Engineering orthogonal dual transcription factors for multi-input synthetic promoters

Synthetic biology has seen an explosive growth in the capability of engineering artificial gene circuits from transcription factors (TFs), particularly in bacteria. However, most artificial networks still employ the same core set of TFs (for example LacI, TetR and cI). The TFs mostly function via repression and it is difficult to integrate multiple inputs in promoter logic. Here we present to our knowledge the first set of dual activator-repressor switches for orthogonal logic gates, based on bacteriophage λ cI variants and multi-input promoter architectures. Our toolkit contains 12 TFs, flexibly operating as activators, repressors, dual activator–repressors or dual repressor–repressors, on up to 270 synthetic promoters. To engineer non cross-reacting cI variants, we design a new M13 phagemid-based system for the directed evolution of biomolecules. Because cI is used in so many synthetic biology projects, the new set of variants will easily slot into the existing projects of other groups, greatly expanding current engineering capacities

Extramedullary Plasmacytoma of Soft Tissues and Gingiva

Extramedullary plasmacytoma (EMP) is a rare plasma cell neoplasm of soft tissue without bone marrow involvement or other systemic characteristics of multiple myeloma. It accounts for 3% of all plasma cell tumors. Multiple extramedullary plasmacytoma is defined when there is more than one extramedullary tumor of clonal plasma cells and such presentation has not been described earlier. We report such rare case of multiple extramedullary plasmacytoma involving multiple soft tissues in chest, abdomen, mandible, maxilla, and gingiva

Tricks to translating TB transcriptomics.

Transcriptomics and other high-throughput methods are increasingly applied to questions relating to tuberculosis (TB) pathogenesis. Whole blood transcriptomics has repeatedly been applied to define correlates of TB risk and has produced new insight into the late stage of disease pathogenesis. In a novel approach, authors of a recently published study in Science Translational Medicine applied complex data analysis of existing TB transcriptomic datasets, and in vitro models, in an attempt to identify correlates of protection in TB, which are crucially required for the development of novel TB diagnostics and therapeutics to halt this global epidemic. Utilizing latent TB infection (LTBI) as a surrogate of protection, they identified IL-32 as a mediator of interferon gamma (IFNγ)-vitamin D dependent antimicrobial immunity and a marker of LTBI. Here, we provide a review of all TB whole-blood transcriptomic studies to date in the context of identifying correlates of protection, discuss potential pitfalls of combining complex analyses originating from such studies, the importance of detailed metadata to interpret differential patient classification algorithms, the effect of differing circulating cell populations between patient groups on the interpretation of resulting biomarkers and we decipher weighted gene co-expression network analysis (WGCNA), a recently developed systems biology tool which holds promise of identifying novel pathway interactions in disease pathogenesis. In conclusion, we propose the development of an integrated OMICS platform and open access to detailed metadata, in order for the TB research community to leverage the vast array of OMICS data being generated with the aim of unraveling the holy grail of TB research: correlates of protection

The Galactic Kinematics of Cataclysmic Variables

Kinematical properties of CVs were investigated according to population types and orbital periods, using the space velocities computed from recently updated systemic velocities, proper motions and parallaxes. Reliability of collected space velocity data are refined by removing 34 systems with largest space velocity errors. The 216 CVs in the refined sample were shown to have a dispersion of $53.70 \pm 7.41$ km s$^{-1}$ corresponding to a mean kinematical age of $5.29 \pm 1.35$ Gyr. Population types of CVs were identified using their Galactic orbital parameters. According to the population analysis, seven old thin disc, nine thick disc and one halo CV were found in the sample, indicating that 94% of CVs in the Solar Neighbourhood belong to the thin-disc component of the Galaxy. Mean kinematical ages $3.40 \pm 1.03$ and $3.90 \pm 1.28$ Gyr are for the non-magnetic thin-disc CVs below and above the period gap, respectively. There is not a meaningful difference between the velocity dispersions below and above the gap. Velocity dispersions of the non-magnetic thin-disc systems below and above the gap are $24.95 \pm 3.46$ and $26.60 \pm 4.18$ km s$^{-1}$, respectively. This result is not in agreement with the standard formation and evolution theory of CVs. The mean kinematical ages of the CV groups in various orbital period intervals increase towards shorter orbital periods. This is in agreement with the standard theory for the evolution of CVs. Rate of orbital period change was found to be $dP/dt=-1.62(\pm 0.15)\times 10^{-5}$ sec yr$^{-1}$.Comment: 17 pages, 6 figures and 4 tables, accepted for publication in Astrophysics and Space Scienc

Fast Spectral Clustering Using Autoencoders and Landmarks

In this paper, we introduce an algorithm for performing spectral clustering efficiently. Spectral clustering is a powerful clustering algorithm that suffers from high computational complexity, due to eigen decomposition. In this work, we first build the adjacency matrix of the corresponding graph of the dataset. To build this matrix, we only consider a limited number of points, called landmarks, and compute the similarity of all data points with the landmarks. Then, we present a definition of the Laplacian matrix of the graph that enable us to perform eigen decomposition efficiently, using a deep autoencoder. The overall complexity of the algorithm for eigen decomposition is $O(np)$, where $n$ is the number of data points and $p$ is the number of landmarks. At last, we evaluate the performance of the algorithm in different experiments.Comment: 8 Pages- Accepted in 14th International Conference on Image Analysis and Recognitio

Road Rage Menace: A Cross-sectional Study to Assess Driver Anger Level in Public Motor Vehicle Drivers in a City in Central India

Introduction: Road rage and aggressive driving is a prevalent condition in today’s society due to motorists’ frustrations during heavy traffic volumes. Objective: This study was done to assess the level of anger amongst the drivers of public transport vehicles in Indore, using Driving Anger Scale (DAS by Deffenbacher et. al.) and various factors affecting it. Material and Methods: A cross-sectional study was conducted among 135 drivers of Public transport vehicle drivers (Star bus, City-van and star cab drivers) in Indore to assess their anger level using Driving Anger Scale. The participants were required to record the amount of anger they would experience in response to each item in the scale (1=not at all angry, 2=a little angry, 3=some anger, 4=much anger, 5=very much angry). Results: The mean DAS score in Indore was found to be 3.013 and in the three organizations namely Star bus drivers, City van drivers and Star cab drivers was 2.92, 3.08 and 3.04 respectively. The DAS score of drivers with respect to the 6 sub-scales were: hostile gestures (Star bus -3.42,City van -3.67,Star cab -3.38), slow driving (Star bus -2.73,City van driv-2.78,Star cab-3.17), traffic obstructions (Star bus-2.85,City van -3.25,Star cab-3.18), discourtesy (Star bus -3.23,City van-3.33,Star cab -3.25)and police presence (Star bus -2.15,City van -1.99,Star cab -2.78), illegal driving (Star bus -3.04,City van -3.14,Star cab -2.89). The DAS scores of the drivers did not vary significantly with age group, experience, and educational qualification. Conclusion: Though DAS scores did not vary between the three groups of drivers, however average level anger for various given circumstances commonly found in the Indian traffic scenario was on the higher side

Permodelan Dinamik dan Validitas Model dari Sistem Kendali Tangki Ganda

This paper describes dynamic modeling and model validation of a couple-tank control system, which consist of a couple-tank, two electric-motor drivers, and two water-level sensors. Initially, dynamic modeling of the couple-tank was derived analytically. This derivation produced several parameters whose values were unknown. Experiments were then performed in order to obtain the values of those parameters. In addition to the couple-tank, other components were also modeled statically. Once all components of the couple-tank controlled system have been modeled, model validation of the whole system can then be performed.Keywords: Dynamic modeling, model validation, control, curve of the smallest quadrate

Undifferentiated Carcinoma of Larynx of Nasopharyngeal Type

Undifferentiated carcinoma of nasopharyngeal type arising in the larynx is unusual. This type of carcinoma-which occurs almost exclusively in nasopharynx-is very infrequent in the larynx (0.2%). Till date only 17 cases are reported in the medical literature. We present the clinical and histopathological findings along with the management of one additional case of undifferentiated carcinoma of nasopharyngeal type in the larynx which was managed successfully with radiotherapy

Pengayaan Materi Pokok Bahasan Tertentu dengan Materi Kimia Lingkungan

Aplikasi prinsip ilmu kimia dapat membangkitkan minat siswa untuk belajar kimia. Banyak pokok bahasan dalam pelajaran IImu Kimia di SMA yang sedikit memuat aplikasi prinsip. Kimia Lingkungan merupakan salah satu pokok bahasan yang banyak berisi aplikasi prinsip ilmu kimia. Agar siswa berminat rnempelajari ilmu kimia, pokok bahasan-pokok bahasan yang sedikit memuat apIikasi prinsip dapat diperkaya dengan materi Kimia Lingkungan

A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence

A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context. Here, we call trivariate vine copulas to extend the bivariate meta-analysis of diagnostic test accuracy studies by accounting for disease prevalence. Our vine copula mixed model includes the trivariate generalized linear mixed model as a special case and can also operate on the original scale of sensitivity, specificity, and disease prevalence. Our general methodology is illustrated by re-analyzing the data of two published meta-analyses. Our study suggests that there can be an improvement on trivariate generalized linear mixed model in fit to data and makes the argument for moving to vine copula random effects models especially because of their richness, including reflection asymmetric tail dependence, and computational feasibility despite their three dimensionality