Immunohistochemical Study of Intralaryngeal Ganglia in the Cat

To study the mechanism of autonomic regulation in the larynx, intralaryngeal local ganglia of the cat were investigated using immunohistochemical techniques. Small intralaryngeal ganglia were found in the peripheral portions of internal branches of the superior laryngeal nerve. Ninety-one percent of the ganglionic neurons were immunoreactive (IR) to vasoactive intestinal polypeptide (VIP), and 10% of the VIP-IR cells were also immunoreactive to enkephalin (ENK) and/or substance P (SP). The immunoreactivity of neuronal cell bodies remained unchanged even after denervation of the bilateral superior and recurrent laryngeal nerves. A dense distribution of calcitonin gene-related peptide (CGRP)-IR nerve fibers was found around almost all neuronal cells in the intralaryngeal. ganglia. A few VIP-IR, ENK-IR, and SP-IR nerve fibers were also observed. Only the CGRP-IR fibers disappeared after the denervation experiments. in the laryngeal glands and mucosal arterioles, VIP-IR nerve terminals were found that were also immunoreactive to ENK and/or SP. However, these Immunoreactive nerve endings in the glands and arterioles remained after the denervation experiments. The results of our study indicate that laryngeal exocrine secretion and blood flow are regulated by postganglionic autonomic parasympathetic fibers from intralaryngeal ganglia that contain VIP alone or VIP with ENK and/or SP, and that these ganglionic neurons may be innervated by CGRP-IR extrinsic nerve fibers.

Machine-learning prediction of the d-band center for metals and bimetals

The d-band centers for eleven metals and their pairwise bimetals for two different structures (1% metal doped- or overlayer-covered metal surfaces) are statistically predicted using machine learning methods from readily available values as descriptors for the target metals.

Privacy-preserving search for chemical compound databases

Background

Searching for similar compounds in a database is the most important process for in-silico drug screening. Since a query compound is an important starting point for the new drug, a query holder, who is afraid of the query being monitored by the database server, usually downloads all the records in the database and uses them in a closed network. However, a serious dilemma arises when the database holder also wants to output no information except for the search results, and such a dilemma prevents the use of many important data resources.

Results

In order to overcome this dilemma, we developed a novel cryptographic protocol that enables database searching while keeping both the query holder's privacy and database holder's privacy. Generally, the application of cryptographic techniques to practical problems is difficult because versatile techniques are computationally expensive while computationally inexpensive techniques can perform only trivial computation tasks. In this study, our protocol is successfully built only from an additive-homomorphic cryptosystem, which allows only addition performed on encrypted values but is computationally efficient compared with versatile techniques such as general purpose multi-party computation. In an experiment searching ChEMBL, which consists of more than 1,200,000 compounds, the proposed method was 36,900 times faster in CPU time and 12,000 times as efficient in communication size compared with general purpose multi-party computation.

Conclusion

We proposed a novel privacy-preserving protocol for searching chemical compound databases. The proposed method, easily scaling for large-scale databases, may help to accelerate drug discovery research by making full use of unused but valuable data that includes sensitive information.

Prediction of Low-Thermal-Conductivity Compounds with First-Principles Anharmonic Lattice-Dynamics Calculations and Bayesian Optimization

Compounds of low lattice thermal conductivity (LTC) are essential for seeking thermoelectric materials with high conversion efficiency. Some strategies have been used to decrease LTC. However, such trials have yielded successes only within a limited exploration space. Here, we report the virtual screening of a library containing 54,779 compounds. Our strategy is to search the library through Bayesian optimization using for the initial data the LTC obtained from first-principles anharmonic lattice-dynamics calculations for a set of 101 compounds. We discovered 221 materials with very low LTC. Two of them even have an electronic band gap <1 eV, which makes them exceptional candidates for thermoelectric applications. In addition to those newly discovered thermoelectric materials, the present strategy is believed to be powerful for many other applications in which the chemistry of materials is required to be optimized.

Metabolomics analysis of saliva from patients with primary Sjögren's syndrome

The recent development of salivary proteomics has led to the identification of potential biomarkers for diagnosing patients with primary Sjögren's syndrome (pSS). Here we sought to identify differentially produced salivary metabolites from pSS patients and healthy controls (HCs) that might be used to characterize this disease. We obtained salivary samples from 12 female pSS patients (mean age 44.2 ± 13.01) and 21 age-matched female HCs. The metabolite profiles of saliva were analysed by gas chromatography-mass spectrometry. The total metabolite levels in each of the samples were calculated and compared across the study participants. A total of 88 metabolites were detected across the study samples, 41 of which were observed at reduced levels in the samples from pSS patients. Principal component analysis (PCA) revealed a loss in salivary metabolite diversity in the pSS patient samples compared to the HC samples. The reduced presence of glycine, tyrosine, uric acid and fucose, which may reflect salivary gland destruction due to chronic sialoadenitis, contributed to the loss of diversity. Comparative PCA of the pSS patients revealed the presence of two subpopulations based on their metabolite profiles, and these two subpopulations showed a significant difference in the prevalence of major salivary glanditis (P = 0.014). In this study, we found that the salivary metabolite profile of pSS patients was less diverse than that of HCs and that the metabolite profiles in pSS patients were affected by the presence of major salivary glanditis.

Health checkup and telemedical intervention program for preventive medicine in developing countries: verification study

BACKGROUND

The prevalence of non-communicable diseases is increasing throughout the world, including developing countries.

OBJECTIVE

The intent was to conduct a study of a preventive medical service in a developing country, combining eHealth checkups and teleconsultation as well as assess stratification rules and the short-term effects of intervention.

METHODS

We developed an eHealth system that comprises a set of sensor devices in an attaché case, a data transmission system linked to a mobile network, and a data management application. We provided eHealth checkups for the populations of five villages and the employees of five factories/offices in Bangladesh. Individual health condition was automatically categorized into four grades based on international diagnostic standards: green (healthy), yellow (caution), orange (affected), and red (emergent). We provided teleconsultation for orange- and red-grade subjects and we provided teleprescription for these subjects as required.

RESULTS

The first checkup was provided to 16,741 subjects. After one year, 2361 subjects participated in the second checkup and the systolic blood pressure of these subjects was significantly decreased from an average of 121 mmHg to an average of 116 mmHg (P<.001). Based on these results, we propose a cost-effective method using a machine learning technique (random forest method) using the medical interview, subject profiles, and checkup results as predictor to avoid costly measurements of blood sugar, to ensure sustainability of the program in developing countries.

CONCLUSIONS

The results of this study demonstrate the benefits of an eHealth checkup and teleconsultation program as an effective health care system in developing countries.

Molecular Stability of Chicken and Rabbit Immunoglobulin G

Molecular stability of chicken egg yolk immunoglobulin G (IgY) and that of rabbit IgG were compared by measuring antibody activities and conformational changes. Stability of rabbit IgG to acid denaturation was much higher than that of IgY. Conformation of the IgY molecule was readily changed in acidic conditions, resulting in a rapid loss of antibody activity. Much less stable natures of IgY to heat-treatment and guanidine-HCl denaturation than rabbit IgG were also observed. Differences in the structure between the two immunoglobulins that might participate in their different stability were inferred from their amino acid sequence data. Importance of the intramolecular disulfide linkage in the rabbit light chain and some other structural differences were suggested.

Discovering combinatorial interactions in survival data

Motivation: Although several methods exist to relate high-dimensional gene expression data to various clinical phenotypes, finding combinations of features in such input remains a challenge, particularly when fitting complex statistical models such as those used for survival studies.

Results: Our proposed method builds on existing ‘regularization path-following’ techniques to produce regression models that can extract arbitrarily complex patterns of input features (such as gene combinations) from large-scale data that relate to a known clinical outcome. Through the use of the data’s structure and itemset mining techniques, we are able to avoid combinatorial complexity issues typically encountered with such methods, and our algorithm performs in similar orders of duration as single-variable versions. Applied to data from various clinical studies of cancer patient survival time, our method was able to produce a number of promising gene-interaction candidates whose tumour-related roles appear confirmed by literature.

Availability: An R implementation of the algorithm described in this article can be found at https://github.com/david-duverle/regularisation-path-following

Contact:dave.duverle@aist.go.jp

Supplementary information:Supplementary data are available at Bioinformatics online.

An in silico model for interpreting polypharmacology in drug-target networks

Recent analysis on polypharmacology leads to the idea that only small fragments of drugs and targets are a key to understanding their interactions forming polypharmacology. This idea motivates us to build an in silico approach of finding significant substructure patterns from drug-target (molecular graph-amino acid sequence) pairs. This article introduces an efficient in silico method for enumerating, from given drug-target pairs, all frequent subgraph-subsequence pairs, which can then be further examined by hypothesis testing for statistical significance. Unique features of the method are its scalability, computational efficiency, and technical soundness in terms of computer science and statistics. The presented method was applied to 11,219 drug-target pairs in DrugBank to obtain significant substructure pairs, which can divide most of the original 11,219 pairs into eight highly exclusive clusters, implying that the obtained substructure pairs are indispensable components for interpreting polypharmacology.

Heat-killed bacillus Calmette-Guérin and Mycobacterium kansasii antigen 85B combined vaccination ameliorates dermatitis in a mouse model of atopic dermatitis by inducing regulatory T cells

BACKGROUND

Atopic dermatitis (AD) is a recurrent inflammatory skin disease characterized by dominant T-helper (Th) 2 cytokine response. Bacillus Calmette-Guérin (BCG) has been used for preventing tuberculosis, and is regarded as a strong Th1 cytokine inducer. Antigen (Ag) 85B is a secretory protein present in Mycobacterium species that induces Th1 cytokine production.

OBJECTIVES

We investigated the effects of combined vaccination of heat-killed BCG (hkBCG) and Mycobacterium kansasii Ag85B in an AD mouse model.

METHODS

For the AD model, keratin 14 promoter-derived caspase-1 overexpressing mice (KCASP1Tg) were used. The mice received a combination therapy of hkBCG at age 3 weeks and Ag85B twice weekly for 11 weeks from the 4th week; Ag85B monotherapy from the 4th week; hkBCG monotherapy at the 3rd week; or control saline. Areas of skin lesions, cytokine mRNA expression and serum interleukin (IL)-18 and immunoglobulin (Ig) E levels were analysed. Inducible Foxp3+  regulatory T cells (iTreg), IL-10-producing T cells (Tr1), and interferon (IFN)-γ/IL-4/IL-17-producing T cells were evaluated in the spleen.

RESULTS

Saline-treated mice and hkBCG monotherapy mice spontaneously developed severe dermatitis. However, combined therapy with hkBCG and Ag85B significantly suppressed the development of skin lesions and mast cell infiltrations. Elevations of the serum IgE and IL-18 levels were significantly suppressed with combined therapy. Mice treated with hkBCG and Ag85B had a normal number of iTreg in the spleen, and decreased number of both IL-4- and IL-17-producing CD4+ T cells. The effect of Ag85B monotherapy was limited.

CONCLUSIONS

Combined vaccination with hkBCG and Ag85B decreases AD skin lesions by inducing regulatory T cells, suggesting that this vaccination is a potent and novel therapeutic strategy for AD.

PoSSuM: a database of similar protein-ligand binding and putative pockets

Numerous potential ligand-binding sites are available today, along with hundreds of thousands of known binding sites observed in the PDB. Exhaustive similarity search for such vastly numerous binding site pairs is useful to predict protein functions and to enable rapid screening of target proteins for drug design. Existing databases of ligand-binding sites offer databases of limited scale. For example, SitesBase covers only ~33,000 known binding sites. Inferring protein function and drug discovery purposes, however, demands a much more comprehensive database including known and putative-binding sites. Using a novel algorithm, we conducted a large-scale all-pairs similarity search for 1.8 million known and potential binding sites in the PDB, and discovered over 14 million similar pairs of binding sites. Here, we present the results as a relational database Pocket Similarity Search using Multiple-sketches (PoSSuM) including all the discovered pairs with annotations of various types. PoSSuM enables rapid exploration of similar binding sites among structures with different global folds as well as similar ones. Moreover, PoSSuM is useful for predicting the binding ligand for unbound structures, which provides important clues for characterizing protein structures with unclear functions. The PoSSuM database is freely available at http://possum.cbrc.jp/PoSSuM/.

PDB-scale analysis of known and putative ligand-binding sites with structural sketches

Computational investigation of protein functions is one of the most urgent and demanding tasks in the field of structural bioinformatics. Exhaustive pairwise comparison of known and putative ligand-binding sites, across protein families and folds, is essential in elucidating the biological functions and evolutionary relationships of proteins. Given the vast amounts of data available now, existing 3D structural comparison methods are not adequate due to their computation time complexity. In this article, we propose a new bit string representation of binding sites called structural sketches, which is obtained by random projections of triplet descriptors. It allows us to use ultra-fast all-pair similarity search methods for strings with strictly controlled error rates. Exhaustive comparison of 1.2 million known and putative binding sites finished in ∼30 h on a single core to yield 88 million similar binding site pairs. Careful investigation of 3.5 million pairs verified by TM-align revealed several notable analogous sites across distinct protein families or folds. In particular, we succeeded in finding highly plausible functions of several pockets via strong structural analogies. These results indicate that our method is a promising tool for functional annotation of binding sites derived from structural genomics projects.

SketchSort: Fast All Pairs Similarity Search for Large Databases of Molecular Fingerprints

Similarity networks of ligands are often reported useful in predicting chemical activities and target proteins. However, the naive method of computing all pairwise similarities of chemical fingerprints takes quadratic time, which is prohibitive for large scale databases with millions of ligands. We propose a fast all pairs similarity search method, called SketchSort, that maps chemical fingerprints to symbol strings with random projections, and finds similar strings by multiple masked sorting. Due to random projection, SketchSort misses a certain fraction of neighbors (i.e., false negatives). Nevertheless, the expected fraction of false negatives is theoretically derived and can be kept under a very small value. Experiments show that SketchSort is much faster than other similarity search methods and enables us to obtain a PubChem-scale similarity network quickly.

ROS-DET: robust detector of switching mechanisms in gene expression

A switching mechanism in gene expression, where two genes are positively correlated in one condition and negatively correlated in the other condition, is a key to elucidating complex biological systems. There already exist methods for detecting switching mechanisms from microarrays. However, current approaches have problems under three real cases: outliers, expression values with a very small range and a small number of examples. ROS-DET overcomes these three problems, keeping the computational complexity of current approaches. We demonstrated that ROS-DET outperformed existing methods, under that all these three situations are considered. Furthermore, for each of the top 10 pairs ranked by ROS-DET, we attempted to identify a pathway, i.e. consecutive biological phenomena, being related with the corresponding two genes by checking the biological literature. In 8 out of the 10 pairs, we found two parallel pathways, one of the two genes being in each of the two pathways and two pathways coming to (or starting with) the same gene. This indicates that two parallel pathways would be cooperatively used under one experimental condition, corresponding to the positive correlation, and the two pathways might be alternatively used under the other condition, corresponding to the negative correlation. ROS-DET is available from http://www.bic.kyoto-u.ac.jp/pathway/kayano/ros-det.htm.