Search

Thermal simulation plays a crucial role in various fields, often involving complex partial differential equation (PDE) simulations for thermal optimization. To tackle this challenge, we have harnessed neural networks for thermal prediction, specifically employing deep neural networks as a universal solver for PDEs. This innovative approach has garnered significant attention in the scientific community. While Physics-Informed Neural Networks (PINNs) have been introduced for thermal prediction using deep neural networks, existing methods primarily focus on offering thermal simulations for predefined relevant parameters, such as heat sources, loads, boundaries, and initial conditions. However, any adjustments to these parameters typically require retraining or transfer learning, resulting in considerable additional work. To overcome this limitation, we integrated PINN methods with the DeepONet model, creating a novel model called PI-DeepONet for thermal simulation. This model takes both relevant parameters and coordinate points as simultaneous input functions, presenting a fresh computational perspective for thermal simulation. Based on the PaddlePaddle deep learning framework, our research demonstrates that after sufficient training, this model can reliably and rapidly predict parameter solutions. Importantly, it significantly surpasses traditional numerical solvers in terms of speed by several orders of magnitude, without requiring additional training. This groundbreaking research framework holds vast application potential and promises substantial advancements in the field of thermal simulation. [ABSTRACT FROM AUTHOR]

In vitro diagnostics (IVD) plays a critical role in healthcare and public health management. Magnetic digital microfluidics (MDM) perform IVD assays by manipulating droplets on an open substrate with magnetic particles. Automated IVD based on MDM could reduce the risk of accidental exposure to contagious pathogens among healthcare workers. However, it remains challenging to create a fully automated IVD platform based on the MDM technology because of a lack of effective feedback control system to ensure the successful execution of various droplet operations required for IVD. In this work, an artificial intelligence (AI)‐empowered MDM platform with image‐based real‐time feedback control is presented. The AI is trained to recognize droplets and magnetic particles, measure their size, and determine their location and relationship in real time; it shows the ability to rectify failed droplet operations based on the feedback information, a function that is unattainable by conventional MDM platforms, thereby ensuring that the entire IVD process is not interrupted due to the failure of liquid handling. We demonstrate fundamental droplet operations, which include droplet transport, particle extraction, droplet merging and droplet mixing, on the MDM platform and show how the AI rectify failed droplet operations by acting upon the feedback information. Protein quantification and antibiotic resistance detection are performed on this AI‐empowered MDM platform, and the results obtained agree well with the benchmarks. We envision that this AI‐based feedback approach will be widely adopted not only by MDM but also by other types of digital microfluidic platforms to offer precise and error‐free droplet operations for a wide range of automated IVD applications. [ABSTRACT FROM AUTHOR]

Placenta accreta spectrum (PAS) is one of the most dangerous complications in obstetrics, which can lead to severe postpartum bleeding and shock, and even necessitate uterine removal. The abnormal migration and invasion of extravillous trophoblast cells (EVTs) and enhanced neovascularization occurring in an uncontrolled manner in time and space are closely related to the abnormal expression of pro-angiogenic and anti-angiogenic factors. The pigment epithelium-derived factor (PEDF) is a multifunctional regulatory factor that participates in several important biological processes and is recognized as the most efficient inhibitor of angiogenesis. The present study aimed to explore the effects of PEDF on EVT phenotypes and the underlying mechanisms in PAS. HTR-8/SVneo cells were transfected to overexpress or knock down PEDF. Cell proliferation and invasion were assessed using Cell Counting Kit-8, 5-ethynyl-2′-deoxyuridine and Transwell assays. In vitro angiogenesis was analyzed using tube formation assays. The degree of ferroptosis was assessed by evaluating the levels of lipid reactive oxygen species, total iron, Fe2+, malondialdehyde and reduced glutathione using commercial kits. The expression levels of biomarkers of ferroptosis, angiogenesis, cell proliferation and Wnt signaling were examined by western blotting. PEDF overexpression decreased the proliferation, invasion and angiogenesis, and induced ferroptosis of EVTs. Activation of Wnt signaling with BML-284 and overexpression of vascular endothelial growth factor (VEGF) reversed the PEDF overexpression-induced suppression of cell proliferation, invasion and tube formation. PEDF overexpression-induced ferroptosis was also decreased by Wnt agonist treatment and VEGF overexpression. It was predicted that PEDF suppressed the proliferation, invasion and angiogenesis, and increased ferroptosis in EVTs by decreasing Wnt-β-catenin/VEGF signaling. The findings of the present study suggested a novel regulatory mechanism of the phenotypes of EVTs and PAS. [ABSTRACT FROM AUTHOR]

After spinal cord injury (SCI), endogenous angiogenesis occurs in the injury core, unexpectedly accompanied by continuous leakage of the blood-spinal cord barrier (BSCB), which may be caused by destruction of the tight junctions (TJs) between vascular endothelial cells—an important structure of the BSCB. Blood-derived macrophages infiltrate into the spinal cord, aggregate to the injury core and then polarize toward M1/M2 phenotypes after SCI. However, the effect of macrophages with different polarizations on the TJs between vascular endothelial cells remains unclear. Here, we demonstrated that from 7 days postinjury (dpi) to 28 dpi, accompanied by the aggregation of macrophages, the expression of claudin-5 (CLN-5) and zonula occludens-1 (ZO-1) in vascular endothelial cells in the injury core was significantly decreased in comparison to that in normal spinal cord tissue and in the penumbra. Moreover, the leakage of the BSCB was severe in the injury core, as demonstrated by FITC-dextran perfusion. Notably, our study demonstrated that depletion of macrophages facilitated the restoration of TJs between vascular endothelial cells and decreased the leakage of BSCB in the injury core after SCI. Furthermore, we confirmed that the endothelial TJs could be impaired by M1 macrophages through secreting IL-6 in vitro, leading to an increased permeability of endothelial cells, but it was not significantly affected by M0 and M2 macrophages. These results indicated that the TJs between vascular endothelial cells were impaired by M1 macrophages in the injury core, potentially resulting in continuous leakage of the BSCB after SCI. Preventing M1 polarization of macrophages or blocking IL-6 in the injury core may promote restoration of the BSCB, thus accelerating functional recovery after SCI. ● The endothelial TJs are impaired in the injury core at the chronic phase of SCI. ● M1 macrophages impair the endothelial TJs by secreting IL-6 after SCI. ● Myelin-laden macrophages impair the TJs while M2 macrophages protect them in vitro. [ABSTRACT FROM AUTHOR]

Molybdenum disulfide (MoS 2 )-based materials for piezocatalysis are unsatisfactory due to their low actual piezoelectric coefficient and poor electrical conductivity. Herein, 1T/3R phase MoS 2 grown in situ on multiwalled carbon nanotubes (MWCNTs) was proposed. MoS 2 @MWCNTs exhibited the interwoven morphology of thin nanoflowers and tubes, and the piezoelectric response of MoS 2 @MWCNTs was 4.07 times higher than that of MoS 2 via piezoresponse force microscopy (PFM) characterization. MoS 2 @MWCNTs exhibited superior activity with a 91% degradation rate of norfloxacin (NOR) after actually working 24 min (as for rhodamine B, reached 100% within 18 min) by pulse-mode ultrasonic vibration-triggered piezocatalysis. It was found that piezocatalysis for removing pollutants was attributed to the synergistic effect of free radicals ( • OH and O 2 •- ) and nonfree radical ( 1 O 2 , key role) pathways, together with the innergenerated-H 2 O 2 promoting the degradation rate. 1 O 2 can be generated by electron transfer and energy transfer pathways. The presence of oxygen vacancies (OVs) induced the transformation of O 2 to 1 O 2 by triplet energy transfer. The fast charge transfer in MoS 2 @MWCNTs heterostructure and the coexistence of sulfur vacancies and OVs enhanced charge carrier separation resulting in a prominent piezoelectric effect. This work opens up new avenues for the development of efficient piezocatalysts that can be utilized for environmental purification.

The compound N , N -dimethylformamide (DMF) is a widely used industrial chemical and a common environmental contaminant that has been found to be harmful to human health. In this study, electrochemical oxidation was adopted for the degradation of DMF. The effects of four kinds of electrodes on the removal rates of DMF and total organic carbon were compared, and based on the result, the Ti/RuO 2 -IrO 2 electrode was selected as the operating electrode. The effects of three independent factors (current density, pH, and NaCl proportion) on the DMF degradation were investigated through single-factor experiments, and the experimental results were optimized by response surface methodology. The optimal experimental conditions were obtained as follows: current density = 47 mA cm -2 , pH = 5.5, and NaCl proportion = 15%. The electrochemical oxidation of 50 mg L -1 DMF was performed under the optimal conditions; the degradation rate was 97.2% after 7 h, and the reaction followed the pseudo-first-order kinetic model. The degradation products under optimal conditions and chlorine-free conditions were analyzed, and four degradation pathways were proposed. The DMF degradation was more thorough under optimal conditions., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)