migration, inhibition of nonradiative recombination, and more n-type characteristics for efficient electron transfer. Consequently, an impressive power conversion efficiency of 25% was achieved, maintaining 95% of its initial efficiency after 500 hours of continuous maximum power point tracking.

Identification and analysis of chemokine-related and NETosis-related genes in acute pancreatitis to develop a predictive model

Background: Chemokines and NETosis are significant contributors to the inflammatory response, yet there still needs to be a more comprehensive understanding regarding the specific molecular characteristics and interactions of NETosis and chemokines in the context of acute pancreatitis (AP) and severe AP (SAP).Methods: To address this gap, the mRNA expression profile dataset GSE194331 was utilized for analysis, comprising 87 AP samples (77 non-SAP and 10 SAP) and 32 healthy control samples. Enrichment analyses were conducted for differentially expressed chemokine-related genes (DECRGs) and NETosis-related genes (DENRGs). Three machine-learning algorithms were used for the identification of signature genes, which were subsequently utilized in the development and validation of nomogram diagnostic models for the prediction of AP and SAP. Furthermore, single-gene Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed. Lastly, an interaction network for the identified signature genes was constructed.Results: We identified 12 DECRGs and 7 DENRGs, and enrichment analyses indicated they were primarily enriched in cytokine-cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and T cell receptor signaling pathway. Moreover, these machine learning algorithms finally recognized three signature genes (S100A8, AIF1, and IL18). Utilizing the identified signature genes, we developed nomogram models with high predictive accuracy for AP and differentiation of SAP from non-SAP, as demonstrated by area under the curve (AUC) values of 0.968 (95% CI 0.937–0.990) and 0.862 (95% CI 0.742–0.955), respectively, in receiver operating characteristic (ROC) curve analysis. Subsequent single-gene GESA and GSVA indicated a significant positive correlation between these signature genes and the proteasome complex. At the same time, a negative association was observed with the Th1 and Th2 cell differentiation signaling pathways.Conclusion: We have identified three genes (S100A8, AIF1, and IL18) related to chemokines and NETosis, and have developed accurate diagnostic models that might provide a novel method for diagnosing AP and differentiating between severe and non-severe cases.

Study of molecular dynamic interactions during the optimized extrusion processing of corn (Zea mays) and substandard bean (Phaseolus vulgaris)

Within the agri-food industry, substantial quantities of by-products are generated during the collection of raw materials and the preparation of derived food products. A common by-product is the low-value substandard bean that might have structural damages but retains its nutritional characteristics. This research aimed to evaluate the compatibility of bean protein with corn flour starch within an extruded snack model through molecular dynamics simulation by the calculation of the solubility parameter (δ). For the extrusion processing, a central composite design was used with four factors: temperature [150–190 °C], screw speed [150–210 rpm], moisture content [14–18%] and substandard bean content [20–80%]. Simulation calculations were performed using Materials Studio 8.0 software (Accelrys, San Diego, CA). The bean protein was identified as ARC5A, and its structure was obtained from the UniProt database. Starch and protein models evaluated within a temperature profile [25–150 °C] emulating the extrusion processing showed Δδ < 7.0 MPa0.5, indicating that are likely miscible. Optimal processing conditions of the extruded snack were obtained. This research developed an extruded snack using an agro-industrial by-product while predicting the solubility and miscibility parameters of more compounds using molecular dynamics simulations.

Alkyl Chains Tune Molecular Orientations to Enable Dual Passivation in Inverted Perovskite Solar Cells

Nonradiative recombination losses occurring at the interface pose a significant obstacle to achieve high‐efficiency perovskite solar cells (PSCs), particularly in inverted PSCs. Passivating surface defects using molecules with different functional groups represents one of the key strategies for enhancing PSCs efficiency. However, a lack of insight into the passivation orientation of molecules on the surface is a challenge for rational molecular design. In this study, aminothiol hydrochlorides with different alkyl chains but identical electron‐donating (‐SH) and electron‐withdrawing (‐NH3+) groups were employed to investigate the interplay between molecular structure, orientation, and interaction on perovskite surface. The 2‐Aminoethane‐1‐thiol hydrochloride with shorter alkyl chains exhibited a preference of parallel orientations, which facilitating stronger interactions with the surface defects through strong coordination and hydrogen bonding. The resultant perovskite films following defect passivation demonstrate reduced ion migration, inhibition of nonradiative recombination, and more n‐type characteristics for efficient electron transfer. Consequently, an impressive power conversion efficiency of 25% was achieved, maintaining 95% of its initial efficiency after 500 hours of continuous maximum power point tracking.

Boosting the performance of polymer field-effect transistors through fluorine atom substitutions and comparing the effect of various acceptor units and channel mobilities

Three conjugated copolymers, PDPP-2FTVT, PIID-2FTVT, and PNDI-2FTVT based on the 2,2′-(1E)-1,2-ethenediylbis[3-fluorothiophene] (2FTVT) core with varying acceptor units, diketopyrrolopyrrole (DPP), isoindigo (IID), and naphthalenediimide (NDI) were developed for organic field-effect transistors (OFETs). Combined electron-withdrawing fluorine atoms and vinyl linkage in the 2FTVT unit not only reduce the frontier molecular orbital energies but also extended the absorption profile and planarize the polymer backbone, manifesting synergetic effect on the strengthened molecular interactions and charge-carrier properties. The resulted copolymer, PDPP-2FTVT show highly reliable thin film transistor properties with highest hole mobility of 1.93 cm2 V−1 s−1 compared to PIID-2FTV and PNDI-2FTVT. PIID-2FTV copolymer show ambipolar characteristic with hole and electron mobilities of 0.71 and 0.03 cm2 V−1 s−1 respectively while PNDI-2FTVT exhibited the highest electron mobility of 0.20 cm2 V−1 s−1 among three copolymers. Thin film micro-structure characterization reveal that the three copolymers formed lamellar, edge-on molecular packing (for PDPP-2FTVT and PIID-2FTV), increased crystallinity with smaller π-π stacking distances, and strengthen the planarity after thermal annealing. These results contribute important progresses in solution-processed OFET and could provide a greater possibility of 2FTVT based copolymers for commercial application.

Effects of Adding Sorghum Procyanidins on the Structure, Molecular Interactions, and Thermal Properties of Agar-Glycerol-Gelatin Films

Films made with blends of agar and gelatin are usually unstable in aqueous environments and susceptible to temperature, so modifying these films with the addition of compatible compounds is necessary to improve their structural stability, properties, and potential uses. This work determined the effects of adding sorghum procyanidins on the structure, molecular interactions and thermal properties of agar-glycerol-gelatin films. Films were prepared by solution cast method and characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and computational methods. Adding sorghum procyanidins to agar-gelatin films plasticized with glycerol produced significant modifications compared to control films. They contributed to the amorphous character and roughness of these films and the film’s microstructure, reducing weight loss and enhancing thermal stability. The predominant interactions among the film components were hydrogen bonds, van der Waals, and [Formula: see text]–[Formula: see text] interactions.

Taxifolin alleviate metabolic and neurochemical alterations in the hippocampus and cortex of rats with rotenone-induced toxicity: In vivo and in silico insight

IntroductionExposure to rotenone could directly affects the function of mitochondrial which leads to neurodegeneration. This study evaluated the therapeutic potential of taxifolin (Huāqí sōng dài; 花旗松甙) to alleviate metabolic and neurochemical alterations in the hippocampal and cortical region of brain of rotenone-toxified rats. MethodsMale Wistar rats were subcutaneously administered 1.5 mg/kg rotenone for 10 days, followed by post-treatment with varying doses of taxifolin (0.25, 0.5 and 1.0 mg/kg) for 3 days through the same route. Activities of mitochondrial complex I, membrane ion pump and lactate dehydrogenase (LDH) were evaluated in the hippocampus and cortex of the brain of rotenone-toxified rats. Markers of neurotransmitter metabolism and oxidative stress were also biochemically estimated and molecular interaction between taxifolin and tyrosine hydroxylase, monoamine oxidase, glutamine synthetase and Na+/K+ATPase was determined by in silico simulation. ResultsTaxifolin attenuated dysfunction of mitochondrial, Na+/K+ATPase, LDH and modulate neurotransmitter metabolism. Also, the elicited oxidative stress was mitigated by taxifolin in the hippocampus and cortex of the brain of rotenone-toxified rats. Furthermore, taxifolin showed excellent interactions with targeted enzymes in silico. The highest binding affinity was recorded in taxifolin-tyrosine hydroxylase complex. Hydrogen bond and hydrophobic interactions were the two key molecular interaction between the taxifolin and targeted enzymes. DiscussionTaxifolin alleviates metabolic and neurochemical aberrations in rotenone-induced neurotoxicity model in rats in vivo and exhibits promising interactions with specific target enzymes that are key to neurotransmission in silico.

Design, synthesis and Anti-PVY activity of planar chiral thiourea derivatives incorporated with [2.2]Paracyclophane.

Potato virus Y (PVY) is a prominent representative of plant viruses. It can inflict severe damage upon Solanaceae plants, leading to global dissemination and substantial economic losses. To discover new antiviral agents, a class of planar chiral thiourea molecules through the key step of N-heterocyclic carbene-catalyzed nitrile formation reaction was synthesized with excellent optical purities for antiviral evaluations against plant virus PVY. The absolute configurations of the planar chiral compounds exhibited obvious distinctions in the anti-PVY activities. Notability, compound (S)-4u exhibited remarkable curative activities against PVY, with a half maximal effective concentration (EC50) of 349.3 μg mL-1, which was lower than that of the ningnanmycin (NNM) (EC50 = 400.8 μg mL-1). Additionally, The EC50 value for the protective effects of (S)-4u was 146.2 μg mL-1, which was superior to that of NNM (276.4 μg mL-1). Furthermore, the mechanism-of-action of enantiomers of planar chiral compound 4u was investigated through molecular docking, defensive enzyme activity tests and chlorophyll content tests. Biological mechanism studies have demonstrated that the configuration of planar chiral target compounds plays a crucial role in the molecular interaction with PVY-CP, enhancing the activity of defense enzymes and affecting chlorophyll content. The current study has provided significant insights into the roles played by planar chiralities in plant protection against viruses. This paves the way for the development of novel green pesticides bearing planar chiralities with excellent optical purities. © 2024 Society of Chemical Industry.

An end-cloud collaboration approach for online state-of-health estimation of lithium-ion batteries based on multi-feature and transformer

State-of-Health (SOH) estimation of lithium-ion batteries is critical for reliable and efficient energy storage and usage. Traditional SOH estimation approaches either compromise on real-time performance or on estimation accuracy. This paper introduces an end-cloud collaboration approach that synergistically combines a cloud-based deep learning model with an end-based empirical model to achieve both high-accuracy and real-time SOH estimation. Utilizing the Transformer architecture, the cloud-side model employs multiple features extracted through signal analysis technology. On the other hand, the end-side employs a fast, iterative double exponential empirical model that provides real-time estimates. Two methods of end-cloud collaborative updating are presented, both leveraging Kalman Filter and Unscented Kalman Filter (UKF) to integrate and iteratively update the models. Evaluation shows that the cloud-side model achieves a Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of around 0.8 %, while the end-cloud collaboration system maintains these metrics at 1 %, successfully capturing nonlinear capacity rebound phenomena. The work contributes to the domain by offering an approach that balances computational load and latency, making it suitable for online applications. Under the Cyber Hierarchy and Interactional Network (CHAIN) framework, this end-cloud collaboration architecture holds promise for high-accuracy, real-time health management of lithium-ion batteries across their full lifecycle.