Fecal calprotectin: A novel predictor of ulcerated esophageal injury after atrial fibrillation catheter ablation.

BACKGROUND: Atrial esophageal fistula (AEF) is a lethal complication that can occur post atrial fibrillation (AF) ablation. Esophageal injury (EI) is likely to be the initial lesion leading to AEF. Endoscopic examination is the gold standard for a diagnosis of EI but extensive endoscopic screening is invasive and costly. This study was conducted to determine whether fecal calprotectin (Fcal), a marker of inflammation throughout the intestinal tract, may be associated with the existence of esophageal injury. METHODS: This diagnostic study was conducted in a cohort of 166 patients with symptomatic AF undergoing radiofrequency catheter ablation from May 2020 to June 2021. Fcal tests were performed 1-7 days after ablation. All patients underwent endoscopic ultrasonography 1 or 2 days after ablation. RESULTS: The levels of Fcal were significantly different between the EI and non-EI groups (404.9 µg/g (IQR 129.6-723.6) vs. 40.4 µg/g (IQR 15.0-246.2), p < .001). Analysis of ROC curves revealed that a Fcal level of 125 µg/g might be the optimal cut-off value for a diagnosis of EI, giving a 78.8% sensitivity and a 65.4% specificity. The negative predictive value of Fcal was 100% for ulcerated EI. CONCLUSIONS: The level of Fcal is associated with EI post AF catheter ablation. 125 µg/g might be the optimal cut-off value for a diagnosis of EI. Negative Fcal could predict the absence of ulcerated EI, which could be considered a precursor to AEF.

Artificial Intelligence-based database for prediction of protein structure and their alterations in ocular diseases.

The aim of the study is to establish an online database for predicting protein structures altered in ocular diseases by Alphafold2 and RoseTTAFold algorithms. Totally, 726 genes of multiple ocular diseases were collected for protein structure prediction. Both Alphafold2 and RoseTTAFold algorithms were built locally using the open-source codebases. A dataset with 48 protein structures from Protein Data Bank (PDB) was adopted for algorithm set-up validation. A website was built to match ocular genes with the corresponding predicted tertiary protein structures for each amino acid sequence. The predicted local distance difference test-Cα (pLDDT) and template modeling (TM) scores of the validation protein structure and the selected ocular genes were evaluated. Molecular dynamics and molecular docking simulations were performed to demonstrate the applications of the predicted structures. For the validation dataset, 70.8% of the predicted protein structures showed pLDDT greater than 90. Compared to the PDB structures, 100% of the AlphaFold2-predicted structures and 97.9% of the RoseTTAFold-predicted structure showed TM score greater than 0.5. Totally, 1329 amino acid sequences of 430 ocular disease-related genes have been predicted, of which 75.9% showed pLDDT greater than 70 for the wildtype sequences and 76.1% for the variant sequences. Small molecule docking and molecular dynamics simulations revealed that the predicted protein structures with higher confidence scores showed similar molecular characteristics with the structures from PDB. We have developed an ocular protein structure database (EyeProdb) for ocular disease, which is released for the public and will facilitate the biological investigations and structure-based drug development for ocular diseases. Database URL:  http://eyeprodb.jsiec.org.

The effects of online peer-facilitated learning and distributed pair programming on students' learning.

The COVID-19 pandemic has forced universities and schools around the world to adopt online learning. Teachers may wonder if their students can attain satisfactory learning performance in an online learning environment without teachers' on-the-spot attention. In order to develop students' skills in programming, promote their enjoyment of learning and intention to learn to program, the researchers integrated two innovative teaching approaches, using online peer-facilitated learning and distributed pair programming, and investigated the effects of these on students' online learning performance. This study conducted an experiment that included 128 undergraduates from four class sections of Department of Finance. Thus, the experimental design in this research was a 2 (Peer-facilitated learning vs. non-peer-facilitated learning) × 2 (Distributed pair programming vs. non-distributed pair programming) factorial pretest/post-test design. The participants in this research mainly consisted of four classes of students from a non-computer or information department who took a compulsory course on programming design.' Both quantitative and qualitative data were collected in this study. According to the results, the peer-facilitated learning group exhibited significantly better development of programming skills, enjoyment of learning, and intention to learn, than the non-peer-facilitated learning group. However, expected effects of enhancing the learning of the students in this study who received the distributed pair programming were not found. The design of online pedagogy can be a reference for online educators. The implications of applying online peer-facilitated learning and distributed pair programming to support students' learning and the design of online programming courses are discussed.

Automatic Detection of Peripheral Retinal Lesions From Ultrawide-Field Fundus Images Using Deep Learning.

PURPOSE: To establish a multilabel-based deep learning (DL) algorithm for automatic detection and categorization of clinically significant peripheral retinal lesions using ultrawide-field fundus images. METHODS: A total of 5958 ultrawide-field fundus images from 3740 patients were randomly split into a training set, validation set, and test set. A multilabel classifier was developed to detect rhegmatogenous retinal detachment, cystic retinal tuft, lattice degeneration, and retinal breaks. Referral decision was automatically generated based on the results of each disease class. t -distributed stochastic neighbor embedding heatmaps were used to visualize the features extracted by the neural networks. Gradient-weighted class activation mapping and guided backpropagation heatmaps were generated to investigate the image locations for decision-making by the DL models. The performance of the classifier(s) was evaluated by sensitivity, specificity, accuracy, F 1 score, area under receiver operating characteristic curve (AUROC) with 95% CI, and area under the precision-recall curve. RESULTS: In the test set, all categories achieved a sensitivity of 0.836-0.918, a specificity of 0.858-0.989, an accuracy of 0.854-0.977, an F 1 score of 0.400-0.931, an AUROC of 0.9205-0.9882, and an area under the precision-recall curve of 0.6723-0.9745. The referral decisions achieved an AUROC of 0.9758 (95% CI= 0.9648-0.9869). The multilabel classifier had significantly better performance in cystic retinal tuft detection than the binary classifier (AUROC= 0.9781 vs 0.6112, P < 0.001). The model showed comparable performance with human experts. CONCLUSIONS: This new DL model of a multilabel classifier is capable of automatic, accurate, and early detection of clinically significant peripheral retinal lesions with various sample sizes. It can be applied in peripheral retinal screening in clinics.

Development of prediction models to estimate extubation time and midterm recovery time of ophthalmic patients undergoing general anesthesia: a cross-sectional study.

BACKGROUND: To develop prediction models for extubation time and midterm recovery time estimation in ophthalmic patients who underwent general anesthesia. METHODS: Totally 1824 ophthalmic patients who received general anesthesia at Joint Shantou International Eye Center were included. They were divided into a training dataset of 1276 samples, a validation dataset of 274 samples and a check dataset of 274 samples. Up to 85 to 87 related factors were collected for extubation time and midterm recovery time analysis, respectively, including patient factors, anesthetic factors, surgery factors and laboratory examination results. First, multiple linear regression was used for predictor selection. Second, different methods were used to develop predictive models for extubation time and midterm recovery time respectively. Finally, the models' generalization abilities were evaluated using a same check dataset with MSE, RMSE, MAE, MAPE, R-Squared and CCC. RESULTS: The fuzzy neural network achieved the highest R-Squared of 0.956 for extubation time prediction and 0.885 for midterm recovery time, and the RMSE value was 6.637 and 9.285, respectively. CONCLUSION: The fuzzy neural network developed in this study had good generalization performance in predicting both extubation time and midterm recovery time of ophthalmic patients undergoing general anesthesia. TRIAL REGISTRATION: This study is prospectively registered in the Chinese Clinical Trial Registry, registration number: CHiCRT2000036416, registration date: August 23, 2020.

Prevalence of myopia and uncorrected myopia among 721 032 schoolchildren in a city-wide vision screening in southern China: the Shantou Myopia Study.

AIMS: To explore the prevalence and risk factors for myopia and uncorrected myopia in schoolchildren in southern China. METHODS: The government-led Shantou Myopia Study was conducted from September 2020 to June 2021. Non-cycloplegic refraction was performed. Uncorrected visual acuity (UCVA) was measured along with presenting visual acuity if participants wore spectacles. Spherical equivalent refraction (SER) is defined as the spherical dioptres added to half of the cylindrical dioptres. Myopia is defined as SER <-0.50 dioptre with UCVA of <20/20 in at least one eye. RESULTS: This study enrolled 724 828 schoolchildren (77.8% of all schoolchildren in Shantou) from 901 schools. Data from 721 032 schoolchildren (99.5%) were analysed (mean age 11.53±3.13 years, 6-20 years, 373 230 boys and 347 802 girls). Among them, 373 459 (51.8%) had myopia: 37.1% of 465 696 children in primary schools, 75.4% of 170 164 children in junior high schools and 84.8% of 85 172 children in senior high schools. The prevalence of myopia increases non-linearly with age. Older age, female and urban living environment were independently associated with myopia prevalence and myopic SER. Among the 373 459 children with myopia, 60.0% had no refractive correction: 74.9%, 53.9% and 35.5% in primary, junior high and senior high schools, respectively. CONCLUSION: The overall prevalence of myopia among schoolchildren in Shantou was 51.8%, higher than the national average in China. The proportion of uncorrected myopia is high, especially in primary schools. Our results indicate the need for public education on eye care among schoolchildren even in a municipal city.

Evaluation of Myocilin Variant Protein Structures Modeled by AlphaFold2.

Deep neural network-based programs can be applied to protein structure modeling by inputting amino acid sequences. Here, we aimed to evaluate the AlphaFold2-modeled myocilin wild-type and variant protein structures and compare to the experimentally determined protein structures. Molecular dynamic and ligand binding properties of the experimentally determined and AlphaFold2-modeled protein structures were also analyzed. AlphaFold2-modeled myocilin variant protein structures showed high similarities in overall structure to the experimentally determined mutant protein structures, but the orientations and geometries of amino acid side chains were slightly different. The olfactomedin-like domain of the modeled missense variant protein structures showed fewer folding changes than the nonsense variant when compared to the predicted wild-type protein structure. Differences were also observed in molecular dynamics and ligand binding sites between the AlphaFold2-modeled and experimentally determined structures as well as between the wild-type and variant structures. In summary, the folding of the AlphaFold2-modeled MYOC variant protein structures could be similar to that determined by the experiments but with differences in amino acid side chain orientations and geometries. Careful comparisons with experimentally determined structures are needed before the applications of the in silico modeled variant protein structures.

Integrating online meta-cognitive learning strategy and team regulation to develop students' programming skills, academic motivation, and refusal self-efficacy of Internet use in a cloud classroom.

With the development of technology and demand for online courses, there have been considerable quantities of online, blended, or flipped courses designed and provided. However, in the technology-enhanced learning environments, which are also full of social networking websites, shopping websites, and free online games, it is challenging to focus students' attention and help them achieve satisfactory learning performance. In addition, the instruction of programming courses constantly challenges both teachers and students, particularly in online learning environments. To overcome and solve these problems and to facilitate students' learning, the researchers in this study integrated two teaching approaches, using meta-cognitive learning strategy (MCLS) and team regulation (TR), to develop students' regular learning habits and further contribute to their programming skills, academic motivation, and refusal self-efficacy of Internet use, in a cloud classroom. In this research, a quasi-experiment was conducted to investigate the effects of MCLS and TR adopting the experimental design of a 2 (MCLS vs. non-MCLS) × 2 (TR vs. non-TR) factorial pre-test/post-test. In this research, the participants consisted of four classes of university students from non-information or computer departments enrolled in programming design, a required course. The experimental groups comprised three of the classes, labelled as G1, G2, and G3. G1 concurrently received both the online MCLS and TR intervention, while G2 only received the online MCLS intervention, and G3 only received the online TR intervention. Serving as the control group, the fourth class (G4) received traditional teaching. This study investigated the effects of MCLS, TR, and their combination, on improving students' programming skills, academic motivation, and refusal self-efficacy of Internet use in an online computing course. According to the results, students who received online TR significantly enhanced their programming design skills and their refusal self-efficacy of Internet use a cloud classroom. However, the expected effects of MCLS on developing students' programming skills, academic motivation, and refusal self-efficacy of Internet use were not found in this study. The teaching strategy of integrating MCLS and TR in an online programming course in this study can serve as a reference for educators when conducting online, blended, or flipped courses during the COVID-19 pandemic.

Automated multidimensional deep learning platform for referable diabetic retinopathy detection: a multicentre, retrospective study.

OBJECTIVE: To develop and validate a real-world screening, guideline-based deep learning (DL) system for referable diabetic retinopathy (DR) detection. DESIGN: This is a multicentre platform development study based on retrospective, cross-sectional data sets. Images were labelled by two-level certificated graders as the ground truth. According to the UK DR screening guideline, a DL model based on colour retinal images with five-dimensional classifiers, namely image quality, retinopathy, maculopathy gradability, maculopathy and photocoagulation, was developed. Referable decisions were generated by integrating the output of all classifiers and reported at the image, eye and patient level. The performance of the DL was compared with DR experts. SETTING: DR screening programmes from three hospitals and the Lifeline Express Diabetic Retinopathy Screening Program in China. PARTICIPANTS: 83 465 images of 39 836 eyes from 21 716 patients were annotated, of which 53 211 images were used as the development set and 30 254 images were used as the external validation set, split based on centre and period. MAIN OUTCOMES: Accuracy, F1 score, sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), Cohen's unweighted κ and Gwet's AC1 were calculated to evaluate the performance of the DL algorithm. RESULTS: In the external validation set, the five classifiers achieved an accuracy of 0.915-0.980, F1 score of 0.682-0.966, sensitivity of 0.917-0.978, specificity of 0.907-0.981, AUROC of 0.9639-0.9944 and AUPRC of 0.7504-0.9949. Referable DR at three levels was detected with an accuracy of 0.918-0.967, F1 score of 0.822-0.918, sensitivity of 0.970-0.971, specificity of 0.905-0.967, AUROC of 0.9848-0.9931 and AUPRC of 0.9527-0.9760. With reference to the ground truth, the DL system showed comparable performance (Cohen's κ: 0.86-0.93; Gwet's AC1: 0.89-0.94) with three DR experts (Cohen's κ: 0.89-0.96; Gwet's AC1: 0.91-0.97) in detecting referable lesions. CONCLUSIONS: The automatic DL system for detection of referable DR based on the UK guideline could achieve high accuracy in multidimensional classifications. It is suitable for large-scale, real-world DR screening.

Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks.

Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appropriate treatments. Single disease-based deep learning algorithms had been developed for the detection of diabetic retinopathy, age-related macular degeneration, and glaucoma. Here, we developed a deep learning platform (DLP) capable of detecting multiple common referable fundus diseases and conditions (39 classes) by using 249,620 fundus images marked with 275,543 labels from heterogenous sources. Our DLP achieved a frequency-weighted average F1 score of 0.923, sensitivity of 0.978, specificity of 0.996 and area under the receiver operating characteristic curve (AUC) of 0.9984 for multi-label classification in the primary test dataset and reached the average level of retina specialists. External multihospital test, public data test and tele-reading application also showed high efficiency for multiple retinal diseases and conditions detection. These results indicate that our DLP can be applied for retinal fundus disease triage, especially in remote areas around the world.

Automated Explainable Multidimensional Deep Learning Platform of Retinal Images for Retinopathy of Prematurity Screening.

Importance: A retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy assessed by experienced ophthalmologists. A deep learning algorithm based on retinal images may facilitate early detection and timely treatment of ROP to improve visual outcomes. Objective: To develop a retinal image-based, multidimensional, automated, deep learning platform for ROP screening and validate its performance accuracy. Design, Setting, and Participants: A total of 14 108 eyes of 8652 preterm infants who received ROP screening from 4 centers from November 4, 2010, to November 14, 2019, were included, and a total of 52 249 retinal images were randomly split into training, validation, and test sets. Four main dimensional independent classifiers were developed, including image quality, any stage of ROP, intraocular hemorrhage, and preplus/plus disease. Referral-warranted ROP was automatically generated by integrating the results of 4 classifiers at the image, eye, and patient levels. DeepSHAP, a method based on DeepLIFT and Shapley values (solution concepts in cooperative game theory), was adopted as the heat map technology to explain the predictions. The performance of the platform was further validated as compared with that of the experienced ROP experts. Data were analyzed from February 12, 2020, to June 24, 2020. Exposure: A deep learning algorithm. Main Outcomes and Measures: The performance of each classifier included true negative, false positive, false negative, true positive, F1 score, sensitivity, specificity, receiver operating characteristic, area under curve (AUC), and Cohen unweighted κ. Results: A total of 14 108 eyes of 8652 preterm infants (mean [SD] gestational age, 32.9 [3.1] weeks; 4818 boys [60.4%] of 7973 with known sex) received ROP screening. The performance of all classifiers achieved an F1 score of 0.718 to 0.981, a sensitivity of 0.918 to 0.982, a specificity of 0.949 to 0.992, and an AUC of 0.983 to 0.998, whereas that of the referral system achieved an F1 score of 0.898 to 0.956, a sensitivity of 0.981 to 0.986, a specificity of 0.939 to 0.974, and an AUC of 0.9901 to 0.9956. Fine-grained and class-discriminative heat maps were generated by DeepSHAP in real time. The platform achieved a Cohen unweighted κ of 0.86 to 0.98 compared with a Cohen κ of 0.93 to 0.98 by the ROP experts. Conclusions and Relevance: In this diagnostic study, an automated ROP screening platform was able to identify and classify multidimensional pathologic lesions in the retinal images. This platform may be able to assist routine ROP screening in general and children hospitals.

[Effect of the Combined Use of Denitrifying Bacteria, Calcium Nitrate, and Zirconium-Modified Zeolite on the Mobilization of Nitrogen and Phosphorus in Sediments and Evaluation of Its Nitrate-Nitrogen Releasing Risk].

In this work, the influence of an integrated method based on calcium nitrate, denitrifying bacteria, and zirconium-modified zeolite (CN+DB+ZZ) on the transport and transformation of nitrogen (N) and phosphorus (P) in sediments was investigated, and the risk of nitrate release from the calcium nitrate-injected sediment was evaluated. The effects of the single calcium nitrate injection (CN), calcium nitrate, and denitrifying bacteria combined treatment (CN+DB) and the combined treatment using calcium nitrate injection and zirconium-modified zeolite capping (CN+ZZ) on the mobilization of N and P in sediment were compared, and the nitrate releasing risk of these methods was also evaluated. The results indicated that although CN treatment could effectively control the P release from the sediment, this method could not effectively control the release of ammonium-nitrogen from sediment and has a high risk of releasing nitrate-nitrogen. The CN+DB combined method not only could effectively control the liberation of sedimentary P but also reduce the risk of nitrate-nitrogen release from the calcium nitrate-injected sediment compared with the single CN method. However, the CN+DB combined method could not effectively control the release of ammonium-nitrogen from the sediment. The CN+ZZ combined treatment not only could effectively prevent the release of sedimentary P but could also greatly reduce the release of ammonium-nitrogen from the sediment. However, the CN+ZZ combined method could result in a substantial release of nitrate-nitrogen from the calcium nitrate-injected sediment. The CN+DB+ZZ combined technology could effectively control the release of P from sediment as well as greatly reduce the risk of ammonium-nitrogen release from the sediment. Furthermore, the CN+DB+ZZ combined method resulted in a significant reduction of nitrate-nitrogen released from the calcium nitrate-injected sediment compared with the CN and CN+ZZ treatment methods. The prevention of the dissolution of the P-bound iron oxide/hydroxide in the sediment, the reduction of redox-sensitive P in sediment, and the improvement of the phosphate and ammonium adsorption abilities of sediment by the CN+DB+ZZ combined method is critical to control the release of phosphorus and ammonium-nitrogen from sediment using this method. Results of this study reveal that the CN+DB+ZZ combined technology could be a promising method for the control of phosphorus and ammonium-nitrogen release from sediments.

[Combined Use of Zirconium-Modified Bentonite Capping and Calcium Nitrate Addition to Control the Release of Phosphorus from Sediments].

In this study, sediment incubation experiments were carried out to investigate the efficiency and mechanism of the control of phosphorus (P) release from sediments. The results showed that under anoxic conditions, P could be released from the sediment into the pore water first and then the dissolved P in the pore water could be transported into the overlying water, leading to high concentrations of soluble reactive P (SRP) and diffusive gradient in thin-films (DGT)-labile P in the overlying water. However, the combined use of calcium nitrate (CN) addition and zirconium-modified bentonite (ZB) capping could effectively control the release of P from sediment, resulting in the low concentrations of SRP and DGT-labile P in the overlying water. Furthermore, the combined use of CN addition and ZB capping could significantly decrease the concentrations of SRP and DGT-labile P in the sediment. In addition, the combined utilization of CN addition and ZB capping also could result in a reduction of redox sensitive P (BD-P) in the uppermost sediment layer. The reduction of pore water SRP, DGT-labile P, and BD-P in sediment solids is of great importance to the control of sediment-P liberation by the combined use of CN addition and ZB capping. The reduction efficiency of overlying water SRP by combined CN addition/ZB capping technology was higher than that of single CN addition technology. Compared to that of single CN addition technology, the reduction efficiencies of pore water SRP, SRP diffusion flux across the sediment/overlying water interface (SWI), and BD-P in the sediment by the combined use of CN addition and ZB capping were also higher. The combined technology based on CN addition and ZB capping had a higher reduction efficiency of overlying water SRP during the late stage of sediment remediation than the single technology based on ZB capping, and the former had higher reduction efficiencies of pore water SRP, DGT-labile P, and SRP diffusion flux across the SWI and apparent P diffusion flux through the SWI than the latter. The results of this work indicate that the combined use of CN addition and ZB capping is a very promising method for the control of P release from sediments.

Qingxin Kaiqiao Fang Inhibits Aß 25-35-Induced Apoptosis in Primary Cultured Rat Hippocampal Neuronal Cells via the p38 MAPK Pathway: An Experimental Validation and Network Pharmacology Study.

Qingxin kaiqiao fang (QKF), a traditional Chinese medicine compound, has been applied to treat Alzheimer's disease (AD) for many years and has exhibited remarkable effects. However, the underlying mechanism is still not explicit. The current study aims to investigate whether QKF exerts an antiapoptotic role through the p38 MAPK pathway in the course of AD. Network pharmacology analysis was applied to study the effective components, possible therapeutic targets, and AD-related pathway of QKF. Further, the AD cell model was established using amyloid-beta (Aß)25-35 peptide and primary hippocampal neuronal cells extracted from newborn Sprague-Dawley rats. Microtubule-associated protein-2 (MAP-2) imaging was used to detect the morphology of hippocampal neurons. Western blot (WB) analysis was applied to detect the protein expression levels of p38 MAPK, p-p38 MAPK, Bcl-2, Bax, caspase-3, and cleaved caspase-3. Cell viability and apoptosis were determined using cell counting kit-8 (CCK-8) and terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling (TUNEL) assays, respectively. SB203580 and U46619 were used to detect changes in cell morphology, cell viability, and apoptosis upon inhibiting or activating p38 MAPK. Our present work showed that QKF protects hippocampal neuronal morphology, enhances cell viability, and reduces the number of TUNEL-positive cells. In addition, our results showed that QKF increased the expression levels of antiapoptotic proteins and decreased the expression of proapoptotic proteins. QKF at 25 mg·mL-1 best inhibited neuronal apoptosis among the three doses of QKF by suppressing p38 MAPK activity. Collectively, QKF plays an antiapoptotic role via the p38 MAPK pathway.

[Use of Iron-modified Calcite as an Active Capping Material to Control Phosphorus Release from Sediments in Surface Water Bodies].

The use of calcite (CA) as an active capping material has high potential for controlling the release of phosphorus (P) from sediments, but its efficiency still needs to be enhanced. To address this issue, an iron-modified CA (Fe-CA) was prepared, the removal performance of phosphate from aqueous solution by Fe-CA was studied, and the efficiency of the use of Fe-CA as an active capping material to prevent the liberation of P from sediments was investigated. The results showed that Fe-CA exhibited much higher phosphate removal ability than CA. The phosphate removal efficiency of Fe-CA increased with an increase in the Fe-CA dosage. Increasing the initial phosphate concentration gave rise to an increase in the amount of phosphate removed by Fe-CA, and the maximum amount of phosphate removed by Fe-CZ reached 3.09 mg·g-1. Sediment capping with Fe-CA could effectively control the release of soluble reactive P (SRP) from the sediment into the overlying water, leading to a very low concentration of SRP in the overlying water. Additionally, the Fe-CA capping also resulted in the transformation of a small amount of redox-sensitive P (BD-P) and metal-oxide-bound P (NaOH-rP) in sediments to residual P (Res-P), leading to a slight increase in the stability of P in the sediment. The overwhelming majority (90.8%) of P bound by the Fe-CA capping layer existed in the form of NaOH-rP, calcium-bound P (HCl-P), and Res-P, which are relatively very stable. Furthermore, the percentage of bioavailable P (BAP) as a proportion of total extractable P in the P-bound Fe-CA capping layer was very low, and the bound P was re-released with difficulty into the water column for algae growth. Compared to CA capping, the efficiency for the control of sedimentary P release into the overlying water by Fe-CA capping was much higher, and the stability of P bound by the Fe-CA capping layer was also higher. The results of this work indicate that Fe-CA is a very promising active capping material for the interception of the release of P from sediments into the overlying water.

[Efficiency of Magnesium Hydroxide Capping and Amendment to Control Phosphorus Release from Sediments].

Eutrophication of freshwater bodies has become a global environmental problem, and phosphorus (P) has been identified as one of the key limiting factors responsible for this eutrophication problem. Reducing internal P release is crucial to the control of the eutrophication of freshwater bodies besides reducing the input of external P. To control sedimentary P release, magnesium hydroxide[Mg(OH)2] was applied as a capping and amendment material in this study. The adsorption performance of phosphate on Mg(OH)2 was investigated in batch mode, and the effect of Mg(OH)2 capping and amendment on the mobilization of P in sediments was studied using sediment incubation experiments. Results showed that Mg(OH)2 exhibited good adsorption performance toward phosphate. The phosphate removal efficiency of Mg(OH)2 increased with increasing adsorbent dosage. The adsorption equilibrium data of phosphate on Mg(OH)2 could be better described by the Freundlich and Dubinin-Radushkevich isotherm models compared to the Langmuir isotherm model. Mg(OH)2 capping and addition both could effectively control the release of reactive soluble P (SRP) from sediments into the overlying water, resulting in a low concentration of SRP in the overlying water under Mg(OH)2 capping and amendment conditions. Mg(OH)2 capping and amendment both could reduce pore water SRP in the uppermost sediment (0-10 mm), which played a key role in the control of the release of SRP from sediments into the overlying water. The as-prepared Mg(OH)2 possessed a much higher phosphate adsorption ability than commercial Mg(OH)2, and the former also had a higher controlling efficiency of sedimentary P release than the latter. In summary, Mg(OH)2 is a promising capping and amendment material for the control of internal phosphorus release in freshwater bodies.

[Regulating Effect and Mechanism of Calcite/Chlorapatite Mixture Addition on Transformation and Transport of Phosphorus in Sediments].

Understanding the effect of calcite and chlorapatite mixture (CA/ClAP) addition on the mobilization of phosphorus (P) in sediments is crucial to the application of CA/ClAP as an amendment material to control the release of P from sediments. To address this issue, batch experiments were conducted to investigate the removal performance of phosphate by CA/ClAP, and sediment incubation experiments were carried out to study the effect of CA/ClAP addition on the mobilization of P in sediments. The results showed that the removal ability of phosphate by CA/ClAP was much higher than those by calcite and chlorapatite, and the kinetics data of phosphate removal by CA/ClAP followed a pseudo-second-order kinetics model. Increasing calcite and chlorapatite dosages would be favorable for the removal of phosphate by CA/ClAP, and coexisting Ca2+ enhanced the phosphate removal. CA/ClAP addition not only reduced the concentration of soluble reactive P (SRP) in the overlying water, but also decreased the concentration of SRP in the pore water. The addition of CA/ClAP in sediments caused an increase in the content of P in the sediments, but the increased P mainly existed in the form of calcium-bound P (HCl-P), which was difficult to be re-released into the water column under anoxic and common pH (5-9) conditions. The reduction of SRP in the pore water after the addition of CA/ClAP played an important role in the prevention of sedimentary P liberation into the overlying water by the CA/ClAP amendment. The results of this work indicate that CA/ClAP can be used as an amendment material for interception of the release of P from sediments into overlying water.

Risk of esophageal thermal injury during catheter ablation for atrial fibrillation guided by different ablation index.

BACKGROUND: During ablation for atrial fibrillation (AF), energy delivery toward the left atrial posterior wall may cause esophageal injury (EI). Ablation index (AI) was introduced to estimate ablation lesion size, however, the impact of AI technology on the risk of EI has not been explored. METHOD: From March 2019 to December 2019, 60 patients with paroxysmal AF undergoing first-time ablation were prospectively enrolled. The first 30 consecutive patients were ablated with the AI target value of 400 (AI-400 group), and the later 30 consecutive patients were ablated with the AI target value of 350 at the posterior wall (AI-350 group). Endoscopic ultrasonography was used to evaluate EI postablation. EI was classified as a category 1 (erythema or erosion) or a category 2 (hematoma or ulceration). RESULTS: Compared with the AI-400 group (59.9 ± 8.4 years; male, 60%), the AI-350 group (59.1 ± 9.9 years; male, 50%) had a lower incidence of EI (3.3% vs 26.7%, P = .03). There was no significant difference in the percentage of first-pass PVI between the AI-400 group and the AI-350 group (left PVI: 80% vs 73.4%, P = .54; right PVI: 80% vs 60%, P = .1). Neither ablation time nor fluoroscopy time was significantly different between the AI-400 group and the AI-350 group. CONCLUSIONS: AF ablation guide by AI target value of 350 may reduce esophageal thermal injury and has a similar efficiency on the acute success rate of first-pass PVI compared with an AI target value of 400 at the posterior wall.

Qingxin Kaiqiao Recipe Improves Cognitive Performance, Inhibits Apoptosis, and Reduces Pathological Deposits in APP/PS1 Double Transgenic Mice via the PI3K/Akt Pathway.

The traditional Chinese medicine of Qingxin Kaiqiao Recipe (QKR) is effective in the treatment of Alzheimer's disease (AD). This study aims to investigate whether QKR improves the cognitive ability and takes neuroprotective effect on APP/PS1 double transgenic mice via the PI3K/Akt pathway. APP/PS1 double transgenic mice were randomly divided into a model, donepezil-treated, or QKR-treated group (L-QKR: 4.75 mg/kg/d, M-QKR: 9.5 mg/kg/d, and H-QKR: 19 mg/kg/d, respectively). Wild-type C57/BL6J mice were used as the control group. Morris water maze (MWM) was used to test the ability of spatial navigation and memorization; terminal deoxynucleotidyl transferase-mediated dUTP nick end-labelling (TUNEL) assay was applied to test the apoptosis; amyloid protein granule deposition was detected via Methenamine silver staining; Western blot (WB) analysis, immunohistochemistry, and RT-PCR were applied to measure the expression of Aß and corresponding indicators of the PI3K/Akt pathway. Compared with the model group, QKR significantly relieved the cognitive impairment, reduced the deposition of senile plaques, decreased the expression of GSK-3α and Aß, and increased the expression of p-PI3K, p-Akt, and IDE. In addition, the number of TUNEL-positive cells decreased after treatment using QKR. The current study proved that QKR, especially at the high dose tested, exerted a protective effect on improving learning and memory, inhibiting apoptosis, and reducing the process of pathological degeneration in the hippocampus of AD mice.

[Adsorption of Phosphate on Mg/Fe Layered Double Hydroxides (Mg/Fe-LDH) and Use of Mg/Fe-LDH as an Amendment for Controlling Phosphorus Release from Sediments].

We determine the efficiency and mechanism of Mg/Fe layered double hydroxides (Mg/Fe-LDH) addition for the control of phosphorus (P) release from sediments by studying the adsorption behavior and mechanism of phosphate from an aqueous solution on Mg/Fe-LDH. The impact of Mg/Fe-LDH addition on the mobilization of P in sediments as well as the adsorptive removal of phosphate by sediments is investigated, and the stabilization of P bound by Mg/Fe-LDH is also evaluated. Results showed that the kinetics data of phosphate adsorption onto Mg/Fe-LDH fitted better with the Elovich kinetics model than with the pseudo-first-order and pseudo-second-order kinetics models, and that the Freundlich and Dubinin-Radushkevich models were more suitable for describing the adsorption isotherm behavior of phosphate on Mg/Fe-LDH than the Langmuir model. Phosphate adsorption possessed a wide effective pH range of 4-10. Coexisting Ca2+ and Mg2+ enhanced phosphate adsorption onto Mg/Fe-LDH, while coexisting Na+, K+, and Cl- had negligible impacts on the phosphate adsorption. The presence of SO42- and HCO3- in aqueous solution inhibited the adsorption of phosphate on Mg/Fe-LDH. The phosphate adsorption mechanisms were deduced to be anion exchange, electrostatic attraction, ligand exchange and inner-sphere complex formation. The addition of Mg/Fe-LDH into sediments not only greatly reduced the concentration of reactive soluble P (SRP) in the overlying water, but also significantly decreased the level of SRP in the pore water. In addition, Mg/Fe-LDH addition also increased the adsorption capacity for the sediments, and the phosphate adsorption ability for the Mg/Fe-LDH-amended sediments increased with increased amendment dosage. Almost half of the phosphate bound by Mg/Fe-LDH existed in the form of relatively stable P, i.e., metal oxide-bound P (NaOH-rP), which was difficult to release back into the water column under normal pH and anoxic conditions. Nearly half of the phosphate bound by Mg/Fe-LDH existed in the form of easily released P, i.e., NH4Cl extractable P (NH4Cl-P) and redox-sensitive P (BD-P), which had a high risk of re-releasing into the water column. We conclude that it is very necessary for Mg/Fe-LDH to be recycled from the sediments after the application of Mg/Fe-LDH as an amendment to control sedimentary P liberation.