Image-based deep learning model using DNA methylation data predicts the origin of cancer of unknown primary.

Cancer of unknown primary (CUP) is a rare type of metastatic cancer in which the origin of the tumor is unknown. Since the treatment strategy for patients with metastatic tumors depends on knowing the primary site, accurate identification of the origin site is important. Here, we developed an image-based deep-learning model that utilizes a vision transformer algorithm for predicting the origin of CUP. Using DNA methylation dataset of 8,233 primary tumors from The Cancer Genome Atlas (TCGA), we categorized 29 cancer types into 18 organ classes and extracted 2,312 differentially methylated CpG sites (DMCs) from non-squamous cancer group and 420 DMCs from squamous cell cancer group. Using these DMCs, we created organ-specific DNA methylation images and used them for model training and testing. Model performance was evaluated using 394 metastatic cancer samples from TCGA (TCGA-meta) and 995 samples (693 primary and 302 metastatic cancers) obtained from 20 independent external studies. We identified that the DNA methylation image reveals a distinct pattern based on the origin of cancer. Our model achieved an overall accuracy of 96.95 % in the TCGA-meta dataset. In the external validation datasets, our classifier achieved overall accuracies of 96.39 % and 94.37 % in primary and metastatic tumors, respectively. Especially, the overall accuracies for both primary and metastatic samples of non-squamous cell cancer were exceptionally high, with 96.79 % and 96.85 %, respectively.

Central neurocytoma exhibits radial glial cell signatures with FGFR3 hypomethylation and overexpression.

We explored the genomic events underlying central neurocytoma (CN), a rare neoplasm of the central nervous system, via multiomics approaches, including whole-exome sequencing, bulk and single-nuclei RNA sequencing, and methylation sequencing. We identified FGFR3 hypomethylation leading to FGFR3 overexpression as a major event in the ontogeny of CN that affects crucial downstream events, such as aberrant PI3K-AKT activity and neuronal development pathways. Furthermore, we found similarities between CN and radial glial cells based on analyses of gene markers and CN tumor cells and postulate that CN tumorigenesis is due to dysregulation of radial glial cell differentiation into neurons. Our data demonstrate the potential role of FGFR3 as one of the leading drivers of tumorigenesis in CN.

Rational design of hybrid sensor arrays combined synergistically with machine learning for rapid response to a hazardous gas leak environment in chemical plants.

Combinations of semiconductor metal oxide (SMO) sensors, electrochemical (EC) sensors, and photoionization detection (PID) sensors were used to discriminate chemical hazards on the basis of machine learning. Sensing data inputs were exploited in the form of either numerical or image data formats, and the classification of chemical hazards with high accuracy was achieved in both cases. Even a small amount of gas sensing or purging data (input for ∼30 s) input can be exploited in machine-learning-based gas discrimination. SMO sensors exhibit high performance even in a single-sensor mode, presumably because of the intrinsic cross-sensitivity of metal oxides, which is otherwise considered a major disadvantage of SMO sensors. EC sensors were enhanced through synergistic integration of sensor combinations with machine learning. For precision detection of multiple target analytes, a minimum number of sensors can be proposed for gas detection/discrimination by combining sensors with dissimilar operating principles. The Type I hybrid sensor combines one SMO sensor, one EC sensor, and one PID sensor and is used to identify NH3 gas mixed with sulfur compounds in simulations of NH3 gas leak accidents in chemical plants. The portable remote sensing module made with a Type I hybrid sensor and LTE module can identify mixed NH3 gas with a detection time of 60 s, demonstrating the potential of the proposed system to quickly respond to hazardous gas leak accidents and prevent additional damage to the environment.

Synergistic Integration of Machine Learning with Microstructure/Composition-Designed SnO2 and WO3 Breath Sensors.

A high-performance semiconductor metal oxide gas sensing strategy is proposed for efficient sensor-based disease prediction by integrating a machine learning methodology with complementary sensor arrays composed of SnO2- and WO3-based sensors. The six sensors, including SnO2- and WO3-based sensors and neural network algorithms, were used to measure gas mixtures. The six constituent sensors were subjected to acetone and hydrogen environments to monitor the effect of diet and/or irritable bowel syndrome (IBS) under the interference of ethanol. The SnO2- and WO3-based sensors suffer from poor discrimination ability if sensors (a single sensor or multiple sensors) within the same group (SnO2- or WO3-based) are separately applied, even when deep learning is applied to enhance the sensing operation. However, hybrid integration is proven to be effective in discerning acetone from hydrogen even in a two-sensor configuration through the synergistic contribution of supervised learning, i.e., neural network approaches involving deep neural networks (DNNs) and convolutional neural networks (CNNs). DNN-based numeric data and CNN-based image data can be exploited for discriminating acetone and hydrogen, with the aim of predicting the status of an exercise-driven diet and IBS. The ramifications of the proposed hybrid sensor combinations and machine learning for the high-performance breath sensor domain are discussed.

Identification of a Complex Karyotype Signature with Clinical Implications in AML and MDS-EB Using Gene Expression Profiling.

Complex karyotype (CK) is associated with a poor prognosis in both acute myeloid leukemia (AML) and myelodysplastic syndrome with excess blasts (MDS-EB). Transcriptomic analyses have improved our understanding of the disease and risk stratification of myeloid neoplasms; however, CK-specific gene expression signatures have been rarely investigated. In this study, we developed and validated a CK-specific gene expression signature. Differential gene expression analysis between the CK and non-CK groups using data from 348 patients with AML and MDS-EB from four cohorts revealed enrichment of the downregulated genes localized on chromosome 5q or 7q, suggesting that haploinsufficiency due to the deletion of these chromosomes possibly underlies CK pathogenesis. We built a robust transcriptional model for CK prediction using LASSO regression for gene subset selection and validated it using the leave-one-out cross-validation method for fitting the logistic regression model. We established a 10-gene CK signature (CKS) predictive of CK with high predictive accuracy (accuracy 94.22%; AUC 0.977). CKS was significantly associated with shorter overall survival in three independent cohorts, and was comparable to that of previously established risk stratification models for AML. Furthermore, we explored of therapeutic targets among the genes comprising CKS and identified the dysregulated expression of superoxide dismutase 1 (SOD1) gene, which is potentially amenable to SOD1 inhibitors.

Molecular characterization of human respiratory syncytial virus in Seoul, South Korea, during 10 consecutive years, 2010-2019.

Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infections and hospitalization in infants and young children. Here, we analyzed the genetic diversity of RSV using partial G gene sequences in 84 RSV-A and 78 RSV- B positive samples collected in Seoul, South Korea, for 10 consecutive years, from 2010 to 2019. Our phylogenetic analysis revealed that RSV-A strains were classified into either the ON1 (80.9%) or NA1 (19.0%) genotypes. On the other hand, RSV-B strains demonstrated diversified clusters within the BA genotype. Notably, some sequences designated as BA-SE, BA-SE1, and BA-DIS did not cluster with previously identified BA genotypes in the phylogenetic trees. Despite this, they did not meet the criteria for the assignment of a new genotype based on recent classification methods. Selection pressure analysis identified three positive selection sites (amino acid positions 273, 274, and 298) in RSV-A, and one possible positive selection site (amino acid position 296) in RSV-B, respectively. The mean evolutionary rates of Korean RSV-A from 1999 to 2019 and RSV-B strains from 1991 and 2019 were estimated at 3.51 × 10-3 nucleotides (nt) substitutions/site/year and 3.32 × 10-3 nt substitutions/site/year, respectively. The population dynamics in the Bayesian skyline plot revealed fluctuations corresponding to the emergence of dominant strains, including a switch of the dominant genotype from NA1 to ON1. Our study on time-scaled cumulative evolutionary analysis contributes to a better understanding of RSV epidemiology at the local level in South Korea.

Antimicrobial activities of Asian plant extracts against pathogenic and spoilage bacteria.

This study was conducted to investigate the antimicrobial effects of 300 Asian plant extracts (PEs) against pathogenic and spoilage bacteria. The antimicrobial activities were examined using agar well or agar disc diffusion, and micro-titer methods. Results revealed that PEs exhibited higher antimicrobial effects against Gram-positive bacteria compared than against Gram-negative bacteria. With few exceptions, PEs delayed the lag time (LT) of pathogenic bacteria (1.17-3.75 times). Among PEs tested, Alchornea trewioides (AT) and Erodium stephanianum (ES) were the most effective in inhibiting pathogenic and spoilage bacteria. In the study evaluating the effect on the growth inhibition in the broth, Acetobacter aceti was inhibited at 2.77 and 3.02 log CFU/mL by the combination treatment of AT+nisin and ES+nisin after storage for 7 days, respectively. Although further investigations are needed to clarify the antimicrobial mechanism of PEs, this study demonstrated that antimicrobial efficacy varied with PE types, solvents, and bacteria. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-022-01182-0.

An integrative approach for exploring the nature of fibroepithelial neoplasms.

BACKGROUND: Malignant phyllodes tumour (MPT) is a rare breast malignancy with epithelial and mesenchymal features. Currently, there are no appropriate research models or effective targeted therapeutic approaches for MPT. METHODS: We collected fresh frozen tissues from nine patients with MPT and performed whole-exome and RNA sequencing. Additionally, we established patient-derived xenograft (PDX) models from patients with MPT and tested the efficacy of targeting dysregulated pathways in MPT using the PDX model from one MPT. RESULTS: MPT has unique molecular characteristics when compared to breast cancers of epithelial origin and can be classified into two groups. The PDX model derived from one patient with MPT showed that the mouse epithelial component increased during tumour growth. Moreover, targeted inhibition of platelet-derived growth factor receptor (PDGFR) and phosphoinositide 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) by imatinib mesylate and PKI-587 showed in vivo tumour suppression effects. CONCLUSIONS: This study revealed the molecular profiles of MPT that can lead to molecular classification and potential targeted therapy, and suggested that the MPT PDX model can be a useful tool for studying the pathogenesis of fibroepithelial neoplasms and for preclinical drug screening to find new therapeutic strategies for MPT.

PCW-A1001, AI-assisted de novo design approach to design a selective inhibitor for FLT-3(D835Y) in acute myeloid leukemia.

Treating acute myeloid leukemia (AML) by targeting FMS-like tyrosine kinase 3 (FLT-3) is considered an effective treatment strategy. By using AI-assisted hit optimization, we discovered a novel and highly selective compound with desired drug-like properties with which to target the FLT-3 (D835Y) mutant. In the current study, we applied an AI-assisted de novo design approach to identify a novel inhibitor of FLT-3 (D835Y). A recurrent neural network containing long short-term memory cells (LSTM) was implemented to generate potential candidates related to our in-house hit compound (PCW-1001). Approximately 10,416 hits were generated from 20 epochs, and the generated hits were further filtered using various toxicity and synthetic feasibility filters. Based on the docking and free energy ranking, the top compound was selected for synthesis and screening. Of these three compounds, PCW-A1001 proved to be highly selective for the FLT-3 (D835Y) mutant, with an IC50 of 764 nM, whereas the IC50 of FLT-3 WT was 2.54 µM.

Genomic characteristics of invasive mucinous adenocarcinoma of the lung with multiple pulmonary sites of involvement.

Invasive mucinous adenocarcinoma (IMA) of the lung frequently presents with diffuse pneumonic-type features or multifocal lesions, which are regarded as a pattern of intrapulmonary metastases. However, the genomics of multifocal IMAs have not been well studied. We performed whole exome sequencing on samples taken from 2 to 5 regions in seven patients with synchronous multifocal IMAs of the lung (24 regions total). Early initiating driver events, such as KRAS, NKX2-1, TP53, or ARID1A mutations, are clonal mutations and were present in all multifocal IMAs in each patient. The tumor mutational burden of multifocal IMAs was low (mean: 1.13/mega base), but further analyses suggested intra-tumor heterogeneity. The mutational signature analysis found that IMAs were predominantly associated with endogenous mutational process (signature 1), APOBEC activity (signatures 2 and 13), and defective DNA mismatch repair (signature 6), but not related to smoking signature. IMAs synchronously located in the bilateral lower lobes of two patients with background usual interstitial pneumonia had different mutation types, suggesting that they were double primaries. In conclusion, genomic evidence found in this study indicated the clonal intrapulmonary spread of diffuse pneumonic-type or multifocal IMAs, although they can occur in multicentric origins in the background of usual interstitial pneumonia. IMAs exhibited a heterogeneous genomic landscape despite the low somatic mutation burden. Further studies are warranted to determine the clinical significance of the genomic characteristics of IMAs in expanded cohorts.

Three-Dimensional Printing of Natural Materials Involving Loess-Based Composite Materials Designed for Ecofriendly Applications.

In this work, loess-based materials were designed based on a multicomponent composite materials system for ecofriendly natural three-dimensional (3D) printing involving quick lime, gypsum, and water. The 3D printing process was monitored as a function of gypsum content; in terms of mechanical strength and electrical resistance, in the cube-shaped bulk form. After initial optimization, the 3D printing composition was refined to provide improved printability in a 3D printing system. The optimal 3D fabrication allowed for reproducible printing of rectangular columns and cubes. The development of 3D printing materials was scrutinized using a multitude of physicochemical probing tools, including X-ray diffraction for phase identification, impedance spectroscopy to monitor setting behaviors, and mercury intrusion porosimetry to extract the pore structure of loess-based composite materials. Additionally, the setting behavior in the loess-based composite materials was analyzed by investigating the formation of gypsum hydrates induced by chemical reaction between quick lime and water. This setting reaction provides reasonable mechanical strength that is sufficient to print loess-based pastes via 3D printing. Such mechanical strength allows utilization of robotic 3D printing applications that can be used to fabricate ecofriendly structures.

Keratinocyte transglutaminase 2 promotes CCR6+ γδT-cell recruitment by upregulating CCL20 in psoriatic inflammation.

Keratinocyte-derived cytokines and chemokines amplify psoriatic inflammation by recruiting IL-17-producing CCR6+ γδT-cells and neutrophils. The expression of these cytokines and chemokines mainly depends on NF-κB activity; however, the pathway that activates NF-κB in response to triggering factors is poorly defined. Here, we show that transglutaminase 2 (TG2), previously reported to elicit a TH17 response by increasing IL-6 expression in a mouse model of lung fibrosis, mediates the upregulation of cytokines and chemokines by activating NF-κB in imiquimod (IMQ)-treated keratinocytes. TG2-deficient mice exhibited reduced psoriatic inflammation in skin treated with IMQ but showed systemic immune responses similar to wild-type mice. Experiments in bone marrow (BM) chimeric mice revealed that TG2 is responsible for promoting psoriatic inflammation in non-BM-derived cells. In keratinocytes, IMQ treatment activated TG2, which in turn activated NF-κB signaling, leading to the upregulation of IL-6, CCL20, and CXCL8 and increased leukocyte migration, in vitro. Consequently, TG2-deficient mice showed markedly decreased CCR6+ γδT-cell and neutrophil infiltration in IMQ-treated skin. Moreover, TG2 levels were higher in psoriatic skin than in normal skin and correlated with IL-6, CXCL8, and CCL20 levels. Therefore, these results indicate that keratinocyte TG2 acts as a critical mediator in the amplification of psoriatic inflammation.

Integrative analysis of genomic and transcriptomic characteristics associated with progression of aggressive thyroid cancer.

Anaplastic thyroid cancer (ATC) and advanced differentiated thyroid cancers (DTCs) show fatal outcomes, unlike DTCs. Here, we demonstrate mutational landscape of 27 ATCs and 86 advanced DTCs by massively-parallel DNA sequencing, and transcriptome of 13 ATCs and 12 advanced DTCs were profiled by RNA sequencing. TERT, AKT1, PIK3CA, and EIF1AX were frequently co-mutated with driver genes (BRAFV600E and RAS) in advanced DTCs as well as ATC, but tumor suppressors (e.g., TP53 and CDKN2A) were predominantly altered in ATC. CDKN2A loss was significantly associated with poor disease-specific survival in patients with ATC or advanced DTCs, and up-regulation of CD274 (PD-L1) and PDCD1LG2 (PD-L2). Transcriptome analysis revealed a fourth molecular subtype of thyroid cancer (TC), ATC-like, which hardly reflects the molecular signatures in DTC. Furthermore, the activation of JAK-STAT signaling pathway could be a potential druggable target in RAS-positive ATC. Our findings provide insights for precision medicine in patients with advanced TCs.

Multidomain-Based Responsive Materials with Dual-Mode Optical Readouts.

Responsive materials designed to generate signals for both surface-enhanced Raman spectroscopy (SERS) and phosphorescence lifetime-"dual-mode"-measurements are described. To demonstrate this concept, we incorporated pH-sensitive and oxygen-sensitive microdomains into a single hydrogel that could be interrogated via SERS and phosphorescence lifetime, respectively. Microdomains consisted two populations of discrete microcapsules containing either (1) gold nanoparticles capped with pH-sensitive Raman molecules or (2) oxygen-sensitive benzoporphyrin phosphors. While the microdomain-embedded hydrogels presented an expected background luminescence, the pH-sensitive SERS signal was distinguishable for all tested conditions. Response characteristics of the dual sensor showed no significant difference when compared to standalone single-mode pH and oxygen sensors. In addition, the feasibility of redundant multimode sensing was proven by observing the reaction produced by glucose oxidase chemically cross-linked within the corresponding alginate matrix. Each optical mode showed a signal change proportional to glucose concentration with an opposite signal directionality. These results support the promise of micro-/nanocomposite materials to improve measurement accuracy using intrinsic multimode responses and built-in redundancy, concepts that have broad appeal in the chemical sensing and biosensing fields.

MicroRNA Expression Profiles in Gastric Carcinogenesis.

Intestinal-type gastric carcinoma exhibits a multistep carcinogenic sequence from adenoma to carcinoma with a gradual increase in genomic alterations. But the roles of microRNAs (miRNA) in this multistage cascade are not fully explored. To identify differentially expressed miRNA (DEM) during early gastric carcinogenesis, we performed miRNA microarray profiling with 24 gastric cancers and precursor lesions (7 early gastric cancer [EGC], 3 adenomas with high-grade dysplasia, 4 adenomas with low-grade dysplasia, and 10 adjacent normal tissues). Alterations in the expression of 132 miRNA were detected; these were categorized into three groups based on their expression patterns. Of these, 42 miRNAs were aberrantly expressed in EGC. Five miRNA (miR-26a, miR-375, miR-574-3p, miR-145, and miR-15b) showed decreased expression since adenoma. Expression of two miRNA, miR-200C and miR-29a, was down-regulated in EGCs compared to normal mucosa or adenomas. Six miRNA (miR-601, miR-107, miR-18a, miR-370, miR-300, and miR-96) showed increased expression in gastric cancer compared to normal or adenoma samples. Five representative miRNAs were further validated with RT-qPCR in independent 77 samples. Taken together, these results suggest that the dysregulated miRNA show alterations at the early stages of gastric tumorigenesis and may be used as a candidate biomarker.

Investigating Self-Centering Capacity of Superelastic Shape Memory Alloy Fibers with Different Anchorages Through Pullout Tests.

This study investigated the pull-out resistance of superelastic shape memory alloy (SMA) short fibers in mortar with consideration of various end-anchorages that provide different anchoring actions. For the purpose, four types of SMA fibers were prepared using NiTi SMA wires with a diameter of 1.0 mm and the following four end shapes: straight (ST), L-shaped (LS), N-shaped (NS), and spearhead-shaped (SH). The straight-ended fiber was a reference with no working on the end, and the fiber with the spearhead-shaped end was crimped to make the end part flat. The fibers with L- and N-shaped ends were bent with single or double bending. The results showed that only the spearhead-shaped fibers showed self-centering behavior because of the superelasticity of the SMA after slip occurred. This paper discusses the reasons that the ST, LS, and NS fibers do not show self-centering behavior and proposes a concept to induce superelastic behavior in SMA fibers in mortar or concrete.

Full-color capable light-emitting diodes based on solution-processed quantum dot layer stacking.

To date, most of the studies on quantum dot-light-emitting diodes (QLEDs) have been dedicated to the fabrication of high-efficiency monochromatic devices. However, for the ultimate application of QLEDs to the next-generation display devices, QLEDs should possess a full-color emissivity. In this study, we report the fabrication of all-solution-processed full-color-capable white QLEDs with a standard device architecture, where sequentially stacked blue (B)/green (G)/red (R) quantum dot (QD)-emitting layers (EMLs) are sandwiched by poly(9-vinylcarbazole) as the hole transport layer and ZnO nanoparticles (NPs) as the electron transport layer. To produce interlayer mixing-free, well-defined B/G/R QD layering assemblies via successive spin casting, an ultrathin ZnO NP buffer is inserted between different-colored QD layers. The present full-color-capable white QLED exhibits high device performance with the maximum values of 16 241 cd m-2 for luminance and 6.8% for external quantum efficiency. The promising results indicate that our novel EML design of ZnO NP buffer-mediated QD layer stacking may afford a viable means towards bright, efficient full-color-capable white devices.

Electrical/Mechanical Monitoring of Shape Memory Alloy Reinforcing Fibers Obtained by Pullout Tests in SMA/Cement Composite Materials.

Self-healing is an essential property of smart concrete structures. In contrast to other structural metals, shape memory alloys (SMAs) offer two unique effects: shape memory effects, and superelastic effects. Composites composed of SMA wires and conventional cements can overcome the mechanical weaknesses associated with tensile fractures in conventional concretes. Under specialized environments, the material interface between the cementitious component and the SMA materials plays an important role in achieving the enhanced mechanical performance and robustness of the SMA/cement interface. This material interface is traditionally evaluated in terms of mechanical aspects, i.e., strain-stress characteristics. However, the current work attempts to simultaneously characterize the mechanical load-displacement relationships synchronized with impedance spectroscopy as a function of displacement. Frequency-dependent impedance spectroscopy is tested as an in situ monitoring tool for structural variations in smart composites composed of non-conducting cementitious materials and conducting metals. The artificial geometry change in the SMA wires is associated with an improved anchoring action that is compatible with the smallest variation in resistance compared with prismatic SMA wires embedded into a cement matrix. The significant increase in resistance is interpreted to be associated with the slip of the SMA fibers following the elastic deformation and the debonding of the SMA fiber/matrix.

3D Graphene-Ni Foam as an Advanced Electrode for High-Performance Nonaqueous Redox Flow Batteries.

Electrodes composed of multilayered graphene grown on a metal foam (GMF) were prepared by directly growing multilayer graphene sheets on a three-dimensional (3D) Ni-foam substrate via a self-catalyzing chemical vapor deposition process. The multilayer graphene sheets are successfully grown on the Ni-foam substrate surface, maintaining the unique 3D macroporous structure of the Ni foam. The potential use of GMF electrodes in nonaqueous redox flow batteries (RFBs) is carefully examined using [Co(bpy)3]+/2+ and [Fe(bpy)3]2+/3+ redox couples. The GMF electrodes display a much improved electrochemical activity and enhanced kinetics toward the [Co(bpy)3]+/2+ (anolyte) and [Fe(bpy)3]2+/3+ (catholyte) redox couples, compared with the bare Ni metal foam electrodes, suggesting that the 2D graphene sheets having lots of interdomain defects provide sufficient reaction sites and secure electric-conduction pathways. Consequently, a nonaqueous RFB cell assembled with GMF electrodes exhibits high Coulombic and voltage efficiencies of 87.2 and 90.9%, respectively, at the first cycle. This performance can be maintained up to the 50th cycle without significant efficiency loss. Moreover, the importance of a rational electrode design for improving electrochemical performance is addressed.

Effect of the precutting process on sanitizing treatments for reducing pathogens in vegetables.

The effectiveness of sanitizing treatments was investigated on reducing pathogens inoculated in whole or cut fresh vegetables, including Brussels sprouts, carrots, cherry tomatoes, paprika, and lettuce. These products were inoculated with Escherichia coli O157:H7, Salmonella enterica serovar Typhimurium, and Listeria monocytogenes and then treated with chlorine and alcohol sanitizers, followed by the subsequent washing procedure in sterile distilled water at 25°C for 5min. Alcohol sanitizer was the most effective in inhibiting E. coli O157:H7, S. Typhimurium, and L. monocytogenes on cut Brussels sprouts, showing bacterial reductions of 4.16, 3.60, and 3.26 log CFU/g, respectively. Interestingly, the effects of sanitizing treatments were significantly lower for fresh cut produce than those for whole products (p<0.05), indicating that the effectiveness of sanitizers would be different, depending on fresh produce and the pre-cut process. Therefore, further information should be obtained to develop an effective sanitizing treatment for fresh produce.