Nicotinic Acid Increases Adiponectin Secretion from Differentiated Bovine Preadipocytes through G-Protein Coupled Receptor Signaling

The transition period in dairy cows (3 weeks prepartum until 3 weeks postpartum) is associated with substantial mobilization of energy stores, which is often associated with metabolic diseases. Nicotinic acid (NA) is an antilipolytic and lipid-lowering compound used to treat dyslipidaemia in humans, and it also reduces non-esterified fatty acids in cattle. In mice the G-protein coupled receptor 109A (GPR109A) ligand NA positively affects the secretion of adiponectin, an important modulator of glucose and fat metabolism. In cattle, the corresponding data linking NA to adiponectin are missing. Our objective was to examine the effects of NA on adiponectin and AMPK protein abundance and the expression of mRNAs of related genes such as chemerin, an adipokine that enhances adiponectin secretion in vitro. Differentiated bovine adipocytes were incubated with pertussis toxin (PTX) to verify the involvement of GPR signaling, and treated with 10 or 15 µM NA for 12 or 24 h. NA increased adiponectin concentrations (p ≤ 0.001) and the mRNA abundances of GPR109A (p ≤ 0.05) and chemerin (p ≤ 0.01). Pre-incubation with PTX reduced the adiponectin response to NA (p ≤ 0.001). The NA-stimulated secretion of adiponectin and the mRNA expression of chemerin in the bovine adipocytes were suggestive of GPR signaling-dependent improved insulin sensitivity and/or adipocyte metabolism in dairy cows.     

Augmented semantic segmentation for the digitization of grinding tools based on deep learning

In order to analyze various process characteristics, grinding simulations can be used, which need accurate models of the tool and the individual grains. For this purpose, grinding tools can be digitized. To identify characteristic grains from a large number of measurements, each individual grain has to be analyzed and separated from the bond manually. Therefore, a deep learning-based methodology was developed to achieve a high segmentation accuracy of the grain boundaries efficiently. Additionally, a data augmentation approach was investigated to limit the data necessary for learning. The model transferability was quantified by analyzing different states of tool wear.     

Mass Spectrometric Assays Reveal Discrepancies in Inhibition Profiles for the SARS-CoV-2 Papain-Like Protease

The two SARS-CoV-2 proteases, i. e. the main protease (M^pro) and the papain-like protease (PL^pro), which hydrolyze the viral polypeptide chain giving functional non-structural proteins, are essential for viral replication and are medicinal chemistry targets. We report a high-throughput mass spectrometry (MS)-based assay which directly monitors PL^pro catalysis in vitro. The assay was applied to investigate the effect of reported small-molecule PL^pro inhibitors and selected M^pro inhibitors on PL^pro catalysis. The results reveal that some, but not all, PL^pro inhibitor potencies differ substantially from those obtained using fluorescence-based assays. Some substrate-competing M^pro inhibitors, notably PF-07321332 (nirmatrelvir) which is in clinical development, do not inhibit PL^pro. Less selective M^pro inhibitors, e. g. auranofin, inhibit PL^pro, highlighting the potential for dual PL^pro/M^pro inhibition. MS-based PL^pro assays, which are orthogonal to widely employed fluorescence-based assays, are of utility in validating inhibitor potencies, especially for inhibitors operating by non-covalent mechanisms.     

The Low‐Temperature Cosintering of Cobalt Ferrite and Lead Zirconate Titanate Ceramic Composites

Magneto‐electric (ME) ceramic composites of cobalt ferrite (CoF) and lead zirconate titanate (PZT) were prepared by mechanical mixing of the constituent powders followed by cosintering. The cosintering conditions for nano‐sized CoF and submicrometer‐sized PZT powders were studied in detail. It was found that the CoF powder needs to be presintered at 700°C for 2 h to minimize the differences in the sintering kinetics of the constituent powders. Despite the low cosintering temperatures (900°C–1000°C) the interdiffusion of the cations from both phases was confirmed with energy‐dispersive X‐ray analysis and X‐ray diffraction. Efforts were made to optimize the cosintering conditions to prepare dense ceramic ME composites, which showed the converse ME effect.     

Achieving β-phase poly(vinylidene fluoride) from melt cooling: Effect of surface functionalized carbon nanotubes

Poly(vinylidene fluoride) (PVDF) based nanocomposites with different surface-functionalized multi-walled carbon nanotubes (MWCNTs) were prepared by melt mixing in a small scale compounder. With the incorporation of commercial functionalized MWCNTs, the β-phase in PVDF can be directly achieved from melt cooling, as verified by results of Fourier transform infrared spectrum and X-ray diffraction. Interestingly, nanocomposites with amino group functionalized MWCNTs showed the highest percentage of β-phase (17.4%) formation in PVDF, followed by those with hydroxyl groups (11.6%) and unmodified MWCNTs (9.4%). However, the nanocomposites containing MWCNTs with carboxyl groups which were thought to be able to well interact with the dipoles on PVDF chains have the lowest amount of β-phase, i.e. 4.7%. The analysis on the mechanism of the influence of surface functionalization of MWCNTs on the formation of β-phase in PVDF shows that the combined effects of the dispersion of MWCNTs and the nanotube–polymer interactions account for the formation of the β-phase in PVDF.     

Influence of a cyclic butylene terephthalate oligomer on the processability and thermoelectric properties of polycarbonate/MWCNT nanocomposites

The thermoelectric properties of melt-processed nanocomposites consisting of a polycarbonate (PC) thermoplastic matrix filled with commercially available carboxyl (–COOH) functionalized multi-walled carbon nanotubes (MWCNTs) were evaluated. MWCNTs carrying carboxylic acid moieties (MWCNT-COOH) were used due the p-doping that the carboxyl groups facilitate, via electron withdrawing from the electron-rich π-conjugated system. Preliminary thermogravimetric analysis (TGA) of MWCNT-COOH revealed that the melt-mixing was limited at low temperatures due to thermal decomposition of the MWCNT functional groups. Therefore, PC was mixed with 2.5 wt% MWCNT-COOH (PC/MWCNT-COOH) at 240 °C and 270 °C. In order to reduce the polymer melt viscosity, a cyclic butylene terephthalate (CBT) oligomer was utilized as an additive, improving additionally the electrical conductivity of the nanocomposites. The melt rheological characterization of neat PC and PC/CBT blends demonstrated a significant decrease of the complex viscosity by the addition of CBT (10 wt%). Optical and transmission electron microscopy (OM, TEM) depicted an improved MWCNT dispersion in the PC/CBT polymer blend. The electrical conductivity was remarkably higher for the PC/MWCNT-COOH/CBT composites compared to the PC/MWCNT-COOH ones. Namely, the PC/MWCNT-COOH/CBT processed at 270 °C exhibited the best values with electrical conductivity; σ = 0.05 S/m, Seebeck coefficient; S = 13.55 μV/K, power factor; PF = 7.60 × 10⁻⁶μW/m K⁻², and thermoelectric figure of merit; ZT = 7.94 × 10⁻⁹. The PC/MWCNT-COOH/CBT nanocomposites could be ideal candidates for large-scale thermal energy harvesting, even though the presently obtained ZT values are still too low for commercial applications.     

Rapid Discrimination of Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis Using Machine Learning on Infrared Spectra of Sera

Neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS) are both autoimmune inflammatory and demyelinating diseases of the central nervous system. NMOSD is a highly disabling disease and rapid introduction of the appropriate treatment at the acute phase is crucial to prevent sequelae. Specific criteria were established in 2015 and provide keys to distinguish NMOSD and MS. One of the most reliable criteria for NMOSD diagnosis is detection in patient’s serum of an antibody that attacks the water channel aquaporin-4 (AQP-4). Another target in NMOSD is myelin oligodendrocyte glycoprotein (MOG), delineating a new spectrum of diseases called MOG-associated diseases. Lastly, patients with NMOSD can be negative for both AQP-4 and MOG antibodies. At disease onset, NMOSD symptoms are very similar to MS symptoms from a clinical and radiological perspective. Thus, at first episode, given the urgency of starting the anti-inflammatory treatment, there is an unmet need to differentiate NMOSD subtypes from MS. Here, we used Fourier transform infrared spectroscopy in combination with a machine learning algorithm with the aim of distinguishing the infrared signatures of sera of a first episode of NMOSD from those of a first episode of relapsing-remitting MS, as well as from those of healthy subjects and patients with chronic inflammatory demyelinating polyneuropathy. Our results showed that NMOSD patients were distinguished from MS patients and healthy subjects with a sensitivity of 100% and a specificity of 100%. We also discuss the distinction between the different NMOSD serostatuses. The coupling of infrared spectroscopy of sera to machine learning is a promising cost-effective, rapid and reliable differential diagnosis tool capable of helping to gain valuable time in patients’ treatment.     

The Fight against Cancer by Microgravity: The Multicellular Spheroid as a Metastasis Model

Cancer is a disease exhibiting uncontrollable cell growth and spreading to other parts of the organism. It is a heavy, worldwide burden for mankind with high morbidity and mortality. Therefore, groundbreaking research and innovations are necessary. Research in space under microgravity (µg) conditions is a novel approach with the potential to fight cancer and develop future cancer therapies. Space travel is accompanied by adverse effects on our health, and there is a need to counteract these health problems. On the cellular level, studies have shown that real (r-) and simulated (s-) µg impact survival, apoptosis, proliferation, migration, and adhesion as well as the cytoskeleton, the extracellular matrix, focal adhesion, and growth factors in cancer cells. Moreover, the µg-environment induces in vitro 3D tumor models (multicellular spheroids and organoids) with a high potential for preclinical drug targeting, cancer drug development, and studying the processes of cancer progression and metastasis on a molecular level. This review focuses on the effects of r- and s-µg on different types of cells deriving from thyroid, breast, lung, skin, and prostate cancer, as well as tumors of the gastrointestinal tract. In addition, we summarize the current knowledge of the impact of µg on cancerous stem cells. The information demonstrates that µg has become an important new technology for increasing current knowledge of cancer biology.     

纤维基材料的仿生学研究动向

纤维基技术的应用对仿生学的成功发展呈现出巨大的潜力,因为宇宙成物在生长过程、多毛结构和增强纤维方面具有许多相似性.约七年前,邓肯道夫纺织技术与工艺研究所协同众位生物学家一起开创了仿生学的研发,至今方兴未艾.