Urticarial vasculitis is characterized clinically by urticarial skin lesions and histologically by leukocytoclastic vasculitis. Hypocomplementemic urticarial vasculitis is associated with connective tissue diseases such as systemic lupus erythematosus (SLE). We report a case of urticarial vasculitis that preceded manifestations of SLE.
Anti-Infective Agents/therapeutic use ; Anti-Inflammatory Agents/therapeutic use ; Diagnosis, Differential ; Female ; Humans ; Lupus Erythematosus, Systemic/*diagnosis/etiology/pathology ; Middle Aged ; Recurrence ; Skin/pathology ; Urticaria/complications/*diagnosis ; Vasculitis, Hypersensitivity/complications/*diagnosis/pathology

Objectives: The aim of this study was to classify polysomnography (PSG)-based sleep disorders using actigraphy data using a convolutional neural network (CNN). Methods: Actigraphy data, PSG data, and diagnoses were obtained from 214 patients from a single-center sleep clinic. Patients diagnosed with circadian sleep disorders, narcolepsy, or periodic limb movement disorders were excluded. From the actigraphy data, three types of data were selected from the first 5 days, namely, sleep-wake status, activity count, and light exposure per epoch. The data were processed into a two-dimensional array with four instances, namely, 24-hour full-day data and data for 6, 8, and 10 hours timepoints after sleep onset, and then analyzed. Using a CNN, we attempted to classify the processed data into PSG-based diagnoses. Results: Overfitting of the training data was observed. The CNN showed near-perfect accuracy on the test data, but failed to classify the validation data (area under the curve: 24-hour full-day data: 0.6031, 6 hours after sleep onset: 0.5148, 8 hours: 0.6122, and 10 hours: 0.5769). Conclusions The lack and inaccuracy of data were responsible for the results. A higher sampling rate and additional ancillary data, such as PSG or heart rate variability data, are necessary for accurate classification. Additionally, alternative approaches to machine learning, such as transformers, should be considered in future studies.

Objectives: The aim of this study was to classify polysomnography (PSG)-based sleep disorders using actigraphy data using a convolutional neural network (CNN). Methods: Actigraphy data, PSG data, and diagnoses were obtained from 214 patients from a single-center sleep clinic. Patients diagnosed with circadian sleep disorders, narcolepsy, or periodic limb movement disorders were excluded. From the actigraphy data, three types of data were selected from the first 5 days, namely, sleep-wake status, activity count, and light exposure per epoch. The data were processed into a two-dimensional array with four instances, namely, 24-hour full-day data and data for 6, 8, and 10 hours timepoints after sleep onset, and then analyzed. Using a CNN, we attempted to classify the processed data into PSG-based diagnoses. Results: Overfitting of the training data was observed. The CNN showed near-perfect accuracy on the test data, but failed to classify the validation data (area under the curve: 24-hour full-day data: 0.6031, 6 hours after sleep onset: 0.5148, 8 hours: 0.6122, and 10 hours: 0.5769). Conclusions The lack and inaccuracy of data were responsible for the results. A higher sampling rate and additional ancillary data, such as PSG or heart rate variability data, are necessary for accurate classification. Additionally, alternative approaches to machine learning, such as transformers, should be considered in future studies.

Objectives: The aim of this study was to classify polysomnography (PSG)-based sleep disorders using actigraphy data using a convolutional neural network (CNN). Methods: Actigraphy data, PSG data, and diagnoses were obtained from 214 patients from a single-center sleep clinic. Patients diagnosed with circadian sleep disorders, narcolepsy, or periodic limb movement disorders were excluded. From the actigraphy data, three types of data were selected from the first 5 days, namely, sleep-wake status, activity count, and light exposure per epoch. The data were processed into a two-dimensional array with four instances, namely, 24-hour full-day data and data for 6, 8, and 10 hours timepoints after sleep onset, and then analyzed. Using a CNN, we attempted to classify the processed data into PSG-based diagnoses. Results: Overfitting of the training data was observed. The CNN showed near-perfect accuracy on the test data, but failed to classify the validation data (area under the curve: 24-hour full-day data: 0.6031, 6 hours after sleep onset: 0.5148, 8 hours: 0.6122, and 10 hours: 0.5769). Conclusions The lack and inaccuracy of data were responsible for the results. A higher sampling rate and additional ancillary data, such as PSG or heart rate variability data, are necessary for accurate classification. Additionally, alternative approaches to machine learning, such as transformers, should be considered in future studies.

OBJECTIVE: The purpose of this study was to describe the clinical presentation and histopathologic findings that help in decisions about management of ovarian mass in childhood and adolescence. METHODS:We retrospectively analyzed the data on 307 patients with surgically treated ovarian mass under 20 years of age at the Cheil General Hospital, between January 1995 and December 2005. RESULTS: Of the 307 cases, 40 cases (13%) were ovarian malignancy. The incidence of malignant ovarian tumor increased to 16.9% in 237 neoplastic tumors. Epithelial, germ cell, and sex-cord stromal malignancies accounted for 57.5%, 30% and 12.5%, respectively, of the 40 ovarian malignancies. The stage of the 35 cases (87.5%) with the ovarian malignancy was the FIGO stage I. The incidence of ovarian malignancies increased with larger size, higher CA125 level. Solid ovarian masses on ultrasound were more likely ovarian malignancy. But age and menarchal status was not correlated with ovarian malignancy. Mature cystic teratoma seen in 132 patients (55.7%), was the most common neoplasm of ovary in this age group, and the incidence of bilaterality was 12.1%. On follow up, 4.9% (13/267) of previously diagnosed benign ovarian tumor were reoperated due to recurred or newly developed ovarian tumor. After cystectomy, the recurrence rate of ipsilateral ovarian tumor was 2.8% (4/142). CONCLUSION: If there is no evidence of malignancy, conservative surgical treatment should be employed to preserve future endocrine function and fertility in this age group.
Adolescent ; Cystectomy ; Female ; Fertility ; Follow-Up Studies ; Germ Cells ; Hospitals, General ; Humans ; Incidence ; Ovary ; Recurrence ; Retrospective Studies ; Teratoma

OBJECTIVE: The purpose of this study was to describe the clinical presentation and histopathologic findings that help in decisions about management of ovarian mass in childhood and adolescence. METHODS:We retrospectively analyzed the data on 307 patients with surgically treated ovarian mass under 20 years of age at the Cheil General Hospital, between January 1995 and December 2005. RESULTS: Of the 307 cases, 40 cases (13%) were ovarian malignancy. The incidence of malignant ovarian tumor increased to 16.9% in 237 neoplastic tumors. Epithelial, germ cell, and sex-cord stromal malignancies accounted for 57.5%, 30% and 12.5%, respectively, of the 40 ovarian malignancies. The stage of the 35 cases (87.5%) with the ovarian malignancy was the FIGO stage I. The incidence of ovarian malignancies increased with larger size, higher CA125 level. Solid ovarian masses on ultrasound were more likely ovarian malignancy. But age and menarchal status was not correlated with ovarian malignancy. Mature cystic teratoma seen in 132 patients (55.7%), was the most common neoplasm of ovary in this age group, and the incidence of bilaterality was 12.1%. On follow up, 4.9% (13/267) of previously diagnosed benign ovarian tumor were reoperated due to recurred or newly developed ovarian tumor. After cystectomy, the recurrence rate of ipsilateral ovarian tumor was 2.8% (4/142). CONCLUSION: If there is no evidence of malignancy, conservative surgical treatment should be employed to preserve future endocrine function and fertility in this age group.
Adolescent ; Cystectomy ; Female ; Fertility ; Follow-Up Studies ; Germ Cells ; Hospitals, General ; Humans ; Incidence ; Ovary ; Recurrence ; Retrospective Studies ; Teratoma

BACKGROUND: Leukemic cells originate from hypoxic bone marrow, which protects them from anti-cancer drugs. Although many factors that cause drug resistance in leukemic cells have been studied, the effect of hypoxia on drug-induced apoptosis is still poorly understood. METHODS: In this study, we examined the effect of hypoxia on anti-leukemic drug resistance in leukemic cell lines treated with cobalt chloride (CoCl2), a hypoxia-mimetic agent. Cellular proliferation was evaluated using the methyl thiazolyl tetrazolium (MTT) assay. Flow cytometry analysis and western blots were performed to investigate apoptosis-related proteins. RESULTS: Unlike its previously known apoptotic effect, the expression of HIF-1alpha increased the survival rate of human promyelocytic leukemia HL-60 cells when these cells were exposed to anti-leukemic drugs; these effects were mediated by heat-shock protein HSP70 and the pro-apoptotic protein Bax. CONCLUSION: These findings may provide new insights for understanding the mechanisms underlying hypoxia and for designing new therapeutic strategies for acute myeloid leukemia.
Anoxia ; Apoptosis ; Arsenicals ; Blotting, Western ; Bone Marrow ; Cell Line ; Cell Proliferation ; Cobalt ; Drug Resistance ; Flow Cytometry ; Heat-Shock Proteins ; HL-60 Cells ; Humans ; Leukemia ; Leukemia, Myeloid, Acute ; Oxides ; Proteins ; Survival Rate

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by formation of multiple fluid-filled cysts that expand over time and destroy renal architecture. The proteins encoded by the PKD1 and PKD2 genes, mutations in which account for nearly all cases of ADPKD, may help guard against cystogenesis. Previously developed mouse models of PKD1 and PKD2 demonstrated an embryonic lethal phenotype and massive cyst formation in the kidney, indicating that PKD1 and PKD2 probably play important roles during normal renal tubular development. However, their precise role in development and the cellular mechanisms of cyst formation induced by PKD1 and PKD2 mutations are not fully understood. To address this question, we presently created Pkd2 knockout and PKD2 transgenic mouse embryo fibroblasts. We used a mouse oligonucleotide microarray to identify messenger RNAs whose expression was altered by the overexpression of the PKD2 or knockout of the Pkd2. The majority of identified mutations was involved in critical biological processes, such as metabolism, transcription, cell adhesion, cell cycle, and signal transduction. Herein, we confirmed differential expressions of several genes including aquaporin-1, according to different PKD2 expression levels in ADPKD mouse models, through microarray analysis. These data may be helpful in PKD2-related mechanisms of ADPKD pathogenesis.
Animals ; Biological Processes ; Cell Adhesion ; Cell Cycle ; Embryonic Structures ; Fibroblasts ; Kidney ; Mice ; Mice, Transgenic ; Microarray Analysis ; Oligonucleotide Array Sequence Analysis ; Phenotype ; Polycystic Kidney Diseases ; Polycystic Kidney, Autosomal Dominant ; Proteins ; RNA, Messenger ; Signal Transduction

PURPOSE: Mucopolysaccharidosis type II (MPS II or Hunter syndrome) is a rare lysosomal storage disorder caused by iduronate-2-sulfatase (IDS) deficiency. MPS II causes a wide phenotypic spectrum of symptoms ranging from mild to severe. IDS activity, which is measured in leukocyte pellets or fibroblasts, was reported to be related to clinical phenotype by Sukegawa-Hayasaka et al. Measurement of residual plasma IDS activity using a fluorometric assay is simpler than conventional measurements using skin fibroblasts or peripheral blood mononuclear cells. This is the first study to describe the relationship between plasma IDS activity and clinical phenotype of MPS II. METHODS: We hypothesized that residual plasma IDS activity is related to clinical phenotype. We classified 43 Hunter syndrome patients as having attenuated or severe disease types based on clinical characteristics, especially intellectual and cognitive status. There were 27 patients with the severe type and 16 with the attenuated type. Plasma IDS activity was measured by a fluorometric enzyme assay using 4-methylumbelliferyl-alpha-iduronate 2-sulphate. RESULTS: Plasma IDS activity in patients with the severe type was significantly lower than that in patients with the attenuated type (P=0.006). The optimal cut-off value of plasma IDS activity for distinguishing the severe type from the attenuated type was 0.63 nmol.4 hr-1.mL-1. This value had 88.2% sensitivity, 65.4% specificity, and an area under receiver-operator characteristics (ROC) curve of 0.768 (ROC curve analysis; P=0.003). CONCLUSION: These results show that the mild phenotype may be related to residual lysosomal enzyme activity.
Enzyme Assays ; Fibroblasts ; Humans ; Iduronate Sulfatase ; Leukocytes ; Mucopolysaccharidoses ; Mucopolysaccharidosis II ; Phenotype ; Plasma ; Sensitivity and Specificity ; Skin

PURPOSE: Mucopolysaccharidosis type II (MPS II or Hunter syndrome) is a rare lysosomal storage disorder caused by iduronate-2-sulfatase (IDS) deficiency. MPS II causes a wide phenotypic spectrum of symptoms ranging from mild to severe. IDS activity, which is measured in leukocyte pellets or fibroblasts, was reported to be related to clinical phenotype by Sukegawa-Hayasaka et al. Measurement of residual plasma IDS activity using a fluorometric assay is simpler than conventional measurements using skin fibroblasts or peripheral blood mononuclear cells. This is the first study to describe the relationship between plasma IDS activity and clinical phenotype of MPS II. METHODS: We hypothesized that residual plasma IDS activity is related to clinical phenotype. We classified 43 Hunter syndrome patients as having attenuated or severe disease types based on clinical characteristics, especially intellectual and cognitive status. There were 27 patients with the severe type and 16 with the attenuated type. Plasma IDS activity was measured by a fluorometric enzyme assay using 4-methylumbelliferyl-alpha-iduronate 2-sulphate. RESULTS: Plasma IDS activity in patients with the severe type was significantly lower than that in patients with the attenuated type (P=0.006). The optimal cut-off value of plasma IDS activity for distinguishing the severe type from the attenuated type was 0.63 nmol.4 hr-1.mL-1. This value had 88.2% sensitivity, 65.4% specificity, and an area under receiver-operator characteristics (ROC) curve of 0.768 (ROC curve analysis; P=0.003). CONCLUSION: These results show that the mild phenotype may be related to residual lysosomal enzyme activity.
Enzyme Assays ; Fibroblasts ; Humans ; Iduronate Sulfatase ; Leukocytes ; Mucopolysaccharidoses ; Mucopolysaccharidosis II ; Phenotype ; Plasma ; Sensitivity and Specificity ; Skin