Ultrastretchable E-Skin Based on Conductive Hydrogel Microfibers for Wearable Sensors.

Conductive microfibers play a significant role in the flexibility, stretchability, and conductivity of electronic skin (e-skin). Currently, the fabrication of conductive microfibers suffers from either time-consuming and complex operations or is limited in complex fabrication environments. Thus, it presents a one-step method to prepare conductive hydrogel microfibers based on microfluidics for the construction of ultrastretchable e-skin. The microfibers are achieved with conductive MXene cores and hydrogel shells, which are solidified with the covalent cross-linking between sodium alginate and calcium chloride, and mechanically enhanced by the complexation reaction of poly(vinyl alcohol) and sodium hydroxide. The microfiber conductivities are tailorable by adjusting the flow rate and concentration of core and shell fluids, which is essential to more practical applications in complex scenarios. More importantly, patterned e-skin based on conductive hydrogel microfibers can be constructed by combining microfluidics with 3D printing technology. Because of the great advantages in mechanical and electrical performance of the microfibers, the achieved e-skin shows impressive stretching and sensitivity, which also demonstrate attractive application values in motion monitoring and gesture recognition. These characteristics indicate that the ultrastretchable e-skin based on conductive hydrogel microfibers has great potential for applications in health monitoring, wearable devices, and smart medicine.

Butyrolactone-I, an efficient α-glucosidase inhibitor, improves type 2 diabetes with potent TNF-α-lowering properties through modulating gut microbiota in db/db mice.

The aim of this study was to evaluate the effects of butyrolactone-I (A6) on type 2 diabetes (T2D) in db/db mice because A6 was found to inhibit α-glucosidase activities and TNF-α release, which were associated with improving T2D. Male db/db mice were divided into 6 groups and given an equivalent volume of olive oil, acarbose, or different doses of A6 for 4 wk (n = 8/group). In this study, 11 butenolide derivatives were screened for their α-glucosidase and TNF-α suppressive activity in vitro. A6, an efficient α-glucosidase inhibitor, exerts hypoglycemic and multiple activities in reducing weight, improving glucose tolerance and insulin resistance, increasing short-chain fatty acid (SCFA) levels, activating SCFA-induced increases in glucagon-like peptide 1 and peroxisome proliferator-activated receptor-γ expression, enhancing intestinal mucosal barrier function and mitigating endoxemia in db/db mice. These effects may result from mediation of gut microbiota by A6. Meanwhile, A6, with potent TNF-α-lowering properties, was demonstrated to have multiple salutary effects with excellent structural stability and long-term safety in vivo. A6, an effective α-glucosidase inhibitor with high security and stability, exerted potent antidiabetic effects in vivo. Furthermore, the modulation of gut microbiota of A6 was demonstrated to be one of the mechanisms contributing to anti-inflammation properties and improving endoxemia. Our work confirms that the compound A6 is a prospective drug candidate for T2D.-Wu, W., Liu, L., Zhu, H., Sun, Y., Wu, Y., Liao, H., Gui, Y., Li, L., Liu, L., Sun, F., Lin, H. Butyrolactone-I, an efficient α-glucosidase inhibitor, improves type 2 diabetes with potent TNF-α-lowering properties through modulating gut microbiota in db/db mice.

Discovery of nitrogenous sesquiterpene quinone derivatives from sponge Dysidea septosa with anti-inflammatory activity in vivo zebrafish model.

Two unique nitrogenous sesquiterpene quinone meroterpenoids, dysidinoid B (1) and dysicigyhone A (2), together with eight known analogues (3-10) were isolated and characterized from the marine sponge Dysidea septosa. Their structures with absolute configurations were established by a combination of extensive spectroscopic, electron circular dichroism (ECD) and single-crystal X-ray diffraction data analysis. Structurally, dysicigyhone A (2) possessed a unique benzo[d]oxazolidine-2-one unit. Additionally, dysidinoid B (1) exhibited significant anti-inflammatory effect by inhibiting TNF-α and IL-6 generation with IC50 values of 9.15 µM and 17.62 µM, respectively. Further in vivo anti-inflammatory assay verified that the dysidinoid B (1) alleviated the CuSO4-induced robust acute inflammatory response in zebrafish model.

Spongiactinospora rosea gen. nov., sp. nov., a new member of the family Streptosporangiaceae.

A novel aerobic, spore-forming, marine actinomycete, designated strain LHW63015T, was isolated from a Craniella marine sponge collected in the South China Sea. The strain formed extensively branched substrate and aerial mycelia which carried long and crooked spore chains composed of ridged spores and spherical pseudosporangia. Strain LHW63015T contained meso-diaminopimelic acid as the diagnostic diamino acid. Glucose, ribose, mannose, galactose and madurose occured in whole-cell hydrolysates. The predominant polar lipids were hydroxyl-phosphatidylethanolamine, phosphoglycolipid and ninhydrin-positive phosphoglycolipid. MK-10(H4) and MK-10(H6) were the predominant menaquinones. The major fatty acids were 10-methyl C17 : 0 and C17 : 1ω8c. The G+C content of the genomic DNA was 70.8 mol%. In phylogenetic analysis based on 16S rRNA gene sequences, strain LHW63015T fell within the family Streptosporangiaceae and formed a distinct monophyletic lineage adjacent to the genus Sphaerisporangium, and shared the highest 16S rRNA gene sequence similarity of 96.2 % with Sphaerisporangium album YIM 48782T. On the basis of the polyphasic evidence, a novel genus and species of the family Streptosporangiaceae, for which the name Spongiactinospora rosea gen. nov., sp. nov., is proposed, with the type strain LHW63015T (=DSM 106635T=CCTCC AA 2018019T).

Machine-Learning-Based Data Analysis Method for Cell-Based Selection of DNA-Encoded Libraries.

DNA-encoded library (DEL) is a powerful ligand discovery technology that has been widely adopted in the pharmaceutical industry. DEL selections are typically performed with a purified protein target immobilized on a matrix or in solution phase. Recently, DELs have also been used to interrogate the targets in the complex biological environment, such as membrane proteins on live cells. However, due to the complex landscape of the cell surface, the selection inevitably involves significant nonspecific interactions, and the selection data are much noisier than the ones with purified proteins, making reliable hit identification highly challenging. Researchers have developed several approaches to denoise DEL datasets, but it remains unclear whether they are suitable for cell-based DEL selections. Here, we report the proof-of-principle of a new machine-learning (ML)-based approach to process cell-based DEL selection datasets by using a Maximum A Posteriori (MAP) estimation loss function, a probabilistic framework that can account for and quantify uncertainties of noisy data. We applied the approach to a DEL selection dataset, where a library of 7,721,415 compounds was selected against a purified carbonic anhydrase 2 (CA-2) and a cell line expressing the membrane protein carbonic anhydrase 12 (CA-12). The extended-connectivity fingerprint (ECFP)-based regression model using the MAP loss function was able to identify true binders and also reliable structure-activity relationship (SAR) from the noisy cell-based selection datasets. In addition, the regularized enrichment metric (known as MAP enrichment) could also be calculated directly without involving the specific machine-learning model, effectively suppressing low-confidence outliers and enhancing the signal-to-noise ratio. Future applications of this method will focus on de novo ligand discovery from cell-based DEL selections.

Converting Double-Stranded DNA-Encoded Libraries (DELs) to Single-Stranded Libraries for More Versatile Selections.

DNA-encoded library (DEL) is an efficient high-throughput screening technology platform in drug discovery and is also gaining momentum in academic research. Today, the majority of DELs are assembled and encoded with double-stranded DNA tags (dsDELs) and has been selected against numerous biological targets; however, dsDELs are not amendable to some of the recently developed selection methods, such as the cross-linking-based selection against immobilized targets and live-cell-based selections, which require DELs encoded with single-stranded DNAs (ssDELs). Herein, we present a simple method to convert dsDELs to ssDELs using exonuclease digestion without library redesign and resynthesis. We show that dsDELs could be efficiently converted to ssDELs and used for affinity-based selections either with purified proteins or on live cells.

Frondoplysins A and B, Unprecedented Terpene-Alkaloid Bioconjugates from Dysidea frondosa.

The chemical investigation of the marine sponge Dysidea frondosa discovered a pair of unprecedented bioconjugates that are composed of a meroterpene and an unusual psammaplysin alkaloid. The structures of frondoplysins A (1) and B (2) were characterized by analysis of HRMS and NMR data coupled with single-crystal X-ray diffraction. Frondoplysin A was found to be a potent inhibitor targeting protein-tyrosine phosphatase 1B (PTP1B) with an IC50 value of 0.39 µM.

Septosones A-C, in Vivo Anti-inflammatory Meroterpenoids with Rearranged Carbon Skeletons from the Marine Sponge Dysidea septosa.

Three unusual meroterpenoids, septosones A-C (1-3), were isolated from the marine sponge Dysidea septosa. The structures were determined by analysis of spectroscopic data combined with single-crystal X-ray diffraction and ECD calculations. Septosone A (1) features an unprecedented "septosane" carbon skeleton, whereas septosones B (2) and C (3) share a rare spiro[4.5]decane motif. Septosone A showed in vivo anti-inflammatory activity in CuSO4-induced transgenic fluorescent zebrafish likely through inactivation of the NF-κB signaling pathway.