Diffusion Tensor and Kurtosis MRI-Based Radiomics Analysis of Kidney Injury in Type 2 Diabetes.

BACKGROUND: Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) can provide quantitative parameters that show promise for evaluation of diabetic kidney disease (DKD). The combination of radiomics with DTI and DKI may hold potential clinical value in detecting DKD. PURPOSE: To investigate radiomics models of DKI and DTI for predicting DKD in type 2 diabetes mellitus (T2DM) and evaluate their performance in automated renal parenchyma segmentation. STUDY TYPE: Prospective. POPULATION: One hundred and sixty-three T2DM patients (87 DKD; 63 females; 27-80 years), randomly divided into training cohort (N = 114) and validation cohort (N = 49). FIELD STRENGTH/SEQUENCE: 1.5-T, diffusion spectrum imaging (DSI) with 9 different b-values. ASSESSMENT: The images of DSI were processed to generate DKI and DTI parameter maps, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). The Swin UNETR model was trained with 5-fold cross-validation using 100 samples for renal parenchyma segmentation. Subsequently, radiomics features were automatically extracted from each parameter map. The performance of the radiomics models on the validation cohort was evaluated by utilizing the receiver operating characteristic (ROC) curve. STATISTICAL TESTS: Mann-Whitney U test, Chi-squared test, Pearson correlation coefficient, least absolute shrinkage and selection operator (LASSO), dice similarity coefficient (DSC), decision curve analysis (DCA), area under the curve (AUC), and DeLong's test. The threshold for statistical significance was set at P < 0.05. RESULTS: The DKI_MD achieved the best segmentation performance (DSC, 0.925 ± 0.011). A combined radiomics model (DTI_FA, DTI_MD, DKI_FA, DKI_MD, and DKI_RD) showed the best performance (AUC, 0.918; 95% confidence interval [CI]: 0.820-0.991). When the threshold probability was greater than 20%, the combined model provided the greatest net benefit. Among the single parameter maps, the DTI_FA exhibited superior diagnostic performance (AUC, 887; 95% CI: 0.779-0.972). DATA CONCLUSION: The radiomics signature constructed based on DKI and DTI may be used as an accurate and non-invasive tool to identify T2DM and DKD. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

A Retrospective Study on COVID-19 Infections Caused by Omicron Variant with Clinical, Epidemiological, and Viral Load Evaluations in Breakthrough Infections.

Purpose: To explore the clinical, epidemiological, and viral load characteristics of COVID-19 caused by the omicron variant. Methods: Based on the COVID-19 epidemic caused by SARS-CoV-2 Omicron BA.2 broke out in Shanghai, China. To analyze whether there is any association between clinical symptoms and viral load of COVID-19 with age, sex, and combined disease and whether the clinical symptoms and viral load are associated with vaccine-breakthrough infections. Results: The most common symptoms were cough, expectoration, and fatigue, which were more common in women than males (p < 0.001). The average viral clearance time in the > 75 years group was the longest (6.64 days). The viral load in the 60-75 years group was significantly higher than that in the other groups (p < 0.001). The 18-45 years old group had the most clinical symptoms at admission (45.39%). The days of nucleic acid-negative conversion, average viral load, highest viral load, and clinical symptoms in comorbid chronic disease patients are longer (p < 0.001). The average and highest viral loads in the unvaccinated group were longer than those in the vaccine breakthrough infection groups (p < 0.001). However, the clinical symptoms in the vaccine breakthrough infection group were significantly more severe than those in the unvaccinated group (p < 0.001). Conclusions: We found that female patients, the elderly, and those with underlying comorbidities had longer clinical positive symptoms and viral loads. Although vaccination may not reduce clinical symptoms, it can shorten the viral load and the time required for virus clearance.

COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19.

OBJECTIVES: We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging to determine the current status and indicate possible future directions. METHODS: This research provides an analysis of Web of Science Core Collection (WoSCC) indexed articles on COVID-19 and medical imaging published between 1 January 2020 and 30 June 2022, using the search terms "COVID-19" and medical imaging terms (such as "X-ray" or "CT"). Publications based solely on COVID-19 themes or medical image themes were excluded. CiteSpace was used to identify the predominant topics and generate a visual map of countries, institutions, authors, and keyword networks. RESULTS: The search included 4444 publications. The journal with the most publications was European Radiology, and the most co-cited journal was Radiology. China was the most frequently cited country in terms of co-authorship, with the Huazhong University of Science and Technology being the institution contributing with the highest number of relevant co-authorships. Research trends and leading topics included: assessment of initial COVID-19-related clinical imaging features, differential diagnosis using artificial intelligence (AI) technology and model interpretability, diagnosis systems construction, COVID-19 vaccination, complications, and predicting prognosis. CONCLUSIONS: This bibliometric analysis of COVID-19-related medical imaging helps clarify the current research situation and developmental trends. Subsequent trends in COVID-19 imaging are likely to shift from lung structure to function, from lung tissue to other related organs, and from COVID-19 to the impact of COVID-19 on the diagnosis and treatment of other diseases. Key Points • We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging from 1 January 2020 to 30 June 2022. • Research trends and leading topics included assessment of initial COVID-19-related clinical imaging features, differential diagnosis using AI technology and model interpretability, diagnosis systems construction, COVID-19 vaccination, complications, and predicting prognosis. • Future trends in COVID-19-related imaging are likely to involve a shift from lung structure to function, from lung tissue to other related organs, and from COVID-19 to the impact of COVID-19 on the diagnosis and treatment of other diseases.

Contradictory Impacts of Nitrate on the Dissimilatory Arsenate-Respiring Prokaryotes-Induced Reductive Mobilization of Arsenic from Contaminated Sediments: Mechanism Insight from Metagenomic and Functional Analyses.

Dissimilatory arsenate-respiring prokaryotes (DARPs) are considered to be a key impetus of the reductive dissolution of solid-phase arsenic. However, little is known about the interaction between nitrate and DARPs so far. In this study, we showed that nitrate either inhibited or promoted the DARP population-catalyzed reductive mobilization of As in sediments. Metagenomic analysis of the microbial communities in the microcosms after seven days of As release assays suggested that microbes mainly consisted of: Type-I DARPs having potential to reduce NO3- into NO2- and Type-II DARPs having potential to reduce NO3- to NH4+. We further isolated two cultivable DARPs, Neobacillus sp. A01 and Paenibacillus sp. A02, which represent Type-I and -II DARPs, respectively. We observed that nitrate suppressed A01-mediated release of As(III) but promoted A02-mediated release of As(III). Furthermore, we demonstrated that this observation was due to the fact that nitrite, the end product of incomplete denitrification by Type-I DARPs, suppressed the arrA gene expression per cell and growth of all DARPs, whereas ammonium, the end product of dissimilatory nitrate reduction to ammonium (DNRA) by Type-II DARPs, enhanced the arrA gene expression per cell and significantly promoted the growth of all DARPs. These findings suggest that the actual effects of nitrate on DARP population-catalyzed reductive mobilization of arsenic, largely depend on the ratio of Type-I to Type-II DARPs in sediments.

A radiomics based approach using adrenal gland and periadrenal fat CT images to allocate COVID-19 health care resources fairly.

BACKGROUND: The value of radiomics features from the adrenal gland and periadrenal fat CT images for predicting disease progression in patients with COVID-19 has not been studied extensively. We assess the value of radiomics features from the adrenal gland and periadrenal fat CT images in predicting COVID-19 disease exacerbation. METHODS: A total of 1,245 patients (685 moderate and 560 severe patients) were enrolled in a retrospective study. We proposed a 3D V-net to segment adrenal glands in onset CT images automatically, and periadrenal fat was obtained using inflation operation around the adrenal gland. Next, we built a clinical model (CM), three radiomics models (adrenal gland model [AM], periadrenal fat model [PM], and fusion of adrenal gland and periadrenal fat model [FM]), and radiomics nomogram (RN) after radiomics features extracted. RESULTS: The auto-segmentation framework yielded a dice value 0.79 in the training set. CM, AM, PM, FM, and RN obtained AUCs of 0.717, 0.716, 0.736, 0.760, and 0.833 in the validation set. FM and RN had better predictive efficacy than CM (P < 0.0001) in the training set. RN showed that there was no significant difference in the validation set (mean absolute error [MAE] = 0.04) and test set (MAE = 0.075) between predictive and actual results. Decision curve analysis showed that if the threshold probability was between 0.4 and 0.8 in the validation set or between 0.3 and 0.7 in the test set, it could gain more net benefits using RN than FM and CM. CONCLUSIONS: Radiomics features extracted from the adrenal gland and periadrenal fat CT images are related to disease exacerbation in patients with COVID-19.

Environmental Mn(II) enhances the activity of dissimilatory arsenate-respiring prokaryotes from arsenic-contaminated soils.

Many investigations suggest that dissimilatory arsenate-respiring prokaryotes (DARPs) play a key role in stimulating reductive mobilization of As from solid phase into groundwater, but it is not clear how environmental Mn(II) affects the DARPs-mediated reductive mobilization of arsenic. To resolve this issue, we collected soil samples from a realgar tailings-affected area. We found that there were diverse arsenate-respiratory reductase (arr) genes in the soils. The microbial communities had high arsenate-respiring activity, and were able to efficiently stimulate the reductive mobilization of As. Compared to the microcosms without Mn(II), addition of 10 mmol/L Mn(II) to the microcosms led to 23.99%-251.79% increases in the microbial mobilization of As, and led to 133.3%-239.2% increases in the abundances of arr genes. We further isolated a new cultivable DARP, Bacillus sp. F11, from the arsenic-contaminated soils. It completely reduced 1 mmol/L As(V) in 5 days under the optimal reaction conditions. We further found that it was able to efficiently catalyze the reductive mobilization and release of As from the solid phase; the addition of 2 mmol/L Mn(II) led to 98.49%-248.78% increases in the F11 cells-mediated reductive mobilization of As, and 70.6%-104.4% increases in the arr gene abundances. These data suggest that environmental Mn(II) markedly increased the DARPs-mediated reductive mobilization of As in arsenic-contaminated soils. This work provided a new insight into the close association between the biogeochemical cycles of arsenic and manganese.

A novel biofilm bioreactor derived from a consortium of acidophilic arsenite-oxidizing bacteria for the cleaning up of arsenite from acid mine drainage.

Arsenite (As(III)) was considered to be of great concern in acid mine drainage (AMD). A promising approach for cleaning up of arsenite from AMD is microbial oxidation of As(III) followed by adsorptions. However, there is virtually no research about the acidophilic bioreactor for As(III) oxidation so far. In this study, we formed a new biofilm bioreactor with a consortium of acidophilic As(III) oxidation bacteria. It is totally chemoautotrophic, with no need to add any carbon or other materials during the operations. It works well under pH 3.0-4.0, capable of oxidizing 1.0-20.0 mg/L As(III) in 3.0-4.5 h, respectively. A continuous operation of the bioreactor suggests that it is very stable and sustainable. Functional gene detection indicated that the biofilms possessed a unique diversity of As(III) oxidase genes. Taken together, this acidophilic bioreactor has great potential for industrial applications in the cleaning up of As(III) from AMD solution.

FaNet: fast assessment network for the novel coronavirus (COVID-19) pneumonia based on 3D CT imaging and clinical symptoms.

The novel coronavirus (COVID-19) pneumonia has become a serious health challenge in countries worldwide. Many radiological findings have shown that X-ray and CT imaging scans are an effective solution to assess disease severity during the early stage of COVID-19. Many artificial intelligence (AI)-assisted diagnosis works have rapidly been proposed to focus on solving this classification problem and determine whether a patient is infected with COVID-19. Most of these works have designed networks and applied a single CT image to perform classification; however, this approach ignores prior information such as the patient's clinical symptoms. Second, making a more specific diagnosis of clinical severity, such as slight or severe, is worthy of attention and is conducive to determining better follow-up treatments. In this paper, we propose a deep learning (DL) based dual-tasks network, named FaNet, that can perform rapid both diagnosis and severity assessments for COVID-19 based on the combination of 3D CT imaging and clinical symptoms. Generally, 3D CT image sequences provide more spatial information than do single CT images. In addition, the clinical symptoms can be considered as prior information to improve the assessment accuracy; these symptoms are typically quickly and easily accessible to radiologists. Therefore, we designed a network that considers both CT image information and existing clinical symptom information and conducted experiments on 416 patient data, including 207 normal chest CT cases and 209 COVID-19 confirmed ones. The experimental results demonstrate the effectiveness of the additional symptom prior information as well as the network architecture designing. The proposed FaNet achieved an accuracy of 98.28% on diagnosis assessment and 94.83% on severity assessment for test datasets. In the future, we will collect more covid-CT patient data and seek further improvement.

Clinical features and outcomes of seven patients with COVID-19 in a family cluster.

BACKGROUND: The family cluster is one of most important modes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission throughout China, and more details are needed about how family clusters cause the spread of coronavirus disease 2019 (COVID-19). CASE PRESENTATION: We retrospectively reviewed 7 confirmed cases from one family cluster. Both clinical features and laboratory examination results were described. Patient 1 had been in close contact with someone who was later confirmed to have COVID-19 in Wuhan City before he returned back to his hometown. He had dinner with 6 other members in his family. All the persons developed COVID-19 successively except for one older woman who neither had dinner with them nor shared a sleeping room with her husband. Six patients had mild or moderate COVID-19 but one older man with underlying diseases progressed into the severe type. After general and symptomatic treatments, all the patients recovered. CONCLUSIONS: In a family cluster, having dinner together may be an important mode for the transmission of SARS-CoV-2. In this setting, most cases are mild with a favorable prognosis, while elderly patients with underlying diseases may progress into the severe type. For someone who has close contact with a confirmed case, 14-day isolation is necessary to contain virus transmission.

Microbial reactions and environmental factors affecting the dissolution and release of arsenic in the severely contaminated soils under anaerobic or aerobic conditions.

The soils near the abandoned Shimen Realgar Mine are characterized by containing extremely high contents of total and soluble arsenic. To determine the microbial reactions and environmental factors affecting the mobilization and release of arsenic from soils phase into pore water, we collected 24 soil samples from the representative points around the abandoned Shimen Realgar Mine. They contained 8310.84 mg/kg total arsenic and 703.21 mg/kg soluble arsenic in average. The soluble arsenic in the soils shows significant positive and negative correlations with environmental SO42-/TOC/pH/PO43-, and Fe/Mn, respectively. We found that diverse dissimilatory As(V)-respiring prokaryotes (DARPs) and As(III)-oxidizing bacteria (AOB) exist in all the examined soil samples. The activities of DARPs led to 65-1275% increase of soluble As(III) in the examined soils after 21.0 days of anaerobic incubation, and the microbial dissolution and releases of arsenic show significant positive and negative correlations with the environmental pH/TN and NH4+/PO43-, respectively. In comparison, the activities of AOB led to 24-346% inhibition of the dissolved oxygen-mediated dissolution of arsenic in the soils, and the AOB-mediated releases of As(V) show significant positive and negative correlations with the environmental SO42- and pH/NH4+, respectively. The microbial communities of 24 samples contain 54 phyla of bacteria that show extremely high diversities. Total arsenic, TOC, NO3- and pH are the key environmental factors that indirectly controlled the mobilization and release of arsenic via influencing the structures of the microbial communities in the soils. This work gained new insights into the mechanism for how microbial communities catalyze the dissolution and releases of arsenic from the soils with extremely high contents of arsenic.

Unique diversity and functions of the arsenic-methylating microorganisms from the tailings of Shimen Realgar Mine.

Microbial arsenic (As) methylation plays important roles in the As biogeochemical cycle. However, little is known about the diversity and functions of As-methylating microorganisms from the tailings of a Realgar Mine, which is characterized as containing extremely high concentrations of As. To address this issue, we collected five samples (T1-T5) from the tailings of Shimen Realgar Mine. Microcosm assays without addition of exogenous As and carbon indicated that all the five samples possess significant As-methylating activities, producing 0.8-5.7 µg/L DMAsV, and 1.1-10.7 µg/L MMAsV with an exception of T3, from which MMAsV was not detectable after 14.0 days of incubation. In comparison, addition of 20.0 mM lactate to the microcosms significantly enhanced the activities of these samples; the produced DMAsV and MMAsV are 8.0-39.7 µg/L and 5.8-38.3 µg/L, respectively. The biogenic DMAsV shows significant positive correlations with the Fe concentrations and negative correlations with the total nitrogen concentrations in the environment. A total of 63 different arsM genes were identified from the five samples, which code for new or new-type ArsM proteins, suggesting that a unique diversity of As-methylating microbes are present in the environment. The microbial community structures of the samples were significantly shaped by the environmental total organic carbon, total As contents and NO3- contents. These data help to better understand the microorganisms-catalyzed As methylation occurred in the environment with extremely high contents of As.

A Study of the Correlation of Perfusion Parameters in High-Resolution GRASP MRI With Microvascular Density in Lung Cancer.

BACKGROUND: The histological count of microvascular density (MVD) is the current clinical standard for assessing tumor angiogenesis. Although it is hypothesized that perfusion MRI can be a noninvasive alternative to MVD, there have been few studies to validate their correlations, particularly in lung cancer. PURPOSE: To investigate the correlation between MVD and perfusion parameters obtained from high-resolution GRASP (Golden-angle RAdial Sparse Parallel) dynamic contrast-enhanced (DCE)-MRI in a cohort of lung cancer patients, and to validate that GRASP MRI can serve as a free-breathing, noninvasive imaging approach for studying tumor angiogenesis. STUDY TYPE: Prospective. POPULATION: Twenty-five lung cancer patients (16 male, 9 female, mean age = 57.3 ± 11.7 years). FIELD STRENGTH/SEQUENCE: 3T MRI; a prototype golden-angle stack-of-stars sequence. ASSESSMENT: Contrast-enhanced MR data were acquired during free breathing and were reconstructed using GRASP with a temporal resolution of ∼3 sec/phase. For all data, perfusion analysis was performed using a standard Tofts model to generate the volume transfer coefficient (Ktrans ) and the interstitial volume (Ve ). The MVD of corresponding tumor specimens, obtained from Computed Tomography-guided biopsies, were counted with CD34 staining. STATISTICAL TESTS: Pearson correlation analysis; one-way analysis of variance analysis; least significant difference-t method of multiple comparisons. RESULTS: The correlation coefficient was 0.983 and 0.972 for the measurement and remeasurement of Ktrans and Ve . The mean values of Ktrans , Ve , and MVD were 0.33 ± 0.22 min-1 , 0.25 ± 0.12, and 49.68 ± 27.08 vessels/0.723 mm2 , respectively, in all patients (n = 25); 0.36 ± 0.26 min-1 , 0.27 ± 0.13, and 49.09 ± 29.84 vessels/0.723 mm2 , respectively, in adenocarcinoma (n = 15); 0.34 ± 0.17 min-1 , 0.26 ± 0.12, and 53.85 ± 23.53 vessels/0.723 mm2 , respectively, in squamous cell carcinoma (n = 8); and 0.13 ± 0.15 min-1 , 0.14 ± 0.06, and 37.20 ± 28.28 vessels/0.723 mm2 , respectively, in small-cell carcinoma (n = 2). There was a positive relationship between the Ktrans and MVD in all patients (r = 0.738, P < 0.001). DATA CONCLUSION: High spatiotemporal resolution DCE-MRI using GRASP is a promising noninvasive alternative to the histological count of MVD for assessing tumor angiogenesis in lung cancer. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1186-1194.

Pseudaminobacter arsenicus sp. nov., an arsenic-resistant bacterium isolated from arsenic-rich aquifers.

An arsenic-resistant strain, CB3T, was isolated from arsenic-rich aquifers at the Jianghan Plain in Hubei, China. Phylogenetic and biochemical analysis suggested that it should represent a new species of the genus Pseudaminobacter in the family Phyllobacteriaceae. The 16S rRNA gene of CB3T shared the highest sequence similarities to those of the type strains Pseudaminobacter defluvii THI 051T (97.8 % identity) and Pseudaminobacter salicylatoxidans BN12T (97.4 %). The DNA-DNA relatedness values of CB3T with respect to strains belonging to the genus Pseudaminobacter were less than 70 %. The fatty acid profile of CB3T consisted of C16 : 0, cyclo-C19 : 0ω8c and summed feature 8 (C18 : 1ω7c and/or C18 : 1ω6c) as major components. The major polar lipids were phosphatidylcholine, phosphatidylglycerol, phosphatidyldimethylethanolamine, phosphatidylmonomethylethanolamine, phosphatidylethanolamine and diphosphatidylglycerol. The DNA G+C content was 61.4 mol%. On the basis of phenotypic, chemotaxonomic and phylogenetic data, strain CB3T was distinct from previously described Pseudaminobacter species. Therefore, we propose that strain CB3T represents a novel species of the genus Pseudaminobacter, Pseudaminobacterarsenicus sp. nov., strain CB3T (=CCTCC AB2016116T=KCTC 52625T) is designated as the type strain.

Inhibitory effect of nitrate/nitrite on the microbial reductive dissolution of arsenic and iron from soils into pore water.

It was well established that microbial communities are the major drive for the formation of arsenic-contaminated groundwater. However, it remains to be elucidated for how nitrate/nitrite affects the microorganisms-catalyzed dissolution and reduction of arsenic. To address this issue, we collected soil samples containing high-contents of arsenic from the Shimen Realgar Mine area. Microcosm assay indicated that addition of nitrate/nitrite significantly inhibited the dissolution, reduction and release of As and Fe caused by the biological catalysis of microbial communities in the soils, meanwhile nitrate/nitrite was reduced into N2. To further investigate the molecular mechanism of this finding, we used a representative dissimilatory arsenate-respiring strain Shewanella sp. GL90 from the soils to perform the arsenic release assay. GL90 can efficiently catalyze the reductive dissolution, and promote the release of As and Fe in soils. It is interesting to see that the addition of nitrate/nitrite to the soils led to marked decreases in the GL90-mediated dissolution of As and Fe in the soils. Moreover, we found that this finding was attributed to that nitrate/nitrite significantly inhibited the transcription of the gene of the respiratory arsenate reductase protein in GL90 cells. This work provided new insights into the mechanisms for the coupling of As, N and Fe geochemical cycles in arsenic-rich soils, and for how environmental factors affect As concentration in groundwater.

Wireless amplified NMR detector for improved visibility of image contrast in heterogeneous lesions.

To demonstrate the capability of a wireless amplified NMR detector (WAND) to improve the visibility of lesion heterogeneity without the use of exogenous contrast agents, a cylindrically symmetric WAND was constructed to sensitively detect and simultaneously amplify MR signals emitted from adjacent tissues. Based on a two-leg high-pass birdcage coil design, this WAND could be activated by a pumping field aligned along the main field (B0 ), without perturbing MR signal reception. Compared with an equivalent pair of external detectors, the WAND could achieve more than 10-fold gain for immediately adjacent regions. Even for regions with 3.4 radius distance separation from the detector's cylindrical center, the WAND was at least 1.4 times more sensitive than an equivalent pair of surface arrays or at least twice as sensitive as a single-sided external surface detector. When the WAND was inserted into a rat's rectum to observe adjacent tumors implanted beneath the mucosa, it could enhance the detection sensitivity of lesion regions, and thus enlarge the observable signal difference between heterogeneous tissues and clearly identify lesion boundaries as continuous lines in the intensity gradient profile. Hyperintense regions observable by the WAND existed due to higher levels of blood supply, which was indicated by a similar pattern of signal enhancement after contrast agent administration. By better observing the endogenous signal contrast, the endoluminal WAND could characterize lesions without the use of exogenous contrast agents, and thus reduce contrast-induced toxicity.

Effects of arsenic on the biofilm formations of arsenite-oxidizing bacteria.

Arsenite-oxidizing bacteria (AOB) play a key role in the biogeochemical cycle of arsenic in the environment, and are used for the bioremediation of As contaminated groundwater; however, it is not yet known about how arsenic affects biofilm formations of AOB, and how biofilm formations affect bacterial arsenite-oxidizing activities. To address these issues, we isolated seven novel AOB strains from the arsenic-contaminated soils. They can completely oxidize 1.0 mM As(III) in 22-60 h. Their arsenite oxidase sequences show 43-99% identities to those of other known AOB. Strains Cug1, Cug2, Cug3, Cug4, and Cug6 are able to form biofilms with thickness of 15-95 µm, whereas Cug8 and Cug9 cannot form biofilms. It is interesting to see that arsenite inhibited the biofilm formations of heterotrophic AOB strains, but promoted the biofilm formations of autotrophic strains in a concentration-dependent manner. The arsenite-oxidizing rates of Cug1 and Cug4 biofilms are 31.6% and 27.6% lower than those of their suspension cultures, whereas the biofilm activities of other strains are similar to those of their suspension cultures. The biofilm formation significantly promoted the bacterial resistance to arsenic. This work is the first report on the complex correlations among environmental arsenic, bacterial biofilm formations and bacterial arsenite-oxidizing activities. The data highlight the diverse lifestyle of different AOB under arsenic stress, and provide essential knowledge for the screening of efficient AOB strains used for constructions of bioreactors.

Dissimilatory arsenate-respiring prokaryotes catalyze the dissolution, reduction and release of arsenic from paddy soils into groundwater: implication for the effect of sulfate.

The paddy soils in some areas in Jianghan Plain were severely contaminated by arsenic. However, little is known about the activity and diversity of the dissimilatory arsenate-respiring prokaryotes (DARPs) in the paddy soils, and the effects of sulfate on the microbial mobilization and release of arsenic from soils into solution. To address this issue, we collected arsenic-rich soils from the depths of 1.6 and 4.6 m in a paddy region in the Xiantao city, Hubei Province, China. Microcosm assays indicated that all of the soils have significant arsenate-respiring activities using lactate, pyruvate or acetate as the sole electron donor. Functional gene cloning and analysis suggest that there are diverse DARPs in the indigenous microbial communities of the soils. They efficiently promoted the mobilization, reduction and release of arsenic and iron from soils under anaerobic conditions. Remarkably, when sulfate was amended into the microcosms, the microorganisms-catalyzed reduction and release of arsenic and iron were significantly increased. We further found that sulfate significantly enhanced the arsenate-respiring reductase gene abundances in the soils. Taken together, a diversity of DARPs in the paddy soils significantly catalyzed the dissolution, reduction and release of arsenic and iron from insoluble phase into solution, and the presence of sulfate significantly increased the microbial reactions.

Inhibitory Effect of an Acidic Peptide on the Activity of an Antimicrobial Peptide from the Scorpion Mesobuthus martensii Karsch.

Highly acidic peptides with no disulfide bridges are widely present in the scorpion venoms; however, none of them has been functionally characterized so far. Here, we cloned the full-length cDNA of a short-chain highly acidic peptide (referred to as HAP-1) from a cDNA library made from the venom glands of the Chinese scorpion Mesobuthus martensii Karsch. HAP-1 contains 19 amino acid residues with a predicted IP value of 4.25. Acidic amino residues account for 33.3% of the total residues in the molecule of HAP-1. HAP-1 shows 76⁻98% identities to some scorpion venom peptides that have not yet been functionally characterized. Secondary structure prediction showed that HAP-1 contains a beta-sheet region (residues 9⁻17), and two coiled coil regions (residues 1⁻8 and 18⁻19) located at the N-terminal and C-terminal regions of the peptide, respectively. Antimicrobial assay showed that HAP-1 does not have any effect on the growth of the bacterium Staphylococcus aureus AB94004. However, it potently inhibits the antimicrobial activity of a 13-mer peptide from M. martensii Karsch against Staphylococcus aureus AB94004. This finding is the first characterization of the function of such highly acidic peptides from scorpions.