Cellular senescence causes cell cycle arrest and promotes permanent cessation of proliferation. Since the senescence of mesenchymal stem cells (MSCs) reduces proliferation and multipotency and increases immunogenicity, aged MSCs are not suitable for cell therapy. Therefore, it is important to inhibit cellular senescence in MSCs. It has recently been reported that metabolites can control aging diseases. Therefore, we aimed to identify novel metabolites that regulate the replicative senescence in MSCs. Using a fecal metabolites library, we identified nervonic acid (NA) as a candidate metabolite for replicative senescence regulation. In replicative senescent MSCs, NA reduced senescence-associated β-galactosidase positive cells, the expression of senescence-related genes, as well as increased stemness and adipogenesis. Moreover, in non-senescent MSCs, NA treatment delayed senescence caused by sequential subculture and promoted proliferation. We confirmed, for the first time, that NA delayed and inhibited cellular senescence.Considering optimal concentration, duration, and timing of drug treatment, NA is a novel potential metabolite that can be used in the development of technologies that regulate cellular senescence.

Purpose: We aimed to assess the real-world efficacy of nab-paclitaxel in metastatic breast cancer patients. Materials and Methods: This is a retrospective study performed in two tertiary referral hospitals in Korea. Patients with metastatic breast cancer treated with nab-paclitaxel (Abraxane®) between March 2016 and March 2020 were enrolled. Results: A total of 102 patients with metastatic breast cancer were included. Patients were heavily pre-treated with a median of four prior lines of chemotherapy (5 lines when including endocrine therapy in hormone-receptor-positive patients), and 66 patients (64.7%) were exposed to taxanes in the metastatic setting. According to St. Gallen molecular subtypes, 36 patients (35.3%) were luminal A, 28 (27.5%) were luminal B, 18 (17.7%) were human epidermal growth factor receptor 2–positive and 20 (19.6%) had triple-negative disease. Fifty patients (49.0%) were treated with a 3-weekly regimen (260 mg/m2 on day 1 every 3 weeks), and 52 (51.0%) were treated with a weekly regimen (100 mg/m2 every week). Objective response rate was 22.9%. After a median follow-up of 22.0 months, median progression-free survival (PFS) was 4.0 months (95% confidence interval [CI], 2.6 to 4.8) and median overall survival was 8.7 months (95% CI, 7.5 to 11.2). Patients treated with weekly regimen had longer PFS compared to 3-weekly regimen (5.5 vs. 2.3 months, p < 0.001). Multivariate analysis revealed the treatment regimen as an independent prognostic factor for PFS. There was no grade 3 or 4 hypersensitivity reaction. Conclusion This real-world data shows that nab-paclitaxel is a reasonable treatment option in heavily pre-treated and/or taxane-exposed metastatic breast cancer patients.

Purpose: Little is known about the relationship between brain-derived neurotrophic factor (BDNF) gene polymorphisms and psychiatric symptoms in diabetes patients. We investigated the effects of BDNF Val/66/Met polymorphism, glucose status, psychological susceptibility, and resilience on anxiety and depression symptoms in patients newly diagnosed with type 2 diabetes mellitus (T2DM). Materials and Methods: We examined biochemical factors and BDNF polymorphism in 89 patients who were newly diagnosed with T2DM. Psychiatric symptoms were investigated with the Hospital Anxiety and Depression Scale (HADS), and the ConnorDavidson Resilience Scale (CD-RISC) and Impact of Event Scale (IES) were used to assess psychological resilience and susceptibility to psychological distress, respectively. Logistic regression analyses were conducted to investigate factors associated with psychiatric symptoms. Results: We determined that 62 patients (70%) were Met-carriers. No significant differences were found between the Val/Val homozygous and Met-carrier groups regarding age, sex, body mass index, and clinical factors related to glycemic control and lipid profiles. HADS-anxiety and HADS-depression scores and IES factor scores were higher in the Met-carrier than the Val/Val homozygous group. Hemoglobin A1c (HbA1c) level was significantly inversely correlated with the severity of depressive symptoms. Resilience factors showed significant inverse correlations, and IES factors showed positive correlations with depressive symptom severity. In the logistic regression analysis model, depressive symptoms were significantly associated with HbA1c and BDNF polymorphism, whereas only the hyperarousal factor of the IES scale was associated with anxiety. Conclusion Depressive symptoms are associated with the presence of the Met-carriers and lower HbA1c in patients newly diagnosed with T2DM.

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601 hip AP radiographs, 5076 cropped unilateral hip joint images were used to construct a dataset that was further divided into training (80%), validation (10%), or test sets (10%). Three radiologists were asked to label the hip images as normal or DDH. To investigate the diagnostic performance of the deep learning algorithm, we calculated the receiver operating characteristics (ROC), precision-recall curve (PRC) plots, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) and compared them with the performance of radiologists with different levels of experience. Results: The area under the ROC plot generated by the deep learning algorithm and radiologists was 0.988 and 0.988–0.919, respectively. The area under the PRC plot generated by the deep learning algorithm and radiologists was 0.973 and 0.618– 0.958, respectively. The sensitivity, specificity, PPV, and NPV of the proposed deep learning algorithm were 98.0, 98.1, 84.5, and 99.8%, respectively. There was no significant difference in the diagnosis of DDH by the algorithm and the radiologist with experience in pediatric radiology (p = 0.180). However, the proposed model showed higher sensitivity, specificity, and PPV, compared to the radiologist without experience in pediatric radiology (p < 0.001). Conclusion The proposed deep learning algorithm provided an accurate diagnosis of DDH on hip radiographs, which was comparable to the diagnosis by an experienced radiologist.

Background: People are generally considered overweight and obese if their body mass index (BMI) is above 25 kg/m 2 and 30.0 kg/m 2 , respectively. The World Health Organization proposed stricter criteria for Asians (≥ 23 kg/m2 : overweight, ≥ 25 kg/m2 : obese). We aimed to verify whether this criteria could predict adverse pregnancy outcomes in Korean women. Methods: We included 7,547 Korean women from 12 institutions enrolled between June 2016 and October 2018. Women with no pre-pregnancy BMI data, not Korean, or lost to followup were excluded, leaving 6,331. The subjects were categorized into underweight, normal, overweight, class I obesity, and class II/III obesity based on a pre-pregnancy BMI of < 18.5, 18.5–22.9, 23.0–24.9, 25.0–29.9, and ≥ 30.0 kg/m2 , respectively. Results: Overall, 13.4%, 63.0%, 11.8%, 9.1%, and 2.6% of women were underweight, normal, and overweight and had class I obesity and class II/III obesity, respectively. In the multivariable analysis adjusted for maternal age, a higher BMI significantly increased the risk of preeclampsia, gestational diabetes, preterm delivery caused by maternal-fetal indications, cesarean section, large for gestational age, and neonatal intensive care unit admission. Conclusion Adverse pregnancy outcomes started to increase in those with a pre-pregnancy BMI ≥ 23.0 kg/m2 after adjusting for maternal age. The modified obesity criteria could help predict adverse pregnancy outcomes in Koreans.

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601 hip AP radiographs, 5076 cropped unilateral hip joint images were used to construct a dataset that was further divided into training (80%), validation (10%), or test sets (10%). Three radiologists were asked to label the hip images as normal or DDH. To investigate the diagnostic performance of the deep learning algorithm, we calculated the receiver operating characteristics (ROC), precision-recall curve (PRC) plots, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) and compared them with the performance of radiologists with different levels of experience. Results: The area under the ROC plot generated by the deep learning algorithm and radiologists was 0.988 and 0.988–0.919, respectively. The area under the PRC plot generated by the deep learning algorithm and radiologists was 0.973 and 0.618– 0.958, respectively. The sensitivity, specificity, PPV, and NPV of the proposed deep learning algorithm were 98.0, 98.1, 84.5, and 99.8%, respectively. There was no significant difference in the diagnosis of DDH by the algorithm and the radiologist with experience in pediatric radiology (p = 0.180). However, the proposed model showed higher sensitivity, specificity, and PPV, compared to the radiologist without experience in pediatric radiology (p < 0.001). Conclusion The proposed deep learning algorithm provided an accurate diagnosis of DDH on hip radiographs, which was comparable to the diagnosis by an experienced radiologist.

Objectives: The Korea Centers for Disease Control and Prevention has published “A Guideline for Unknown Disease Outbreaks (UDO).” The aim of this report was to introduce tabletop exercises (TTX) to prepare for UDO in the future. Methods: The UDO Laboratory Analyses Task Force in Korea Centers for Disease Control and Prevention in April 2018, assigned unknown diseases into 5 syndromes, designed an algorithm for diagnosis, and made a panel list for diagnosis by exclusion. Using the guidelines and laboratory analyses for UDO, TTX were introduced. Results: Since September 9th , 2018, the UDO Laboratory Analyses Task Force has been preparing TTX based on a scenario of an outbreak caused by a novel coronavirus. In December 2019, through TTX, individual missions, epidemiological investigations, sample treatments, diagnosis by exclusions, and next generation sequencing analysis were discussed, and a novel coronavirus was identified as the causal pathogen. Conclusion Guideline and laboratory analyses for UDO successfully applied in TTX. Conclusions drawn from TTX could be applied effectively in the analyses for the initial response to COVID-19, an ongoing epidemic of 2019 - 2020. Therefore, TTX should continuously be conducted for the response and preparation against UDO.

PURPOSE: We investigated the expression of the N-myc and STAT interactor (NMI) protein in invasive ductal carcinoma tissue and estimated its clinicopathologic significance as a prognostic factor. The expression levels and prognostic significance of NMI were also analyzed according to the molecular subgroup of breast cancers. METHODS: Human NMI detection by immunohistochemistry was performed using tissue microarrays of 382 invasive ductal carcinomas. The correlation of NMI expression with patient clinicopathological parameters and prognostic significance was analyzed and further assessed according to the molecular subgroup of breast cancers. Moreover, in vitro experiments with 13 breast cancer cell lines were carried out. We also validated NMI expression significance in The Cancer Genome Atlas cohort using the Human Protein Atlas (HPA) database. RESULTS: Low NMI expression was observed in 190 cases (49.7%). Low NMI expression was significantly associated with the “triple-negative” molecular subtype (p < 0.001), high nuclear grade (p < 0.001), high histologic grade (p < 0.001), and advanced anatomic stage (p = 0.041). Patients with low NMI expression had poorer progression-free survival (p = 0.038) than patients with high NMI expression. Low NMI expression was not significantly associated with patient prognosis in the molecular subgroup analysis. In vitro, a reduction of NMI expression was observed in 8 breast cancer cell lines, especially in the estrogen receptor-positive and basal B type of triple-negative breast cancer molecular subgroups. The HPA database showed that low NMI expression levels were associated with a lower survival probability compared with that associated with high NMI expression (p = 0.053). CONCLUSION NMI expression could be a useful prognostic biomarker and a potential novel therapeutic target in invasive ductal carcinoma.

Objective: To evaluate the predictive performance of optic nerve sheath thickness (ONST) on the outcomes of traumatic brain injury (TBI) and to compare the inter-observer agreement To evaluate the predictive performance of optic nerve sheath thickness (ONST) for traumatic brain injury (TBI) and to compare the predictive performance and inter-observer agreement between ONST and optic nerve sheath diameter (ONSD) on facial computed tomography (CT). Methods: We retrospectively enrolled patients with a history of facial trauma and who underwent both facial CT and brain CT. Two reviewers independently measured ONST and ONSD of each patient using facial CT images. Final brain CT with clinical outcome was used as the reference standard for TBI. Multivariate logistic regression analyses, receiver operating characteristic (ROC) curves, and intraclass correlation coefficients were used for statistical analyses. Results: Both ONST (P=0.002) and ONSD (P=0.001) on facial CT were significantly independent factors to distinguish between TBI and healthy brains; an increase in ONST and ONSD values corresponded with an increase in the risk of TBI by 8.9- and 7.6-fold, respectively. The predictive performances of the ONST (sensitivity, 96.2%; specificity, 94.3%; area under the ROC curve, 0.968) and ONSD (sensitivity, 92.6%; specificity, 90.2%; area under the ROC curve, 0.955) were excellent and exhibited similar sensitivity, specificity, and area under the curve (P=0.18–0.99). Interobserver and intraobserver intraclass correlation coefficients for ONST were significantly higher than those for ONSD (all P<0.001). Conclusion ONST on facial CT is a feasible predictor of TBI and demonstrates similar performance and superior observer agreement than ONSD. We recommend using ONST measurements to assess the need for additional brain CT scans in TBI-suspected cases.

PURPOSE: With the emergence of next-generation sequencing (NGS) technology, profiling a wide range of genomic alterations has become a possibility resulting in improved implementation of targeted cancer therapy. In Asian populations, the prevalence and spectrum of clinically actionable genetic alterations has not yet been determined because of a lack of studies examining high-throughput cancer genomic data. MATERIALS AND METHODS: To address this issue, 1,071 tumor samples were collected from five major cancer institutes in Korea and analyzed using targeted NGS at a centralized laboratory. Samples were either fresh frozen or formalin-fixed, paraffin embedded (FFPE) and the quality and yield of extracted genomic DNA was assessed. In order to estimate the effect of sample condition on the quality of sequencing results, tissue preparation method, specimen type (resected or biopsied) and tissue storage time were compared. RESULTS: We detected 7,360 non-synonymous point mutations, 1,164 small insertions and deletions, 3,173 copy number alterations, and 462 structural variants. Fifty-four percent of tumors had one or more clinically relevant genetic mutation. The distribution of actionable variants was variable among different genes. Fresh frozen tissues, surgically resected specimens, and recently obtained specimens generated superior sequencing results over FFPE tissues, biopsied specimens, and tissues with long storage duration. CONCLUSION: In order to overcome, challenges involved in bringing NGS testing into routine clinical use, a centralized laboratory model was designed that could improve the NGS workflows, provide appropriate turnaround times and control costs with goal of enabling precision medicine.
Academies and Institutes ; Asian Continental Ancestry Group ; DNA ; Humans ; Korea ; Methods ; Paraffin ; Point Mutation ; Precision Medicine ; Prevalence