Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling

Acquiring reliable microstructure datasets is a pivotal step toward the systematic design of materials with the aid of integrated computational materials engineering (ICME) approaches. However, obtaining three-dimensional (3D) microstructure datasets is often challenging due to high experimental costs or technical limitations, while acquiring two-dimensional (2D) micrographs is comparatively easier. To deal with this issue, this study proposes a novel framework for 2D-to-3D reconstruction of microstructures called Micro3Diff using diffusion-based generative models (DGMs). Specifically, this approach solely requires pre-trained DGMs for the generation of 2D samples, and dimensionality expansion (2D-to-3D) takes place only during the generation process (i.e., reverse diffusion process). The proposed framework incorporates a new concept referred to as multi-plane denoising diffusion, which transforms noisy samples (i.e., latent variables) from different planes into the data structure while maintaining spatial connectivity in 3D space. Furthermore, a harmonized sampling process is developed to address possible deviations from the reverse Markov chain of DGMs during the dimensionality expansion. Combined, we demonstrate the feasibility of Micro3Diff in reconstructing 3D samples with connected slices that maintain morphologically equivalence to the original 2D images. To validate the performance of Micro3Diff, various types of microstructures (synthetic and experimentally observed) are reconstructed, and the quality of the generated samples is assessed both qualitatively and quantitatively. The successful reconstruction outcomes inspire the potential utilization of Micro3Diff in upcoming ICME applications while achieving a breakthrough in comprehending and manipulating the latent space of DGMs

Microstructure reconstruction using diffusion-based generative models

Microstructure reconstruction has been an essential part of computational material engineering to reveal the relationship between the microstructures and the material properties. However, it is still challenging to find a general solution for microstructure characterization and reconstruction (MCR) tasks although there have been many attempts such as the descriptor-based reconstruction methods. To address this generality problem, the denoising diffusion probabilistic models are first employed for the microstructure reconstruction task which can be applied to various types of material systems. Several microstructures (e.g., carbonate, ceramics, copolymer, etc.) are considered to be reproduced for validating the proposed models while addressing the quality of the generated images with the quantitative evaluation metrics (FID score, precision and recall). The results show that the proposed diffusion model based approach is applicable for reproducing various types of microstructures with different spatial distributions of morphological features. The present approach also provides a stable training procedure with simple implementation for generating visually similar microstructures (and also statistically equivalent) without requiring expert knowledge and some time-consuming parametric studies. The proposed approach has the potential of being a universal microstructure reconstruction method for handling complex microstructures for materials science

Microstructure Design of Multifunctional Particulate Composite Materials using Conditional Diffusion Models

This paper presents a novel modeling framework to generate an optimal microstructure having ultimate multifunctionality using a diffusion-based generative model. In computational material science, generating microstructure is a crucial step in understanding the relationship between the microstructure and properties. However, using finite element (FE)-based direct numerical simulation (DNS) of microstructure for multiscale analysis is extremely resource-intensive, particularly in iterative calculations. To address this time-consuming issue, this study employs a diffusion-based generative model as a replacement for computational analysis in design optimization. The model learns the geometry of microstructure and corresponding stress contours, allowing for the prediction of microstructural behavior based solely on geometry, without the need for additional analysis. The focus on this work is on mechanoluminescence (ML) particulate composites made with europium ions and dysprosium ions. Multi-objective optimization is conducted based on the generative diffusion model to improve light sensitivity and fracture toughness. The results show multiple candidates of microstructure that meet the design requirements. Furthermore, the designed microstructure is not present in the training data but generates new morphology following the characteristics of particulate composites. The proposed approach provides a new way to characterize a performance-based microstructure of composite materials

Pleural effusion after microtia reconstructive surgery -A case report-

Microtia reconstructive surgery is usually a multi-stage repair procedure that involves the use of cartilage and skin grafts. Complications can arise at both ear reconstruction sites and cartilage donor sites. In particular, pneumothorax, atelectasis, chest scars, and chest deformities are known to be associated with the harvesting of costal cartilage. However, delayed pleural effusion can also develop. Our patient complained of a cough and chest pain at 5 days postoperatively, and pleural effusion was detected by chest radiography. However, thoracentesis was not performed and the effusion resolved spontaneously and completely

Isolation and Characterization of a Defensin-Like Peptide (Coprisin) from the Dung Beetle, Copris tripartitus

The antibacterial activity of immune-related peptides, identified by a differential gene expression analysis, was investigated to suggest novel antibacterial peptides. A cDNA encoding a defensin-like peptide, Coprisin, was isolated from bacteria-immunized dung beetle, Copris tripartitus, by using differential dot blot hybridization. Northern blot analysis showed that Coprisin mRNA was up-regulated from 4 hours after bacteria injection and its expression level was reached a peak at 16 hours. The deduced amino acid sequence of Coprisin was composed of 80 amino acids with a predicted molecular weight of 8.6 kDa and a pI of 8.7. The amino acid sequence of mature Coprisin was found to be 79.1% and 67.4% identical to those of defensin-like peptides of Anomala cuprea and Allomyrina dichotoma, respectively. We also investigated active sequences of Coprisin by using amino acid modification. The result showed that the 9-mer peptide, LLCIALRKK-NH2, exhibited potent antibacterial activities against Escherichia coli and Staphylococcus aureus

Heart Transplantation in Pediatric Patients: Twelve-Year Experience of the Asan Medical Center

Heart transplantation is a standard treatment for end-stage heart disease. Pediatric heart transplantation, however, is not frequently performed due to the shortage of pediatric heart donors. This is the first report of pediatric heart transplantation in Korea. Our retrospective study included 37 patients younger than 18 yr of age who underwent heart transplantation at Asan Medical Center between August 1997 and April 2009. Preoperative diagnosis was either cardiomyopathy (n = 29, 78.3%) or congenital heart disease (n = 8, 22.7%). Mean follow up period was 56.9 ± 44.6 months. There were no early death, but 7 late deaths (7/37, 18.9%) due to rejection after 11, 15, 41 months (n = 3), infection after 5, 8, 10 months (n = 3), suspicious ventricular arrhythmia after 50 months (n = 1). There was no significant risk factor for survival. There were 25 rejections (25/37, 67.6%); less than grade II occurred in 17 patients (17/25, 68%) and more than grade II occurred in 8 patients (8/25, 32%). Actuarial 1, 5, and 10 yr survival was 88.6%, 76.8%, and 76.8%. Our midterm survival of pediatric heart transplantation showed excellent results. We hope this result could be an encouraging message to do more pediatric heart transplantation in Korean society

Simultaneous Detection of EGFR and VEGF in Colorectal Cancer using Fluorescence-Raman Endoscopy

Fluorescence endomicroscopy provides quick access to molecular targets, while Raman spectroscopy allows the detection of multiple molecular targets. Using a simultaneous fluorescence-Raman endoscopic system (FRES), we herein demonstrate its potential in cancer diagnosis in an orthotopically induced colorectal cancer (CRC) xenograft model. In the model, epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF) were targeted with antibody-conjugated fluorescence and surface-enhanced Raman scattering (F-SERS) dots. FRES demonstrated fast signal detection and multiplex targeting ability using fluorescence and Raman signals to detect the F-SERS dots. In addition, FRES showed a multiplex targeting ability even on a subcentimeter-sized CRC after spraying with a dose of 50 µg F-SERS dots. In conclusion, molecular characteristics of tumor cells (EGFR in cancer cell membranes) and tumor microenvironments (VEGF in the extracellular matrix) could be simultaneously investigated when performing a colonoscopy

Prevalence and detection of low-allele-fraction variants in clinical cancer samples

Accurate detection of genomic alterations using high-throughput sequencing is an essential component of precision cancer medicine. We characterize the variant allele fractions (VAFs) of somatic single nucleotide variants and indels across 5095 clinical samples profiled using a custom panel, CancerSCAN. Our results demonstrate that a significant fraction of clinically actionable variants have low VAFs, often due to low tumor purity and treatment-induced mutations. The percentages of mutations under 5% VAF across hotspots in EGFR, KRAS, PIK3CA, and BRAF are 16%, 11%, 12%, and 10%, respectively, with 24% for EGFR T790M and 17% for PIK3CA E545. For clinical relevance, we describe two patients for whom targeted therapy achieved remission despite low VAF mutations. We also characterize the read depths necessary to achieve sensitivity and specificity comparable to current laboratory assays. These results show that capturing low VAF mutations at hotspots by sufficient sequencing coverage and carefully tuned algorithms is imperative for a clinical assay

A genome-wide association study of anorexia nervosa suggests a risk locus implicated in dysregulated leptin signaling

J. Kaprio, A. Palotie, A. Raevuori-Helkamaa ja S. Ripatti ovat työryhmän Eating Disorders Working Group of the Psychiatric Genomics Consortium jäseniä. Erratum in: Sci Rep. 2017 Aug 21;7(1):8379, doi: 10.1038/s41598-017-06409-3We conducted a genome-wide association study (GWAS) of anorexia nervosa (AN) using a stringently defined phenotype. Analysis of phenotypic variability led to the identification of a specific genetic risk factor that approached genome-wide significance (rs929626 in EBF1 (Early B-Cell Factor 1); P = 2.04 x 10(-7); OR = 0.7; 95% confidence interval (CI) = 0.61-0.8) with independent replication (P = 0.04), suggesting a variant-mediated dysregulation of leptin signaling may play a role in AN. Multiple SNPs in LD with the variant support the nominal association. This demonstrates that although the clinical and etiologic heterogeneity of AN is universally recognized, further careful sub-typing of cases may provide more precise genomic signals. In this study, through a refinement of the phenotype spectrum of AN, we present a replicable GWAS signal that is nominally associated with AN, highlighting a potentially important candidate locus for further investigation.Peer reviewe

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data