Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Evaluation of Hemoglobin A1c Criteria to Assess Preoperative Diabetes Risk in Cardiac Surgery Patients

Objective: Hemoglobin A1c (A1C) has recently been recommended for diagnosing diabetes mellitus and diabetes risk (prediabetes). Its performance compared with fasting plasma glucose (FPG) and 2-h post-glucose load (2HPG) is not well delineated. We compared the performance of A1C with that of FPG and 2HPG in preoperative cardiac surgery patients. Methods: Data from 92 patients without a history of diabetes were analyzed. Patients were classified with diabetes or prediabetes using established cutoffs for FPG, 2HPG, and A1C. Sensitivity and specificity of the new A1C criteria were evaluated. Results: All patients diagnosed with diabetes by A1C also had impaired fasting glucose, impaired glucose tolerance, or diabetes by other criteria. Using FPG as the reference, sensitivity and specificity of A1C for diagnosing diabetes were 50% and 96%, and using 2HPG as the reference they were 25% and 95%. Sensitivity and specificity for identifying prediabetes with FPG as the reference were 51% and 51%, respectively, and with 2HPG were 53% and 51%, respectively. One-third each of patients with prediabetes was identified using FPG, A1C, or both. When testing A1C and FPG concurrently, the sensitivity of diagnosing dysglycemia increased to 93% stipulating one or both tests are abnormal; specificity increased to 100% if both tests were required to be abnormal. Conclusions: In patients before cardiac surgery, A1C criteria identified the largest number of patients with diabetes and prediabetes. For diagnosing prediabetes, A1C and FPG were discordant and characterized different groups of patients, therefore altering the distribution of diabetes risk. Simultaneous measurement of FGP and A1C may be a more sensitive and specific tool for identifying high-risk individuals with diabetes and prediabetes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90436/1/dia-2E2011-2E0074.pd

Ultrasonic interferometer for first-sound measurements of confined liquid He-4

We present a new technique for probing the properties of quantum fluids in restricted geometries. We have confined liquid 4He within microfluidic devices formed from glass wafers, in which one dimension is on the micro scale. Using an ultrasonic analog to Fabry-Perot interferometry, we have measured the first-sound of the confined liquid 4He, which can be a probe of critical behavior near the lambda point ($T_{\lambda}$). All thermodynamic properties of liquid $^4$He can be derived from first-sound and heat capacity measurements, and although quite a bit of experimental work has been done on the latter, no measurement of first-sound has been reported for a precisely confined geometry smaller than a few tens of micrometers. In this work, we report measurements of isobaric first sound in liquid $^4$He confined in cavities as small as ~ 5 ${\mu}$m. Our experimental set-up allows us to pressurize the liquid up to ~ 25 bar without causing deformation of the confined geometry, a pressure which is about 4 times larger than previously reported with similar microfluidic devices. Our preliminary results indicate that one can possibly observe finite-size effects and verify scaling laws, by using similar devices with smaller confinement.Comment: 9 pages, 11 figure

Genotyping and phylogenic study of Acanthamoeba isolates from human keratitis and swimming pool water samples in Iran

Objective: Acanthamoeba keratitis cause severe corneal infection and lead to poor vision and blindness. This disease is caused by a unicellular amphizoic protozoon called Acanthamoeba spp. that present in different environments. This study aimed to represent the existence and genotyping of Acanthamoeba spp. in patients with keratitis and swimming pool water (SPW) in Tehran Province, Central Iran. Methods: In this descriptive study, 56 clinical samples were collected from patients with keratitis and 30 water samples were collected from different swimming pools in Tehran Province. All samples were examined based on the morphological and molecular techniques. The genotypes were determined by sequencing the partial of 18S rRNA gene. Results: Of 56 clinical (corneal) and 30 environmental (SPW) samples, 30.3 and 40.0 were positive for Acanthamoeba spp., respectively. According to sequencing analysis, 94.1 of amoebic keratitis isolates were belonged to T4 genotype and only one (5.8) isolate was belonged to T11 genotype. All genotypes were detected from SPW samples were identified as T4 genotype. Conclusion: According to our results, use of contact lens and swimming in pool poses the major risk factor for amoebic keratitis in the studied area (Tehran). Moreover, T4 genotype was the predominant genotype of human keratitis and swimming pool samples there. Consequently, essential and practical measures are urgently needed to prevent subjects against this ocular seriously disease. © 202

BAF(mSWI/SNF) complex regulates mediolateral cortical patterning in the developing forebrain

Early forebrain patterning entails the correct regional designation of the neuroepithelium, and appropriate specification, generation, and distribution of neural cells during brain development. Specific signaling and transcription factors are known to tightly regulate patterning of the dorsal telencephalon to afford proper structural/functional cortical arealization and morphogenesis. Nevertheless, whether and how changes of the chromatin structure link to the transcriptional program(s) that control cortical patterning remains elusive. Here, we report that the BAF chromatin remodeling complex regulates the spatiotemporal patterning of the mouse dorsal telencephalon. To determine whether and how the BAF complex regulates cortical patterning, we conditionally deleted the BAF complex scaffolding subunits BAF155 and BAF170 in the mouse dorsal telencephalic neuroepithelium. Morphological and cellular changes in the BAF mutant forebrain were examined using immunohistochemistry and in situ hybridization. RNA sequencing, Co-immunoprecipitation, and mass spectrometry were used to investigate the molecular basis of BAF complex involvement in forebrain patterning. We found that conditional ablation of BAF complex in the dorsal telencephalon neuroepithelium caused expansion of the cortical hem and medial cortex beyond their developmental boundaries. Consequently, the hippocampal primordium is not specified, the mediolateral cortical patterning is compromised, and the cortical identity is disturbed in the absence of BAF complex. The BAF complex was found to interact with the cortical hem suppressor LHX2. The BAF complex suppresses cortical hem fate to permit proper forebrain patterning. We provide evidence that BAF complex modulates mediolateral cortical patterning possibly by interacting with the transcription factor LHX2 to drive the LHX2-dependent transcriptional program essential for dorsal telencephalon patterning. Our data suggest a putative mechanistic synergy between BAF chromatin remodeling complex and LHX2 in regulating forebrain patterning and ontogeny