Hydrochemical characteristics and water quality evaluation for irrigation and drinking purposes of Bangong Co Lake Watershed (preprint)

In order to explore the hydrochemical characteristics, influencing factors, and water quality of various water bodies in Bangong Co Lake Watershed, 60 water samples were collected from lake, river, groundwater, glacier water bodies in the watershed. Piper diagram, Gibbs’ diagrams, ion ratio analysis, statistical methods, and principal component analysis were used to study the hydrochemical characteristics and its influencing factors. Drinking water quality index (DWQI) and USSL classification were applied to assess the groundwater quality suitability for agricultural and drinking purposes. The hydrochemical characteristics show the differences among water bodies and their spatial distribution. Analyzed groundwater and surface water samples such as river water and glaciers mainly presented Ca-HCO3 type, and lake water mainly presented Na-Cl type and a small number of Na-HCO3·Cl type. The lake water chemical components are mainly affected by evaporative karst decomposition. The main mineralization process of groundwater and river water was related to the dissolution of reservoir minerals such as dolomite and calcite, and halite. The DWQI indicates that 79% of the groundwater samples in the study area showed a good quality for drinking. For irrigation water quality, the electrical conductivity (EC), calculated Sodium adsorption ratio (SAR), Magnesium hazardous ratio (MHR) showed that more than 13% of the total samples were not suitable for irrigation. USSL classification indicated that glacier and river water are relatively suitable for irrigation. And part of the groundwater and lake water has very high alkalinity or salinity which is alarming when considered for irrigation.

Uncovering the Effects of Ammonium Sulfate on Neomycin B Biosynthesis in Streptomyces fradiae SF-2

The aminoglycoside antibiotic neomycin has broad antibacterial properties and is widely used in medicine and agriculture. With the discovery of neomycin's potential applications in treating tumors and SARS-CoV-2, it is necessary to accelerate the biosynthesis of neomycin. In the present study, we investigated the effects of various inorganic salts on neomycin B (the main active neomycin) biosynthesis in Streptomyces fradiae SF-2. We found that 60 mM (NH4)2SO4 could promote neomycin B biosynthesis and cell growth most effectively. Further comparative transcriptomic analyses revealed that 60 mM (NH4)2SO4 inhibited the EMP and TCA cycles and enhanced the expression of neo genes involved in the neomycin B biosynthesis pathway. Finally, a neomycin B potency of 17,399 U/mL in shaking flasks was achieved by overexpressing neoE and adding 60 mM (NH4)2SO4, corresponding to a 51.2% increase compared with the control S. fradiae SF-2. In the present study, the mechanism by which (NH4)2SO4 affects neomycin biosynthesis was revealed through transcriptomics, providing a reference for the further metabolic engineering of S. fradiae SF-2 for neomycin B production.

Temporal variation of gaseous elemental mercury in a northern coastal city in China: Monsoon and COVID-19 lockdown effects

Continuous measurements of gaseous elemental mercury (GEM) were conducted in Qingdao from March 2020 to March 2021. The average concentration of GEM was (2.39 ± 1.07 ng/m3) with a variation range of 0.27–10.78 ng/m3. GEM exhibited a clear pattern of daily variation, with daily peaks occurring between 11:00–13:00. GEM concentrations were higher in winter (2.80 ± 1.28 ng/m3) than that in summer (2.18 ± 1.05 ng/m3). The high winter concentrations were related to coal-fired heating and the increased frequency of polluted weather in northern China. Principal component analysis showed that the main factors affecting GEM concentration were fossil fuel combustion, natural source release and atmospheric diffusion conditions. The anthropogenic emission sources were the main source of GEM in spring and winter, and natural sources of GEM was large in summer. The potential source contribution function suggested that North and Central China were the main potential sources of GEM, and there were large differences in the potential sources of GEM in different seasons. Comparing the GEM in the same time periods in 2018, 2020, and 2021, government policies, temporary lockdown measures for the COVID-19 epidemic, and urban village renovation led to a decreasing trend of GEM concentrations. This study contributes to a better understanding of the effects of long-range transport of air masses and anthropogenic emissions on atmospheric mercury in eastern coastal cities and offshore areas.

EANet: Iterative Edge Attention Network for Medical Image Segmentation

Accurate and automatic segmentation of medical images can greatly assist the clinical diagnosis and analysis. However, it remains a challenging task due to (1) the diversity of scale in the medical image targets and (2) the complex context environments of medical images, including ambiguity of structural boundaries, complexity of shapes, and the heterogeneity of textures. To comprehensively tackle these challenges, we propose a novel and effective iterative edge attention network (EANet) for medical image segmentation with steps as follows. First, we propose a dynamic scale-aware context (DSC) module, which dynamically adjusts the receptive fields to extract multi-scale contextual information efficiently. Second, an edge-attention preservation (EAP) module is employed to effectively remove noise and help the edge stream focus on processing only the boundary-related information. Finally, a multi-level pairwise regression (MPR) module is designed to combine the complementary edge and region information for refining the ambiguous structure. This iterative optimization helps to learn better representations and more accurate saliency maps. Extensive experimental results demonstrate that the proposed network achieves superior segmentation performance to state-of-the-art methods in four different challenging medical segmentation tasks, including lung nodule segmentation, COVID-19 infection segmentation, lung segmentation, and thyroid nodule segmentation. The source code of our method is available at https://github.com/DLWK/EANet

CGRNet: Contour-guided graph reasoning network for ambiguous biomedical image segmentation

In this work, we propose to address the existing problem of biomedical image segmentation that often produces results, which fail to capture the exact contours of the target and suffer from ambiguity. Most previous techniques are suboptimal because they often simply concatenate contour information to alleviate this problem, while ignoring the correlation between regions and contours. As a matter of fact, the relationship between cross-domain features is an important clue for ambiguous pixel segmentation in biomedical images. To this end, we contribute a simple yet effective framework called Contour-Guided Graph Reasoning Network (CGRNet) for more accurate segmentation against ambiguity, which is capable of capturing the semantic relations between object regions and contours through graph reasoning. Specifically, we first perform a global graph representation of the low-level and high-level features extracted by the feature extractor, where clusters of pixels with similar features are mapped to each vertex. Further, we explicitly combine contour information as the geometric prior, which can aggregate features of contour pixels to graph vertices and focus on features along the boundaries. Then, the cross-domain features propagate information through the vertices on the graph to efficiently learn and reason about the semantic relations. Finally, the learned refinement graph features are projected back to the original pixel coordinate space for the final pixel-wise segmentation task. Extensive experiments on the three publicly available Kvasir, CVC-612, and COVID19-100 datasets show the effectiveness of our CGRNet with superior performance to existing state-of-the-art methods. Our code is publicly available at: https://github.com/DLWK/CGRNet.

3,4-Dihydroxyphenylethanol ameliorates lipopolysaccharide-induced septic cardiac injury in a murine model

3,4-Dihydroxyphenylethanol (DOPET) is a polyphenol found in olive oil. The present study evaluated the protective role of DOPET on LPS provoked septic cardiac injury in a murine model. Four groups were used in the study (n = 3): control, LPS, DOPET alone, and DOPET + LPS. LPS (15 mg/kg;i.p.);they were used to induce cardiac sepsis. The cardiac markers like LDH, CK-MB, and troponin-T, as well as inflammatory cytokines like TNF-α and IL-6 were measured in the serum. The antioxidants and oxidative stress parameters were measured in cardiac tissues. RT-PCR and western blot methods were done to evaluate the expression of inflammatory mediators and apoptotic markers. DOPET significantly decreased the cardiac markers (LDH, CK-MB, and troponin-T) and TNF-α and IL-6 level in the serum. DOPET effectively reduced the levels of MDA and NO in LPS intoxicated rats. DOPET also increased the levels of antioxidants like SOD, CAT, GPx, and GSH in LPS intoxicated rats. The mRNA levels of TNF-α, IL-6, and NF-κB were significantly downregulated by DOPET in cardiac tissues of LPS rats. The protein expression of Bcl-2 was upregulated, and Bax and caspase-3 were downregulated by DOPET. DOPET effectively attenuates LPS-induced cardiac dysfunction through its antioxidant, anti-inflammatory, and anti-apoptotic mechanisms.

Causally Associations of Blood Lipids Levels with COVID-19 Risk: Mendelian Randomization Study (preprint)

BackgroundCoronavirus disease 2019 (COVID-19) is a global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). It has been found that coronary artery disease (CAD) is a comorbid condition for COVID-19. As the risk factors of CAD, whether blood lipids levels are causally related to increasing susceptibility and severity of COVID-19 is still unknown.ObjectiveWe aim to measure the causal effects between blood lipids and COVID-19 using two-sample Mendelian Randomization (MR) methods.MethodsWe performed two-sample MR analyses to explore whether dyslipidemia, low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c), triglyceride (TG) and total cholesterol (TC) were causally related to COVID-19 risk and severity. The GWAS summary data of blood lipids involving in 312571 individuals and dyslipidemia in a total of 53991 individuals were used as exposures, respectively. Two COVID-19 GWASs including 1221 infected patients and 1610 severe patients defined as respiratory failure were employed as outcomes. ResultsThe MR results showed that dyslipidemia was casually associated with the susceptibility of COVID-19 and induced 27% higher odds for COVID-19 infection (MR-IVW OR = 1.27, 95% CI: 1.08 to 1.49, p-value = 3·18 × 10-3). For blood lipids, the increasing level of TC will raise 18 % higher odds for the susceptibility of COVID-19 (MR-IVW OR = 1.18, 95% CI: 1.06 to 1.31, p-value = 3.08 × 10-3). Based on MR estimates, we further carried out gene-based analysis and found that ABO gene was associated with TC.Conclusions Dyslipidemia is casually associated with the susceptibility of COVID-19 and the blood TC level is a risk factor for the susceptibility of COVID-19. In addition, the different susceptibility of COVID-19 in specific blood group may be partly explained by the TC concentration in diverse ABO blood groups. 

Causally Associations of Blood Lipids Levels with COVID-19 Risk: Mendelian Randomization Study (preprint)

Background: Coronavirus disease 2019 (COVID-19) is a global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). It has been found that coronary artery disease (CAD) is a comorbid condition for COVID-19. As the risk factors of CAD, whether blood lipids levels are causally related to increasing susceptibility and severity of COVID-19 is still unknown. Design: We performed two-sample Mendelian Randomization (MR) analyses to explore whether dyslipidemia, low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c), triglyceride (TG) and total cholesterol (TC) were causally related to COVID-19 risk and severity. The GWAS summary data of blood lipids involving in 188,578 individuals and dyslipidemia in a total of 53,991 individuals were used as exposures, respectively. Two COVID-19 GWASs including 1,221 infected patients and 1,610 severe patients defined as respiratory failure were employed as outcomes. Based on the MR estimates, we further carried out gene-based and gene-set analysis to explain the potential mechanism for causal effect. Results: The MR results showed that dyslipidemia was casually associated with the susceptibility of COVID-19 and induced 27% higher odds for COVID-19 infection (MR-IVW OR = 1.27, 95% CI: 1.08 to 1.49, p-value = 3.18 x 10-3). Moreover, the increasing level of blood TC will raise 14 % higher odds for the susceptibility of COVID-19 (MR-IVW OR = 1.14, 95% CI: 1.04 to 1.25, p-value = 5.07 x 10-3). Gene-based analysis identified that ABO gene was associated with TC and the gene-set analysis found that immune processes were involved in the risk effect of TC. Conclusions: We obtained three conclusions: 1) Dyslipidemia is casually associated with the susceptibility of COVID-19; 2) TC is a risk factor for the susceptibility of COVID-19; 3) The different susceptibility of COVID-19 in specific blood group may be partly explained by the TC concentration in diverse ABO blood groups.

High Acceptance of HIV Self-testing Among PrEP Recipients before COVID-19 Era: A Cross-sectional Analysis from PrEP Demonstration Project of MSM in China (preprint)

Background: Many Pre-exposure prophylaxis (PrEP) users have difficulty attending the quarterly facility-based HIV testing, which leads to the potential risk of drug resistance in the context of breakthrough infection with low drug compliance. We explored the acceptance of HIV self-testing (HIVST) service among PrEP recipients. Methods: MSM were recruited for the PrEP demonstration in four major cities in China from December 2018 to September 2019, provided with regimens of both daily and on-demand PrEP. Facility-based HIV testing was provided quarterly at clinic visits. Previous HIV testing history and acceptance of free HIVST kits to use between each quarterly clinic visit was collected. Correlates of levels of acceptance were analysed using multivariable ordinal logistic regression. Results: We recruited 1,222 MSM. among which 48.5% preferred daily PrEP and 51.5% preferred on-demand PrEP. There was 26.8% (321/1222) had never been to any facility-based HIV testing previously, and the self-reported major reason was that they had already routinely used HIVST. A quarter of the participants (74.5%, 910/1222) had used HIVST previously. There were 1184 MSM (96.9%) accepted to use HIVST between each quarterly clinic visits during PrEP usage, composing 947 ( 77.5%) very willing to, 237（19.4%）willing to, 29 (2.4%) unwilling to, and 9 (0.7%) very unwilling to. Participants preferred daily PrEP (vs. on-demand PrEP, aOR=1.8, 95% CI:1.3-2.4) and had less than 2 times of facility-based HIV testing in the past year (vs. ³2, aOR=1.4,95% CI:1.1-1.9) were more likely to have higher level of acceptance of HIVST.Conclusions: MSM had high acceptance of HIVST, especially among those preferred daily PrEP and with less facility-based HIV testing in the previous year. Offering HIVST services PrEP recipients is feasible and necessary. Above result is of great significance for promoting HIVST among PrEP users during COVID-19, improving awareness of their HIV infection status and ensuring compliance with medication. Future study should exam the impact of HIVST on HIV testing frequency among PrEP users.Trial registration: ChiCTR1800020374 on 27th Dec 2018. http://www.chictr.org.cn/searchproj.aspx

Association between Clinical, Laboratory and CT Characteristics and RT-PCR Results in the Follow-up of COVID-19 patients (preprint)

Abstract Background: Since December 2019, more than 100,000 coronavirus disease 2019 (COVID-19) patients have been confirmed globally based on positive viral nucleic acids with real-time reverse transcriptase-polymerase chain reaction (RT-PCR). However, the association between clinical, laboratory and CT characteristics and RT-PCR results is still unclear. We sought to examine this association in detail, especially in recovered patients. Methods: We analysed data from 52 confirmed patients who had been discharged with COVID-19. The clinical, laboratory, and radiological data were dynamically recorded and compared with the admission and follow-up RT-PCR results. Results: In this cohort, 52 admitted COVID-19 patients who had confirmed positive RT-PCR results were discharged after 2 rounds of consecutively negative RT-PCR results. Compared with admission levels, CRP levels (median 4.93 mg/L [IQR: 1.78-10.20]) decreased significantly (p<0.001). and lymphocyte counts (median 1.50x109/L [IQR: 1.11-1.88]) increased obviously after obtaining negative RT-PCR results (p<0.001). Additionally, substantially improved inflammatory exudation was observed on chest CT except for 2 progressed patients. At the two-week follow-up after discharge, 7 patients had re-positive RT-PCR results, including the abovementioned 2 progressed patients. Among the 7 patients, new GGO was demonstrated in 2 patients. There were no significant differences in CPR levels or lymphocyte counts when comparing the negative and re-positive PCT results (all p >0.05). Conclusion: Heterogeneity between CT features and RT-PCR results was found in COVID-19, especially in some recovered patients with negative RT-PCR results. Our study highlights that both RT-PCR and chest CT should be considered as the key determinants for the diagnosis and management of COVID-19 patients.

Clinical characteristics and current treatment of critically ill patients with COVID-19 outside Wuhan, China: a multicenter, retrospective, observational study (preprint)

Background: A novel coronavirus disease 2019 (COVID-19) occurred in Wuhan and rapidly spread elsewhere. The clinical characteristics and treatment of critical ill patients outside Wuhan remain unknown. We aimed to describe the epidemiology and treatment of critical ill patients with COVID-19 in Hebei province.Methods: All patients were from designated hospitals of Hebei province and fit the criteria. We collected the clinical data, laboratory examinations and treatment of all participants.Results: By 14 February 2020, 37 critical ill patients were included. The mean age of the patients was 58.73 (SD 13.76) years, 21 (56.80%) patients were men, 18 (48.60%) were familial cluster, 26 (70.30%) patients had chronic illness. The patients with critical type had a longer period of confirmation time, more severe inflammation and lung injury, a lower lymphocyte percentage. All patients were treated with antiviral agents, 33 (89.20%) with antibacterial agents, 35 (95.60%) patients with methylprednisolone and traditional Chinese drugs. Nine (60.00%) patients with critical type were treated with invasive mechanical ventilation, 9 (60.00%) of those with complications. The patients with critical type received more fluid and more diuretics.Conclusion: Patients with underlying disease and the confirmation time> 10 days were more likely to develop to critical type. The critical type patients had higher risk of infection, respiratory depression, circulatory collapse, and complications. The strategy of lung-protective mechanical ventilation and restrictive fluid management should be strictly followed.

Acute Myocardial Injury of Patients with Coronavirus Disease 2019 (preprint)

Background: Since the outbreak of the Coronavirus Disease 2019 (COVID-19) in China, respiratory manifestations of the disease have been observed. However, as a fatal comorbidity, acute myocardial injury (AMI) in COVID-19 patients has not been previously investigated in detail. We investigated the clinical characteristics of COVID-19 patients with AMI and determined the risk factors for AMI in them. Methods: We analyzed data from 53 consecutive laboratory-confirmed and hospitalized COVID-19 patients (28 men, 25 women; age, 19-81 years). We collected information on epidemiological and demographic characteristics, clinical features, routine laboratory tests (including cardiac injury biomarkers), echocardiography, electrocardiography, imaging findings, management methods, and clinical outcomes. Results: Cardiac complications were found in 42 of the 53 (79.25%) patients: tachycardia (n=15), electrocardiography abnormities (n=11), diastolic dysfunction (n=20), elevated myocardial enzymes (n=30), and AMI (n=6). All the six AMI patients were aged >60 years; five of them had two or more underlying comorbidities (hypertension, diabetes, cardiovascular diseases, and chronic obstructive pulmonary disease). Novel coronavirus pneumonia (NCP) severity was higher in the AMI patients than in patients with non-definite AMI (p<0.001). All the AMI patients required care in intensive care unit; of them, three died, two remain hospitalized. Multivariate analyses showed that C-reactive protein (CRP) levels, NCP severity, and underlying comorbidities were the risk factors for cardiac abnormalities in COVID-19 patients. Conclusions: Cardiac complications are common in COVID-19 patients. Elevated CRP levels, underlying comorbidities, and NCP severity are the main risk factors for cardiac complications in COVID-19 patients.