Protein complex detection with semi-supervised learning in protein interaction networks

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions (PPIs) play fundamental roles in nearly all biological processes. The systematic analysis of PPI networks can enable a great understanding of cellular organization, processes and function. In this paper, we investigate the problem of protein complex detection from noisy protein interaction data, i.e., finding the subsets of proteins that are closely coupled via protein interactions. However, protein complexes are likely to overlap and the interaction data are very noisy. It is a great challenge to effectively analyze the massive data for biologically meaningful protein complex detection.</p> <p>Results</p> <p>Many people try to solve the problem by using the traditional unsupervised graph clustering methods. Here, we stand from a different point of view, redefining the properties and features for protein complexes and designing a “semi-supervised” method to analyze the problem. In this paper, we utilize the neural network with the “semi-supervised” mechanism to detect the protein complexes. By retraining the neural network model recursively, we could find the optimized parameters for the model, in such a way we can successfully detect the protein complexes. The comparison results show that our algorithm could identify protein complexes that are missed by other methods. We also have shown that our method achieve better precision and recall rates for the identified protein complexes than other existing methods. In addition, the framework we proposed is easy to be extended in the future.</p> <p>Conclusions</p> <p>Using a weighted network to represent the protein interaction network is more appropriate than using a traditional unweighted network. In addition, integrating biological features and topological features to represent protein complexes is more meaningful than using dense subgraphs. Last, the “semi-supervised” learning model is a promising model to detect protein complexes with more biological and topological features available.</p

Nonlocal bright spatial solitons in defocusing Kerr media supported by PT symmetric potentials

It is studied the bright spatial solitons in nonlocal defocusing Kerr media with parity-time (PT) symmetric potentials. We find that these solitons can exist and be stable over a different range of potential parameters. The influence of the degree of nonlocality on the solitons and the transverse energy flow within the stable solitons are also examined.Comment: 4 page

Nonlocal gap solitons in parity-time symmetric optical lattices

We numerically study the nonlocal gap solitons in parity-time (PT) symmetric optical lattices built into a nonlocal self-focusing medium. We state the existence, stability, and propagation dynamics of such PT gap solitons in detail. Simulated results show that there exist stable gap soltions. The influences of the degree of nonlocality on the soliton power, the energy flow density and the stable region of the PT gap solitons are also examined.Comment: 4 page

Carrier-free nanodrugs for safe and effective cancer treatment

Clinical applications of many anti-cancer drugs are restricted due to their hydrophobic nature, requiring use of harmful organic solvents for administration, and poor selectivity and pharmacokinetics resulting in off-target toxicity and inefficient therapies. A wide variety of carrier-based nanoparticles have been developed to tackle these issues, but such strategies often fail to encapsulate drug efficiently and require significant amounts of inorganic and/or organic nanocarriers which may cause toxicity problems in the long term. Preparation of nano-formulations for the delivery of water insoluble drugs without using carriers is thus desired, requiring elegantly designed strategies for products with high quality, stability and performance. These strategies include simple self-assembly or involving chemical modifications via coupling drugs together or conjugating them with various functional molecules such as lipids, carbohydrates and photosensitizers. During nanodrugs synthesis, insertion of redox-responsive linkers and tumor targeting ligands endows them with additional characteristics like on-target delivery, and conjugation with immunotherapeutic reagents enhances immune response alongside therapeutic efficacy. This review aims to summarize the methods of making carrier-free nanodrugs from hydrophobic drug molecules, evaluating their performance, and discussing the advantages, challenges, and future development of these strategies

Structural and functional characteristics of soil microbial communities in response to different ecological risk levels of heavy metals

ObjectiveThe potential ecological risk index (RI) is the most commonly used method to assess heavy metals (HMs) contamination in soils. However, studies have focused on the response of soil microorganisms to different concentrations, whereas little is known about the responses of the microbial community structures and functions to HMs at different RI levels.MethodsHere, we conducted soil microcosms with low (L), medium (M) and high (H) RI levels, depending on the Pb and Cd concentrations, were conducted. The original soil was used as the control (CK). High-throughput sequencing, qPCR, and Biolog plate approaches were applied to investigate the microbial community structures, abundance, diversity, metabolic capacity, functional genes, and community assembly processes.ResultThe abundance and alpha diversity indices for the bacteria at different RI levels were significantly lower than those of the CK. Meanwhile, the abundance and ACE index for the fungi increased significantly with RI levels. Acidobacteria, Basidiomycota and Planctomycetes were enriched as the RI level increased. Keystone taxa and co-occurrence pattern analysis showed that rare taxa play a vital role in the stability and function of the microbial community at different RI levels. Network analysis indicates that not only did the complexity and vulnerability of microbial community decrease as risk levels increased, but that the lowest number of keystone taxa was found at the H level. However, the microbial community showed enhanced intraspecific cooperation to adapt to the HMs stress. The Biolog plate data suggested that the average well color development (AWCD) reduced significantly with RI levels in bacteria, whereas the fungal AWCD was dramatically reduced only at the H level. The functional diversity indices and gene abundance for the microorganisms at the H level were significantly lower than those the CK. In addition, microbial community assembly tended to be more stochastic with an increase in RI levels.ConclusionOur results provide new insight into the ecological impacts of HMs on the soil microbiome at different risk levels, and will aid in future risk assessments for Pb and Cd contamination

Transmissible ST3-IncHI2 Plasmids Are Predominant Carriers of Diverse Complex IS26-Class 1 Integron Arrangements in Multidrug-Resistant Salmonella

Diverse mobile genetic elements (MGEs) including plasmids, insertion sequences, and integrons play an important role in the occurrence and spread of multidrug resistance (MDR) in bacteria. It was found in previous studies that IS26 and class 1 integrons integrated on plasmids to speed the dissemination of antibiotic-resistance genes in Salmonella. It is aimed to figure out the patterns of specific genetic arrangements between IS26 and class 1 integrons located in plasmids in MDR Salmonella in this study. A total of 74 plasmid-harboring Salmonella isolates were screened for the presence of IS26 by PCR amplification, and 39 were IS26-positive. Among them, 37 isolates were resistant to at least one antibiotic. The thirty-seven antibiotic-resistant isolates were further involved in PCR detection of class 1 integrons and variable regions, and all were positive for class 1 integrons. Six IS26-class 1 integron arrangements with IS26 inserted into the upstream or downstream of class 1 integrons were characterized. Eight combinations of these IS26-class 1 integron arrangements were identified among 31 antibiotic-resistant isolates. Multidrug-resistance plasmids of the IncHI2 incompatibility group were dominant, which all belonged to ST3 by plasmid double locus sequence typing. These 21 IncHI2-positive isolates harbored six complex IS26-class 1 integron arrangement patterns. Conjugation assays and Southern blot hybridizations confirmed that conjugative multidrug-resistance IncHI2 plasmids harbored the different complex IS26-class 1 integron arrangements. The conjugation frequency of IncHI2 plasmids transferring alone was 10−5-10−6, reflecting that different complex IS26-class 1 integron arrangement patterns didn't significantly affect conjugation frequency (P &gt; 0.05). These data suggested that class 1 integrons represent the hot spot for IS26 insertion, forming diverse MDR loci. And ST3-IncHI2 was the major plasmid lineage contributing to the horizontal transfer of composite IS26-class 1 integron MDR elements in Salmonella

Knowledge-Guided Robust MRI Brain Extraction for Diverse Large-Scale Neuroimaging Studies on Humans and Non-Human Primates

Accurate and robust brain extraction is a critical step in most neuroimaging analysis pipelines. In particular, for the large-scale multi-site neuroimaging studies involving a significant number of subjects with diverse age and diagnostic groups, accurate and robust extraction of the brain automatically and consistently is highly desirable. In this paper, we introduce population-specific probability maps to guide the brain extraction of diverse subject groups, including both healthy and diseased adult human populations, both developing and aging human populations, as well as non-human primates. Specifically, the proposed method combines an atlas-based approach, for coarse skull-stripping, with a deformable-surface-based approach that is guided by local intensity information and population-specific prior information learned from a set of real brain images for more localized refinement. Comprehensive quantitative evaluations were performed on the diverse large-scale populations of ADNI dataset with over 800 subjects (55 approximately 90 years of age, multi-site, various diagnosis groups), OASIS dataset with over 400 subjects (18 approximately 96 years of age, wide age range, various diagnosis groups), and NIH pediatrics dataset with 150 subjects (5 approximately 18 years of age, multi-site, wide age range as a complementary age group to the adult dataset). The results demonstrate that our method consistently yields the best overall results across almost the entire human life span, with only a single set of parameters. To demonstrate its capability to work on non-human primates, the proposed method is further evaluated using a rhesus macaque dataset with 20 subjects. Quantitative comparisons with popularly used state-of-the-art methods, including BET, Two-pass BET, BET-B, BSE, HWA, ROBEX and AFNI, demonstrate that the proposed method performs favorably with superior performance on all testing datasets, indicating its robustness and effectiveness.published_or_final_versio

The roles of inflammasomes in cancer

Inflammation is a key characteristic of all stages of tumor development, including tumor initiation, progression, malignant transformation, invasion, and metastasis. Inflammasomes are an important component of the inflammatory response and an indispensable part of the innate immune system. Inflammasomes regulate the nature of infiltrating immune cells by signaling the secretion of different cytokines and chemokines, thus regulating the anti-tumor immunity of the body. Inflammasome expression patterns vary across different tumor types and stages, playing different roles during tumor progression. The complex diversity of the inflammasomes is determined by both internal and external factors relating to tumor establishment and progression. Therefore, elucidating the specific effects of different inflammasomes in anti-tumor immunity is critical for promoting the discovery of inflammasome-targeting drugs. This review focuses on the structure, activation pathway, and identification methods of the NLRP3, NLRC4, NLRP1 and AIM2 inflammasomes. Herein, we also explore the role of inflammasomes in different cancers and their complex regulatory mechanisms, and discuss current and future directions for targeting inflammasomes in cancer therapy. A detailed knowledge of inflammasome function and regulation may lead to novel therapies that target the activation of inflammasomes as well as the discovery of new drug targets