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Turbidity is an indication of water quality and enables the growth of pathogenic microorganisms. For drinking water treatment plants (DWTPs), violent fluctuations in turbidity are highly disruptive to operational performance due to the lag in process parameter adjustments. Such risks must be carefully managed to guarantee safe drinking water. Machine learning techniques have been proven to be effective for modeling complex nonlinear environmental systems, and this study adopted such a technique to develop a model for predicting source water turbidity for DWTPs to allow DWTPs to make proactive interventions in advance. A random forest (RF) model used preprocessed (empirical mode decomposition and quartile rejecting) meteorological factors (wind speed, wind direction, air temperature, and rainfall) as the input variables, to establish the turbidity prediction of a lake with significant turbidity in China's South Tai Lake. The modeling process included four main stages: (1) source data analysis, (2) raw data preprocessing, (3) modeling and tuning, and (4) model evaluation. The results of the RF model indicated that the correlation coefficient between the predicted and actual sequences is over 0.7, and more than 55% of the predicted values could control the errors within 20% compared to the actual measured values, suggesting that machine learning techniques are suitable for predicting the turbidity of raw source water. It was found that the RF model can provide a modest performance boost because of its stronger capacity to capture nonlinear interactions in the data. The findings of this study can inform the development of turbidity prediction models using readily available meteorological forecast data. The model can be applied to other DWTPs using similar shallow lakes as water sources.
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Monitoreo del Ambiente , Lagos , China , Calidad del Agua , VientoRESUMEN
A novel construction strategy of monolithic capillary column for selectively enriching perfluorinated persistent organic pollutants was proposed. The organic-inorganic hybrid fluorous monolithic capillary column was synthesized by a "one-pot" approach via the polycondensation of γ-methacryloxypropyltrimethoxy-silane, then in situ copolymerization of 1H,1H,7H-dodecafluoroheptyl methacrylate and vinyl group on the precondensed siloxanes. The obtained monolithic columns were systematically characterized. The results demonstrated that the optimal column possessed good mechanical stability and high permeability. The adsorption capacities of the optimized monolithic column for perfluorooctanoic acid and perfluorooctane sulfonate were 0.257 and 0.513 µg/mg, respectively. Adsorption capacities of the monoliths were proved to increasing with increasing the amounts of fluorinated monomers in the fluorous monoliths. Sodium 1-octanesulfonate, as a comparison compound, was hardly adsorbed on the fluorous monolith. In addition, the trace amounts of perfluorooctanoic acid and perfluorooctane sulfonate in water samples can be successfully concentrated about 160 times to their original concentrations by this monolithic column. These results demonstrated that the capacity and selectivity of the affinity fluorous column is high and can be applied to the selective enrichment for the perfluorinated persistent organic pollutants from environmental samples.
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Fluorocarburos/aislamiento & purificación , Resinas Sintéticas/química , Microextracción en Fase Sólida/métodos , Contaminantes Químicos del Agua/aislamiento & purificación , Adsorción , Fluorocarburos/química , Microextracción en Fase Sólida/instrumentación , Contaminantes Químicos del Agua/químicaRESUMEN
OBJECTIVE: To explore the risk factors of type 2 diabetes mellitus (T2DM) of Dong nationality in Western Hunan, and to provide a scientific basis for the prevention and treatment of T2DM in the district. METHODS: In the case-control study, the subjects were divided into a T2DM group, an impaired glucose regulation (IGR) group and a normal glucose tolerance (NGT) group through oral glucose tolerance test (OGTT). A questionnaire survey was conducted, and physical measurements and the detection of blood glucose, blood lipids and serum insulin were done. RESULTS: Univariate analysis found significant difference in age, fasting insulin (FINS), HOMA insulin resistance index (HOMA-IRI), HOMA ß-cell function index (HOMA-ßC), trigalloyl glycerol (TG), high density lipoprotein cholesterol (HDL-C), systolic blood pressure, and diastolic blood pressure in the glucose metabolism among different groups (P<0.05). Body mass index (BMI), waist/hip ratio (WHR), family history of diabetes, number of physical activities per week, dinner taste, fat and protein-rich foods, fresh vegetables and fruits intake were associated with T2DM. Multifactor non-conditional ordinal logistic regression indicated that age was the risk factor of T2DM and IGR. Compared with the group whose age was≤50, the odds ratios of the groups of 50
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Diabetes Mellitus Tipo 2/epidemiología , Factores de Riesgo , Glucemia , Índice de Masa Corporal , Estudios de Casos y Controles , China/epidemiología , Diabetes Mellitus Tipo 2/etnología , Etnicidad , Prueba de Tolerancia a la Glucosa , Humanos , Insulina , Resistencia a la Insulina , Células Secretoras de Insulina , Lípidos , Obesidad , Sobrepeso , Factores SocioeconómicosRESUMEN
Skeletal muscle, the largest organ in the human body, plays a crucial role in supporting and defending the body and is essential for movement. It also participates in regulating the processes of protein synthesis and degradation. Inhibition of protein synthesis and activation of degradation metabolism can both lead to the development of skeletal muscle atrophy, a pathological condition characterized by a decrease in muscle mass and fiber size. Many physiological and pathological conditions can cause a decline in muscle mass, but the underlying mechanisms of its pathogenesis remain incompletely understood, and the selection of treatment strategies and efficacy evaluations vary. Moreover, the early symptoms of this condition are often not apparent, making it easily overlooked in clinical practice. Therefore, it is necessary to develop and use cell models to understand the etiology and influencing factors of skeletal muscle atrophy. In this review, we summarize the methods used to construct skeletal muscle cell models, including hormone, inflammation, cachexia, genetic engineering, drug, and physicochemical models. We also analyze, compare, and evaluate the various construction and assessment methods.
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Músculo Esquelético , Atrofia Muscular , Humanos , Atrofia Muscular/patología , Músculo Esquelético/metabolismo , Fibras Musculares Esqueléticas/metabolismo , Caquexia/patología , Biosíntesis de ProteínasRESUMEN
Liver-targeted drug delivery improves the efficacy of anti-liver cancer agents and reduces systemic toxicity by limiting the bioavailability of these drugs to within tumors. Liver targeting reagents with galactose residues, which selectively combine to asialoglyco protein receptors, have previously been used to improve liposome-encapsulated drug accumulation within liver cells. They lead to a reduction in liver cancer cell growth and have been used to cure certain hepatic diseases. In the present study, curcumol, which is the primary active component of Chinese traditional medicine Rhizoma zedoariae, was encapsulated in galactosylated-liposomes to enhance its anti-liver cancer efficacy. Galactosylated-liposomes and normal liposomes were labeled with propidium iodide. Galactosylated-liposomes with increasing concentrations of galactosylated-stearate (Gal-s) had a notably increased level of uptake in HepG2 cells (hepatoblastoma) compared with SGC-7901 (gastric cancer) and A549 (non-small cell lung cancer) cells. When the percentage of Gal-s reached 20%, liposome uptake plateaued. In the in vitro anti-liver cancer experiment, the anti-liver cancer efficacy of galactosylated-curcumol-liposomes increased significantly more compared with normal curcumol liposomes and free curcumol as indicated by cell survival rate and lactate dehydrogenase release rate. Collectively, these results demonstrate that galactosylated-liposomes are able to enhance the in vitro liver-targeting effect and anti-liver cancer efficacy of curcumol.
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OBJECTIVE: To evaluate the safety of GM yeast feed additive with cecropin CAD and to study and set up a model of Safety assessment for GM feed and detecting method. METHODS: To ensure the safety of the GM products, it has been done that to detect and value the safety of receptor organisms and expression products of extrinsic gene, the genetic stability of biologic properties of genomic modified yeast feed and condition of transfer and cumulation of anti-bacterial peptide and its products in circumstance and the feeded animals. RESULT AND CONCLUSION: The receptor animals and expression products of extrinic gene are safe, and the genomic modified products have steady genetic characters. The cectopin CAD neither cumulates in feeded animal nor releases into environment. The genomic modified feed additive is safe.