Order Polynomial Regression Research Articles

Calibrating Carbonization Temperatures of Wood Fragments Embedded within Pyroclastic Density Currents through Raman Spectroscopy

The study of the structural order of charcoals embedded in pyroclastic density currents provides information on their emplacement temperature during volcanic eruptions. In the present work, a set of charcoals from three distinct pyroclastic density currents deposits whose temperatures have been previously estimated by charcoal reflectance analyses to lie between 250 °C and 550 °C, was studied by means of Raman spectroscopy. The analyses reveal a very disordered structural ordering of the charcoals, similar to kerogen matured under diagenetic conditions. Changes in Raman spectra at increasing temperatures reflect depolymerization and an increase of aromaticity and can be expressed by parameters derived from a simplified fitting method. Based on this approach, a second order polynomial regression with a high degree of correlation and a minimum error was derived to predict paleotemperatures of pyroclastic deposits. Our results show that Raman spectroscopy can provide a reliable and powerful tool for volcanological studies and volcanic hazard assessment given its advantage of minimum samples preparation, rapid acquisition processes and high precision.

Оптимизация условий мицеллярно-ферментативной экстракции пектина из плодов боярышника ( Crataegus monogyna Jacq.)

Introduction. Commercial pectin is usually obtained from apples or citrus fruits. However, some wild fruits, such as hawthorn, are also rich in pectin with valuable nutritional and medical properties. The research objective was to study and improve the process of combined surfactant and enzyme-assisted extraction of pectin from hawthorn fruits.
 Study objects and methods. The study involved a 1% solution of Polysorbate-20 surfactant and a mix of two enzymes, namely cellulase and xylanase, in a ratio of 4:1. The response surface methodology with the Box-Behnken experimental design improved the extraction parameters. The experiment featured three independent variables – temperature, time, and solvent-to-material ratio. They varied at three levels: 20, 40, and 60°C; 120, 180, and 240 min; 15, 30, and 45 mL per g. Their effect on the parameters on the pectin yield was assessed using a quadratic mathematical model based on a second order polynomial equation.
 Results and discussion. The response surface methodology made it possible to derive a second order polynomial regression equation that illustrated the effect of extraction parameters on the yield of polyphenols. The regression coefficient (R2 = 98.14%) and the lack-of-fit test (P > 0.05) showed a good accuracy of the model. The optimal extraction conditions were found as follows: temperature = 41°C, time = 160 min, solvent-to-material ratio = 32 mL per 1 g. Under the optimal conditions, the predicted pectin yield was 14.9%, while the experimental yield was 15.2 ± 0.4%. The content of galacturonic acid in the obtained pectin was 58.5%, while the degree of esterification was 51.5%. The hawthorn pectin demonstrated a good complex-building ability in relation to ions of copper (564 mg Cu2+/g), lead (254 mg Pb2+/g), and cobalt (120 mg Co2+/g).
 Conclusion. Combined surfactant and enzyme-assisted extraction made improved the extraction of pectin from hawthorn fruits. The hawthorn pectin can be used to develop new functional products.

Combining Global Geopotential Models, Digital Elevation Models, and GNSS/Leveling for Precise Local Geoid Determination in Some Mexico Urban Areas: Case Study

This work shows improvements of geoid undulation values obtained from a high-resolution Global Geopotential Model (GGM), applied to local urban areas. The methodology employed made use of a Residual Terrain Model (RTM) to account for the topographic masses effect on the geoid. This effect was computed applying the spherical tesseroids approach for mass discretization. The required numerical integration was performed by 2-D integration with 1DFFT technique that combines DFT along parallels with direct numerical integration along meridians. In order to eliminate the GGM commission error, independent geoid undulations values obtained from a set of GNSS/leveling stations are employed. A corrector surface from the associated geoid undulation differences at the stations was generated through a polynomial regression model. The corrector surface, in addition to the GGM commission error, also absorbs the GNSS/leveling errors as well as datum inconsistencies and systematic errors of the data. The procedure was applied to five Mexican urban areas that have a geodetic network of GNSS/leveling points, which range from 166 to 811. Two GGM were evaluated: EGM2008 and XGM2019e_2159. EGM2008 was the model that showed relatively better agreement with the GNSS/leveling stations having differences with RMSE values in the range of 8–60 cm and standard deviations of 5–8 cm in four of the networks and 17 cm in one of them. The computed topographic masses contribution to the geoid were relatively small, having standard deviations on the range 1–24 mm. With respect to corrector surface estimations, they turned out to be fairly smooth yielding similar residuals values for two geoid models. This was also the case for the most recent Mexican gravity geoid GGM10. For the three geoid models, the second order polynomial regression model performed slightly better than the first order with differences up to 1 cm. These two models produced geoid correction residuals with a standard deviation in one test area of 14 cm while for the others it was of about 4–7 cm. However, the kriging method that was applied for comparison purposes produced slightly smaller values: 8 cm for one area and 4–6 cm for the others.

Machine learning for DCO-OFDM based LiFi

Light fidelity (LiFi) uses different forms of orthogonal frequency division multiplexing (OFDM), including DC biased optical OFDM (DCO-OFDM). In DCO-OFDM, the use of a large DC bias causes optical power inefficiency, while a small bias leads to higher clipping noise. Hence, finding an appropriate DC bias level for DCO-OFDM is important. This paper applies machine learning (ML) algorithms to find optimum DC-bias value for DCO-OFDM based LiFi systems. For this, a dataset is generated for DCO-OFDM using MATLAB tool. Next, ML algorithms are applied using Python programming language. ML is used to find the important attributes of DCO-OFDM that influence the optimum DC bias. It is shown here that the optimum DC bias is a function of several factors including, the minimum, the standard deviation, and the maximum value of the bipolar OFDM signal, and the constellation size. Next, linear and polynomial regression algorithms are successfully applied to predict the optimum DC bias value. Results show that polynomial regression of order 2 can predict the optimum DC bias value with a coefficient of determination of 96.77% which confirms the effectiveness of the prediction.

Enhancement of permeability estimation by high order polynomial regression for capillary pressure curve correlation with water saturation

Suggesting a cost-effective and straightforward approach is indispensable for obtaining permeability estimates in carbonate reservoirs utilizing available well logs. In this study, several procedures were conducted to reach an optimum approach, primarily by constructing a correlation between capillary pressure and water saturation using core data plotted and utilized a good polynomial regression to obtain a better relationship, which leads to calculating the permeability. The second step is to use different theoretical models which Tixier introduces, Timur, Coats, and Dumanior, which resulted not good matching with the permeability from core analysis and modified Brown and Husseini correlation which used and gave better matching than others correlations by comparing the results with the calculated permeability depending on core data. The proposed approach in this study based on modified Husseini equation using the well logs data by applying Statistical regression techniques within capillary pressure prediction to enhance reservoir characterization can potentially advantage reservoir simulation efforts. Obtained results of permeability prediction based on capillary pressure correlation was examined for a certain well and compared with the measured permeability value of cores. There was a good matching between the predicted and measured permeability.

Study of Salted Octopus Drying Kinetics and Hygroscopy from Artisanal Fishing in Agadir Region

Salt-and-dry technique is an artisanal fish conservation method adopted in the Maghreb countries which is based on lowering the water activity. This latter factor is crucial in food preservation, where the relationship between the water activity and the water content of the salted octopus helps control its storage. However, the realization of this processing in controlled conditions is limited by the lack of information regarding the drying time and the behavior towards humidity of this specie. This work describes the drying kinetics by plotting the drying curve (70 ° C; 1.5 m/s) and helps define the salted octopus drying time. Also it presents the desorption and adsorption isotherms at three temperatures which represent the storage temperatures (30, 40 and 50°C) following the gravimetric method. The drying of the salted octopus carried out helped reduce the water activity to a value of 0.63 and the water content of 0.505 g water/g MS during 10 hours. In addition, the sorption curves were experimentally determined and modeled by polynomial regression of order 4. The fitting has given correlation coefficients close to 1 for the three temperatures.

Influence of electrode to cochlear duct length ratio on post-operative speech understanding outcomes

Objective To assess whether the pre-operative electrode to cochlear duct length ratio (ECDLR), is associated with post-operative speech recognition outcomes. Study Design A retrospective chart review study. Setting: Tertiary referral center. Patients The study included sixty-one adult CI recipients with a pre-operative computed tomography scan and a speech recognition test 12 months after implantation. Interventions The average of two raters’ cochlear duct length (CDL) measurements and the length of the recipient’s cochlear implant electrode array formed the basis for the electrode-to-cochlear duct length ratio (ECLDR). Speech recognition tests were compared as a function of ECDLR and electrode array length itself. Main outcome measures The relationship between ECDLR and percent correct on speech recognition tests. Results A second order polynomial regression relating ECDLR to percent correct on the CNC words speech recognition test was statistically significant, as was a fourth order polynomial regression for the AzBio Quiet test. In contrast, there was no statistically significant relationship between speech recognition scores and electrode array length. Conclusions ECDLR values can be statistically associated to speech-recognition outcomes. However, these ECDLR values cannot be predicted by the electrode length alone, and must include a measure of CDL.

Development of an image‐based measurement system for human facial skin colour

AbstractIn this study, an image‐based measurement system was developed for human facial skin colour, involving the development of a digital imaging system, collection of facial skin colour from 60 human subjects, generation of different colour characterization models, and performance evaluation. The factors that affect facial skin colour characterization, including different training datasets (two colour charts and the collected facial skin colour dataset), mathematical mapping methods (linear transformation, polynomial regression, root‐polynomial regression and neural network) and camera image formats (JPG and RAW), were investigated and quantified not only by the conventional method of CIELAB colour difference, but also two newly introduced measures, facial colour contrast and skin colour gamut. The results indicate that the RAW image format for camera digital signals gave a more stable performance than the JPG format images, and the higher order polynomial regression with good predictive accuracy in terms of CIELAB colour difference did not perform well for the whole facial image. It is suggested to evaluate the model performance using the colour of both specific facial positions and the overall facial skin colour. Our comparative analysis in this study provides useful guidance for determining the colour characterization model for facial skin.

Isotope partitioning between cow milk and farm water: A tool for verification of milk provenance

RationaleThe oxygen and hydrogen isotope compositions of the water component of the milk from nine Italian dairy farms were studied together with the farm water for one year. The aim was to verify the importance of farm water and seasonal temperature variation on milk isotope values and propose mathematical relations as new tools to identify the milk origin.MethodsMilk was centrifuged to separate the solids and then distilled under vacuum to separate water. δ(18O/16O) and δ(2H/1H) analyses of the water molecules were carried out using a water equilibrator online with a mass spectrometer. For oxygen and hydrogen isotope determination, water was equilibrated with pure CO2 for 7.5 h and with pure H2 for 5 h, respectively. The isotope ratio value is indicated with δ (expressed on the VSMOW/SLAP scale) as defined by IUPAC.ResultsThe average annual isotope value of milk at the different cattle sheds is mostly related to the farm water suggesting that the drinking water is the most important factor influencing the isotopic values of the milk water. The milk/water fractionation factor correlates with the milking time and, thus, the seasonal temperature is best described by a 4th order polynomial regression line. A two‐level check model was used to verify the milking provenance.ConclusionsThis study shows that it is essential to analyze both milk and farm water to indicate provenance. A two‐step verification tool, based on the difference between the measured and calculated δ(18O/16O)M values, and the difference between the calculated and estimated milk‐water fractionation factors, allowed the source determination of milk. Both conditions must be met if the milk is considered to be from the Parmigiano‐Reggiano production region. Although this approach was developed for this region, it can easily be tested and adapted to other dairy production areas.

Coagulation kinetic study and optimization using response surface methodology for effective removal of turbidity from paint wastewater using natural coagulants

The wastewater from paint manufacturing industry contains high quantity of pollutants that are generated from washing equipment, as well as chemical additives. Hence, coagulation–flocculation was applied in the present study to evaluate the performance of some natural coagulant derived from Hibiscus esculentus L,(okra) Detarium microcarpum,(sweet dater) Xanthosoma (cocoyam) and Crassostrea Virginica, (oyster shell) in the removal of turbidity from paint wastewater (PW). The coagulants were characterized using Fourier transform infrared spectrometer (FTIR), Scanning electron microscopy (SEM) and X-ray diffraction (XRD). A laboratory jar test was employed for the experiments. Process kinetic was studied to determine coagulation-flocculation parameters such as coagulation rate constant and coagulation half-life τ1/2. The effects of the operating parameters such as initial pH of the wastewater, coagulant dosage and settling time affecting the efficiency of turbidity removal were studied in a one-factor-at-a-time (OFAT) process. Box-Behnken Design (BBD) was used in designing the experiment; evaluate the individual and interactive effect of the variables and determining the optimum conditions. Statistical parameters such as coefficient of determination R2, sum of square roots due to error (SSE) and the root mean square error (RMSE) were used to evaluate the adequacy of the process. The optimum removal of turbidity was observed at pH range 2–4, dosage 100–200 mg/L and settling time of 30 min for the coagulants, with removal efficiency of 60–92.6% a second order polynomial regression equation with R2 values of 0.9644, 0.9827, 0.9707 and 0.9718 for OSC, DMC, CYC and ODC, respectively. While the coagulation half-time, τ1/2 ranges from 0.98 for OSC, 0.87 for DMC, 13.73 for CYC and 9.15 for ODC. The study has proved the coagulant can be used in treatment of turbidity from paint wastewater.

Utilizing Design of Experiments Approach to Assess Kinetic Parameters for a Mn Homogeneous Hydrogenation Catalyst.

Homogeneous hydrogenation catalysts based on metal complexes provide a diverse and highly tunable tool for the fine chemical industry. To fully unleash their potential, fast and effective methods for the evaluation of catalytic properties are needed. In turn, this requires changes in the experimental approaches to test and evaluate the performance of the catalytic processes. Design of experiment combined with statistical analysis can enable time‐ and resource‐efficient experimentation. In this work, we employ a set of different statistical models to obtain the detailed kinetic description of a highly active homogeneous Mn (I) ketone hydrogenation catalyst as a representative model system. The reaction kinetics were analyzed using a full second order polynomial regression model, two models with eliminated parameters and finally a model which implements “chemical logic”. The coefficients obtained are compared with the corresponding high‐quality kinetic parameters acquired using conventional kinetic experiments. We demonstrate that various kinetic effects can be well captured using different statistical models, providing important insights into the reaction kinetics and mechanism of a complex catalytic reaction.

Development of organizational and technical methods for predicting emergency situations and possible losses as their results

Emergency prevention is based on analysis, forecasting and early response to emergencies. A systematic approach to solving the problem of preventing emergencies envisages forecasting emergencies by type, level and possible losses caused as a their results both in the state as a whole and in its regions. To implement a systematic approach based on a formalized mathematical model, an organizational and technical method has been developed for predicting emergencies and possible losses caused as their results.
 The method is a combination of a variable order polynomial regression method, a weighted least squares method, and a probabilistic statistical method. This allows to compensate for the shortcomings of some at the expense of others, which will lead to an increase in forecasting accuracy.
 A control algorithm has been developed for the implementation of an organizational and technical method for predicting emergency situations and possible losses caused as their results. Its use involves the implementation of a number of interrelated procedures. At the first stage, the collection, processing and analysis of information on emergency situations in the country for a certain period of monitoring is carried out. This is the basis for predicting the processes of emergencies in general, in nature, level and types, as well as losses due to them both in the state and its regions. The information received is taken into account when forming a decision on the actions of civil protection units in order to adequately respond to emergency situations and eliminate their consequences. Based on the analysis of the effectiveness of the actions of the response units, the decisions on the elimination of emergency situations are adjusted.
 The developed method makes it possible to reasonably approach the planning and implementation of organizational and technical measures to prevent emergency situations, taking into account the potential threats to the territories and population of the country's regions

Ginkgo biloba leaf extract improves growth, intestinal histomorphometry, immunity, antioxidant status and modulates transcription of cytokine genes in hapa-reared Oreochromis niloticus

This study was designed to evaluate the impacts of dietary supplementation with Ginkgo biloba leaf extract (GBL) on the growth, intestinal histomorphometry, immunity, antioxidant status, and expression of cytokine genes in Nile tilapia reared in the hapas. A control diet was enriched with different GBL levels (0.0, 5.0, 7.0, and 9.0 g/kg) to form 4 experimental diets and were fed to Nile tilapia for 8 weeks. The findings illustrated that dietary GBL significantly enhanced the growth and feed utilization indices compared to those reared in the control group. A dose-dependent increase of hepatic catalase, superoxide dismutase, and glutathione peroxidase activities alongside a decline of hepatic malondialdehyde levels were recorded in GBL groups compared with the control. Serum lysozyme activity, complement C3, and immunoglobulin M levels were significantly increased in GBL groups compared with the control group. Moreover, dietary GBL maintained the normal intestinal and hepatopancreatic histological structures with a significant increase of some histomorphometric measurements of proximal, middle, and distal intestinal parts of the treated fish. Interestingly, dietary GBL supplementation significantly increased the mRNA expression of interleukin-1 beta (IL-1β), IL-6, IL-10, tumor necrosis factor alpha (TNF-α) and interferon gamma (INF-γ) genes in the splenic tissues of treated fish over the control group. To conclude, it could be recommended to use GBL as a functional phytogenic feed additive to improve the growth, hepatic and intestinal health status, hepatic antioxidant status, and immunity of treated Nile tilapia. Besides, the second order polynomial regression revealed that 7.50 g GBL/kg diet is the optimal inclusion level to improve growth with no negative impacts on the overall health condition of treated Nile tilapia.

Predictive model of water stress in tenera oil palm by means of spectral signature methods

Agriculture as a competitive business, seeks to improve productivity within crops with a more sustainable environmental management. It is important that agriculture includes new technologies that allow it to generate differential, precise and real-time information. In Colombia, the current lack of knowledge about techniques that allow early identification of water stress in African palm could generate a loss in the investment made in the fertilization of the crop, cause an increase in diseases, pests, and susceptibility to compaction or abortions in female flowers that would lead to decreases in production. In this work, a predictive model is established to quantify water stress based on spectral, physiological and soil information in African palm plants. To this end, a study was carried out in an oil palm plantation where treatments were established with 3 ranges of humidity. It was found that the indices with the highest correlation with the biophysical variable soil moisture were: NDVI_1 and NDVI_16 for treatment 1, SR_4 for treatment 2 and NDVI_16 and NDVI_20 for treatment 3. Finally, the third order polynomial regression model that obtained higher correlation coefficients of Pearson R^2=0.73 was selected as the most suitable model to estimate soil moisture content for treatments 2 and 3.

21 Geometric analysis of the urethral-vaginal interface in women with and without stress urinary incontinence

Previous studies have demonstrated structural differences of the urethra between women with and without stress urinary incontinence (SUI). In this pilot study, we hypothesize that there is a difference in the curvature of the urethral-vaginal interface in this population, as assessed by geometric analysis, due to differences in lateral urethral support associated with SUI. We conducted a pilot case-control study using magnetic resonance imaging (MRI) scans of 18 women with and without SUI. The urethral-vaginal interface at the level of the mid-urethra was marked with 9 points (Figure 1a) and fitted with a second order polynomial regression (Figure 1b). The chord length and chord-to-vertex length of the resulting parabolic curve, with respect to the lateral interface borders, were used to calculate the arc length and radius of a circular arc fitted to the interface curvature. Two evaluators made measurements. Demographic and clinical data including age, body mass index (BMI), maximal urethral closing pressure (MUCP), and POP-Q parameters were collected. The groups were stratified by those with and without SUI as well as those with and without anterior wall prolapse beyond 2 cm proximal to the hymen (Aa >-2), given the relationship between anterior wall prolapse and SUI. Normality of data was assessed using the Shapiro-Wilk test. Comparison of groups was performed using the Wilcoxon Rank-Sum test. Age and BMI were similar in the two groups (Table 1). The radius of the urethral-vaginal interface curvature was found to be smaller in subjects with Aa >-2 (8.4 vs 11.9 mm, P = 0.03); this was not found to be different between subjects with and without SUI (8.8 vs 9.2 mm, P = 0.53). The chord length, chord-to-vertex length, and arc length comprising the urethral-vaginal interface curvature were similar between subjects with and without SUI, and between subjects with and without Aa >-2 (P > 0.05 for all). Subjects with SUI had a lower MUCP than subjects without SUI (41.5 vs 67.3 cm H2O, P = 0.008); MUCP among subjects with and without anterior wall prolapse, as defined above, was similar (48.0 vs 45.7 cm H2O, P = 0.82). In this pilot study population, the radius of the urethral-vaginal interface curvature at the mid-urethra was smaller among women with anterior vaginal wall prolapse beyond 2 cm proximal to the hymen. A statistically significant difference in the urethral-vaginal interface curvature among women with and without SUI was not found; however, this may be due to the small sample size.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Dietary organic selenium improves growth, serum biochemical indices, immune responses, antioxidative capacity, and modulates transcription of stress-related genes in Nile tilapia reared under sub-optimal temperature.

A 56-day feeding experiment was carried out to investigate the influences of dietary organic selenium (OS) on the growth, body composition, serum biochemistry, stress responses, and immune indices of Nile tilapia reared under sub-optimal temperature. Fish (5.61±0.5g) were allotted in seven experimental groups (5 replicates per each) and fed on a basal diet supplemented with 0.0 (CTR), 0.1, 0.2, 0.3, 0.4, 0.5, and 0.6mg OS/kg diet and reared under temperature ranged 21.50±0.50°C. Final body weight, weight gain, and specific growth rate were significantly increased in OS groups compared to the CTR group. Moreover, the feed conversion ratio was significantly decreased in OS groups, especially at fish groups fed 0.3-0.6mg OS/kg diet compared to the other groups. The lowest survival rate (%) was found in OS groups between 0.0 and 0.2mg/kg diet. A significant increase in the crude protein (%) and dry matter (%) in OS groups alongside a significant decrease in the ash (%) compared to the CTR group. Blood proteins (total protein, albumin, and globulin), reduced glutathione, immunoglobulin M, and complement C3 values alongside the serum lysozyme and catalase activities were significantly increased compared to the CTR group. Contrarywise, serum transaminases (alanine transaminase and aspartate transaminase), cortisol, urea, and creatinine values were significantly decreased in OS groups than the CTR group. No significant differences were noticed in the mRNA transcripts of the hepatic heat shock protein 70 among all experimental groups. Meanwhile, significant differences were observed in the mRNA transcripts of hepatic heat shock protein 27, superoxide dismutase, and glutathione peroxidase genes among all experimental groups. The second order polynomial regressions illustrated that the optimal inclusion OS level in diets for Nile tilapia reared under sub-optimal temperature is 0.36-0.39mg/kg diet based on weight gain and cortisol levels, respectively. Conclusively, the present study exemplified that dietary inclusion with 0.36-0.39mg OS/kg diet improved the growth, immunity and modulate the stress responses in Nile tilapia reared under sub-optimal temperature.

A Statistical Analysis of Observational Hubble Parameter Data to Discuss the Cosmology of Holographic Chaplygin Gas

A scheme for the generalized Chaplygin gas equation of state is shown by using the holographic Ricci dark energy. Regression analysis and a chi-square test were performed. A second order polynomial regression has been established as the relation between the Hubble Parameter and redshift. It has established a set of parameters that can predict the Equation of State (EoS) parameter.

Study of mathematics modeling on ginger geometric changes during drying using image analysis

Many studies have examined the drying process, but only a few studies have examined shrinkage as one of the parameters that affect drying. Depreciation of agricultural products could have an impact on damage and reduce quality. This study aimed to examine the shrinkage pattern of product size during drying using the mathematical model approach regression. The method used was experimental with sliced ginger as material. The equipment used was a rack-type hybrid dryer and a set of image capture devices. This study indicates that to dry the sliced ginger from 95.65% to 9.49% moisture content required approximately 8 hours. The results of image processing showed shrinkage that occurs in sliced ginger was 52.49%. The most accurate mathematical model describing the prediction of sliced ginger shrinkage during drying was the 2nd order polynomial regression model with the equation of y = - 131.3.x 2 - 1804.4x + 41941.6 and an R2 value of 0.99.

Sensitively and quickly detecting Vibrio vulnificus by real time recombinase polymerase amplification targeted to vvhA gene

Vibrio vulnificus (V. vulnificus) is a Gram-negative bacterium living in warm and salty water. This marine bacterium could produce hemolysin (VVH), which often causes serious gastroenteritis or septicemia when people contact to seawater or seafood containing V. vulnificus. Timely diagnosis is regard as essential to disease surveillance. In this paper, we aimed at developing a quick and sensitive method for the detection of Vibrio vulnificus using real time recombinase polymerase amplification (real time RPA). Specific primers and an exo probe were designed on the basis of the vvhA gene sequence available in GenBank. Target DNA could be amplified and labeled with specific fluorophore within 20 min at 38 °C. The method exhibited a high specificity, only detecting Vibrio vulnificus and not showing cross-reaction with other bacteria. The sensitivity of this method was 2 pg per reaction (20 μL) for DNA, or 200 copies per reaction (20 μL) for standard plasmid. The detection limit (LOD) stated as the target level that would be detected 95% of the time and estimated was 1.58 × 102 copies by fit of the probit to the results of 8 replicates in different concentration. For quantitative analysis of the real time RPA, the second order polynomial regression was adopted in our study. The results showed the correlation coefficients were raised above 0.98, which suggested this model might be a better choice for the quantitative analysis of real time RPA compared to the routine linear regression model. For artificially contaminated plasma samples, Vibrio vulnificus could be detected within 16 min by real time RPA at concentration as low as 1.2 × 102 CFU/mL or 2.4 CFU per reaction (20 μL). Thus, the real time RPA method established in this study shows great potential for detecting Vibrio vulnificus in the research laboratory and disease diagnosis.

Effects of fermented Broussonetia papyrifera on growth, intestinal antioxidant, inflammation and microbiota of grass carp (Ctenopharyngodon idella)

The present study was conducted to investigate the influence of fermented Broussonetia Papyrifera (FBP) on growth performance, intestinal antioxidant capacity, inflammation and microbiota of grass carp. Fish (initial weight: 50.0 ± 0.5 g) were fed diets with 0 (control diet), 5 % (FBP5), 10 % (FBP10), 15 % (FBP15) and 20 % (FBP20) of FBP supplementation respectively for 8 weeks. The results showed that FBP5 group significantly decreased FCR of grass carp (P < 0.05). Besides, FBP supplementation significantly decreased intestine Cu/Zn SOD activity (P < 0.05), as well as significantly elevated mRNA expression level of kelch-like-ECH-associated protein 1 (keap1) and depressed mRNA expression level of NF-E2-related factor 2 (nrf2), superoxide dismutase 1 (sod1) and catalase (cat) (P < 0.05). The content of malondialdehyde (MDA) increased significantly in the FBP20 group compared to the control diet (P < 0.05). The expression level of interleukin-8 (il-8) and interferon γ (ifnγ) downregulated with increased dietary FBP, and significant difference was found in FBP20 group (P < 0.05). In addition, when the supplementation of FBP was no more than 15 %, the abundance of Firmicutes and Fusobacteria increased significantly, while the abundance of Actinobacteria and Cyanobacteria decreased significantly in intestine of grass carp (P < 0.05). Compared to the control diet, the richness and diversity of intestinal microbiota of grass carp decreased significantly in FBP20 group (P < 0.05). According to the second order polynomial regression equation analysis of SGR and FCR, the optimal additional level of FBP was estimated to be 4.58 % and 5.28 %, respectively. The recommended maximum addition of FBP in diet of grass carp was up to 15 % according to the results of intestinal microbiota.