Background: From our previous study, we established that cyclin A1 (CCNA1) promoter methylation is strongly correlated with multistep progression of HPV-associated cervical cancer, suggesting potential use as a diagnostic maker of disease. Objectives: The purpose of the present study was to assess the prevalence of CCNA1 promoter methylation in residual cervical cells isolated from liquid-based cytology that underwent hrHPV DNA screening for cervical cancer, and then to evaluate this marker for diagnostic accuracy using parameters like sensitivity, specificity, predictive values and likelihood ratio. Methods: In this retrospective study, histopathology was used as the gold standard method with specimens separated into the following groups: negative (n=31), low-grade squamous intraepithelial lesions (LSIL, n=34) and high-grade squamous intraepithelial lesions or worse (HSIL+, n=32). The hrHPV was detected by Hybrid Capture 2 (HC2) and CCNA1 promoter methylation was examined by CCNA1 duplex methylation specific PCR. Results: The results showed the frequencies of CCNA1 promoter methylation were 0%, 5.88% and 83.33%, while the percentages of hrHPV were 66.67%, 82.35% and 100% in the negative, LSIL and HSIL+ groups, respectively. Although hrHPV infection showed high frequency in all three groups, it could not differentiate between the different groups and grades of precancerous lesions. In contrast, CCNA1 promoter methylation clearly distinguished between negative/LSIL and HSIL+, with high levels of all statistic parameters. Conclusion: CCNA1 promoter methylation is a potential marker for distinguishing between histologic negative/LSIL and HSIL+using cervical cytology samples.
Yurim Jang;Ji Hyun Moon;Byung Kwan Jeon;Ho Jin Park;Hong Jin Lee;Do Yup Lee
Journal of Microbiology and Biotechnology
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v.33
no.10
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pp.1351-1360
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2023
Endocrine-disrupting chemicals (EDCs) are compounds that disturb hormonal homeostasis by binding to receptors. EDCs are metabolized through hepatic enzymes, causing altered transcriptional activities of hormone receptors, and thus necessitating the exploration of the potential endocrine-disrupting activities of EDC-derived metabolites. Accordingly, we have developed an integrative workflow for evaluating the post-metabolic activity of potential hazardous compounds. The system facilitates the identification of metabolites that exert hormonal disruption through the integrative application of an MS/MS similarity network and predictive biotransformation based on known hepatic enzymatic reactions. As proof-of-concept, the transcriptional activities of 13 chemicals were evaluated by applying the in vitro metabolic module (S9 fraction). Identified among the tested chemicals were three thyroid hormone receptor (THR) agonistic compounds that showed increased transcriptional activities after phase I+II reactions (T3, 309.1 ± 17.3%; DITPA, 30.7 ± 1.8%; GC-1, 160.6 ± 8.6% to the corresponding parents). The metabolic profiles of these three compounds showed common biotransformation patterns, particularly in the phase II reactions (glucuronide conjugation, sulfation, GSH conjugation, and amino acid conjugation). Data-dependent exploration based on molecular network analysis of T3 profiles revealed that lipids and lipid-like molecules were the most enriched biotransformants. The subsequent subnetwork analysis proposed 14 additional features, including T4 in addition to 9 metabolized compounds that were annotated by prediction system based on possible hepatic enzymatic reaction. The other 10 THR agonistic negative compounds showed unique biotransformation patterns according to structural commonality, which corresponded to previous in vivo studies. Our evaluation system demonstrated highly predictive and accurate performance in determining the potential thyroid-disrupting activity of EDC-derived metabolites and for proposing novel biotransformants.
Background: Hepatocellular carcinoma (HCC) is a major cause of cancer mortality worldwide. The outcome of HCC depends mainly on its early diagnosis. To date, the performance of traditional biomarkers is unsatisfactory. Talins were firstly identified as cytoplasmic protein partners of integrins but Talin-1 appears to play a crucial role in cancer formation and progression. Our study was conducted to assess the diagnostic value of serum Talin-1 (TLN1) compared to the most feasible traditional biomarker alpha-fetoprotein (AFP) for the diagnosis of HCC. Methods: TLN1 was detected using enzyme linked immunosorbent assay (ELISA) in serum samples from 120 Egyptian subjects including 40 with HCC, 40 with liver cirrhosis (LC) and 40 healthy controls (HC). Results: ROC curve analysis was used to create a predictive model for TLN1 relative to AFP in HCC diagnosis. Serum levels of TLN1 in hepatocellular carcinoma patients were significantly higher compared to the other groups (p<0.0001). The diagnostic accuracy of TLN1 was higher than that of AFP regarding sensitivity, specificity, positive predictive value and negative predictive value in diagnosis of HCC. Conclusions: The present study showed for the first time that Talin-1 (TLN1) is a potential diagnostic marker for HCC, with a higher sensitivity and specificity compared to the traditional biomarker AFP.
Kim, Jin-Wook;Han, Jung-Ho;Park, Chul-Kee;Chung, Hyun-Tai;Paek, Sun-Ha;Kim, Dong-Gyu
Journal of Korean Neurosurgical Society
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v.42
no.2
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pp.92-96
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2007
Objective : The authors have speculated that metastatic brain lesions from renal cell carcinoma (RCC) show diverse radiological patterns and tumor responses after Gamma knife surgery (GKS), and have hypothesized that these can be predicted from tumor radiological characteristics. The goal of the current study was to identify the radiological characteristics of RCC brain metastases and the predictors of initial radiosurgical response after GKS. Methods : A retrospective analysis was performed on 48 lesions in 18 patients with RCC brain metastasis treated by GKS. The radiological characteristics of these lesions in magnetic resonance images (MRI) were classified into 3 categories according to enhancement patterns in T1-weighted images and signal intensity characteristics in T2-weighted images. Responses to GKS were analyzed according to these categories, and in addition, other potential predictive factors were also evaluated. Results : MRI findings in the three categories were diverse, though numbers of the lesion were comparable. At 2-month MRI follow-ups after GKS, response rate was 54% and the local tumor control rate 83%. T2 signal intensity was found to be the principal predictive factor of response to GKS, namely negative predictive factor. Other variables such as age, sex, tumor volume, dose, duration from initial diagnosis to GKS, and previous systemic therapies failed to show significant relationships with treatment response by multivariate analysis. Conclusion : Careful evaluation of the radiological characteristics of brain metastases from RCC is important prior to GKS because MRI heterogeneity has predictive value in terms of determining initial tumor response.
Mogendi, Joseph Birundu;De Steur, Hans;Gellynck, Xavier;Saeed, Hibbah Araba;Makokha, Anselimo
Nutrition Research and Practice
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v.9
no.3
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pp.268-277
/
2015
BACKGROUND/OBJECTIVES: Although it is crucial to identify those children likely to be treated in an appropriate nutrition rehabilitation programme and discharge them at the appropriate time, there is no golden standard for such identification. The current study examined the appropriateness of using Mid-Upper Arm Circumference for the identification, follow-up and discharge of malnourished children. We also assessed its discrepancy with the Weight-for-Height based diagnosis, the rate of recovery, and the discharge criteria of the children during nutrition rehabilitation. SUBJECTS/METHODS: The study present findings from 156 children (aged 6-59 months) attending a supplementary feeding programme at Makadara and Jericho Health Centres, Eastern District of Nairobi, Kenya. Records of age, weight, height and mid-upper arm circumference were selected at three stages of nutrition rehabilitation: admission, follow-up and discharge. The values obtained were then used to calculate z-scores as defined by WHO Anthro while estimating different diagnostic indices. RESULTS: Mid-upper arm circumference single cut-off (< 12.5 cm) was found to exhibit high values of sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio at both admission and discharge. Besides, children recorded higher rate of recovery at 86 days, an average increment of 0.98 cm at the rate of 0.14mm/day, and a weight gain of 13.49gm/day, albeit higher in female than their male counterparts. Nevertheless, children admitted on basis of low MUAC had a significantly higher MUAC gain than WH at 0.19mm/day and 0.13mm/day respectively. CONCLUSIONS: Mid-upper arm circumference can be an appropriate tool for identifying malnourished children for admission to nutrition rehabilitation programs. Our results confirm the appropriateness of this tool for monitoring recovery trends and discharging the children thereafter. In principle the tool has potential to minimize nutrition rehabilitation costs, particularly in community therapeutic centres in developing countries.
To evaluate the potential value of $^1H$ Magnetic resonance spectroscopy (MRS) for detecting and characterizing invasive ductal carcinoma of breast. We conducted $^1H$ Magnetic resonance spectroscopy (MRS), using a 3.0T MR scanner, on 40 patients who were histologically diagnosed to have invasive ductal carcinoma (IDC); tumor areas of the patients were designated as experimental samples, and non-tumor areas as control samples. The peak at 3.2 ppm is characteristically intense and observed in 34 cases of the total 40 invasive ductal carcinoma (sensitivity 86.2%; specificity 100%; positive predictive value 100%; negative predictive value 60%). In constrast peak at 1.3 ppm is characteristically intense and observed in normal breast (sensitivity 86.2%; specificity 100%; positive predictive value 100%; negative predictive value 60%). The study shows that $^1H$ MRS can effectively discriminate invasive ductal carcinoma from normal breast in most cases. It also demonstrates the feasibility of localized in vivo $^1H$ MRS technique as a new diagnostic modality in the detection of breast tumor.
Aim: To identify new biomarkers for NPC diagnosis with an anti-EBV Western blot test kit. Methods: Serum samples from 64 NPC patients and healthy subjects with four specific VCA-IgA/EA-IgA profiles were tested with an anti-EBV Western blot test kit from EUROIMMUN AG. Proteins were quantified with scores of intensity visually assigned to the protein bands. The markers which showed statistical differences between the NPC and non-NPC subjects were further evaluated in another 32 NPC patients and 32 controls in comparison with established biomarkers including VCA-IgA, EA-IgA, EBV-related protein IgG, and EBV DNA. Results: Among the markers screened, EA-D p45-IgG showed a statistically significant difference (p < 0.05) between NPC and non-NPC subjects with VCA-IgA positivy. In 32 VCA-IgA positive NPC patients and 32 control subjects, the diagnostic accuracy of EA-D p45-IgG was 78.1% with a positive predictive value of 77.8% and a negative predictive value of 78.6%. In the verification experiment, the specificity and sensitivity of EA-D p45-IgG were 75.0% and 90.6 %, respectively. Conclusions: EA-D p45-IgG might be a potential biomarker for NPC diagnosis, especially among VCA-IgA positive subjects.
Journal of the Korean Society of Environmental Restoration Technology
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v.19
no.6
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pp.19-30
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2016
The projection of climate-related range shift is critical information for conservation planning of Korean fir (Abies koreana E. H. Wilson). We first modeled the distribution of Korean fir under current climate condition using five single-model species distribution models (SDMs) and the pre-evaluation weighted ensemble method and then predicted the distributions under future climate conditions projected with HadGEM2-AO under four $CO_2$ emission scenarios, the Representative Concentration Pathways (RCP) 2.6, 4.5, 6.0 and 8.5. We also investigated the predictive uncertainty stemming from five individual algorithms and four $CO_2$ emission scenarios for better interpretation of SDM projections. Five individual algorithms were Generalized linear model (GLM), Generalized additive model (GAM), Multivariate adaptive regression splines (MARS), Generalized boosted model (GBM) and Random forest (RF). The results showed high variations of model performances among individual SDMs and the wide range of diverging predictions of future distributions of Korean fir in response to RCPs. The ensemble model presented the highest predictive accuracy (TSS = 0.97, AUC = 0.99) and predicted that the climate habitat suitability of Korean fir would increase under climate changes. Accordingly, the fir distribution could expand under future climate conditions. Increasing precipitation may account for increases in the distribution of Korean fir. Increasing precipitation compensates the negative effects of increasing temperature. However, the future distribution of Korean fir is also affected by other ecological processes, such as interactions with co-existing species, adaptation and dispersal limitation, and other environmental factors, such as extreme weather events and land-use changes. Therefore, we need further ecological research and to develop mechanistic and process-based distribution models for improving the predictive accuracy.
Purpose: The aim of the current study was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the potential usefulness and accuracy of this system for the diagnosis and prediction of periodontally compromised teeth (PCT). Methods: Combining pretrained deep CNN architecture and a self-trained network, periapical radiographic images were used to determine the optimal CNN algorithm and weights. The diagnostic and predictive accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve, area under the ROC curve, confusion matrix, and 95% confidence intervals (CIs) were calculated using our deep CNN algorithm, based on a Keras framework in Python. Results: The periapical radiographic dataset was split into training (n=1,044), validation (n=348), and test (n=348) datasets. With the deep learning algorithm, the diagnostic accuracy for PCT was 81.0% for premolars and 76.7% for molars. Using 64 premolars and 64 molars that were clinically diagnosed as severe PCT, the accuracy of predicting extraction was 82.8% (95% CI, 70.1%-91.2%) for premolars and 73.4% (95% CI, 59.9%-84.0%) for molars. Conclusions: We demonstrated that the deep CNN algorithm was useful for assessing the diagnosis and predictability of PCT. Therefore, with further optimization of the PCT dataset and improvements in the algorithm, a computer-aided detection system can be expected to become an effective and efficient method of diagnosing and predicting PCT.
Purpose : Early identification of developmental disabilities allows intervention at the earliest possible point to improve the developmental potential. The Ages and Stages Questionnaire (ASQ), a parent- completed questionnaire, can be used as a substitute for formal screening tests. The purpose of this study was to evaluate the validity of the Korean version of the ASQ (K-ASQ) as a screening tool for detecting developmental delay of young Korean children in the setting of a busy pediatric outpatient clinic. Methods : Parents completed the K-ASQ in the waiting room of the pediatric outpatient clinic of St. Mary's Hospital, Catholic University Medical College. Out of 150 completed the ASQ, 67 who were born term and had no previous diagnosis of developmental delay, congenital anomalies, or neurological abnormalities were enrolled. The cut-off values of less than 2 standard deviations (SD) below the mean for the ASQ were used to define a "fail", and children who failed in one or more domains tested were classified as "screen-positive". Diagnosis of developmental delay was made when the developmental indices fell below -1 SD of the Bayley Scales of Infant Development-II. Results : (1) The mean age of children was $16.4{\pm}7.4$ months. Ten children (14.9%) were small-for- gestational age infants. The mean birth weight and gestational age were $3.1{\pm}0.6kg$ and $38.8{\pm}1.4$ weeks. Nine children (13.4%) were twins and 33 (49.0%) were male. The mean maternal education in years was $13.6{\pm}2.4$, and 31.3% had full-time jobs. The time for completing the ASQ was $10.2{\pm}3.0$ minutes. (2) Seventeen children (25.4%) were classified as screen-positive, four of them were delayed in development. Among eight children diagnosed with developmental delay, four were screen-positive and the other four were screen-negative by the ASQ. (3) The test characteristics of the ASQ were as follows: sensitivity (50.0%); specificity (78.0%); positive predictive value (23.5%); negative predictive value (92.0%). Conclusion : The high negative predictive value of the K-ASQ supports its use as a screening tool for developmental delay in the setting of a pediatric outpatient clinic.
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