Suppression of steady-state, but not stimulus-induced NF-kappaB activity inhibits alphavirus-induced apoptosis.

Recent studies have established cell type- specific, proapoptotic, or antiapoptotic functions for the transcription factor NF-kappaB. In each of these studies, inhibitors of NF-kappaB activity have been present before the apoptotic stimulus, and so the role of stimulus- induced NF-kappaB activation in enhancing or inhibiting survival could not be directly assessed. Sindbis virus, an alphavirus, induces NF-kappaB activation and apoptosis in cultured cell lines. To address whether Sindbis virus- induced NF-kappaB activation is required for apoptosis, we used a chimeric Sindbis virus that expresses a superrepressor of NF-kappaB activity. Complete suppression of virus-induced NF-kappaB activity neither prevents nor potentiates Sindbis virus-induced apoptosis. In contrast, inhibition of NF-kappaB activity before infection inhibits Sindbis virus-induced apoptosis. Our results demonstrate that suppression of steady-state, but not stimulus-induced NF-kappaB activity, regulates expression of gene products required for Sindbis virus-induced death. Furthermore, we show that in the same cell line, NF-kappaB can be proapoptotic or antiapoptotic depending on the death stimulus. We propose that the role of NF-kappaB in regulating apoptosis is determined by the death stimulus and by the timing of modulating NF-kappaB activity relative to the death stimulus

Metabolic Syndrome among Type-2 Diabetic Patients in Benghazi-Libya: A pilot study

ABSTRACTBackground: Metabolic syndrome is a cluster of three out of five conditions that are due to hyperinsulinemia: abdominal obesity, atherogenic dyslipidemia (high triglycerides and/or low HDL),elevated blood pressure, and elevated plasma glucose. The syndrome is highly prevalent in patients with type-2 diabetes mellitus and often precedes the onset of hyperglycemia. It has been shown thatmetabolic syndrome is an independent clinical indicator of macro- and microvascular complications in diabetics. Aim and objectives: the aim of this pilot study was to estimate the frequency andcharacteristics of metabolic syndrome among type-2 diabetic patients in Benghazi. Patients and methods: This cross-sectional study involved 99 randomly selected adult patients with type-2diabetes mellitus. The patients were interviewed and examined, and their lipid profiles were checked 9-12 hours after overnight fasting. Metabolic syndrome was defined according to the criteria of the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) and of the International Diabetes Federation (IDF). Results: About 92% of the patients had the metabolicsyndrome according to ATP III criteria and 80.8% according to IDF criteria. Females were more affected, males with metabolic syndrome were significantly older, and females were significantly moreobese. No significant difference was observed between males and females regarding waistcircumference, HDL level and triglyceride level. The commonest and most important component ofmetabolic syndrome in the study group was low HDL. Conclusion: Metabolic syndrome is common among Libyans with type-2 diabetes mellitus, and it is significantly more common in females thanmales. The most significant predictor of metabolic syndrome in type-2 diabetic patients in Benghazi is low HDL

Busy Beaver Scores and Alphabet Size

We investigate the Busy Beaver Game introduced by Rado (1962) generalized to non-binary alphabets. Harland (2016) conjectured that activity (number of steps) and productivity (number of non-blank symbols) of candidate machines grow as the alphabet size increases. We prove this conjecture for any alphabet size under the condition that the number of states is sufficiently large. For the measure activity we show that increasing the alphabet size from two to three allows an increase. By a classical construction it is even possible to obtain a two-state machine increasing activity and productivity of any machine if we allow an alphabet size depending on the number of states of the original machine. We also show that an increase of the alphabet by a factor of three admits an increase of activity

Modelling endoplasmic reticulum network maintenance in a plant cell

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.The endoplasmic reticulum (ER) in plant cells forms a highly dynamic network of complex geometry. ER network morphology and dynamics are influenced by a number of biophysical processes, including filament/tubule tension, viscous forces, Brownian diffusion and interactions with many other organelles and cytoskeletal elements. Previous studies have indicated that ER networks can be thought of as constrained minimal-length networks acted on by a variety of forces that perturb and/or remodel the network. Here, we study two specific biophysical processes involved in remodelling. One is the dynamic relaxation process involving a combination of tubule tension and viscous forces. The other is the rapid creation of cross-connection tubules by direct or indirect interactions with cytoskeletal elements. These processes are able to remodel the ER network: the first reduces network length and complexity while the second increases both. Using live cell imaging of ER network dynamics in tobacco leaf epidermal cells, we examine these processes on ER network dynamics. Away from regions of cytoplasmic streaming, we suggest that the dynamic network structure is a balance between the two processes, and we build an integrative model of the two processes for network remodelling. This model produces quantitatively similar ER networks to those observed in experiments. We use the model to explore the effect of parameter variation on statistical properties of the ER network.This work was funded by a Leverhulme Trust grant (RPG-2015-106)

Plant ER geometry and dynamics: biophysical and cytoskeletal control during growth and biotic response.

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.The endoplasmic reticulum (ER) is an intricate and dynamic network of membrane tubules and cisternae. In plant cells, the ER 'web' pervades the cortex and endoplasm and is continuous with adjacent cells as it passes through plasmodesmata. It is therefore the largest membranous organelle in plant cells. It performs essential functions including protein and lipid synthesis, and its morphology and movement are linked to cellular function. An emerging trend is that organelles can no longer be seen as discrete membrane-bound compartments, since they can physically interact and 'communicate' with one another. The ER may form a connecting central role in this process. This review tackles our current understanding and quantification of ER dynamics and how these change under a variety of biotic and developmental cues.IS, RW and CL are funded by a Leverhulme Trust grant (RPG-2015-106) and CP by a Sainsbury studentship. LG is funded by the Gordon and Betty Moore Foundation for the lattice light sheet microscopy and by the Biology Department, Texas A&M University. L. Griffing would like to thank John Heddleston and Teng-Leong Chew at the Advanced Imaging Center in Janelia-HHMI Research Campus, Ashburn VA, for images taken with the light sheet microscope

Defining the role of oxygen tension in human neural progenitor fate.

Hypoxia augments human embryonic stem cell (hESC) self-renewal via hypoxia-inducible factor 2α-activated OCT4 transcription. Hypoxia also increases the efficiency of reprogramming differentiated cells to a pluripotent-like state. Combined, these findings suggest that low O2 tension would impair the purposeful differentiation of pluripotent stem cells. Here, we show that low O2 tension and hypoxia-inducible factor (HIF) activity instead promote appropriate hESC differentiation. Through gain- and loss-of-function studies, we implicate O2 tension as a modifier of a key cell fate decision, namely whether neural progenitors differentiate toward neurons or glia. Furthermore, our data show that even transient changes in O2 concentration can affect cell fate through HIF by regulating the activity of MYC, a regulator of LIN28/let-7 that is critical for fate decisions in the neural lineage. We also identify key small molecules that can take advantage of this pathway to quickly and efficiently promote the development of mature cell types

Exploring the Impact of Evolutionary Computing based Feature Selection in Suicidal Ideation Detection

© 2019 IEEE. The ubiquitous availability of smartphones and the increasing popularity of social media provide a platform for users to express their feelings, including suicidal ideation. Suicide prevention by suicidal ideation detection on social media lights the path to controlling the rapidly increasing suicide rates amongst youth. This paper proposes a diverse set of features and investigates into feature selection using the Firefly algorithm to build an efficient and robust supervised approach to classifying tweets with suicidal ideation. The development of a suicidal language to create three diverse, manually annotated datasets leads to the validation of the proposed model. An in-depth result and error analysis lead to an accurate system for monitoring suicidal ideation on social media along with the discovery of optimal feature subsets and selection methods using a penalty based Firefly algorithm

Deconstructing Weight Management Interventions for Young Adults: Looking Inside the Black Box of the EARLY Consortium Trials.

ObjectiveThe goal of the present study was to deconstruct the 17 treatment arms used in the Early Adult Reduction of weight through LifestYle (EARLY) weight management trials.MethodsIntervention materials were coded to reflect behavioral domains and behavior change techniques (BCTs) within those domains planned for each treatment arm. The analytical hierarchy process was employed to determine an emphasis profile of domains in each intervention.ResultsThe intervention arms used BCTs from all of the 16 domains, with an average of 29.3 BCTs per intervention arm. All 12 of the interventions included BCTs from the six domains of Goals and Planning, Feedback and Monitoring, Social Support, Shaping Knowledge, Natural Consequences, and Comparison of Outcomes; 11 of the 12 interventions shared 15 BCTs in common across those six domains.ConclusionsWeight management interventions are complex. The shared set of BCTs used in the EARLY trials may represent a core intervention that could be studied to determine the required emphases of BCTs and whether additional BCTs add to or detract from efficacy. Deconstructing interventions will aid in reproducibility and understanding of active ingredients

Relating the Radar Bright Band and Its Strength to Surface Rainfall Rate Using an Automated Approach

In radar observations of hydrometeors, the 0°C isotherm in the atmosphere (i.e., the freezing level) usually appears as a region of enhanced reflectivity. This region is known as the bright band (BB). In this study, observations over 12 months from a vertically pointing 35-GHz radar and a collocated disdrometer at the Natural Environment Research Council (NERC) Facility for Atmospheric and Radio Research (NFARR) are used to identify and compare microphysical differences between BB and non-brightband (NBB) periods. From these observations, the relationship between radar reflectivity Z and rainfall intensity R is found to be Z = 772R0.57 for BB periods and Z = 108R0.99 for NBB periods. Additionally, the brightband strength (BBS) was calculated using a novel method derived from the Michelson contrast equation in an attempt to explain the observed variability in BB precipitation. A series of Z–R relationships are computed with respect to BBS. The coefficients increase with increasing BBS from 227 to 926, while the exponents decrease with increasing BBS from 0.85 to 0.38. The results also indicate that NBB periods identified in the presence of a 0°C isotherm in other studies may be misclassified due to their inability to identify weak brightband periods. As such, it is hypothesized that NBB periods are solely due to warm rain processes

A computational framework to emulate the human perspective in flow cytometric data analysis

Background: In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation. <p/>Results: To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Finally, we extended manual gating with a new capacity for constructing templates that can identify target populations in terms of their relative parameters, as opposed to the more commonly used absolute or physical parameters. This allows flowScape to apply such templates in batch mode for detecting the corresponding populations in a flexible, sample-specific manner. We also demonstrated different applications of our framework to flow data analysis and show its superiority over other analytical methods. <p/>Conclusions: The human perspective, built on top of intuition and experience, is a very important component of flow cytometric data analysis. By emulating some of its approaches and extending these with automation and rigor, flowScape provides a flexible and robust framework for computational cytomics