Somatic mutations render human exome and pathogen DNA more similar

Immunotherapy has recently shown important clinical successes in a substantial number of oncology indications. Additionally, the tumor somatic mutation load has been shown to associate with response to these therapeutic agents, and specific mutational signatures are hypothesized to improve this association, including signatures related to pathogen insults. We sought to study in silico the validity of these observations and how they relate to each other. We first addressed whether somatic mutations typically involved in cancer may increase, in a statistically meaningful manner, the similarity between common pathogens and the human exome. Our study shows that common mutagenic processes increase, in the upper range of biologically plausible frequencies, the similarity between cancer exomes and pathogen DNA at a scale of 12-16 nucleotide sequences and established that this increased similarity is due to the specific mutation distribution of the considered mutagenic processes. Next, we studied the impact of mutation rate and showed that increasing mutation rate generally results in an increased similarity between the cancer exome and pathogen DNA, at a scale of 4-5 amino acids. Finally, we investigated whether the considered mutational processes result in amino-acid changes with functional relevance that are more likely to be immunogenic. We showed that functional tolerance to mutagenic processes across species generally suggests more resilience to mutagenic processes that are due to exposure to elements of nature than to mutagenic processes that are due to exposure to cancer-causing artificial substances. These results support the idea that recognition of pathogen sequences as well as differential functional tolerance to mutagenic processes may play an important role in the immune recognition process involved in tumor infiltration by lymphocytes

Signaling in Frequency Selective Gaussian Interference Channels

Sharing communication resources in wireless communication networks, due to the ever increasing growth in the number of users and the growing demand for higher data rates, appears to be inevitable. Consequently, present wireless communication networks should provide service for a large number of users through a frequency selective and interference limited medium rather than a single band, noise limited channel. In this thesis, we study a Gaussian interference network with orthogonal frequency sub-bands with slow faded and frequency-selective channel coefficients. The network is decentralized in the sense that there is no central node to assign the frequency sub-bands to the users. Moreover, due to lack of a feedback link between the two ends of any transmitter-receiver pair, all transmitters are unaware of the channel coefficients. Since the channel is assumed to be static during the communication period of interest, the concept of outage probability is employed in order to assess the performance of the network. In a scenario where all transmitters distribute their available power uniformly across the sub-bands, we investigate the problem of how establishing a nonzero correlation ρ among the Gaussian signals transmitted by each user along different frequency sub-bands can improve the outage probability at each of the receivers. Specifically, we show in a general k-user interference channel over N orthogonal frequency sub-bands that , when receivers treat interference as noise, ρ=0 is a point of local extremum for the achievable rate at each receiver, for any realization of channel coefficients. Moreover, in the case of K=2 with arbitrary number of sub-bands, it is verified that there exists a finite level of Signal-to-Noise Ratio (SNR) such that the achievable rate has a local minimum at ρ=0, which is not necessarily the case when K>2. We then concentrate on a 2-user interference channel over 2 orthogonal frequency sub-bands and characterize the behavior of the outage probability in the high SNR regime. We consider two simple decoding strategies at the receiver. In the first scenario, receivers simply treat interference as noise. In the second scenario, the receivers have the choice either to decode the desired signal treating interference as noise or to decode interference treating the desired signal as noise before decoding the interference free signal. Indeed, in both cases, we first show that the achievable rate is an increasing function of ρ in the high SNR regime, which suggests to repeat the same signal over the sub-bands. This observation, in a sense, reflects to the behavior of the outage probability, the scaling behavior of which in the high SNR regime is characterized for the Rayleigh fading scenario.1 yea

An automated pipeline for the discovery of conspiracy and conspiracy theory narrative frameworks: Bridgegate, Pizzagate and storytelling on the web

Although a great deal of attention has been paid to how conspiracy theories circulate on social media and their factual counterpart conspiracies, there has been little computational work done on describing their narrative structures. We present an automated pipeline for the discovery and description of the generative narrative frameworks of conspiracy theories on social media, and actual conspiracies reported in the news media. We base this work on two separate repositories of posts and news articles describing the well-known conspiracy theory Pizzagate from 2016, and the New Jersey conspiracy Bridgegate from 2013. We formulate a graphical generative machine learning model where nodes represent actors/actants, and multi-edges and self-loops among nodes capture context-specific relationships. Posts and news items are viewed as samples of subgraphs of the hidden narrative network. The problem of reconstructing the underlying structure is posed as a latent model estimation problem. We automatically extract and aggregate the actants and their relationships from the posts and articles. We capture context specific actants and interactant relationships by developing a system of supernodes and subnodes. We use these to construct a network, which constitutes the underlying narrative framework. We show how the Pizzagate framework relies on the conspiracy theorists' interpretation of "hidden knowledge" to link otherwise unlinked domains of human interaction, and hypothesize that this multi-domain focus is an important feature of conspiracy theories. While Pizzagate relies on the alignment of multiple domains, Bridgegate remains firmly rooted in the single domain of New Jersey politics. We hypothesize that the narrative framework of a conspiracy theory might stabilize quickly in contrast to the narrative framework of an actual one, which may develop more slowly as revelations come to light.Comment: conspiracy theory, narrative structur

An Automated Pipeline for Character and Relationship Extraction from Readers' Literary Book Reviews on Goodreads.com

Reader reviews of literary fiction on social media, especially those in persistent, dedicated forums, create and are in turn driven by underlying narrative frameworks. In their comments about a novel, readers generally include only a subset of characters and their relationships, thus offering a limited perspective on that work. Yet in aggregate, these reviews capture an underlying narrative framework comprised of different actants (people, places, things), their roles, and interactions that we label the "consensus narrative framework". We represent this framework in the form of an actant-relationship story graph. Extracting this graph is a challenging computational problem, which we pose as a latent graphical model estimation problem. Posts and reviews are viewed as samples of sub graphs/networks of the hidden narrative framework. Inspired by the qualitative narrative theory of Greimas, we formulate a graphical generative Machine Learning (ML) model where nodes represent actants, and multi-edges and self-loops among nodes capture context-specific relationships. We develop a pipeline of interlocking automated methods to extract key actants and their relationships, and apply it to thousands of reviews and comments posted on Goodreads.com. We manually derive the ground truth narrative framework from SparkNotes, and then use word embedding tools to compare relationships in ground truth networks with our extracted networks. We find that our automated methodology generates highly accurate consensus narrative frameworks: for our four target novels, with approximately 2900 reviews per novel, we report average coverage/recall of important relationships of > 80% and an average edge detection rate of >89\%. These extracted narrative frameworks can generate insight into how people (or classes of people) read and how they recount what they have read to others

Validity and Cross-Cultural Adaptation of the Persian Version of the Oxford Elbow Score

Oxford Elbow Score (OES) is a patient-reported questionnaire used to assess outcomes after elbow surgery. The aim of this study was to validate and adapt the OES into Persian language. After forward-backward translation of the OES into Persian, a total number of 92 patients after elbow surgeries completed the Persian OES along with the Persian DASH and SF-36. To assess test-retest reliability, 31 randomly selected patients (34%) completed the Persian OES again after three days while abstaining from all forms of therapeutic regimens. Reliability of the Persian OES was assessed by measuring intraclass correlation coefficient (ICC) for test-retest reliability and Cronbach's alpha for internal consistency. Spearman's correlation coefficient was used to test the construct validity. Cronbach's alpha coefficient was 0.92 showing excellent reliability. Cronbach's alpha for function, pain, and social-psychological subscales was 0.95, 0.86, and 0.85, respectively. Intraclass correlation coefficient (ICC) was 0.85 for the overall questionnaire and 0.90, 0.76, and 0.75 for function, pain, and social-psychological subscales, respectively. Construct validity was confirmed as the Spearman correlation between OES and DASH was 0.80. Persian OES is a valid and reliable patient-reported outcome measure to assess postsurgical elbow status in Persian speaking population

Effect of melatonin on male offspring testis and sperm parameters in BALB/c mice after exposing their mother to METHamphetamine during pregnancy and lactation

Objective(s): Methamphetamine (METH) is a psychostimulant that has harmful effects on all organs,  the nervous system, cardiovascular system, and reproductive system. Since many METH consumers are young people of reproductive age, it poses a risk to the next generation of METH consumers. METH can pass through the placenta and is also secreted into breast milk. Melatonin (MLT) is the primary hormone of the pineal gland that regulates the circadian cycle, and it is also an antioxidant that can mitigate the effects of toxic substances. This study aims to investigate the protective effect of melatonin against the detrimental effects that METH has on the reproductive system of male newborns, whose mothers consumed METH during pregnancy and lactation.Materials and Methods: In the current study, 30 female adult balb/c mice were divided into three groups: control group, vehicle group that received normal saline, and the experimental group that received 5 mg/kg METH intraperitoneally during gestation and lactation. After lactation, the male offspring of each group were randomly divided into two subgroups, one of which received 10 mg/kg melatonin intragastrically for 21 days (corresponding to the lactation period of the mice) (METH-MLT) and the other did not (METH -D.W). After treatment, the mice were sacrificed and testicular tissue and epididymis were obtained for the following tests.Results: The diameter of seminiferous tubules, SOD activity, total Thiol groups concentration, catalase activity, sperm count, and PCNA and CCND gene expression were significantly increased in the METH-MLT group compared with the METH-DW. Apoptotic cells and MDA level ameliorated in the METH-MLT group compared with METH-D.W, and testicular weight had no notable change.Conclusion: The current study represents that consumption of METH during pregnancy and lactation can have adverse effects on the histological and biochemical factors of testis and sperm parameters of male newborns,  which can be mitigated by taking melatonin after the end of the breastfeeding period

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic