Lesion-aware cross-phase attention network for renal tumor subtype classification on multi-phase CT scans.

Multi-phase computed tomography (CT) has been widely used for the preoperative diagnosis of kidney cancer due to its non-invasive nature and ability to characterize renal lesions. However, since enhancement patterns of renal lesions across CT phases are different even for the same lesion type, the visual assessment by radiologists suffers from inter-observer variability in clinical practice. Although deep learning-based approaches have been recently explored for differential diagnosis of kidney cancer, they do not explicitly model the relationships between CT phases in the network design, limiting the diagnostic performance. In this paper, we propose a novel lesion-aware cross-phase attention network (LACPANet) that can effectively capture temporal dependencies of renal lesions across CT phases to accurately classify the lesions into five major pathological subtypes from time-series multi-phase CT images. We introduce a 3D inter-phase lesion-aware attention mechanism to learn effective 3D lesion features that are used to estimate attention weights describing the inter-phase relations of the enhancement patterns. We also present a multi-scale attention scheme to capture and aggregate temporal patterns of lesion features at different spatial scales for further improvement. Extensive experiments on multi-phase CT scans of kidney cancer patients from the collected dataset demonstrate that our LACPANet outperforms state-of-the-art approaches in diagnostic accuracy.

Cross-domain Denoising for Low-dose Multi-frame Spiral Computed Tomography.

Computed tomography (CT) has been used worldwide as a non-invasive test to assist in diagnosis. However, the ionizing nature of X-ray exposure raises concerns about potential health risks such as cancer. The desire for lower radiation doses has driven researchers to improve reconstruction quality. Although previous studies on low-dose computed tomography (LDCT) denoising have demonstrated the effectiveness of learning-based methods, most were developed on the simulated data. However, the real-world scenario differs significantly from the simulation domain, especially when using the multi-slice spiral scanner geometry. This paper proposes a two-stage method for the commercially available multi-slice spiral CT scanners that better exploits the complete reconstruction pipeline for LDCT denoising across different domains. Our approach makes good use of the high redundancy of multi-slice projections and the volumetric reconstructions while leveraging the over-smoothing issue in conventional cascaded frameworks caused by aggressive denoising. The dedicated design also provides a more explicit interpretation of the data flow. Extensive experiments on various datasets showed that the proposed method could remove up to 70% of noise without compromised spatial resolution, while subjective evaluations by two experienced radiologists further supported its superior performance against state-of-the-art methods in clinical practice. Code is available at https://github.com/YCL92/TMD-LDCT.

Deep Learning-Based Evaluation of Ultrasound Images for Benign Skin Tumors.

In this study, a combined convolutional neural network for the diagnosis of three benign skin tumors was designed, and its effectiveness was verified through quantitative and statistical analysis. To this end, 698 sonographic images were taken and diagnosed at the Department of Dermatology at Severance Hospital in Seoul, Korea, between 10 November 2017 and 17 January 2020. Through an empirical process, a convolutional neural network combining two structures, which consist of a residual structure and an attention-gated structure, was designed. Five-fold cross-validation was applied, and the train set for each fold was augmented by the Fast AutoAugment technique. As a result of training, for three benign skin tumors, an average accuracy of 95.87%, an average sensitivity of 90.10%, and an average specificity of 96.23% were derived. Also, through statistical analysis using a class activation map and physicians' findings, it was found that the judgment criteria of physicians and the trained combined convolutional neural network were similar. This study suggests that the model designed and trained in this study can be a diagnostic aid to assist physicians and enable more efficient and accurate diagnoses.

Selective attachment of prokaryotes and emergence of potentially pathogenic prokaryotes on four plastic surfaces: Adhesion study in a natural marine environment.

This study employed 16S rRNA metabarcoding to establish the diversity of prokaryotic communities and specific characteristics of potentially pathogenic prokaryotic primary colonizers of four plastic materials (EPS, expanded polystyrene; PE, polyethylene; PP, polypropylene; and PET, polyethylene terephthalate). Bacteria inhabiting plastic and seawater differ; thus, distinct changes in the attached prokaryotic community were observed over an exposure time of 21 days, specifically on Days 3, 6, 9, and 12-21. Frist colonizers were Gammaproteobacteria and Alphaproteobacteria; Bacilli and Clostridia represented secondary colonizers. On Day 3, Pseudoalteromonas had a relative abundance >80 %; whereas, the prevalence of Vibrio spp. (potentially pathogenic prokaryotes) increased rapidly on Days 6 and 9. However, after Day 12, the prevalence of other potential pathogens, namely, Clostridium spp., steadily increased. Despite the diversity of the plastic surfaces, attached prokaryotes changed over time instead of showing similar adherent diversity in all plastic materials.

Risk-aware survival time prediction from whole slide pathological images.

Deep-learning-based survival prediction can assist doctors by providing additional information for diagnosis by estimating the risk or time of death. The former focuses on ranking deaths among patients based on the Cox model, whereas the latter directly predicts the survival time of each patient. However, it is observed that survival time prediction for the patients, particularly with close observation times, possibly has incorrect orders, leading to low prediction accuracy. Therefore, in this paper, we present a whole slide image (WSI)-based survival time prediction method that takes advantage of both the risk as well as time prediction. Specifically, we propose to combine these two approaches by extracting the risk prediction features and using them as guides for the survival time prediction. Considering the high resolution of WSIs, we extract tumor patches from WSIs using a pre-trained tumor classifier and apply the graph convolutional network to aggregate information across these patches effectively. Extensive experiments demonstrate that the proposed method significantly improves the time prediction accuracy when compared with direct prediction of the survival times without guidance and outperforms existing methods.

A Unified Multi-Phase CT Synthesis and Classification Framework for Kidney Cancer Diagnosis With Incomplete Data.

Multi-phase computed tomography (CT) is widely adopted for the diagnosis of kidney cancer due to the complementary information among phases. However, the complete set of multi-phase CT is often not available in practical clinical applications. In recent years, there have been some studies to generate the missing modality image from the available data. Nevertheless, the generated images are not guaranteed to be effective for the diagnosis task. In this paper, we propose a unified framework for kidney cancer diagnosis with incomplete multi-phase CT, which simultaneously recovers missing CT images and classifies cancer subtypes using the completed set of images. The advantage of our framework is that it encourages a synthesis model to explicitly learn to generate missing CT phases that are helpful for classifying cancer subtypes. We further incorporate lesion segmentation network into our framework to exploit lesion-level features for effective cancer classification in the whole CT volumes. The proposed framework is based on fully 3D convolutional neural networks to jointly optimize both synthesis and classification of 3D CT volumes. Extensive experiments on both in-house and external datasets demonstrate the effectiveness of our framework for the diagnosis with incomplete data compared with state-of-the-art baselines. In particular, cancer subtype classification using the completed CT data by our method achieves higher performance than the classification using the given incomplete data.

Deep learning for end-to-end kidney cancer diagnosis on multi-phase abdominal computed tomography.

In 2020, it is estimated that 73,750 kidney cancer cases were diagnosed, and 14,830 people died from cancer in the United States. Preoperative multi-phase abdominal computed tomography (CT) is often used for detecting lesions and classifying histologic subtypes of renal tumor to avoid unnecessary biopsy or surgery. However, there exists inter-observer variability due to subtle differences in the imaging features of tumor subtypes, which makes decisions on treatment challenging. While deep learning has been recently applied to the automated diagnosis of renal tumor, classification of a wide range of subtype classes has not been sufficiently studied yet. In this paper, we propose an end-to-end deep learning model for the differential diagnosis of five major histologic subtypes of renal tumors including both benign and malignant tumors on multi-phase CT. Our model is a unified framework to simultaneously identify lesions and classify subtypes for the diagnosis without manual intervention. We trained and tested the model using CT data from 308 patients who underwent nephrectomy for renal tumors. The model achieved an area under the curve (AUC) of 0.889, and outperformed radiologists for most subtypes. We further validated the model on an independent dataset of 184 patients from The Cancer Imaging Archive (TCIA). The AUC for this dataset was 0.855, and the model performed comparably to the radiologists. These results indicate that our model can achieve similar or better diagnostic performance than radiologists in differentiating a wide range of renal tumors on multi-phase CT.

Antarctic freshwater microalga, Chloromonas reticulata, suppresses inflammation and carcinogenesis.

Inflammation triggered by the innate immune system is a strategy to protect organisms from the risk of environmental infection. However, it has recently become clear that inflammation can cause a variety of human diseases, including cancer. In this study, we investigated the effects of an ethanol extract of the Antarctic freshwater microalgae, Chloromonas reticulata (ETCH), on inflammation and carcinogenesis in RAW 264.7 macrophages and HCT116 human colon cancer cells, respectively. ETCH exhibited significant anti-inflammatory activity through the dose-dependent modulation of major inflammatory markers such as COX-2, IL-6, iNOS, TNF-α, and NO production. For example, ETCH reduced LPS-induced upregulation of COX-2, IL-6, iNOS, and TNF- alpha mRNA levels, leading to a significant decrease in the levels of LPS-stimulated NO and IL-6 as well as TNF-alpha products. In contract, ETCH exhibited dose-dependent cytotoxic activity against HCT116 cells, yielding a profound reduction in the proliferation of the cancer cells. Furthermore, ETCH induced G2 phase cell cycle arrest by transcriptionally regulating of genes involved in G2 / M transition including p21 (CDKN1A), cyclin B1 (CCNB1), and CDK1; CDKN1A mRNA levels were upregulated in response to ETCH, whereas CCNB1 and CDK1 were downregulated. This study reports for the first time anti-inflammatory and anti-cancer effects of, C. reticulata and provides new insights into the molecular mechanisms of the linkage between inflammation and cancer.

Anti-inflammation and Anti-Cancer Activity of Ethanol Extract of Antarctic Freshwater Microalga, Micractinium sp.

Inflammation mediated by the innate immune system is an organism's protective mechanism against infectious environmental risk factors. It is also a driver of the pathogeneses of various human diseases, including cancer development and progression. Microalgae are increasingly being focused on as sources of bioactive molecules with therapeutic potential against various diseases. Furthermore, the antioxidant, anti-inflammatory, and anticancer potentials of microalgae and their secondary metabolites have been widely reported. However, the underlying mechanisms remain to be elucidated. Therefore, in this study, we investigated the molecular mechanisms underlying the anti-inflammatory and anticancer activities of the ethanol extract of the Antarctic freshwater microalga Micractinium sp. (ETMI) by several in vitro assays using RAW 264.7 macrophages and HCT116 human colon cancer cells. ETMI exerted its anti-inflammatory activity by modulating the main inflammatory indicators such as cyclooxygenase (COX)-2, interleukin (IL)-6, inducible nitric oxide synthase (iNOS), tumor necrosis factor (TNF)-α, and nitric oxide (NO) in a dose-dependent manner. In addition, ETMI exerted cytotoxic activity against HCT116 cells in a dose-dependent manner, leading to significantly reduced cancer cell proliferation. Further, it induced cell cycle arrest in the G1 phase through the regulation of hallmark genes of the G1/S phase transition, including CDKN1A, and cyclin-dependent kinase 4 and 6 (CDK4 and CDK6, respectively). At the transcriptional level, the expression of CDKN1A gradually increased in response to ETMI treatment while that of CDK4 and CDK6 decreased. Taken together, our findings suggest that the anti-inflammatory and anticancer activities of the Antarctic freshwater microalga, Micractinium sp., and ETMI may provide a new clue for understanding the molecular link between inflammation and cancer and that ETMI may be a potential anticancer agent for targeted therapy of colorectal cancer.

Mapping distribution of cysts of recent dinoflagellate and Cochlodinium polykrikoides using next-generation sequencing and morphological approaches in South Sea, Korea.

The total dinoflagellate cyst community and the cysts of Cochlodinium polykrikoides in the surface sediments of South Sea (Tongyeong coast), South Korea, were analysed using next-generation sequencing (NGS) and morphological approaches. Dinoflagellate cysts can be highly abundant (111-4,087 cysts g-1 dry weight) and have diverse species composition. A total of 35 taxa of dinoflagellate cysts representing 16 genera, 21 species (including four unconfirmed species), and 14 complex species were identified by NGS analysis. Cysts of Scrippsiella spp (mostly Scrippsiella trochoidea) were the most dominant and Polykrikos schwartzii, Pentapharsodinium dalei, Ensiculifera carinata, and Alexandrium catenella/tamarense were common. Thus, a combination of NGS and morphological analysis is effective for studying the cyst communities present in a given environment. Although C. polykrikoides developed massive blooms during 2013-2014, microscopy revealed low density of their cysts, whereas no cysts were detected by NGS. However, the vegetative C. polykrikoides not appeared during 2015-2017 in spite of the observation of C. polykrikoides cysts. This suggests that the C. polykrikoides blooms were not due to development of their cysts but to other factors such as currents transporting them to a marine environment suitable for their growth.

Combined Effects of UV Exposure Duration and Mechanical Abrasion on Microplastic Fragmentation by Polymer Type.

It is important to understand the fragmentation processes and mechanisms of plastic litter to predict microplastic production in the marine environment. In this study, accelerated weathering experiments were performed in the laboratory, with ultraviolet (UV) exposure for up to 12 months followed by mechanical abrasion (MA) with sand for 2 months. Fragmentation of low-density polyethylene (PE), polypropylene (PP), and expanded polystyrene (EPS) was evaluated under conditions that simulated a beach environment. PE and PP were minimally fragmented by MA without photooxidation by UV (8.7 ± 2.5 and 10.7 ± 0.7 particles/pellet, respectively). The rate of fragmentation by UV exposure duration increased more for PP than PE. A 12-month UV exposure and 2-month MA of PP and PE produced 6084 ± 1061 and 20 ± 8.3 particles/pellet, respectively. EPS pellets were susceptible to MA alone (4220 ± 33 particles/pellet), while the combination of 6 months of UV exposure followed by 2 months of MA produced 12,152 ± 3276 particles/pellet. The number of fragmented polymer particles produced by UV exposure and mechanical abrasion increased with decreasing size in all polymer types. The size-normalized abundance of the fragmented PE, PP, and EPS particles according to particle size after UV exposure and MA was predictable. Up to 76.5% of the initial EPS volume was unaccounted for in the final volume of pellet produced particle fragments, indicating that a large proportion of the particles had fragmented into undetectable submicron particles.

Noninvasive predictors of nonalcoholic steatohepatitis in Korean patients with histologically proven nonalcoholic fatty liver disease.

BACKGROUND/AIMS: The aims of this study were (1) to identify the useful clinical parameters of noninvasive approach for distinguishing nonalcoholic steatohepatitis (NASH) from nonalcoholic fatty liver disease (NAFLD), and (2) to determine whether the levels of the identified parameters are correlated with the severity of liver injury in patients with NASH. METHODS: One hundred and eight consecutive patients with biopsy-proven NAFLD (age, 39.8±13.5 years, mean±SD; males, 67.6%) were prospectively enrolled from 10 participating centers across Korea. RESULTS: According to the original criteria for NAFLD subtypes, 67 patients (62.0%) had NASH (defined as steatosis with hepatocellular ballooning and/or Mallory-Denk bodies or fibrosis ≥2). Among those with NAFLD subtype 3 or 4, none had an NAFLD histologic activity score (NAS) below 3 points, 40.3% had a score of 3 or 4 points, and 59.7% had a score >4 points. Fragmented cytokeratin-18 (CK-18) levels were positively correlated with NAS (r=0.401), as well as NAS components such as lobular inflammation (r=0.387) and ballooning (r=0.231). Fragmented CK-18 was also correlated with aspartate aminotransferase (r=0.609), alanine aminotransferase (r=0.588), serum ferritin (r=0.432), and the fibrosis stage (r=0.314). A fragmented CK-18 cutoff level of 235.5 U/L yielded sensitivity, specificity, and positive and negative predictive values of 69.0%, 64.9%, 75.5% (95% CI 62.4-85.1), and 57.1% (95% CI 42.2-70.9), respectively, for the diagnosis of NASH. CONCLUSIONS: Serum fragmented CK-18 levels can be used to distinguish between NASH and NAFL. Further evaluation is required to determine whether the combined measurement of serum CK-18 and ferritin levels improves the diagnostic performance of this distinction.

A Case of Endobronchial Aspergilloma Associated with Foreign Body in Immunocompetent Patient without Underlying Lung Disease.

Aspergillus causes a variety of clinical syndromes in the lung including tracheobronchial aspergillosis, invasive aspergillosis, chronic necrotizing pulmonary aspergillosis, allergic bronchopulmonary aspergillosis, and aspergilloma. Aspergilloma usually results from ingrowths of colonized Aspergillus in damaged bronchial tree, pulmonary cyst or cavities of patients with underlying lung diseases. There are a few reports on endobronchial aspergilloma without underlying pulmonary lesion. We have experienced a case of endobronchial aspergilloma associated with foreign body developed in an immunocompetent patient without underlying lung diseases. A 59-year-old man is being hospitalized with recurring hemoptysis for 5 months. X-ray and computed tomography scans of chest showed a nodular opacity in superior segment of left lower lobe. Fiberoptic bronchoscopy revealed an irregular, mass-like, brownish material which totally obstructed the sub-segmental bronchus and a foreign body in superior segmental bronchus of the lower left lobe. Histopathologic examinations of biopsy specimen revealed fungal hyphae, characteristic of Aspergillus species.

Diagnostic value of AFP-L3 and PIVKA-II in hepatocellular carcinoma according to total-AFP.

AIM: To evaluate diagnostic value of α-fetoprotein (AFP)-L3 and prothrombin induced by vitamin K absence-II (PIVKA-II) in hepatocellular carcinoma (HCC). METHODS: One hundred and sixty-eight patients during routine HCC surveillance were included in this study. Of the 168 patients, 90 (53.6%) had HCC including newly developed HCC (n = 82) or recurrent HCC after treatment (n = 8). Sera were obtained during their first evaluation for HCC development and at the time of HCC diagnosis before commencing HCC treatment. HCC was diagnosed by histological examination, appropriate imaging characteristics-computed tomography or magnetic resonance imaging. Control sera were collected from 78 patients with benign liver disease (BLD), which were obtained during routine surveillance with a suspicion of HCC. AFP, AFP-L3 and PIVKA-II were measured in the same serum by microchip capillary electrophoresis and liquid-phase binding assay on a micro-total analysis system Wako i30 auto analyzer. The performance characteristics of three tests and combined tests for the diagnosis of HCC were obtained using receiver operating characteristic curves in all populations and subgroups with AFP < 20 ng/mL. RESULTS: Of 90 HCC patients, 38 (42.2%) patients had AFP < 20 ng/mL, 20 (22.2%) patients had AFP 20-200 ng/mL and 32 (35.6%) patients had AFP > 200 ng/mL. Of the 78 BLD patients, 74 (94.9%) patients had AFP < 20 ng/mL. After adjustment for age and HBV infection status, AFP-L3 levels were higher in HCC than in BLD among patients with low AFP levels (< 20 ng/mL) (P < 0.001). In a total of 168 patients, areas under the curve (AUC) for HCC were 0.879, 0.887, 0.801 and 0.939 for AFP, AFP-L3, PIVKA-II and the combined markers, respectively. The combined AUC for three markers showed higher value than the AUCs of individual marker (P < 0.05). AFP-L3 had higher AUC value than PIVKA-II for HCC detection in entire patients (P = 0.043). With combination of AFP-L3 (cut-off > 5%) and PIVKA-II (cut-off > 40 AU/L), the sensitivity were 94.4% and specificity were 75.6% in all patients. In 112 patients with low AFP levels (< 20 ng/mL), AUCs of AFP-L3, PIVKA-II and combine AFP-L3 and PIVKA-II tests were 0.824, 0.774 and 0.939, respectively. AFP-L3 with a cut-off value of 5% showed sensitivity of 71.1% and specificity of 83.8%, and PIVKA-II with a cut-off value of 40 AU/L had sensitivity of 57.9% and specificity of 95.9% in patients with low AFP levels. The combination of AFP-L3 and PIVKA-II increased the sensitivity and specificity up to 92.1% and 79.7%, respectively, in low AFP group. Combined markers detected 81.8% of early stage HCC (Union for International Cancer Control stage I), 86.7% of small sized tumor (< 2 cm) and 91.7% of single tumor of HCC in the low AFP group. In multivariate analysis, AFP-L3 was correlated with AFP and tumor size, and PIVKA-II was correlated with laboratory tests including serum aspartate aminotransferase, total bilirubin, platelets and albumin levels. PIVKA-II had no correlation with AFP, AFP-L3 or tumor characteristics. CONCLUSION: Combined determination of AFP-L3 and PIVKA-II could improve the diagnostic value for HCC detection in patients with or without increased AFP levels.

Mesocosm study on weathering characteristics of Iranian Heavy crude oil with and without dispersants.

The environmental fate of Iranian Heavy crude oil (IHC) with and without an added oil spill dispersant (OSD) has been studied using a 1000 kL capacity in situ mesocosm. Physical weathering and chemical composition changes of the oil were monitored for 77 days. Compound-specific effects of the OSD could be observed as changes over time in the content of the total petroleum hydrocarbon (TPH), unresolved complex mixture (UCM), alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes and steranes in the oil. As oil weathers, most hydrocarbons showed a rapid decreasing phase followed by a slowdown and stabilization. Recalcitrant biomarkers, however, showed a different trend. An increase in hydrocarbon contents in the form of UCM occurred after OSD treatment. The enhanced solubility of the low molecular weight PAHs by the OSD decreased the half-life of the alkylated PAHs in the OD. After 77 days of exposure at the sea surface, both the oils with and without the OSD exhibited moderate weathering. Most of the source diagnostic indices maintained their source information, and the weathering indices indicated that evaporation, dissolution, and dispersion were the major weathering processes. The mass balance of the weathered oil was calculated using laboratory and mesocosm data and the results demonstrate the importance of using a mesocosm for the production of environmentally realistic data.

Stronger impact of dispersant plus crude oil on natural plankton assemblages in short-term marine mesocosms.

To assess the effects of crude oil and dispersant on marine planktonic ecosystems, analyses were performed in 1000-L mesocosm over a period of nine days. Triplicate experiments were conducted for two different treatments, namely, addition of crude oil alone and oil plus dispersant. In the mesocosm with oil plus dispersant, high concentrations of total petroleum hydrocarbon (TPH) were soon found in the bottom layer. In addition, most planktonic communities responded drastically to the presence of dispersant acting to disperse TPH: total bacterial abundances increased for the first two days and then decreased rapidly for the remainder of the experiment. The abundance of heterotrophic flagellates increased rapidly in association with the increase in bacterial cells. The abundance of phytoplankton and zooplankton communities decreased clearly within two days. Time-delayed relationship also revealed that the TPH concentration had a significant negative relationship with phyto- and zooplankton communities within two days. However, most planktonic communities were affected less adversely in the mesocosms treated with crude oil alone than in those treated with both crude oil and dispersant. The present results demonstrate that the planktonic ecosystem was damaged more severely by the introduction of dispersant than by the harmful effects of crude oil itself. Therefore, caution should be taken when considering the direct application of dispersant in natural environments, even though it has the advantage of rapidly removing crude oil.

Cytogenetic characteristics and prognosis analysis in 231 myelodysplastic syndrome patients from a single institution.

We analyzed the clinical and hematologic data of 231 patients diagnosed with de novo myelodysplastic syndrome (MDS), identified cytogenetic characteristics, and evaluated the significance of prognostic systems. The median age was 51 years and the distribution of MDS subtypes demonstrated a markedly low incidence of MDS with deletion 5q (0.9%). The proportions of World Health Organization (WHO) categories differed according to patient age group. Refractory anemia with excess blasts-2 demonstrated the most significant trend toward increased frequency with advancing age. The incidence of abnormal karyotypes in our study was comparable to a previous study (50.2%), although with different patterns. The most frequent cytogenetic abnormality was +8 (34.5% of patients with abnormality), followed by 1q+ (17.2%), 5q- (15.5%), and 20q- (12.9%). Majority of +8, 1q+, -5/5q- and -7/7q- cases combined with additional cytogenetic abnormalities (60.0%, 75.0%, 88.5% and 100%, respectively). The median survival time was 49.5 months and 13.8% patients developed acute leukemia. WHO Prognostic Scoring System (WPSS) and age group were significant factors associated with overall survival. Otherwise, International Prognostic Scoring System was not included in the model. These results demonstrated the different cytogenetic features in Korean MDS patients compared to those of Western country. In addition, WPSS and age group are applicable to our patients as an effective and reliable prognostic model.

Effects of crude oil on marine microbial communities in short term outdoor microcosms.

To assess the effects of crude oil spills on marine microbial communities, 10 L outdoor microcosms were manipulated over an exposure period of 8 days. The responses of microbial organisms exposed to five crude oil concentrations in 10 to 10,000 ppm (v/v) were monitored in the microcosms. The abundance of microalgae and copepods decreased rapidly upon the addition of crude oil at concentrations over 1,000 ppm, whereas the total density of heterotrophic bacteria increased dramatically at the higher concentrations. Bacterial diversity, determined by denaturing gradient gel electrophoresis, was increased at higher concentrations. In particular, the intensity of the bands representing Jannaschia sp. and Sulfitobacter brevis increased with the addition of oil. These results indicate that crude oil spills with concentrations over 1,000 ppm seriously affected the structure of the microbial communities.

[Usefulness of real-time semi-quantitative PCR, JAK2 MutaScreen kit for JAK2 V617F screening].

BACKGROUND: Real-time PCR for quantification of JAK2 V617F has recently been introduced and used to evaluate the importance of mutant allele burden in both diagnosis and disease progression in myeloproliferative diseases (MPDs). We evaluated the usefulness of JAK2 MutaScreen kit that uses a real-time semiquantitative PCR method and has been designed to screen JAK2 V617F mutant allele burden. METHODS: Forty MPD patients were included in this study. We screened JAK2 V617F and determined the mutant allele burden using JAK2 MutaScreen kit. The mutant allele burden was estimated by six-scaled standards of JAK2 V617F mutant allele (2%, 5%, 12.5%, 31%, 50%, and 78%). For evaluation of test performance, an allele-specific PCR (AS-PCR) was carried out in all samples by using Seeplex JAK2 Genotyping kit. We assessed the clinical differences in distinct disease entities of MPDs according to JAK2 V617F mutant allele burden. RESULTS: JAK2 V617F mutation was detected in 30 cases, including 10 of 11 cases (91%) of polycythemia vera (PV), 13 of 20 cases (65%) of essential thrombocythemia (ET), and 2 of 3 cases (67%) of chronic idiopathic myelofibrosis (CIMF). The concordance rate between the two tests was 95% (38/40). JAK2 V617F mutant allele burden was greater than 50% in 17 cases, and 10 of them (59%) were PV. In contrast, mutant allele burden was less than 50% in 13 cases and 11 of them (85%) were ET. CONCLUSIONS: JAK2 MutaScreen kit that utilizes a real-time semi-quantitative PCR method is a useful tool for diagnosing MPDs precisely. It can be used to assess the grade of mutant allele burden as well as to screen JAK2 V617F simultaneously.