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1.
Environ Pollut ; 273: 116427, 2021 Jan 05.
Artigo em Inglês | MEDLINE | ID: mdl-33445128

RESUMO

To assess organochlorine compound (OC) contamination, its possible sources, and adverse health impacts on giant pandas, we collected soil, bamboo, and panda fecal samples from the habitat and research center of the Qinling panda (Ailuropoda melanoleuca qinlingensis)-the rarest recognized panda subspecies. The polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) concentrations were comparatively low which suggests that moderate sources of OC pollution currently. OC levels were lower in samples from nature reserve than in those collected from pandas held in captivity, and OC levels within the reserve increased between functional areas in the order: core, buffer and experimental. The distribution patterns, and correlation analyses, combined with congener distributions suggested PCBs and OCPs originated from similar sources, were dispersed by similar processes, being transported through atmosphere and characterized by historical residues. Backward trajectory analyses results, and detected DRINs (aldrin, dieldrin, endrin and isodrin) both suggest long-range atmospheric transport of pollution source. PCBs pose potential cancer risk, and PCB 126 was the most notable toxicant as assessed be the high carcinogenic risk index. We provide data for health risk assessment that can guide the identification of priority congeners, and recommend a long-term monitoring plan. This study proposes an approach to ecotoxicological threats whereby giant pandas may be used as sentinel species for other threatened or endangered mammals. By highlighting the risks of long-distance transmission of pollutants, the study emphasizes the importance of transboundary cooperation to safeguard biodiversity.

2.
Entropy (Basel) ; 22(7)2020 Jul 09.
Artigo em Inglês | MEDLINE | ID: mdl-33286530

RESUMO

The main challenge of classification systems is the processing of undesirable data. Filter-based feature selection is an effective solution to improve the performance of classification systems by selecting the significant features and discarding the undesirable ones. The success of this solution depends on the extracted information from data characteristics. For this reason, many research theories have been introduced to extract different feature relations. Unfortunately, traditional feature selection methods estimate the feature significance based on either individually or dependency discriminative ability. This paper introduces a new ensemble feature selection, called fuzzy feature selection based on relevancy, redundancy, and dependency (FFS-RRD). The proposed method considers both individually and dependency discriminative ability to extract all possible feature relations. To evaluate the proposed method, experimental comparisons are conducted with eight state-of-the-art and conventional feature selection methods. Based on 13 benchmark datasets, the experimental results over four well-known classifiers show the outperformance of our proposed method in terms of classification performance and stability.

3.
Artigo em Inglês | MEDLINE | ID: mdl-33305564

RESUMO

Reversing the immunosuppressive tumor microenvironment (TME) is a strategic initiative to sensitize cancer immunotherapy. Emerging evidence shows that cyclic diguanylate monophosphate (c-di-GMP or cdG) can induce the stimulator of interferon genes (STING) pathway activation of antigen-presenting cells (APCs) and upregulate expression of type I interferons (IFNs) to enhance tumor immunogenicity. In vitro anionic cdG revealed fast plasma clearance, poor membrane permeability, and inadequate cytosolic bioavailability. Therefore, we explored a comprehensive "in situ vaccination" strategy on the basis of nanomedicine to trigger robust antitumor immunity. Rhodamine B isothiocyanate (RITC) fluorescent mesoporous silica nanoparticles (MSN) synthesized and modified with poly(ethylene glycol) (PEG) and an ammonium-based cationic molecule (TA) were loaded with negatively charged cdG via electrostatic interactions to form cdG@RMSN-PEG-TA. Treatment of RAW 264.7 cells with cdG@RMSN-PEG-TA markedly stimulated the secretion of IL-6, IL-1ß, and IFN-ß along with phospho-STING (Ser365) protein expression. In vivo cdG@RMSN-PEG-TA enhanced infiltration of leukocytes, including CD11c+ dendritic cells, F4/80+ macrophages, CD4+ T cells, and CD8+ T cells within the tumor microenvironment (TME), resulting in dramatic tumor growth inhibition in 4T1 breast tumor-bearing Balb/c mice. Our findings suggest that a nanobased platform can overcome the obstacles bare cdG can face in the TME. Our approach of an in situ vaccination using a STING agonist provides an attractive immunotherapy-based strategy for treating breast cancer.

4.
Database (Oxford) ; 20202020 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-33181824

RESUMO

Accumulating evidences have shown that the deregulation of circRNA has close association with many human cancers. However, these experimental verified circRNA-cancer associations are not collected in any database. Here, we develop a manually curated database (circR2Cancer) that provides experimentally supported associations between circRNAs and cancers. The current version of the circR2Cancer contains 1439 associations between 1135 circRNAs and 82 cancers by extracting data from existing literatures and databases. In addition, circR2Cancer contains the information of cancer exacted from Disease Ontology and basic biological information of circRNAs from circBase. At the same time, circR2Cancer provides a simple and friendly interface for users to conveniently browse, search and download the data. It will be a useful and valuable resource for researchers to understanding the regulation mechanism of circRNA in cancers. DATABASE URL: http://www.biobdlab.cn:8000.

5.
J Sports Sci ; : 1-7, 2020 Oct 04.
Artigo em Inglês | MEDLINE | ID: mdl-33016229

RESUMO

Muscles serve as a critical regulator of locomotion and damping, resulting in changes of soft tissue vibration. However, whether muscle fibre compositions of different individuals will cause different extents of soft tissue vibration during gait is unclear. Therefore, this study investigated the differences in lower extremity vibration frequencies among power-trained and non-power-trained athletes during walking and running. Twelve weightlifting athletes were assigned to the power-trained group and twelve recreational runners were assigned to the non-power-trained group. Accelerometers were used to detect soft tissue compartment vibration frequencies of the rectus femoris (RF) and gastrocnemius medialis (GMS) during walking and running. Results indicated that power-trained athletes, as compared to the non-power-trained, induced significantly (p < 0.05) higher vibration frequencies in their soft tissue compartments during walking and running. This suggests that power-trained athletes, who have higher ratios of fatigable fast-twitch muscle fibres, may have induced higher soft tissue compartment vibration frequencies. As a result, there is a likelihood that power-trained athletes may recruit more fatigable fast-twitch muscle fibres during muscle tuning, causing dysfunctions during prolonged exercises.

6.
Artigo em Inglês | MEDLINE | ID: mdl-33125333

RESUMO

It has been proved that long noncoding RNA (lncRNA) plays critical roles in many human diseases. Therefore, inferring associations between lncRNAs and diseases can contribute to disease diagnosis, prognosis and treatment. To overcome the limitation of traditional experimental methods such as expensive and time-consuming, several computational methods have been proposed to predict lncRNA-disease associations by fusing different biological data. However, the prediction performance of lncRNA-disease associations identification need to be improved. In this study, we propose a computational model (named LDICDL) to identify lncRNA-disease associations based on collaborative deep learning. It uses an automatic encoder to denoise multiple lncRNA feature information and multiple disease feature information, respectively. Then, the matrix decomposition algorithm is employed to predict the potential lncRNA-disease associations. In addition, to overcome the limitation of matrix decomposition, the hybrid model is developed to predict associations between new lncRNA (or disease) and diseases (or lncRNA). The ten-fold cross validation and de novo test are applied to evaluate the performance of method. The experimental results show LDICDL outperforms than other state-of-the-art methods in prediction performance.

7.
Bioinformatics ; 2020 Oct 16.
Artigo em Inglês | MEDLINE | ID: mdl-33063094

RESUMO

MOTIVATION: Infection with strains of different subtypes and the subsequent crossover reading between the two strands of genomic RNAs by host cells' reverse transcriptase are the main causes of the vast HIV-1 sequence diversity. Such inter-subtype genomic recombinants can become circulating recombinant forms (CRFs) after widespread transmissions in a population. Complete prediction of all the subtype sources of a CRF strain is a complicated machine learning problem. It is also difficult to understand whether a strain is an emerging new subtype and if so, how to accurately identify the new components of the genetic source. RESULTS: We introduce a multi-label learning algorithm for the complete prediction of multiple sources of a CRF sequence as well as the prediction of its chronological number. The prediction is strengthened by a voting of various multi-label learning methods to avoid biased decisions. In our steps, frequency and position features of the sequences are both extracted to capture signature patterns of pure subtypes and CRFs. The method was applied to 7185 HIV-1 sequences, comprising 5530 pure subtype sequences and 1655 CRF sequences. Results have demonstrated that the method can achieve very high accuracy (reaching 99%) in the prediction of the complete set of labels of HIV-1 recombinant forms. A few wrong predictions are actually incomplete predictions, very close to the complete set of genuine labels. AVAILABILITY: https://github.com/Runbin-tang/The-source-of-HIV-CRFs-prediction. CONTACT: yuzuguo@aliyun.com;jinyan.li@uts.edu.au. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

8.
Artigo em Inglês | MEDLINE | ID: mdl-32959318

RESUMO

The present study investigated the ecotoxicity of raw mining effluent from the largest molybdenum (Mo) open-pit mine in the Qinling mountains, China, and the treated effluent with neutralization and coagulation/adsorption processes, using zebrafish (Danio rerio). The results showed the following: (1) the mining effluent is acid mine drainage (AMD) and is highly toxic to zebrafish with a 96-h median lethal concentration (LC50) of 3.80% (volume percentage) of the raw effluent; (2) sublethal concentrations of the raw effluent (1/50, 1/10, and 1/2 96-h LC50) induced oxidative stress and osmoregulatory impairment, as reflected by the alterations in activities of superoxide dismutase and catalase and contents of malondialdehyde, and inhibition of Na+, K+-ATPase activity in gills and muscle after 28 days of sub-chronic exposure when compared with the unexposed group; and (3) the treatment of the raw effluent with neutralizer (NaOH) and adsorbent activated carbon reduced the acute lethal effect of raw effluent. The used endpoints including acute lethal and biochemical parameters related to oxidative stress and osmoregulatory impairment in zebrafish are cost-effective for toxicity assessment of AMD like the studied Mo mining effluent. Mining effluent management strategies extended by these results, i.e., the restriction of discharging raw and diluted effluent to adjacent waterways and the introduction of bio-monitoring system across all mining drainages in this area, were also proposed and discussed.

9.
Artigo em Inglês | MEDLINE | ID: mdl-32989699

RESUMO

The growth performance and trace metal accumulation of pak choi (Brassica chinensis L.) were investigated to evaluate the ameliorative effect of humic acid on molybdenum (Mo) slag-spiked calcareous soil. Calcareous soil spiked with 5.0% (w/w) slag was amended with humic acid derived from leonardite from 0 to 5.0% (w/w). With increasing application rate, humic acid enhanced the antioxidative capacity of pak choi seedling, as indicated by increases in the activities of antioxidant enzymes (superoxide dismutase, catalase, and peroxidase) and a decrease in malondialdehyde content; humic acid application also increased total chlorophyll content, leaf area, seedling height, and fresh biomass of pak choi. These stimulation effects started to decrease above 2.5-5.0% application of humic acid. The contents of trace metals (Cu, Mn, Zn, As, Cd, and Pb) in the aboveground part of pak choi seedling generally decreased at low rates (0.5% and 1.0%), and then increased with higher rates (2.5% and 5.0%) of humic acid application. Health risk assessment of trace metals based on target hazard quotient (THQ) suggested that consuming pak choi grown on these soils is safe. Low rate (0.5%) of humic acid reduced the potential health risk, while high rates (2.5% and 5.0%) accumulated trace metals and increased health risk. Humic acid could be added to Mo slag-spiked calcareous soil for the yield and food safety of pak choi, but the overuse of humic acid should be avoided.

10.
Artigo em Inglês | MEDLINE | ID: mdl-32853155

RESUMO

Tracking cells over time is crucial in the fields of computer vision and biomedical science. Studying neutrophils and their migratory profile is the highly topical fields in inflammation research due to determining role of these cells during immune responses. As neutrophils generally are of various shapes and motion, it remains challenging to track and describe their behaviours from multi-dimensional microscopy datasets. In this study, we propose a robust novel multi-channel feature learning (MCFL) model inspired by deep learning to extract the complex behaviour of neutrophils moved in time lapse images. In this model, the convolutional neural networks along with cell relocation distance and orientation channels learn the robust significant spatial and temporal features of an individual neutrophil. Additionally, we also proposed a new cell tracking framework to detect and track neutrophils in the original time-laps microscopy images, entails sampling, observation, and visualisation functions. Our proposed cell tracking-based-multi channel feature learning method has remarkable performance in rectifying common cell tracking problem compared with state-of the-art methods.

11.
Artigo em Inglês | MEDLINE | ID: mdl-32614745

RESUMO

Traditional network-based computational methods have shown good results in drug analysis and prediction. However, these methods are time consuming and lack universality, and it is difficult to exploit the auxiliary information of nodes and edges. Network embedding provides a promising way for alleviating the above problems by transforming network into a low-dimensional space while preserving network structure and auxiliary information. This thus facilitates the application of machine learning algorithms for subsequent processing. Network embedding has been introduced into drug analysis and prediction in the last few years, and has shown superior performance over traditional methods. However, there is no systematic review of this issue. This article offers a comprehensive survey of the primary network embedding methods and their applications in drug analysis and prediction. The network embedding technologies applied in homogeneous network and heterogeneous network are investigated and compared, including matrix decomposition, random walk, and deep learning. Especially, the Graph neural network (GNN) methods in deep learning are highlighted. Further, the applications of network embedding in drug similarity estimation, drug-target interaction prediction, adverse drug reactions prediction, protein function and therapeutic peptides prediction are discussed. Several future potential research directions are also discussed.

12.
Sci Total Environ ; 745: 140941, 2020 Nov 25.
Artigo em Inglês | MEDLINE | ID: mdl-32731070

RESUMO

Heavy metals (HM) are ubiquitous in environments, and HM pollution has become a severe global crisis. Previous studies have identified HM levels in Qinling panda habitats but their levels and the associated risks in Sichuan panda habitats are still unknown. Risk-based conservation management is in urgent need and should rely upon identifying risk distributions, quantified risk-source apportionment and collaborative governance. We carried out research in Sichuan panda (Ailuropoda melanoleuca melanoleuca) habitats taking soil, bamboo, and water samples from three different areas (nature reserves, potential habitats, and surrounding regions) of five mountains. The concentrations of HM in the soil were higher than those in bamboo, but both exceeded the background or national standards to varying degrees, suggesting long-term pollution and multi-element contamination. Regional and geographical distribution differences revealed a positive correlation between intensity of human activities and HM pollution. HM contaminants observed in the Sichuan panda habitats, based on their sources, were categorized into coal combustion (34%), industry (44%), and traffic (22%). In particular, our results showed the northern and southern parts of habitat were of highest concern, as they had environmental conditions that could be harmful to the health of giant pandas. Coupling models applying positive matrix factorization model/risk were used to quantify source contributions to various risk types, which was based on real-time monitoring and served as a positive role in multi-step process for developing countermeasures, with the goal of collaboratively reframing the vision and governance of panda conservation in order to incorporate regional disparities.


Assuntos
Metais Pesados/análise , Ursidae , Animais , China , Ecossistema , Poluição Ambiental , Humanos , Solo
13.
Anticancer Res ; 40(8): 4513-4522, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32727781

RESUMO

BACKGROUND/AIM: Hepatocellular carcinoma (HCC) arises from hepatocytes, and is the most frequently occurring malignancy of primary liver cancer. In this study, we investigated the anti-metastatic effects of the quaternary ammonium compound, cetyltrimethylammonium bromide (CTAB), on HA22T/VGH HCC cells. MATERIALS AND METHODS: According to our preliminary data, the effect of CTAB on cell cycle distribution, migration, invasion and the associated protein levels was examined using flow cytometry, wound-healing migration, Matrigel transwell invasion assay and western blotting under sub-lethal concentrations. RESULTS: CTAB treatment of HA22T/VGH cells casued dose-dependent mesenchymal-epithelial transition (MET)-like changes and impaired migration and invasion capabilities. In addition, CTAB reduced the levels of metastasis-related proteins including c-Met, phosphoinositide 3-kinase (PI3K), Akt, mammalian target of rapamycin (mTOR), ribosomal protein S6 kinase (p70S6K), Twist, N-cadherin, and Vimentin. Moreover, pretreatment with hepatocyte growth factor (HGF) rescued CTAB-mediated effects. CONCLUSION: CTAB exhibited potent anti-EMT and anti-metastatic activities through the inhibition of migration and invasion of HA22T/VGH cells. CTAB interrupted the mesenchymal characteristics of HA22T/VGH cells, which were significantly alleviated by HGF in a dose-dependent manner. CTAB has the potential to evolve as a therapeutic agent for HCC.


Assuntos
Carcinoma Hepatocelular/metabolismo , Cetrimônio/farmacologia , Transição Epitelial-Mesenquimal/efeitos dos fármacos , Neoplasias Hepáticas/metabolismo , Transdução de Sinais/efeitos dos fármacos , Carcinoma Hepatocelular/tratamento farmacológico , Linhagem Celular Tumoral , Movimento Celular/efeitos dos fármacos , Sobrevivência Celular/efeitos dos fármacos , Relação Dose-Resposta a Droga , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Humanos , Neoplasias Hepáticas/tratamento farmacológico , Masculino , Pessoa de Meia-Idade , Fosfatidilinositol 3-Quinases/metabolismo , Proteínas Proto-Oncogênicas c-akt/metabolismo , Proteínas Proto-Oncogênicas c-met/metabolismo , Serina-Treonina Quinases TOR/metabolismo
14.
Chem Biol Drug Des ; 96(5): 1262-1271, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32491252

RESUMO

Bacterial RNA polymerase (RNAP) is a validated drug target for broad-spectrum antibiotics, and its "switch region" is considered as the promising binding site for novel antibiotics. Based on the core scaffold of dithiolopyrrolone, a series of N-aryl pyrrothine derivatives was designed, synthesized, and evaluated for their antibacterial activity. Compounds generally displayed more active against Gram-positive bacteria, but less against Gram-negative bacteria. Among them, compound 6e exhibited moderate antibacterial activity against clinical isolates of rifampin-resistant Staphylococcus aureus with minimum inhibition concentration value of 1-2 µg/ml and inhibited Escherichia coli RNAP with IC50 value of 12.0 ± 0.9 µM. In addition, compound 6e showed certain degree of cytotoxicity against HepG2 and LO2 cells. Furthermore, molecular docking studies suggested that compound 6e might interact with the switch region of bacterial RNAP in a similar conformation to myxopyronin A. Together, the N-aryl pyrrothine scaffold is a promising lead for discovery of antibacterial drugs acting against bacterial RNAP.

15.
Brief Bioinform ; 2020 Apr 29.
Artigo em Inglês | MEDLINE | ID: mdl-32349125

RESUMO

Traditional machine learning methods used to detect the side effects of drugs pose significant challenges as feature engineering processes are labor-intensive, expert-dependent, time-consuming and cost-ineffective. Moreover, these methods only focus on detecting the association between drugs and their side effects or classifying drug-drug interaction. Motivated by technological advancements and the availability of big data, we provide a review on the detection and classification of side effects using deep learning approaches. It is shown that the effective integration of heterogeneous, multidimensional drug data sources, together with the innovative deployment of deep learning approaches, helps reduce or prevent the occurrence of adverse drug reactions (ADRs). Deep learning approaches can also be exploited to find replacements for drugs which have side effects or help to diversify the utilization of drugs through drug repurposing.

16.
Biomaterials ; 246: 119997, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32247937

RESUMO

Transcription factor complex NF-κB (p65/p50) is localized to the cytoplasm by its inhibitor IκBα. Upon activation, the Rel proteins p65/p50 are released from IκBα and transported through nuclear pore to affect many gene expressions. While inhibitions of up or down stream signal pathways are often ineffective due to crosstalks and compensations, direct blocking of the Rel proteins p65/p50 has long been proposed as a potential target for cancer therapy. In this work, a nanoparticle/antibody complex targeting NF-κB is employed to catch the Rel protein p65 in perinuclear region and thus blocking the translocation near the nuclear pore gate. TAT peptide conjugated on mesoporous silica nanoparticles (MSN) help non-endocytosis cell-membrane transducing and converge toward perinuclear region, where the p65 specific antibody performed the targeting and catching against active NF-κB p65 effectively. The size of the p65 bound nanoparticle becomes too big to enter nucleus. Simultaneous treatment of mice with the hybrid MSN and doxorubicin conferred a significant therapeutic effect against 4T1 tumor-bearing mice. The new approach of anti-body therapy targeting on transcription factor with "nucleus focusing" and "size exclusion blocking" effects of the antibody-conjugated nanoparticle is general and may be applicable to modulating other transcription factors.

17.
Sci Total Environ ; 722: 137861, 2020 Jun 20.
Artigo em Inglês | MEDLINE | ID: mdl-32199378

RESUMO

To determine the water quality status of the primary tributaries in middle and lower reaches of the Yellow River Basin, water collected from the confluence of the ten tributaries and some physical, chemical and biological parameters were analyzed, and then water quality index and health risk were evaluated. Of the ten main tributaries in the middle and lower reaches, only the Qingshui River had water of medium quality in the upper reaches, while all the other tributaries contributed water of poor quality. The Jindi and Dawen rivers in the lower reaches had the poorest water quality, especially the Jindi River. TP, TN, BOD5, COD, TOC and coliform bacteria exceeded the national criteria by 155%, 1%, 97.5%, 35.5%, 114.2%, and 80%, respectively. Cluster analysis indicated that industrial, agricultural, and domestic sewage, along with industrial waste gas, were the main sources of pollution in these tributaries. An analysis of the bacterial community structure showed that the Jindi River was the most polluted and had the largest species diversity and richness of bacteria. Also, its number of pathogenic microorganisms was much higher than that of other areas, and the bacterial functional genes of related metabolic pathways were significantly enriched. This was in sharp contrast with that of the Qingshui River, which had the best water quality. We suggest more specifics policy should be taken for different tributaries, and poor water quality of Jindi and Dawen River should be further studied to explore the most suitable pollution control methods.

18.
Nucleic Acids Res ; 48(7): 3949-3961, 2020 04 17.
Artigo em Inglês | MEDLINE | ID: mdl-32083663

RESUMO

DNA methyltransferases are primary enzymes for cytosine methylation at CpG sites of epigenetic gene regulation in mammals. De novo methyltransferases DNMT3A and DNMT3B create DNA methylation patterns during development, but how they differentially implement genomic DNA methylation patterns is poorly understood. Here, we report crystal structures of the catalytic domain of human DNMT3B-3L complex, noncovalently bound with and without DNA of different sequences. Human DNMT3B uses two flexible loops to enclose DNA and employs its catalytic loop to flip out the cytosine base. As opposed to DNMT3A, DNMT3B specifically recognizes DNA with CpGpG sites via residues Asn779 and Lys777 in its more stable and well-ordered target recognition domain loop to facilitate processive methylation of tandemly repeated CpG sites. We also identify a proton wire water channel for the final deprotonation step, revealing the complete working mechanism for cytosine methylation by DNMT3B and providing the structural basis for DNMT3B mutation-induced hypomethylation in immunodeficiency, centromere instability and facial anomalies syndrome.


Assuntos
Ilhas de CpG , DNA (Citosina-5-)-Metiltransferases/química , Metilação de DNA , Domínio Catalítico , Citosina/metabolismo , DNA/química , DNA/metabolismo , DNA (Citosina-5-)-Metiltransferases/metabolismo , Humanos , Modelos Moleculares , Ligação Proteica , Conformação Proteica
19.
Chemosphere ; 243: 125405, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-31995872

RESUMO

To develop the microbial resources of the Yellow River, seven water samples were collected along the Lanzhou region of the river from upstream to downstream for testing. Analysis of various physico-chemical indexes was conducted, and key parameters influencing the water quality were selected through principal component analysis, after which the decisive factors impacting water quality were determined by correlation and regression analysis. The results indicated that (1) DO, NH3-N, NO2--N, TN, TC, As, Cr6+ and Pb were the main physico-chemical factors influencing water quality in the Lanzhou region, with NH3-N having the greatest effect. (2) Ammonia-oxidizing microorganisms [ammonia-oxidizing archaea (AOA), ammonia-oxidizing bacteria (AOB), and anaerobic ammonia-oxidizing bacteria (AMX)] were found to mediate the transformation of NH3-N in the studied section. AOA was the primary microbe community among the two aerobic ammonia-oxidizing microorganisms (AOA and AOB) in the Yellow River. (3) Phylogenetic analysis showed that there were some known groups, and there were still many unknown species in the water of the studied section, especially within the AMX population. (4) Correlation analysis revealed that AOA has strong adaptability to unhealthy environments, and that some environmental factors (higher concentrations of carbon, nitrogen and some heavy metals) could increase the AOA gene abundance. Overall, these results suggested there are rich ammonia-oxidizing microbial resources, especially AOA, in the Lanzhou section of the Yellow River, which have the potential for application in nitrogen sewage treatment.


Assuntos
Amônia/metabolismo , Archaea/metabolismo , Bactérias/metabolismo , Rios/química , Amônia/análise , Archaea/classificação , Archaea/genética , Bactérias/classificação , Bactérias/genética , China , Metais Pesados/análise , Microbiota , Nitrificação , Nitrogênio/metabolismo , Oxirredução , Filogenia , Esgotos/microbiologia , Microbiologia do Solo , Purificação da Água/métodos
20.
Brief Bioinform ; 21(2): 511-526, 2020 03 23.
Artigo em Inglês | MEDLINE | ID: mdl-30759195

RESUMO

In recent times, the reduced cost of DNA sequencing has resulted in a plethora of genomic data that is being used to advance biomedical research and improve clinical procedures and healthcare delivery. These advances are revolutionizing areas in genome-wide association studies (GWASs), diagnostic testing, personalized medicine and drug discovery. This, however, comes with security and privacy challenges as the human genome is sensitive in nature and uniquely identifies an individual. In this article, we discuss the genome privacy problem and review relevant privacy attacks, classified into identity tracing, attribute disclosure and completion attacks, which have been used to breach the privacy of an individual. We then classify state-of-the-art genomic privacy-preserving solutions based on their application and computational domains (genomic aggregation, GWASs and statistical analysis, sequence comparison and genetic testing) that have been proposed to mitigate these attacks and compare them in terms of their underlining cryptographic primitives, security goals and complexities-computation and transmission overheads. Finally, we identify and discuss the open issues, research challenges and future directions in the field of genomic privacy. We believe this article will provide researchers with the current trends and insights on the importance and challenges of privacy and security issues in the area of genomics.

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