The Effects of Heavy Metal Pollution on Soil Nitrogen Transformation and Rice Volatile Organic Compounds under Different Water Management Practices.

One of the most concerning global environmental issues is the pollution of agricultural soils by heavy metals (HMs), especially cadmium, which not only affects human health through Cd-containing foods but also impacts the quality of rice. The soil's nitrification and denitrification processes, coupled with the release of volatile organic compounds by plants, raise substantial concerns. In this review, we summarize the recent literature related to the deleterious effects of Cd on both soil processes related to the N cycle and rice quality, particularly aroma, in different water management practices. Under both continuous flooding (CF) and alternate wetting and drying (AWD) conditions, cadmium has been observed to reduce both the nitrification and denitrification processes. The adverse effects are more pronounced in alternate wetting and drying (AWD) as compared to continuous flooding (CF). Similarly, the alteration in rice aroma is more significant in AWD than in CF. The precise modulation of volatile organic compounds (VOCs) by Cd remains unclear based on the available literature. Nevertheless, HM accumulation is higher in AWD conditions compared to CF, leading to a detrimental impact on volatile organic compounds (VOCs). The literature concludes that AWD practices should be avoided in Cd-contaminated fields to decrease accumulation and maintain the quality of the rice. In the future, rhizospheric engineering and plant biotechnology can be used to decrease the transport of HMs from the soil to the plant's edible parts.

Model-based exploration of the rationality of off-label use of cetirizine in Chinese pediatric patients: a prospective cohort study.

Aims: Cetirizine is frequently administered at an increased dosage in clinical practice and recommended by several guidelines. Nonetheless, the pharmacokinetic (PK) profile and real-world safety data remain insufficient in the Chinese pediatric population. The objective of the current study is to develop a population pharmacokinetic (PPK) model for cetirizine in Chinese pediatric patients and to investigate the rationale behind its off-label usage. Methods: A prospective cohort study was conducted, enrolling children who had been diagnosed with allergic diseases and prescribed cetirizine. The outcomes were safety and pharmacokinetic (PK) parameters. Cetirizine concentrations were measured using a pre-established analytical method. Subsequently, a PK model was developed, followed by model evaluation and simulation. The developed PK model was employed to investigate the drug exposure differences across various age groups and to simulate scenarios of potential overdose. Results: Sixty-three children were enrolled, and 24 of them received a cetirizine dose exceeding the recommended dosage. A PPK model, based on published literature, served as the basis of our analysis, with adjustment made to estimate certain parameters. The final model evaluation and validation indicated accurate predictive performance and robust parameter estimation. Simulations conducted for the label-dose among age 1-12 indicated median maximum concentration at steady state (Cmax,ss) of 7 year old children could be the highest. The model was also used to predict the off-label dose scenarios and overdose patient to support the clinical decision. There were no adverse drug reactions in either group. Conclusion: This study provides evidence-based and model-based exploration for optimizing cetirizine usage in Chinese pediatric patients. The cetirizine PPK model showed accurate predictive performance and could be utilized to simulate individual patient exposure in real-world clinical scenarios.

scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution.

SUMMARY: Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different approaches or criteria to define the cell subtypes for the same major cell lineages. The relationships between the cell subtypes defined in different studies should be carefully evaluated. In this updated package scCancer2, designed for integrative tumor scRNA-seq data analysis, we developed a supervised machine learning framework to annotate TME cells with annotated cell subtypes from 15 scRNA-seq datasets with 594 samples in total. Based on the trained classifiers, we quantitatively constructed the similarity maps between the cell subtypes defined in different references by testing on all the 15 datasets. Secondly, to improve the identification of malignant cells, we designed a classifier by integrating large-scale pan-cancer TCGA bulk gene expression datasets and scRNA-seq datasets (10 cancer types, 175 samples, 663 857 cells). This classifier shows robust performances when no internal confidential reference cells are available. Thirdly, scCancer2 integrated a module to process the spatial transcriptomic data and analyze the spatial features of TME. AVAILABILITY AND IMPLEMENTATION: The package and user documentation are available at http://lifeome.net/software/sccancer2/ and https://doi.org/10.5281/zenodo.10477296.

Simulating Synaptic Behaviors through Frequency Modulation in a Capacitor-Memristor Circuit.

Memristors, known for their adjustable and non-volatile resistance, offer a promising avenue for emulating synapses. However, achieving pulse frequency-dependent synaptic plasticity in memristors or memristive systems necessitates further exploration. In this study, we present a novel approach to modulate the conductance of a memristor in a capacitor-memristor circuit by finely tuning the frequency of input pulses. Our experimental results demonstrate that these phenomena align with the long-term depression (LTD) and long-term potentiation (LTP) observed in synapses, which are induced by the frequency of action potentials. Additionally, we successfully implement a Hebbian-like learning mechanism in a simple circuit that connects a pair of memristors to a capacitor, resulting in observed associative memory formation and forgetting processes. Our findings highlight the potential of capacitor-memristor circuits in faithfully replicating the frequency-dependent behavior of synapses, thereby offering a valuable contribution to the development of brain-inspired neural networks.

Pre-Configured Error Pattern Ordered Statistics Decoding for CRC-Polar Codes.

In this paper, we propose a pre-configured error pattern ordered statistics decoding (PEPOSD) algorithm and discuss its application to short cyclic redundancy check (CRC)-polar codes. Unlike the traditional OSD that changes the most reliable independent symbols, we regard the decoding process as testing the error patterns, like guessing random additive noise decoding (GRAND). Also, the pre-configurator referred from ordered reliability bits (ORB) GRAND can better control the range and testing order of EPs. An offline-online structure can accelerate the decoding process. Additionally, we also introduce two orders to optimize the search order for testing EPs. Compared with CRC-aided OSD and list decoding, PEPOSD can achieve a better trade-off between accuracy and complexity.

Biological functions of endophytic bacteria in Robinia pseudoacacia 'Hongsen'.

Introduction: Endophytes and their host plants have co-evolved for a very long time. This relationship has led to the general recognition of endophytes as a particular class of microbial resources. R. pseudoacacia 'Hongsen' is drought- and barren-resistant species that can be grown in both the north and south of China, efficiently addresses the ecological issues caused by China's 'southern eucalyptus and northern poplar. Up to date, cultured-dependent studies are available for the R. pseudoacacia nitrogen-fixing and other endophytes. Therefore, the present research studied the R. pseudoacacia 'Hongsen,' microbiome in detail by high-throughput sequencing and culture dependant. Methods: This study examined microbial species and functional diversity in Robinia pseudoacacia 'Hongsen' using culture-dependent (isolation) and culture-independent techniques. Results: A total of 210 isolates were isolated from R. pseudoacacia 'Hongsen.' These isolates were clustered into 16 groups by the In Situ PCR (IS-PCR) fingerprinting patterns. 16S rRNA gene sequence analysis of the representative strain of each group revealed that these groups belonged to 16 species of 8 genera, demonstrating the diversity of endophytes in R. pseudoacacia 'Hongsen'. 'Bacillus is the most prevalent genus among all the endophytic bacteria. High-throughput sequencing of endophytic bacteria from R. pseudoacacia 'Hongsen' of the plant and the rhizosphere soil bacteria showed that the bacterial populations of soil near the root, leaf, and rhizosphere differed significantly. The microbial abundance decreased in the endophytes as compared to the rhizosphere. We observed a similar community structure of roots and leaves. With and without root nodules, Mesorhizobium sp. was significantly different in R. pseudoacacia 'Hongsen' plant. Discussion: It was predicted that R. pseudoacacia 'Hongsen' plant endophytic bacteria would play a significant role in the metabolic process, such as carbohydrate metabolism, amino acid metabolism, membrane transport, and energy metabolism.

MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification.

In the medical research domain, limited data and high annotation costs have made efficient classification under few-shot conditions a popular research area. This paper proposes a meta-learning framework, termed MedOptNet, for few-shot medical image classification. The framework enables the use of various high-performance convex optimization models as classifiers, such as multi-class kernel support vector machines, ridge regression, and other models. End-to-end training is then implemented using dual problems and differentiation in the paper. Additionally, various regularization techniques are employed to enhance the model's generalization capabilities. Experiments on the BreakHis, ISIC2018, and Pap smear medical few-shot datasets demonstrate that the MedOptNet framework outperforms benchmark models. Moreover, the model training time is also compared to prove its effectiveness in the paper, and an ablation study is conducted to validate the effectiveness of each module.

Ensemble learning-based IDS for sensors telemetry data in IoT networks.

The Internet of Things (IoT) is a paradigm that connects a range of physical smart devices to provide ubiquitous services to individuals and automate their daily tasks. IoT devices collect data from the surrounding environment and communicate with other devices using different communication protocols such as CoAP, MQTT, DDS, etc. Study shows that these protocols are vulnerable to attack and prove a significant threat to IoT telemetry data. Within a network, IoT devices are interdependent, and the behaviour of one device depends on the data coming from another device. An intruder exploits vulnerabilities of a device's interdependent feature and can alter the telemetry data to indirectly control the behaviour of other dependent devices in a network. Therefore, securing IoT devices have become a significant concern in IoT networks. The research community often proposes intrusion Detection Systems (IDS) using different techniques. One of the most adopted techniques is machine learning (ML) based intrusion detection. This study suggests a stacking-based ensemble model makes IoT devices more intelligent for detecting unusual behaviour in IoT networks. The TON-IoT (2020) dataset is used to assess the effectiveness of the proposed model. The proposed model achieves significant improvements in accuracy and other evaluation measures in binary and multi-class classification scenarios for most of the sensors compared to traditional ML algorithms and other ensemble techniques.

Revealing the promoting effect of multiple Mn valences on the catalytic activity of CeO2 nanorods toward soot oxidation.

Mn-modified CeO2 nanomaterials have attracted extensive attention as efficient and promising catalysts for soot combustion due to their low cost and high catalytic activity. However, a detailed mechanism of how Mn promotes soot oxidation over CeO2 is still not clearly elucidated, which is crucial to further optimize the catalyst for achieving its practical applications. We here report a Mn-doped CeO2 catalyst with tunable surface Mn chemical valence states to study the Mn-promoting mechanism for improving CeO2 catalyst activity in soot oxidation. Experimental results show that Mn-doped CeO2 nanorods with surface Mn chemical valence states being optimized (Mn0.19Ce0.81O2) can lower the eliminating temperature of soot to 410 °C (T90) when in a loose contact and exhibit a strong resistance towards water molecules. The catalytic performances of Mn0.19Ce0.81O2 nanorods are comparable with those of other reported oxide catalysts both in the mimetic realistic and ideal reaction environments. Detailed characterization and theoretical calculation results demonstrate that balanced multiple Mn valences can dramatically enhance the catalysts' redox properties and their ability to activate O2 molecules, as well as improve the dynamic contact efficiency during the oxidation, which synergistically result in superior catalytic performances. This work might provide insight for the future design and preparation of catalysts to efficiently eliminate soot particles.

Building towards Automated Cyberbullying Detection: A Comparative Analysis.

The increased use of social media among digitally anonymous users, sharing their thoughts and opinions, can facilitate participation and collaboration. However, this anonymity feature which gives users freedom of speech and allows them to conduct activities without being judged by others can also encourage cyberbullying and hate speech. Predators can hide their identity and reach a wide range of audience anytime and anywhere. According to the detrimental effect of cyberbullying, there is a growing need for cyberbullying detection approaches. In this survey paper, a comparative analysis of the automated cyberbullying techniques from different perspectives is discussed including data annotation, data preprocessing, and feature engineering. In addition, the importance of emojis in expressing emotions as well as their influence on sentiment classification and text comprehension leads us to discuss the role of incorporating emojis in the process of cyberbullying detection and their influence on the detection performance. Furthermore, the different domains for using self-supervised learning (SSL) as an annotation technique for cyberbullying detection are explored.

Characterization and genome analysis of a novel Vibrio parahaemolyticus phage vB_VpP_DE17.

A novel phage vB_VpP_DE17, which infects Vibrio parahaemolyticus, was isolated from the sewer of the Huangsha aquatic market in Guangzhou. Transmission electron microscopy indicated that DE17 had an icosahedral head (47 ± 2 nm diameter) and a short, non-contractile tail (17 ± 2 nm). The genome of DE17 was a double-stranded linear DNA with a length of 43,397 bp and GC content of 49.23%. In total, 49 putative open reading frames (ORFs) were predicted and could be divided into six modules: DNA metabolism, lysis, packaging, structure, additional function, and hypothetical proteins. Taxonomic analysis revealed that the phage belonging to the genus of Maculvirus, Autographivirinae subfamily, Podoviridae family. DE17 had a short latent period of 5 min with burst size of 80 pfu/cell. Its optimum temperature and pH ranges were 4 °C-50 °C and 5-10, respectively; it was completely inactivated after 20 min of ultraviolet irradiation. No transfer RNA (tRNA), virulence associated, or antibiotic resistance genes were identified. Bacterial challenge test revealed that DE17 had a certain inhibitory effect on V. parahaemolyticus within 6 h. Characterization, genomic analysis and in vitro antibacterial assays of DE17 will further enhance our understanding of phage biology and diversity.

Medication therapy of high-dose methotrexate: An evidence-based practice guideline of the Division of Therapeutic Drug Monitoring, Chinese Pharmacological Society.

AIMS: A lot of medication risks related to high-dose methotrexate (HDMTX) therapy still remain to be identified and standardized. This study aims to establish an evidence-based practice guideline for individualized medication of HDMTX. METHODS: The practice guideline was launched by the Division of Therapeutic Drug Monitoring, Chinese Pharmacological Society. The guideline was developed following the WHO handbook for guideline development and the methodology of evidence-based medicine (EBM). The guideline was initially registered in the International Practice Guidelines Registry Platform (IPGRP-2017CN021). Systematic reviews were conducted to synthesize available evidence. A multicentre cross-sectional study was conducted using questionnaires to evaluate patients' perception and willingness concerning individualized medication of HDMTX. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was used to rate the quality of evidence and to grade the strength of recommendations. RESULTS: Multidisciplinary working groups were included in this guideline, including clinicians, pharmacists, methodologists, pharmacologists and pharmacoeconomic specialists. A total of 124 patients were involved to integrate patient values and preferences. Finally, the guideline presents 28 recommendations, regarding evaluation prior to administration (renal function, liver function, pleural effusion, comedications, genetic testing), pre-treatment and routine dosing regimen, therapeutic drug monitoring (necessity, method, timing, target concentration), leucovorin rescue (initial timing, dosage regimen and optimization), and management of toxicities. Of these, 12 are strong recommendations. CONCLUSIONS: We developed an evidence-based practice guideline with respect to HDMTX medication using a rigorous and multidisciplinary approach. This guideline provides comprehensive and practical recommendations involving the whole process of HDMTX administration to health care providers.

Diversity of endophytic bacteria in wild rice (Oryza meridionalis) and potential for promoting plant growth and degrading phthalates.

Phthalates (PAEs) accumulated in agricultural soils and rice have increased human exposure risks. Microbial degradation could efficiently reduce the residue of organic pollutants in soil and crop plants. Here, we hypothesized that endophytic bacteria from wild rice have the potential for degradation of PAEs and plant growth promoting. The endophytic bacterial community and functional diversity in wild rice (Oryza meridionalis) were analyzed for the first time, and the potential for PAE degradation and plant growth promoting by endophytes were investigated. The results of Illumina high-throughput sequencing revealed that abundant endophytes inhabited in wild rice with Proteobacteria, Bacteroidetes, Firmicutes and Actinobacteria being the dominant phyla. Endophytic bacterial diversity and complexity were confirmed by isolation and clustering of isolates. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that endophytes exerted diverse functions such as plant growth promoting, xenobiotics biodegradation, pollution remediation and bacterial chemotaxis. Pure culture experiment showed that 30 isolated endophytic strains exhibited in vitro plant growth promoting activities, and rice plants inoculated with these strains confirmed their growth promoting abilities. Some endophytic strains were capable of efficiently degrading PAEs, with the highest removal percentage of di-n-butyl phthalate (DBP) up to 96.1% by Bacillus amyloliquefaciens strain L381 within 5 days. Synthetic community F and strain L381 rapidly removed DBP from soil (removing 91.0%-99.2% within 10 d and from rice plant slurry (removing 93.4%-99.2% within 5 d). These results confirmed the hypothesis and demonstrated the diversity of endophytic bacteria in wild rice with diverse functions, especially for plant growth promoting and removing PAEs. These multifunctional endophytic bacteria provided good alternatives to reduce PAE accumulation in crops and increase yield.

Bioanalytical strategies in drug discovery and development.

A reliable, rapid, and effective bioanalytical method is essential for the determination of the pharmacokinetic, pharmacodynamic, and toxicokinetic parameters that inform the safety and efficacy profile of investigational drugs. The overall goal of bioanalytical method development is to elucidate the procedure and operating conditions under which a method can sufficiently extract, qualify, and/or quantify the analyte(s) of interest and/or their metabolites for the intended purpose. Given the difference in the physicochemical properties of small and large molecule drugs, different strategies need to be adopted for the development of an effective and efficient bioanalytical method. Herein, we provide an overview of different sample preparation strategies, analytical platforms, as well as procedures for achieving high throughput for bioanalysis of small and large molecule drugs.

Effects of Pharmacist-Led Clinical Pathway/Order Sets on Cancer Patients: A Systematic Review.

Background: Pharmacist-led clinical pathways/order sets (PLCOs) were first applied for designated diseases and surgical operations, such as cancer. They were not used in pharmacotherapy until recently. After screening a large number of publications, we found that PLCOs were rarely accessible. Objective: To evaluate the effects and the changes of relevant medical outcomes of PLCOs. Methods: Articles from PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang database, and China Biology Medicine disc (CBM) were systematically retrieved. Clinical research comparing cancer patients' clinical effects with or without clinical pathway/order sets was performed. Two reviewers performed quality assessment, and the data were abstracted independently. A narrative synthesis of the extracted data was performed due to heterogeneity. Results: Nine studies were identified, including six uncontrolled before-after studies and three case-series studies. The scopes of PLCOs of included research can be divided into two types, one focusing on chemotherapy agents and the other on the managements of chemotherapy-induced complications. The PLCOs shortened hospital length of stay, decreased initial antibiotic time intervals in patients with febrile neutropenia, reduced medication error incidence, and increased physicians' adherence rate to clinical pathway/order sets. Moreover, three articles included economic effects showing positive savings on medication costs through PLCOs. Conclusion: PLCOs can have beneficial effects on medication effectiveness, safety, and economic outcomes. Nevertheless, clinical pathway/order sets need to be further optimized and expanded to other clinical areas.

Isolation and Characterization of the Novel Phages vB_VpS_BA3 and vB_VpS_CA8 for Lysing Vibrio parahaemolyticus.

Accumulating evidence has indicated that the multiple drug resistant Vibrio parahaemolyticus may pose a serious threat to public health and economic concerns for humans globally. Here, two lytic bacteriophages, namely vB_VpS_BA3 and vB_VpS_CA8, were isolated from sewage collected in Guangzhou, China. Electron microscopy studies revealed both virions taxonomically belonged to the Siphoviridae family with icosahedral head and a long non-contractile tail. The double-stranded DNA genome of phage BA3 was composed of 58648 bp with a GC content of 46.30% while phage CA8 was 58480 bp with an average GC content of 46.42%. In total, 85 putative open reading frames (ORFs) were predicted in the phage BA3 genome while 84 were predicted in that of CA8. The ORFs were associated with phage structure, packing, host lysis, DNA metabolism, and additional functions. Furthermore, average nucleotide identity analysis, comparative genomic features and phylogenetic analysis revealed that BA3 and CA8 represented different isolates but novel members of the family, Siphoviridae. Regarding the host range of the 61 V. parahaemolyticus isolates, BA3 and CA8 had an infectivity of 8.2 and 36.1%, respectively. Furthermore, ∼100 plaque-forming units (pfu)/cell for phage BA3 and ∼180 pfu/cell for phage CA8 were determined to be the viral load under laboratory growth conditions. Accordingly, the phage-killing assay in vitro revealed that phage CA8 achieved approximately 3.65 log unit reductions. The present results indicate that CA8 is potentially applicable for biological control of multidrug resistant V. parahaemolyticus.

Severe toxic effects of low-dose methotrexate treatment for placenta accreta in a patient with methylenetetrahydrofolate reductase mutations.

WHAT IS KNOWN AND OBJECTIVE: Low-dose methotrexate (LDMTX) has been widely used for many decades in clinical settings, with good safety profiles compared with those of high-dose methotrexate. LDMTX is also used as one of the off-label conservative therapies in treating placenta accreta (PA). Until now, only a few mild adverse drug reactions (ADRs) have been published after short-term use of LDMTX, and no severe cases have been reported. CASE SUMMARY: We present a case of a 30-year-old female who developed acute severe oral ulcerative mucositis with degree IV myelosuppression and degree III hepatic injury, after three doses of LDMTX to treat placenta accrete. The symptoms gradually improved after leucovorin rescue and supportive treatments. WHAT IS NEW AND CONCLUSION: The present case provides the first severe ADR report for the short-term use of LDMTX for treating PA, indicating that potentially life-threatening complications can also occur when using LDMTX. Early recognition and immediate leucovorin rescue could result in a favourable outcome.

Mobility Aware Duty Cycling Algorithm (MADCAL) A Dynamic Communication Threshold for Mobile Sink in Wireless Sensor Network.

The hotspot issue in wireless sensor networks, with nodes nearest the sink node losing energy fastest and degrading network lifetime, is a well-referenced problem. Mobile sink nodes have been proposed as a solution to this. They do not completely remove the hotspot problem though, with nodes the sink passes most closely still expending more energy than others. This study proposes a lightweight algorithm, located in the media access control (MAC) layer of static nodes and utilising knowledge of predictable sink node mobility. This is in order to create a dynamic communication threshold between static nodes and the sink, within which static nodes awaken, lessening competition for sink communication between nodes. In utilising predictable mobility and factors already known to the static node, such as location and interference range, there is no need for energy-consuming messaging. Analysis and simulation results, tested on a lightweight implementation of a carrier-sense multiple-access-based MAC protocol, show a significant improvement in energy consumption in both controlled and random environments, with frame delivery improved to the point where sink speed is negated. This is when compared to the existing duty cycling approach.

A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks.

The Internet of Things (IoT) is an emerging technology that aims to enable the interconnection of a large number of smart devices and heterogeneous networks. Ad hoc networks play an important role in the designing of IoT-enabled platforms due to their efficient, flexible, low-cost and dynamic infrastructures. These networks utilize the available resources efficiently to maintain the Quality of Service (QoS) in a multi-hop communication. However, in a multi-hop communication, the relay nodes can be malicious, thus requiring a secured and reliable data transmission. In this paper, we propose a QoS-aware secured communication scheme for IoT-based networks (QoS-IoT). In QoS-IoT, a Sybil attack detection mechanism is used for the identification of Sybil nodes and their forged identities in multi-hop communication. After Sybil nodes detection, an optimal contention window (CW) is selected for QoS provisioning, that is, to achieve per-flow fairness and efficient utilization of the available bandwidth. In a multi-hop communication, the medium access control (MAC) layer protocols do not perform well in terms of fairness and throughput, especially when the nodes generate a large amount of data. It is because the MAC layer has no capability of providing QoS to prioritized or forwarding flows. We evaluate the performance of QoS-IoT in terms of Sybil attack detection, fairness, throughput and buffer utilization. The simulation results show that the proposed scheme outperforms the existing schemes and significantly enhances the performance of the network with a large volume of data. Moreover, the proposed scheme is resilient against Sybil attack.

Azotobacter bryophylli sp. nov., isolated from the succulent plant Bryophyllum pinnatum.

A Gram-stain-negative, aerobic, nitrogen-fixing bacterium, designated strain L461T, was isolated from leaves of Bryophyllum pinnatum growing at the South China Agricultural University. Phylogenetic analysis of the 16S rRNA gene sequence indicated it as a member of the genus Azotobacter closely related to Azotobacter beijerinckii JCM 20725T (97.82 % similarity) and Azotobacter chroococcum ATCC 9043T (97.34 %). Its major fatty acid components were C16 : 1 ω9c and C16 : 0. Its predominant isoprenoid quinone was Q-9. Its major polar lipids were phosphatidylethanolamine, phosphatidylglycerol, aminophospholipid, phospholipid and one unknown lipid. Its DNA G+C content was 64.9 mol% (Tm). DNA-DNA relatedness values between strain L461T and the reference strains of A. beijerinckii and A. chroococcum were 46.43 and 28.23 %, respectively. Biological and biochemical tests, protein patterns, genomic DNA fingerprinting, and comparison of cellular fatty acids distinguished strain L461T from the closely related Azotobacter species. Based on these data, the novel species Azotobacter bryophylli sp. nov. is proposed, with the type strain L461T (=KCTC 62195T=GDMCC 1.1250T).