Diffusion-driven GAN Inversion for Multi-Modal Face Image Generation

We present a new multi-modal face image generation method that converts a text prompt and a visual input, such as a semantic mask or scribble map, into a photo-realistic face image. To do this, we combine the strengths of Generative Adversarial networks (GANs) and diffusion models (DMs) by employing the multi-modal features in the DM into the latent space of the pre-trained GANs. We present a simple mapping and a style modulation network to link two models and convert meaningful representations in feature maps and attention maps into latent codes. With GAN inversion, the estimated latent codes can be used to generate 2D or 3D-aware facial images. We further present a multi-step training strategy that reflects textual and structural representations into the generated image. Our proposed network produces realistic 2D, multi-view, and stylized face images, which align well with inputs. We validate our method by using pre-trained 2D and 3D GANs, and our results outperform existing methods. Our project page is available at https://github.com/1211sh/Diffusion-driven_GAN-Inversion/.Comment: Accepted by CVPR 202

A Case of Acute Carbon Monoxide Poisoning Resulting in an ST Elevation Myocardial Infarction

Carbon monoxide (CO) is a well-known chemical asphyxiant, which causes tissue hypoxia with prominent neurological and cardiovascular injury. After exposure to CO, several cardiac manifestations have been reported, including arrhythmias, acute myocardial infarction, and pulmonary edema. However, an ST elevation myocardial infarction (STEMI) due to CO poisoning is a very rare presentation, and the treatment for STEMI due to CO poisoning is not well established. Here, we report a rare case of STEMI complicated by increased thrombogenicity secondary to acute CO poisoning and complete revascularization after antithrombotic treatment

Ruptured uterus in a 36-week pregnant patient with hemorrhagic shock after blunt trauma in Korea: a case report

Traumatic uterine rupture is uncommon but can be fatal and life-threatening for both the mother and infant. In addition to complications caused by trauma itself, such as pelvic fracture, gestational complications such as placental abruption, abortion, premature labor, rupture of membranes, maternal death, and stillbirth can occur. In particular, fetuses have been reported to have a high mortality rate in cases of traumatic uterine rupture. A 35-year-old pregnant female patient fell from the fourth floor and was admitted to our trauma center. We observed large hemoperitoneum, pelvic fractures, and spleen laceration, and the fetus was presumed to be located outside the uterus. The pregnant woman was hemodynamically unstable. Although the fetus was stillborn, angioembolization and surgical treatment were properly performed through collaboration with an interventional radiologist, obstetrician, and trauma surgeons. After two orthopedic operations, the patient was discharged after 34 days. This case report suggests the importance of a multidisciplinary approach in the treatment of pregnant trauma patients

Towards pathogenomics: a web-based resource for pathogenicity islands

Pathogenicity islands (PAIs) are genetic elements whose products are essential to the process of disease development. They have been horizontally (laterally) transferred from other microbes and are important in evolution of pathogenesis. In this study, a comprehensive database and search engines specialized for PAIs were established. The pathogenicity island database (PAIDB) is a comprehensive relational database of all the reported PAIs and potential PAI regions which were predicted by a method that combines feature-based analysis and similarity-based analysis. Also, using the PAI Finder search application, a multi-sequence query can be analyzed onsite for the presence of potential PAIs. As of April 2006, PAIDB contains 112 types of PAIs and 889 GenBank accessions containing either partial or all PAI loci previously reported in the literature, which are present in 497 strains of pathogenic bacteria. The database also offers 310 candidate PAIs predicted from 118 sequenced prokaryotic genomes. With the increasing number of prokaryotic genomes without functional inference and sequenced genetic regions of suspected involvement in diseases, this web-based, user-friendly resource has the potential to be of significant use in pathogenomics. PAIDB is freely accessible at

Discovery of Q203, a potent clinical candidate for the treatment of tuberculosis

New therapeutic strategies are needed to combat the tuberculosis pandemic and the spread of multidrug-resistant (MDR) and extensively drug-resistant (XDR) forms of the disease, which remain a serious public health challenge worldwide1, 2. The most urgent clinical need is to discover potent agents capable of reducing the duration of MDR and XDR tuberculosis therapy with a success rate comparable to that of current therapies for drug-susceptible tuberculosis. The last decade has seen the discovery of new agent classes for the management of tuberculosis3, 4, 5, several of which are currently in clinical trials6, 7, 8. However, given the high attrition rate of drug candidates during clinical development and the emergence of drug resistance, the discovery of additional clinical candidates is clearly needed. Here, we report on a promising class of imidazopyridine amide (IPA) compounds that block Mycobacterium tuberculosis growth by targeting the respiratory cytochrome bc1 complex. The optimized IPA compound Q203 inhibited the growth of MDR and XDR M. tuberculosis clinical isolates in culture broth medium in the low nanomolar range and was efficacious in a mouse model of tuberculosis at a dose less than 1 mg per kg body weight, which highlights the potency of this compound. In addition, Q203 displays pharmacokinetic and safety profiles compatible with once-daily dosing. Together, our data indicate that Q203 is a promising new clinical candidate for the treatment of tuberculosis

Comparative analysis of de novo genomes reveals dynamic intra-species divergence of NLRs in pepper

Background Peppers (Capsicum annuum L.) containing distinct capsaicinoids are the most widely cultivated spices in the world. However, extreme genomic diversity among species represents an obstacle to breeding pepper. Results Here, we report de novo genome assemblies of Capsicum annuum Early Calwonder (non-pungent, ECW) and Small Fruit (pungent, SF) along with their annotations. In total, we assembled 2.9 Gb of ECW and SF genome sequences, representing over 91% of the estimated genome sizes. Structural and functional annotation of the two pepper genomes generated about 35,000 protein-coding genes each, of which 93% were assigned putative functions. Comparison between newly and publicly available pepper gene annotations revealed both shared and specific gene content. In addition, a comprehensive analysis of nucleotide-binding and leucine-rich repeat (NLR) genes through whole-genome alignment identified five significant regions of NLR copy number variation (CNV). Detailed comparisons of those regions revealed that these CNVs were generated by intra-specific genomic variations that accelerated diversification of NLRs among peppers. Conclusions Our analyses unveil an evolutionary mechanism responsible for generating CNVs of NLRs among pepper accessions, and provide novel genomic resources for functional genomics and molecular breeding of disease resistance in Capsicum species.This study was supported by a grant from the Agricultural Genome Center of the Next Generation BioGreen 21 Program of RDA (Project No. PJ013153) and the National Research Foundation of Korea (NRF) grant funded by the Korean government (No. 2018R1A5A1023599 [SRC]) to D.C., and by the 2020 Research Fund of the University of Seoul to S.K. Theses funding bodies had no role in the study design, data collection, analysis, and preparation of the manuscript

Coculture of Marine Streptomyces sp. With Bacillus sp. Produces a New Piperazic Acid-Bearing Cyclic Peptide

Microbial culture conditions in the laboratory, which conventionally involve the cultivation of one strain in one culture vessel, are vastly different from natural microbial environments. Even though perfectly mimicking natural microbial interactions is virtually impossible, the cocultivation of multiple microbial strains is a reasonable strategy to induce the production of secondary metabolites, which enables the discovery of new bioactive natural products. Our coculture of marine Streptomyces and Bacillus strains isolated together from an intertidal mudflat led to discover a new metabolite, dentigerumycin E (1). Dentigerumycin E was determined to be a new cyclic hexapeptide incorporating three piperazic acids, N-OH-Thr, N-OH-Gly, β-OH-Leu, and a pyran-bearing polyketide acyl chain mainly by analysis of its NMR and MS spectroscopic data. The putative PKS-NRPS biosynthetic gene cluster for dentigerumycin E was found in the Streptomyces strain, providing clear evidence that this cyclic peptide is produced by the Streptomyces strain. The absolute configuration of dentigerumycin E was established based on the advanced Marfey's method, ROESY NMR correlations, and analysis of the amino acid sequence of the ketoreductase domain in the biosynthetic gene cluster. In biological evaluation of dentigerumycin E (1) and its chemical derivatives [2-N,16-N-deoxydenteigerumycin E (2) and dentigerumycin methyl ester (3)], only dentigerumycin E exhibited antiproliferative and antimetastatic activities against human cancer cells, indicating that N-OH and carboxylic acid functional groups are essential for the biological activity

Accurate quantification of transcriptome from RNA-Seq data by effective length normalization

We propose a novel, efficient and intuitive approach of estimating mRNA abundances from the whole transcriptome shotgun sequencing (RNA-Seq) data. Our method, NEUMA (Normalization by Expected Uniquely Mappable Area), is based on effective length normalization using uniquely mappable areas of gene and mRNA isoform models. Using the known transcriptome sequence model such as RefSeq, NEUMA pre-computes the numbers of all possible gene-wise and isoform-wise informative reads: the former being sequences mapped to all mRNA isoforms of a single gene exclusively and the latter uniquely mapped to a single mRNA isoform. The results are used to estimate the effective length of genes and transcripts, taking experimental distributions of fragment size into consideration. Quantitative RT–PCR based on 27 randomly selected genes in two human cell lines and computer simulation experiments demonstrated superior accuracy of NEUMA over other recently developed methods. NEUMA covers a large proportion of genes and mRNA isoforms and offers a measure of consistency (‘consistency coefficient’) for each gene between an independently measured gene-wise level and the sum of the isoform levels. NEUMA is applicable to both paired-end and single-end RNA-Seq data. We propose that NEUMA could make a standard method in quantifying gene transcript levels from RNA-Seq data