A 35-year-old male presented with atypical aphasia following left anterior choroidal artery infarction associated with distal internal carotid artery dissection. He presented with 1) lexical-semantic deficit without semantic impairment, 2) frequent surface errors (both surface dyslexia and dysgraphia), and 3) intact non-word reading/repetition (preserved sub-lexical route), suggesting deficit in the phonological output lexicon. Diffusion-tensor tractography analysis revealed disruption in the inferior fronto-occipital fasciculus and inferior longitudinal fasciculus, which might serve as potential subcortical neural correlates for phonological output lexicon.

Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC50 and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC50 and 0.81 for AUC. We identify common predictor genes for IC50 and AUC, with which the performance was similar to those with genes separately found for IC50 and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC50, 0.7945 for AUC) with 321 predictor genes.

Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC50 and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC50 and 0.81 for AUC. We identify common predictor genes for IC50 and AUC, with which the performance was similar to those with genes separately found for IC50 and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC50, 0.7945 for AUC) with 321 predictor genes.

OBJECTIVES: Effects of multiple trauma are complex and extend beyond core PTSD symptoms. However, few psychological instruments for trauma assessment address this issue of symptom complexity. The Trauma Symptom Checklist-40 (TSC-40) is a self-report scale that assesses wide range of symptoms associated with childhood or adult traumatic experience. The purpose of the present study was to evaluate the validity of the Korean Version of the TSC-40 in a sample of psychiatric outpatients. METHODS: Data of 367 treatment-seeking patients with DSM-IV diagnoses were obtained from an outpatient department of psychiatric unit at a university hospital. The diagnoses were anxiety disorder, posttraumatic stress disorder, depressive disorder, adjustment disorder and others. Included in the psychometric data were the TSC-40, the Life events checklist, the Impact of Event Scale-Revised, the Zung's Self-report Depression Scale, and the Zung's Self-report Anxiety Scale. Cronbach's α for internal consistency were calculated. Convergent and concurrent validity was approached with correlation between the TSC-40 and other scales (PTSD, anxiety and depression). RESULTS: Exploratory factor analysis of the Korean Version of TSC-40 extracted seven-factor structure accounted for 59.55% of total variance that was contextually similar to a six-factor structure and five-factor structure of the original English version. The Korean Version of TSC-40 demonstrated a high level of internal consistency. (Cronbach's α=0.94) and good concurrent and convergent validity with another PTSD scale and anxiety and depression scales. CONCLUSIONS: Excellent construct validity of The Korean Version of TSC-40 was proved in this study. And subtle difference in the factor structure may reflect the cultural issues and the sample characteristics such as heterogeneous clinical population (including non-trauma related disorders) and outpatient status. Overall, this study TSCdemonstrated that the Korean version of TSC-40 is psychometrically sound and can be used for Korean clinical population.
Adjustment Disorders ; Adult ; Anxiety ; Anxiety Disorders ; Checklist ; Depression ; Depressive Disorder ; Diagnosis ; Diagnostic and Statistical Manual of Mental Disorders ; Humans ; Multiple Trauma ; Outpatients ; Psychometrics ; Stress Disorders, Post-Traumatic ; Weights and Measures

OBJECTIVE: Ovarian reserve tests are commonly used to predict ovarian response in infertile patients undergoing ovarian stimulation. Although serum markers such as basal follicle-stimulating hormone (FSH) or random anti-Müllerian hormone (AMH) level and ultrasonographic markers (antral follicle count, AFC) are good predictors, no single test has proven to be the best predictor. In this study, we developed appropriate equations and novel nomograms to predict the number of oocytes that will be retrieved using patients' age, serum levels of basal FSH and AMH, and AFC. METHODS: We analyzed a database containing clinical and laboratory information of 141 stimulated in vitro fertilization (IVF) cycles performed at a university-based hospital between September 2009 and December 2013. We used generalized linear models for prediction of the number of oocytes. RESULTS: Age, basal serum FSH level, serum AMH level, and AFC were significantly related to the number of oocytes retrieved according to the univariate and multivariate analyses. The equations that predicted the number of oocytes retrieved (log scale) were as follows: model (1) 3.21-0.036×(age)+0.089×(AMH), model (2) 3.422-0.03×(age)-0.049×(FSH)+0.08×(AMH), model (3) 2.32-0.017×(age)+0.039×(AMH)+0. 03×(AFC), model (4) 2.584-0.015×(age)-0.035×(FSH)+0.038×(AMH)+0.026×(AFC). model 4 showed the best performance. On the basis of these variables, we developed nomograms to predict the number of oocytes that can be retrieved. CONCLUSION: Our nomograms helped predict the number of oocytes retrieved in stimulated IVF cycles.
Biomarkers ; Fertilization in Vitro ; Follicle Stimulating Hormone ; Humans ; Linear Models ; Multivariate Analysis ; Nomograms* ; Oocytes* ; Ovarian Reserve ; Ovulation Induction*

OBJECTIVE: In 2009 anti-Mullerian hormone (AMH) assay was approved for clinical use in Korea. This study was performed to determine the reference values of AMH for predicting ovarian response to controlled ovarian hyperstimulation (COH) using the clinical assay data. METHODS: One hundred sixty-two women who underwent COH cycles were included in this study. We collected data on age, basal AMH and FSH levels, total dose of gonadotropins, stimulation duration, and numbers of oocytes retrieved and fertilized. Blood samples were obtained on cycle day 3 before gonadotropin administration started. Serum AMH levels were measured at a centralized clinical laboratory center. The correlation between the AMH level and COH outcomes and cut-off values for poor and high response after COH was analyzed. RESULTS: Concentration of AMH was significantly correlated with the number of oocytes retrieved (OPU; r=0.700, p<0.001). The mean+/-SE serum AMH levels for poor (OPU< or =3), normal (4< or =OPU< or =19), and high (OPU> or =20) response were 0.94+/-0.15 ng/mL, 2.79+/-0.21 ng/mL, and 6.94+/-0.90 ng/mL, respectively. The cut-off level, sensitivity and specificity for poor and high response were 1.08 ng/mL, 85.8%, and 78.6%; and 3.57 ng/mL, 94.4%, and 83.3%, respectively. CONCLUSION: Our data present clinical reference values of the serum AMH level for ovarian response in Korean women. The serum AMH level could be a clinically useful predictor of ovarian response to COH.
Anti-Mullerian Hormone ; Female ; Gonadotropins ; Humans ; Korea ; Oocytes ; Reference Values ; Sensitivity and Specificity

PURPOSE: To investigate the direct relationship between the follicular fluid (FF) level of soluble human leukocyte antigen G (HLA-G) and fertilizability of the corresponding oocyte as well as the morphological quality of the corresponding embryo. MATERIALS AND METHODS: Sixty-three patients were stimulated with recombinant FSH combined with gonadotropin-releasing hormone (GnRH) agonist long (n=5) or antagonist protocol (n=58) for standard in vitro fertilization (IVF). At the time oocyte retrieval, follicular fluid was obtained from single dominant follicle in 63 patients, and the level of soluble HLA-G was measured by sandwich enzyme-liked immunosorbent assay (ELISA). Normal fertilization and individual embryo quality were evaluated, and were graded to four categories by morphological criteria (the embryo with symmetrical blastomeres and no fragmentation were assigned as grade A). Good-quality embryo was defined as those with grade A or B. RESULTS: Soluble HLA-G was not detected in 15 FF samples. In the group with positive FF soluble HLA-G (sHLA-G) (n=48), high levels of sHLA-G (>117.758 U/mL) could predict the failure of fertilization with statistical significance {area under the curve (AUC) 0.676, 95% confidence interval (CI) 0.525-0.804}. However, the FF sHLA-G level was not related with the formation of good-quality embryo. CONCLUSION: High level of FF sHLA-G could predict the fertilization failure of the corresponding oocyte, but was not related with the formation of good-quality embryo.
Adult ; Enzyme-Linked Immunosorbent Assay ; Female ; Follicular Fluid/*metabolism ; HLA-G Antigens/*metabolism ; Humans ; Oocytes/*cytology/physiology ; Ovarian Follicle/*cytology/physiology

Anti-Mullerian hormone (AMH), also called Mullerian-inhibiting substance, is a member of the transforming growth factor (TGF)-beta superfamily. It is well known that AMH is expressed by Sertoli cells in fetal testis, and that it induces Mullerian duct degeneration during male fetal development. However, in females AMH is produced by granulosa cells of the ovarian follicles. Recently, numerous studies have demonstrated that AMH could be a useful marker of ovarian function. Serum AMH levels decrease progressively with age, become undetectable after menopause, and show high cycle-to-cycle reproducibility. It has been shown that AMH level is correlated with various outcomes of controlled ovarian hyperstimulation (COH). Many studies showed that AMH can discriminate very effectively poor responders, cycle cancellation, and ovarian hyperstimulation syndrome after COH. AMH also has a functional role in folliculogenesis and could be a qualitative marker of ovarian follicular states. In addition, AMH has been associated with various clinical statuses such as polycystic ovarian syndrome, endometriosis, obesity, granulosa cell tumor, and premature ovarian failure. AMH is an effective and promising biomarker of various conditions in female reproduction. In this article, current research results on role of AMH as a marker of ovarian function and dysfunction are discussed.
Anti-Mullerian Hormone ; Endometriosis ; Female ; Fetal Development ; Granulosa Cell Tumor ; Granulosa Cells ; Humans ; Male ; Menopause ; Obesity ; Ovarian Follicle ; Ovarian Hyperstimulation Syndrome ; Polycystic Ovary Syndrome ; Primary Ovarian Insufficiency ; Reproduction ; Sertoli Cells ; Testis ; Transforming Growth Factors

Cancer is not rare in women in reproductive ages, and there has been a remarkable improvement in the survival rates due to progress in cancer treatment. Moreover, women have been delaying the initiation of childbearing to later in life. Thus the preservation of fertility in female cancer survivors has become an important health issue. Because of the variations in the type of cancer, type and dose of chemotherapy, the time available before onset of treatment, the patient's age, and the status of partners, each case should be individualized and requires a different strategy in fertility preservation. When a partner or donor sperm is available, embryo cryopreservation is now an established and acceptable technique for fertility preservation, providing a delay in the initiation of chemotherapy or radiotherapy. Oocyte cryopreservation is available for women without partners, but there is a limited experience with this technique and pregnancy rate is still low. In spite of the recent reports of successful birth after autotransplantation of cryopreserved-thawed human ovarian tissue, clinical experience is also limited and this technique remains still experimental. Further researches for establishing optimal cryopreservation and thawing protocols and increasing post-thawing survival, pregnancy, and delivery rates are necessary. In this article, the mechanisms of reproductive failure after cancer therapy and the strategies for fertility preservation in cancer survivors are discussed.
Cryopreservation ; Embryonic Structures ; Female ; Fertility ; Fertility Preservation ; Humans ; Oocytes ; Parturition ; Pregnancy ; Pregnancy Rate ; Spermatozoa ; Survival Rate ; Survivors ; Tissue Donors