Revealing Cryptic Changes of Cyanobacterial Community Structure in Two Eutrophic Lakes Using eDNA Sequencing.

Harmful cyanobacterial blooms pose a risk to human health worldwide. To enhance understanding on the bloom-forming mechanism, the spatiotemporal changes in cyanobacterial diversity and composition in two eutrophic lakes (Erhai Lake and Lushui Reservoir) of China were investigated from 2010 to 2011 by high-throughput sequencing of environmental DNA. For each sample, 118 to 260 cpcBA-IGS operational taxonomic units (OTUs) were obtained. Fifty-two abundant OTUs were identified, which made up 95.2% of the total sequences and were clustered into nine cyanobacterial groups. Although the cyanobacterial communities of both lakes were mainly dominated by Microcystis, Erhai Lake had a higher cyanobacterial diversity. The abundance of mixed Nostocales species was lower than that of Microcystis, whereas Phormidium and Synechococcus were opportunistically dominant. The correlation between the occurrence frequency and relative abundance of OTUs was poorly fitted by the Sloan neutral model. Deterministic processes such as phosphorus availability were shown to have significant effects on the cyanobacterial community structure in Erhai Lake. In summary, the Microcystis-dominated cyanobacterial community was mainly affected by the deterministic process. Opportunistically dominant species have the potential to replace Microcystis and form blooms in eutrophic lakes, indicating the necessity to monitor these species for drinking water safety.

New therapy with XLQ® to suppress chronic prostatitis through its anti-inflammatory and antioxidative activities.

Chronic prostatitis is a common urological disease. The etiology of this disease and effective therapy for its treatment are yet to be elucidated. We investigated the functions of XLQ® in chronic nonbacterial prostatitis using a complete Freund's adjuvant-induced rat model. Prostates and blood samples were collected for further evaluation after oral gavage with XLQ ® or a vehicle for 4 weeks. The results showed that XLQ ® significantly decreased the prostate index, ameliorated the histopathologic changes, and reduced CD3+ and CD45+ cell infiltration in the prostate stroma. Further study showed that XLQ ® suppressed the expression of proinflammatory cytokines, such as interleukin (IL)-1ß, IL-2, IL-6, IL-17A, monocyte chemoattractant protein-1, and tumor necrosis factor-α. XLQ ® showed a strong antioxidant capacity by enhancing the activities of antioxidative enzymes (e.g., total superoxide dismutase, catalase, and glutathione peroxidase) and decreasing the level of lipid peroxidation products (malondialdehyde). Moreover, XLQ ® can suppress the activation of nuclear factor-κB and P38-mitogen-activated protein kinase signaling pathways. In summary, XLQ ® has affirmative effects on chronic prostatitis, which could be attributed to its anti-inflammatory and antioxidative capacities. On the basis of these results, XLQ ® can be developed as an effective and safe therapy for chronic prostatitis.

Variations of Growth and Toxin Yield in Cylindrospermopsis raciborskii under Different Phosphorus Concentrations.

The bloom-forming cyanobacteria, Cylindrospermopsis raciborskii, is a producer of the cytotoxic cylindrospermopsin (CYN). In this study, the growth, toxin yield, and expression of CYN biosynthesis genes of C. raciborskii were examined under varying phosphorus (P) concentrations. The results show the cell number at 0.00 and 0.01 mg·L-1 P was significantly lower than that at higher P concentrations (≥0.5 mg·L-1). The chlorophyll a content, filament length, heterocyst, and akinete numbers at P ≤ 0.05 mg·L-1 were also significantly reduced. The intracellular and extracellular CYN concentrations and the extracellular proportions increased during the culture period, and larger values were observed at higher P concentrations. Total CYN content reached 45.34-63.83 fg·cell-1 and extracellular CYN proportion reached 11.49%-20.44% at the stationary growth phase. A significantly positive correlation was observed between CYN production and cell growth rate. Three cyr genes were expressed constantly even at P-deficient conditions. The transcription of cyr genes at P-replete conditions or after P supplementation increased from 1.18-fold to 8.33-fold. In conclusion, C. raciborskii may rapidly reorganize metabolic processes as an adaptive response to environmental P fluctuations. CYN production and cyr gene expression were constitutive metabolic processes in toxic C. raciborskii.

Fatty acid and metabolomic profiling approaches differentiate heterotrophic and mixotrophic culture conditions in a microalgal food supplement 'Euglena'.

BACKGROUND: Microalgae have been recognized as a good food source of natural biologically active ingredients. Among them, the green microalga Euglena is a very promising food and nutritional supplements, providing high value-added poly-unsaturated fatty acids, paramylon and proteins. Different culture conditions could affect the chemical composition and food quality of microalgal cells. However, little information is available for distinguishing the different cellular changes especially the active ingredients including poly-saturated fatty acids and other metabolites under different culture conditions, such as light and dark. RESULTS: In this study, together with fatty acid profiling, we applied a gas chromatography-mass spectrometry (GC-MS)-based metabolomics to differentiate hetrotrophic and mixotrophic culture conditions. CONCLUSIONS: This study suggests metabolomics can shed light on understanding metabolomic changes under different culture conditions and provides a theoretical basis for industrial applications of microalgae, as food with better high-quality active ingredients.

Variation of Microcystis and microcystins coupling nitrogen and phosphorus nutrients in Lake Erhai, a drinking-water source in Southwest Plateau, China.

Lake Erhai is the second largest lake of Southwest China and an important drinking water source. The lake is currently defined as the preliminary stage of eutrophic states, but facing a serious threat with transfer into intensive eutrophication. The present study examined the dynamics of Microcystis blooms and toxic Microcystis in Lake Erhai during 2010, based on quantitative real-time PCR method using 16S rRNA gene specific for Microcystis and microcystin systhesis gene (mcy), and chemical analysis on microcystin (MC) concentrations. Total Microcystis cell abundance at 16 sampling sites were shown as an average of 1.7 × 10(7) cells l(-1) (1.3 × 10(2)-3.8 × 10(9) cells l(-1)). Microcystin LR (MC-LR) and microcystin RR (MC-RR) were the main variants. The strong southwesterly winds, anticlockwise circular flows and geographical characteristics of lake and phytoplankton community succession impacted the distribution patterns of Chl a and MC in the lake. The concentration of Chl a and MC and abundances of total Microsytis and MC-producing Microsystis (MCM) were shown to be positively correlated with pH, DO and TP, negatively correlated with SD, NO3-N, TN/Chl a and TN/TP, and not correlated with NH4-N, TN, dissolved total nitrogen (DTN) and water temperatures. When TN/TP decrease, Microcystis tended to dominate and MC concentrations tended to increase, suggesting that the "TN/TP rule" can be partially applied to explain the correlation between the cyanobacterial blooms and nutrients N and P only within a certain nutrient level. It is speculated that N and P nutrients and the associated genes (e.g., mcy) may jointly drive MC concentration and toxigenicity of Microcystis in Lake Erhai.

Supervised methods for symptom name recognition in free-text clinical records of traditional Chinese medicine: an empirical study.

Clinical records of traditional Chinese medicine (TCM) are documented by TCM doctors during their routine diagnostic work. These records contain abundant knowledge and reflect the clinical experience of TCM doctors. In recent years, with the modernization of TCM clinical practice, these clinical records have begun to be digitized. Data mining (DM) and machine learning (ML) methods provide an opportunity for researchers to discover TCM regularities buried in the large volume of clinical records. There has been some work on this problem. Existing methods have been validated on a limited amount of manually well-structured data. However, the contents of most fields in the clinical records are unstructured. As a result, the previous methods verified on the well-structured data will not work effectively on the free-text clinical records (FCRs), and the FCRs are, consequently, required to be structured in advance. Manually structuring the large volume of TCM FCRs is time-consuming and labor-intensive, but the development of automatic methods for the structuring task is at an early stage. Therefore, in this paper, symptom name recognition (SNR) in the chief complaints, which is one of the important tasks to structure the FCRs of TCM, is carefully studied. The SNR task is reasonably treated as a sequence labeling problem, and several fundamental and practical problems in the SNR task are studied, such as how to adapt a general sequence labeling strategy for the SNR task according to the domain-specific characteristics of the chief complaints and which sequence classifier is more appropriate to solve the SNR task. To answer these questions, a series of elaborate experiments were performed, and the results are explained in detail.

A framework and its empirical study of automatic diagnosis of traditional Chinese medicine utilizing raw free-text clinical records.

Automatic diagnosis is one of the most important parts in the expert system of traditional Chinese medicine (TCM), and in recent years, it has been studied widely. Most of the previous researches are based on well-structured datasets which are manually collected, structured and normalized by TCM experts. However, the obtained results of the former work could not be directly and effectively applied to clinical practice, because the raw free-text clinical records differ a lot from the well-structured datasets. They are unstructured and are denoted by TCM doctors without the support of authoritative editorial board in their routine diagnostic work. Therefore, in this paper, a novel framework of automatic diagnosis of TCM utilizing raw free-text clinical records for clinical practice is proposed and investigated for the first time. A series of appropriate methods are attempted to tackle several challenges in the framework, and the Naïve Bayes classifier and the Support Vector Machine classifier are employed for TCM automatic diagnosis. The framework is analyzed carefully. Its feasibility is validated through evaluating the performance of each module of the framework and its effectiveness is demonstrated based on the precision, recall and F-Measure of automatic diagnosis results.

Effects of prostate manipulation on serum total and free prostate specific antigen, and free-to-total prostate specific antigen ratio.

OBJECTIVE: To evaluate the effects of the different types of manipulation on prostate total specific antigen (tPSA), free prostate specific antigen (fPSA), and free-to-total prostate specific antigen (f/tPSA). METHODS: A total of 160 males were enrolled from January 2006 to December 2009 in the Urology Department, Beijing Anzhen Hospital affiliated to the Capital Medical University, Beijing, China. Of these patients, 23 had digital rectal examination (DRE), 21 had urethral catheterization, 28 had rigid cystoscopy, 35 had prostate biopsy, 35 underwent transurethral resection of the prostate (TURP), and 18 underwent suprapubic prostatectomy. Blood samples were taken before, at 24 hours, and 4 weeks after the manipulation for PSA tests. RESULTS: The DRE had no significant effect on PSA. Catheterization and cystoscopy exerted significant increases in tPSA at 24 hours. However, these small increases may not be clinically significant. The fPSA and f/tPSA were not significantly changed. There was a marked increase in tPSA and fPSA, associated with a decrease in f/tPSA at 24 hours after biopsy. No significant alterations were found in tPSA, fPSA, and f/tPSA at 4 weeks after catheterization, cystoscopy, and biopsy. The TURP and prostatectomy caused significant increases in tPSA and fPSA at 24 hours, associated with decreases in f/tPSA. The tPSA and fPSA values were below the baseline levels at 4 weeks after TURP and prostatectomy, however, f/tPSA remained constant. CONCLUSION: The DRE, catheterization, and cystoscopy had no crucial effect on PSA. Prostatic biopsy, TURP and prostatectomy significantly affected the PSA levels, and their longitudinal courses should be considered while evaluating different forms of PSA levels.

Automatic symptom name normalization in clinical records of traditional Chinese medicine.

BACKGROUND: In recent years, Data Mining technology has been applied more than ever before in the field of traditional Chinese medicine (TCM) to discover regularities from the experience accumulated in the past thousands of years in China. Electronic medical records (or clinical records) of TCM, containing larger amount of information than well-structured data of prescriptions extracted manually from TCM literature such as information related to medical treatment process, could be an important source for discovering valuable regularities of TCM. However, they are collected by TCM doctors on a day to day basis without the support of authoritative editorial board, and owing to different experience and background of TCM doctors, the same concept might be described in several different terms. Therefore, clinical records of TCM cannot be used directly to Data Mining and Knowledge Discovery. This paper focuses its attention on the phenomena of "one symptom with different names" and investigates a series of metrics for automatically normalizing symptom names in clinical records of TCM. RESULTS: A series of extensive experiments were performed to validate the metrics proposed, and they have shown that the hybrid similarity metrics integrating literal similarity and remedy-based similarity are more accurate than the others which are based on literal similarity or remedy-based similarity alone, and the highest F-Measure (65.62%) of all the metrics is achieved by hybrid similarity metric VSM+TFIDF+SWD. CONCLUSIONS: Automatic symptom name normalization is an essential task for discovering knowledge from clinical data of TCM. The problem is introduced for the first time by this paper. The results have verified that the investigated metrics are reasonable and accurate, and the hybrid similarity metrics are much better than the metrics based on literal similarity or remedy-based similarity alone.