Convolutional LSTM Networks for Subcellular Localization of Proteins

Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model on the other hand are designed to handle sequences. In this study we demonstrate that LSTM networks predict the subcellular location of proteins given only the protein sequence with high accuracy (0.902) outperforming current state of the art algorithms. We further improve the performance by introducing convolutional filters and experiment with an attention mechanism which lets the LSTM focus on specific parts of the protein. Lastly we introduce new visualizations of both the convolutional filters and the attention mechanisms and show how they can be used to extract biological relevant knowledge from the LSTM networks

Random Lasing Action from Randomly Assembled ZnS Nanosheets

Lasing characteristics of randomly assembled ZnS nanosheets are studied at room temperature. Under 266-nm optical excitation, sharp lasing peaks emitted at around 332 nm with a linewidth less than 0.4 nm are observed in all directions. In addition, the dependence of lasing threshold intensity with the excitation area is shown in good agreement with the random laser theory. Hence, it is verified that the lasing characteristics of randomly assembled ZnS nanosheets are attributed to coherent random lasing action

Combined acoustic radiation force impulse, aminotransferase to platelet ratio index and Forns index assessment for hepatic fibrosis grading in hepatitis B

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Preserving Differential Privacy in Convolutional Deep Belief Networks

The remarkable development of deep learning in medicine and healthcare domain presents obvious privacy issues, when deep neural networks are built on users' personal and highly sensitive data, e.g., clinical records, user profiles, biomedical images, etc. However, only a few scientific studies on preserving privacy in deep learning have been conducted. In this paper, we focus on developing a private convolutional deep belief network (pCDBN), which essentially is a convolutional deep belief network (CDBN) under differential privacy. Our main idea of enforcing epsilon-differential privacy is to leverage the functional mechanism to perturb the energy-based objective functions of traditional CDBNs, rather than their results. One key contribution of this work is that we propose the use of Chebyshev expansion to derive the approximate polynomial representation of objective functions. Our theoretical analysis shows that we can further derive the sensitivity and error bounds of the approximate polynomial representation. As a result, preserving differential privacy in CDBNs is feasible. We applied our model in a health social network, i.e., YesiWell data, and in a handwriting digit dataset, i.e., MNIST data, for human behavior prediction, human behavior classification, and handwriting digit recognition tasks. Theoretical analysis and rigorous experimental evaluations show that the pCDBN is highly effective. It significantly outperforms existing solutions

A Novel Splicing Mutation Alters DSPP Transcription and Leads to Dentinogenesis Imperfecta Type II

Dentinogenesis imperfecta (DGI) type II is an autosomal dominant disease characterized by a serious disorders in teeth. Mutations of dentin sialophosphoprotein (DSPP) gene were revealed to be the causation of DGI type II (DGI-II). In this study, we identified a novel mutation (NG_011595.1:g.8662T>C, c.135+2T>C) lying in the splice donor site of intron 3 of DSPP gene in a Chinese Han DGI-II pedigree. It was found in all affected subjects but not in unaffected ones or other unrelated healthy controls. The function of the mutant DSPP gene, which was predicted online and subsequently confirmed by in vitro splicing analysis, was the loss of splicing of intron 3, leading to the extended length of DSPP mRNA. For the first time, the functional non-splicing of intron was revealed in a novel DSPP mutation and was considered as the causation of DGI-II. It was also indicated that splicing was of key importance to the function of DSPP and this splice donor site might be a sensitive mutation hot spot. Our findings combined with other reports would facilitate the genetic diagnosis of DGI-II, shed light on its gene therapy and help to finally conquer human diseases

Long-term safety and outcome of a temporary self-expanding metallic stent for achalasia: a prospective study with a 13-year single-center experience

To prospectively evaluate the long-term clinical safety and efficacy of a newly designed self-expanding metallic stent (SEMS) in the treatment of patients with achalasia. Seventy-five patients with achalasia were treated with a temporary SEMS with a 30-mm diameter. The SEMSs were placed under fluoroscopic guidance and removed by gastroscopy 4–5 days after stent placement. Follow-up data focused on dysphagia score, technique and clinical success, clinical remissions and failures, and complications and was performed at 6 months, 1 year, and within 3 to 5 years, 5 to 8 years, 8 to 10 years, and >10 years postoperatively. Stent placement was technically successful in all patients. Complications included stent migration (n = 4, 5.33%), chest pain (n = 28, 38.7%), reflux (n = 15, 20%), and bleeding (n = 9, 12%). No perforation or 30-day mortality occurred. Clinical success was achieved in all patients 1 month after stent removal. The overall remission rates at 6 months, 1, 1–3, 3–5, 5–8, 8–10, and >10 year follow-up periods were 100%, 96%, 93.9%, 90.9%, 100%, 100%, and 83.3%, respectively. Stent treatment failed in six patients, and the overall remission rate in our series was 92%. The median and mean primary patencies were 2.8 ± 0.28 years (95% CI: 2.25–3.35) and 4.28 ± 0.40 years (95% CI: 3.51–5.05), respectively. The use of temporary SEMSs with 30-mm diameter proved to be a safe and effective approach for managing achalasia with a long-term satisfactory clinical remission rate

Identification of Autotoxic Compounds in Fibrous Roots of Rehmannia (Rehmannia glutinosa Libosch.)

Rehmannia is a medicinal plant in China. Autotoxicity has been reported to be one of the major problems hindering the consecutive monoculture of Rehmannia. However, potential autotoxins produced by the fibrous roots are less known. In this study, the autotoxicity of these fibrous roots was investigated. Four groups of autotoxic compounds from the aqueous extracts of the fibrous roots were isolated and characterized. The ethyl acetate extracts of these water-soluble compounds were further analyzed and separated into five fractions. Among them, the most autotoxic fraction (Fr 3) was subjected to GC/MS analysis, resulting in 32 identified compounds. Based on literature, nine compounds were selected for testing their autotoxic effects on radicle growth. Seven out of the nine compounds were phenolic, which significantly reduced radicle growth in a concentration-dependent manner. The other two were aliphatic compounds that showed a moderate inhibition effect at three concentrations. Concentration of these compounds in soil samples was determined by HPLC. Furthermore, the autotoxic compounds were also found in the top soil of the commercially cultivated Rehmannia fields. It appears that a close link exists between the autotoxic effects on the seedlings and the compounds extracted from fibrous roots of Rehmannia

In Situ Prior Proliferation of CD4+ CCR6+ Regulatory T Cells Facilitated by TGF-β Secreting DCs Is Crucial for Their Enrichment and Suppression in Tumor Immunity

BACKGROUND: CD4(+)CD25(+) regulatory T cells (Tregs), a heterogeneous population, were enrichment in tumor mass and played an important role in modulating anti-tumor immunity. Recently, we reported a Treg subset, CCR6(+) Tregs but not CCR6(-)Tregs, were enriched in tumor mass and closely related to poor prognosis of breast cancer patients. However, the underlying mechanism remains elusive. Here, we carefully evaluate the enrichment of CCR6(+)Tregs in tumor mass during progression of breast cancer and explore its possible mechanism. METHODOLOGY/PRINCIPAL FINDINGS: The frequency of CCR6(+)Tregs in tumor infiltrating lymphocytes (TILs ) was analyzed at early stage and at late stage of tumor in a murine breast cancer model by FACS respectively. The expansion of CCR6(+)Tregs and their CCR6(-) counterpart in tumor mass were determined by BrdU incorporation assay. The effect and its possible mechanism of tumor-resident antigen presenting cells (APCs) on the proliferation of CCR6(+)Tregs also were evaluated. The role of local expansion of CCR6(+)Tregs in their enrichment and suppression in vivo also was evaluated in adoptive cell transfer assay. We found that the prior enrichment of CCR6(+)Tregs but not CCR6(-)Tregs in tumor mass during progression of murine breast cancer, which was dependent on the dominant proliferation of CCR6(+) Tregs in situ. Further study demonstrated that tumor-resident DCs triggered the proliferation of CCR6(+)Treg cells in TGF-β dependent manner. Adoptive transfer of CCR6(+)Tregs was found to potently inhibit the function of CD8(+)T cells in vivo, which was dependent on their proliferation and subsequently enrichment in tumor mass. CONCLUSIONS/SIGNIFICANCE: Our finding suggested that CCR6(+) Tregs, a distinct subset of Tregs, exert its predominant suppressive role in tumor immunity through prior in situ expansion, which might ultimately provide helpful thoughts for the designing of Treg-based immunotherapy for tumor in the future