Holmbergpihl2484

Newly developed high-throughput methods for property predictions make the process of materials design faster and more efficient. Density is an important physical property for energetic compounds to assess detonation velocity and detonation pressure, but the time cost of recent density prediction models is still high owing to the time-consuming processes to calculate molecular descriptors. To improve the screening efficiency of potential energetic compounds, new methods for density prediction with more accuracy and less time cost are urgently needed, and a possible solution is to establish direct mappings between the molecular structure and density. We propose three machine learning (ML) models, support vector machine (SVM), random forest (RF), and Graph neural network (GNN), using molecular topology as the only known input. The widely applied quantitative structure-property relationship based on the density functional theory (DFT-QSPR) is adopted as the benchmark to evaluate the accuracies of the models. All these four models are trained and tested by using the same data set enclosing over 2000 reported nitro compounds searched out from the Cambridge Structural Database. The proportions of compounds with prediction error less than 5% are evaluated by using the independent test set, and the values for the models of SVM, RF, DFT-QSPR, and GNN are 48, 63, 85, and 88%, respectively. The results show that, for the models of SVM and RF, fingerprint bit vectors alone are not facilitated to obtain good QSPRs. Mapping between the molecular structure and density can be well established by using GNN and molecular topology, and its accuracy is slightly better than that of the time-consuming DFT-QSPR method. The GNN-based model has higher accuracy and lower computational resource cost than the widely accepted DFT-QSPR model, so it is more suitable for high-throughput screening of energetic compounds.In this paper, we report a series of six neutral, blue-phosphorescent cyclometalated iridium complexes of the type Ir(C^Y)2(CNAr)(CN). The cyclometalating ligands in these compounds (C^Y) are either aryl-substituted 1,2,4-triazole or NHC ligands, known to produce complexes with blue phosphorescence. Curzerene These cyclometalating ligands are paired with π-acidic, strongly σ-donating cyano and aryl isocyanide (CNAr) ancillary ligands, the hypothesis being that these ancillary ligands would destabilize the higher-lying ligand-field (d-d) excited states, allowing efficient blue photoluminescence. The compounds are prepared by substituting the cyanide ancillary ligand onto a chloride precursor and are characterized by NMR, mass spectrometry, infrared spectroscopy, and, for five of the compounds, by X-ray crystallography. Cyclic voltammetry establishes that these compounds have large HOMO-LUMO gaps. The mixed cyano-isocyanide compounds are weakly luminescent in solution, but they phosphoresce with moderate to good efficiency when doped into poly(methyl methacrylate) films, with Commission Internationale de L'Eclairage coordinates that indicate deep blue emission for five of the six compounds. The photophysical studies show that the photoluminescence quantum yields are greatly enhanced in the cyano complexes relative to the chloride precursors, affirming the benefit of strong-field ancillary ligands in the design of blue-phosphorescent complexes. Density functional theory calculations confirm that this enhancement arises from a significant destabilization of the higher-energy ligand-field states in the cyanide complexes relative to the chloride precursors.Starting from lead compound 4, the 1,4-oxazine headgroup was optimized to improve potency and brain penetration. Focusing at the 6-position of the 5-amino-1,4-oxazine, the insertion of a Me and a CF3 group delivered an excellent pharmacological profile with a pKa of 7.1 and a very low P-gp efflux ratio enabling high central nervous system (CNS) penetration and exposure. Various synthetic routes to access BACE1 inhibitors bearing a 5-amino-6-methyl-6-(trifluoromethyl)-1,4-oxazine headgroup were investigated. Subsequent optimization of the P3 fragment provided the highly potent N-(3-((3R,6R)-5-amino-3,6-dimethyl-6-(trifluoromethyl)-3,6-dihydro-2H-1,4-oxazin-3-yl)-4-fluorophenyl)-5-cyano-3-methylpicolinamide 54 (NB-360), able to reduce significantly Aβ levels in mice, rats, and dogs in acute and chronic treatment regimens.PAr3 containing o-OMe, o-Me, or o-Et substituents reacts with Brønsted sites on sulfated zirconium oxide (SZO) to form [HPAr3][SZO]. The phosphonium sites on this material react with bis(cyclooctadiene)nickel [Ni(cod)2] to form [Ni(PAr3)(codH)][SZO] that are active in ethylene polymerization reactions. Selective poisoning studies with pyridine show that ∼90% of the Ni(PAr3)(codH)+ sites in this material are active in polymerization reactions.We report a dramatic effect on product outcomes of the lithium ion enabled amino-Cope-like anionic asymmetric cascade when different γ-dienolate heteroatom substituents are employed. For dienolates with azide, thiomethyl, and trifluoromethylthiol substituents, a Mannich/amino-Cope/cyclization cascade ensues to form chiral cyclohexenone products with two new stereocenters in an anti-relationship. For fluoride-substituted nucleophiles, a Mannich/amino-Cope cascade proceeds to afford chiral acyclic products with two new stereocenters in a syn-relationship. Bromide- and chloride-substituted nucleophiles appear to proceed via the same pathway as the fluoride albeit with the added twist of a 3-exo-trig cyclization to yield chiral cyclopropane products with three stereocenters. When this same class of nucleophiles is substituted with a γ-nitro group, the Mannich-initiated cascade is now diverted to a β-lactam product instead of the amino-Cope pathway. These anionic asymmetric cascades are solvent- and counterion-dependent, with a lithium counterion being essential in combination with etheral solvents such as MTBE and CPME. By altering the geometry of the imine double bond from E to Z, the configurations at the R1 and X stereocenters are flipped. Mechanistic, computational, substituent, and counterion studies suggest that these cascades proceed via a common Mannich-product intermediate, which then proceeds via either a chair (X = N3, SMe, or SCF3) or boat-like (X = F, Cl, or Br) transition state to afford amino-Cope-like products or β-lactam in the case of X = NO2.A novel series of antimalarial benzimidazole derivatives incorporating phenolic Mannich base side chains at the C2 position, which possess dual asexual blood and sexual stage activities, is presented. Structure-activity relationship studies revealed that the 1-benzylbenzimidazole analogues possessed submicromolar asexual blood and sexual stage activities in contrast to the 1H-benzimidazole analogues, which were only active against asexual blood stage (ABS) parasites. Further, the former demonstrated microtubule inhibitory activity in ABS parasites but more significantly in stage II/III gametocytes. In addition to being bona fide inhibitors of hemozoin formation, the 1H-benzimidazole analogues also showed inhibitory effects on microtubules. In vivo efficacy studies in Plasmodium berghei-infected mice revealed that the frontrunner compound 41 exhibited high efficacy (98% reduction in parasitemia) when dosed orally at 4 × 50 mg/kg. Generally, the compounds were noncytotoxic to mammalian cells.Hypercholesterolemia is often considered to be a major risk factor for atherosclerosis, and medium-chain fatty acids have been found to reduce the total cholesterol (TC) level and maintain low-density lipoprotein cholesterol (LDL-c) stability. However, we unexpectedly found that the levels of TC and LDL-c were increased in obese rats treated with high-dose lauric triglycerides (LT). The study aimed to investigate the effect and mechanism of LT on cholesterol metabolism in obese rats. Our results showed that LT intervention could reduce cholesterol biosynthesis by downregulating the expression of HMG-CoA reductase in obese rats. LT increased the expression levels of PPARγ1, LXRα, ABCA1, and ABCG8 in the liver. These results indicated that LT could improve the lipid transfer and bile acid efflux. However, LT significantly increased the expression of PCSK 9, resulting in accelerated degradation of LDLR, thus reducing the transport of very LDL (VLDL) and LDL to the liver. Together with the increased expression of NPC1L1 protein, LT impaired the uptake of VLDL/LDL by the liver and increased the reabsorption of sterols, leading to an increase in the levels of TC and LDL-c in obese rats.Massively multitask bioactivity models that transfer learning between thousands of assays have been shown to work dramatically better than separate models trained on each individual assay. In particular, the applicability domain for a given model can expand from compounds similar to those tested in that specific assay to those tested across the full complement of contributing assays. If many large companies would share their assay data and train models on the superset, predictions should be better than what each company can do alone. However, a company's compounds, targets, and activities are among their most guarded trade secrets. Strategies have been proposed to share just the individual collaborators' models, without exposing any of the training data. Profile-QSAR (pQSAR) is a two-level, multitask, stacked model. It uses profiles of level-1 predictions from single-task models for thousands of assays as compound descriptors for level-2 models. This work describes its simple and natural adaptation to safe cog only the outside profile, but a consensus of models using all three profiles is best on external compounds and a good compromise on internal compounds. We anticipate similar results from other model-sharing approaches. Indeed, since collaborative pQSAR through model sharing is mathematically identical to pQSAR using actual shared data, we believe our conclusions should apply to collaborative modeling by any current method even including the unlikely scenario of directly sharing all chemical structures and assay data.Exosomes are expected to be used as cancer biomarkers because they carry a variety of cancer-related proteins inherited from parental cells. However, it is still challenging to develop a sensitive, robust, and high-throughput technique for simultaneous detection of exosomal proteins. Herein, three aptamers specific to cancer-associated proteins (CD63, EpCAM, and HER2) are selected to connect gold nanoparticles (AuNPs) as core with three different elements (Y, Eu, and Tb) doped up-conversion nanoparticles (UCNPs) as satellites, thereby forming three nanosatellite assemblies. The presence of exosomes causes specific aptamers to recognize surface proteins and release the corresponding UCNPs, which can be simultaneously detected by inductively coupled plasma-mass spectrometry (ICP-MS). It is worth noting that rare earth elements are scarcely present in living systems, which minimize the background for ICP-MS detection and exclude potential interferences from the coexisting species. Using this method, we are able to simultaneously detect three exosomal proteins within 40 min, and the limit of detection for exosome is 4.7 × 103 particles/mL. The exosomes from seven different cell lines (L-02, HepG2, GES-1, MGC803, AGS, HeLa, and MCF-7) can be distinguished with 100% accuracy by linear discriminant analysis. In addition, this analytical strategy is successfully used to detect exosomes in clinical samples to distinguish stomach cancer patients from healthy individuals. These results suggest that this sensitive and high-throughput analytical strategy based on ICP-MS has the potential to play an important role in the detection of multiple exosomal proteins and the identification of early cancer.