Abstract
Predicting mechanical properties such as yield strength (YS) and ultimate tensile strength (UTS) is an intricate undertaking in practice, notwithstanding a plethora of well-established ...theoretical and empirical models. A data-driven approach should be a fundamental exercise when making YS/UTS predictions. For this study, we collected 16 descriptors (attributes) that implicate the compositional and processing information and the corresponding YS/UTS values for 5473 thermo-mechanically controlled processed (TMCP) steel alloys. We set up an integrated machine-learning (ML) platform consisting of 16 ML algorithms to predict the YS/UTS based on the descriptors. The integrated ML platform involved regularization-based linear regression algorithms, ensemble ML algorithms, and some non-linear ML algorithms. Despite the dirty nature of most real-world industry data, we obtained acceptable holdout dataset test results such as R
2
> 0.6 and MSE < 0.01 for seven non-linear ML algorithms. The seven fully trained non-linear ML models were used for the ensuing ‘inverse design (prediction)’ based on an elitist-reinforced, non-dominated sorting genetic algorithm (NSGA-II). The NSGA-II enabled us to predict solutions that exhibit desirable YS/UTS values for each ML algorithm. In addition, the NSGA-II-driven solutions in the 16-dimensional input feature space were visualized using holographic research strategy (HRS) in order to systematically compare and analyze the inverse-predicted solutions for each ML algorithm.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Influenza viruses (IVs) have become increasingly resistant to antiviral drugs that target neuraminidase and matrix protein 2 due to gene mutations that alter their drug-binding target protein ...regions. Consequently, almost all recent IV pandemics have exhibited resistance to commercial antiviral vaccines. To overcome this challenge, an antiviral target is needed that is effective regardless of genetic mutations.
In particular, hemagglutinin (HA), a highly conserved surface protein across many IV strains, could be an effective antiviral target as it mediates binding of IVs with host cell receptors, which is crucial for membrane fusion. HA has 6 disulfide bonds that can easily bind with the surfaces of gold nanoparticles. Herein, we fabricated porous gold nanoparticles (PoGNPs) via a surfactant-free emulsion method that exhibited strong affinity for disulfide bonds due to gold-thiol interactions, and provided extensive surface area for these interactions. A remarkable decrease in viral infectivity was demonstrated by increased cell viability results after exposing MDCK cells to various IV strains (H1N1, H3N2, and H9N2) treated with PoGNP. Most of all, the viability of MDCK cells infected with all IV strains increased to 96.8% after PoGNP treatment of the viruses compared to 33.9% cell viability with non-treated viruses. Intracellular viral RNA quantification by real-time RT-PCR also confirmed that PoGNP successfully inhibited viral membrane fusion by blocking the viral entry process through conformational deformation of HA.
We believe that the technique described herein can be further developed for PoGNP-utilized antiviral protection as well as metal nanoparticle-based therapy to treat viral infection. Additionally, facile detection of IAV can be achieved by developing PoGNP as a multiplatform for detection of the virus.
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Patient-derived organoids (PDO) of lung cancer has been recently introduced, reflecting the genomic landscape of lung cancer. However, clinical relevance of advanced lung adenocarcinoma organoids ...remains unknown. Here, we examined the ability of PDOs to predict clinical responses to targeted therapies in individual patients and to identify effective anticancer therapies for novel molecular targets.
Eighty-four organoids were established from patients with advanced lung adenocarcinoma. Formalin-fixed, paraffin-embedded tumor specimens from corresponding patients were analyzed by whole-exome sequencing (
= 12). Organoids were analyzed by whole-exome sequencing (
= 61) and RNA sequencing (
= 55). Responses to mono or combination targeted therapies were examined in organoids and organoid-derived xenografts.
PDOs largely retained somatic alterations including driver mutations of matching patient tumors. PDOs were able to recapitulate progression-free survival and objective responses of patients with non-small cell lung cancer receiving clinically approved tyrosine kinase inhibitors. PDOs recapitulated activity of therapeutic strategies under clinical investigation. YUO-071 harboring an
exon 19 deletion and a
G464A mutation and the matching patient responded to dabrafenib/trametinib combination therapy. YUO-004 and YUO-050 harboring an
L747P mutation was sensitive to afatinib, consistent with the response in the matching patient of YUO-050. Furthermore, we utilized organoids to identify effective therapies for novel molecular targets by demonstrating the efficacy of poziotinib against
exon 20 insertions and pralsetinib against
fusions.
We demonstrated translational relevance of PDOs in advanced lung adenocarcinoma. PDOs are an important diagnostic tool, which can assist clinical decision making and accelerate development of therapeutic strategies.
While the coronavirus disease (COVID‐19) accounts for the current global pandemic, the emergence of other unknown pathogens, named “Disease X,” remains a serious concern in the future. Emerging or ...re‐emerging pathogens continue to pose significant challenges to global public health. In response, the scientific community has been urged to create advanced platform technologies to meet the ever‐increasing needs presented by these devastating diseases with pandemic potential. This review aims to bring new insights to allow for the application of advanced nanomaterials in future diagnostics, vaccines, and antiviral therapies, thereby addressing the challenges associated with the current preparedness strategies in clinical settings against viruses. The application of nanomaterials has advanced medicine and provided cutting‐edge solutions for unmet needs. Herein, an overview of the currently available nanotechnologies is presented, highlighting the significant features that enable them to control infectious diseases, and identifying the challenges that remain to be addressed for the commercial production of nano‐based products is presented. Finally, to conclude, the development of a nanomaterial‐based system using a “One Health” approach is suggested. This strategy would require a transdisciplinary collaboration and communication between all stakeholders throughout the entire process spanning across research and development, as well as the preclinical, clinical, and manufacturing phases.
Nanomaterials have a significant potential for creating sophisticated complexes, mimicking the natural size and structures of viruses without the complications of toxicity. New approaches for applying advanced nanomaterial‐based platform technologies to future diagnostics, vaccines, and antiviral treatments against emerging infectious diseases are reviewed. The unmet needs and future directions of current nanomaterial‐based tools in the clinical settings are also addressed.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
In the domain of modern manufacturing, computer numerical control (CNC) milling machines have emerged as instrumental assets. However, the data they generate is of vast amount, but usually contains ...redundancies and displays consistent patterns, making it inefficient for deep learning training. This paper proposes a novel sampling algorithm tailored for CNC milling machine data, emphasizing both diversity and efficiency. The proposed method leverages the entropy concept from the information‐theoretic perspective to evaluate and enhance data diversity, aiming to achieve efficient learning with high accuracy. This in turn enables to not only facilitates a deeper understanding of CNC data characteristics but also contributes significantly to the optimization of deep learning training processes in the context of CNC milling data.
This paper proposes a novel sampling algorithm tailored for computer numerical control milling machine data, emphasizing both diversity and efficiency. The proposed method leverages the entropy concept from the information‐theoretic perspective to evaluate and enhance data diversity, aiming to achieve efficient learning with high accuracy.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
A recurrent pandemic with unpredictable viral nature has implied the need for a rapid diagnostic technology to facilitate timely and appropriate countermeasures against viral infections. In this ...study, conductive polymer-based nanoparticles have been developed as a tool for rapid diagnosis of influenza A (H1N1) virus. The distinctive property of a conductive polymer that transduces stimulus to respond, enabled immediate optical signal processing for the specific recognition of H1N1 virus. Conductive poly(aniline-co-pyrrole)-encapsulated polymeric vesicles, functionalized with peptides, were fabricated for the specific recognition of H1N1 virus. The low solubility of conductive polymers was successfully improved by employing vesicles consisting of amphiphilic copolymers, facilitating the viral titer-dependent production of the optical response. The optical response of the detection system to the binding event with H1N1, a mechanical stimulation, was extensively analyzed and provided concordant information on viral titers of H1N1 virus in 15 min. The specificity toward the H1N1 virus was experimentally demonstrated via a negative optical response against the control group, H3N2. Therefore, the designed system that transduces the optical response to the target-specific binding can be a rapid tool for the diagnosis of H1N1.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Accurate diagnosis of Alzheimer's disease (AD) in its earliest stage can prevent the disease and delay the symptoms. Therefore, more sensitive, non-invasive, and simple screening tools are required ...for the early diagnosis and monitoring of AD. Here, we design a self-assembled nanoparticle-mediated amplified fluorogenic immunoassay (SNAFIA) consisting of magnetic and fluorophore-loaded polymeric nanoparticles. Using a discovery cohort of 21 subjects, proteomic analysis identifies adenylyl cyclase-associated protein 1 (CAP1) as a potential tear biomarker. The SNAFIA demonstrates a low detection limit (236 aM), good reliability (R
= 0.991), and a wide analytical range (0.320-1000 fM) for CAP1 in tear fluid. Crucially, in the verification phase with 39 subjects, SNAFIA discriminates AD patients from healthy controls with 90% sensitivity and 100% specificity in under an hour. Utilizing tear fluid as a liquid biopsy, SNAFIA could potentially aid in long-term care planning, improve clinical trial efficiency, and accelerate therapeutic development for AD.
Non-alcoholic fatty liver disease (NAFLD) refers to a range of conditions in which excess lipids accumulate in the liver, possibly leading to serious hepatic manifestations such as steatohepatitis, ...fibrosis/cirrhosis and cancer. Despite its increasing prevalence and significant impact on liver disease-associated mortality worldwide, no medication has been approved for the treatment of NAFLD yet. Liver X receptors α/β (LXRα and LXRβ) are lipid-activated nuclear receptors that serve as master regulators of lipid homeostasis and play pivotal roles in controlling various metabolic processes, including lipid metabolism, inflammation and immune response. Of note, NAFLD progression is characterized by increased accumulation of triglycerides and cholesterol, hepatic de novo lipogenesis, mitochondrial dysfunction and augmented inflammation, all of which are highly attributed to dysregulated LXR signaling. Thus, targeting LXRs may provide promising strategies for the treatment of NAFLD. However, emerging evidence has revealed that modulating the activity of LXRs has various metabolic consequences, as the main functions of LXRs can distinctively vary in a cell type-dependent manner. Therefore, understanding how LXRs in the liver integrate various signaling pathways and regulate metabolic homeostasis from a cellular perspective using recent advances in research may provide new insights into therapeutic strategies for NAFLD and associated metabolic diseases.
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Class Activation Mapping (CAM) is a powerful technique used to understand the decision making of Convolutional Neural Network (CNN) in computer vision. Recently, there have been attempts not only to ...generate better visual explanations, but also to improve classification performance using visual explanations. However, previous works still have their own drawbacks. In this paper, we propose a novel architecture, LFI-CAM *** (Learning Feature Importance Class Activation Mapping), which is trainable for image classification and visual explanation in an end-to-end manner. LFI-CAM generates attention map for visual explanation during forward propagation, and simultaneously uses attention map to improve classification performance through the attention mechanism. Feature Importance Network (FIN) focuses on learning the feature importance instead of directly learning the attention map to obtain a more reliable and consistent attention map. We confirmed that LFI-CAM is optimized not only by learning the feature importance but also by enhancing the backbone feature representation to focus more on important features of the input image. Experiments show that LFI-CAM outperforms baseline models' accuracy on classification tasks as well as significantly improves on previous works in terms of attention map quality and stability over different hyper-parameters.
Abstract
There is still an unmet need for development of safer antimelanogenic or melanin-degrading agents for skin hyperpigmentation, induced by intrinsic or extrinsic factors including aging or ...ultraviolet irradiation. Owing to the relatively low cytotoxicity compared with other chemical materials, several studies have explored the role of 2'-fucosyllactose (2'-FL), the most dominant component of human milk oligosaccharides. Here, we showed that 2'-FL reduced melanin levels in both melanocytic cells and a human skin equivalent three-dimensional in vitro model. Regarding the cellular and molecular mechanism, 2'-FL induced LC3I conversion into LC3II, an autophagy activation marker, followed by the formation of LC3II
+
/PMEL
+
autophagosomes. Comparative transcriptome analysis provided a comprehensive understanding for the up- and downstream cellular processes and signaling pathways of the AMPK–ULK1 signaling axis triggered by 2'-FL treatment. Moreover, 2'-FL activated the phosphorylation of AMPK at Thr172 and of ULK1 at Ser555, which were readily reversed in the presence of dorsomorphin, a specific AMPK inhibitor, with consequent reduction of the 2'-FL-mediated hypopigmentation. Taken together, these findings demonstrate that 2'-FL promotes melanin degradation by inducing autophagy through the AMPK–ULK1 axis. Hence, 2'-FL may represent a new natural melanin-degrading agent for hyperpigmentation.
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