Search

Non-small cell lung cancer (NSCLC) is a prevalent tumour type in our country, with lung squamous carcinoma being a commonly observed NSCLC subtype besides lung adenocarcinoma. Epidermal growth factor receptor (EGFR) is a significant driver gene in lung cancer, and EGFR mutation frequency is considerably lower in lung squamous carcinoma in comparison to lung adenocarcinoma. Although targeted therapy against EGFR has demonstrated significant advancements in lung adenocarcinoma, while progress in lung squamous carcinoma has been relatively sluggish. This paper reviews recent studies on molecular targeted therapy for EGFR-mutated lung squamous carcinoma and summarises the efficacy of EGFR-tyrosine kinase inhibitors (TKIs) in treating squamous carcinoma of the lung, in order to provide a reference for treating patients with EGFR-mutated squamous carcinoma of the lung. [ABSTRACT FROM AUTHOR]

Abstract: This study investigated the various factors affecting DNA profiling from DNA recovered from fingerprints deposited on paper before and after fingerprint enhancement treatments. The DNeasy® plant mini kit (QIAGEN®) was found to improve DNA recovery from paper by over 150% compared with the QIAamp® mini kit. A significant decrease in the amount of DNA recovered was observed following treatment with DFO and/or Ninhydrin. This decrease in yield did not have a comparably significant effect on the quality of the SGM Plus™ profiles. Furthermore, this study found that whilst certain paper types, such as newspaper, magazine and filter paper allowed for the good recovery of DNA, common office paper and white card, strongly interfered with the recovery of DNA resulting in poor quality profiles. [Copyright &y& Elsevier]

Lung cancer associated with cystic airspaces (LCCA) is a type of lung cancer characterized by the presence of cystic cavities in or around the tumor on imaging. Due to its high potential for misdiagnosis or underdiagnosis, the prognosis of LCCA patients is poor, necessitating further large-scale clinical studies to elucidate its characteristics. Currently, four imaging classification systems exist, and there has been a progressive increase in attention towards LCCA, particularly with regard to the study of its imaging features. The results indicate a correlation between the pathological features and imaging findings of LCCA; however, research on driver gene mutations and molecular subtyping associated with lung cancer remains insufficient. Due to the challenges associated with early diagnosis and the poorer prognosis compared to general types of lung cancer, this paper comprehensively reviews the research progress on LCCA, including its definition, etiology, pathogenesis, imaging features, histological and pathological features, treatment, and prognosis, aiming to serve as a valuable resource for clinical decision-making. [ABSTRACT FROM AUTHOR]

Bioinformatics computing is a kind of big data processing problem, which usually has the characteristics of large data scale, large computational load and long computational time. Therefore, the use of big data technology in bioinformatics computing has gradually become a research hotspot, and using Hadoop for gene sequence alignment is one of it. It is a common way to use various tools to complete a job in the field of Biocomputing. In most studies of parallel alignment of gene sequences using Hadoop, third-party tools are also needed. However, there are few methods using Hadoop independently to complete gene sequences alignment. Adding data processing with other tools to Hadoop workflow not only affects the improvement of computing performance, but also complicates the application. In this paper, a parallel alignment model of gene sequences based on multiple inputs and outputs is proposed, which can independently complete parallel alignment of gene sequences in Hadoop platform without using other tools. This model not only simplifies the process flow of gene sequence alignment, but also improves the performance compared with other methods. This paper describes in detail the method of manipulating gene sequences with multiple inputs and outputs modes on Hadoop platform and the design of a computing model based on this method, and proves the superiority of this model through experiments. [ABSTRACT FROM AUTHOR]

Bio-Named Entity Recognition (Bio-NER) is the process of identifying and semantically classifying biomedical technical terms and named entities in Biomedicine literature. Therefore, it is a major task in biomedical knowledge acquisition. Meanwhile, Natural Language Processing (NLP) plays an important role in Bio-NER in the biomedical domain. The first and most essential biomedical literature mining task incorporates biomedical entity recognition such as protein, gene, and chemicals. The most recent Bio-NER methods rely on predefined traditional features, which attempt to capture the specific surface properties of entity types. However, these empirically predefined feature sets differ between entity types and are manually constructed and complicated, which means developing them is costly. In this paper, we systematically present a comparative evaluation study of three methods, which are: the traditional feature representation method, the continuous bag-of-words (CBOW) model, and a new prototypical representation method with two popular sequence-labeling approaches (Conditional Random Fields (CRFs) and Maximum Entropy Markov Models (MEMM)). We evaluated these models with two major Bio-NER tasks, which involve the JNLPBA and GENETAG corpora. This paper examined the prototypical word representation method and found that Word2Vec can be successfully used for Bio-NER. Our results show that the new prototypical representation method improved the performance of the two machine learning models with different datasets. Also, the new prototypical representation method performed better than the traditional feature representation method and CBOW model for both datasets. Finally, our experiment proved that the CRF classifier with the new prototypical representation method achieved the best results when 90% data was used as training data, yielding overall F-measure values of 0.79% and 0.85% for the JNLPBA corpus and GENETAG corpus, respectively. In comparison, the results achieved using the ME classifier yielded overall F-measure values of 0.76% and 0.78% for the JNLPBA corpus and GENETAG corpus, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Brazilian Journal of Biology is the property of Instituto Internacional de Ecologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Co-production regularly falls short of its transformation ambitions. • Co-production is being stretched beyond the local into global research and technology spaces. • The meaning of co-production is extended in transformative ways in global gene drive. • Transformative ambitions in gene drive'slip' towards reductive framings of collaboration. • Slippage in co-production can be linked to established and new knowledge hierarchies. Co-production is an increasingly popular framework for knowledge generation, evaluation and decision making. Despite its potential to open up decisions and practices to the input of others, co-production regularly falls short of its transformative ambitions. Through documentary analysis, we investigate the meaning and dynamics of co-production as it stretches beyond the local into global research and technology spaces. We find that in the case of global gene drive, the meaning of co-production is extended in novel ways and underpinned by new possibilities for meaningful transformation. At the same time, we also identify a simultaneous resurfacing of reductive framings of collaboration. In the paper we present 'slippage' as a useful heuristic in helping to understand why co-production fails. We argue that if co-production in these new spaces is to achieve its transformative ambitions, there is a need to engage with new and entrenched knowledge hierarchies that contribute to this slippage. [ABSTRACT FROM AUTHOR]

Breast cancer poses the greatest threat to human life and especially to women's life. Despite the progress made in data mining technology in recent years, the ability to predict and diagnose such fatal diseases based on gene expression data still reveals a limited prediction performance, which may not be surprising since most of the genes in expression data are believed to be irrelevant or redundant. The dimensionality reduction process may be considered as a crucial step to analyze gene expression data, as it can reduce the high dimensionality of the breast cancer datasets, which may result into a better prediction performance of such diseases. The paper suggests a new hybrid approach-based gene selection that combines the filter method and the Ant Colony Optimization algorithm to find the smallest subset of informative genes (genes markers) among 24,481 genes. The proposed approach combines four machine learning algorithms - C5.0 Decision Tree, Support Vector Machines, K-Nearest Neighbors algorithm, and Random Forest Classifier - to classify each of the selected samples (patients) into two classes which have cancer or not. Compared with existing methods in the literature, experimental results indicate that our proposed gene selection approach achieved globally higher classification accuracies with a relatively smaller number of genes. [ABSTRACT FROM AUTHOR]

Pelamera atra (Rondani, 1861) is an enigmatic species of bristle fly that has been challenging dipterologists with regard to its taxonomic position within the family Tachinidae since it was first described. The species is rarely collected and is only known from a handful of female specimens. The first ever male specimen of P. atra was collected in southern Italy in 2017, and it allowed for the discovery of its unique terminalia. The present paper provides the first description of a male of P. atra and presents new insights about its phylogenetic position within the family based on molecular data. A maximum likelihood analysis was conducted on a selection of tachinid taxa using sequences of two nuclear protein-coding genes (CAD and MCS) to formulate the first hypothesis concerning the phylogenetic placement of P. atra. Phylogenetic analyses reconstructed P. atra as a member of the Tachininae sister to the (Loewiini + (Polideini + Ernestiini)) clade. This reconstruction challenges previous attempts at classifying Pelamera based on female external morphology, which instead suggested a close affinity to the tribes Brachymerini or Minthoini. Due to the morphological distinctiveness of this taxon, we here propose the placement of P. atra in the monotypic tribe Pelamerini stat. rev. [ABSTRACT FROM AUTHOR]

Hidden Markov models (HMMs) are applied to many problems of computational Molecular Biology. In a predictive task, the HMM is endowed with a decoding algorithm in order to assign the most probable path of states, and in turn the class labelling, to an unknown sequence. In this paper we introduce a novel decoding algorithm Log-posterior-best (LPB) which combines the log-odd posterior probability and 1-best algorithms. LPB is a two steps process: first the Log odd probability of each state is computed and then the best allowed label path through the model is evaluated by a 1-best algorithm. We show that our LPB decoding performs better than other existing algorithms in some computational biological problems such as gene finding in prokaryotes. [ABSTRACT FROM AUTHOR]

Copyright of Arquivos de Neuro-Psiquiatria is the property of Thieme Medical Publishing Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Biomédica: Revista del Instituto Nacional de Salud is the property of Instituto Nacional de Salud of Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Evolutionary neural architecture search (ENAS) algorithms benefit from the non-convex optimization capability of evolutionary computation. However, most ENAS algorithms use a genetic algorithm (GA) with fixed parameter settings, which limits the algorithm's search performance. Furthermore, the information generated during the evolutionary process is often ignored, while this information can be helpful for guiding the evolutionary direction of the population. This paper proposes a novel ENAS algorithm based on adaptive parameter control and gene potential contribution (AG-ENAS) to evolve neural networks efficiently. Firstly, an adaptive parameter adjustment mechanism is designed, based on population diversity and fitness. This enables better-informed adaptation of related parameters of genetic operators. Secondly, the mutation operator guided by the gene potential contribution of genes tends to produce better offspring. The gene potential contribution reflects the positive effect of the current gene on fitness. It guides the evolution by weighting the more valuable genes with the distribution index matrix. Finally, the concept of aging is introduced into the environmental selection, to offer more opportunities to the young generation and alleviate premature convergence. The proposed algorithm has been evaluated on eight different datasets, and compared against 44 state-of-the-art algorithms from the literature. The experimental results show that the network designed by AG-ENAS obtains higher classification accuracy than manual-designed networks such as SENet, DenseNet, and other ENAS algorithms such as Large-Evo and AE-CNN. [ABSTRACT FROM AUTHOR]

Because of the high cost of label collection, people are now faced with a large number of partially labeled gene expression data (p l g e -data). Single cell RNA-seq data (s c r s -data) are a kind of important p l g e -data and reflect the abundance of gene transcript mRNA measured directly or indirectly in cells. For convenience, a decision information system (DIS) based on s c r s -data is called a single cell gene decision space (s c g d -space). Due to the high dimensionality of s c r s -data, feature selection must be done before clustering and classification. The existing feature selection methods based on equivalence relation are ineffective for the s c g d -space owing to the strictness of equality between information values. To solve the above problems, this paper studies the uncertainty measurement of the s c g d -space based on class-consistent technology and considers its application to semi-supervised gene selection. Class-consistent technology replaces equality with approximate equality between two expression values at a gene. Based on the proposed technology, class-consistent and non-class-consistent relations on the cell set of the s c g d -space are established first. Then, the s c g d -space (O , A , d) is divided into labeled space (O l , A , d) and unlabeled space (O u , A , d). Next, four metrics of importance on each gene subset of (O , A , d) are defined. They are the weighted sum of (O l , A , d) and (O u , A , d) determined by the missing rate of labels and the established relations and can be used to measure the uncertainty of (O , A , d). In addition, as an application of four metrics to the s c g d -space, a semi-supervised gene selection algorithm is designed. Finally, the experimental results and statistical tests on 16 large-scale s c r s -data sets show that the defined metrics can effectively measure the uncertainty of the s c g d -space. The designed algorithm with a high reduction rate outperforms some state-of-the-art feature selection algorithms in terms of eight performance evaluation indicators. • We establish a class-consistent relation on the cell set of a s c g d -space based on classconsistent technology. • We define four metrics of importance on each gene subset of a s c g d -space. • We design a semi-supervised gene selection algorithm in a s c g d -space. • Experimental results show that the designed algorithm outperforms some state-ofthe-art feature selection algorithms. [ABSTRACT FROM AUTHOR]

Although sociologists in Britain have debated the nature of their field's relationship with biology since the late nineteenth century, interest in the full range of responses has only grown in recent years. This paper contributes to the spirit of historical revisionism by turning to the work of the biologist and first director of UNESCO, Julian Huxley (1887-1975). Paying particular attention to the doctrine he called 'scientific humanism' and his ideas about a biosocial agenda separate from the priorities of biology itself, the paper uses historical tools to address a concern that has frequently cast a shadow over debates about biosocial science: does it interfere with the progressive agenda sociologists have traditionally seen themselves as contributing to? The paper argues that Huxley's work is evidence that biosocial science is compatible with progressive goals and that recent developments in biology mean it may be the ideal time to reconsider long-standing attitudes. [ABSTRACT FROM AUTHOR]

Although sociologists in Britain have debated the nature of their field's relationship with biology since the late nineteenth century, interest in the full range of responses has only grown in recent years. This paper contributes to the spirit of historical revisionism by turning to the work of the biologist and first director of UNESCO, Julian Huxley (1887–1975). Paying particular attention to the doctrine he called ‘scientific humanism’ and his ideas about a biosocial agenda separate from the priorities of biology itself, the paper uses historical tools to address a concern that has frequently cast a shadow over debates about biosocial science: does it interfere with the progressive agenda sociologists have traditionally seen themselves as contributing to? The paper argues that Huxley's work is evidence that biosocial science is compatible with progressive goals and that recent developments in biology mean it may be the ideal time to reconsider long-standing attitudes. [ABSTRACT FROM AUTHOR]

Objectives: To perform a review of the literature of published articles assessing the role of genetic factors in the etiology of temporomandibular disorders (TMDs).Methods: A PubMed search was carried out by looking for all controlled clinical trials related to the topic and limiting the search to English language and humans. The references from the studies included and those from review articles were also examined for further relevant papers.Results: A total of 1999 articles were first identified, 24 of which were considered relevant to the topic. Two other papers were found while searching the references. While TMD signs and symptoms' co-occurrence was not found in subjects within the same family, many gene polymorphisms were shown to be associated with a higher or lower risk of TMD. Such genes were mainly related to serotonin activity and metabolism, Tcellreceptor pathway, catecholamine activity and metabolism, estrogen activity, folate metabolism, glutathione activity, ANKH gene, major histocompatibility complex, extracellular matrix metabolism, genes studied in the orofacial pain prospective evaluation risk and assessment (OPPERA) study, and related to cytokines activity and metabolism.Discussion: This new understanding of the pathophysiology of TMD can lead to a different treatment approach by identifying the subjects at higher risk for this pathology, and possibly by creating new drugs targeted at interfering with the expression of the genes that enhance such risk. [ABSTRACT FROM AUTHOR]

The paper reveals original findings in agrobiodiversity, as part of the global biodiversity puzzle. The Grey Steppe cattle are endangered to extinction and are part of a genetic preservation program in Romania. The research approached the productive performance, the genetic determinism of milk production traits, studied on a Grey Steppe breed population nucleus of 30 individuals, throughout 4 productive cycles. The average milk yield in all 4 consecutive lactations reached 1858 kg per capita, while total lipids and proteins reached 4.41% and 3.56%. Recalculated for Maturity Equivalent, the production summed up 2197 kg milk (4.36% fat, 3.52% proteins). The electrophoresis profiling revealed 6 loci codifying the major proteins in milk: alpha-casein S1 (αS1-cz), beta-casein (β-cz), kappa-casein (K-cz), beta-lactoglobulin (β-lg), alpha-lactoglobulin (α-la) and alpha-casein S2 (αS2-cz). Apart from these, we identified a new allele in heterozygote state in two individuals of the studied population and we coded it αS1-CN IRV. The main lactoprotein is the kappa-casein (K-cz), identified with high heritability in the studied population (h² = 0.57 %), while the αS1 casein (αS1-cz) had intermediate capacity of transmittance across generations (h² = 0.29%). The Grey Steppe breed represents a valuable gene pool due to its high capacity of adaptation to local conditions, to its versatileness in using lower quality feed than other specialized breeds, as well as to its reproductive robustness and to its potential in bearing ancestral, undiscovered genes coding beneficial lactoprotein species. [ABSTRACT FROM AUTHOR]

This paper is a carrying on of the theme examined in (Bazzani, Freguglia 2013) where we discuss a proposal of studying of essential structural aspects of Darwinian Evolution Theory. Also in this case we apply a mathematical ago-antagonist theory inspired by Y. Cherruault's ideas (Cherruault 1998). In the present paper we consider the network structure of genes activity and its dynamics. [ABSTRACT FROM AUTHOR]

This paper characterizes the heat stress response (HSR) and explores the impact of temperatures on the immune response of larvae from two chironomid species, Prodiamesa olivacea and Chironomus riparius. Genes involved in crucial metabolic pathways were de novo identified in P. olivacea : Hsp27 , Hsp60 , Hsp70 , Hsc70 , Cdc37, and HSF for the heat stress response (HSR) and TOLL , PGRP , C-type lectin, and JAK/hopscotch for the immune system response (ISR). Quantitative real-time PCR was used to evaluate the expression levels of the selected genes in short-term treatments (up to 120') at high temperatures (35 °C and 39 °C). Exposing P. olivacea to elevated temperatures resulted in HSR induction with increased expression of specific heat shock genes, suggesting the potential of HSPs as early indicators of acute thermal stress. Surprisingly, we found that heat shock represses multiple immune genes, revealing the antagonist relation between the heat shock response and the innate immune response in P. olivacea. Our results also showed species-dependent gene responses, with more significant effects in P. olivacea, for most of the biomarkers studied, demonstrating a higher sensitivity in this species to environmental stress conditions than that of C. riparius. This work shows a multi-species approach that enables a deeper understanding of the effects of heat stress at the molecular level in aquatic dipterans. [Display omitted] • P. olivacea and C. riparius were used to assess the effects of heat stress. • New genes, related to cell stress and immune responses, were characterised in P. olivacea. • Expression of stress and immune response genes were altered by elevated temperature. • The heat shock and immune responses are antagonists in P. olivacea. • The transcriptional alterations detected were species-dependent. [ABSTRACT FROM AUTHOR]

Monogonont rotifers are common species in aquatic environments and make model species for ecotoxicology studies. Whole genomes of several species of the genus Brachionus have been assembled, but no information on the freshwater rotifer Brachionus rubens has been reported. In this study, the whole-genome sequence of B. rubens was successfully assembled using NextDenovo. The total length of the genome was 132.7 Mb (N50 = 2.51 Mb), including 122 contigs. The GC contents accounted for 29.96% of the genome. Aquatic organisms are always exposed to various external stresses, and a comprehensive genomic analysis is needed to better understand the adverse effects on organisms. This paper focuses on the ecotoxicological aspect and conducted genome analysis of representative gene families involved in detoxification mechanisms against environmental stressors. Specifically, we identified cytochrome P450 genes (CYPs) of phase I, glutathione S -transferase genes (GSTs) of phase II, and ATP-binding cassette transporter genes (ABCs) of phase III in the genome of B. rubens. Gene duplications were found in CYP , GST , and ABC genes, as is the case for other Brachionus rotifers. Our results suggest that these detoxification-related gene families have evolved in a species-specific and/or lineage-specific manner. This paper improves our understanding of how the freshwater Brachionus rotifers respond to environmental stressors in a molecular ecotoxicology context. [Display omitted] • The whole-genome sequence of B. rubens was successfully assembled using NextDenovo. • The total length of the genome was 132.7 Mb (N50 = 2.51 Mb), including 122 contigs. • Representative genes (CYP s, GST sI, and ABC s) for detoxification mechanisms were identified. • Gene duplications were found in CYP , GST , and ABC genes. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we present new extension of RuleGO rule generation method. The method was designed to discover logical rules including combination of GO terms in their premises in order to provide functional description of analyzed gene signatures. As the number of obtained rules is typically huge, filtration algorithm is required to select only the most interesting ones. Rule interestingness measures currently used within the RuleGO method do not always allow for the selection of the rules according to user's subjective preferences. In this paper we propose an application of the UTA method for estimation of the multicriteria rule interestingness measure reflecting expert's subjective rule evaluation. In the presented method, each of the rules is characterized by a vector of values reflecting its quality due to the different parial interestingness measures. From the designated set of rules a set of representative rules is selected and presented to an expert who orders the rules based on his preferences. Using the information about the order and values of the partial interestingness measures, the additive multicriteria interestingness measure is estimated. The measure is estimated in such a way that the rule ranking obtained by this function is consistent with the ranking given by an expert. The presented approach is applied to three microarray data sets and obtained rule orders are compared with rule orders generated with the standard RuleGO rule evaluation method. Presented method allows obtaining the rule ranking that is better correlated with expert ranking than the ranking obtained in the standard way. [Copyright &y& Elsevier]

Graphical abstract Highlights • Fusion of Thresholding and Ratio method selects the subset of genes with less ratio within the chosen threshold range. • Thresholding gives the alternate subset of genes to confirmation of result of classification. • Stacked Autoencoder algorithm gives best possible compromise between number of genes and accuracy. • 100% classification accuracy obtained using five common genes across four glioma datasets (GDS1975, GDS1976, GDS1815 and GDS1816). Abstract Invention of the microarray technology has rendered it possible to inspect the whole genome at once in cancer classification. However, in order to curtail the computational complexity and augment the accuracy of cancer classification, it is essential to sift the vast microarray data for the informative genes. In this paper, Thresholding and Ratio methods are presented, individually as well as conjointly (hybrid method) to choose optimal gene subset from the microarray data. Moreover, Discrete Wavelet Transform (DWT) is deployed to pare the size of microarray data still further. The classification is accomplished by using various neural network algorithms and Stacked Autoencoder algorithm. The results of classification are compared for number of thresholds, ratios, wavelets and classification algorithms. It is observed that the Stacked Autoencoder network trained by Back Propagation algorithm delivers the best results in terms of classification accuracy and number of genes. [ABSTRACT FROM AUTHOR]

The hypothesis being advanced in this paper is that there is a new medical paradigm emerging from the biomedical research carried out in this century, mainly due to the explosion of the so called "omics" and associated techniques. The main idea is that there is a common pathway from wellbeing and health to chronic disease ("chronopathy") and even to death, which comprises following steps: 1) unhealthy diet, sedentary life style and permanent exposition to xenobiotics and all kinds of noxious stimuli;→2) intestinal dysbiosis;→3) alteration of the intestinal mucus layer (especially that of the colon);→4) disruption of the endothelial tight junctions;→5) metabolic endotoxemia+bacterial translocation;→6) inflammation;→7) exacerbation of the enteric nervous system (ENS) and consequent maladaptation and malfunctioning of the colon;→8) epigenetic manifestations;→9) "chronopathy" and premature death. Therefore, in order to maintain a good health or to improve or even reverse chronic diseases in a person, the main outcome to look for is a homeostatic balance of the intestinal microbiota (eubiosis), most of which is located in the colon. Lynn Margulis was one of the main scientists to highlight the importance of the role played by bacteria not only in the origin of all biological species now present on earth, but also on their role in global homeostasis. Bacteria do not rely on other living beings for their existence, while the latter depend completely on the former. Humans are no exemption, and new evidence emerges each day about the pivotal role of intestinal microbiota in human health, disease and, in general, in its wellbeing. The following facts about intestinal microbiota are nowadays generally accepted: there are about 10 times more bacteria in the gut than human cells in every human being; the microbioma is about 100-150 times bigger that the human genome, and there is a clear link between intestinal microbiota and many of the most common chronic diseases, from obesity and diabetes to depression and Parkinson disease and different kinds of cancer. The main implication of this theory is that we should become a sort of microbiota farmers, that is, we ought to be more conscious of our intestinal microbiota, take care of it and monitor it permanently. Thus, as part of our good life habits (healthy eating, physical exercise), we should probably undergo periodic seasons of fasting and colon cleansing, as it was common in older times. [ABSTRACT FROM AUTHOR]

This paper addresses the concepts of face and (im)politeness from both first-order and second-order perspectives, and attempts at rethinking face, (im)politeness, and Face-Threatening Acts (FTAs). It suggests that each and every speech act is issued as a result of the interplay between self's intention and his motivation, with intention being the ignition, and motivation the fuel. Listing a number of features of speech acts, the paper further argues that FTAs must be redefined, and suggests the existence of Face-Attacking Acts (FAAs) as well as Face-Guarding Acts (FGAs)-but uses FAAs as a cover term for both. The paper also suggests a model for the description of FAAs/FGAs, and argues that they fall into four classes: (1) self-destructive hypothetical FAAs, (2) self-/other-guarding hypothetical FGAs, (3) other-destructive objective FAAs, and (4) self-/other-guarding objective FGAs. It then goes on to rethink the concept of (im)politeness, and suggests a model for politeness theory which entails a redefinition of politeness and impoliteness. It provides colorful examples and tangible evidence to relate (im)politeness to both context and collective pragmatic competence, and claims that action can be dominant or recess to speech just like dominant versus recess genes in biology. [ABSTRACT FROM AUTHOR]

Epidemiological and interventional research has highlighted sleep as a potentially modifiable risk factor associated with poor physical and mental health. Emerging evidence from (behavioral) genetic research also shows that sleep characteristics are under strong genetic control. With this study we aimed to meta-analyze the literature in this area to quantify the heritability of sleep duration and sleep quality in the general population. We conducted a systematic literature search in five online databases on January 24th 2020. Two authors independently screened 5644 abstracts, and 160 complete articles for the inclusion criteria of twin studies from the general population reporting heritability statistics on sleep duration and/or quality, and written in English. We ultimately included 23 papers (19 independent samples: 45,328 twins between 6 mo and 88 y) for sleep duration, and 13 papers (10 independent samples: 39,020 twins between 16 and 95 y) for sleep quality. Collectively, we showed that 46% of the variability in sleep duration and 44% of the variability in sleep quality is genetically determined. The remaining variation in the sleep characteristics can mostly be attributed to the unique environment the twins experience, although the shared environment seemed to play a role for the variability of childhood sleep duration. Meta-analyzed heritability estimates for sleep duration, however, varied substantially with age (17% infancy, 20-52% childhood, 69% adolescence and 42-45% adulthood) and reporter (8% parent-report, 38-52% self-report). Heritability estimates for actigraphic and Polysomnography (PSG)-estimated sleep were based on few small samples, warranting more research. Our findings highlight the importance of considering genetic influences when aiming to understand the underlying mechanisms contributing to the trajectories of sleep patterns across the lifespan. [ABSTRACT FROM AUTHOR]

Introduction: The pathogenesis of abdominal aortic aneurysm (AAA) remains poorly understood, however significant evidence has emerged in recent years to suggest a chronic inflammatory process. Observational studies have highlighted a familial trend towards AAA development among relatives of affected individuals and it is thought that inflammatory genes may influence an individual''s susceptibility. Conflicting reports exist over single gene versus multiple gene inheritance patterns in addition to a collection of studies examining individual inflammatory genes. This paper reviews the evidence for a genetic predisposition to aneurysm formation including familial and segregation studies in addition to experimental evidence investigating specific candidate genes. Method: Medline and Pubmed database searches were conducted using the search terms abdominal aortic aneurysm and gene. Papers were reviewed and references manually searched for further relevant publications which were added to the data. Papers were categorised under the headings familial, segregation and candidate gene studies. Results: A review of 58 papers is presented under sub-headings as above. In the case of the candidate gene section, a brief report of the functional relevance of each gene is included. Conclusion: A summary of the evidence presented is given and the direction of future work in this field is briefly considered. [Copyright &y& Elsevier]

This text reviews briefly the context in which epigenetics regulate gene expression in trophoblast development and function. It is an attempt to focus on a limited number of recent papers that, according to the author, shed new light on placental development, and constitute possible trails for improving knowledge and women follow-up in pathological pregnancies. [ABSTRACT FROM AUTHOR]

Copyright of Informatica (03505596) is the property of Slovene Society Informatika and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

It is not feasible to investigate the whole genes at a microscopic level for disease classification in Genomics. It might take substantial time to execute any meaningful analysis and the computational resources will be misused as not all the genes are responsible for the disease linked to a cell. Currently, it is quite challenging to select the most significant genes from high-dimensional microarray data for disease classification. In search of a better process, a novel gene subset selection technique has been developed based on Heatmap Analysis and Graph Neural Network (HAGNN). In the proposed method, a heatmap analysis has been performed for the different classes of microarray data to obtain the Region of Interest (ROIs). These ROIs are extracted from the original dataset and undergo a node reduction technique followed by an edge reduction technique in Graph Neural Network (GNN). This paper is concluded with an optimal subset of the most significant genes that cause cancer. The popular base classifiers have been used to evidence the importance of the selected genes as compared to the original data with the help of several metrics. The obtained results clearly show that the proposed methodology outperformed the other existing methods and make a greater impact on the advancement of the GNN -based gene selection method. • Dimension reduction of microarray data / informative gene selection. • Heatmap analysis. • Apply Graph Neural Network for gene selection. • Node Reduction and Edge Reduction of graph for dimension reduction. • Select Region of Interest from heatmap to reduce the dimension. [ABSTRACT FROM AUTHOR]

Genetic association is a challenging task for the identification and characterization of genes that increase the susceptibility to common complex multifactorial diseases. To fully execute genetic studies of complex diseases, modern geneticists face the challenge of detecting interactions between loci. In this paper, two evolutionary methods were compared to detect associations of single nucleotide polymorphisms (SNPs): a genetic algorithm and Gauss particle swarm optimization. Genetic algorithm was developed with partial matched crossover operator and two different strategies for initialization: regular initialization and top-5 strategy initialization. In both methods for different SNP barcodes (SNP combinations with their corresponding genotypes) the difference between case and control data is computed systematically. The algorithms look for the best combination which is the barcode with maximum difference between the two groups. Analysis results support that the genetic algorithm with top-5 strategy for initialization provides higher frequency difference values than the Gauss particle swarm optimization. It is also proved that a genetic algorithm reduces a computational cost for obtaining higher frequency difference between the case and control group. [ABSTRACT FROM AUTHOR]

The prevalence of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the microbiome is a major public health concern globally. Many habitats in the environment are under threat due to excessive use of antibiotics and evolutionary changes occurring in the resistome. ARB and ARGs from farms, cities and hospitals, wastewater treatment plants (WWTPs) or as water runoffs, may accumulate in water, soil, and air. We present a global picture of the resistome by examining ARG-related papers retrieved from PubMed and published in the last 30 years (1990–2020). Natural Language Processing (NLP) was used to retrieve 496,640 papers, out of which 9374 passed the filtering test and were further analyzed to determine the distribution and diversity of ARG subtypes. The papers revealed seven major antibiotic families together with their respective ARG subtypes in different habitats on six continents. Asia, especially China, had the highest number of ARGs related papers compared to other countries/regions/continents. ARGs belonging to multidrug, glycopeptide, and β-lactam families were the most common in reports from hospitals and sulfonamide and tetracycline families were common in reports from farms, WWTPs, water and soil. We also highlight the 'omics' tools used in resistome research, describe some factors that shape the development of resistome, and suggest future work needed to better understand the resistome. The goal was to show the global nature of ARB and ARGs in order to encourage collaborate research efforts aimed at reducing the negative impacts of antibiotic resistance on the One Health concept. [Display omitted] • Antibiotic resistant bacteria (ARB) are major public health concerns globally. • The diversity and distribution of antibiotic resistance genes (ARGs) are presented. • Factors that affect ARB and ARGs in different environments are discussed. • Different 'omics' tools used to study resistome development are also presented. [ABSTRACT FROM AUTHOR]

Extended-spectrum β-lactam antibiotics are critically important antibiotics for humans, but their use in food-animals poses a potential threat for public health. This paper addressed the occurrence of high-risk β-lactamase genes (bla genes) in intensive dairy farms, and assessed the effects of different waste treatment technologies at dairies on the propagation and dissemination of bla genes. Results showed that ESBL genes (bla TEM-1 , bla OXA-1), ampC β-lactamase genes (bla ampC) and carbapenemase genes (bla GES-1 , bla NDM) were prevalent in dairy cow waste, and even prevailed through each processing stage of solid manure and dairy wastewater. Significant levels of bla genes were present in the final lagoon (from 104 to 106 copies/mL, representing from 10% to 151%, of raw influent levels), raising the possibility of dissemination to the receiving environment. This concern was validated by the investigation on farmland that had long-term undergone wastewater irrigation, where causing an increase in bla gene levels in soils (approximately 1–3 orders of magnitude). More troublesomely, considerable levels of certain bla genes were still observed in the bedding material (up to 105 and 107 copies/g), which would directly threaten the dairy cow health. Otherwise, correlation analysis showed that both bacterial community and environmental factors played important roles in the bla genes abundances in dairy farms. This study demonstrated the prevalence of high-risk bla genes in dairy farms, and also underscored that dairy waste was a non-ignored great source of multidrug resistance for their surroundings. Image 1 • Pollution and transfer of β-lactamase (bla) genes in dairy farms were addressed. • This paper demonstrated the prevalence of high-risk bla genes in dairy cow waste. • Bedding recovery unit effectively reduced the levels of bla genes in dairy manure. • The wastewater treatment systems had poor removal efficiency on bla genes. • Irrigation with wastewater from dairy farms spread high-risk bla genes. This paper first focused on the pollution status of high-risk β-lactamase genes in intensive dairy farms, and tracked their transfers in full-scale dairy cow waste management systems. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus can survive at low temperature which existed a potential risk of food safety. In this paper, the properties of cold-induced small colony variants (SCVs) were investigated including the antibiotic resistance, biofilm formation and virulence. The results confirmed that the SCVs were menadione auxotrophic types with slow growth, reduced membrane potential, increased resistance to aminoglycosides, ampicillin, cefotetan, doxycycline and chloromycetin. Additionally, the biofilm formation of SCVs was enhanced following the up-regulated of icaADBC genes. The biofilms of S. aureus cells can be effectively eliminated by 1% concentration of '84′ disinfection and 3% concentration of hydrogen peroxide. Furthermore, SCVs could revert to a normal phenotype through subculture. And the reversion mutation (R) cells increased expression of virulence factors. The findings in this paper enriched the cataloguing of SCV formation. • The cold-induced SCVs were identified as menadione auxotrophic type. • The SCVs cells enhanced resistance to β-lactam, doxycycline and chloromycetin. • The biofilm formation of SCVs was enhanced following the up-regulated of icaADBC genes. • The reversion mutation cells increased expression of virulence factors. [ABSTRACT FROM AUTHOR]

This paper uses a twin-based approach to examine the extent to which institutional differences in school systems that relate to tracking across German states moderate the role of genes and environment in explaining children's attendance at upper secondary school. The results show moderation effects for two of the three indicators included: teacher recommendations and rigidness of tracking. Contrary to expectations, binding recommendations do not reduce the relevance of environmental influences. Similarly, differences in the timing of tracking do not lead to changes in the relevance of genetic and environmental influences on track attendance. Overall, the results provide little evidence that any of the tracking systems distinguished here for Germany offer significant advantages over others when it comes to providing students with better opportunities to reach their full potential. However, this is true only for the indicators considered here. [ABSTRACT FROM AUTHOR]

Recent evidence shows that mitochondria regulate nuclear transcriptional activity both in normal and cell stress conditions, known as retrograde signaling. Under normal mitochondrial function, retrograde signaling is associated with mitochondrial biogenesis, normal cell phenotype and metabolic profile. In contrast, mitochondrial dysfunction leads to abnormal (oncogenic) cell phenotype and altered bio-energetic profile (nucleus reprogramming). Despite intense research efforts, a concrete mechanism through which mitochondria determine the group of genes expressed by the nucleus is still missing. The present paper proposes a novel hypothesis regarding retrograde signaling. More specifically, it reveals the mitochondrial membrane potential (MMP) and the accompanied strong electromagnetic field (EF) as key regulatory factors of nuclear activity. Mitochondrial emitted EFs extend in long distance and affect the function of nuclear membrane receptors. Depending on their frequencies, EFs can directly activate or deactivate different groups of nuclear receptors and so determine nuclear gene expression. One of the key features of the above hypothesis is that nuclear membrane receptors, besides their own endogenous or chemical ligands (hormones, lipids, etc.), can also be activated by electromagnetic signals. Moreover, normal MMP values (about -140 mV) are associated with the production of high ATP quantities and small levels of reactive oxygen species (ROS) while the hyperpolarization observed in all cancer cell types leads to a dramatic fall in ATP production and an analogous increase in ROS. The diminished ATP and increased ROS production negatively affect the function of all cellular systems including nucleus. Restoration of mitochondrial function, which is characterized by the fluctuation of MMP and EF values within a certain (normal) range, is proposed as a necessary condition for normal nuclear function and cancer therapy. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Lung Cancer is the property of Chinese Journal of Lung Cancer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cleft lip and palate are common congenital anomalies with significant medical, psychological, social, and economic ramifications, affecting one in seven hundred live births. Genetic causes of non syndromic cleft lip and/or palate (NSCLP) include chromosomal rearrangements, genetic susceptibility to teratogenic exposures, and complex genetic contributions of multiple genes. Development of the orofacial clefts in an individual will depend on the interaction of several moderately effecting genes with environmental factors. Several candidate genes have been genotyped in different population types, using case parent trio or case control design; also genes have been sequenced and SNPs have been reported. Quantitative and molecular analysis have shown linkage and association studies to be more relevant. Recent literature search shows genome wide association studies using microarray. The aim of this paper was to review the approaches to identify genes associated with NSCLP and to analyze their differential expressions. Although no major gene has been confirmed, a lot of research is ongoing to provide an understanding of the pathophysiology of the orofacial clefts. [ABSTRACT FROM AUTHOR]

Progress in understanding core pathways of cancer requires analysis of many genes. New insights are hampered due to the lack of tools to make sense of large lists of genes identified using high throughput technology. Data mining, particularly visualisation that finds relationships between genes and the Gene Ontology (GO), can assist in functional understanding. This paper addresses the question using GO annotations for functional understanding of genes. We augment genes with GO terms using two similarity measures: a Hop-based measure and an Information Content based measure, and visualise with Singular Value Decomposition (SVD). The results demonstrate that SVD visualisation of GO augmented genes matches the biological understanding expected in simulated and real-life data. Differences are observed in visualisation of GO terms, where the information content method produces more tightly-packed clusters than the hop-based method. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Lung Cancer is the property of Chinese Journal of Lung Cancer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Avascular necrosis of the head of the femur is a serious event which occurs following any trauma. There is profuse blood loss due to rupture of arteries supplying the head of the femur. There may be possible association of any gene with avascular necrosis of the head of the femur. Design: A short narrative review for genes involved in the avascular necrosis of femur. Methods: A thorough search of literature was done to scrutinize various published papers related to avascular necrosis of head of femur and the genes involved were noted. Results: The retrieved results showed the involvement of various genes in avascular necrosis of the head of the femur. Genes related to Alpha-2 macroglobulin (A2M), basic fibroblast growth factor (bFGF), Sterol regulatory element binding factor, Osteoprotegerin (OPG), Receptor Activator of Nuclear Factor kappa-B (RANK) and RANK ligand (RANKL), Bone morphogenetic proteins, COL2AI mutations and Factor V Leiden were found to influence avascular necrosis of the head of the femur. Conclusion: Knowledge of the genes involved in avascular necrosis of the head of femur may be important for academic and therapeutic purpose. The knowledge of the genes linked to such avascular necrosis could also form the basis of future stem cell treatment. [ABSTRACT FROM AUTHOR]

Genetic commodification relies on methods that treat genes as information. By representing genes as information, scientists produce standardized and stable objects that are easily tradable. In this paper, I argue that a Midwestern plant conservation science institution (MPCSI) challenges genetic commodification through distinct knowledge-making and social practices. In particular, scientists at this institution treat genes not as information, but as contextual and contingent entities. By employing genetic technologies that deemphasize the code metaphor of genes, these scientists make genes unavailable to trade as information. I analyze the socionatural implications of this institution's use of genetic technology in native ecosystem restoration. Drawing from interviews and participant observation, I focus on specific techniques used by the MPCSI's scientists to view genes as embodied relational entities, rather than abstract information. I illustrate how these technologies allow the MPCSI to challenge the epistemologies and methodologies that are crucial to producing genetic commodities. Additionally, I illustrate how the MPCSI serves as a model for plant science institutions to reconceptualize their use of banked plant genetic resources. This model complicates the commodity speculation paradigm common to bioprospectors. At the same time, this genetic restoration approach relies on and produces different engagements with markets. I detail the MPCSI's emerging relationship with commercial seed nurseries to illustrate how decommodification is integral to commodification. Finally, I argue that although the MPCSI's genetic restoration strategy necessitates limited market engagements, their scientific practices and institutional relationships produce drastically different socioecological outcomes compared to institutions that treat genes as information. [ABSTRACT FROM AUTHOR]

The article discusses a research paper examining the effects of yamogenin on the accumulation of triacylglyceride (TG) in hepatocytes. Topics discussed include expression of fatty acid synthesis-related genes, activation of the liver X receptor (LXR) in luciferase ligand assay, and structural difference between yamogenin and diosgenin.

The article discusses a research paper in which the expression of genes related to glucose metabolism during muscle development was investigated. Topics discussed include important roles of Skeletal and cardiac muscle in glucose uptake and utilization, age-dependent increase in gene expression in cardiac muscle, and mitochondrial oxidative-related processes.

Copyright of Chinese Journal of Lung Cancer is the property of Chinese Journal of Lung Cancer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: Sleep is a complex physiological process and still remains one of the great mysteries of science. Over the past 10 y, genetic research has provided a new avenue to address the regulation and function of sleep. Gene loci that contribute quantitatively to sleep characteristics and variability have already been identified. However, up to now, a genetic basis has been established only for a few sleep disorders. Little is yet known about the genetic background of insomnia, one of the most common sleep disorders. According to the conceptualisation of the 3P model of insomnia, predisposing, precipitating and perpetuating factors contribute to the development and maintenance of insomnia. Growing evidence from studies of predisposing factors suggests a certain degree of heritability for insomnia and for a reactivity of sleep patterns to stressful events, explaining the emergence of insomnia in response to stressful life events. While a genetic susceptibility may modulate the impact of stress on the brain, this finding does not provide us with a complete understanding of the capacity of stress to produce long-lasting perturbations of brain and behaviour. Epigenetic gene–environment interactions have been identified just recently and may provide a more complex understanding of the genetic control of sleep and its disorders. It was recently hypothesised that stress-response-related brain plasticity might be epigenetically controlled and, moreover, several epigenetic mechanisms have been assumed to be involved in the regulation of sleep. Hence, it might be postulated that insomnia may be influenced by an epigenetic control process of both sleep mechanisms and stress-response-related gene–environment interactions having an impact on brain plasticity. This paper reviews the evidence for the genetic basis of insomnia and recent theories about epigenetic mechanisms involved in both sleep regulation and brain-stress response, leading to the hypothesis of an involvement of epigenetic mechanisms in the development and maintenance of insomnia. [Copyright &y& Elsevier]