Accelerating Elastic Property Prediction in Fe-C Alloys through Coupling of Molecular Dynamics and Machine Learning.

The scarcity of high-quality data presents a major challenge to the prediction of material properties using machine learning (ML) models. Obtaining material property data from experiments is economically cost-prohibitive, if not impossible. In this work, we address this challenge by generating an extensive material property dataset comprising thousands of data points pertaining to the elastic properties of Fe-C alloys. The data were generated using molecular dynamic (MD) calculations utilizing reference-free Modified embedded atom method (RF-MEAM) interatomic potential. This potential was developed by fitting atomic structure-dependent energies, forces, and stress tensors evaluated at ground state and finite temperatures using ab-initio. Various ML algorithms were subsequently trained and deployed to predict elastic properties. In addition to individual algorithms, super learner (SL), an ensemble ML technique, was incorporated to refine predictions further. The input parameters comprised the alloy's composition, crystal structure, interstitial sites, lattice parameters, and temperature. The target properties were the bulk modulus and shear modulus. Two distinct prediction approaches were undertaken: employing individual models for each property prediction and simultaneously predicting both properties using a single integrated model, enabling a comparative analysis. The efficiency of these models was assessed through rigorous evaluation using a range of accuracy metrics. This work showcases the synergistic power of MD simulations and ML techniques for accelerating the prediction of elastic properties in alloys.

Engineering microcracks in MWCNT/elastomer bilayers for high-performance stretchable sensor development.

Stretchable strain sensors in motion detection, health monitoring, and human-machine interfaces are limited by device sensitivity, linearity, hysteresis, stability, and reproducibility in addition to stretchability. Engineering defect structures in sensing material is an effective approach in modulating the material's physical properties, particularly those associated with mechanical responses. Here, we demonstrate that bilayers of carbon nanotubes deposited on an elastomer substrate are mechanically coupled. The microcrack size, density, and distribution in the nanotube thin film can be engineered through uniaxial tensile training to exhibit highly tunable and stable piezoresistive responses with sensitivity, linearity, range, and reproducibility. These responses far exceeding those in uniform metallic films, patterned structures, and composites. In addition, numerical analyses performed on a two-dimensional network model of the cracked nanotube film provide quantitative explanations of how crack configuration, and evolvement under strain, lead to the significant enhancements in stretchable sensor performance using current bilayer structures.

CD45- erythroid progenitor cells promote lymph node metastasis in gastric cancer by inducing a hybrid epithelial/mesenchymal state in lymphatic endothelial cells.

BACKGROUND AND AIMS: Specific mechanisms of lymph node (LN) metastasis in early-stage gastric cancer (GC) have not been elucidated. The role of anemia, a vital clinical feature of GC, in LN metastasis is also unclear. Since the number of erythroid progenitor cells (EPCs) is increased in chronic anemia, we investigated its association with LN metastasis in GC. METHODS: Flow cytometry and immunofluorescence analyses were performed to sort and study EPCs from the circulation and tumors of patients with stage I-III GC. The effect of these EPCs on the activation of T and B cells and on the functions of lymphatic endothelial cells (LECs) was determined, and their ability to promote LN metastasis was evaluated using a footpad-popliteal LN metastasis model based on two human adenocarcinoma GC cell lines in nude mice. The prognostic value of EPCs was also analyzed. RESULTS: The proportion of CD45- EPCs was higher in the mononuclear cells in the circulation, tumors, and LNs of GC patients with LN metastasis (N+) than in those of GC patients without LN metastasis (N0). In N+ patients, CD45- EPCs were more abundant in metastatic LNs than in non-metastatic LNs. Lymphatic vessel endothelial hyaluronan receptor 1 immunoreactivity in tumors revealed that CD45- EPCs were positively associated with nodal stages and lymph vessel density. Furthermore, CD45- EPCs increased LEC proliferation and migration through their S100A8/A9 heterodimer-induced hybrid epithelial/mesenchymal (E/M) state; however, they did not influence the invasion and tubulogenesis of LECs or T and B cell proliferation. CD45- EPCs promoted LN metastasis in vivo; the S100A8/A9 heterodimer mimicked this phenomenon. Finally, CD45- EPCs predicted the overall and disease-free survival of stage I-III GC patients after radical resection. CONCLUSIONS: The CD45- EPCs accumulated in GC tissues and metastatic LNs and promoted LN metastasis via the S100A8/9-induced hybrid E/M state of LECs, which was the specific mechanism of LN metastasis in the early stages of GC.

Erythroid-transdifferentiated myeloid cells promote portal vein tumor thrombus in hepatocellular carcinoma.

Rationale: Hepatocellular carcinoma (HCC) is primarily characterized by a high incidence of vascular invasion. However, the specific mechanism underlying portal vein tumor thrombus (PVTT) in HCC remains unclear. As a consequence of myeloid cell developmental arrest, CD71+ erythroid progenitor cells (EPCs) and myeloid-derived suppressor cells play important roles in HCC; however, their roles in PVTT remain unclear. Methods: The role of CD71+ EPCs in the HCC tumor microenvironment (TME) was evaluated via morphological, RNA-sequencing, enzyme-linked immunosorbent assay, and flow cytometric analyses. Co-culture techniques were employed to assess the CD45+ EPCs and their vascular compromising effect. Additionally, the PVTT-promoting function of CD45+ EPCs was explored in vivo in a murine model. Results: The CD45+EPCs in HCC tissues exhibited increased myeloid cell features, including morphology, surface markers, transforming growth factor (TGF)-ß generation, and gene expression, compared with those in circulation. Hence, a large proportion of CD45+EPCs, particularly those in TMEs, comprise erythroid-transdifferentiated myeloid cells (EDMCs). Additionally, the expression of C-C chemokine receptor type 2 (CCR2) mRNA was upregulated in CD45+EPCs within the TME. Tumor macrophages from HCC tissues induced substantial migration of CD45+EPCs in a dose-dependent manner. Meanwhile, results from immunofluorescence analyses revealed that these two cell types are positively associated in the TME and circulation. That is, EDMCs are chemoattracted by HCC macrophages mainly via CCR2 from CD45+ EPCs in the circulation. Additionally, the expressions of FX, FVII, FGB, C4b, CFB, and CFH were elevated in CD45+EPCs within the TME compared with those in the spleen. The CD45+EPCs from the HCC TME promoted vessel endothelial cell migration and compromised tube formation through TGF-ß and FGB, respectively. Additionally, CD45+EPCs from the TME induced HCC cell migration. HCC macrophage-induced CD45+EPCs to exhibit higher levels of FX, FVII, FGB, and TGF-ß. Meanwhile, upregulation of CCAAT/enhancer binding protein beta expression induced FGB and TGF-ß generation in CD45+EPCs in the TME. WTAP, a major RNA m6A writer, stabilized FX and FVII mRNA and enhanced their nuclear export in CD45+EPCs from the TME. CD45+EPCs from the TME were positively associated with PVTT and poor prognosis. Splenectomy reduced the level of CD45+EPCs in the circulation and TME, as well as the incidence of microvascular invasion. The incidence of microvascular invasion increased following the transfer of HCC tissue CD45+EPCs to splenectomized HCC-bearing mice. Conclusions: The CD45+EPCs enriched in the HCC microenvironment are EDMCs, which are induced by HCC macrophages to migrate from the circulation to the TME. Subsequently, EDMCs promote PVTT by compromising the blood vessel endothelium, aggravating coagulation, and promoting HCC cell migration.

PKM2 promotes proinflammatory macrophage activation in ankylosing spondylitis.

Macrophages play a critical role in ankylosing spondylitis by promoting autoimmune tissue inflammation through various effector functions. The inflammatory potential of macrophages is highly influenced by their metabolic environment. Here, we demonstrate that glycolysis is linked to the proinflammatory activation of human blood monocyte-derived macrophages in ankylosing spondylitis. Specifically, ankylosing spondylitis macrophages produced excessive inflammation, including TNFα, IL1ß, and IL23, and displayed an overactive status by exhibiting stronger costimulatory signals, such as CD80, CD86, and HLA-DR. Moreover, we found that patient-derived monocyte-derived M1-type macrophages (M1 macrophages) exhibited intensified glycolysis, as evidenced by a higher extracellular acidification rate. Upregulation of PKM2 and GLUT1 was observed in ankylosing spondylitis-derived monocytes and monocyte-derived macrophages, especially in M1 macrophages, indicating glucose metabolic alteration in ankylosing spondylitis macrophages. To investigate the impact of glycolysis on macrophage inflammatory ability, we treated ankylosing spondylitis M1 macrophages with 2 inhibitors: 2-deoxy-D-glucose, a glycolysis inhibitor, and shikonin, a PKM2 inhibitor. Both inhibitors reduced proinflammatory function and reversed the overactive status of ankylosing spondylitis macrophages, suggesting their potential utility in treating the disease. These data place PKM2 at the crosstalk between glucose metabolic changes and the activation of inflammatory macrophages in patients with ankylosing spondylitis.

Development of the RF-MEAM Interatomic Potential for the Fe-C System to Study the Temperature-Dependent Elastic Properties.

One of the major impediments to the computational investigation and design of complex alloys such as steel is the lack of effective and versatile interatomic potentials to perform large-scale calculations. In this study, we developed an RF-MEAM potential for the iron-carbon (Fe-C) system to predict the elastic properties at elevated temperatures. Several potentials were produced by fitting potential parameters to the various datasets containing forces, energies, and stress tensor data generated using density functional theory (DFT) calculations. The potentials were then evaluated using a two-step filter process. In the first step, the optimized RSME error function of the potential fitting code, MEAMfit, was used as the selection criterion. In the second step, molecular dynamics (MD) calculations were employed to calculate ground-state elastic properties of structures present in the training set of the data fitting process. The calculated single crystal and poly-crystalline elastic constants for various Fe-C structures were compared with the DFT and experimental results. The resulting best potential accurately predicted the ground state elastic properties of B1, cementite, and orthorhombic-Fe7C3 (O-Fe7C3), and also calculated the phonon spectra in good agreement with the DFT-calculated ones for cementite and O-Fe7C3. Furthermore, the potential was used to successfully predict the elastic properties of interstitial Fe-C alloys (FeC-0.2% and FeC-0.4%) and O-Fe7C3 at elevated temperatures. The results were in good agreement with the published literature. The successful prediction of elevated temperature properties of structures not included in data fitting validated the potential's ability to model elevated-temperature elastic properties.

LAG3+ erythroid progenitor cells inhibit HBsAg seroclearance during finite pegylated interferon treatment through LAG3 and TGF-ß.

HBsAg seroclearance, the ideal aim of anti-hepatitis B virus (HBV) treatment, cannot be achieved easily. Anemia is another common issue for chronic hepatitis B (CHB) patients, which leads to elevation of erythroid progenitor cells (EPCs) and immune suppression in cancer. This study investigated the role of EPCs in HBsAg seroclearance following pegylated interferon-α (PEG-IFN) treatment. CD45+EPC accumulation in CHB patients and an AAV/HBV mice model was found in the circulation and liver by flow cytometry and immunofluorescence tests. Wright-Giemsa staining showed that these pathological CD45+EPCs presented elevated erythroid cells with relative immature morphologies and atypical cells compared with the control cells. CD45+EPCs were associated with immune tolerance and decreased HBsAg seroclearance during finite PEG-IFN treatment. CD45+EPCs suppressed antigen non-specific T cell activation and HBV-specific CD8+T cells, partially through transforming growth factor ß (TGF-ß). RNA-seq revealed that CD45+EPCs in patients with CHB presented a distinct gene expression profile compared with CD45-EPCs and CD45+EPCs from cord blood. Notably, CD45+EPCs from patients with CHB expressed high level of Lymphocyte-activation gene 3 (LAG3), an immune checkpoint molecule, and were then defined as LAG3+EPCs. LAG3+EPCs diminished the function of antigen presenting cells through LAG3, which was another mechanism by which LAG3+EPCs' suppressed HBV-specific CD8+T cells. Anti-LAG3 and anti-TGF-ß combination treatment decreased serum HBeAg, HBV DNA levels and HBsAg level, as well as HBsAg-expression in hepatocytes during PEG-IFN treatment in the AAV/HBV mice model. Conclusions: LAG3+EPCs inhibited the efficacy of PEG-IFN treatment on HBsAg seroclearance induced by LAG3 and TGF-ß. Anti-LAG3, anti-TGF-ß and PEG-IFN combination treatment might facilitate HBV clearance.

Customizable, reconfigurable, and anatomically coordinated large-area, high-density electromyography from drawn-on-skin electrode arrays.

Accurate anatomical matching for patient-specific electromyographic (EMG) mapping is crucial yet technically challenging in various medical disciplines. The fixed electrode construction of multielectrode arrays (MEAs) makes it nearly impossible to match an individual's unique muscle anatomy. This mismatch between the MEAs and target muscles leads to missing relevant muscle activity, highly redundant data, complicated electrode placement optimization, and inaccuracies in classification algorithms. Here, we present customizable and reconfigurable drawn-on-skin (DoS) MEAs as the first demonstration of high-density EMG mapping from in situ-fabricated electrodes with tunable configurations adapted to subject-specific muscle anatomy. The DoS MEAs show uniform electrical properties and can map EMG activity with high fidelity under skin deformation-induced motion, which stems from the unique and robust skin-electrode interface. They can be used to localize innervation zones (IZs), detect motor unit propagation, and capture EMG signals with consistent quality during large muscle movements. Reconfiguring the electrode arrangement of DoS MEAs to match and extend the coverage of the forearm flexors enables localization of the muscle activity and prevents missed information such as IZs. In addition, DoS MEAs customized to the specific anatomy of subjects produce highly informative data, leading to accurate finger gesture detection and prosthetic control compared with conventional technology.

Drawn-on-Skin Sensors from Fully Biocompatible Inks toward High-Quality Electrophysiology.

The need to develop wearable devices for personal health monitoring, diagnostics, and therapy has inspired the production of innovative on-demand, customizable technologies. Several of these technologies enable printing of raw electronic materials directly onto biological organs and tissues. However, few of them have been thoroughly investigated for biocompatibility of the raw materials on the cellular, tissue, and organ levels or with different cell types. In addition, highly accurate multiday in vivo monitoring using such on-demand, in situ fabricated devices has yet to be done. Presented herein is the first fully biocompatible, on-skin fabricated electronics for multiple cell types and tissues that can capture electrophysiological signals with high fidelity. While also demonstrating improved mechanical and electrical properties, the drawn-on-skin ink retains its properties under various writing conditions, which minimizes the variation in electrical performance. Furthermore, the drawn-on-skin ink shows excellent biocompatibility with cardiomyocytes, neurons, mice skin tissue, and human skin. The high signal-to-noise ratios of the electrophysiological signals recorded with the DoS sensor over multiple days demonstrate its potential for personalized, long-term, and accurate electrophysiological health monitoring.

Challenges and opportunities in producing high-quality edible mushrooms from lignocellulosic biomass in a small scale.

Mushrooms are high-value products that can be produced from lignocellulosic biomass. Mushrooms are the fruiting body of fungi and are domestically cultivated using lignocellulosic biomass obtained from agricultural byproducts and woody biomass. A handful of edible mushroom species are commercially cultivated at small, medium, and large scales for culinary and medicinal use. Details about different lignocellulosic biomass and their composition that are commonly used to produce mushrooms are outlined in this review. In addition, discussions on four major processing steps (i) producing solid and liquid spawn, (ii) conventional and mechanized processing lignocellulosic biomass substrates to produce mushroom beds, (iii) maintaining growth conditions in climate-controlled rooms, and (iv) energy requirements and managements to produce mushrooms are also provided. The new processing methods and technology outlined in this review may allow mushrooms to be economically and sustainably produced at a small scale to satisfy the growing food needs and create rural jobs. KEY POINTS: • Some of the challenges faced by small-scale mushroom growers are presented. This review is expected to stimulate more research to address the challenges.

A real-time optimization method for economic and effective operation of electrostatic precipitators.

Electrostatic precipitators (ESP) have been considered as the main particulate matter (PM) removal facility in the energy industry. This paper presents a real-time optimization method for a one-chamber industrial ESP in an ultra-low emission power plant with an intelligent optimization system (IOS). The IOS seeks to optimize the energy consumption of ESP subject to the outlet concentration requirement in real-time. A coordination control logic is designed to regulate the optimized operation set points with varying operation conditions. The operation optimized by the IOS is compared with the operations under PID (proportion-integral-derivative) and manual control. The results show that the IOS improves the emission compliance rate from 95% of manual control to 100% and the medium concentration is tuned to be 46.6% closer to the emission target. Furthermore, a good balance between emission and energy consumption is achieved, with 35.50% energy conservation for the same emission upper limit of 30 mg/m3. These results prove that the IOS significantly contributes to the efficient operation and economic PM removal by ESP for the energy industry. IMPLICATIONS: Electrostatic precipitators (ESP) is one of the main PM removal facilities in coal-fired power plants. An intelligent optimization system (IOS) with prediction, optimization, and control modules is designed and constructed for the ESP in an ultra-low emission power plant. A PM removal model is used to predict the outlet concentration of the ESP. The optimal energy consumption of ESP subject to the outlet concentration requirement problem is solved by the particle swarm optimization. A closed-loop and rapping tolerant method is used to eliminate the fluctuation in time-averaged concentration. The system raised is able to ensure the compliance rate while decreasing the energy consumption of the ESP.

Dynamic Hand Gesture Recognition Based on a Leap Motion Controller and Two-Layer Bidirectional Recurrent Neural Network.

Dynamic hand gesture recognition is one of the most significant tools for human-computer interaction. In order to improve the accuracy of the dynamic hand gesture recognition, in this paper, a two-layer Bidirectional Recurrent Neural Network for the recognition of dynamic hand gestures from a Leap Motion Controller (LMC) is proposed. In addition, based on LMC, an efficient way to capture the dynamic hand gestures is identified. Dynamic hand gestures are represented by sets of feature vectors from the LMC. The proposed system has been tested on the American Sign Language (ASL) datasets with 360 samples and 480 samples, and the Handicraft-Gesture dataset, respectively. On the ASL dataset with 360 samples, the system achieves accuracies of 100% and 96.3% on the training and testing sets. On the ASL dataset with 480 samples, the system achieves accuracies of 100% and 95.2%. On the Handicraft-Gesture dataset, the system achieves accuracies of 100% and 96.7%. In addition, 5-fold, 10-fold, and Leave-One-Out cross-validation are performed on these datasets. The accuracies are 93.33%, 94.1%, and 98.33% (360 samples), 93.75%, 93.5%, and 98.13% (480 samples), and 88.66%, 90%, and 92% on ASL and Handicraft-Gesture datasets, respectively. The developed system demonstrates similar or better performance compared to other approaches in the literature.

A signal amplification system on a lateral flow immunoassay detecting for hepatitis e-antigen in human blood samples.

Hepatitis B e-antigen (HBeAg) is the secretory form of the nucleocapsid of the hepatitis B virus (HBV), which is a marker of viral replication. In this study, a novel signal amplification system (SAS) based on the lateral flow immunoassay (LFIA) was used for rapid detection of HBeAg in blood samples from patients or blood donors. In this assay, the detection antibody was conjugated with gold nanoparticles (GNPs), and the capture antibody was labeled with biotin. The presence of targeting antigen HBeAg in blood sample would act as a bridge with biotinylated captured antibody and GNP-conjugated detection antibody to form the dendritic nanoparticle complex. The dendritic complexes in the sample solution were migrated and immobilized on the testing line of strip coated with antibiotin antibodies. Signal intensity was massively amplified by the SAS, which was positively correlated with the concentration of targeting antigen in the blood sample and was assessed by eyes or strip scanner. The SAS worked only when targeting antigens were present in the sample. By using this SAS-LFIA, we were able to detect a very low concentration of HBeAg (9 ng/mL), which was 27-fold sensitive than that by conventional LFIA (cLFIA). A number of 420 blood samples were detested by this novel SAS-LFIA, the results were in accordance with those of enzyme-linked immunosorbent assay (ELISA) completely, while the cLFIA missed an HBeAg-positive sample. In conclusion, the novel SAS has high specificity and sensitivity, which can be used to replace the conventional rapid test and ELISA in clinical diagnosis.

The Role of Haptic Feedback in Robotic-Assisted Retinal Microsurgery Systems: A Systematic Review.

Retinal microsurgery is one of the most technically difficult surgeries since it is performed at the threshold of human capability. If certain retinal conditions are left untreated, they can lead to severe damage, including irreversible blindness. Thus, techniques for reliable retinal microsurgery operations are critical. Recent research shows promise for improving surgical safety by implementing various types of sensory input and output. Sensory information is used to inform the surgeon about the environment inside the eye in real time. This review examines literature that discusses human factors and ergonomics (HFE) of sensory inputs and outputs of retinal microsurgery instrumentation with a focus on force and haptic feedback. Thirty-four studies were reviewed on the following topics: (1) variation between different input sensory devices and their performance, (2) variation between alternative output sensory devices and their performance, and (3) variation between alternative output sensory devices and their user satisfaction. This review finds that the implementation of HFE is important for the consideration of retinal microsurgery devices, but it is largely missing from current research. The addition of direct comparisons between devices, measures of user acceptance, usability evaluations, and greater realism in testing would help advance the use of haptic sensory feedback for retinal microsurgery instruments.