Current Status of Clinical Diagnosis and Genetic Analysis of Hereditary Hemorrhagic Telangiectasia in South Korea: Multicenter Case Series and a Systematic Review

Purpose Hereditary hemorrhagic telangiectasia (HHT), a rare genetic vascular disorder, has been rarely reported in South Korea. We investigated the current prevalence and presenting patterns of genetically confirmed HHT in South Korea. Materials and Methods We defined HHT patients as those with proven mutations on known HHT-related genes (ENG, ACVRL1, SMAD4, and GDF2) or those fulfilling 3 or 4 of the Curaçao criteria. A computerized systematic search was performed in PubMed and KoreaMed using the following search term: (“hereditary hemorrhagic telangiectasia” AND “Korea”) OR (“Osler-Weber-Rendu” AND “Korea”). We also collected government health insurance data. HHT genetic testing results were collected from three tertiary hospitals in which the genetic tests were performed. We integrated patient data by analyzing each case to obtain the prevalence and presenting pattern of HHT in South Korea. Results We extracted 90 cases from 52 relevant articles from PubMed and KoreaMed. An additional 22 cases were identified from the three Korean tertiary hospitals after excluding seven cases that overlapped with those in the published articles. Finally, 112 HHT patients were identified (41 males and 71 females, aged 4–82 years [mean±standard deviation, 45.3±20.6 years]). The prevalence of HHT in South Korea is about 1 in 500,000, with an almost equal prevalence among men and women. Forty-nine patients underwent genetic testing, of whom 28 had HHT1 (ENG mutation) and 19 had HHT2 (ACVRL1 mutation); the other two patients were negative for ENG, ACVRL1, and SMAD4 mutations. Conclusion The prevalence of HHT is underestimated in Korea. The rate of phenotypic presentation seems to be similar to that found worldwide. Korean health insurance coverage is limited to representative genetic analysis to detect ENG and ACVRL1 mutations. Further genetic analyses to detect HHT3, HHT4, and other forms of HHT should be implemented

Ultrastructure of Cryptosporidium parvum Found in the Small Intestine of Immunosuppressed Mice

The ultrastructure of various stages of Cryptosporidium parvum was observed by transmission electron microscopy. C. parvum infection was activated in the small intestine of Korean laboratory mice (fCR) by immunosuppression with prednisolone for 7 weeks. The oocyst discharge was confirmed by modified Kinyon's acid fast stain of fecal specimens. Various endogenous stages of parasites, i. e., trophozoites, meronts, merozoites, and macrogametocytes, were observed in the middle part of the small intestine, as an extracytoplasmic but intracellular parasite of host mucosal epithelial cells. In trophozoites, a large nucleus with a prominent nucleolus was seen, and as they developed into meronts, endoplasmic reticulum appeared prominently in the cytoplasm. Two kinds of meronts, type I and type II, with eight and four merozoites respectively, were found. New merozoites were produced by nuclear division and external budding of the residual body of the meronts. The merozoites were lined with two unit membranes, unlike C. muris that has three membranes, and a nucleus was located near the posterior end. Mature merozoites had conoids, rhoptries and numerous micronemes; the characteristic structures of coccidian parasites. Macrogametocytes were largely vacuolated and "wall-forming body I" was recognized. Other sexual stages were difficult to recognize from our specimens. The present study confirmed that the Cryptosporidium found in the small intestine of Korean laboratory mice has a characteristic ultrastructure consistent with C. parvum

Epitaxial Growth of a Single-Crystal Hybridized Boron Nitride and Graphene layer on a Wide-Band Gap Semiconductor

Vertical and lateral heterogeneous structures of two-dimensional (2D) materials have paved the way for pioneering studies on the physics and applications of 2D materials. A hybridized hexagonal boron nitride (h-BN) and graphene lateral structure, a heterogeneous 2D structure, has been fabricated on single-crystal metals or metal foils by chemical vapor deposition (CVD). However, once fabricated on metals, the h-BN/graphene lateral structures require an additional transfer process for device applications, as reported for CVD graphene grown on metal foils. Here, we demonstrate that a single-crystal h-BN/graphene lateral structure can be epitaxially grown on a wide-gap semiconductor, SiC(0001). First, a single-crystal h-BN layer with the same orientation as bulk SiC was grown on a Si-terminated SiC substrate at 850 oC using borazine molecules. Second, when heated above 1150 oC in vacuum, the h-BN layer was partially removed and, subsequently, replaced with graphene domains. Interestingly, these graphene domains possess the same orientation as the h-BN layer, resulting in a single-crystal h-BN/graphene lateral structure on a whole sample area. For temperatures above 1600 oC, the single-crystal h-BN layer was completely replaced by the single-crystal graphene layer. The crystalline structure, electronic band structure, and atomic structure of the h-BN/graphene lateral structure were studied by using low energy electron diffraction, angle-resolved photoemission spectroscopy, and scanning tunneling microscopy, respectively. The h-BN/graphene lateral structure fabricated on a wide-gap semiconductor substrate can be directly applied to devices without a further transfer process, as reported for epitaxial graphene on a SiC substrate.Comment: 23 pages, 7 figure

Molecular Responses in Osteogenic Differentiation of Mesenchymal Stem Cells Induced by Physical Stimulation

Mesenchymal stem cells (MSCs) have been recognized as a great source of stem cells in the field of regenerative medicine and regulation of MSCs such as differentiation into specific cells. Particular interest is the use of physical stimulation for the expression of the osteoblast-specific genes from MSCs for bone tissue regeneration. The mechanical forces on MSCs, such as fluid flow, enhance the mineralized matrix and specific gene expressions. This process called mechanotransduction comprises of the steps of mechanoreception, biochemical coupling, transmission of signal and effector cell response. Physical stimuli effectively regulate extracellular and intracellular signaling pathways to enhance the expression of specific transcription factors, and the release of osteocytes, ultimately expedite the production of active osteoblasts. Thus understating, identification and functional characterization of the mechanotransduction underlying the physical stimulation of MSCs is a critical issue for devising new bone regenerative treatments for bone-related diseases. In this review, we focus on the molecular mechanism responsible for the mechanotransduction of osteogenic differentiation of MSCs induced by physical stimulation.

Nusinersen demonstrates effectiveness in treating spinal muscular atrophy: findings from a three-year nationwide study in Korea

IntroductionNusinersen is the first drug approved for spinal muscular atrophy (SMA) treatment. In this study, we aimed to evaluate the long-term safety and efficacy of nusinersen, assess the therapeutic effects based on the treatment initiation timing and baseline motor function, and explore the perception of functional improvement from either parents or patients, utilizing 3-year nationwide follow-up data in South Korea.MethodsWe enrolled patients with SMA who were treated with nusinersen under the National Health Insurance coverage, with complete motor score records available and a minimum treatment duration of 6 months. To evaluate the motor function of patients, the Hammersmith Infant Neurological Examination-2 (HINE-2) was used for type 1 and the Expanded Hammersmith Functional Motor Scale (HFMSE) was used for types 2 and 3 patients. A significant improvement was defined as a HINE-2 score gain ≥5 for patients with type 1 and an HFMSE score ≥ 3 for patients with types 2 and 3 SMA. Effects of treatment timing were assessed. Patients with type 2 were further categorized based on baseline motor scores for outcome analysis. We also analyzed a second dataset from five tertiary hospitals with the information on parents/patients-reported impressions of improvement.ResultsThe study comprised 137 patients, with 21, 103, and 13 patients representing type 1, 2, and 3 SMA, respectively. At the 3-year follow-up, the analysis encompassed 7 patients with type 1, 12 patients with type 2, and none with type 3. Nearly half of all enrolled patients across SMA types (42.8, 59.2 and 46.2%, respectively) reached the 2-year follow-up for analysis. Patients with type 1 SMA exhibited gradual motor function improvement over 1-, 2-, and 3-year follow-ups (16, 9, and 7 patients, respectively). Patients with type 2 SMA demonstrated improvement over 1-, 2-, and 3-year follow-ups (96, 61 and 12 patients, respectively). Early treatment from symptom onset resulted in better outcomes for patients with type 1 and 2 SMA. In the second dataset, 90.7% of 108 patients reported subjective improvement at the 1-year follow-up.ConclusionNusinersen treatment for types 1–3 SMA is safe and effective in long-term follow-up. Early treatment initiation was a significant factor affecting long-term motor outcome

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing