Thermodynamics of protein-ligand interactions seems to be associated to a narrow range of Gibbs Free Energy. As a consequence, a linear enthalpy-entropy relationship showing an apparent Enthalpy-Entropy compensation (EEC) is frequently observed associated to the study of protein-ligand interactions. This EEC affects negatively the design and discovery of new and more efficient drugs capable of binding protein-targets with a higher affinity. Originally attributed to experimental errors, compensation between H and TS values is a real observable fact, although its molecular origin has remained obscure and controversial. Herein we show the results of a data search of G values of 2558 protein-ligand interactions and 3025 “in vivo” ligand concentrations from the Protein Data Bank bind Database and the Metabolome Data Base (2020). These results, together with the mechano-statistical interpretation of the thermodynamic properties leads to the conclusion that the EEC has no basis in statistical thermodynamics. It can be plausibly explained as a consequence of the narrow range of G associated to protein-ligand interactions. The Gaussian distribution of the G values matches very well with that of ligands. These results suggest the hypothesis that the set of G values for the protein-ligand interactions is the result of the evolution of proteins. The conformation versatility of present proteins and the exchange of thousands (even millions) of minute amounts of energy with the environment may have functioned as a homeostatic mechanism to make G of proteins adaptive to changes in availability of ligands, and therefore achieve the maximum regulatory capacity of the protein function. Finally, a plausible strategy to avoid the EEC is suggested.

The progesterone receptor (PR) mediates progesterone regulation of female reproductive physiology, as well as gene transcription in non-reproductive tissues, such as brain, bone, lung and vasculature, in both women and men. An unusual property of progesterone is its high affinity for the mineralocorticoid receptor (MR), which regulates electrolyte transport in the kidney in humans and other terrestrial vertebrates. In humans, rats, alligators and frogs, progesterone antagonizes activation of the MR by aldosterone, the physiological mineralocorticoid in terrestrial vertebrates. In contrast, in elephant shark, ray-finned fishes and chickens, progesterone activates the MR. Interestingly, cartilaginous fishes and ray-finned fishes do not synthesize aldosterone, raising the question of which steroid(s) activate the MR in cartilaginous fishes and ray-finned fishes. The simpler synthesis of progesterone, compared to cortisol and other corticosteroids, makes progesterone a candidate physiological activator of the MR in elephant sharks and ray-finned fishes. Elephant shark and ray-finned fish MRs are expressed in diverse tissues, including heart, brain and lung, as well as, ovary and testis, two reproductive tissues that are targets for progesterone, which together suggests a multi-faceted physiological role for progesterone activation of the MR in elephant shark and ray-finned fish. The functional consequences of progesterone as an antagonist of some terrestrial vertebrate MRs and as an agonist of fish and chicken MRs are not fully understood. Indeed, little is known of physiological activities of progesterone via any vertebrate MR.

Heptanuclear {GdIII7} (complex 1) and tetradecanuclear {GdIII14} (complex 2) have been synthesized using a Rhodamine 6G ligand HL (Rhodamine 6G salicylaldehyde hydrazone) and characterized. Complex 1 has a rare disc-shaped structure, where the central Gd ion was connected to the peripheral six GdIII ions via CH3O-/μ3-OH- bridges. Complex 2 has an unexpected three-layer double sandwich structure with a rare μ6-O2- ion in the center of the cluster. Magnetic studies revealed that complex 1 exhibits a magnetic entropy change of 17.4 J kg−1 K−1 at 3 K and 5 T. On the other hand, complex 2 shows a higher magnetic entropy change of 22.3 J kg−1 K−1 at 2 K and 5 T.

G-protein-coupled receptors (GPCRs) are ubiquitous sensors and regulators of cellular functions. Each GPCR exists in complex aggregates with multiple resting and active conformations. Designed to detect weak stimuli, GPCRs can also activate spontaneously, resulting in basal ligand-free signaling. Agonists trigger a cascade of events leading to an activate agonist-receptor-G protein complex with high agonist affinity. However, the ensuing signaling process can further remodel the receptor complex to reduce agonist affinity, causing rapid ligand dissociation. The acutely activated ligand-free receptor can continue signaling, as proposed for rhodopsin and  opioid receptors, resulting in robust receptor activation at low agonist occupancy with enhanced agonist potency. Continued receptor stimulation can further modify the receptor complex, regulating sustained ligand-free signaling - proposed to play a role in opioid dependence. Basal, acutely agonist-triggered, and sustained elevated ligand-free signaling could each have distinct functions, reflecting multi-state conformations of GPCRs. This review addresses basal and stimulus-activated ligand-free signaling, its regulation, genetic factors, and pharmacological implications, focusing on opioid and serotonin receptors, and the growth hormone secretagogue receptor (GHSR). Ligand-free signaling of intracellular 5-HT2A receptors could mediate therapeutic effects of psychedelic drugs. Research avenues are suggested to close gaps in our knowledge of ligand-free GPCR signaling.

Interactions between proteins and ions are essential for various biological functions like structural stability, metabolism, and signal transport. Given that more than half of all proteins bind to ions, it becomes crucial to identify ion-binding sites. Accurate identification of protein-ion binding sites helps us to understand proteins’ biological functions and plays a significant role in drug discovery. While several computational approaches have been proposed, this remains a challenging problem due to the small size and high versatility of metals and acid radicals. In this study, we propose IonPred, a sequence-based approach that employs ELECTRA (Efficiently Learning an Encoder that Classifies Token Replacements Accurately) to predict ion binding sites using only raw protein sequences. We successfully fine-tuned our pretrained model to predict the binding sites for nine metal ions (Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, and K+) and four acid radical ion ligands (CO32−, SO42−, PO43−, NO2−). IonPred surpassed six current state-of-the-art tools by over 44.65% and 28.46% respectively in F1 score and MCC when compared on an independent test dataset. Our method is more computationally efficient than existing tools producing prediction results for a hundred sequences for a specific ion in under ten minutes.

The reckless use of non-replenishable fuels by the growing population for energy and the resultant incessant emission of hazardous gases and waste products into the atmosphere insisted scientists to fabricate materials capable of managing these global threats at once. In recent studies, photo-catalysis employed focus on utilizing renewable solar energy to initiate chemical processes with the aid of semiconductors and highly selective catalysts. A wide range of nanoparticles have showcased promising photocatalytic properties. Ultrasmall metal nanoclusters (MNCs) with sizes below 2 nm, stabilized by ligands shows discrete energy levels, exhibits unique optoelectronic properties which are vital to photocatalysis. In this review, we intend to compile information on varying photocatalytic efficiency of metal NCs with respect to changes in their properties. Review discusses about the photocatalytic activity of atomically precise ligand-protected MNCs and its hybrids in the domain of in energy conversion processes like photodegradation of dyes, Oxygen Evolution Reaction (ORR), Hydrogen Evolution Reaction (HER) and CO2 Reduction Reaction (CO2RR), and photosensitizer in solar cell.

Different dopamine receptor (DR) subtypes are involved in pathophysiological conditions such as Parkinson´s Disease (PD), schizophrenia and depression. While many DR-targeting drugs have been approved by the FDA, only a very small number is truly selective for one of the DR subtypes. Additionally, most of them show promiscuous activity at related G-protein coupled receptors, thus suffering from diverse side-effect profiles. Multiple studies have shown that combined in silico / in vitro approaches are a valuable contribution to drug discovery processes. They can also be applied to divulge the mechanisms behind ligand selectivity. In this study, novel DR ligands were investigated in vitro to assess binding affinities at different DR subtypes. Thus, nine D2R/D3R-selective ligands (micro- to nanomolar binding affinities, D3R-selective profile) were successfully identified. The most promising ligand exerted nanomolar D3R activity (KI = 2.3 nM) with 263.7-fold D2R/D3R selectivity. Subsequently, ligand selectivity was rationalized in silico based on ligand interaction with a secondary binding pocket, supporting selectivity data determined in vitro. The developed workflow and identified ligands could aid in the further understanding of structural motifs responsible for DR subtype selectivity, thus, benefitting drug development in D2R/D3R-associated pathologies like PD.

Diarylethene is a prototypical molecular switch that can be reversibly photoisomerized between its open and closed forms. Ligands bpy-DAE-bpy, consisting of a phenyl-diarylethene-phenyl (DAE) central core and bipyridine (bpy) terminal substituents, are able to self-organize. They are investigated by scanning tunneling microscopy at the solid-liquid interface. Upon light irradiation, cooperative photochromic switching of the ligands is recognized down to the sub-molecular level. The closed isomers show different electron density of states (DOS) contrasts, attributed to the HOMO or LUMO molecular orbitals observed. More importantly, the LUMO images show remarkable differences between the open and closed isomers, attributed to combined topographic and electronic contrasts mainly on the DAE moieties. The electronic contrasts from multiple HOMO or LUMO distributions, combined with topographic distortion of the open or closed DAE, are interpreted by density functional theory (DFT) calculations.

Three monoruthenium complexes 1(PF6)23(PF6)2 bearing a N(CH3)-bridged ligand have been synthesized and characterized. These complexes have a general formula of [Ru(bpy)2(L)](PF6)2, where L is a 2,5-di(N-methyl-N-(pyrid-2-yl)amino)pyrazine (dapz) derivative with various substituents and bpy is 2,2′-bipyridine. The photophyscial and electrochemical properties of these compounds have been examined. The solid-state structure of complex 3(PF6)2 is studied by single crystal X-ray analysis. These complexes show two well-separated emission bands centered at 451 and 646 nm (max = 195 nm) for 1(PF6)2, 465 and 627 nm (max = 162 nm) for 2(PF6)2, and 455 and 608 nm (max = 153 nm) for 3(PF6)2 in dilute acetonitrile solution, respectively. The emission maxima of the higher-energy emission bands of these complexes are similar, while the lower-energy emission bands are dependent on the electronic nature of substituents. These complexes display two consecutive redox couples owing to the stepwise oxidation of the N(CH3)-bridged ligand and ruthenium component. In addition, density functional theory (DFT) and time-dependent density functional theory (TD-DFT) calculations are carried out to elucidate these experimental findings.

Human ether-a-go-go-related gene (hERG) potassium channel is well-known contributor to drug-induced cardiotoxicity and therefore an extremely important target when performing safety assessments of drug candidates. Ligand-based approaches in connection with quantitative structure active relationships (QSAR) analyses have been developed to predict hERG toxicity. Availability of the recent published cryogenic electron microscopy (cryo-EM) structure for the hERG channel opened the prospect for using structure-based simulation and docking approaches for hERG drug liability predictions. In recent time, the idea of combining structure- and ligand-based approaches for modeling hERG drug liability has gained momentum offering improvements in predictability when compared to ligand-based QSAR practices alone. The present article demonstrates uniting the structure-based SILCS (site-identification by ligand competitive saturation) approach in conjunction with physicochemical properties to develop predictive models for hERG blockade. This combination leads to improved model predictability based on Pearson’s R and percent correct (represents rank-ordering of ligands) metric for different validation sets of hERG blockers involving diverse chemical scaffold and wide range of pIC50 values. The inclusion of the SILCS structure-based approach allows determination of the hERG region to which compounds bind and the contribution of different chemical moieties in the compounds to blockade, thereby facilitating the rational ligand design to minimize hERG liability.

Two ligands, 1, 3-bis(4-carboxyphenyl)imidazolium chloride and 4, 4՛-bipyridine, were employed to prepare nickel and zinc azolium based MOFs, 1 and 2 by the mixed ligand solvothermal approach. The positively charged azolium moieties in the imidazolium linker resulted in a charged environment in the as-synthesized frameworks. As a result, 1 and 2 demonstrated preferential adsorption of CO2 over methane molecules in the gas phase adsorption due to the higher quadruple moment of CO2, which interacts more with the positively charged frameworks. Besides, in aqueous media, 1 and 2 exhibited incredible adsorption efficiency for anionic dyes. In the following, MOF 1 was metallated at the carbene site of the azolium linker to generate the novel heterogeneous catalyst 1-Pd, which was successfully applied for Sonogashira and Suzuki-Miyaura coupling reactions without losing its activity after three cycles.

The epidermal growth factor receptor (EGFR) plays vital roles in cellular processes including cell proliferation, survival, motility and differentiation. Dysregulated activation of the receptor is often implicated in human cancers. EGFR is synthesized as a single-pass transmembrane protein, which consists of an extracellular ligand-binding domain and an intracellular kinase domain separated by a single transmembrane domain. The receptor is activated by a variety of polypeptide ligands such as epidermal growth factor and transforming growth factor α. It has long been thought that EGFR is activated by ligand-induced dimerization of the receptor monomer, which brings intracellular kinase domains into close proximity for trans-autophosphorylation. An increasing number of diverse studies, however, demonstrate that EGFR is present as a pre-formed, yet inactive, dimer prior to ligand binding. Furthermore, recent progress in structural studies has provided insight into conformational changes during the activation of a pre-formed EGFR dimer. Upon ligand binding to the extracellular domain of EGFR, its transmembrane domains rotate or twist parallel to the plane of the cell membrane, resulting in reorientation of the intracellular kinase domain dimer from a symmetric inactive configuration to an asymmetric active form (the “rotation model”). This model is also able to explain how oncogenic mutations activate the receptor in the absence of ligand without assuming that the mutations induce receptor dimerization. In this review, we discuss mechanisms underlying ligand-induced activation of the preformed EGFR dimer, as well as how oncogenic mutations constitutively activate the receptor dimer, based on the rotation model.

Cyclooxygenases (COX), or prostaglandin endoperoxide synthases (PTGS), are key enzimes in the synthesis of prostaglandins, which are chemical species critical in mediating inflammatory processes. There are two highly homologous COX isoforms: COX-1 and COX-2. COX-1 is involved in the production of prostaglandins, chemical compuounds that take part in physiological processes such as: protection of the gastric epithelium, maintenance of renal flow, platelet aggregation, neutrophil migration and, also, are expressed in the vascular endothelium. Meanwhile, COX-2 is induced by proinflammatory stimuli. It is very frequent the use of nonsteroidal antiinflammatory drugs (NSAIDs) to counteract the symptoms of inflammatory processes. These drugs, in addition to its benefits, can cause side effects on people’s health, such as cardiovascular and respiratory problems, among others. In the past years, it has been recognized the potential of plants secondary metabolites as pharmacological agents, prompting the need for investigations that shed light into its mechanism of action. In this work we have applied computational techniques, based on quantum chemistry and mechanical statistics, to study the protein-ligand interaction involving COX’s and secondary metabolites from natural sources. Our aim is to determine the structure activity interplay in processes involving the participation of secondary plant metabolites such as luteolin, galangin, kaempferol, apigenin, morine and quercetin on the inactivation of COX’s. From molecular docking analysis, we have extracted the energetics of the COX-(1,2)/metabolite coupling. By defining energy based factors, we have determined a procedure that predicts the chemical species with highest stability and selectivity towards inactivation of COX-2 over COX-1. The results are discussed with regard to conformational features of the selected ligands and its intermolecular strong/weak interactions inside the active-sites of the COX’s hosts.

Background: Selectively targeting dopamine receptors has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases evolving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific binding mode on a molecular basis has not been fully elucidated. Methods: Homology modeling and molecular dynamics were applied to construct robust conformational models of all dopamine receptor subtypes (D1-like and D2-like receptors). Fifteen structurally diverse ligands were docked to these models. Contacts at the binding pocket were fully described in order to reveal new structural findings responsible for DR sub-type specificity. Results: We showed that the number of conformations for a receptor:ligand complex was associated to unspecific interactions > 2.5 Å and hydrophobic contacts, while the decoys binding energy was influenced by specific electrostatic interactions. Known residues such as 3.32Asp, the serine microdomain and the aromatic microdomain were found interacting in a variety of modes (HB, SB, π-stacking). Purposed TM2-TM3-TM7 microdomain was found to form a hydrophobic network involving Orthosteric Binding Pocket (OBP) and Secondary Binding Pocket (SBP). T-stacking interactions revealed as especially relevant for some large ligands such as apomorphine, risperidone or aripiprazole. Conclusions: This in silico approach was successful in showing known receptor-ligand interactions as well as in determining unique combinations of interactions, key for the design of more specific ligands.

Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain development, and prostate cancer, among others. State-of-the-art databases with experimental data of human, chimp, and rat effects by chemicals have been used to build machine learning classifiers and regressors and evaluate these on independent sets. Different featurizations, algorithms, and protein structures lead to dif- ferent results, with deep neural networks (DNNs) on user-defined physicochemically-relevant features developed for this work outperforming graph convolutional, random forest, and large featurizations. The results show that these user-provided structure-, ligand-, and statistically-based features and specific DNNs provided the best results as determined by AUC (0.87), MCC (0.47), and other metrics and by their interpretability and chemical meaning of the descriptors/features. In addition, the same features in the DNN method performed better than in a multivariate logistic model: validation MCC = 0.468 and training MCC = 0.868 for the present work compared to evalu- ation set MCC = 0.2036 and training set MCC = 0.5364 for the multivariate logistic regression on the full, unbalanced set. Techniques of this type may improve AR and toxicity description and predic- tion, improving assessment and design of compounds. Source code and data are available at https://github.com/AlfonsoTGarcia-Sosa/ML

In the present work, we report on a 3D MOF of {[Pb5(3-OH)(3-NO3)3(6-pmdc)3·H2O}n formula (pmdc = pyrimidine-4,6-dicarboxylate) synthesized by an oven-heated solvent-free procedure. The large connectivity afforded by the three ligands in their coordination to lead(II) ions grows cubic building units characterized by a central Pb atom with an unusual coordination index of 12 and six pmdc ligands occupying the faces. These cubic units are linked one another giving rise to a quite condensed structure that represents an unprecedented topology showing the (4.62)6(43)2(45.610)3(45.68.82)6(46.69)6(612.83) point symbol. The crystalline material has been characterized by routine physico-chemical techniques to confirm its purity and its thermal behaviour has been also studied by thermogravimetric and thermodiffractometric analyses. The solid presents greenish blue photoluminescent emission based on pmdc ligands, as revealed time-dependent density-functional theory (TD-DFT) calculations, by that is substantially more intense than in free H2pmdc ligand according to its improved quantum yield. The emissive capacity of the material is further analysed according to decreasing temperature of the polycrystalline sample, finding that sizeable long-lasting phosphorescence is present.

The 1,2,3-triazole derivative 2-(4-chlorophenyl)-5-(pyrrolidin-1-yl)-2H-1,2,3-triazole-4-carboxylic acid with potential anticancer activity was used as a ligand in complex formation with the lan-thanum(III) ion. The molecular structure and vibrational spectra of the complex were optimized at three DFT levels and the scaled IR and Raman spectra were compared to the experimental ones. Several scaling procedures were used. Through a detailed analysis, the structure predicted for the newly synthetized La(III) complex was confirmed by the good accordance of the calculat-ed-experimental IR and Raman spectra. The best DFT method appears to be M06-2X with the Lanl2mb basis set, followed closely by Lanl2dz. The effect of the lanthanide atom on the molecular structure and atomic charge distribution of the triazole ring was evaluated. Potential free radical scavenging activity of both, ligand and complex, was investigated in several radical-generating model systems. Potential mechanisms of antioxidant action (hydrogen atom transfer – HAT and single electron transfer - SET) were elucidated.

Prediction of protein-ligand binding affinities is crucial for computational drug discovery. A number of deep learning approaches have been developed in recent years to improve the accuracy of such affinity prediction. While the predicting power of these systems have advanced to some degrees depending on the dataset used for model training and testing, the effects of the quality and quantity of the underlying data have not been thoroughly examined. In this study, we employed erroneous datasets and data subsets of different sizes, created from one of the largest databases of experimental binding affinities, to train and evaluate a deep learning system based on convolutional neural networks. Our results show that data quality and quantity do have significant impacts on the prediction performance of trained models. Depending on the variations in data quality and quantity, the performance discrepancies could be comparable to or even larger than those observed among different deep learning approaches. In particular, the presence of proteins during model training leads to a dramatic increase in prediction accuracy. This implies that continued accumulation of high-quality affinity data, especially for new protein targets, is indispensable for improving deep learning models to better predict protein-ligand binding affinities.

Focused electron beam induced deposition is a versatile tool for the direct fabrication of complex-shaped nanostructures with unprecedented shape fidelity and resolution. While the technique is well-established for various materials, the direct electron beam writing of silver is still in its infancy. Here, five different silver carboxylates, three fluorinated: [Ag2(µ-O2CCF3)2], [Ag2(µ-O2CC2F5)2], [Ag2(µ-O2CC3F7)2] and two containing hydrogen: [Ag2(µ-O2CCMe2Et)2] and [Ag2(µ-O2CtBu)2] were examined and compared as potential precursors for focused electron beam induced deposition. All of the compounds show high sensitivity to electron dissociation and efficient dissociation of Ag-O bonds. The as-deposited materials showed high silver content from 42 at.% to above 70at.% and silver nano-crystal formation with impurities of carbon and fluorine incorporated between metal grains. A correlation of the number of carbon atoms in the precursor ligands and silver content of the deposited structures was found. The highest silver contents were achieved for compounds with the shortest CF chains. The deposited silver content depends on the balance of electron induced ligand co-deposition and thermal ligand desorption. Low electron flux is advantageous for high silver content. Our findings demonstrate that silver carboxylates constitute a promising group of precursors for focused electron beam nanoprinting of high silver content materials.

SARS-CoV2 (corona virus) has spread globally at an unprecedented rate; so far, increasing SARS-CoV2-infected individuals have been identified. Although the situation in China is improving and is currently under control, the outbreak in other countries and its pandemic management is only beginning to develop. Based on 154 SARS-CoV2 genome sequence analyses, we used receptor–ligand docking to identify one potential point mutation (V354F) on the spike structure which enhances spike binding to ACE2 receptors underlying potential super infection. Importantly, the V354F site on spike S1 had been identified in 5/10 infected French patients living in Paris, who sharing 100% identical SARS-CoV2 genomes. With Covid-19 cases increasing rapidly in France that could lead to a new explosion, we suggest that the French government should identify all potential super spreaders and treat them accordingly. In summary, our study provides on of the measures to avoid the potential second worldwide explosion of SARS-CoV2.

G-protein coupled receptors (GPCRs) are large protein families known to be important in many cellular processes. They are well known for their allosteric activation mechanisms. They are drug targets for several FDA-approved drugs. We have investigated the diversity of the ligand binding site for these class of proteins against their cognate ligands using computational docking, even if their structures are known in the ligand-complexed form. The cognate ligand of some of these receptors dock at allosteric binding site, with better score than the binding at the conservative site. Further, ligands obtained from GLASS database, which consists of experimentally verified GPCR ligands, also show allosteric binding to GPCRs. The allosteric binders show strong affinity to the binding site, though the residues at the binding site are not conserved across GPCR subfamilies.

The activity and cyclability of Cu-MOF-74 as catalyst was studied for the ligand-free C-O cross-coupling reaction of 4-nitrobenzaldehyde (NB) with phenol (Ph) to form 4-formyldiphenyl ether (FDE). Cu-MOF-74 is characterized by unsaturated copper sites in a highly porous metal-organic framework. The influence of solvent, reaction temperature, NB/Ph ratio, catalyst concentration and basic agent (type and concentration) were evaluated. High conversions were achieved at 120°C, 5 mol% of catalyst, NB/Ph ratio of 1:2, DMF as solvent and 1 equivalent of K2CO3 base. The activity of Cu-MOF-74 material was higher than other ligand-free copper catalytic systems tested in this study. This catalyst was easily separated and reused in five successive runs, achieving a remarkable performance without significant porous framework degradation. The leaching of copper species in the reaction medium was negligible. The O-arylation between NB and Ph took place only in the presence of Cu-MOF-74 material, being negligible without the solid catalyst.

Background; Programmed death-1 (PD-1) and PD-1 ligand 1 (PD-L1) are target molecules for immunotherapy in non-small cell lung cancer. PD-L1 is expressed not only in cancer cells, but also on macrophages, and has been suggested to contribute to macrophage-mediated immune suppression. Methods; Clinical significance of PD-L1 expression on macrophages in human lung adenocarcinoma was examined. The mechanisms of PD-L1 overexpression on macrophages were investigated by means of cell culture studies. Results; High PD-L1 expression on macrophages was correlated with the presence of EGFR mutation, a lower cancer grade, and a shorter cancer-specific overall survival. In an in vitro study using lung cancer cell lines and human monocyte-derived macrophages, the conditioned medium from cancer cells was found to up-regulate PD-L1 expression on macrophages via STAT3 activation, and a cytokine array revealed that granulocyte-macrophage colony-stimulating factor (GM-CSF) was a candidate factor that induced PD-L1 expression. Culture studies using recombinant GM-CSF, neutralizing antibody, and inhibitors indicated that PD-L1 overexpression was induced via STAT3 activation by GM-CSF derived from cancer cells. Conclusions; PD-L1 overexpression on macrophages via the GM-CSF/STAT3 pathway was suggested to promote cancer progression in lung adenocarcinoma. Cancer cell-derived GM-CSF might be a promising target for anti-cancer therapy.

The influence of the ligands in coupled organic-inorganic nanostructures (COINs) on the performance of optoelectronic devices is investigated. We fabricated photodiodes based on pentacene and PbS nanocrystals coupled to organic ligands like 1,2-ethanedithiol (EDT) and tetrabutylammonium iodide (TBAI) and a combination of both, EDT and TBAI, as a heterostructure. These ligands were first separately used to fabricate single ligand-type of organic-inorganic devices and later compared with a heterostructure of PbS-EDT and PbS-TBAI. To tune the optical energy gap of COINs to align with the triplet level of pentacene, it was necessary to choose a suitable particle size. For this purpose, ultraviolet photo-emission spectroscopy (UPS) was used to determine the energy of the highest occupied molecular orbital (HOMO) and the work function of COINs, while the energy of the lowest unoccupied molecular orbital (LUMO) of COINs was estimated subsequently by adding the exciton binding energy and the optical band gap to the measured HOMO energy. Devices with heterostructure COINs achieve a higher short circuit current than COINs with a single type of the ligands. Finally, even if the requirements of proper energy level alignment are satisfied, the photodiodes' performance was affected by the morphology of COINs. This finding has been demonstrated by atomic force microscopy (AFM) and transmission electron microscopy (TEM). Incident photon to current efficiency (IPCE) shows a shift for the excitonic absorption peaks in the visible range at opposite applied voltages. The IPCE signal for the double heterostructure device is higher than the single type device.

G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the molecular mechanisms of ligand-GPCR complexes from Molecular Dynamics (MD) simulations. However, to explore ligand-specific differences in the response of a GPCR to diverse ligands, as is required to understand ligand bias and functional selectivity, necessitates creating very large amounts of data from the needed large-scale simulations. This becomes a Big Data problem for the high dimensionality analysis of the accumulated trajectories. Here we describe a new machine learning (ML) approach to the problem that is based on transforming the analysis of GPCR function-related, ligand-specific differences encoded in the MD simulation trajectories into a representation recognizable by state-of-the-art deep learning object recognition technology. We illustrate this method by applying it to recognize the pharmacological classification of ligands bound to the 5-HT2A and D2 subtypes of class A GPCRs from the serotonin and dopamine families. The ML-based approach is shown to perform the classification task with high accuracy, and we identify the molecular determinants of the classifications in the context of GPCR structure and function. This study builds a framework for the efficient computational analysis of MD Big Data collected for the purpose of understanding ligand-specific GPCR activity.

The World Health Organization (WHO) documents malaria as one of the leading causes of high morbidity and mortality worldwide. The disease affects millions and kills thousands of people annually. Efforts to reduce the global burden of malaria have prompted WHO to recommend prevention strategies like using anti-malarial drugs. However, these strategies have been ineffective because of anti-malarial drug resistance. The only efficacious malaria treatment is Artemisinin-based Combination Therapy (ACT). However, the extended ACTs clearance times, linked to the emergence of artemisinin monotherapy resistance recorded most recently in Africa and the Great Mekong region, pose a danger to its efficacy. Therefore, better efficacious malaria drugs are required. Since P. falciparum heat shock protein 90 (PfHsp90) is a well-characterized malaria drugs target, this study uses it to discover more efficacious malaria drugs. An in-silico approach was used to discover PfHsp90 inhibitors with pharmacological properties against Plasmodium malaria using molecular dynamics simulation (MDS) and hierarchical virtual screening. Geldanamycin (GDM), a well-known anti-PfHsp90 compound, was used to identify PfHsp90 inhibitors with pharmacological properties against Plasmodium malaria by screening it against the ZINC database via the ZINCPHARMER web server. This virtual screening process resulted in 17 hits. These ZINCPHARMER hits were subjected to drug-likeness and pharmacokinetics properties analysis in the SwissADME web server, and 9 of them satisfied the requirements. The 9 ZINC compounds were docked with PfHsp90 using the PyRx software to understand their interactions. From the molecular docking results, ZINC09060002 (-8.2 kcal/mol), ZINC72133064 (-7.8 kcal/mol), ZINC72163401 (-7.7 kcal/mol), ZINC72358537 (-8.1 kcal/mol), and ZINC72358557 (-7.6 kcal/mol) had better binding affinities to PfHsp90 than GDM (-7.5 kcal/mol). The stability of these molecularly docked protein-inhibitor complexes was assessed through MDS using GROMACS 2022. ZINC72163401, ZINC72358537, and ZINC72358557 formed stable complexes with PfHsp90. The lead compounds were subjected to in vitro validation for their inhibitory capability. They showed promising inhibition of parasite growth with IC50 values ranging between 200 – 400 ng/ml. In this regard, the three PfHsp90 inhibitors can be used as anti-malarial drugs. However, further structural optimization studies and clinical (in vivo) tests are necessary to ascertain the antimalarial activity of these compounds in humans.

Ligand-based virtual screening (LBVS) is a promising approach for rapid and low-cost screening of potentially bioactive molecules in the early stage of drug discovery. Compared with traditional similarity-based machine learning methods, deep learning frameworks for LBVS can more effectively extract high-order molecule structure representations from molecular fingerprints or structures. However, the 3D conformation of a molecule largely influences its bioactivity and physical properties, and has rarely been considered in previous deep learning-based LBVS methods. Moreover, the relative bioactivity benchmark dataset is still lacking. To address these issues, we introduce a novel end-to-end deep learning architecture trained from molecular conformers for LBVS. We first extracted molecule conformers from multiple public molecular bioactivity data and consolidated them into a large-scale bioactivity benchmark dataset, which totally includes millions of endpoints and molecules corresponding to 954 targets. Then, we devised a deep learning-based LBVS called EquiVS to learn molecule representations from conformers for bioactivity prediction. Specifically, graph convolutional network (GCN) and equivariant graph neural network (EGNN) are sequentially stacked to learn high-order molecule-level and conformer-level representations, followed by attention-based deep multiple-instance learning (MIL) to aggregate these representations and then predict the potential bioactivity for the query molecule on a given target. We conducted various experiments to validate the data quality of our benchmark dataset, and confirmed EquiVS achieved better performance compared with 10 traditional machine learning or deep learning-based LBVS methods. Further ablation studies demonstrate the significant contribution of molecular conformation for bioactivity prediction, as well as the reasonability and non-redundancy of deep learning architecture in EquiVS. Finally, a model interpretation case study on CDK2 shows the potential of EquiVS in optimal conformer discovery. The overall study shows that our proposed benchmark dataset and EquiVS method have promising prospects in virtual screening applications.

Activation of the EGFR pathway plays an important role in the progression of cancer and is associated with a poor prognosis in patients. The monoclonal antibody cetuximab, which displays EGFR extracellular domain-specific binding, has proven effective in the treatment of locally advanced disease and relapsed/metastatic disease. However, the effects of cetuximab are weaker than those of EGFR tyrosine kinase inhibitors (TKIs). This study investigates differences in the effects on cell growth of cetuximab and EGFR TKI AG1478 at the molecular level using oral squamous cell carcinoma (OSCC) cell lines. First, we found that there were EGFR-inhibitor sensitive (EIS) and EGFR-inhibitor resistant cell lines. The EIS cell lines expressed not only EGFR but also ErbB3, and both were clearly phosphorylated. The levels of phosphorylated ErbB3 were unaffected by cetuximab but were reduced by AG1478. EGFR ligand treatment increased the levels of phosphorylated EGFR but not phosphorylated ErbB3. Moreover, when EIS cell lines that were only capable of anchorage-dependent growth were grown in suspension, cell growth was suppressed and the levels of phosphorylated FAK, Src, and ErbB3 were significantly reduced. The levels of phosphorylated ErbB3 were unaffected by the FAK inhibitor PF573228, but were reduced by Src inhibition. Finally, combining cetuximab and a Src inhibitor produced an additive effect on the inhibition of EIS cell line growth.

The current report contributes to the understanding of the stereoselectivity of the chiral dirhodium(II) carboxylate catalysts derived from N-protected amino acid ligands. Investigating the possible effect of ligand stereo-purity on catalyst structure and enantioselectivity was carried out. This was justified through a new X-ray crystal structure for Rh2(S,S,S,R-PTTL)4 diastereomer.

[Co(AMPY)(DAPY)Cl2(H2O)].H2O (1) [Cu(AMPY)(DAPY)Cl2(H2O)].H2O (2) [Zn(AMPY)(DAPY)Cl2(H2O)] (3) were prepared from the ligands; AMPY = 2-amino-4-methylpyrimidine (L1), DAPY = 2,3-diaminopyridine (L2) and CoCl2.6H2O, CuCl2.2H2O and ZnCl2 in water/ethanol solutions and the three products characterized by elemental analysis, ultraviolet-visible spectroscopy (UV–Vis), Fourier-transform infrared spectroscopy (FT-IR), magnetic susceptibility, molar conductivity methods, and TGA analysis. The X-ray powder diffraction of the Co(II), Cu(II), and Zn(II) compounds showed that the geometry of monoclinic and SEM analysis revealed their morphology with a smooth surface. Molecular modeling was performed for all compounds using the density functional method DFT/B3LYP to study the structures and the frontier molecular orbitals (HOMO and LUMO). We have used Gaussian09 software for the calculations. In this study, different complexes were tested against Gram negative and Gram positive bacterial species to give insight into their broad-spectrum effects. The used pathogenic strains were two Gram positive species "Staphylococcus aureus and Micrococcus luteus" and two Gram negative species "Salmonella thyphimurium and Escherichia coli. The antifungal activity was evaluated against a pathogenic reference strain of the yeast Candida albicans. The antimicrobial and antioxidant assay results demonstrate that the tested compounds are effective against Gram positive and negative bacteria. Additionally, the compounds have an antifungal effect against Candida albicans with a maximum inhibitory zone of 2.5cm. The results demonstrated high antioxidant potential for the Zn(II) complex with a DPPH scavenging of 91.5%, however, the Cu(II) complex was low (16.5%). The data of docking with tyrosyl-tRNA synthetase presented that all compounds fit very well in the catalytic pockets of the proteins of the receptor.

Background: Targeting Hepatitis B virus (HBV) infection in human is crucial due to its adverse. Herbal medicine has long been significant in this regard, with flavonoids demonstrating promising results. Hence, establishing a way of identifying flavonoids with anti-HBV activities is the aim of the present study. Methods: Flavonoid structures with anti-HBV activities were retrieved. A flavonol-based pharmacophore model was established using LigandScout v4.4. Screening was performed using the PharmIt server. A QSAR equation was developed and validated with independent sets of compounds. Applicability domain (AD) was defined using Euclidean distance calculations for model validation. Results: The best model, consisting of 57 features was generated. HTS using the flavonol-based model resulted in 509 unique hits. The model's sensitivity and specificity were 71% and 100%, respectively. The QSAR model with two predictors, x4a and qed, exhibited strong predictive performance with an adjusted-R² value of 0.85 and 0.90 of Q2. Conclusion: The QSAR model has been validated with two separate chemical sets, guaranteeing the model's reproducibility and usefulness for other flavonols by utilizing the predictive characteristics of X4A and qed. These results provide new possibilities for discovering future anti-HBV drugs by integrating modeling and experimental research.

A Pt(II) complex featuring chelating tridentate bis-aryloxide tetrahydropyrimidinium based N-heterocyclic carbene (NHC) was synthesized and characterized by using different techniques. The electrochemical properties of the complex were investigated by cyclic voltammetry as well as differential pulse voltammetry, which revealed two reversible one-electron oxidation processes. The chemical generation and isolation of one-electron-oxidized species were performed oxidizing the initial complex by means of AgBF4. The combined UV-Vis/NIR- and EPR-spectroscopy studies supported by density functional theory (DFT) calculations suggest the formation of Pt(II)-phenoxyl radical complex. The latter open-shell derivative was structurally characterized by means of X-ray diffraction analysis. Finally, the neutral platinum complex was tested as a mediator in the process of electrocatalytic oxidation of 2-(methylamino)ethanol (MEA).

Two solvated rhenium(IV) complexes with formula [ReCl4(bpym)]·MeCN (1) and [ReCl4(bpym)]·CH3COOH·H2O (2) [bpym = 2,2'-bipyrimidine] have been prepared and characterized by means of Fourier transform infrared spectroscopy (FT–IR), scanning electron microscopy and energy dispersive X-ray analysis (SEM–EDX), single-crystal X-ray diffraction (XRD) and SQUID magnetometer. 1 and 2 crystallize in the monoclinic system with space groups P21/n and P21/c, respectively. In both compounds, the Re(IV) ion is six-coordinate and bound to four chloride ions and two nitrogen atoms of a 2,2’-bipyrimidine molecule forming a distorted octahedral geometry around the metal ion. In the crystal packing of 1 and 2, intermolecular halogen⋯halogen and π⋯halogen type interactions are present. Hydrogen bonds take place only in the crystal structure of 2. Both compounds exhibit an akin crystal framework based on halogen bonds. Variable-temperature dc magnetic susceptibility measurements performed on microcrystalline samples of 1 and 2 show a similar magnetic behavior for both compounds, with antiferromagnetic exchange between the Re(IV) ions connected mainly through intermolecular Re-Cl···Cl-Re interactions.

A dioxomolybdenum catalyst [(MoO2Cl2-O-MoO2Cl2)(L)] (1) (with L (1S,2S)-N,N´-bis(2-pyridinecarboxamide)-1,2-cyclohexane) was prepared and used as catalyst for the desulfurization of a multicomponent model fuel containing the most refractory sulfur compounds in real fuels. This complex showed to have a high efficiency to oxidize the aromatic benzothiophene derivative compounds present in fuels, mainly using a biphasic 1:1 model fuel/MeOH system. This process conciliates catalytic oxidative and extractive desulfurization, occurring the oxidation of the sulfur compounds in the polar organic solvent. The oxidative catalytic performance of (1) showed to be influenced by the presence of water in the system. Using 50% aq. H2O2 it was possible to reuse the catalyst and the extraction solvent MeOH during ten consecutive cycles without loss of desulfurization efficiency.

Excitotoxicity related to the dysfunction of the N-methyl-d-aspartate receptor (NMDAR) has been indicated to play an integral role in the pathophysiology of multiple disease states, including neurodegenerative disorders such as Parkinson’s disease. There is a notable gap in the market for novel NMDAR antagonists, however current methods to analyze potential antagonists rely on indirect measurements of calcium flux and hazardous radioligand binding assays. Recently, a fluorescent NMDAR ligand, N-adamantan-1-yl-dimethylamino-1-naphthalenesulfonic acid, known as AM-DAN was developed by our group. Additional studies on this ligand is necessary to evaluate its potential as a biological tool in NMDAR research. Therefore, this study was aimed at conducting structural analyses, fluorescence experiments, high-accuracy NMDAR molecular modelling and NMDAR phencyclidine (PCP) site competition binding studies using AM-DAN. Results revealed that AM-DAN has appropriate structural properties, significant fluorescent ability in various solvents and is able to bind selectively and compete for the PCP-binding site of the NMDAR. Therefore, AM-DAN holds promise as a novel fluorescent ligand to measure the affinity of prospective drugs binding at the NMDAR PCP-site and may circumvent the use of radioligands.

Taste signaling is a complex process that is linked to obesity and its associated metabolic syndromes. The sweet taste is mediated through a heterodimeric G protein coupled receptor (GPRC) in a species-specific manner and at multi-tissue specific levels. The sweet receptor recognizes a large number of ligands with structural and functional diversities to modulate different amplitudes of downstream signaling pathway(s). The human sweet-taste receptor has been extremely difficult to study by biophysical methods due to inadequate methods for producing large homogeneous quantities of the taste-receptor protein and a lack of reliable in vitro assays to precisely measure productive ligand binding modes leading to activity upon their interactions with the receptor protein. We report a multimodal high throughput assays to monitor ligand binding, receptor stability and conformational changes to model the molecular interactions between ligand-receptor. We applied saturation transfer difference nuclear magnetic resonance spectroscopy (STD-NMR) complemented by differential scanning calorimetry (DSC), circular dichroism (CD) spectroscopy, and intrinsic fluorescence spectroscopy (IF) to characterize binding interactions. Our method using complementary NMR and biophysical analysis is advantageous to study the mechanism of ligand binding and signaling processes in other GPCRs.

Four models of Ce(III) complexes with four ligands based on a 1,2,3-triazole derivatives were studied at four DFT levels. The effect of different ligands on the atomic charge value on the cerium ion was analyzed. Several relationships were clearly established between this atomic charge and that of the surrounding atoms, as well as with several geometric parameters of the ligand and with the molecular properties of the Ce(III) complex. The experimental IR and Raman spectra of the newly obtained Ce(III) complex with the (pyrrolidin-1-yl)-2H-1,2,3-triazole-4-carboxylate ligand were interpreted based on their comparison to the theoretical scaled ones using the scaling equations determined by two procedures and four DFT levels. Therefore, the structure predicted for the synthesized Ce(III) complex was clearly characterized and confirmed. The potential antioxidant action of Ce(III) complex was elucidated and compared with other Ln(III) complexes in order to find out the differences in their biological activity profiles.

Infectious as well as most non-infectious diseases share certain common molecular mechanisms. Among them, oxidative stress and the subsequent inflammatory reaction are of particular note. Metabolic disorders induced by external agents, be they bacterial or viral pathogens, excessive calorie intake, poor-quality nutrients, or environmental factors, produce an imbalance between the production of free radicals and endogenous antioxidant systems; the consequence being the oxidation of lipids, proteins and nucleic acids. Oxidation and inflammation are closely related, and whether oxidative stress and inflammation represent the causes or consequences of cellular pathology, they produce metabolic alterations that influence the pathogenesis of the disease. In this review we highlight two key molecules in the regulation of these processes: Paraoxonase-1 (PON1) and chemokine (C-C motif) ligand 2 (CCL2). PON1 is an enzyme bound to high-density lipoproteins. It breaks down lipid peroxides in lipoproteins and cells, participates in the protection conferred by HDL against different infectious agents, and is considered part of the innate immune system. With PON1 deficiency, CCL2 production increases, which induces migration and infiltration of immune cells in target tissues, and is involved in disturbing normal metabolic function. This disruption involves pathways controlling cellular homeostasis as well as metabolically-driven chronic inflammatory states. Hence, an understanding of these relationships would help improve treatments and, as well, identify new therapeutic targets.

Human NAD(P)H:quinone oxidoreductase 1 (NQO1) is a multi-functional protein whose alteration is associated with cancer, Parkinson´s and Alzheimer´s diseases. NQO1 displays a remarkable functional chemistry, capable of binding different functional ligands that modulate its activity, stability and interaction with proteins and nucleic acids. Our understanding on this functional chemistry is limited by the difficulty of obtaining structural and dynamic information on many of these states. Herein, we have used hydrogen/deuterium exchange monitored by mass-spectrometry (HDXMS) to investigate the structural dynamics of NQO1 in three ligation states: without ligands (NQO1apo), with FAD (NQO1holo) and with FAD and the inhibitor dicoumarol (NQO1dic). We show that NQO1apo has a minimally stable folded core holding the protein dimer and with FAD and dicoumarol ligand binding sites populating binding non-competent conformations. Binding of FAD significantly decreases protein dynamics and stabilizes the FAD and dicoumarol binding sites as well as the monomer:monomer interface. Dicoumarol binding further stabilizes all three functional sites, a result not previously anticipated by available crystallographic models. Our work provides an experimental perspective into the communication of stability effects through the NQO1 dimer, valuable to understand at the molecular level the effects of disease-associated variants, post-translation modifications and ligand binding cooperativity in NQO1.

Histone deacetylases (HDAC) represent promising epigenetic targets for several diseases including different cancer types. The HDAC inhibitors approved to date are pan-HDAC inhibitors and most show a poor selectivity profile, side effects and especially hydroxamic acid based inhibitors lack good pharmacokinetic profiles. Therefore, the development of isoform-selective non-hydroxamic acid HDAC inhibitors is a highly regarded field in medicinal chemistry. In this study, we analyzed different ligand-based and structure-based drug design techniques to predict the binding mode and inhibitory activity of recently developed alkylhydrazide HDAC inhibitors. Alkylhydrazides have recently attracted more attention as they have shown promising effects in various cancer cell lines. In this work, pharmacophore models and atom-based quantitative structure-activity relationship (QSAR) models were generated and evaluated. The binding mode of the studied compounds was determined using molecular docking as well as molecular dynamics simulations and compared with known crystal structures. Calculated free energies of binding were also considered to generate QSAR models. The models created show a good explanation of in vitro data and were used to develop novel HDAC3 inhibitors.

Therapeutic antibodies targeting immune checkpoints have shown limited efficacy in clinical trials in glioblastoma (GBM) patients. Ultrasound-mediated blood-brain barrier opening (UMBO) using low-intensity pulsed ultrasound improved drug delivery to the brain. We explored the safety and the efficacy of UMBO plus immune checkpoint inhibitors in preclinical models of GBM. A Blood-brain barrier (BBB) opening was performed using a 1 MHz preclinical ultrasound system in combination with 10µl/g microbubbles. Brain penetration of immune checkpoint inhibitors was determined, and immune cell populations were evaluated using flow cytometry. The impact of repeated treatments on survival was determined. In syngeneic GL261-bearing immunocompetent mice, we showed that UMBO safely and repeatedly open the BBB. BBB opening was confirmed visually and microscopically using Evans’s blue dye and magnetic resonance imaging. UMBO plus anti-PDL-1 was associated with a significant improvement of the overall survival compared to anti-PD-L1 alone. Using mass spectroscopy, we showed that the penetration of therapeutic antibodies can be increased when delivered intravenously compared to non-sonicated brains. Furthermore, we observed an enhancement of activated microglia percentage when combined with anti-PD-L1. Here, we report that the combination of UMBO and anti-PD-L1 dramatically increases GL261-bearing mice's survival compared to their counterparts treated with anti-PD-L1 alone. Our study highlights the BBB as a limitation to overcome to increase the efficacy of anti-PD-L1 in GBM and supports clinical trials combining UMBO and in GBM patients.

The increasingly common occurrence of antibiotic-resistant bacteria has become an urgent public health issue. There are currently some infections without any effective treatment, which require new therapeutic strategies. An attractive alternative is the design of compounds capable of disrupting bacterial communication known as quorum sensing (QS). In gram-negative bacteria, such communication is regulated by acyl-homoserine lactones (AHLs). QS allows bacteria to proliferate before expressing virulence factors. Our group previously reported that hexyloxy phenyl imidazoline (9) demonstrated 71% inhibitory activity of QS at 100 µM (IC50=90.9 µM) in Chomobacterium violaceum, a gram-negative bacterium. The aim of the present study was to take 9 as a lead compound to design and synthesize three 2-imidazolines (13-15) and three 2-oxazolines (16-18), to be evaluated as quorum sensing inhibitors on C. violaceum CV026. We were looking for compounds with a higher affinity towards the Cvi receptor of this bacterium and the ability to inhibit QS. The binding mode of the test compounds on the Cvi receptor was explored with docking studies and molecular dynamics. It was found that 8-pentyloxyphenyl-2-imidazoline 13 reduced the production of violacein (IC50=56.38 µM) without affecting bacterial growth, suggesting inhibition of quorum sensing. Indeed, compound 13 is apparently one of the best QS inhibitors known to date. Molecular docking revealed the affinity of compound 13 for the orthosteric site of the N-hexanoyl homoserine lactone (C₆-AHL) on the CviR protein. Ten aminoacid residues in the active site of C₆-AHL interacted with 13, and 7 of these are the same as those interacting with AHL. Contrarily, 8-octyloxyphenyl-2-imidazoline 14, 8-decyloxyphenyl-2-imidazoline 15 and 9-decyloxyphenyl-2-oxazoline 18 bound only to an allosteric site and thus did not compete with C₆-AHL for the orthosteric site.

Several therapeutic monoclonal antibodies are approved by FDA against the PD-1/PD-L1 (programmed death-1/programmed death ligand-1) immune checkpoint, which has been a great success in cancer treatment. However, existing therapeutics, including small molecules inhibitors against PD-L1 checkpoint have certain drawbacks such as high cost and drug resistance that challenge the current available anti-PD-L1 therapy. Thereof, this study presents the screening of 32552 compounds from Natural Product Atlas database against PD-L1, including three steps of structure-based virtual screening and binding free energy refinement for the selection of potent PD-L1 inhibitors. Subsequently, five natural compounds, i.e., Neoenactin B1, Actinofuranone I, Cosmosporin, Ganocapenoid A, and 3-[3-hydroxy-4-(3-methylbut-2-enyl)phenyl]-5-(4-hydroxybenzyl)-4-methyldihydrofuran-2(3H)-one, were collected based on the ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiling and binding free energy (>-70 kcal/mol) for further computational investigation by comparison to co-crystallised ligand, i.e. JQT inhibitor. Based on interaction mapping, explicit 100 ns molecular dynamics simulation, and post binding free energy calculations, all the compounds exhibited intermolecular interactions (hydrogen and hydrophobic) with essential residues and substantial complex stability by comparison to the JQT inhibitor. Collectively, the calculated results advocate the selected natural compounds as the putative potent inhibitors of PD-L1 and, therefore, can be considered for further development of PD-L1 immune checkpoint inhibitor in cancer immunotherapy.

A new copper(I) complex, [Cu2(L)2dppm](PF6)2 (1) [L = 3-(2-Pyridyl)-5,6-diphenyl-1,2,4-triazine and dppm: Bis(diphenylphosphino)methane] was prepared and characterized by IR, 1H-NMR, 31P-NMR spectroscopy, elemental and thermogravimetric analysis, and single-crystal X-ray diffraction technique. Complex 1 is a dinuclear compound, showing that L and dppm act as tridentate and bidentate chelating ligands, respectively. The two Cu(I) atoms exhibit a distorted tetrahedral coordination sphere embedded in N3P environments. The supramolecular interactions in the solid-state structure are characterized by C−H···N, C−H···F, C-H···π and π···π intermolecular interactions that were analyzed by inspection of the Hirshfeld surface and fingerprint plots. Additionally, the complex was studied experimentally in solution by UV–Vis spectroscopy and cyclic voltammetry; also, theoretical studies with Time-Dependent Density Functional Theory (TD-DFT) were performed. Moreover, the optical and electrochemical properties have been studied, focusing on the band gap. Compound 1 has been used as a co-sensitizer in a dye-sensitized solar cell, showing good activity.

A new Pd(II) complex of the previously reported ligand N,N′-bis[(2,2′-dihydroxybiphen-3-yl)methyl]-N,N′-dimethylethylenediamine (L) was obtained from a DMF/H2O mixture. It differs from a Pd(II) complex of L previously obtained by sole DMF. The roles in the solid state assembly of solvent molecules and molecular conformation (driven by specific transition metal ions) were studied by comparing six complexes of L containing different metal centers (Ni(II), Cd(II), Cu(II), Pd(II)). Hirshfeld surface analysis, 2D fingerprint plots and energy frameworks calculations were used to investigate the intermolecular interactions within the crystal packing of the six complexes. As suggested by interaction energies, Pd(II) and Ni(II) complexes arrange to form ribbons, while Cd(II) and Cu(II) complexes form 3D networks. Interactions between complexes and solvent molecules in the previous Pd(II) complex are replaced by complex-complex interactions in the new Pd(II) complex, while BuOH and MeOH are interchangeable in the interactions within the crystal packing of the two Ni(II) complexes. Finally, solvent molecules are not involved in the crystal packing of the Cu(II) complex. The present study suggested that the solid state assembly of these systems is mainly driven by the molecular conformation, that depends in turn by the metal ion involved, while the solvent only plays a minor role.

The FAS ligand (FASLG) is expressed on lymphocytes, which employ it to activated death receptors on targets cells. Cancer cells are generally resistant to apoptosis triggered by FASLG. In this work we found a way to circumvent this resistance by treatment with actinomycin D (ActD) and nutlin-3a (Nut3a). We selected this drug combination based on our transcriptomic data showing strong activation of proapoptotic genes, including the ones for receptor mediated apoptosis, in cells exposed to actinomycin D and nutlin-3a. To test our hypothesis, we pre-exposed cancer cell lines to this drug combination for 45h and next we treated them with recombinant FASLG. This almost instantaneously killed most cells. Actinomycin D and nutlin-3a strongly synergized in the sensitization because the effect of the drugs acting solo was not as spectacular as the drug combination, which together with FASLG killed more than 99% of cells. Based on the caspase activation pattern (caspase-8, caspase-9, caspase-10), we conclude that both extrinsic and intrinsic pro-apoptotic pathways were engaged. In engineered p53-deficient cells this pro-apoptotic effect was completely lost. Therefore, the combination of ActD+Nut3a activates p53 in an extraordinary way, which overcomes the resistance of cancer cells to apoptosis triggered by FASLG. Interestingly, other combinations of drugs, e.g., etoposide + nutlin-3a, actinomycin D + RG7112 and actinomycin D + idasanutlin had similar effect. Moreover, normal human fibroblasts are less sensitive to death induced by ActD+Nut3a+FASLG. Our findings create the opportunity to revive the abandoned attempts of cancer immunotherapy employing the recombinant FAS ligand.

Programmed death ligand 1 (PD-L1) is a co-inhibitory molecule expressed on the surface of various cell types, known for its suppressive effect on T cells through interaction with PD-1. Neutrophils also express PD-L1, and its expression is elevated in specific situations; however, the immunobiological role of PD-L1+ neutrophil has not been fully characterized. Here, we report that PD-L1-expressing neutrophils increased in methicillin-resistant Staphylococcus aureus (MRSA) infection are highly functional in bacterial elimination and supporting inflammatory resolution. The frequency of PD-L1+ neutrophils was dramatically increased in MRSA-infected mice, and this population exhibited enhanced activity in bacterial elimination compared to PD-L1- neutrophils. An administration of PD-L1 monoclonal antibody did not impair PD-L1+ neutrophil function suggesting that PD-L1 expression itself does not influence neutrophil activity. However, PD-1/PD-L1 blockade significantly delayed liver inflammation resolution in MRSA-infected mice, as indicated by increased plasma alanine transaminase (ALT) level and frequencies of inflammatory leukocytes in the liver implying that neutrophil PD-L1 suppresses the inflammatory response of these cells during the acute phase of MRSA infection. Our results reveal that elevated PD-L1 expression can be a marker for enhanced anti-bacterial function of neutrophils. Moreover, PD-L1+ neutrophils are an indispensable population attenuating inflammatory leukocyte activities assisting in a smooth transition into the resolution phase in MRSA infection.

Androgen insensitivity syndrome (AIS) is the most common disorder of sex development in people with karyotype 46,XY. Mutations in AR (androgen receptor) gene are found in most individuals with AIS. Exons 4-8, which encode LBD, were shown to be a mutation hotspot. The aim of this study was the search of mutations in the sequence of exons 6-8 which encode LBD of AR gene in patients with different clinical AIS phenotypes from Ukraine. The investigated patients were 4 women with 46,XY karyotype, SRY-positive and clinical features of AIS (2 – CAIS, 2 – PAIS). Serum levels of T, LH, and FSH were quantified by electrochemiluminescence immunoassay (ECLIA) technology. Cytogenetic studies were performed on peripheral blood lymphocytes with further use of standard protocols of chromosomal analysis (GTG-banding). The presence of SRY sequence was confirmed by FISH with LSI SRY probe. Direct Sanger sequencing of 6-8 exons was performed in patients and family members on the PCR products on the matrix of DNA samples isolated from peripheral blood lymphocytes. Detected SNPs were analysed using gnomAD, VEP, MutationTaster, Human Splicing Finder, NetPhorest 2.1, Group-based Prediction System 5.0, and PhosphoPICK bioinformatical resources. Modelling of mutant proteins based on available 3D models was conducted using the open source software UCSF Chimera 1.14rc. We have detected 3 previously described mutations (missense mutation X:67722905 Т>С (rs9332970) in PAIS patient, missense mutation X:67722943 C>T (rs886041132) in CAIS patient and, samesense mutation X:67723745 C>T (rs137852594) in PAIS patient). We determined these mutations as pathogenic using SIFT, PolyPhen, MutationTaster, Human Splicing Finder. Moreover the synonymous mutation X:67723745 C>T (rs137852594) detected in patient with PAIS was determined as mutation affecting processes of splicing. In our study we have identified novel mutation X:67722884 T>G in CAIS patient and family members. This mutation was predicted as a pathogenic using aforementioned bioinformatical tools. STRUM calculations of the protein stability change caused by single-point mutation showed a destabilization effect of the Ile836Ser substitution ΔΔG=-2.6. Possible aberrant phosphorylation analysis revealed the ability of MAPK family, Akt family, CDK1, CDK7, CDK9, PKC kinases to phosphorylate Ser836. Results concerning the pathogenicity of X:67722905 Т>С (rs9332970), X:67722943 C>T (rs886041132), X:67723745 C>T (rs137852594) mutations detected in patients with AIS from Ukraine obtained using bioinformatical resources SIFT, PolyPhen, MutationTaster, Human Splicing Finder correlate with previously published data concerning weaker binding of androgens in patients with the same mutations. This approves informativity of using such resources for mutation pathogenicity analysis. Analysis of the ortholog proteins, subdomain structure, and aberrant phosphorylation of AR-LBD suggests novel X:67722884 T>G mutation to be pathogenic. Based on analysis of mutant protein modelling followed by assessment of free energy change using STRUM it was predicted that mutant protein binds androgens 460 times worse than wild type.

Herein, we are proposing two chalcone molecules, (E)-1-(4-methoxyphenyl)-3-(p-tolyl) prop-2-en-1-one and (E)-3-(4-hydroxyphenyl)-1-(2,4,6-trihydroxyphenyl) prop-2-en-1-one, based on the anticancer bioactive molecule Xanthohumol, which are suitable for further in vitro and in vivo studies. Their ability to create stable complexes with the antiapoptotic X-linked IAP (XIAP) protein makes them promising anticancer agents. The calculations were based on ligand-based and structure-based virtual screening combined for the pharmacophore built. Additionally, the structures passed Lipinski's rule for drug use, and their reactivity was confirmed using density functional theory studies. The candidates were chosen between 10639400 compounds, and the docking protocols were evaluated using molecular dynamics simulations.

This research investigated the antihypertensive effects of tamarind products and compared their potentials based on their animal model’s data verified by molecular docking, multitarget interactions in network pharmacology, and dynamic simulation assays. The GC-MS characterized tamarind products were administered to the cholesterol-induced hypertensive Wistar albino rat models. Two-week-intervened animals were dissected to collect serum and organs which were respectively subjected to the analyses of hypertension-linked markers and tissue architectures. Lead biometabolites of tamarinds interacted with eight target receptors in molecular docking and dynamic simulation studies and they were tested for multitarget interactions using network pharmacological analyses. Results showed that serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), C-reactive protein (CRP), Troponin I, and lipid profiles were maximally reinstated by the phenolic-enriched ripened sour over the sweet tamarind flesh extracts, but seed extracts had a smaller influence. Among the tamarind’s biometabolites, Gamma-sitosterol (ϒ-sitosterol) was found to be the best ligand in managing hypertension via the possible ligand-receptor interactions with the guanylate cyclase which displayed the best drug-likeliness through the highest binding energy -9.3 Kcal. Multitargeted interactions-based degree algorithm and phylogenetic tree of pathways showed 14 targeted genes, of which NR3C1, REN, PPARG, and CYP11B1 hub genes, were consistently modulated by the ϒ-sitosterol to reduce hypertension and related risk factors. The dynamic simulation study showed that the P-RMSD values of ϒ-sitosterol-guanylate cyclase were stable between 75.00 to 100.00 ns at the binding pocket. The findings demonstrate that ripened sour tamarind extract may be supplemented to be a more prospective antihypertensive target or nutraceuticals affirming through advanced preclinical and clinical studies.

We performed Bayesian network meta-analysis (NMA) to suggest frontline treatments for patients with high PD-L1 expression (at least 50%). A total of 5,237 patients from 22 studies were included in this NMA. In terms of progression-free survival, immune checkpoint inhibitors (ICIs) plus bevacizumab plus chemotherapy had the highest surface under the cumulative ranking curve (SUCRA) value (98.1%), followed by ICI plus chemotherapy (82.9%). In terms of overall survival (OS), dual immunotherapy plus chemotherapy had the highest SUCRA value (79.1%), followed by ICI plus bevacizumab plus chemotherapy (73.4%). However, there was no significant difference of survival outcomes among treatment regimens combined with immunotherapy. Moreover, ICI plus chemotherapy failed to reveal a significant OS superiority to ICI monotherapy (hazard ratio = 0.978, 95% credible internal: 0.771-1.259). In conclusion, this NMA indicates that ICI plus chemotherapy with/without bevacizumab might to be the best options in terms of OS for NSCLC with high PD-L1 expression. Considering there was no significant difference of survival outcomes among treatment regimens incorporating immunotherapy and ICI plus chemotherapy failed to show significant survival benefits over ICI monotherapy, however, ICI monotherapy may be reasonable as first-line treatment for advanced NSCLC with high PD-L1 expression and no targetable aberrations.

Transition-metal-catalyzed amide bond formation from alcohols and amines is an atom-economic and eco-friendly route. Herein, we identified a highly active in situ N-heterocyclic carbene (NHC)/ruthenium (Ru) catalytic system for this amide synthesis. Various substrates, including sterically hindered ones, could be directly transformed into the corresponding amides with the catalyst loading as low as 0.25 mol%. In this system, we replaced the p-cymene ligand of the Ru source with a relatively labile cyclooctadiene (cod) ligand so as to more efficiently obtain the corresponding poly-carbene Ru species. Expectedly, the weaker cod ligand could be more easily substituted with multiple mono-NHC ligands. Further HR-MS analyses revealed that two tetra-carbene complexes were probably generated from the in situ catalytic system.

Indirubin-3′-monoxime (I3M) exhibits anti-proliferative activity in various cancer cells; however, its anti-cancer mechanism remains incompletely elucidated. This study revealed that I3M promotes the expression of death receptor 5 (DR5) and tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) in HCT116 p53+/+ cells, resulting in caspase-mediated apoptosis. However, this study demonstrated that HCT116 p53-/- cells are insensitive to I3M-mediated apoptosis, indicating that I3M-induced apoptosis depends on the p53 status of HCT116 cells. Additionally, in HCT116 p53-/- cells, I3M significantly increased Ras expression, while in HCT116 p53+/+ cells, it reduced Ras expression. Furthermore, I3M remarkably increased the production of reactive oxygen species (ROS), which were reduced in transient p53 knockdown, indicating that I3M-mediated apoptosis is promoted by p53-mediated ROS production. Our results also showed that I3M enhanced transcription factor C/EBP homologous protein (CHOP) expression, resulting in endoplasmic reticulum (ER) stress-mediated DR5 expression, which is upregulated by ROS production in HCT116 p53+/+ cells. Moreover, co-treatment with TRAIL synergistically enhanced I3M-induced DR5 expression, thereby triggering TRAIL-induced apoptosis of HCT116 p53+/+ cells, which was interfered by a DR5-specific blocking chimeric antibody. In summary, I3M potently enhances TRAIL-induced apoptosis by upregulating DR5 expression via p53-mediated ROS production in HCT116 p53+/+ cells. However, HCT116 p53-/- cells were resistant to I3M-mediated apoptosis, suggesting that I3M could be a promising anti-cancer candidate against TRAIL-resistant p53+/+ cancer cells.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p < 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

New Schiff base ofN'-((E)-3,3-diphenyl-2,3-dihydro-1H-inden-1-ylidene)-2-((Z)-2-oxoindolin-3-ylidene)hydrazine-1-carbothiohydrazide (HL) and its Co(II),Ni(II), Fe(III), Cu(II), Cd(II), Zn(II) and Mn(II) complexes were created, isolated, and characterized by analytical analysis in good yields of 60 to 90%, UV–Vis, magnetic measurements, molar conductivity, and FT-IR. Additionally, mass spectrometry was used to examine the new ligand complexes' structural characteristics.1H NMR spectroscopy and elemental analysis. Depending on the electronic spectra and magnetic susceptibility measurements, these complexes are predicted to have octahedral molecular geometry. As an example, the quantum chemical properties, bond lengths, and bond angles were discussed. The structural formula for the examined ligand was improved using the Gaussian09 tool. The DFT/B3LYP method was used to calculate the energy gaps and other crucial theoretical features. The prepared hydrazine ligand complexes Co (II), Ni (II), Fe (III), Cu (II), Cd (II), Zn (II) and Mn (II) complexes were evaluated for its antimicrobial properties. As antimicrobial agents, it was found that the organic ligand was less biologically active than the targeted complexes. Gram positive bacteria (3ty7-Staphylococcus), Gram negative bacteria (3t88-Escherichia coli), and fungi (5k04-Candida albicans) all have crystal structures that interact well with the chemicals in the title, according to molecular docking.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

To secure logic circuits against the illegal copying the insertion of the so-called key bit inputs using XOR/XNOR gates has been proposed in . The inserted gates modify (lock) the behavior of the original circuit and only the correct choice of the secret key bits guarantees the equivalent behaviour of the locked circuit to the original circuit. To break this kind of security, i.e. to find the secret key bits, there was a SAT solver based attack proposed in . The aim of this work is to experimentally verify this attack on several locked circuits with various number of primary inputs and outputs and with various number of gates. Except for the random placement of the key gates we evaluate also the positioning with chaining elimination. The obtained and presented results show that we were able to unlock 10 of 11 circuits within few minutes on a common PC.

Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed: the unknown node is in the positioning unit or not. When the unknown node is on the side of the positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is not on the side of the positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.

Early discharge after childbirth has led to a rise in neonatal readmission, becoming a major concern in recent decades. Our research aimed to identify the risk factors and incidence of neonatal readmission, as well as explore preventive measures. Our study at the Clinical Hospital of Pediatrics in Ploiești, Romania included 108 neonates admitted during the neonatal period. This accounted for 2.06% of all admissions (5226). The most prevalent cases were malnutrition (25%), fever (20.3%) and bronchiolitis (17.5%). Diarrhea and infectious gastroenteritis were also observed (14.8%), along with acute rhinoconjunctivitis (9.2%) and late onset sepsis (3.7%). No deaths were recorded. The most significant characteristics identified were number of children (p<0.001) and age at maternity discharge (p<0.001). By following the prevention rules, malnutrition, feeding errors, and infections can be avoided. This includes practicing proper hand hygiene for both mothers and medical staff, as well as educating and demonstrating to mothers the benefits of breastfeeding. In addition, all newborns discharged from the maternity ward should benefit from follow-up at 7-10 days of life. Our results confirm the effectiveness of a multidisciplinary team and endorse promoting breastfeeding. Implementing quality control measures and regularly evaluating the surveillance program will help improve its effectiveness.

Wearable technology has been proposed as a potential tool to change the way of human life, such as the smart bracelet and the Google Glass. In the wearable technology, the inertial sensor has great significance in tracking the object movements. The paper focused on detecting the movements of user’s finger based on the inertial sensor to give the control signals. Firstly, the attitude matrix, which represented the transformation relation of carrier coordinate system and the navigation coordinate system, was obtained. Secondly, the attitude matrix was expressed based on the quaternions. Thirdly, the finger gesture was processed by the attitude matrix to get the attitude angle. Finally, the robot was controlled by attitude angle to make the moving action. The experimental results showed the detection of the finger movement is effective.

Two interesting compounds such as quaternary ammonium lignin(QAL) and 2-ethylhexyl phosphoric acid mono-2-ethylhexyl ester (P507) were synthesized as ionic liquids(QP-ILs) for the extraction of metal ions. The extraction behavior of Co(II) and Ni(II) from chloride solution was compared between QP-ILs and P507. The results showed that the extraction rates of Co(II) and Ni(II) in the two solutions varied with the extraction conditions, but QP-ILs has stronger extractability for cobalt than P507, while Ni is on the contrary. Under the same conditions, the Co/Ni separation performance(βCo/Ni) in QP-ILs is superior to that in p507. At pH4.0, 55℃, concentration of 20%, extraction time of 10 minutes, the βCo/Ni of QP-ILs reached to 2703, while that of P507 was only 164. In conclusion, QP-ILs was more efficient than P507 for separating Co from mixed solutions.

Brain aging causes a wide variety of changes at molecular and cellular levels, leading to the decline of cognitive functions and increased vulnerability to neurodegenerative disorders. The research aimed at understanding the aging of the brain has made much progress in recent decades. Technological innovations such as single-cell RNA-sequencing (scRNA-seq), proteomic analyses, and spatial transcriptomic analyses have facilitated the research on the dynamic changes occurring within neurons, glia, and other cells along with their impacts on intercellular communication during aging. In this review, we introduce recent trends of how neurons and glia change during aging and discuss the impact of the brain microenvironment such as the blood-brain barrier (BBB).

In this paper, we study the semilinear pseudo-parabolic equations $\displaystyle u_{t} - \triangle_{\mathbb{B}}u - \triangle_{\mathbb{B}}u_{t} = \left|u\right|^{p-1}u$ on a manifold with conical singularity, where $\triangle _{\mathbb{B}}$ is Fuchsian type Laplace operator investigated with totally characteristic degeneracy on the boundary $x_{1} = 0$. Firstly, we discuss the invariant sets and the vacuum isolating behavior of solutions with the help of a family of potential wells. Then, we derive a threshold result of existence and nonexistence of global weak solution: for the low initial energy $J(u_{0})<d$, the solution is global in time with $I(u_{0}) >0$ or $\displaystyle\Vert \nabla_{\mathbb{B}}u_{0}\Vert_{L_{2}^{\frac{n}{2}}(\mathbb{B})} = 0$ and blows up in finite time with $I(u_{0}) < 0$; for the critical initial energy $J(u_{0}) = d$, the solution is global in time with $I(u_{0}) \geq0$ and blows up in finite time with $I(u_{0}) < 0$. The decay estimate of the energy functional for the global solution and the estimates of the lifespan of local solution are also given.

Multimodal remote sensing data classification can enhance the model’s ability to distinguish land features through multimodal data fusion. In this context, how to help models understand the relationship between multimodal data and target tasks is the focus of researchers. Inspired by human feedback learning mechanisms, causal reasoning mechanisms, and knowledge induction mechanisms, this paper integrates causal learning, reinforcement learning, and meta learning into a unified remote sensing data classification framework and proposed the causal meta-reinforcement learning (CMRL). First, based on feedback learning mechanisms, we have overcome the limitations of traditional implicit optimization of fusion features and customized a reinforcement learning environment for multimodal remote sensing data classification tasks. Through feedback interactive learning between agents and the environment, we help them understand the complex relationships between multimodal data and labels, thereby achieving full mining of multimodal complementary information. Second, based on the causal inference mechanism we designed causal distribution prediction action, classification reward, and causal intervention reward, capturing pure causal factors in multimodal data and cutting off false statistical associations between non-causal factors and class labels. Finally, based on the knowledge induction mechanism, we designed a bi-layer optimization mechanism based on meta-learning. By constructing a meta training task and meta validation task simulation model in the generalization scenario of unseen data, we helped the model induce cross-task shared knowledge, thereby improving its generalization ability for unseen multimodal data. The experimental results on multiple sets of multimodal datasets show that the proposed method achieved state-of-the-art performance in multimodal remote sensing data classification tasks.

Moso bamboo is famous for fast growing and biomass accumulation, as well as high annual output for timber and bamboo shoots. These high outputs require high nutrient inputs to maintain and improve stand productivity. Soil nitrogen (N), phosphorus (P) and potassium (K) are important micronutrients for plant growth and productivity. Due to high variability of soils, analysing spatial patterns of soil N, P and K stocks is necessary for scientific nutrient management in Moso bamboo forests. In this study, soils were sampled from 138 locations across Yong’an City and ordinary kriging was applied for spatial interpolation of soil N, P and K stocks. Soil N stock showed a strong spatial dependence while soil N and P stocks presented a moderate spatial dependence, indicating soil N was mainly controlled by intrinsic factors while soil N and P stocks were controlled by both intrinsic and extrinsic factors. Different spatial patterns were observed for soil N, P and K stocks across the whole study area, indicating that fertilizations with different ratios of N:P:K should be applied for different sites to maintain and improve stand productivity. The total soil N, P and K stocks within 0-60 cm were 0.624, 0.020 and 0.583 Tg, respectively.

With the increasing concern of environment, the energy-efficiency scheduling of manufacturing industry is becoming urgent and popular. In turning processes, both spindle speed and processing time can affect the final energy consumption and thus the spindle speed and scheduling scheme need to be optimized simultaneously. Since the turning workshop can be regarded as the flexible flow shop, this paper formulates a mixed integer linear programming model for energy-efficient scheduling of flexible flow shop. Accordingly, a new decoding method is developed by considering of the optimization of spindle speed and scheduling scheme simultaneously, and an estimation of distribution algorithm adopting the new decoding method is proposed to solve large-size problems. The parameters of this algorithm are determined by statistical technique with a simplified practical case. In order to validate the proposed method, a case from practical factories is studied, in which the makespan can be shortened by 25.22%, and the consumed energy can be saved by 5.48%. These results demonstrate the effectiveness of the proposed mathematical model and algorithm.

Lignocellulosic biomass, an abundant and renewable resource, serves as a crucial raw material for the production of biofuels, biochemicals, and various value-added products. This paper aims to develop and optimize a mild alkaline treatment of sawdust assisted by ultrasound, along with enzymatic hydrolysis of the pretreated material. The sonochemical pretreatment with alkali emerged as the optimal approach to enhance the susceptibility of cellulose to subsequent enzymatic hydrolysis, thereby increasing the yield of reducing sugars. A comparative study was performed using various ultrasonic applicators (horn and bath) and conventional assisted alkaline pretreatment. The ultrasonic assisted pretreatment revealed a higher delignification as 68% (horn) and 57% (bath) comparing with conventional pretreatment. Processes were optimized using a statistical analysis based on a 23 factorial design. The ratio between sawdust and alkanine solution (RSL = 0.5–1.5 g/100 mL), US amplitude (A = 20–60%), and working temperature (t = 30–50 °C) were selected as process factors. The optimal operating conditions to maximize the reducing sugar yield (138.15 mg GE /gsubstrate) were found as following: solid/liquid ratio RSL,opt = 1.25 g/100 mL, US amplitude Aopt = 60%, and and pretreatment temperature topt = 50 °C. The overall outcomes clearly confirmed the intensification of delignification by ultrasound assisted alkaline pretreatment

At 12:28 UTC (8:28 PM, local time) on 15 January 2023, a shallow, moderate earthquake with a magnitude (Mw) of 4.7 and a depth of one (1) kilometer shook the northern part of Leyte Island in the central part of the Philippines. The ground shaking was felt at PHIVOLCS Earthquake Intensity Scale (PEIS) VI, (very strong) equivalent to Modified Mercalli Intensity (MMI) VI in areas along the strike of the Leyte segment of the Philippine Fault. Even though this earthquake is classified as moderate in size, significant geologic, structural, and socio-economic impacts were documented. Most of the earthquake impacts that include surface rupture, liquefaction, and mass movements are limited near the epicentral area. The earthquake produced an 8-km-long surface rupture, the first documented rupture generated by a magnitude &lt;6 along the Philippine Fault, and is unusual in other surface rupturing earthquakes worldwide. It injured 18 persons and damaged 434 residential buildings and 26 public infrastructures which amounts to about 500 thousand US dollars. Structural damages were caused by surface rupture and/or poor engineering construction practices. Analysis of the seismic waveform and recorded peak ground acceleration (PGA) suggests that the subsurface geology influenced the ground motion amplification in an area near the epicenter. Based on the hypocenter, focal mechanism solution, aftershock distribution, and actual field observation, the causative fault for this event is the northern end of the Philippine Fault – Leyte segment. Moderate in size, this earthquake emphasizes the need and importance of documenting moderate-sized earthquakes as a tool and guide for medium and long-term earthquake risk assessment and resiliency.

Background: The bacterium Capnocytophaga spp. is a part of the oral microbiome of dogs, which has zoonotic potential. This study aimed to assess factors that influence the prevalence of Capnocytophaga cynodegmi and Capnocytophaga canimorsus in Wrocaw’s dog population. Methods: Molecular detection (PCR) involved 105 swabs, examining parameters such as oral cavity condition, underlying health issues, recent antibiotics, age, medications, material collection, and dog chews. Results: The study highlighted significant associations between the presence of Capnocytophaga cynodegmi and oral cavity condition, material collection method, and use of dog’s chews. Conclusions: Correlations obtained in this study between the oral health of Wroclaw's dog population and the presence of Capnocytophaga cynodegmi suggest its significance in the oral microbiome of dogs. Limitations, including the small sample size, highlight the need for more research to comprehensively understand additional factors that affect the prevalence of Capnocytophaga spp. in dogs

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

The assortment of low-cost 3D printers for “in-practice” use, e.g., for clear aligner therapies, is ever increasing. To address concerns about the accuracy of orthodontic models produced on such printers when cost efficient modes of 3D printing are employed, this study examined the effect of print model body type and print angulation on accuracy. Six printing-configuration groups were included: 2 model types (solid or hollow shell) combined with 3 print angles (0°, 70°, or 90°) with 10 models/group; all models were printed with 100-µm layer thickness using a digital light processing-based 3-dimensional printer. Eleven selected structures and distances were measured on the printed models with a digital microscope and compared to the same measures on a digitized master model. The clinically-acceptability range was set at ±0.25 mm difference from the master model for single tooth measurements (intra-tooth) and ±0.5 mm for cross-arch measurements (inter-tooth). For individual measurements across all models, 98% fell within clinical acceptability. For mean measurements within each model group, only canine height for the shell-0° model had a mean difference (0.26 mm ± 0.03) outside the clinically acceptable range for intra-tooth measurements. Standard deviations for all intra-tooth measurements were within 0.07 mm. While none of the mean inter-tooth measurements exceeded the acceptability range, the standard deviations were larger (0.04 to 0.30 mm). Accuracy of orthodontic models for clear aligner therapies was not impacted beyond the clinically acceptable range when altering model body type and print angulation to improve efficiency of 3D printing. These findings suggest greater flexibility of the practitioner to alter print settings to address time and cost efficiency in various clinical scenarios and still maintain clinically acceptable model accuracy.

Background: Alfalfa, the most economically important forage legume worldwide, features modest genetic progress due to long selection cycles and large extent of non-additive genetic variance associated with its autotetraploid genome. Methods: To improve the efficiency of genomic selection in alfalfa, we explored the effects of genome parametrization (as autotetraploid and diploid dosage, plus allele ratios) and SNP marker subsetting (all available SNPs; only genic regions; only non-genic regions) on genomic regressions, together with various levels of filtering on reading depth and missing rates. We used Genotyping by Sequencing-generated data and focused on traits of different genetic complexity, i.e., dry biomass yield in moisture-favorable (FE) and drought stress (SE) environments, leaf size, and onset of flowering, assessed on 143 genotyped plants from a genetically-broad European reference population and their phenotyped half-sib progenies. Results: On average, allele ratio improved the predictive ability compared with other genome parametrizations (+7.9% vs. tetraploid dosage, +12.6% vs. diploid dosage), SNP subsetting offered an advantage compared with any tested subsettings (+3.7% vs. genic regions, +7.6% vs. non-genic regions). However, when focusing on specific traits, different combinations of genome parametrization and subsetting reached better performances. We also released Legpipe2, a SNP calling pipeline tailored for reduced representation (GBS, RAD) medium-sized genotyping experiments.

Climate change is challenging the agricultural sector worldwide. The pressure exerted by the altered thermal conditions drives the zonal shift for various cultivations. This study presents the multiyear analysis of the Growing Degree Days (GDD) index over the Northern Mediterranean Basin (NMB), focused on the high-value vine cultivation derived from the E-OBS dataset. To handle this extensive environmental dataset, R-language scripts and packages were applied, along with the capabilities of the GIS software. The investigated time period spans from 1969 to 2018, and the performed analysis indicates a broad shift/expansion in areas of GDD exceeding 2000 heat units. The extracted results specify the viticultural areas where the GDD index surpasses the suitable values for vine cultivation, owing to the increase of the thermal stress risk. In addition to mapping areas with GDD ≥ 2000, spatial calculations of the surface of areas meeting this criterion per country in the study area were made. In the northern parts of the NMB, the rise of the GDD index values indicates the establishment of vine plantations in the future.

In this article, we describe a simple procedure for evaluating the sterility of nutrient media using a shear-horizontal surface acoustic wave (SH-SAW) biosensor. We used the SH-SAW biosensor platform to monitor the time-dependent phase responses of the material for the media that binds to a monolayer of 3-mercaptopropanyl-N-hydroxy succinimide on the biosensor surface. Increases in the phase shift less than 50% of the starting phase shift recorded 180 minutes after the sterilization indicate a successful sterility test of the media. Our devices were then applied to sterility testing using a viable Escherichia coli (E. coli) K-12 solution to confirm our hypothesis. Filtered LB Broth was the negative control, and a 24-hour culture of E. coli was the positive control. Before testing, the cell solution was pelleted, the media decanted and then replaced with a 1x phosphate-buffered saline solution (1x PBS). Since we know that the N-hydroxysuccinimide residues will bind to amine groups, only in cases where microbial species are present will the surface binding increase greater than 50%. We confirmed our hypothesis using SH-SAW biosensors and overnight E. coli cultures. The sensitivity for our 250 MHz quartz SH-SAW sensors was calculated based on the response from the E. coli K-12 solution over the linear dynamic range, which appears to be 2x104 – 2x107 CFU per ml and has a sensitivity of S = 1.655x105 o m2 Kg-1. The limit of detection (LOD) for these sensors was calculated to be approximately 2x10-9 grams (g) which is estimated to be approximately 2,000 Escherichia coli (E. coli) K-12 cells. However, the sensitivity and insertion loss remained approximately unchanged before and after coating the sensor with 3,3'-Dithiobis(succinimidyl) Propionate (DSP).

Regeneration of lost tail is of great importance to lizards. Anolis carolinensis, a green lizard, is capable of regenerating its tail efficiently after autotomy. Hence, it is considered as a model organism in regeneration study. A. carolinensis shed its tail in order to distract the predator’s attention and thus makes a way to escape. Restoring of the amputated tail takes several days and the mechanism is currently clearly understood. Although save its life, tail regeneration is associated with the impairment of several vital functions in Anoles. In addition, various differences have been observed between original and regenerated tail in terms of mechanism and structure. To date, very little work has been conducted on tail autotomy and regeneration at molecular and genetic level. The genes responsible for regeneration in anoles are identified recently. These genes are evolutionarily conserved through all tetrapod vertebrates. They are, however, in a state of ‘switched-off’ in other vertebrates including humans. Consequently, a throughout study of these so called ‘switched-off’ genes may provide a way of restoring lost organs in human, and thus could revolutionize the modern medical science.

The strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a Lean Learning Factory was developed in the Pitesti University Center, which allows students to learn, experiment, and research, in an environment similar to that of enterprises, the new Lean Manufacturing methods and techniques, and Industry 4.0. The research presented in this study had as its objective identifying the minimum number of repetitions necessary to train operators who serve two differently organized workstations, one classic, the other including digital techniques, but on which the same assembly operation is performed. Several indicators were considered in the analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percentage ratio between the standard duration of cyclical activities and the effective duration of the work cycle. The evolution of these indicators was mathematically modelled by regression functions, using the least squares method. The obtained results also highlight the usefulness of applying the DOJO method as a Lean manufacturing-specific learning technique and the efficiency of implementing digital techniques in work organization.

Classifying network flow subsequences in an Industrial IoT gateway is an effective method for identifying Industrial IoT faults. This paper proposes a subsequence classification algorithm SSGBUL-IKNN based on unsupervised learning encoding to address the problem of low classification accuracy. Firstly, we built a network module based on unsupervised learning to encode the flow sequence of the Industrial IoT gateway. In the encoding module, a subsequence calibration algorithm controls the increasing error during the coding process. Then, the specific fault type is obtained through an improved KNN classification algorithm based on the indication distance source from the integrated coding sequences converted by multi-dimensional network flow sequences. The test result on three Industrial IoT datasets of a sewage treatment plant shows that the accuracy of SSGBUL-IKNN in this paper exceeds 92%, significantly higher than the algorithm DTW and TSF. It reaches the classification requirements of Industrial IoT fault diagnosis.

In this paper, we study the global existence and exponential decay for a dynamic contact problem between a Timoshenko beam with second sound and two rigid obstacles, of which the heat flux is given by Cattaneo's law instead of the usual Fourier's law. The main difficulties arise from the irregular boundary terms, from the low regularity of the weak solution and from the weaker dissipative effects of heat conduction induced by Cattaneo's law. By considering related penalized problems, proving some a priori estimates and passing to the limit, we prove the global existence of the solutions. By considering the approximate framework, constructing some new functionals and applying the perturbed energy method, we obtain the exponential decay result for the approximate solution, and then prove the exponential decay rate to the original problem by utilizing the weak lower semicontinuity arguments.

Reducing the hardness of hard water is of great concern nowadays due to some adverse effects on water pipes, boilers and soap consumption. Using the method of biomineralization to precipitate calcium and magnesium ions to become carbonate minerals was one of the most important innovations for reducing the hardness of hard water. The present study sought to explore the physical and chemical conditions of carbonates bio-precipitation and the potential use of Bacillus licheniformis SRB2 strain (GenBank: KM884945.1) isolated from sludge sample of Moshui River (Shandong University of Science and Technology, Qingdao, China) in reducing the hardness of hard waters by the induction of carbonate minerals. In this study, B. licheniformis SRB2 strain was identified based on the morphological, biochemical and 16S rDNA gene sequence homology analysis. The carbonate minerals induced by B. licheniformis bacteria in the liquid culture medium with 3% NaCl and Mg/Ca molar ratio of 0, 6, 8, 10 and 12 were investigated. The culture medium was inoculated with the bacterial liquid seed was set as the experimental group and the other culture medium was inoculated with the same volume of distilled water was set as the control group. The mineral phases, micromorphologies, and crystal structures were analyzed using X-ray powder diffraction, scanning electron microscope, energy dispersive X-ray detector, high resolution transmission electron microscopy and selected area electron diffraction. The bacterial concentrations and pH values of the solution were measured by a spectrophotometer and a pH meter, respectively. The urease secreted by B. licheniformis SRB2 was found to greatly increase the pH values of the liquid medium, which favored the formation of calcium carbonate.As a result, Mg²⁺ and Ca²⁺ ion concentrations decreased greatly due to the biomineralization of calcium carbonate and nesquehonite minerals in the presence of B. licheniformis SRB2 bacterium. There were only few calcium carbonates and no nesquehonite minerals in the control groups. It was also found that the minerals of nesquehonite induced by B. licheniformis SRB2 had a phenomenon of preferred orientation. What was more, even though Mg²⁺ ions inhibited the precipitation of Ca²⁺ ions, but under the action of B. licheniformis SRB2 bacteria, the inhibition effect was significantly declined. The bio-precipitation of calcium carbonate and nesquehonite minerals may represent a new method of pretreatment for the hardness reduction of hard water. The accomplished study is of certain interest for interpretation of the carbonates biomineralization in natural environment, and maybe also has a certain application value in the former processing of hard water

In this paper, a novel permanent magnet-assisted synchronous reluctance machine (PMASynRM) with rare-earth PMs and ferrite magnets is proposed. The performance of PMASynRM is discussed with respected to the different magnet ratio of rare-earth PMs and ferrite magnets. Some characteristics including the flux density, output torque, cogging torque, output power, power factor, torque ripple, loss, efficiency, and demagnetization are calculated by 2-D finite element analysis (FEA). The analysis results show that the excellent performance can be obtained by using hybrid magnet of rare-earth PMs and ferrite magnets with the suitable magnet ratio, and provide some desirable cost-performance trade-off.

Saikosaponin (SS) a is a compound with various pharmacological properties and easily degraded into SSb1 and SSg in acid condition. In present work another two new degradation products of SSa formed under acid hydrolytic condition were detected and isolated by analytical and semi-preparative liquid chromatography technology, furthermore their structures were characterized as hydroxyl-saikosaponin a and SSb2 by spectral analysis, which is not only essential in stability-indicating method development and validation but also could be used as a worst case to assess the analytical method performance of SSa. Moreover their structural transformation pathways were also proposed.

In recent years, cerium dioxide (CeO2) has attracted considerable attention owing to its remarkable performance in various applications, including photocatalysis, fuel cells, and catalysis. This study explores the effect of nickel (Ni) doping on the structural, thermal, and chemical properties of CeO2 nanorods, particularly focusing on oxygen vacancy-related phenomena. Utilizing X-ray powder diffraction (XRD), alterations in crystal structure and peak shifts were observed, indicating successful Ni doping and the formation of Ni2O3 at higher doping levels, likely due to non-equilibrium reactions. Thermal gravimetric analysis (TGA) revealed changes in oxygen release mechanisms, with increasing Ni doping resulting in the release of lattice oxygen at lower temperatures. Raman spectroscopy corroborated these findings by identifying characteristic peaks associated with oxygen vacancies, facilitating the assessment of Ni doping levels. Overall, this study underscores the substantial impact of Ni doping on CeO2 nanorods, shedding light on tailored catalytic applications through modulation of oxygen vacancies while preserving the nanorod morphology.

(1) Background: Thrombophilia is a tendency towards hypercoagulability, and it is increased by pregnancy, peaking around delivery. Research question: does thrombophilia stimulate the in-flammatory state of the patient, already suppressed by pregnancy? (2) Methods: Eighty thrombo-philia patients admitted for delivery between 1/10/2017 and 1/12/2021 were prospectively stud-ied, together with eighty age- and para-matched control patients. Patients were admitted for de-livery at term by means of cesarean section. The inflammation indexes from the complete blood count values analysis during both the 24 hours before and after labor—extracted from the hospi-tal’s medical records—were calculated and then correlated with uterine involution. (3) Results: Except for the PLR, most of the numerous inflammation indexes studied were not significantly different in treated thrombophilia patients, before and after delivery, compared to non-thrombophilia patients. Only when we split the patients, based on the uterine haematometra in the first 24-48 hours postpartum, we found out that the few treated thrombophilia patients with haematometra (14 with haematometra out of 79 with treated thrombophilia) had elevated SII and AISI antepartum. In pregnant patients treated for thrombophilia, MLR is higher in pa-tients without the Rh factor than in those with the Rh factor. In non-thrombophilia patients, MCVL and NLPR increased with age and before labor, while SII and AISI increased with age postpartum. (4) Conclusions: Thrombophilia did not stimulate the inflammatory state of the pa-tient, already suppressed by pregnancy.

The necessity for precise and current data concerning the dynamics of land cover change in Indonesia is crucial for efforts to reduce natural vegetation cover due to agricultural expansion. The functionality of monitoring systems that incorporate Terra-MODIS is currently compromised by the limited availability of data for the immediate future. This study seeks to assess the potential of VIIRS satellite imagery in developing an early warning system for monitoring vegetation cover change in Indonesia. The Normalized Differential Open Area Index (NDOAI) computed from the 8-day’ VIIRS data was employed to detect changes in vegetation cover based on pixel-by-pixel subtraction in the NDOAI data time series. Evaluating the pixel-level accuracy of change detection is complicated due to the fact that we evaluate a change map at a coarser resolution than the Landsat-based reference map. The results revealed that increasing the threshold percentage is associated with improved accuracy. In change detection, there is often a trade-off between accuracy and sensitivity. A threshold that is too low may result in false positives, while a threshold that is too high may lead to missed changes. This study demonstrates that when a threshold value of less than 20% is applied, Landsat can identify vegetation cover changes at an earlier stage. Conversely, when a threshold value greater than 20% is employed, VIIRS will detect the change 4.5 days earlier than Landsat. Additionally, VIIRS is capable of detecting changes 25.4 days and 54.8 days faster than Landsat, respectively, when using thresholds of 40% and 75%.

By using the particle swarm optimization algorithm for crystal structure prediction, we reveal a newly orthorhombic Cmcm structure of HfB4, which is more energetically superior to the previously proposed YB4-, ReP4-, FeB4-, CrB4-, and MnB4-type structures in the considered pressure range. The phonon dispersion and elastic constants calculations confirm that the new phase is dynamically and mechanically stable. The calculated large shear modulus (240 GPa) and high hardness (45.7 GPa) imply that the predicted Cmcm-HfB4 is a potential superhard material. Meanwhile, the directional dependences of the Young's modulus, bulk modulus, and shear modulus for HfB4 are systematically investigated. Further analyses of the density of states and electronic localization function indicate that the strong B-B and B-Hf covalent bonds greatly contribute to its high hardness and stability.