A novel approach has been developed to produce pure plant-based gel soy yogurt by combining soy proteins (7S/11S), high pressure homogenization, and glycation reaction.

This research sought to examine how the physicochemical characteristics of soy globulins and different processing techniques influence the gel properties of soy yogurt. The goal was to improve these gel properties and rectify any texture issues in soy yogurt, ultimately aiming to produce premium-quality plant-based soy yogurt. In this research study, the investigation focused on examining the impact of 7S/11S, homogenization pressure, and glycation modified with glucose on the gel properties of soy yogurt. A plant-based soy yogurt with superior gel and texture properties was successfully developed using a 7S/11S globulin-glucose conjugate at a 1:3 ratio and a homogenization pressure of 110 MPa. Compared to soy yogurt supplemented with pectin or gelatin, this yogurt demonstrated enhanced characteristics. These findings provide valuable insights into advancing plant protein gels and serve as a reference for cultivating new soybean varieties by soybean breeding experts.

Data-Driven Quantitative Structure-Activity Relationship Modeling for Human Carcinogenicity by Chronic Oral Exposure.

Traditional methodologies for assessing chemical toxicity are expensive and time-consuming. Computational modeling approaches have emerged as low-cost alternatives, especially those used to develop quantitative structure-activity relationship (QSAR) models. However, conventional QSAR models have limited training data, leading to low predictivity for new compounds. We developed a data-driven modeling approach for constructing carcinogenicity-related models and used these models to identify potential new human carcinogens. To this goal, we used a probe carcinogen dataset from the US Environmental Protection Agency's Integrated Risk Information System (IRIS) to identify relevant PubChem bioassays. Responses of 25 PubChem assays were significantly relevant to carcinogenicity. Eight assays inferred carcinogenicity predictivity and were selected for QSAR model training. Using 5 machine learning algorithms and 3 types of chemical fingerprints, 15 QSAR models were developed for each PubChem assay dataset. These models showed acceptable predictivity during 5-fold cross-validation (average CCR = 0.71). Using our QSAR models, we can correctly predict and rank 342 IRIS compounds' carcinogenic potentials (PPV = 0.72). The models predicted potential new carcinogens, which were validated by a literature search. This study portends an automated technique that can be applied to prioritize potential toxicants using validated QSAR models based on extensive training sets from public data resources.

How ambient temperature affects the heading date of foxtail millet (Setaria italica).

Foxtail millet (Setaria italica), a short-day plant, is one of the important crops for food security encountering climate change, particularly in regions where it is a staple food. Under the short-day condition in Taiwan, the heading dates (HDs) of foxtail millet accessions varied by genotypes and ambient temperature (AT). The allelic polymorphisms in flowering time (FT)-related genes were associated with HD variations. AT, in the range of 13°C-30°C that was based on field studies at three different latitudes in Taiwan and observations in the phytotron at four different AT regimes, was positively correlated with growth rate, and high AT promoted HD. To elucidate the molecular mechanism of foxtail millet HD, the expression of 14 key FT-related genes in four accessions at different ATs was assessed. We found that the expression levels of SiPRR95, SiPRR1, SiPRR59, SiGhd7-2, SiPHYB, and SiGhd7 were negatively correlated with AT, whereas the expression levels of SiEhd1, SiFT11, and SiCO4 were positively correlated with AT. Furthermore, the expression levels of SiGhd7-2, SiEhd1, SiFT, and SiFT11 were significantly associated with HD. A coexpression regulatory network was identified that shown genes involved in the circadian clock, light and temperature signaling, and regulation of flowering, but not those involved in photoperiod pathway, interacted and were influenced by AT. The results reveal how gene × temperature and gene × gene interactions affect the HD in foxtail millet and could serve as a foundation for breeding foxtail millet cultivars for shift production to increase yield in response to global warming.

Total Synthesis of (±)-Fasicularin through Double Consecutive Epimerizations.

The total synthesis of tricyclic marine alkaloid fasicularin (1b) has been accomplished from a novel sterically well-defined α-aminonitrile 7, featuring a novel double consecutive epimerization process and Ir-catalyzed reductive functionalization of a tertiary γ-lactam. The required configuration is obtained through the thermodynamically stereoselectively driven isomerization of a readily available 8a-cyanodecahydroquinoline framework. The strategy allows us to achieve the tricyclic core structures efficiently from affordable starting materials through simple operations.

Efficacy and Safety of Veno-Arterial Extracorporeal Membrane Oxygenation in the Treatment of High-Risk Pulmonary Embolism: A Retrospective Cohort Study.

Objectives: Veno-arterial extracorporeal membrane oxygenation (ECMO) is increasingly used to treat high-risk pulmonary embolism (PE). However, its efficacy and safety remain uncertain. This retrospective cohort study aimed to determine whether ECMO could improve the clinical outcomes of patients with high-risk PE. Methods: Forty patients with high-risk PE, who were admitted to Kaohsiung Chang Gung Memorial Hospital between January 2012 and December 2019, were included in this study. Demographic data and clinical outcomes were compared between patients treated without ECMO (non-ECMO group) and those treated with ECMO (ECMO group). Appropriate statistical tools were used to compare variables between groups and the survival was analyzed using the Kaplan-Meier method. Results: The overall in-hospital mortality rate was 55%, in which 65% (26/40) of patients presented with cardiac arrest with a mortality rate of 77%, which was higher than that of patients without cardiac arrest (14%). There was no significant difference in major complications and in-hospital mortality between the non-ECMO and ECMO groups. However, in subgroup analysis, compared with patients treated without ECMO, earlier ECMO treatment was associated with a reduced risk of cardiac arrest (P = 0.023) and lower in-hospital mortality (P = 0.036). A log-rank test showed a significantly higher cumulative overall survival in the earlier ECMO treatment group (P = 0.033). Conclusions: In this retrospective cohort study, earlier ECMO treatment was associated with lower in-hospital mortality among unstable patients without cardiac arrest. Our findings suggest that ECMO can be considered as an initial treatment option for patients with high-risk PE in higher-volume hospitals.

A systematic review and meta-analysis of the gut microbiota-dependent metabolite trimethylamine N-oxide with the incidence of atrial fibrillation.

BACKGROUND: The gut microbiota-dependent metabolite trimethylamine N-oxide (TMAO) has recently been recognized as one of the novel marker for adverse cardiovascular events and risk of death. However, data on the relationship between TMAO and atrial fibrillation (AF) is limited. The current study was performed to quantify and evaluate the relationship between circulating TMAO levels and AF occurrence. METHODS: The electronic databases PubMed, Cochrane Library, and Embase were systematically searched to March 20, 2021. Research studies were considered that recorded or analyzed the prevalence of AF in individuals in specific populations as well as their circulating TMAO levels. A meta-analysis of two-class variables was used to obtain pooled effects. A dose-response meta-analysis was used to investigate the dose-response relationship between TMAO levels and the risk of AF. RESULTS: Six studies with a total of 8,837 individuals and 1,668 AF cases were included in the present meta-analysis. Compared with a lower circulating TMAO level, a higher TMAO level was associated with a higher prevalence of AF [odds ratio (OR): 1.40; 95% confidence interval (CI): 1.23, 1.59; I2=19.8%]. The dose-response analysis revealed the risk of AF increased by 6% per 1-µmol/L increment (OR: 1.06; 95% CI: 1.00, 1.11), 32% per 5-µmol/L increment (OR: 1.32; 95% CI: 1.03, 1.70), and 73% per 10-µmol/L increment (OR: 1.73; 95% CI: 1.05, 2.86) of the circulating TMAO level. DISCUSSION: This is the first systematic literature review and meta-analysis to demonstrate a significant dose-dependent relationship between increased AF risk and circulating TMAO levels.

[Dynamic comparisons of epicardial electrograms between the left atrium and pulmonary veins in atrial fibrillation in goat model].

Objective: To compare epicardial electrograms between the left atrium (LA) and pulmonary veins (PVs) dynamically at development of persistent atrial fibrillation(AF) in goats PVs. Methods: Ten female goats were instrumented with electrodes at the LA and left side PV. Sustained AF (＞24 h) was induced in the goat by rapid intermittent left atrial pacing for(9.5±2.3)days at a pacing interval of 20 ms for 1 s with a maximum output of 6.0 V, followed by a 2-s period without pacing. Characteristics of PVs and LA epicardial electrograms were analyzed in the development of AF. Results: With prolonged stimulation, the duration of AF was prolonged, complex fractionated atrial electrograms(CFAEs) in LA and was increased gradually, PVs had more CFAEs than LA all the time. When induced AF lasted for more than 24 h, CFAEs in PVs became sustained approximately (2.7%±3.6% vs 92.6%±6.4%, at onset of AF vs AF lasted for more than 24 h, P＜0.05), and the ratio of CFAEs in PVs was more than that in LA (92.6%±6.4% vs 72.8%±5.3%, P＜0.05). Conclusion: The epicardial CFAEs are in specific area, which increase along with electrical remodeling. The epicardial CFAEs may play an important role in the maintenance of AF in this model.

Various machine learning approaches coupled with molecule simulation in the screening of natural compounds with xanthine oxidase inhibitory activity.

Gout is a common inflammatory arthritis associated with various comorbidities, such as cardiovascular disease and metabolic syndrome. Xanthine oxidase inhibitors (XOIs) have emerged as effective substances to control gout. Much attention has been given to the search for natural XOIs. In this study, a molecular database of natural XOIs was created for modeling purposes. Quantitative structure-activity relationship models were developed by combining various machine learning approaches and three descriptor pools. The models revealed several features of XOIs, including hydrophobicity and steric molecular structures. Experimental results showed the xanthine oxidase (XO) inhibitory activity of predicted compounds. Vanillic acid was identified as a promising new XOI candidate, with an IC50 of 0.593 µg mL-1. The functions of hydrogen bonds and hydrophobic interactions in XO activity inhibition were confirmed by molecular docking. This study fills knowledge gaps pertaining to the discovery of natural XOIs and to the interaction mechanisms between XOIs and XO.

Prediction of flavor and retention index for compounds in beer depending on molecular structure using a machine learning method.

In order to make a preliminary prediction of flavor and retention index (RI) for compounds in beer, this work applied the machine learning method to modeling depending on molecular structure. Towards this goal, the flavor compounds in beer from existing literature were collected. The database was classified into four groups as aromatic, bitter, sulfury, and others. The RI values on a non-polar SE-30 column and a polar Carbowax 20M column from the National Institute of Standards Technology (NIST) were investigated. The structures were converted to molecular descriptors calculated by molecular operating environment (MOE), ChemoPy and Mordred, respectively. By combining the pretreatment of the descriptors, machine learning models, including support vector machine (SVM), random forest (RF) and k-nearest neighbour (kNN) were utilized for beer flavor models. Principal component regression (PCR), random forest regression (RFR) and partial least squares (PLS) regression were employed to predict the RI. The accuracy of the test set was obtained by SVM, RF, and kNN. Among them, the combination of descriptors calculated by Mordred and RF model afforded the highest accuracy of 0.686. R 2 of the optimal regression model achieved 0.96. The results indicated that the models can be used to predict the flavor of a specific compound in beer and its RI value.

Predictive Modeling of Angiotensin I-Converting Enzyme Inhibitory Peptides Using Various Machine Learning Approaches.

Food-derived angiotensin I-converting enzyme (ACE) inhibitory peptides could potentially be used as safe supportive therapeutic products for high blood pressure. Theoretical approaches are promising methods with the advantage through exploring the relationships between peptide structures and their bioactivities. In this study, peptides with ACE inhibitory activity were collected and curated. Quantitative structure-activity relationship (QSAR) models were developed by using the combination of various machine learning approaches and chemical descriptors. The resultant models have revealed several structure features accounting for the ACE inhibitions. 14 new dipeptides predicted to lower blood pressure by inhibiting ACE were selected. Molecular docking indicated that these dipeptides formed hydrogen bonds with ACE. Five of these dipeptides were synthesized for experimental testing. The QSAR models developed were proofed to design and propose novel ACE inhibitory peptides. Machine learning algorithms and properly selected chemical descriptors can be promising modeling approaches for rational design of natural functional food components.

Amplitude reduction of autonomic nerve function is correlated with ablation lesion quality in patients with paroxysmal atrial fibrillation.

OBJECTIVE: Circumferential pulmonary vein isolation (CPVI) is a common procedure that is performed on patients with atrial fibrillation (AF). However, AF may recur in some patients after treatment. This study assesses the association between autonomic modulation and late recurrence after CPVI and between autonomic modulation and ablation lesion quality. METHODS: We prospectively enrolled 72 patients with paroxysmal AF who underwent CPVI from January 2017 to January 2018. Pre- and post-ablation 24 h electrocardiograms were performed to document heart rate variability (HRV), which represents cardiac autonomic function. The intraablation force-time integral (FTI) was used to indicate the extent of ablation injury. Patients were followed up for 12 months after the procedure and cases of AF recurrence were recorded. RESULTS: Changes in HRV decreased after the procedure, which was correlated with FTI (ΔSDNN: r = -0.26, P = 0.03; ΔrMMSD: r = -0.28, P = 0.02; ΔlnHF: r = -0.22, P = 0.04; ΔLnLF: r = -0.29, P = 0.01). Patients without AF recurrence had more pronounced ΔLF (-21.84 ± 33.21% vs. -8.68 ± 34.59%, P = 0.01) and ΔHF (-17.26 ± 16.61% vs. -1.28 ± 9.81%, P = 0.01) than patients with recurrence. Multivariate regression analysis showed that both ΔLF (HR: 1.07, P = 0.04) and ΔHF (HR: 1.11, P = 0.01) were associated with AF recurrence. After adjusting for FTI, ΔLF was no longer associated with AF recurrence (HR: 1.05, P = 0.10). ΔHF remained associated with AF recurrence (HR: 1.08, P = 0.03), but the correlation coefficient was decreased (HR: 1.08, P = 0.03). CONCLUSION: Decreased autonomic nerve function is a valid predictor of AF recurrence and is indicated by the extent of ablation injury, which is independently associated with AF recurrence after CPVI.

FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners.

Fourier transform infrared (FTIR) spectroscopy calibrations were developed to simultaneously determine the multianalytes of five artificial sweeteners, including sodium cyclamate, sucralose, sodium saccharin, acesulfame-K and aspartame. By combining the pretreatment of the spectrum and principal component analysis, 131 feature wavenumbers were extracted from the full spectral range for modelling to qualitative and quantitative analysis. Compared to random forest, k nearest neighbour and linear discriminant analysis, support vector machine model had better predictivity, indicating the most effective identification performance. Furthermore, multivariate calibration models based on partial least squares regression were constructed for quantifying any combinations of the five artificial sweeteners, and validated by prediction data sets. As shown by the good agreement between the proposed method and the reference HPLC for the determination of the sweeteners in beverage samples, a promising and rapid tool based on FTIR spectroscopy, coupled with chemometrics, has been performed to identify and objectively quantify artificial sweeteners.

Effects of febuxostat on atrial remodeling in a rabbit model of atrial fibrillation induced by rapid atrial pacing.

BACKGROUND: Febuxostat, a novel nonpurine selective inhibitor of xanthine oxidase (XO), may be used in the prevention and management of atrial fibrillation (AF). The purpose of this study was to evaluate the effects of febuxostat on atrial remodeling in a rabbit model of AF induced by rapid atrial pacing (RAP) and the mechanisms by which it acts. METHODS: Twenty-four rabbits were randomly divided into four groups: sham-operated group (Group S), RAP group (Group P), RAP with 5 mg/kg per day febuxostat group (Group LFP), and RAP with 10 mg/kg per day febuxostat group (Group HFP). All rabbits except those in Group S were subjected to RAP at 600 beats/min for four weeks. The effects of febuxostat on atrial electrical and structural remodeling, markers of inflammation and oxidative stress, and signaling pathways involved in the left atrium were examined. RESULTS: Shortened atrial effective refractory period (AERP), increased AF inducibility, decreased mRNA levels of Cav1.2 and Kv4.3, and left atrial enlargement and dysfunction were observed in Group P, and these changes were suppressed in the groups treated with febuxostat. Prominent atrial fibrosis was observed in Group P, as were increased levels of TGF-ß1, Collagen I, and α-SMA and decreased levels of Smad7 and eNOS. Treatment with febuxostat attenuated these differences. Changes in inflammatory and oxidative stress markers induced by RAP were consistent with the protective effects of febuxostat. CONCLUSIONS: This study is the first to find that febuxostat can inhibit atrial electrical and structural remodeling of AF by suppressing XO and inhibiting the TGF-ß1/Smad signaling pathway.

C2 HEST Score and Prediction of Incident Atrial Fibrillation in Poststroke Patients: A French Nationwide Study.

Background The C2HEST score (coronary artery disease or chronic obstructive pulmonary disease [1 point each]; hypertension [1 point]; elderly [age ≥75 years, 2 points]; systolic heart failure [2 points]; thyroid disease [hyperthyroidism, 1 point]) was initially proposed for predicting incident atrial fibrillation (AF) in the general population. Its performance in poststroke patients remains to be established, especially because patients at high risk for incident AF should be targeted for more comprehensive screening. This study aimed to evaluate this newly established incident AF prediction risk score in a post-ischemic stroke population. Methods and Results Validation was based on a hospital-based nationwide cohort with 240 459 French post-ischemic stroke patients. Kaplan-Meier curves for incident rate of AF depict differences between varying risk categories. Discrimination of the C2HEST score was evaluated using the C index, the net reclassification index, integrated discriminatory improvement, and decision curve analysis. During 7.9±11.5 months of follow-up, 14 095 patients developed incident AF. The incidence of AF increased from 23.5 per 1000 patient-years in patients with a C2HEST score of 0 to 196.8 per 1000 patient-years in patients with a C2HEST score ≥6. Kaplan-Meier curves showed a clear difference among different risk strata (log-rank P<0.0001). The C2HEST score had good discrimination with a C index of 0.734 (95% CI, 0.732-0.736), which was better than the Framingham risk score and the CHA2DS2-VASc score (congestive heart failure, hypertension, age ≥75 [doubled], diabetes mellitus, stroke [doubled], vascular disease, age 65 to 74 years, and female sex) ( P<0.0001, respectively). The C2HEST score was also superior to the Framingham risk score and the CHA2DS2-VASc score as shown by the net reclassification index, integrated discriminatory improvement ( P<0.0001, respectively) and decision curve analysis. Conclusions The C2HEST score performed well in discriminating the individual risk of developing incident AF in a white European population hospitalized with previous ischemic stroke. This simple score may potentially be used as a risk stratification tool for decision making in relation to a screening strategy for AF in post-ischemic stroke patients.

Diagnostic Performance of a Smart Device With Photoplethysmography Technology for Atrial Fibrillation Detection: Pilot Study (Pre-mAFA II Registry).

BACKGROUND: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. The asymptomatic nature and paroxysmal frequency of AF lead to suboptimal early detection. A novel technology, photoplethysmography (PPG), has been developed for AF screening. However, there has been limited validation of mobile phone and smart band apps with PPG compared to 12-lead electrocardiograms (ECG). OBJECTIVE: We investigated the feasibility and accuracy of a mobile phone and smart band for AF detection using pulse data measured by PPG. METHODS: A total of 112 consecutive inpatients were recruited from the Chinese PLA General Hospital from March 15 to April 1, 2018. Participants were simultaneously tested with mobile phones (HUAWEI Mate 9, HUAWEI Honor 7X), smart bands (HUAWEI Band 2), and 12-lead ECG for 3 minutes. RESULTS: In all, 108 patients (56 with normal sinus rhythm, 52 with persistent AF) were enrolled in the final analysis after excluding four patients with unclear cardiac rhythms. The corresponding sensitivity and specificity of the smart band PPG were 95.36% (95% CI 92.00%-97.40%) and 99.70% (95% CI 98.08%-99.98%), respectively. The positive predictive value of the smart band PPG was 99.63% (95% CI 97.61%-99.98%), the negative predictive value was 96.24% (95% CI 93.50%-97.90%), and the accuracy was 97.72% (95% CI 96.11%-98.70%). Moreover, the diagnostic sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of mobile phones with PPG for AF detection were over 94%. There was no significant difference after further statistical analysis of the results from the different smart devices compared with the gold-standard ECG (P>.99). CONCLUSIONS: The algorithm based on mobile phones and smart bands with PPG demonstrated good performance in detecting AF and may represent a convenient tool for AF detection in at-risk individuals, allowing widespread screening of AF in the population. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-OOC-17014138; http://www.chictr.org.cn/showproj.aspx?proj=24191 (Archived by WebCite at http://www.webcitation/76WXknvE6).

A Simple Clinical Risk Score (C2HEST) for Predicting Incident Atrial Fibrillation in Asian Subjects: Derivation in 471,446 Chinese Subjects, With Internal Validation and External Application in 451,199 Korean Subjects.

BACKGROUND: The incidence of atrial fibrillation (AF) is increasing, conferring a major health-care issue in Asia. No risk score for predicting incident AF has been specifically developed in Asian subjects. Our aim was to investigate risk factors for incident AF in Asian subjects and to combine them into a simple clinical risk score. METHODS: Risk factors for incident AF were analyzed in 471,446 subjects from the Chinese Yunnan Insurance Database (internal derivation cohort) and then combined into a simple clinical risk score. External application of the new score was performed in 451,199 subjects from the Korean National Health Insurance Service (external cohort). RESULTS: In the internal cohort, structural heart disease (SHD), heart failure (HF), age ≥ 75 years, coronary artery disease (CAD), hyperthyroidism, COPD, and hypertension were associated with incident AF. Given the low prevalence and the strong association of SHD with incident AF (hazard ratio, 26.07; 95% CI, 18.22-37.30; P < .001), these patients should be independently considered as high risk for AF and were excluded from the analysis. The remaining predictors were combined into the new simple C2HEST score: C2: CAD/COPD (1 point each); H: hypertension (1 point); E: elderly (age ≥ 75 years, 2 points); S: systolic HF (2 points); and T: thyroid disease (hyperthyroidism, 1 point). The C2HEST score showed good discrimination with the area under the curve (AUC) of 0.75 (95% CI, 0.73-0.77) and had good calibration (P = .774). The score was internally validated by bootstrap sampling procedure, giving an AUC of 0.75 (95% CI, 0.73-0.77). External application gave an AUC of 0.65 (95% CI, 0.65-0.66). The C2HEST score was superior to CHADS2 and CHA2DS2-VASc scores in both cohorts in predicting incident AF. CONCLUSIONS: We have developed and validated the C2HEST score as a simple clinical tool to assess the individual risk of developing AF in the Asian population without SHD.

The prognostic values of beta-2 microglobulin for risks of cardiovascular events and mortality in the elderly patients with isolated systolic hypertension.

BACKGROUND: The present study aimed to investigate the effects of serum beta-2 microglobulin (B2M) on the risks of major cardiovascular events (MACEs) and all-cause death in Chinese elderly isolated systolic hypertension (ISH) patients without severe renal insufficiency (estimated glomerular filtration rate [eGFR] <30 ml/min/1.73 m2). MATERIALS AND METHODS: Serum B2M concentration, creatinine-eGFR, and blood pressure variability were evaluated in 460 elderly patients (mean age, 82.6 years; 28 women) with ISH in this observational study. The Cox proportional hazard model was adopted to calculate adjusted hazard ratios (HRs) of risk factors for cardiovascular events and all-cause deaths. RESULTS: During a median follow-up period of 37.6 months, 63 patients (13.7%) died, and 65 patients (14.1%) had MACEs. Multivariable analysis showed that the higher serum B2M concentration (B2M ≥0.28 mg/dl) was an independent predictor of increased risk of MACEs (nonfatal acute myocardial infarction, acute heart failure, ischemic stroke, and cardiovascular deaths) and all-cause death (HR: 2.62, 95% confidence interval [CI]: 1.46-4.69, P = 0.001 and HR: 3.40, 95% CI: 1.78-6.48, P < 0.001, respectively) adjusting for other multiple confounders including creatinine-eGFR and cystatin C. In addition, blood pressure variability derived from ambulatory blood pressure measurement was not associated with incidence of MACEs and all-cause mortality (P > 0.05). CONCLUSION: Our data suggest that serum B2M concentration may be individually associated with MACEs and all-cause death in elderly ISH patients without severe renal insufficiency even after adjusted for creatinine-eGFR and cystatin C.

[Heavy Metal Content of Rural Living Solid Waste and Related Source and Distribution Analysis].

Living solid waste of 72 typical villages and towns in 12 provinces was investigated, and related heavy metal pollution characteristics, source, and distribution were analyzed. Results showed that heavy metal content of As, Hg, Pb, Cd, Cr, Cu, Zn, and Ni in living solid waste of typical northern villages of China was (7.51±8.89), (0.64±0.42), (21.91±12.29), (4.82±8.37), (86.36±59.99), (36.43±15.98), (62.19±36.61), and (46.07±25.22) mg·kg-1, respectively. Content of As, Hg, Pb, Cd, Cr, Cu, Zn, and Ni in living solid waste of typical southern towns was (7.43±8.82), (0.83±0.74), (21.62±13.76), (1.84±4.55), (131.06±74.96), (37.20±16.80), (98.04±63.71), and (46.75±25.75) mg·kg-1, respectively. Cd and Hg exceeded the standards for urban garbage agricultural control and soil environmental quality. Sources of heavy metals in domestic waste were explored by Pearson correlation analysis, cluster analysis, and principal component analysis. Results showed that Pb and Cd were mainly derived from kitchen waste, dust, paper, rubber, and plastic. Hg was mainly from kitchen waste and dust. Zn and Cr were mainly from dust. Cu was mainly from dust, paper, rubber, plastic, battery, and electronic waste. Ni was mainly from battery and electronic wastes. As was mainly derived from pesticides and fertilizers.

Investigation of interaction modes involved in alkaline phosphatase and organophosphorus pesticides via molecular simulations.

Organophosphorus pesticides (OPPs) are widely used in agricultural production but cause serious pollution. Alkaline phosphatase (ALP) has been implemented to enhance the degradation of OPPs. Deciphering the structural and energetic determinants of OPPs-ALP interaction harbors the potential to understand key biodegradation processes of pesticides at the molecular level. With this aim, the binding modes of OPPs and ALP were studied using computational methods as molecular docking.The CASTp server was used to predict the active site residues. The Discovery Studio Visualizer was used for docking analysis. The results show that OPPs have high binding affinities to ALP with the free energy in the range of-7.68 to-4.06 Kcal mol-1. OPPs and ALP mainly form hydrogen bonds, and amino acid residues, Gln375, Asp55, and Thr413 play important roles in the catalysis process. The experimental data of the OPPs instability in the ALP system is consistent with the binding energy.