In the present study, the simulated coarse-grained heat-affected zones (CGHAZs) of X90 pipeline steel were produced using a Gleeble 3500 simulator under different heat inputs (HIs) varying from 10 to ...50 kJ/cm to study the effect of HI on grain boundary evolution and toughness properties in CGHAZ of X90 pipeline steel. The experimental results show that the microstructure and grain boundary is significantly influenced by different HIs. All the studied specimens have baintic dominant microstructure that composed of lath bainite (LB), granular bainite (GB) and M/A (martensite/austenite) constituents. The fraction of LB decreased with increasing of HIs, and the fraction of GB increased. The excellent combination of GB and LB obtained at an HI of 25 kJ/cm, resulting the highest impact absorbed energy, is 267 J. The impact toughness decreased sharply when HI increase from 25 kJ/cm to 30 kJ/cm, the impact toughness decreased to 18 J when the HI is larger than 30 kJ/cm. The number of HAGBs increased first and then decreased with increasing of HIs. However, for low energy coincidence lattice grain boundaries (low-ΣCSLs), the Σ3, Σ11, Σ25b boundaries decreased with increasing of HIs. Low fraction of M/A constituents are not the direct reason for the reduction of impact toughness in the simulated CGHAZs of the studied steel.
One promising application of photonics to astronomical instrumentation is the miniaturization of near-infrared (NIR) spectrometers for large ground- and space-based astronomical telescopes. Here we ...present new results from our effort to fabricate arrayed waveguide grating (AWG) spectrometers for astronomical applications entirely in-house. Our latest devices have a peak overall of ∼23%, a spectral resolving power (λ/δλ) of ~1300, and cover the entire H band (1450-1650 nm) for Transverse Electric (TE) polarization. These AWGs use a silica-on-silicon platform with a very thin layer of Si
N
as the core of the waveguides. They have a free spectral range of ~10 nm at a of ~1600 about wavelength nm and a contrast ratio or crosstalk of 2% (-17 dB). Various practical aspects of implementing AWGs as astronomical spectrographs are discussed, including the coupling of the light between the fibers and AWGs, high-temperature annealing to improve the throughput of the devices at ~1500 nm, cleaving at the output focal plane of the AWG to provide continuous wavelength coverage, and a novel algorithm to make the devices polarization insensitive over a broad band. These milestones will guide the development of the next generation of AWGs with wider free spectral range and higher resolving power and throughput.
Abstract Chirality is one of the most fascinating and ubiquitous cues in nature, especially in life. The effects of chiral surfaces on stem cells have, however, not yet been revealed. Herein we ...examined the molecular chirality effect on stem cell behaviors. Self assembly monolayers of l - or d -cysteine (Cys) were formed on a glass surface coated with gold. Mesenchymal stem cells (MSCs) derived from bone marrow of rats exhibited more adhering preference and thus less cell spreading on the l surface than on the d one at the confluent condition. More protein adsorption was observed on the l surface after immersed in cell culture medium with fetal bovine serum. After osteogenic and adipogenic co-induction at the confluent condition, a larger proportion of cells became osteoblasts on the d surface, while the adipogenic fraction on the l surface was found to be higher than on the d surface. In order to interpret how this chirality effect worked, we fabricated Cys microislands of two sizes on the non-fouling poly(ethylene glycol) hydrogel to pre-define the spreading areas of single cells. Then the differentiation extents did not exhibit a significant difference between l and d surfaces under a given area of microislands, yet very significant differences of osteogenesis and adipogenesis were found between different areas. So, the molecular chirality influenced stem cells, probably via favored adsorption of natural proteins on the l surface, which led to more cell adhesion; and the larger cell spreading area with higher cell tension in turn favored osteogenesis rather than adipogenesis. As a result, this study reveals the molecular chirality on material surfaces as an indirect regulator of stem cells.
Neural mechanisms underlying semantic processing have been extensively studied by using functional magnetic resonance imaging, nevertheless, the individual differences of it are yet to be unveiled. ...To further our understanding of functional and anatomical brain organization underlying semantic processing to the level of individual humans, we used out-of-scanner language behavioral data, T1, resting-state, and story comprehension task-evoked functional image data in the Human Connectome Project, to investigate individual variability in the task-evoked semantic processing network, and attempted to predict individuals' language skills based on task and intrinsic functional connectivity of highly variable regions, by employing a machine-learning framework. Our findings first confirmed that individual variability in both functional and anatomical markers were heterogeneously distributed throughout the semantic processing network, and that the variability increased towards higher levels in the processing hierarchy. Furthermore, intrinsic functional connectivities among these highly variable regions were found to contribute to predict individual reading decoding abilities. The contributing nodes in the overall network were distributed in the left superior, inferior frontal, and temporo-parietal cortices. Our results suggested that the individual differences of neurobiological markers were heterogeneously distributed in the semantic processing network, and that neurobiological markers of highly variable areas are not only linked to individual variability in language skills, but can predict language skills at the individual level.
In the context of contemporary urbanization, the significance of diversifying urban public facilities has attracted significant attention. This study examines the relationship between road network ...and the diversity of urban public facilities in Changsha City. These factors are measured through the Shannon-Weiner Index and Space Syntax method. To provide greater specificity, the study employs Random Forest and Geographically Weighted Regression models to analyze the relationship between road networks and the diversity of urban public facilities. The results identify a nonlinear relationship between these variables. In addition, high accessibility exhibits a stronger association with diversity than accessibility alone, and this correlation is reflected in varying degrees of inconsistency across different study areas. Finally, the cartographic depiction of diversity clusters is overlaid on the road network, demonstrating a significant relationship between the configuration of the road network and diversity patterns. In conclusion, this research emphasizes the robust correlation between the roadway network and the diversity of urban public facilities. It prompts local governments to focus beyond mere equality, with a greater commitment to enhancing the quality of life for residents through diversity.
Every year, hundreds of new compounds are discovered from the metabolites of marine organisms. Finding new and useful compounds is one of the crucial drivers for this field of research. Here we ...describe the statistics of bioactive compounds discovered from marine organisms from 1985 to 2012. This work is based on our database, which contains information on more than 15,000 chemical substances including 4196 bioactive marine natural products. We performed a comprehensive statistical analysis to understand the characteristics of the novel bioactive compounds and detail temporal trends, chemical structures, species distribution, and research progress. We hope this meta-analysis will provide useful information for research into the bioactivity of marine natural products and drug development.
This study investigated sex-specific pathogenesis mechanisms in Alzheimer's disease (AD) using single-nucleus RNA sequencing (snRNA-seq) data.
Data from the Gene Expression Omnibus (GEO) were ...searched using terms “Alzheimer's Disease”, “single cell”, and “Homo sapiens”. Studies excluding APOE E4 and including comprehensive gender information with 10× sequencing methods were selected, resulting in GSE157827 and GSE174367 datasets from human prefrontal cortex samples. Sex-stratified analyses were conducted on these datasets, and the outcomes of the analysis for GSE157827 were compared with those of GSE174367. The findings were validated using expression profiling from the mouse dataset GSE85162. Furthermore, real-time PCR experiments in mice further confirmed these findings. The Seurat R package was used to identify cell types, and batch effects were mitigated using the Harmony R package. Cell proportions by sex were compared using the Mann-Whitney-Wilcoxon test, and gene expression variability was displayed with an empirical cumulative distribution plot. Differentially expressed genes were identified using the FindMarkers function with the MAST test. Transcription factors were analyzed using the RcisTarget R package.
Seven cell types were identified: astrocytes, endothelial cells, excitatory neurons, inhibitory neurons, microglia, oligodendrocytes, and oligodendrocyte progenitor cells. Additionally, five distinct subpopulations of both endothelial and microglial cells were also identified, respectively. Key findings included: (1) In endothelial cells, genes involved in synapse organization, such as Insulin Like Growth Factor 1 Receptor (IGF1R) and Fms Related Receptor Tyrosine Kinase 1(FLT1), showed higher expression in females with AD. (2) In microglial cells, genes in the ribosome pathway exhibited higher expression in males without AD compared to females (with or without AD) and males with AD. (3) Chromodomain Helicase DNA Binding Protein 2 (CHD2) negatively regulated gene expression in the ribosome pathway in male microglia, suppressing AD, this finding was further validated in mice. (4) Differences between Asians and Caucasians were observed based on sex and disease status stratification.
IGF1R and FLT1 in endothelial cells contribute to AD in females, while CHD2 negatively regulates ribosome pathway gene expression in male microglia, suppressing AD in humans and mice.
•IGF1R and FLT1 in female endothelial cells exacerbate Alzheimer's disease.•CHD2 in male microglia suppresses Alzheimer's disease by regulating ribosome genes.
Machine learning (ML) has emerged as an indispensable methodology to describe, discover, and predict complex physical phenomena that efficiently help us learn underlying functional rules, especially ...in cases when conventional modeling approaches cannot be applied. While conventional feedforward neural networks are typically limited to performing tasks related to static patterns in data, recursive models can both work iteratively based on a changing input and discover complex dynamical relationships in the data. Deep language models can model flexible modalities of data and are capable of learning rich dynamical behaviors as they operate on discrete or continuous symbols that define the states of a physical system, yielding great potential toward end-to-end predictions. Similar to how words form a sentence, materials can be considered as a self-assembly of physically interacted building blocks, where the emerging functions of materials are analogous to the meaning of sentences. While discovering the fundamental relationships between building blocks and function emergence can be challenging, language models, such as recurrent neural networks and long-short term memory networks, and, in particular, attention models, such as the transformer architecture, can solve many such complex problems. Application areas of such models include protein folding, molecular property prediction, prediction of material failure of complex nonlinear architected materials, and also generative strategies for materials discovery. We outline challenges and opportunities, especially focusing on extending the deep-rooted kinship of humans with symbolism toward generalizable artificial intelligence (AI) systems using neuro-symbolic AI, and outline how tools such as ChatGPT and DALL·E can drive materials discovery.
Dengue virus (DENV) is the most common mosquito-borne virus infecting humans and is currently a serious global health challenge. To establish infection in its host cells, DENV must subvert the ...production and/or antiviral effects of interferon (IFN). The aim of this study was to understand the mechanisms by which DENV suppresses IFN production. We determined that DENV NS4A interacts with mitochondrial antiviral signaling protein (MAVS), which was previously found to activate NF-κB and IFN regulatory factor 3 (IRF3), thus inducing type I IFN in the mitochondrion-associated endoplasmic reticulum membranes (MAMs). We further demonstrated that NS4A is associated with the N-terminal CARD-like (CL) domain and the C-terminal transmembrane (TM) domain of MAVS. This association prevented the binding of MAVS to RIG-I, resulting in the repression of RIG-I-induced IRF3 activation and, consequently, the abrogation of IFN production. Collectively, our findings illustrate a new molecular mechanism by which DENV evades the host immune system and suggest new targets for anti-DENV strategies.
Type I interferon (IFN) constitutes the first line of host defense against invading viruses. To successfully establish infection, dengue virus (DENV) must counteract either the production or the function of IFN. The mechanism by which DENV suppresses IFN production is poorly understood and characterized. In this study, we demonstrate that the DENV NS4A protein plays an important role in suppressing interferon production through binding MAVS and disrupting the RIG-I-MAVS interaction in mitochondrion-associated endoplasmic reticulum membranes (MAMs). Our study reveals that MAVS is a novel host target of NS4A and provides a molecular mechanism for DENV evasion of the host innate immune response. These findings have important implications for understanding the pathogenesis of DENV and may provide new insights into using NS4A as a therapeutic and/or prevention target.
Due to image quality limitations, online Megavoltage cone beam CT (MV CBCT), which represents real online patient anatomy, cannot be used to perform adaptive radiotherapy (ART). In this study, we ...used a deep learning method, the cycle-consistent adversarial network (CycleGAN), to improve the MV CBCT image quality and Hounsfield-unit (HU) accuracy for rectal cancer patients to make the generated synthetic CT (sCT) eligible for ART. Forty rectal cancer patients treated with the intensity modulated radiotherapy (IMRT) were involved in this study. The CT and MV CBCT images of 30 patients were used for model training, and the images of the remaining 10 patients were used for evaluation. Image quality, autosegmentation capability and dose calculation capability using the autoplanning technique of the generated sCT were evaluated. The mean absolute error (MAE) was reduced from 135.84 ± 41.59 HU for the CT and CBCT comparison to 52.99 ± 12.09 HU for the CT and sCT comparison. The structural similarity (SSIM) index for the CT and sCT comparison was 0.81 ± 0.03, which is a great improvement over the 0.44 ± 0.07 for the CT and CBCT comparison. The autosegmentation model performance on sCT for femoral heads was accurate and required almost no manual modification. For the CTV and bladder, although modification was needed for autocontouring, the Dice similarity coefficient (DSC) indices were high, at 0.93 and 0.94 for the CTV and bladder, respectively. For dose evaluation, the sCT-based plan has a much smaller dose deviation from the CT-based plan than that of the CBCT-based plan. The proposed method solved a key problem for rectal cancer ART realization based on MV CBCT. The generated sCT enables ART based on the actual patient anatomy at the treatment position.
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