The effect of temperature on bacterial growth in the presence of nonsterile ultrasound coupling gel

Ricci, Samantha; Pinette, Michael G.; Wax, Joseph R.; Craig, Wendy Y.; Forrest, Lisa J.; Dragoni, Catherine

doi:10.1016/j.ajog.2019.10.001

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…Bacterial growth is the coordinated sum of a series of complex processes, including chemical synthesis, assembly, polymerization, biosynthesis, and transport. The activity of bacterial growth is affected by temperature [ 34 , 35 ]. The variation of bacterial growth rate with temperature is a complex process, and the Arrhenius equation suggests that the maximum specific growth rate of bacteria is temperature-dependent [ 36 ].…”

Section: Resultsmentioning

confidence: 99%

Efficient Removal of Dental Plaque Biofilm from Training Typodont Teeth via Water Flosser

Wang,

Gao,

Chang

et al. 2023

Bioengineering

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Plaque biofilms play critical roles in the development of dental caries. Mechanical plaque control methods are considered to be most effective for plaque removal, such as brushing teeth or using flosser. Recently, water flosser has been paid much attention. Here, we tested the ability of a water flosser to remove the adhered sucrose and the dental plaque biofilms formed by Streptococcus mutans, Streptococcus sanguinis, and Actinobacillus viscosus. We found that the residual sucrose concentration was 3.54 mg/mL in the control group, 1.75 mg/mL in the syringe group (simulating the ordinary mouthwash), and 0 mg/mL in water flosser group. In addition, the residual bacterial concentration was 3.6 × 108 CFU/mL in the control group, 1.6 × 107 CFU/mL in the syringe group, and only 5.5 × 105 CFU/mL in the water flosser group. In summary, water flosser is effective for cleaning the teeth, which may have significant potential in preventing dental caries and maintaining oral health.

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Section: Resultsmentioning

confidence: 99%

Efficient Removal of Dental Plaque Biofilm from Training Typodont Teeth via Water Flosser

Wang,

Gao,

Chang

et al. 2023

Bioengineering

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“…This implies that the maximum growth of microorganisms in the wastewater was 30°C. The group of microorganisms that are found in wastewater are classified as mesophilic, and grow in the temperature range between 10°C and 45°C, with an optimum growth of 32.5°C [ 88 , 89 ]. Therefore, to ensure that microorganisms stay alive and maintain maximum growth, temperature should not exceed 30°C.…”

Section: Resultsmentioning

confidence: 99%

“…Biomass growth reached the peak at a temperature of 30 • C, beyond that temperature, biomass growth declined linearly as shown in Figure 17D. This implies that the maximum growth of microorganisms in the wastewater was 30 • C. The group of microorganisms that are found in wastewater are classified as mesophilic, and grow in the temperature range between 10 • C and 45 • C, with an optimum growth of 32.5 • C [88,89]. Therefore, to ensure that microorganisms stay alive and maintain maximum growth, temperature should not exceed 30 • C. Similar results have been reported by scholars [90,91].…”

Section: Sensitivity Analysismentioning

confidence: 89%

Application of Artificial Neural Network for predicting biomass growth during domestic wastewater treatment through a biological process

Muloiwa

Dinka

Nyende‐Byakika

2023

Engineering in Life Sciences

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The biological treatment process is responsible for removing organic and inorganic matter in wastewater. This process relies heavily on microorganisms to successfully remove organic and inorganic matter. The aim of the study was to model biomass growth in the biological treatment process. Multilayer perceptron (MLP) Artificial Neural Network (ANN) algorithm was used to model biomass growth. Three metrics: coefficient of determination ( R 2 ), root mean squared error (RMSE), and mean squared error (MSE) were used to evaluate the performance of the model. Sensitivity analysis was applied to confirm variables that have a strong influence on biomass growth. The results of the study showed that MLP ANN algorithm was able to model biomass growth successfully. R 2 values were 0.844, 0.853, and 0.823 during training, validation, and testing phases, respectively. RMSE values were 0.7476, 1.1641, and 0.7798 during training, validation, and testing phases respectively. MSE values were 0.5589, 1.3551, and 0.6081 during training, validation, and testing phases, respectively. Sensitivity analysis results showed that temperature (47.2%) and dissolved oxygen (DO) concentration (40.2%) were the biggest drivers of biomass growth. Aeration period (4.3%), chemical oxygen demand (COD) concentration (3.2%), and oxygen uptake rate (OUR) (5.1%) contributed minimally. The biomass growth model can be applied at different wastewater treatment plants by different plant managers/operators in order to achieve optimum biomass growth. The optimum biomass growth will improve the removal of organic and inorganic matter in the biological treatment process.

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Society for Maternal-Fetal Medicine Special Statement: Reducing the risk of transmitting infection by transvaginal ultrasound examination

Hamm

Combs

Davidson

2020

American Journal of Obstetrics and Gynecology

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The effect of temperature on bacterial growth in the presence of nonsterile ultrasound coupling gel

Cited by 5 publications

References 3 publications

Efficient Removal of Dental Plaque Biofilm from Training Typodont Teeth via Water Flosser

Efficient Removal of Dental Plaque Biofilm from Training Typodont Teeth via Water Flosser

Application of Artificial Neural Network for predicting biomass growth during domestic wastewater treatment through a biological process

Society for Maternal-Fetal Medicine Special Statement: Reducing the risk of transmitting infection by transvaginal ultrasound examination

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