Optimization on structure and operation parameters of biofilter for decentralized sewage treatment.

Aiming for treating decentralized domestic wastewater in rural China, this study evaluates the effects of ceramsite size and structure, and water recirculation parameters, upon the performance of recirculating biofilter (RBF). RBF shows stable capability of chemical oxygen demand (COD) remediation and ammonia nitrification. In addition, the microbial flora and structures of the various layers in the system are analyzed via high-throughput sequencing in order to study the microbial diversity. The results indicate that while the ceramic particle size has no significant influence on the COD remediation capacity, the ceramics with smaller particle sizes exhibit better ammonia nitrogen (NH4+-N) removal ability, with a first-order linear relationship between the influent ammonia nitrogen load and the effluent NH4+-N concentration in RBF (R2 > 0.64). An increased hydraulic load and intermittent operation are shown to deteriorate the water quality with respect to NH4+-N, while an increased recirculation ratio increases the removal rate of NH4+-N from the effluent. Further, the water distribution time has a stronger effect upon the NH4+-N concentration in the effluent than does the recirculation ratio. Moreover, the microbial structure of the multi-layer recirculating trickle biofilter varies significantly during the process. The results indicate that a high recirculation ratio, long water distribution time, and multi-layer structure will be beneficial for improving the pollutant treatment capacity of RBF.

Diagnosis of COVID-19 via acoustic analysis and artificial intelligence by monitoring breath sounds on smartphones.

Scientific evidence shows that acoustic analysis could be an indicator for diagnosing COVID-19. From analyzing recorded breath sounds on smartphones, it is discovered that patients with COVID-19 have different patterns in both the time domain and frequency domain. These patterns are used in this paper to diagnose the infection of COVID-19. Statistics of the sound signals, analysis in the frequency domain, and Mel-Frequency Cepstral Coefficients (MFCCs) are then calculated and applied in two classifiers, k-Nearest Neighbors (kNN) and Convolutional Neural Network (CNN), to diagnose whether a user is contracted with COVID-19 or not. Test results show that, amazingly, an accuracy of over 97% could be achieved with a CNN classifier and more than 85% on kNN with optimized features. Optimization methods for selecting the best features and using various metrics to evaluate the performance are also demonstrated in this paper. Owing to the high accuracy of the CNN model, the CNN model was implemented in an Android app to diagnose COVID-19 with a probability to indicate the confidence level. The initial medical test shows a similar test result between the method proposed in this paper and the lateral flow method, which indicates that the proposed method is feasible and effective. Because of the use of breath sound and tested on the smartphone, this method could be used by everybody regardless of the availability of other medical resources, which could be a powerful tool for society to diagnose COVID-19.

Regulation of anaerobic fermentation for producing short-chain fatty acids from primary sludge in WWTPs by different alkalis.

Carbon source production from primary sludge in wastewater treatment plants (WWTPs) via anaerobic fermentation process has been paid more attention. However, slow hydrolysis rate and low yield of short-chain fatty acids (SCFAs) limited its application. This study aimed at improving the anaerobic fermentation efficiency of primary sludge by alkali regulation (NaOH, Na2CO3 and Ca(OH)2), and revealing the mechanism. Results showed that three kinds of alkalis allowed enhancing hydrolysis and acidification, and reducing methane production in the anaerobic fermentation process of primary sludge. The Na2CO3 regulation contributed to highest yield and productivity of SCFAs, reaching 1626 mg COD/L and 0.189 g COD/g VSS at 4th day, respectively. Microbial community structure analysis indicated that the relative abundance of fermentative microbial community was improved in the alkali regulation system, where methanogenic archaea was effectively inhibited. The continuous flow experiment further verified that the Na2CO3 regulation could steadily increase yield of SCFAs in the anaerobic fermentation process of primary sludge, and the yield was also the highest among three kinds of alkali regulation.

Modeling sulfide production in full flow concrete sewers based on the HRT variation of sewerage.

The corrosion and odor in concrete sewers are mainly related to the sulfide production, which is, under certain circumstances, directly proportional to the hydraulic retention time (HRT) of the sewer. To reduce the corrosion and control the odor in concrete sewers, it is necessary to model the production of sulfide in the concrete sewers with different HRTs. However, previous researches were mostly carried out in simulated Perspex-made sewers, and the obtained theoretical formulas based on the Monod equation were impractical because of the complexity. An actual concrete pipe with domestic sewage was employed in this study to obtain a simple but practical model, which can be applied to quantitively describe the sulfide production according to the HRT of the sewer and the chemical oxygen demand (COD) of the sewage. The empirical equation obtained was rs = (0.045 × lnHRT + 0.071) × ([COD] - b)0.6, the coefficient is a logarithmic function of the HRT, and the sulfide production rate and COD have a power relationship. Based on the data of COD and HRT obtained in the realistic sewer, the production of sulfide in the sewer can be predicted for better maintaining sewers through sulfide control.

Design, synthesis and evaluation of wound healing activity for ß-sitosterols derivatives as potent Na+/K+-ATPase inhibitors.

ß-Sitosterols, is a common steroid that can be identified in a variety of plants and their efficacy in promoting wound healing has been demonstrated. Na+/K+-ATPase, more than a pump, its signal transduction function for involvement in cell growth regulation attracts widespread concern. The Na+/K+-ATPase/Src receptor complex can serve as a receptor involved in multiple signaling pathways including promoting wound healing pathways. To finding potent accelerating wound healing small molecular, we choose the high inhibitory activity of Na+/K+-ATPase and non-cardiotoxic natural compound, ß-sitosterol as the substrate. A series of ß-sitosterol derivatives were designed, synthesized and evaluated as potential Na+/K+-ATPase inhibitors. Among them, compounds 31, 47, 49, showed improved inhibitory activity on Na+/K+-ATPase, with IC50 value of 3.0 µM, 3.4 µM, 2.2 µM, which are more potent than ß-sitosterol with IC50 7.6 µM. Especially, compound 49 can induce cell proliferation, migration and soluble collagen production in L929 fibroblasts. Compared to model, compound 49 can accelerate wound healing in SD rats. Further studies indicated that 49 can activate the sarcoma (Src), uptake the protein kinase B (Akt), extracellular signal-regulated kinase (ERK) proteins expression in a concentration dependent manner. Finally, binding mode of compound 49 with Na+/K+-ATPase was studied, which provides insights into the determinants of potency and selectivity. These results proved ß-stitosterol derivative 49 can serve as an effective inhibitor of Na+/K+-ATPase and potential candidate for accelerating wound healing agents.

Molecular mechanisms through which different carbon sources affect denitrification by Thauera linaloolentis: Electron generation, transfer, and competition.

Characterizing the molecular mechanism through which different carbon sources affect the denitrification process would provide a basis for the proper selection of carbon sources, thus avoiding excessive carbon source dosing and secondary pollution while also improving denitrification efficiency. Here, we selected Thauera linaloolentis as a model organism of denitrification, whose genomic information was elucidated by draft genome sequencing and KEGG annotations, to investigate the growth kinetics, denitrification performances and characteristics of metabolic pathways under diverse carbon source conditions. We reconstructed a metabolic network of Thauera linaloolentis based on genomic analysis to help develop a systematic method of researching electron pathways. Our findings indicated that carbon sources with simple metabolic pathways (e.g., ethanol and sodium acetate) promoted the reproduction of Thauera linaloolentis, and its maximum growth density reached OD600 = 0.36 and maximum specific growth rate reached 0.145 h-1. These carbon sources also accelerated the denitrification process without the accumulation of intermediates. Nitrate could be reduced completely under any carbon source condition; but in the "glucose group", the maximum accumulation of nitrite was 117.00 mg/L (1.51 times more than that in the "ethanol group", which was 77.41 mg/L), the maximum accumulation of nitric oxide was 363.02 µg/L (7.35 times more than that in the "ethanol group", which was 49.40 µg/L), and the maximum accumulation of nitrous oxide was 22.58 mg/L (26.56 times more than that in the "ethanol group", which was 0.85 mg/L). Molecular biological analyses demonstrated that diverse types of carbon sources directly induced different carbon metabolic activities, resulting in variations in electron generation efficiency. Furthermore, the activities of the electron transport system were positively correlated with different carbon metabolic activities. Finally, these differences were reflected in the phenomenon of electronic competition between denitrifying reductases. Thus we concluded that this was the main molecular mechanism through which the carbon source type affected the denitrification process. In brief, carbon sources with simple metabolic pathways induced higher efficiency of electron generation, transfer, and competition, which promoted rapid proliferation and complete denitrification; otherwise Thauera linaloolentis would grow slowly and intermediate products would accumulate seriously. Our study established a method to evaluate and optimize carbon source utilization efficiency based on confirmed molecular mechanisms.

A Blockchain-Based Federated Learning Method for Smart Healthcare.

The development of artificial intelligence and worldwide epidemic events has promoted the implementation of smart healthcare while bringing issues of data privacy, malicious attack, and service quality. The Medical Internet of Things (MIoT), along with the technologies of federated learning and blockchain, has become a feasible solution for these issues. In this paper, we present a blockchain-based federated learning method for smart healthcare in which the edge nodes maintain the blockchain to resist a single point of failure and MIoT devices implement the federated learning to make full of the distributed clinical data. In particular, we design an adaptive differential privacy algorithm to protect data privacy and gradient verification-based consensus protocol to detect poisoning attacks. We compare our method with two similar methods on a real-world diabetes dataset. Promising experimental results show that our method can achieve high model accuracy in acceptable running time while also showing good performance in reducing the privacy budget consumption and resisting poisoning attacks.

A Machine Learning Model to Predict Risperidone Active Moiety Concentration Based on Initial Therapeutic Drug Monitoring.

Risperidone is an efficacious second-generation antipsychotic (SGA) to treat a wide spectrum of psychiatric diseases, whereas its active moiety (risperidone and 9-hydroxyrisperidone) concentration without a therapeutic reference range may increase the risk of adverse drug reactions. We aimed to establish a prediction model of risperidone active moiety concentration in the next therapeutic drug monitoring (TDM) based on the initial TDM information using machine learning methods. A total of 983 patients treated with risperidone between May 2017 and May 2018 in Beijing Anding Hospital were collected as the data set. Sixteen predictors (the initial TDM value, dosage, age, WBC, PLT, BUN, weight, BMI, prolactin, ALT, MECT, Cr, AST, Ccr, TDM interval, and RBC) were screened from 26 variables through univariate analysis (p < 0.05) and XGBoost (importance score >0). Ten algorithms (XGBoost, LightGBM, CatBoost, AdaBoost, Random Forest, support vector machine, lasso regression, ridge regression, linear regression, and k-nearest neighbor) compared the model performance, and ultimately, XGBoost was chosen to establish the prediction model. A cohort of 210 patients treated with risperidone between March 1, 2019, and May 31, 2019, in Beijing Anding Hospital was used to validate the model. Finally, the prediction model was evaluated, obtaining R 2 (0.512 in test cohort; 0.374 in validation cohort), MAE (10.97 in test cohort; 12.07 in validation cohort), MSE (198.55 in test cohort; 324.15 in validation cohort), RMSE (14.09 in test cohort; 18.00 in validation cohort), and accuracy of the predicted TDM within ±30% of the actual TDM (54.82% in test cohort; 60.95% in validation cohort). The prediction model has promising performance to facilitate rational risperidone regimen on an individualized level and provide reference for other antipsychotic drugs' risk prediction.

FV-429 induces autophagy blockage and lysosome-dependent cell death of T-cell malignancies via lysosomal dysregulation.

It is widely accepted that lysosomes are essential for cell homeostasis, and autophagy plays an important role in tumor development. Here, we found FV-429, a synthetic flavonoid compound, inhibited autophagy flux, promoted autophagosomes accumulation, and inhibited lysosomal degradation in T-cell malignancies. These effects were likely to be achieved by lysosomal dysregulation. The destructive effects of FV-429 on lysosomes resulted in blockage of lysosome-associated membrane fusion, lysosomal membrane permeabilization (LMP), and cathepsin-mediated caspase-independent cell death (CICD). Moreover, we initially investigated the effects of autophagy inhibition by FV-429 on the therapeutic efficacy of chemotherapy and found that FV-429 sensitized cancer cells to chemotherapy agents. Our findings suggest that FV-429 could be a potential novel autophagy inhibitor with notable antitumor efficacy as a single agent.

Cholesterol-associated lysosomal disorder triggers cell death of hematological malignancy: Dynamic analysis on cytotoxic effects of LW-218.

The integrity of lysosomes is of vital importance to survival of tumor cells. We demonstrated that LW-218, a synthetic flavonoid, induced rapid lysosomal enlargement accompanied with lysosomal membrane permeabilization in hematological malignancy. LW-218-induced lysosomal damage and lysosome-dependent cell death were mediated by cathepsin D, as the lysosomal damage and cell apoptosis could be suppressed by depletion of cathepsin D or lysosome alkalization agents, which can alter the activity of cathepsins. Lysophagy, was initiated for cell self-rescue after LW-218 treatment and correlated with calcium release and nuclei translocation of transcription factor EB. LW-218 treatment enhanced the expression of autophagy-related genes which could be inhibited by intracellular calcium chelator. Sustained exposure to LW-218 exhausted the lysosomal capacity so as to repress the normal autophagy. LW-218-induced enlargement and damage of lysosomes were triggered by abnormal cholesterol deposition on lysosome membrane which caused by interaction between LW-218 and NPC intracellular cholesterol transporter 1. Moreover, LW-218 inhibited the leukemia cell growth in vivo. Thus, the necessary impact of integral lysosomal function in cell rescue and death were illustrated.

Effect of operating temperature on the efficiency of ultra-short-sludge retention time activated sludge systems.

There are abundant recyclable carbon, nitrogen, and phosphorus resources in wastewater and their efficient recovery is a heavily studied topic at present. As an effective means of carbon and phosphorus recovery, the ultra-short-sludge retention time (SRT) activated sludge (USSAS) system has increasingly attracted the attention of researchers. In this study, the capture efficiency and mechanism of carbon/phosphorus, and the microbial characteristics of the USSAS system, were studied at different temperatures (12, 18, 24, and 30 °C) and a 3-day SRT. The results showed that temperature had little effect on the carbon capture efficiency but had a considerable impact on the carbon capture mode. Increasing temperature decreased the EPS content and increased the biological metabolic activity, then decreasing adsorption but increasing the biotransformation effect. There was a negative correlation between temperature and phosphorus capture efficiency. As the temperature increased, the biological phosphorus removal effect decreased, but the adsorptive phosphorus removal effect gradually increased. With decreasing temperatures, the mixed liquid volatile suspended solid (MLVSS)/mixed liquid suspended solid (MLSS) value increased, but there was a risk of sludge bulking. Kinetic parameters confirmed microbial energy storage under lower temperature conditions and high biological activity under higher temperature conditions.

A Risk Scoring Model for High-Dose Methotrexate-Induced Liver Injury in Children With Acute Lymphoblastic Leukemia Based on Gene Polymorphism Study.

A study on 70 acute lymphoblastic leukemia (ALL) children (age ≤16 years) treated with high-dose methotrexate (HD-MTX) in Sichuan Provincial People's Hospital was conducted. The aim of the study was to establish a risk-scoring model to predict HD-MTX-induced liver injury, considering gene polymorphisms' effects. Data screening was performed through t-test, chi-square test, and ridge regression, and six predictors were identified: age, MTRR_AA, MTRR_AG, SLCO1B1_11045879_CC, albumin_1 day before MTX administration, and IBIL_1 day before MTX administration (p < 0.1). Then, the risk-scoring model was established by ridge regression and evaluated the prediction performance. In a training cohort (n = 49), the area under the curve (AUC) was 0.76, and metrics including accuracy, precision, sensitivity, specificity, positive predictive value, and negative predictive value were promising (0.86, 0.81, 0.76, 0.91, 0.81, 0.88, respectively). In a test cohort (n = 21), the AUC was 0.62 and negative predictive value was 0.80; other evaluation metrics were not satisfactory, possibly due to the limited sample size. Ultimately, the risk scores were stratified into three groups based on their distributions: low- (≤48), medium- (49-89), and high-risk (>89) groups. This study could provide knowledge for the prediction of HD-MTX-induced liver injury and reference for the clinical medication.

Optimization nutrient removal at different volume ratio of anoxic-to-aerobic zone in integrated fixed-film activated sludge (IFAS) system.

This study evaluated the influence of different volume ratios of the anoxic-to-aerobic zone (Vano/Vaer) on the enhancement of nitrogen and phosphorus removal in an integrated fixed-film activated sludge (IFAS) system. As the Vano/Vaer increased from 1:2 to 2:1, the removal of organic carbon, nitrogen and phosphorus nutrients of the IFAS system was improved. At Vano/Vaer = 1:1, the removal effect of nitrogen and phosphorus nutrients was optimal, and the average removal rates of COD, NH4+-N, TN, and TP of the system reached 90 ± 3.2%, 98.2 ± 1.4%, 88.9 ± 2.2%, and 89.1 ± 2.7%, respectively. As the volume of the anoxic zone continued to increase, the denitrifying phosphate-accumulating capacity of the system was enhanced, and the highest ratio of specific anoxic and aerobic phosphorus uptake rate could reach 65.3%. Analysis of the molecular evaluation showed that, the proportion of nitrifying bacteria in the biofilm gradually increased as Vano increased. Moreover, denitrifying phosphate-accumulating organisms (DNPAOs), ammonia-oxidizing archaea (AOA), and anaerobic ammonium oxidizing (Anammox) bacteria were all enriched all showed enrichment in the biofilm of fiber carriers, which further strengthened the system's synergistic removal of nitrogen and phosphorus.

Prediction of Chloride Distribution for Offshore Concrete Based on Statistical Analysis.

Chloride-induced corrosion is the main threat to the service life of concrete structures. In order to better investigate chloride distribution in offshore concrete, this study proposed a new prediction model based on statistical analysis as well as a large body of experimental results collected from various sources. A detailed discussion found that the key influential parameters, such as diffusion coefficient ( D ), surface chloride concentration ( C S ) and penetration depth ( x ) are all highly time-dependent. The exposure zone, water-cement ratio and service time were also considered as relevant factors. The proposed model is then validated by two alternative tests and the results suggest that it is feasible in predicting the chloride content and penetration depth of concrete structures in a marine environment under chloride attack.

Comparative efficacy and safety of analgesics for acute renal colic: A network meta-analysis protocol.

INTRODUCTION: Acute renal colic is one of the most common urological emergencies. While previous randomized controlled trials (RCTs) and pairwise meta-analyses only looked at the efficacy of 1 or 2 analgesics. It is not fully understood that the comprehensive ranking of the effectiveness and safeness of analgesics from these published articles. Therefore, this network meta-analysis (NMA) aims to compare and rank the different analgesics for treatment of acute renal colic. METHODS AND ANALYSIS: We will perform a systematic literature search in PubMed, EMBASE, CINAHL, Web of Science, and Cochrane Library to identify RCTs of different analgesics for acute renal colic. RCTs assessing active analgesics intervention against active comparator or placebo controls for acute renal colic will be included. We will also screen the reference lists of included studies, previous reviews and meta-analyses to identify other relevant trials. The primary outcomes will be pain variance at 30 minutes, need rescue medicine, complete pain relief or at least 50% pain relief at 30 minutes, and pain relapse within 24 hours. We will also assess secondary outcomes for safeness (side effects: dizziness, vomit, allergic, hypotension, cardiac toxicity, and drug dependence). The risk of bias of included RCTs will be assessed by using the Cochrane Collaboration's tool, and the quality of evidence will be assessed by using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) instrument. We will perform pairwise meta-analysis and Bayesian NMA to compare the effectiveness and safeness of different analgesic interventions. RESULTS: This NMA will compare and rank the different analgesics for treatment of acute renal colic. CONCLUSION: This is the first systematic review to use the NMA to comprehensively compare and rank analgesics for relieving pain of acute renal colic in adults based on most important factors deciding the choice of initial analgesia, and the results can provide implications for clinical practice and further research.