Clustering algorithm based on DINNSM and its application in gene expression data analysis.

BACKGROUND: Selecting an appropriate similarity measurement method is crucial for obtaining biologically meaningful clustering modules. Commonly used measurement methods are insufficient in capturing the complexity of biological systems and fail to accurately represent their intricate interactions. OBJECTIVE: This study aimed to obtain biologically meaningful gene modules by using the clustering algorithm based on a similarity measurement method. METHODS: A new algorithm called the Dual-Index Nearest Neighbor Similarity Measure (DINNSM) was proposed. This algorithm calculated the similarity matrix between genes using Pearson's or Spearman's correlation. It was then used to construct a nearest-neighbor table based on the similarity matrix. The final similarity matrix was reconstructed using the positions of shared genes in the nearest neighbor table and the number of shared genes. RESULTS: Experiments were conducted on five different gene expression datasets and compared with five widely used similarity measurement techniques for gene expression data. The findings demonstrate that when utilizing DINNSM as the similarity measure, the clustering results performed better than using alternative measurement techniques. CONCLUSIONS: DINNSM provided more accurate insights into the intricate biological connections among genes, facilitating the identification of more accurate and biological gene co-expression modules.

Alternating current stimulation promotes neurite outgrowth and plasticity in neurons through activation of the PI3K/AKT signaling pathway.

As a commonly used physical intervention, electrical stimulation (ES) has been demonstrated to be effective in the treatment of central nervous system disorders. Currently, researchers are studying the effects of electrical stimulation on individual neurons and neural networks, which are dependent on factors such as stimulation intensity, duration, location, and neuronal properties. However, the exact mechanism of action of electrical stimulation remains unclear. In some cases, repeated or prolonged electrical stimulation can lead to changes in the morphology or function of the neuron. In this study, immunofluorescence staining and Sholl analysis are used to assess changes in the neurite number and axon length to determine the optimal pattern and stimulation parameters of ES for neurons. Neuronal death and plasticity are detected by TUNEL staining and microelectrode array assays, respectively. mRNA sequencing and bioinformatics analysis are applied to predict the key targets of the action of ES on neurons, and the identified targets are validated by western blot analysis and qRT-PCR. The effects of alternating current stimulation (ACS) on neurons are more significant than those of direct current stimulation (DCS), and the optimal parameters are 3 µA and 20 min. ACS stimulation significantly increases the number of neurites, the length of axons and the spontaneous electrical activity of neurons, significantly elevates the expression of growth-associated protein-43 (GAP-43) without significant changes in the expression of neurotrophic factors. Furthermore, application of PI3K/AKT-specific inhibitors significantly abolishes the beneficial effects of ACS on neurons, confirming that the PI3K/AKT pathway is an important potential signaling pathway in the action of ACS.

Unraveling the source-water fishy odor occurrence during low-temperature periods: Odorants identification, typical algae species and odor-producing potential.

In this study, odor characteristics and phytoplankton composition were systematically investigated in two winter periods in a reservoir with fishy odor in north China. Ten potential fishy odor-producing algae were isolated and odorant-producing potentials were evaluated. Olfactometry profile and odorant composition of water samples were analyzed using GC-Olfactometry combined with GC × GC-TOFMS. The results showed that 2,4-heptadienal and hexanal were major fishy odor contributors. The abundance of Uroglena sp., Synura sp. and Peridinium sp. was negatively correlated with total dissolved organic carbon, ammonia nitrogen, and nitrate, illustrating nutrient level might be major drivers for the succession of fishy odor-producing algae. Dinobryon sp. and Uroglena sp. made the greatest contribution to fishy odor, followed by Peridinium sp., Synura sp., and Ochromonas sp. Fishy odor in 2016 winter and the early of 2017 winter was mainly caused by Dinobryon sp., while Uroglena sp. contributes mostly in March in 2017 winter. This study demonstrates the main odorants and algae causing fishy odor in reservoir, which will provide a scientific basis for the management of seasonal fishy odor problems in water source.

Enrichment of rare methanogenic Archaea shows their important ecological role in natural high-CO2 terrestrial subsurface environments.

Introduction: Long-term stability of underground CO2 storage is partially affected by microbial activity but our knowledge of these effects is limited, mainly due to a lack of sites. A consistently high flux of mantle-derived CO2 makes the Eger Rift in the Czech Republic a natural analogue to underground CO2 storage. The Eger Rift is a seismically active region and H2 is produced abiotically during earthquakes, providing energy to indigenous microbial communities. Methods: To investigate the response of a microbial ecosystem to high levels of CO2 and H2, we enriched microorganisms from samples from a 239.5 m long drill core from the Eger Rift. Microbial abundance, diversity and community structure were assessed using qPCR and 16S rRNA gene sequencing. Enrichment cultures were set up with minimal mineral media and H2/CO2 headspace to simulate a seismically active period with elevated H2. Results and discussion: Methane headspace concentrations in the enrichments indicated that active methanogens were almost exclusively restricted to enrichment cultures from Miocene lacustrine deposits (50-60 m), for which we observed the most significant growth. Taxonomic assessment showed microbial communities in these enrichments to be less diverse than those with little or no growth. Active enrichments were especially abundant in methanogens of the taxa Methanobacterium and Methanosphaerula. Concurrent to the emergence of methanogenic archaea, we also observed sulfate reducers with the metabolic ability to utilize H2 and CO2, specifically the genus Desulfosporosinus, which were able to outcompete methanogens in several enrichments. Low microbial abundance and a diverse non-CO2 driven microbial community, similar to that in drill core samples, also reflect the inactivity in these cultures. Significant growth of sulfate reducing and methanogenic microbial taxa, which make up only a small fraction of the total microbial community, emphasize the need to account for rare biosphere taxa when assessing the metabolic potential of microbial subsurface populations. The observation that CO2 and H2-utilizing microorganisms could only be enriched from a narrow depth interval suggests that factors such as sediment heterogeneity may also be important. This study provides new insight on subsurface microbes under the influence of high CO2 concentrations, similar to those found in CCS sites.

A potential therapeutic approach for ulcerative colitis: targeted regulation of macrophage polarization through phytochemicals.

Ulcerative colitis (UC), a type of inflammatory bowel disease characterized by recurring and incurable symptoms, causes immense suffering and economic burden for patients due to the limited treatment options available. Therefore, it is imperative to develop novel and promising strategies, as well as safe and effective drugs, for the clinical management of UC. Macrophages play a critical role as the initial line of defense in maintaining intestinal immune homeostasis, and their phenotypic transformation significantly influences the progression of UC. Scientific studies have demonstrated that directing macrophage polarization toward the M2 phenotype is an effective strategy for the prevention and treatment of UC. Phytochemicals derived from botanical sources have garnered the interest of the scientific community owing to their distinct bioactivity and nutritional value, which have been shown to confer beneficial protective effects against colonic inflammation. In this review, we explicated the influence of macrophage polarization on the development of UC and collated data on the significant potential of natural substances that can target the macrophage phenotype and elucidate the possible mechanism of action for its treatment. These findings may provide novel directions and references for the clinical management of UC.

Early warning of MIB episode based on gene abundance and expression in drinking water reservoirs.

Cellular 2-methylisoborneol (MIB) yield of cyanobacteria varies under different conditions according to culture studies and field investigations, the causal mechanism remains unclear and results in ineffective MIB prediction. Through an intensive field survey during an MIB episode produced by Pseudanabaena cinerea in QCS reservoir, we demonstrated that MIB synthesis (mic) gene abundance (DNA) and expression (RNA) might be useful as parameters for early warning of MIB production. It was found that the abundance of mic DNA and RNA peaked ahead of MIB concentrations by 10 and 7 days, respectively. In addition, the RNA abundance (R2 = 0.45, p < 0.01) showed a slightly higher correlation with MIB compared to DNA abundance (R2 = 0.37, p < 0.01), suggesting that the conditions for the growth of Pseudanabaena cinerea might be slightly different from those for mic gene expression, which was verified by a culture experiment. The highest cell growth was obtained under 36 µmol photons m-2 s-1, while the highest cellular MIB yield and mic gene expression level were obtained under 85 µmol photons m-2 s-1. Our results clearly supported that light intensity was the virtual regulator governing the mic gene expression within the controlled culture experiment and the actual MIB episode in the reservoir. Besides these results, we developed an early warning model using mic gene abundance as an indicator of MIB episodes, which was verified in two other reservoirs. Our findings highlight the effect of light intensity on mic gene expression and MIB synthesis and provide an early warning tool targeting MIB episode prediction, which therefore should be of importance for source water authorities.

Biosynthesis of 2-methylisoborneol is regulated by chromatic acclimation of Pseudanabaena.

Cyanobacteria can sense different light color by adjusting the components of photosynthetic pigments including chlorophyll a (Chl a), phycoerythrin (PE), and phycocyanin (PC), etc. Filamentous cyanobacteria are the main producer of 2-methylisoborneol (MIB) and many can increase their PE levels so that they are more competitive in subsurface layer where green light is more abundant, and have caused extensive odor problems in drinking water reservoirs. Here, we identified the potential correlation between MIB biosynthesis and ambient light color induced chromatic acclimation (CA) of a MIB-producing Pseudanabaena strain. The results suggest Pseudanabaena regulates the pigment proportion through Type III CA (CA3), by increasing PE abundance and decreasing PC in green light. The biosynthesis of MIB and Chl a share the common precursor, and are positively correlated with statistical significance regardless of light color (R2=0.68; p<0.001). Besides, the PE abundance is also positively correlated with Chl a in green light (R2=0.57; p=0.019) since PE is the antenna that can only transfer the energy to PC and Chl a. In addition, significantly higher MIB production was observed in green light since more Chl a was synthesized.

Bandwidth Optimization of MEMS Accelerometers in Fluid Medium Environment.

There is a constraint between the dynamic range and the bandwidth of MEMS accelerometers. When the input acceleration is comparatively large, the squeeze film damping will increase dramatically with the increase in the oscillation amplitude, resulting in a decrease in bandwidth. Conventional models still lack a complete vibration response analysis in large amplitude ratios and cannot offer a suitable guide in the optimization of such devices. In this paper, the vibration response analysis of the sensing unit of an accelerometer in large amplitude ratios is first completed. Then, the optimal design of the sensing unit is proposed to solve the contradiction between the dynamic range and the bandwidth of the accelerometer. Finally, the results of the vibration experiment prove that the maximum bandwidth can be achieved with 0~10g external acceleration, which shows the effectiveness of the design guide. The new vibration analysis with the complete model of squeeze film damping is applicable to all sensitive structures based on vibration, not limited to the MEMS accelerometer studied in this thesis. The bandwidth optimal scheme also provides a strong reference for similar structures with large oscillation amplitude ratios.

Metagenome-Assembled Genome of a Putative Methanogenic Methanosarcina sp. Strain Enriched from Terrestrial High-CO2 Subsurface Sediments.

A metagenome-assembled genome (MAG), named Methanosarcina sp. strain ERenArc_MAG2, was obtained from a 3-month-old H2/CO2 atmosphere enrichment culture, originally inoculated with 60-m deep drill core sediment collected from the tectonic Eger Rift terrestrial subsurface. Annotation of the recovered draft genome revealed putative archaeal methanogenesis genes in the deep biosphere.

Circular Metagenome-Assembled Genome of Methanobacterium sp. Strain ERen5, a Putative Methanogenic, H2-Utilizing Terrestrial Subsurface Archaeon.

A circular, single-contig Methanobacterium sp. metagenome-assembled genome (MAG) was recovered from high-CO2 enrichments inoculated with drill core material from the tectonic Eger Rift terrestrial subsurface. Annotation of the recovered MAG highlighted putative methanogenesis genes, providing valuable information on archaeal activity in the deep biosphere.

Correlation Analysis Between Magnetic Resonance Imaging-Based Anatomical Assessment and Behavioral Outcome in a Rat Contusion Model of Chronic Thoracic Spinal Cord Injury.

Although plenty of evidences from preclinical studies have led to potential treatments for patients with spinal cord injury (SCI), the failure to translate promising preclinical findings into clinical advances has long puzzled researchers. Thus, a more reliable combination of anatomical assessment and behavioral testing is urgently needed to improve the translational worth of preclinical studies. To address this issue, the present study was designed to relate magnetic resonance imaging (MRI)-based anatomical assessment to behavioral outcome in a rat contusion model. Rats underwent contusion with three different heights to simulate various severities of SCI, and their locomotive functions were evaluated by the grid-walking test, Louisville swim scale (LSS), especially catwalk gait analysis system and basic testing, and Basso, Beattie, Bresnahan (BBB) score. The results showed that the lesion area (LA) is a better indicator for damage assessment compared with other parameters in sagittal T2-weighted MRI (T2WI). Although two samples are marked as outliers by the box plot analysis, LA correlated closely with all of the behavioral testing without ceiling effect and floor effect. Moreover, with a moderate severity of SCI in a contusion height of 25 mm, the smaller the LA of the spinal cord measured on sagittal T2WI the better the functional performance, the smaller the cavity region and glial scar, the more spared the myelin, the higher the volatility, and the thicker the bladder wall. We found that LA significantly related with behavior outcomes, which indicated that LA could be a proxy of damage assessment. The combination of sagittal T2WI and four types of behavioral testing can be used as a reliable scheme to evaluate the prognosis for preclinical studies of SCI.

The alleles of AGT and HIF1A gene affect the risk of hypertension in plateau residents.

Plateau essential hypertension is a common chronic harmful disease of permanent residents in plateau areas. Studies have shown some single nucleotide polymorphisms (SNPs) associations with hypertension, but few have been verified in plateau area-lived people. In this paper, we examined some hypertension-related gene loci to analyze the relationship between risk SNPs and plateau essential hypertension in residents in Qinghai-Tibet plateau area. We screened hypertension-related SNPs from the literature, Clinvar database, GHR database, GTR database, and GWAS database, and then selected 101 susceptible SNPs for detection. Illumina MiSeq NGS platform was used to perform DNA sequencing on the blood samples from 185 Tibetan dwellings of Qinghai, and bioinformatic tools were used to make genotyping. Genetic models adjusted by gender and age were used to calculate the risk effects of genotypes. Four known SNPs as well as a new locus were found associated with PHE, which were rs2493134 (AGT), rs9349379 (PHACTR1), rs1371182 (CYP2C56P-PRPS1P1), rs567481079 (CYP2C56P-PRPS1P1), and chr14:61734822 (HIF1A). Among them, genotypes of rs2493134, rs9349379, and rs567481079 were risk factors, genotypes of rs1371182 and chr14:61734822 were protective factors. The rs2493134 in AGT was found associated with an increased risk of the plateau essential hypertension by 3.24-, 3.24-, and 2.06-fold in co-dominant, dominant, and Log-additive models, respectively. The rs9349379 in PHACTR1 is associated with a 2.61-fold increased risk of plateau essential hypertension according to the dominant model. This study reveals that the alleles of AGT, HIF1A, and PHACTR1 are closely related to plateau essential hypertension risk in the plateau Tibetan population.

The application of machine learning algorithms in predicting the length of stay following femoral neck fracture.

PURPOSE: Femoral neck fracture is a frequent cause of hospitalization, and length of stay is an important marker of hospital cost and quality of care provided. As an extension of traditional statistical methods, machine learning provides the possibility of accurately predicting the length of hospital stay. The aim of this paper is to retrospectively identify predictive factors of the length of hospital stay (LOS) and predict the postoperative LOS by using machine learning algorithms. METHOD: Based on the admission and perioperative data of the patients, linear regression was used to analyze the predictive factors of the LOS. Multiple machine learning models were developed, and the performance of different models was compared. RESULT: Stepwise linear regression showed that preoperative calcium level (P = 0.017) and preoperative lymphocyte percentage (P = 0.007), in addition to intraoperative bleeding (p = 0.041), glucose and sodium chloride infusion after surgery (P = 0.019), Charlson Comorbidity Index (p = 0.007) and BMI (P = 0.031), were significant predictors of LOS. The best performing model was the principal component regression (PCR) with an optimal MAE (1.525) and a proportion of prediction error within 3 days of 90.91%. CONCLUSION: Excessive intravenous glucose and sodium chloride infusion after surgery, preoperative hypocalcemia, preoperative high percentages of lymphocytes, excessive intraoperative bleeding, lower BMI and higher CCI scores were related to prolonged LOS by using linear regression. Machine learning could accurately predict the postoperative LOS. This information allows hospital administrators to plan reasonable resource allocation to fulfill demand, leading to direct care quality improvement and more reasonable use of scarce resources.

Identification of MIB producers and odor risk assessment using routine data: A case study of an estuary drinking water reservoir.

Identification of MIB(2-methylisoborneol)-producing cyanobacteria in source water has been a big challenge for reservoir authorities because it normally requires isolation of cyanobacteria strains. Here, a protocol based on Pearson's product moment correlation analysis combined with standardized data treatment and expert judgement was developed to sort out the MIB producer(s), mainly based on routine monitoring data from an estuary drinking water reservoir in the Yangtze River, China, and a risk model using quantile regressions was established to evaluate the risk of MIB occurrences. This reservoir has suffered from MIB problems in summer since 2011. Among 323 phytoplankton species, Planktothrix was judged to be the MIB producer in this reservoir because it exhibited the highest correlation coefficient (R = 0.60) as well as the lowest false positive-ratio (FP% = 0) and false-negative rate (FN% = 14). The low false-positive rate is particularly important, since MIB should not detected without detection of the producer. A high light extinction coefficient (k=5.57±2.48 m-1) attributed to high turbidity loading in the river water lowered the subsurface water light intensity, which could protect the low irradiance Planktothrix from excessive solar radiation, and allow them to grow throughout the summer. The risk model shows that the probability of suffering unacceptable MIB concentrations (>15 ng L-1) in water is as high as 90% if the cell density of Planktothrix is >609.0 cell mL-1, while the risk will be significantly reduced to 50% and 10% at cell densities of 37.5 cell mL-1 and 9.6 cell mL-1, respectively. The approach developed in this study, including the protocol for identification of potential producers and the risk model, could provide a reference case for the management of source water suffering from MIB problems using routine monitoring data.

Optimizing the hybridization chain reaction-fluorescence in situ hybridization (HCR-FISH) protocol for detection of microbes in sediments.

Fluorescence in situ hybridization (FISH) is a canonical tool commonly used in environmental microbiology research to visualize targeted cells. However, the problems of low signal intensity and false-positive signals impede its widespread application. Alternatively, the signal intensity can be amplified by incorporating Hybridization Chain Reaction (HCR) with FISH, while the specificity can be improved through protocol modification and proper counterstaining. Here we optimized the HCR-FISH protocol for studying microbes in environmental samples, particularly marine sediments. Firstly, five sets of HCR initiator/amplifier pairs were tested on the laboratory-cultured bacterium Escherichia coli and the archaeon Methanococcoides methylutens, and two sets displayed high hybridization efficiency and specificity. Secondly, we tried to find the best combination of sample pretreatment methods and HCR-FISH protocol for environmental sample analysis with the aim of producing less false positive signals. Various detachment methods, extraction methods and formulas of hybridization buffer were tested using sediment samples. Thirdly, an image processing method was developed to enhance the DAPI signal of microbial cells against that of abiotic particles, providing a reliable reference for FISH imaging. In summary, our optimized HCR-FISH protocol showed promise to serve as an addendum to traditional FISH for research on environmental microbes. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-021-00098-8.

Identification of Hub Genes Associated with Hypertension and Their Interaction with miRNA Based on Weighted Gene Coexpression Network Analysis (WGCNA) Analysis.

BACKGROUND Hypertension is one of the most widespread health conditions in the world, and the molecular mechanism of it is still unclear. In this study, we identified the hub genes (hub miRNA genes) associated with hypertension and explored the relationship between hypertension miRNA-gene by constructing a mRNA co-expression network and a miRNA co-expression network, which can help to reveal the mechanism and predict the prognosis of hypertension progression. MATERIAL AND METHODS Based on gene expression profile data of hypertensive samples from the Gene Expression Omnibus database, WGCNA was used to detect hypertension-related biomarkers and key mRNA and miRNA modules. Then, DAVID was used to perform gene-annotation enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) and miRPath were used for pathway analysis of mRNA and miRNAs genes. RESULTS We identified 3 key modules relating to hypertension, 2 mRNA modules named Msaddlebrown and Mgreenyellow and 1 miRNA module named Msalmon. In addition, 12 hub genes (RPL21, RPS28, LOC442727/PTGAP10, LOC100129599/RPS29P14, TBXAS1, FCER1G, CFP, FURIN, PECAM1, IGSF6, NCF1C, and LOC285296/UNC93B3) and 7 hub miRNAs (hsa-miR-1268a/b, hsa-miR-513c-3p, hsa-miR-4799-5p, hsa-miR-296-3p, hsa-miR-5195-5p, hsa-miR-219-2-3p, and hsa-miR-548d-5p) relating to hypertension were identified. HIF-1 signaling pathway and insulin signaling pathway were closely related to the 3 key modules. We also discovered 4 miRNAs (hsa-miR-548am-3p, hsa-miR-513c-3p, hsa-miR-182-5p, and hsa-miR-548d-5p) and 6 genes (IGF1R, GSK3B, FOXO1, PRKAR2B, HIF1A, and PIK3R1) were the core nodes in the hypertension-related miRNA-gene network, and hsa-miR-548am-3p was at the center of the network. CONCLUSIONS These findings will help improve the understanding of the pathogenesis of hypertension, and the discovered genes can serve as signatures for early diagnosis of hypertension.

Identifying the function of activated carbon surface chemical properties in the removability of two common odor compounds.

In this study, the adsorption capacities of two common odor compounds, 2-methylisoborneol (2-MIB) and dimethyl disulfide (DMDS), onto nine common types of powdered activated carbon (PAC) were comprehensively compared to screen the critical surface chemical properties affecting the adsorption performance. The results showed that the adsorption capacities of all the PACs for DMDS were generally lower than those for 2-MIB. The Spearman's rank correlation analysis indicated that the adsorption capacity for 2-MIB did not have any correlation with the PAC surface sites, while the DMDS adsorption capacity was positively related to the number of basic sites. The effect of the PAC basic sites on the DMDS adsorption was further verified by density functional theory (DFT) calculation in two adsorption modes (facial mode and edge mode). The graphene structure in the edge mode was the most favorable for DMDS adsorption with the lowest adsorption enthalpy, followed by the ketone-doped structure under the facial mode. An independent gradient model indicated that van der Waals forces were dominant in the DMDS adsorption. Moreover, thermal modification was conducted to further prove the relationship between the basic sites and the DMDS adsorption. After thermal modification, the PAC with more basic sites and graphene structures was found to be more effective for DMDS adsorption. Overall, this study could offer guidance for water treatment plants with respect to the selection of PAC to solve the odor problems caused by various compounds (e.g., DMDS or 2-MIB), and the modification of PAC, aiming at more efficient odor removal.

Assessing the hidden social risk caused by odor in drinking water through population behavioral responses using economic burden.

Unpleasant odor in drinking water is a worldwide substantial issue for consumers and water utilities. However, its hidden social impact has been ignored as there are no apparent direct health effects compared with other pollutants. In this study, we developed a method to characterize the adverse effects of a typical odorant based on behavioral responses with the corresponding economic burden, illustrated by 2-methylisoborneol (2-MIB). The dose-response based on behavioral responses to odors using a questionnaire was established in consideration of the bandwagon effect. Results showed that about half of consumers adopted averting behaviors after detecting even very weak odor (but generally recognizable) in drinking water. Total economic burden was determined to be 290690 ± 27427 ¥ per million people per day by the surcharges arising from consumer averting behavior or additional treatment of drinking water odor, among which about 13% of surcharge originated from insensitive people because of bandwagon effect. This is the first study to quantify odor hidden risk based on people's behavioral responses using economic burden, which provides a useful tool to comparing the risks of different types of pollutants in drinking water.

Rapid prediction of the activated carbon adsorption ratio by a regression model.

Regression analysis of micropore volume and particle size of powdered activated carbon (PAC) is applied to develop a model to predict the adsorption ratio of a non-polar compound, 2-methylisorneol (2-MIB), onto PACs. This model likewise predicts the adsorption ratio of the same PACs and other PACs in background water containing similar natural organic matter (NOM). When this model is used to predict the same PACs adsorption ratios at 30 and 50 mg L-1, the respective percent sample deviations standard error (SDEV) is of 30% SDEV and 12% were obtained. Further, the model is also employed for the prediction of 2-MIB adsorption capacities for 12 different PACs in water with similar NOM at the same dosages, with average SDEV values of 44% and 28%, respectively. Results indicate that 2-MIB adsorption occurrs mainly through the micropore filling mechanism. Nevertheless, when this model is expanded to predict PAC adsorption of NOM with different properties in water, the results exhibited rather large errors. Though this model cannot be applied to waters containing NOM with different properties, it provides information for water utilities themselves or the ones using similar source water to predict the PAC dosage without any adsorption experiment when change of PAC is needed.

Light as a possible regulator of MIB-producing Planktothrix in source water reservoir, mechanism and in-situ verification.

The typical musty/earthy odor-causing compound, 2-methylisoborneol (MIB), is usually associated with the occurrence and proliferation of benthic/subsurface-living cyanobacteria in source water. Control of MIB-producing cyanobacteria in source water may greatly reduce the processing burden for drinking water treatment plants. We explored the mechanism and feasibility of restricting the growth of subsurface-living Planktothrix sp. by reducing underwater light availability. The effects of light intensity (5, 17, 36, 85, and 250 µmol photons m-2 s-1) on the growth and MIB production of Planktothrix sp. were first determined using batch culture, followed by an in-situ experiment deployed at different depths (0.5, 1.5, 3.5, and 5.0 m) in a drinking source water reservoir (Miyun Reservoir, China) to verify the laboratory results. The optimum conditions for growth (7.5 × 108 cells L-1) and MIB production ((1300 ±â€¯29) µg L-1) of Planktothrix sp. were achieved at 85 µmol photons m-2 s-1 in the laboratory and at 1.5 m (the corresponding average light intensity of 66 µmol photons m-2 s-1) in the field. The minimum light requirement for the growth of Planktothrix sp. (4.4 µmol photons m-2 s-1) was determined according to the laboratory data. While the in-situ experiment further indicated that Planktothrix sp. could not successfully grow at depths of 5 m where light intensity was below the minimum light requirement. In addition, the history data also verified the negative relationships between underwater light availability and MIB concentration.