Nurse Caseload and Patient Survival in Hemodialysis Units: A Korean Nationwide Cohort Study.

INTRODUCTION: The patient-to-nurse ratio is highly variable among dialysis facilities. However, there is little known about the association between nurse caseload and hemodialysis (HD) patient outcomes. We evaluated the association between patient-to-nurse ratio and mortality in the Korean patients undergoing HD. METHODS: We used HD quality assessment data and National Health Insurance Service claim data from the year of 2013 for collecting demographic and clinical data. Altogether, 21,817 patients who participated in the HD quality assessment in 2013 were included in the study. Nurse caseload was defined as the number of HD sessions performed by a nurse per working day. The patients were divided into two groups according to the nurse caseload as follows: low nurse caseload group (≤6.0) and high nurse caseload group (>6.0). We analyzed mortality risk based on nurse caseload using the Cox proportional hazard model. RESULTS: The mean age was 59.1 years, and males accounted for 58.5%. The mean hemoglobin was 10.6 g/dL and albumin was 3.99 g/dL. At the mean follow-up duration of 51.7 (20.6) months, the ratio between low and high groups was 69.6% (15,184 patients) versus 30.4% (6,633 patients). The patients in the high nurse caseload group were older and showed lower levels of hemoglobin, albumin, calcium, and iron saturation and higher levels of phosphorus than those in the low nurse caseload group. A high nurse caseload was associated with a lower survival rate. In the adjusted Cox analysis, a high nurse caseload was an independent risk factor for all-cause mortality (hazard ratio 1.08; 95% confidence interval, 1.02-1.14; p = 0.01). CONCLUSION: High nurse caseload was associated with an increased mortality risk among the patients undergoing HD. Further prospective studies are needed to determine whether a caseload of nursing staff can improve the prognosis of HD patients.

Optimal estimation for regression models on τ-year survival probability.

A logistic regression method can be applied to regressing the [Formula: see text]-year survival probability to covariates, if there are no censored observations before time [Formula: see text]. But if some observations are incomplete due to censoring before time [Formula: see text], then the logistic regression cannot be applied. Jung (1996) proposed to modify the score function for logistic regression to accommodate the right-censored observations. His modified score function, motivated for a consistent estimation of regression parameters, becomes a regular logistic score function if no observations are censored before time [Formula: see text]. In this article, we propose a modification of Jung's estimating function for an optimal estimation for the regression parameters in addition to consistency. We prove that the optimal estimator is more efficient than Jung's estimator. This theoretical comparison is illustrated with a real example data analysis and simulations.

Metabolic versatility of toluene-degrading, iron-reducing bacteria in tidal flat sediment, characterized by stable isotope probing-based metagenomic analysis.

DNA stable isotope probing and metagenomic sequencing were used to assess the metabolic potential of iron-reducing bacteria involved in anaerobic aromatic hydrocarbon degradation in oil spill-affected tidal flats. In a microcosm experiment, (13) C-toluene was degraded with the simultaneous reduction of Fe(III)-NTA, which was also verified by quasi-stoichiometric (13) C-CO2 release. The metabolic potential of the dominant member affiliated with the genus Desulfuromonas in the heavy DNA fraction was inferred using assembled scaffolds (designated TF genome, 4.40 Mbp with 58.8 GC mol%), which were obtained by Illumina sequencing. The gene clusters with peripheral pathways for toluene and benzoate conversion possessed the features of strict and facultative anaerobes. In addition to the class II-type benzoyl-CoA reductase (Bam) of strict anaerobes, the class I-type (Bcr) of facultative anaerobes was encoded. Genes related to the utilization of various anaerobic electron acceptors, including iron, nitrate (to ammonia), sulfur and fumarate, were identified. Furthermore, genes encoding terminal oxidases (caa3 , cbb3 and bd) and a diverse array of genes for oxidative stress responses were detected in the TF genome. This metabolic versatility may be an adaptation to the fluctuating availability of electron acceptors and donors in tidal flats.

Effectiveness of regdanvimab on mortality in COVID-19 infected patients on hemodialysis.

BACKGROUND: Although several therapeutic agents have been evaluated for the treatment of coronavirus disease 2019 (COVID-19), there are lack of effective and proven treatments for end-stage renal disease (ESRD). The present study aims to evaluate the effectiveness of regdanvimab on mortality in COVID-19-infected patients on hemodialysis (HD). METHODS: We conducted an observational retrospective study in 230 COVID-19-infected patients on HD, of whom 77 (33.5%) were administered regdanvimab alone or in combination with dexamethasone or remdesivir during hospitalization (regdanvimab group) and 153 patients (66.5%) were not (no regdanvimab group). The primary outcome was in-hospital mortality. We compared mortality rates according to the use of regdanvimab and investigated the factors associated with mortality. RESULTS: Fifty-nine deaths occurred during hospitalization, 49 in the no regdanvimab group (32.0%) and 10 in the regdanvimab group (13.0%), and the mortality rate was significantly higher in the no regdanvimab group than that in the regdanvimab group (p = 0.001). Multivariate Cox regression analysis showed that malignancy (p = 0.001), SPO2 of <95% at admission (p = 0.003), and administration of antibiotics and regdanvimab (p = 0.007 and p = 0.002, respectively) were significantly associated factors with mortality. CONCLUSION: Regdanvimab administration is beneficial in improving prognosis in hospitalized COVID-19 patients on HD. Considering the vulnerability to infection and high mortality of ESRD patients, regdanvimab may be considered as a therapeutic option in COVID-19 patients on HD.

Remaining life expectancy of Korean hemodialysis patients: how much longer can they live?

Background: Hemodialysis (HD) patients have a higher mortality rate compared to the general population. However, no study has investigated life expectancy in Korean HD patients so far. Therefore, this study aimed to calculate the remaining life expectancy among Korean maintenance HD patients and compare it to those of the general population as well as HD patients from other countries. Methods: Baseline data were retrieved from HD quality assessment data from 2015. Among the patients over 30 years old who were alive at the beginning of 2016 (20,304 males and 14,264 females), a total of 22,078 (12,621 males and 9,457 females) were still alive at the end of 2021 while 12,490 (7,683 males and 4,807 females) were deceased during 6 years of follow-up. We used the life table method to calculate the expected remaining years of life in 2-year increments. Results: The remaining life expectancies for 60-year-old patients were 11.64 years for males and 14.64 years for females. The average remaining lifetimes of the HD population were only about half of the general population. Diabetic patients demonstrated shorter life expectancy compared to patients with hypertension or glomerulonephritis. The remaining life expectancy of Korean HD patients was similar to that of Japanese and was almost double that of HD patients in Western countries such as Europe and the United States. Conclusion: The HD population shows shorter life expectancy compared to the general population. Longitudinal analysis should be warranted to analyze the effect of advanced dialysis technology on improved survival rates among the HD population.

Prediction of a time-to-event trait using genome wide SNP data.

BACKGROUND: A popular objective of many high-throughput genome projects is to discover various genomic markers associated with traits and develop statistical models to predict traits of future patients based on marker values. RESULTS: In this paper, we present a prediction method for time-to-event traits using genome-wide single-nucleotide polymorphisms (SNPs). We also propose a MaxTest associating between a time-to-event trait and a SNP accounting for its possible genetic models. The proposed MaxTest can help screen out nonprognostic SNPs and identify genetic models of prognostic SNPs. The performance of the proposed method is evaluated through simulations. CONCLUSIONS: In conjunction with the MaxTest, the proposed method provides more parsimonious prediction models but includes more prognostic SNPs than some naive prediction methods. The proposed method is demonstrated with real GWAS data.

Regular laboratory testing and patient survival among patients undergoing maintenance hemodialysis: a Korean nationwide cohort study.

Routine laboratory tests are regularly performed in patients undergoing maintenance hemodialysis (HD) to detect anemia, chronic kidney disease-mineral bone disorders, and cardiovascular disease. More frequent laboratory tests may be associated with better outcomes. However, there is little evidence supporting a specific monitoring interval. This study evaluated the impact of regular laboratory testing on mortality in Korean patients undergoing maintenance HD. We used HD quality assessments, and National Health Insurance Service claims data from October to December 2015. In HD quality assessment, 22 tests are recommended every 1-6 months. A total of 34,950 patients were divided into two groups based on the regularity of laboratory testing. A Cox proportional hazards model was used to assess the effects of regular laboratory tests on patient mortality during a mean follow-up duration of 53.7 months. The proportion of patients with and without regular laboratory testing was 85.6% (n = 29,914) and 14.4% (n = 5036), respectively. Patients who underwent regular laboratory testing had a longer dialysis duration, lower serum phosphorus levels and diastolic blood pressure, and higher hemoglobin and single-pool Kt/V levels than those who did not. After adjusting for demographic and clinical parameters, regular laboratory testing independently reduced mortality risk (hazard ratio, 0.90; 95% confidence interval 0.85-0.95; P < 0.001). Regular laboratory testing was associated with a decreased mortality risk among patients undergoing HD. Management of end-stage kidney disease-related complications based on laboratory tests can improve survival.

The Geriatric Nutritional Risk Index Is an Optimal Evaluation Parameter for Predicting Mortality in Adult All Ages Hemodialysis Patients: A Korean Population-Based Study.

The Geriatric Nutritional Risk Index (GNRI) is a nutritional screening tool used for predicting mortality in patients undergoing hemodialysis (HD). This study investigated the cutoff values for the GNRI for predicting mortality in HD patients using Korean HD quality assessment data from 2015. To identify the optimal GNRI cutoff value, we used Harrell's C-index with multivariate Cox regression models. The highest value of C-index was identified as the cutoff value of GNRI for all-cause mortality in this population. In total, 34,933 patients were included; 90.8 of GNRI was the highest value of C-index, and it was used as a cutoff value to predict mortality; 3311 patients (9.5%) had GNRI values < 90.8, and there were 12,499 deaths during the study period. The mean follow-up period was 53.7 months. The crude mortality rates in patients with GNRI values < 90.8 and ≥ 90.8 were 160.4/1000 and 73.2/1000 person-years respectively. In the fully adjusted Cox model, patients with a GNRI < 90.8 had a 1.78 times higher risk of mortality than those with a GNRI ≥ 90.8. These findings suggest that the optimal GNRI cutoff value is 90.8 for predicting mortality in maintenance HD patients.

Dialysis specialist care and patient survival in hemodialysis facilities: a Korean nationwide cohort study.

BACKGROUND: It is important for the dialysis specialist to provide essential and safe care to hemodialysis (HD) patients. However, little is known about the actual effect of dialysis specialist care on the survival of HD patients. We therefore investigated the influence of dialysis specialist care on patient mortality in a nationwide Korean dialysis cohort. METHODS: We used an HD quality assessment and National Health Insurance Service claims data from October to December 2015. A total of 34,408 patients were divided into two groups according to the proportion of dialysis specialists in their HD unit, as follows: 0%, no dialysis specialist care group, and ≥50%, dialysis specialist care group. We analyzed the mortality risk of these groups using the Cox proportional hazards model after matching propensity scores. RESULTS: After propensity score matching, 18,344 patients were enrolled. The ratio of patients from the groups with and without dialysis specialist care was 86.7% to 13.3%. The dialysis specialist care group showed a shorter dialysis vintage, higher levels of hemoglobin, higher single-pool Kt/V values, lower levels of phosphorus, and lower systolic and diastolic blood pressures than the no dialysis specialist care group. After adjusting demographic and clinical parameters, the absence of dialysis specialist care was a significant independent risk factor for all-cause mortality (hazard ratio, 1.10; 95% confidence interval, 1.03-1.18; p = 0.004). CONCLUSION: Dialysis specialist care is an important determinant of overall patient survival among HD patients. Appropriate care given by dialysis specialists may improve clinical outcomes of patients undergoing HD.

Hemodialysis facility star rating affects mortality in chronic hemodialysis patients: a longitudinal observational cohort study.

BACKGROUND: Many countries have their own hemodialysis (HD) quality assurance programs and star rating systems for HD facilities. However, the effects of HD quality assurance programs on patient mortality are not well understood. Therefore, in the present study, the effects of the Korean HD facility star rating on patient mortality in maintenance HD patients were evaluated. METHODS: This longitudinal, observational cohort study included 35,271 patients receiving HD treatment from 741 facilities. The fivestar ratings of HD facilities were determined based on HD quality assessment data from 2015, which includes 12 quality measures in structural, procedural, and outcome domains. The patients were grouped into high (three to five stars) and low (one or two stars) groups based on HD facility star rating. Cox proportional hazards model was used to evaluate the effects of star rating on patient mortality during the mean follow-up duration of 3 years. RESULTS: The patient ratio between high and low HD facility star rating groups was 82.0% vs. 18.0%. The patients in the low star rating group showed lower single-pool Kt/V and higher calcium and phosphorus levels compared with subjects in the high star rating group. After adjusting for sociodemographic and clinical parameters, the HD facility star rating independently increased the mortality risk (hazard ratio, 1.11; 95% confidence interval, 1.04-1.18; p = 0.002). CONCLUSION: The HD facilities with low star rating showed higher patient mortality.

Cultivation of a highly enriched ammonia-oxidizing archaeon of thaumarchaeotal group I.1b from an agricultural soil.

Nitrification of excess ammonia in soil causes eutrophication of water resources and emission of atmospheric N(2) O gas. The first step of nitrification, ammonia oxidation, is mediated by Archaea as well as Bacteria. The physiological reactions mediated by ammonia-oxidizing archaea (AOA) and their contribution to soil nitrification are still unclear. Results of non-culture-based studies have shown the thaumarchaeotal group I.1b lineage of AOA to be dominant over both AOA of group I.1a and ammonia-oxidizing bacteria in various soils. We obtained from an agricultural soil a highly enriched ammonia-oxidizing culture dominated by a single archaeal population [c. 90% of total cells, as determined microscopically (by fluorescence in situ hybridization) and by quantitative PCR of its 16S rRNA gene]. The archaeon (termed 'strain JG1') fell within thaumarchaeotal group I.1b and was related to the moderately thermophilic archaeon, Candidatus Nitrososphaera gargensis, and the mesophilic archaeon, Ca. Nitrososphaera viennensis with 97.0% and 99.1% 16S rRNA gene sequence similarity respectively. Strain JG1 was neutrophilic (growth range pH 6.0-8.0) and mesophilic (growth range temperature 25-40°C). The optimum temperature of strain JG1 (35-40°C) is > 10°C higher than that of ammonia-oxidizing bacteria (AOB). Membrane analysis showed that strain JG1 contained a glycerol dialkyl glycerol tetraether, GDGT-4, and its regioisomer as major core lipids; this crenarchaeol regioisomer was previously detected in similar abundance in the thermophile, Ca. N. gargensis and has been frequently observed in tropical soils. Substrate uptake assays showed that the affinity of strain JG1 for ammonia and oxygen was much higher than those of AOB. These traits may give a competitive advantage to AOA related to strain JG1 in oligotrophic environments. (13) C-bicarbonate incorporation into archaeal lipids of strain JG1 established its ability to grow autotrophically. Strain JG1 produced a significant amount of N(2) O gas - implicating AOA as a possible source of N(2) O emission from soils. Sequences of archaeal amoA and 16S rRNA genes closely related to those of strain JG1 have been retrieved from various terrestrial environments in which lineage of strain JG1 is likely engaged in autotrophic nitrification.

D-lactic acid production from dry biomass of Hydrodictyon reticulatum by simultaneous saccharification and co-fermentation using Lactobacillus coryniformis subsp. torquens.

D-lactic acid production from dry biomass of the microalga, Hydrodictyon reticulatum, was carried out in a 5-l jar fermentor (initial pH 6, 34 °C using CaCO(3) as a neutralizing agent) through simultaneous saccharification and co-fermentation using the Lactobacillus coryniformis subsp. torquens. After 36 h, 36.6 g lactic acid/l was produced from 80 g H. reticulatum/l in the medium containing 3 g yeast extract/l and 3 g peptone/l in the absence of mineral salts. The maximum productivity, average productivity and yield were 2.38 g/l h, 1.02 g/l h and 45.8 %, respectively. The optical purity of D-Lactic acid ranged from 95.8-99.6 %. H. reticulatum is thus a promising biomass material for the production of D-Lactic acid.

COVID-19-related clinical outcomes among Korean hemodialysis patients.

BACKGROUND: Hemodialysis (HD) patients are more vulnerable to viral epidemics, experiencing higher mortality rates compared to individuals without chronic kidney disease (CKD). This retrospective cohort study sought to demonstrate clinical outcomes and associated factors among coronavirus disease 2019 (COVID-19) confirmed Korean HD patients. METHODS: From February 2020 to November 2021, the COVID-19 Task Force Team collected clinical data for HD patients with confirmed COVID-19 via a self-report survey of nephrologists. The composite outcome included in-hospital mortality, admission to the intensive care unit (ICU), and use of mechanical ventilation. Risk factors associated with clinical outcomes were analyzed among HD patients and compared to those of individuals without CKD using the COVID-19 database from the Korea Disease Control and Prevention Agency. RESULTS: A total of 380 HD patients from 206 facilities were diagnosed with COVID-19. Fever (49.5%) and cough (25.7%) were the two most common initial symptoms. The overall in-hospital fatality rate was 22.4% and even higher among ICU admission cases (64.7%). Non-survivors were older, more frequently developed shortness of breath, and were more likely to come from a nursing hospital. Compared to the age- and sex-matched non-CKD population, HD patients showed greater risk of in-hospital mortality (hazard ratio, 2.07; 95% confidence interval, 1.56-2.75; p < 0.001) and composite outcome (hazard ratio, 3.50; 95% confidence interval, 2.56-4.77; p < 0.001). CONCLUSION: HD patients have a greater risk of in-hospital mortality and morbidity from COVID-19. Special attention should be paid to COVID-19 HD patients when they are older or present with symptoms.

Enrichment and characterization of an autotrophic ammonia-oxidizing archaeon of mesophilic crenarchaeal group I.1a from an agricultural soil.

Soil nitrification is an important process for agricultural productivity and environmental pollution. Though one cultivated representative of ammonia-oxidizing Archaea from soil has been described, additional representatives warrant characterization. We describe an ammonia-oxidizing archaeon (strain MY1) in a highly enriched culture derived from agricultural soil. Fluorescence in situ hybridization microscopy showed that, after 2 years of enrichment, the culture was composed of >90% archaeal cells. Clone libraries of both 16S rRNA and archaeal amoA genes featured a single sequence each. No bacterial amoA genes could be detected by PCR. A [¹³C]bicarbonate assimilation assay showed stoichiometric incorporation of ¹³C into Archaea-specific glycerol dialkyl glycerol tetraethers. Strain MY1 falls phylogenetically within crenarchaeal group I.1a; sequence comparisons to "Candidatus Nitrosopumilus maritimus" revealed 96.9% 16S rRNA and 89.2% amoA gene similarities. Completed growth assays showed strain MY1 to be chemoautotrophic, mesophilic (optimum at 25°C), neutrophilic (optimum at pH 6.5 to 7.0), and nonhalophilic (optimum at 0.2 to 0.4% salinity). Kinetic respirometry assays showed that strain MY1's affinities for ammonia and oxygen were much higher than those of ammonia-oxidizing bacteria (AOB). The yield of the greenhouse gas N2O in the strain MY1 culture was lower but comparable to that of soil AOB. We propose that this new soil ammonia-oxidizing archaeon be designated "Candidatus Nitrosoarchaeum koreensis."

Development of antibiotic marker-free creeping bentgrass resistance against herbicides.

Herbicide-resistant creeping bentgrass plants (Agrostis stolonifera L.) without antibiotic-resistant markers were produced by Agrobacterium-mediated transformation. Embryogenic callus tissues were infected with Agrobacterium tumefaciens EHA105, harboring the bar and the CP4-EPSPS genes for bialaphos and glyphosate resistance. Phosphinothricin-resistant calli and plants were selected. Soil-grown plants were obtained at 14-16 weeks after transformation. Genetic transformation of the selected, regenerated plants was validated by PCR. Southern blot analysis revealed that at least one copy of the transgene was integrated into the genome of the transgenic plants. Transgene expression was confirmed by Northern blot. CP4-EPSPS protein was detected by ELISA. Transgenic plants remained green and healthy when sprayed with Basta, containing 0.5% glufosinate ammonium or glyphosate. The optimized Agrobacterium-mediated transformation method resulted in an average of 9.4% transgenic plants. The results of the present study suggest that the optimized marker-free technique could be used as an effective and reliable method for routine transformation, which may facilitate the development of varieties of new antibiotic-free grass species.

Age-adjusted Charlson comorbidity index score is the best predictor for severe clinical outcome in the hospitalized patients with COVID-19 infection.

ABSTRACT: Aged population with comorbidities demonstrated high mortality rate and severe clinical outcome in the patients with coronavirus disease 2019 (COVID-19). However, whether age-adjusted Charlson comorbidity index score (CCIS) predict fatal outcomes remains uncertain.This retrospective, nationwide cohort study was performed to evaluate patient mortality and clinical outcome according to CCIS among the hospitalized patients with COVID-19 infection. We included 5621 patients who had been discharged from isolation or had died from COVID-19 by April 30, 2020. The primary outcome was composites of death, admission to intensive care unit, use of mechanical ventilator or extracorporeal membrane oxygenation. The secondary outcome was mortality. Multivariate Cox proportional hazard model was used to evaluate CCIS as the independent risk factor for death.Among 5621 patients, the high CCIS (≥ 3) group showed higher proportion of elderly population and lower plasma hemoglobin and lower lymphocyte and platelet counts. The high CCIS group was an independent risk factor for composite outcome (HR 3.63, 95% CI 2.45-5.37, P < .001) and patient mortality (HR 22.96, 95% CI 7.20-73.24, P < .001). The nomogram showed that CCIS was the most important factor contributing to the prognosis followed by the presence of dyspnea (hazard ratio [HR] 2.88, 95% confidence interval [CI] 2.16-3.83), low body mass index < 18.5 kg/m2 (HR 2.36, CI 1.49-3.75), lymphopenia (<0.8 x109/L) (HR 2.15, CI 1.59-2.91), thrombocytopenia (<150.0 x109/L) (HR 1.29, CI 0.94-1.78), anemia (<12.0 g/dL) (HR 1.80, CI 1.33-2.43), and male sex (HR 1.76, CI 1.32-2.34). The nomogram demonstrated that the CCIS was the most potent predictive factor for patient mortality.The predictive nomogram using CCIS for the hospitalized patients with COVID-19 may help clinicians to triage the high-risk population and to concentrate limited resources to manage them.

Clinical outcomes of initially asymptomatic patients with COVID-19: a Korean nationwide cohort study.

BACKGROUND: This study was performed to compare severe clinical outcome between initially asymptomatic and symptomatic infections and to identify risk factors associated with high patient mortality among initially asymptomatic patients. METHODS: In this retrospective, nationwide cohort study, we included 5621 patients who had been discharged from isolation or died from COVID-19 by 30 April 2020. The mortality rate and admission rate to intensive care unit (ICU) were compared between initially asymptomatic and symptomatic patients. We established a prediction model for patient mortality through risk factor analysis among initially asymptomatic patients. RESULTS: The prevalence of initially asymptomatic patients upon admission was 25.8%. The mortality rates were not different between groups (3.3% vs. 4.5%, p = .17). However, initially symptomatic patients were more likely to receive ICU care compared to initially asymptomatic patients (4.1% vs. 1.0%, p < .0001). The age-adjusted Charlson comorbidity index score (CCIS) was the most potent predictor for patient mortality in initially asymptomatic patients. CONCLUSIONS: The mortality risk was not determined by the initial presence of symptom among hospitalized COVID-19 patients. The CCIS was the most potent predictors for mortality. The clinicians should predict the risk of death by evaluating age and comorbidities but not the initial presence of symptom. Key messages The mortality rate was not different between initially asymptomatic and symptomatic patients. Symptomatic patients were more likely to admitted to the intensive care unit. Age and comorbidities were the potent risk factors for mortality.

Gradient lasso for Cox proportional hazards model.

MOTIVATION: There has been an increasing interest in expressing a survival phenotype (e.g. time to cancer recurrence or death) or its distribution in terms of a subset of the expression data of a subset of genes. Due to high dimensionality of gene expression data, however, there is a serious problem of collinearity in fitting a prediction model, e.g. Cox's proportional hazards model. To avoid the collinearity problem, several methods based on penalized Cox proportional hazards models have been proposed. However, those methods suffer from severe computational problems, such as slow or even failed convergence, because of high-dimensional matrix inversions required for model fitting. We propose to implement the penalized Cox regression with a lasso penalty via the gradient lasso algorithm that yields faster convergence to the global optimum than do other algorithms. Moreover the gradient lasso algorithm is guaranteed to converge to the optimum under mild regularity conditions. Hence, our gradient lasso algorithm can be a useful tool in developing a prediction model based on high-dimensional covariates including gene expression data. RESULTS: Results from simulation studies showed that the prediction model by gradient lasso recovers the prognostic genes. Also results from diffuse large B-cell lymphoma datasets and Norway/Stanford breast cancer dataset indicate that our method is very competitive compared with popular existing methods by Park and Hastie and Goeman in its computational time, prediction and selectivity. AVAILABILITY: R package glcoxph is available at http://datamining.dongguk.ac.kr/R/glcoxph.

Selective inhibitory potential of silver nanoparticles on the harmful cyanobacterium Microcystis aeruginosa.

Silver nanoparticles (SNPs) at 1 mg/l inhibited the growth of the toxic cyanobacterium, Microcystis aeruginosa, by 87%. Similar results were obtained in field experiments. M. aeruginosa was more sensitive to SNPs than were green algae. SNPs may be a useful selective biocidal agent for the control of M. aeruginosa.

Bioethanol Production from Hydrodictyon reticulatum by Fed-Batch Fermentation Using Saccharomyces cerevisiae KCTC7017.

The aim of this study was to develop a potential process for bioethanol production from Hydrodictyon reticulatum (HR), a filamentous freshwater alga, using Saccharomyces cerevisiae (KCTC7017). From the sugar solutions prepared by the four different hydrolysis methods, bioethanol production ranged from 11.0 g/100 g dried material (acid hydrolysis) to 22.3 g/ 100 g dried material (enzymatic hydrolysis, EH). Bioethanol was fermented from a highly concentrated sugar solution obtained by a decompression-mediated (vacuum) enrichment method (VE). As the results, ethanol was more efficiently produced from HR when sugar solutions were concentrated by VE following EH (EH/VE). Using multiple feeding of the sugar solution prepared by EH/VE from HR, ethanol reached up to a concentration of 54.3 g/l, corresponding to 24.9 g/100 g dried material, which attained the economic level of product concentration (approximately 5%). The results indicate that by using HR, it is feasible to establish a bioethanol production process, which is effective for using microalgae as the raw material for ethanol production.