Biodiversity and antifouling activity of microbes associated with gorgonian corals Leptogorgia rigida and Menella kanisa from the South China Sea.

Recently, coral-associated microorganisms have attracted widespread attention, and most of these studies have focused on stony and soft corals. However, our knowledge of the diversity and bioactivity of microorganisms in gorgonian corals is still limited. In this study, the biodiversity of microbes in two gorgonian corals (Leptogorgia rigida and Menella kanisa) from the South China Sea was investigated by combining traditional culture method with molecular biology technique (bacterial 16S or fungal internal transcribed spacer (ITS) rRNA gene sequences).

Significant correlations between heavy metals and prokaryotes in the Okinawa Trough hydrothermal sediments.

Prokaryotes play crucial roles in hydrothermal vent ecosystems, yet their interactions with heavy metals are not well understood. This study explored the diversity of prokaryotic communities and their correlations with heavy metals and nutrient elements in hydrothermal sediments from Okinawa Trough. A total of 117 bacterial genera in 26 bacterial phyla and 10 archaeal classes in 3 archaeal phyla were identified, including dominant prokaryotic phyla Planctomycetes, Acidobacteria, Verrucomicrobia, and Euryarchaeota.

Mechanisms underlying the efficacy and limitation of dopa and tetrahydrobiopterin therapies for the deficiency of GTP cyclohydrolase 1 revealed in a novel mouse model.

Dopa and tetrahydrobiopterin (BH4) supplementation are recommended therapies for the dopa-responsive dystonia caused by GTP cyclohydrolase 1 (GCH1, also known as GTPCH) deficits. However, the efficacy and mechanisms of these therapies have not been intensively studied yet. In this study, we tested the efficacy of dopa and BH4 therapies by using a novel GTPCH deficiency mouse model, Gch1, which manifested infancy-onset motor deficits and growth retardation similar to the patients.

Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows.

Quantifying the flow of cerebrospinal fluid (CSF) is crucial for understanding brain waste clearance and nutrient delivery, as well as edema in pathological conditions such as stroke. However, existing in vivo techniques are limited to sparse velocity measurements in pial perivascular spaces (PVSs) or low-resolution measurements from brain-wide imaging. Additionally, volume flow rate, pressure, and shear stress variation in PVSs are essentially impossible to measure in vivo.

Iron Removal from Metallurgical Grade Silicon Melts Using Synthetic Slags and Oxygen Injection.

Novel SiO-CaO-CaF-RO-MgO based synthetic slags (RO represents alkali metal oxides) with varied binary basicity values were used with oxygen injection to refine silicon melts and remove Fe from metallurgical-grade silicon. Silicon samples and slags at the silicon-slag interfaces were obtained during refinement. The compositions of the silicon samples were analyzed, and the quenched slag samples and mild cooling slags from the final crucible were inspected using scanning electron microscopy and energy dispersive X-ray spectroscopy.

Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks.

We analyze a plurality of epidemiological models through the lens of physics-informed neural networks (PINNs) that enable us to identify time-dependent parameters and data-driven fractional differential operators. In particular, we consider several variations of the classical susceptible-infectious-removed (SIR) model by introducing more compartments and fractional-order and time-delay models. We report the results for the spread of COVID-19 in New York City, Rhode Island and Michigan states and Italy, by simultaneously inferring the unknown parameters and the unobserved dynamics.

Non-invasive Inference of Thrombus Material Properties with Physics-Informed Neural Networks.

We employ physics-informed neural networks (PINNs) to infer properties of biological materials using synthetic data. In particular, we successfully apply PINNs on inferring permeability and viscoelastic modulus from thrombus deformation data, which can be described by the fourth-order Cahn-Hilliard and Navier-Stokes Equations. In PINNs, the partial differential equations are encoded into a loss function, where partial derivatives can be obtained through automatic differentiation (AD).

Predictive modelling of thrombus formation in diabetic retinal microaneurysms.

Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). Vision can be reduced at any stage of DR by MAs, which may enlarge, rupture and leak fluid into the neural retina. Recent advances in ophthalmic imaging techniques enable reconstruction of the geometries of MAs and quantification of the corresponding haemodynamic metrics, such as shear rate and wall shear stress, but there is lack of computational models that can predict thrombus formation in individual MAs.

A three-dimensional phase-field model for multiscale modeling of thrombus biomechanics in blood vessels.

Mechanical interactions between flowing and coagulated blood (thrombus) are crucial in dictating the deformation and remodeling of a thrombus after its formation in hemostasis. We propose a fully-Eulerian, three-dimensional, phase-field model of thrombus that is calibrated with existing in vitro experimental data. This phase-field model considers spatial variations in permeability and material properties within a single unified mathematical framework derived from an energy perspective, thereby allowing us to study effects of thrombus microstructure and properties on its deformation and possible release of emboli under different hemodynamic conditions.

[Activity and transcriptional regulatory elements of the promoter in Arctic fox (Vulpes lagopus) β-defensin103 gene].

The aim of this study was to screen the active regions and transcription factor binding sites in the promoter of the CBD103 gene related to Arctic fox coat color, and to provide a basis for revealing the molecular genetic mechanism of CBD103 gene regulating the coat color formation. The 5'-flanking region fragment 2 123 bp of Arctic fox CBD103 gene was cloned, and 4 truncated promoter reporter vectors of different lengths were constructed. The promoter activity was detected by the dual-luciferase reporter assay system.

Future of lignite resources: a life cycle analysis.

Lignite is a low-quality energy source which accounts for 13 % of China's coal reserves. It is imperative to improve the quality of lignite for large-scale utilization. To further explore and analyze the influence of various key processes on the environment and economic costs, a lignite drying and compression technology is evaluated using an integrated approach of life cycle assessment and life cycle costs.