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Kim, Jisup,Choi, Sung-Eun,Lee, Keum Hwa,Jeong, Hyeon Joo,Shin, Jae Il,Lim, Beom Jin Hindawi 2019 BioMed research international Vol.2019 No.-
<P>Henoch-Schönlein purpura (HSP) is the most common systemic vasculitis in children, and renal involvement (HSP nephritis, HSPN) is a severe manifestation. HSPN is histologically classified by the International Study of Kidney Disease in Children (ISKDC) based on mesangial hypercellularity and the extent of glomerular crescents. Macrophages, categorized as M1 or M2, frequently infiltrate in various glomerular and tubulointerstitial diseases and infiltration of specific subtypes is associated with disease progression. Therefore, to identify whether infiltration of M1 or M2 macrophages has clinical significance, we quantified the subtypes of macrophages in 49 HSPN specimens and correlated the counts with histologic features and clinical parameters. Higher tubulointerstitial M2 counts were associated with chronic renal failure (CRF), ISKDC classes III-IV, and crescents (<I>P</I><0.001, 0.002, 0.001). Glomerular M2 counts were significantly related to ISKDC classes III-IV and crescents (area under curve, AUC 0.804, 0.833). Tubulointerstitial M2 counts were associated with CRF, ISKDC classes III-IV, and crescents (AUC 0.872, 0.778, 0.830). Tubulointerstitial M2 counts also revealed higher AUC than tubulointerstitial M1 counts for CRF (<I>P</I>=0.036) and ISKDC classes III-IV (<I>P</I>=0.047). Glomerular M2 counts revealed higher AUC than glomerular M1 counts for ISKDC classes III–IV (<I>P</I>=0.024). Tubulointerstitial M2 counts were the most powerful parameter for CRF (AUC 0.872) and revealed even higher AUC than ISKDC classification (AUC 0.716) with borderline significance (<I>P</I>=0.086) for CRF. In summary, tubulointerstitial M2 counts were a superior parameter to tubulointerstitial M1 counts and even to ISKDC classification indicating the presence of CRF.</P>
Joohee Jung,Jisup Kim,Hyun Kyung Lim,Kyoung Mee Kim,Yun Sun Lee,Joon Seong Park,Dong Sup Yoon 대한외과학회 2017 Annals of Surgical Treatment and Research(ASRT) Vol.93 No.4
Purpose: In order to suggest optimal anticancer drugs for patient-tailored chemotherapy, we developed a colorectal cancer (CRC)-liver metastasis patient-derived tumor xenograft (PDTX) model. Methods: Tissue obtained from a patient with CRC-liver metastasis (F0) was transplanted in a nonobese female mouse with diabetic/severe combined immune deficiency (F1) and the tumor tissue was retransplanted into nude mice (F2). When tumor volumes reached ~500 mm3, the F2 mice were randomly divided into 4 groups (n = 4/group) of doxorubicin, cisplatin, docetaxel, and nontreated control groups. The tumor tissues were investigated using H&E staining, terminal deoxynucleotidyl transferase dUTP nick end labeling assays, and immunohistochemistry. To determine where the mutant allele frequencies varied across the different passages, we isolated genomic DNA from the primary tumor, liver metastasis, and PDTX models (F1/F2). Results: The physiological properties of the tumor were in accord with those of the patient’s tumors. Anticancer drugs delayed tumor growth, inhibited proliferation, and caused apoptosis. Histological assessments revealed no observable heterogeneity among the intragenerational PDTX models. Target exon sequencing analysis without high-quality filter conditions revealed some genetic variations in the 83 cancer-related genes across the generations. However, when de novo mutations were defined as a total count of zero in F0 and ≥5 in F2, exactly prognostic impact of clone cancer profiling (EGFR, KRAS, BRAF, PIK3CA, NRAS, APC and TP53) were detected in the paired. Conclusion: A CRC liver metastasis PDTX model was established for the evaluation of chemotherapeutic efficacy. This model retained the physiological characters of the patient tumors and potentially provides a powerful means of assessing chemotherapeutic efficacy.
Jung, Joohee,Kim, Jisup,Lim, Hyun Kyung,Kim, Kyoung Mee,Lee, Yun Sun,Park, Joon Seong,Yoon, Dong Sup The Korean Surgical Society 2017 Annals of Surgical Treatment and Research(ASRT) Vol.93 No.4
<P><B>Purpose</B></P><P>In order to suggest optimal anticancer drugs for patient-tailored chemotherapy, we developed a colorectal cancer (CRC)-liver metastasis patient-derived tumor xenograft (PDTX) model.</P><P><B>Methods</B></P><P>Tissue obtained from a patient with CRC-liver metastasis (F0) was transplanted in a nonobese female mouse with diabetic/severe combined immune deficiency (F1) and the tumor tissue was retransplanted into nude mice (F2). When tumor volumes reached ~500 mm<SUP>3</SUP>, the F2 mice were randomly divided into 4 groups (n = 4/group) of doxorubicin, cisplatin, docetaxel, and nontreated control groups. The tumor tissues were investigated using H&E staining, terminal deoxynucleotidyl transferase dUTP nick end labeling assays, and immunohistochemistry. To determine where the mutant allele frequencies varied across the different passages, we isolated genomic DNA from the primary tumor, liver metastasis, and PDTX models (F1/F2).</P><P><B>Results</B></P><P>The physiological properties of the tumor were in accord with those of the patient's tumors. Anticancer drugs delayed tumor growth, inhibited proliferation, and caused apoptosis. Histological assessments revealed no observable heterogeneity among the intragenerational PDTX models. Target exon sequencing analysis without high-quality filter conditions revealed some genetic variations in the 83 cancer-related genes across the generations. However, when <I>de novo</I> mutations were defined as a total count of zero in F0 and ≥5 in F2, exactly prognostic impact of clone cancer profiling (EGFR, KRAS, BRAF, PIK3CA, NRAS, APC and TP53) were detected in the paired.</P><P><B>Conclusion</B></P><P>A CRC liver metastasis PDTX model was established for the evaluation of chemotherapeutic efficacy. This model retained the physiological characters of the patient tumors and potentially provides a powerful means of assessing chemotherapeutic efficacy.</P>
Han Sung-Hoon,Lim Jisup,Kim Jun-Sik,Cho Jin-Hyoung,Hong Mihee,Kim Minji,Kim Su-Jung,Kim Yoon-Ji,Kim Young Ho,Lim Sung-Hoon,Sung Sang Jin,Kang Kyung-Hwa,Baek Seung-Hak,Choi Sung-Kwon,Kim Namkug 대한치과교정학회 2024 대한치과교정학회지 Vol.54 No.1
Objective: To quantify the effects of midline-related landmark identification on midline deviation measurements in posteroanterior (PA) cephalograms using a cascaded convolutional neural network (CNN). Methods: A total of 2,903 PA cephalogram images obtained from 9 university hospitals were divided into training, internal validation, and test sets (n = 2,150, 376, and 377). As the gold standard, 2 orthodontic professors marked the bilateral landmarks, including the frontozygomatic suture point and latero-orbitale (LO), and the midline landmarks, including the crista galli, anterior nasal spine (ANS), upper dental midpoint (UDM), lower dental midpoint (LDM), and menton (Me). For the test, Examiner-1 and Examiner-2 (3-year and 1-year orthodontic residents) and the Cascaded-CNN models marked the landmarks. After point-to-point errors of landmark identification, the successful detection rate (SDR) and distance and direction of the midline landmark deviation from the midsagittal line (ANS-mid, UDM-mid, LDM-mid, and Me-mid) were measured, and statistical analysis was performed. Results: The cascaded-CNN algorithm showed a clinically acceptable level of point-to-point error (1.26 mm vs. 1.57 mm in Examiner-1 and 1.75 mm in Examiner-2). The average SDR within the 2 mm range was 83.2%, with high accuracy at the LO (right, 96.9%; left, 97.1%), and UDM (96.9%). The absolute measurement errors were less than 1 mm for ANS-mid, UDM-mid, and LDM-mid compared with the gold standard. Conclusions: The cascaded-CNN model may be considered an effective tool for the auto-identification of midline landmarks and quantification of midline deviation in PA cephalograms of adult patients, regardless of variations in the image acquisition method.