Anti-Inflammatory Effects of Phytochemical Components of Clinacanthus nutans

Recent studies on the ethnomedicinal use of Clinacanthus nutans suggest promising anti-inflammatory, anti-tumorigenic, and antiviral properties for this plant. Extraction of the leaves with polar and nonpolar solvents has yielded many C-glycosyl flavones, including schaftoside, isoorientin, orientin, isovitexin, and vitexin. Aside from studies with different extracts, there is increasing interest to understand the properties of these components, especially regarding their ability to exert anti-inflammatory effects on cells and tissues. A major focus for this review is to obtain information on the effects of C. nutans extracts and its phytochemical components on inflammatory signaling pathways in the peripheral and central nervous system. Particular emphasis is placed on their role to target the Toll-like receptor 4 (TLR4)-NF-kB pathway and pro-inflammatory cytokines, the antioxidant defense pathway involving nuclear factor erythroid-2-related factor 2 (NRF2) and heme oxygenase 1 (HO-1); and the phospholipase A₂ (PLA₂) pathway linking to cyclooxygenase-2 (COX-2) and production of eicosanoids. The ability to provide a better understanding of the molecular targets and mechanism of action of C. nutans extracts and their phytochemical components should encourage future studies to develop new therapeutic strategies for better use of this herb to combat inflammatory diseases.     

Oscillations of certain functional differential equations

Sufficient conditions are presented for all bounded solutions of the linear system of delay differential equations to be oscillatory, where q _ij(–, ), h _jj (0, ), i, j = 1,2,..., n. Also, we study the oscillatory behavior of all bounded solutions of the linear system of neutral differential equations where c, g and h are real constants and i = 1,2,..., n.     

Common and divergent structural features of a series of corticotropin releasing factor-related peptides

Members of the corticoliberin family include the corticotropin releasing factors (CRFs), sauvagine, the urotensins, and urocortin 1 (Ucn1), which bind to both the CRF receptors CRF-R1 and CRF-R2, and the urocortins 2 (Ucn2) and 3 (Ucn3), which are selective agonists of CRF-R2. Structure activity relationship studies led to several potent and long-acting analogues with selective binding to either one of the receptors. NMR structures of six ligands of this family (the antagonists astressin B and astressin2-B, the agonists stressin1, and the natural ligands human Ucn1, Ucn2, and Ucn3) were determined in DMSO. These six peptides show differences in binding affinities, receptor-selectivity, and NMR structure. Overall, their backbones are alpha-helical, with a small kink or a turn around residues 25-27, resulting in a helix-loop-helix motif. The C-terminal helices are of amphipathic nature, whereas the N-terminal helices vary in their amphipathicity. The C-terminal helices thereby assume a conformation very similar to that of astressin bound to the ECD1 of CRF-R2 recently reported by our group.1 On the basis of an analysis of the observed 3D structures and relative potencies of [Ala]-substituted analogues, it is proposed that both helices could play a crucial role in receptor binding and selectivity. In conclusion, the C-terminal helices may interact along their hydrophobic faces with the ECD1, whereas the entire N-terminal helical surface may be involved in receptor activation. On the basis of the common and divergent features observed in the 3D structures of these ligands, multiple binding models are proposed that may explain their plurality of actions.     

Semiparametric marginal and association regression methods for clustered binary data

Clustered data arise commonly in practice and it is often of interest to estimate the mean response parameters as well as the association parameters. However, most research has been directed to inference about the mean response parameters with the association parameters relegated to a nuisance role. There is little work concerning both the marginal and association structures, especially in the semiparametric framework. In this paper, our interest centers on inference on the association parameters in addition to the mean parameters. We develop semiparametric methods for both complete and incomplete clustered binary data and establish the theoretical results. The proposed methodology is illustrated through numerical studies.     

A microfabricated electrical differential counter for the selective enumeration of CD4+ T lymphocytes

We have developed a microfabricated biochip that enumerates CD4+ T lymphocytes from leukocyte populations obtained from human blood samples using electrical impedance sensing and immunoaffinity chromatography. T cell counts are found by obtaining the difference between the number of leukocytes before and after depleting CD4+ T cells with immobilized antibodies in a capture chamber. This differential counting technique has been validated to analyze physiological concentrations of leukocytes with an accuracy of ～9 cells per μL by passivating the capture chamber with bovine serum albumin. In addition, the counter provided T cell counts which correlated closely with an optical control (R(2) = 0.997) for CD4 cell concentrations ranging from approximately 100 to 700 cells per μL. We believe that this approach can be a promising method for bringing quantitative HIV/AIDS diagnostics to resource-poor regions in the world.     

New pentacyclic ring systems: intramolecular cyclization of o,o′-disubstituted bibenzothiazoles

Efficient methods for the preparation of isomeric o,o′-diaminobibenzothiazoles (8a and 11a) and o,o′-diamino-2,2′-dimethylbibenzothiazoles (8b and 11b), potentially valuable building blocks for construction of hitherto unknown dithiazolo annulated pentacyclic heterocycles, have been developed. The dithiazolo annulated benzo[c]cinnolines 9a, 9b, and 12a were prepared from the corresponding diamines by oxidation with PhI(OAc)₂ in good yield. The dithiazolo annulated carbazoles 13 and 14 were efficiently prepared from the corresponding diamines by thermal cyclization in H₃PO₄. The unusual course of reduction and product formation of o,o′-dinitrosubstituted bibenzothiazoles 6a and 6b with SnCl₂ under acidic conditions was rationalized by DFT quantum-mechanical calculations. It was suggested that cyclic products are formed from dinitroso derivatives and open-shell species immediately following on a reduction path.     

Synthesis and properties of functionalized 4 nm scale molecular wires with thiolated termini for self-assembly onto metal surfaces

We report the synthesis of new oligo(aryleneethynylene) molecular wires of ca. 4 nm length scale by palladium-catalyzed Sonogashira cross-coupling methodology. Key structural features are the presence of electron donor 9-(1,3-dithiol-2-ylidene)fluorene (compounds 13 and 14) and electron acceptor 9-[di(4-pyridyl)methylene]fluorene units (compound 16) at the core of the molecules. Terminal thiolate substituents are protected as cyanoethylsulfanyl (13 and 16) or thioacetate derivatives (14). The molecules display well-defined redox processes in solution electrochemical studies. The optical properties in solution are similar to those of the fluorenone analog 6: the strongest absorptions for 6, 13 and 16 are in the region lambda(max) = 387-393 nm, with 13 showing an additional shoulder at 415 nm which is not present for 6 and 16; this shoulder is assigned to a HOMO-LUMO transition from the dithiole to the fluorene unit. Molecules 6, 13, 14 and 16 form self-assembled monolayers on gold substrates which exhibit essentially symmetrical current-voltage (I-V) characteristics when contacted by a gold scanning tunelling microscope (STM) tip. The effects of the chemical modifications at the central unit of 6, 14 and 16 on the HOMO-LUMO levels and electron transport through the molecules in vacuum have been computed by an ab initio approach.     

Single-molecule electrical studies on a 7 nm long molecular wire

A self-assembled arylene-ethynylene molecular wire with a rigid 7 nm long backbone exhibits symmetrical current-voltage (I-V) characteristics and a single-molecule current of 0.35 +/- 0.05 nA at 0.3 V; these data are supported by theoretical calculations.     

Physics-informed deep learning for digital materials

In this work, a physics-informed neural network(PINN) designed specifically for analyzing digital materials is introduced. This proposed machine learning(ML) model can be trained free of ground truth data by adopting the minimum energy criteria as its loss function. Results show that our energy-based PINN reaches similar accuracy as supervised ML models. Adding a hinge loss on the Jacobian can constrain the model to avoid erroneous deformation gradient caused by the nonlinear logarithmic strain. Lastly, we discuss how the strain energy of each material element at each numerical integration point can be calculated parallelly on a GPU. The algorithm is tested on different mesh densities to evaluate its computational efficiency which scales linearly with respect to the number of nodes in the system. This work provides a foundation for encoding physical behaviors of digital materials directly into neural networks, enabling label-free learning for the design of next-generation composites.