Search

In this paper, the most probable exit path is applied to understand the switching of a bistable synthetic gene network with genetic toggle in Escherichia coli from a new perspective. It is worth mentioning that the most probable exit path is a deterministic indicator for researching stochastic system, and its role is analogous to the phase diagram and time history diagram of deterministic system. Firstly, the large deviation theory proves that when a dynamic system has a stable equilibrium point, the cumulative effect of its long-term action can make its sample trajectory reach another region with a probability of 1 from the attractive region under weak random disturbance. The concept of the most probable exit path is given by defining Freidlin-Wentzell action functional. Moreover, considering the noise intensity, Onsager-Machlup action functional is defined to obtain the most probable exit path of the system subject to random disturbance. Based on the Onsager-Machlup action functional, it can be observed that the impact of two types of noise intensities on the most probable exit path for the transition of the system. In addition, based on vector field decomposition, energy landscape is used to analyze the global stability of the system. Finally, this article intuitively demonstrates the switching process of the system with genetic toggle. The analysis of Onsager-Machlup action functional reveals that two independent noises have opposite effects on the system switching. The increase in the intensity of the second Gaussian noise is conductive to more accurately observing the most probable exit path of the system. According to the energy landscape, the reduction of noise intensity is not conductive to switching of the system with genetic toggle. • Most probable exit path intuitively illustrates the process of stochastic gene regulation. • Most probable exit path is obtained using FW and OM functional respectively by large deviation theory. • Analyze the effects of noise intensity and final time, provide guidance for gene expression cell differentiation process. • Based on vector field decomposition, energy landscape is used for global stability analysis of the system. [ABSTRACT FROM AUTHOR]

Endoplasmic reticulum (ER) stress, a common cellular stress response induced by various factors that interfere with cellular homeostasis, may trigger cell apoptosis. Autophagy is an important and conserved mechanism for eliminating aggregated proteins and maintaining protein stability of cells, which is closely associated with ER stress and ER stress–induced apoptosis. In this paper, we report for the first time that Hhatl, an ER-resident protein, is downregulated in response to ER stress. Hhatl overexpression alleviated ER stress and ER stress induced apoptosis in cells treated with tunicamycin or thapsigargin, whereas Hhatl knockdown exacerbated ER stress and apoptosis. Further study showed that Hhatl attenuates ER stress by promoting autophagic flux. Mechanistically, we found that Hhatl promotes autophagy by associating with autophagic protein LC3 (microtubule-associated protein 1A/1B-light chain 3) via the conserved LC3-interacting region motif. Noticeably, the LC3-interacting region motif was essential for Hhatlregulated promotion of autophagy and reduction of ER stress. These findings demonstrate that Hhatl ameliorates ER stress via autophagy activation by interacting with LC3, thereby alleviating cellular pressure. The study indicates that pharmacological or genetic regulation of Hhatl-autophagy signaling might be potential for mediating ER stress and related diseases. [ABSTRACT FROM AUTHOR]

• A reaction-diffusion system with positive feedback in gene regulation is established. • The long-term dynamics of the system solution is completely analyzed. • The parameter sets of existence and non-existence of nonconstant steady state solution are obtained. • The influence of diffusivity on the region of attraction of equilibrium solution is explained. Developing appropriate spatiotemporal models can help us understand at the molecular level how organisms function, when and where certain genes are expressed, and to what extent. In this paper, we establish a reaction-diffusion model with positive feedback loop in the process of gene expression, which describes the expression of genes according to probability and random diffusion. We focus on the long-term behavior of the system, including the determination of invariant regions and the global stability of equilibria. In particular, in the absence of a globally stable equilibrium, we derive some results on the existence and nonexistence of nonconstant steady state solutions, and clarify the dependence of the existence of nonconstant solutions on the diffusion rate of reactants and the size of the reaction environment. These results contribute to understanding the heterogeneity of cell characterization. We also carry out numerical simulations to support our theoretical results. [ABSTRACT FROM AUTHOR]

Silencers are regulatory DNA elements that reduce transcription from their target promoters; they are the repressive counterparts of enhancers. Although discovered decades ago, and despite evidence of their importance in development and disease, silencers have been much less studied than enhancers. Recently, however, a series of papers have reported systematic studies of silencers in various model systems. Silencers are often bifunctional regulatory elements that can also act as enhancers, depending on cellular context, and are enriched for expression quantitative trait loci (eQTLs) and disease-associated variants. There is not yet evidence of a 'silencer chromatin signature', in the distribution of histone modifications or associated proteins, that is common to all silencers; instead, silencers may fall into various subclasses, acting by distinct (and possibly overlapping) mechanisms. Silencers are less well-studied than enhancers, but a recent spate of papers has begun to systematically explore these repressive regulatory elements. Silencers are important for precise control of gene expression and are enriched for disease-associated regulatory variants. Most newly discovered silencers are bifunctional regulatory elements that also act as enhancers in other contexts. The traditional distinction between enhancers and silencers may be an oversimplification. Silencers appear to act by a variety of mechanisms, and may fall into various functionally distinct subclasses. This complicates the search for a predictive chromatin signature that would enable the rapid identification of silencers from high-throughput data. Understanding silencer function will be key to predicting the regulatory impact of genomic variation. [ABSTRACT FROM AUTHOR]

• Optimizing FOPID controller parameters for the regulation of BP in a hypertensive patient using GA. • Performance indices (IAE, ISE, and ITAE) calculations for three different patient models. • Using Oustaloup continuous integer order approximation for fractional order equations. • Stability and robustness system against parameter variations in the patient model. In this paper, fractional order PID controller [FOPID] is designed for automatic blood pressure regulation. One of the most common problems faced by post-operative patients is abnormal blood pressure (BP). Infusion of sodium nitroprusside (SNP) into the patient reduces blood pressure by relaxing the peripheral vasculature's muscles. The patient's BP must be continuously monitored by an expert and the correct dose has to be given to the patient. It will be difficult to give the desired dosage to a patient manually because drug sensitivity is different for different patients. So, an appropriate controller must be designed to regulate blood pressure and minimize clinical expenses. A fractional-order PID controller is proposed in this paper to regulate mean arterial pressure, and FOPID parameters are optimized as a function of minimizing integral absolute error (IAE), integral squared error (ISE), and integral time absolute error (ITAE) using genetic algorithm. The performance of the proposed system is improved in terms of undershoot, settling time, and maximum peak overshoot. A MATLAB environment was used for the simulation of the system and the implementation of the algorithm. [ABSTRACT FROM AUTHOR]

Reconstructing gene regulatory networks (GRNs) is an important task to reveal the regulatory relationship between genes and understand the mechanism of intracellular gene expression regulation. With the development of single-cell ribonucleic acid sequencing (scRNA-seq) technology, researchers begin to attempt to infer GRN within cells. In this paper, we propose graph attention network with convolutional layer (GATCL) to infer the latent interactions between transcription factors (TFs) and target genes in GRN. Firstly, GATCL uses graph attention network (GAT), which can effectively extract information about genes and TFs. Secondly, we combine multi-head attention layer with one-head attention layer and propose a new method of using convolution instead of weight matrix. Thirdly, we use the exponential linear unit (ELU) activation function to replace the leaky rectified linear unit (LReLU) commonly used in GAT, which further improves the accuracy of GATCL. The AUROC of our method on seven scRNA-seq datasets with four types of ground-truth networks reached an average of 0.827, which is higher than other state-of-the-art models. GATCL applies a supervised deep learning algorithm to solve the problems existing in the inference of GRN from scRNA-seq in the engineering field, and the effectiveness of this method is verified by a large number of experiments. [ABSTRACT FROM AUTHOR]

[Display omitted] Methylation is a vital chemical reaction in the metabolism of many drugs, neurotransmitters, hormones, and exogenous compounds. Among them, S-methylation plays a significant role in the biotransformation of sulfur-containing compounds, particularly chemicals with sulfhydryl groups. Currently, only three S-methyltransferases have been reported: thiopurine methyltransferase (TPMT), thiol methyltransferase (TMT), and thioether methyltransferase (TEMT). These enzymes are involved in various biological processes such as gene regulation, signal transduction, protein repair, tumor progression, and biosynthesis and degradation reactions in animals, plants, and microorganisms. Furthermore, they play pivotal roles in the metabolic pathways of essential drugs and contribute to the advancement of diseases such as tumors. This paper reviews the research progress on relevant structural features, metabolic mechanisms, inhibitor development, and influencing factors (gene polymorphism, S-adenosylmethionine level, race, sex, age, and disease) of S-methyltransferases. We hope that a better comprehension of S-methyltransferases will help to provide a reference for the development of novel strategies for related disorders and improve long-term efficacy. [ABSTRACT FROM AUTHOR]

We published the first paper to characterize GPX2 (aka GSHPx-GI) as a selenoenzyme with glutathione peroxidase activity in 1993. Among the four Se-GPX isozymes, GPX1-4, GPX1 and GPX2 are closely related in terms of structure, substrate specificities, and subcellular localization. What sets them apart are distinct patterns of gene regulation, tissue distribution and response to selenium. While we identified the digestive tract epithelium as the main site of GPX2 expression, later work has shown GPX2 is found more widely in epithelial tissues with concentration of expression in stem cell and proliferative compartments. GPX2 expression is regulated over a wide range of levels by many pathways, including NRF2, WNT, p53, RARE and this often results in attaching undue significance to GPX2 as GPX2 is only a part of a system of hydroperoxidase activities, including GPX1, peroxiredoxins and catalase. These other activities may play equal or greater roles, particularly in cell lines cultured without selenium supplementation and often with very low GPX2 levels. This could be assessed by examining levels of mRNA and protein among these various peroxidases at the outset of studies. As an example, it was found that GPX1 responds to the absence of GPX2 in mouse ileum and colon epithelium with higher expression. As such, both Gpx1 and Gpx2 had to be knocked out in mice to produce ileocolitis. However, we note that the actual role of GPX1 and GPX2 in relation to peroxiredoxin function is unclear. There may be an interdependence that requires only low amounts of GPX1 and/or GPX2 in a supporting role to maintain proper peroxiredoxin function. GPX2 levels may be prognostic for cancer progression in colon, breast, prostate and liver, however, there is no consistent trend for higher or lower levels to be favorable. [Display omitted] • GPX2 was discovered by investigators screening human liver cDNA libraries with GPX1 probes. • GPX2 was characterized as a cytoplasmic selenoprotein with GPX activity like GPX1 and high expression in gastrointestinal tract. A role for GPX2 in the crypt/gland regions of the mid-lower GI was indicated by work with GPX1-knockout mice, GPX2-knockout mice and a combination of the lines. • Generally independent regulation and compartmentalization define semi-independent roles for the GPX2 and GPX1 isoenzymes. There is likely interaction in other tissues. • Recent work has broadened the range of tissues with expression with suggestion of impact on tumororigenesis and metastasis. Much work is reported without adequate context for GPX2 as a component of an array of hydroperoxidases and performed under conditions where GPX2 protein levels may be miniscule due to cell line or inadequate selenium. • Possible dominance by GPX2 in basal cell compartments is indicated and represents a possible future direction for GPX2 research. [ABSTRACT FROM AUTHOR]

Abstract The etiology of hearing loss tends to be multi-factorial and affects a significant proportion of the global population. Despite the differences in etiology, a common physical pathological change that leads to hearing loss is damage to the mechanosensory hair cells of the inner ear. MicroRNAs (miRNAs) have been shown to play a role in inner ear development and thus, may play a role in the development or prevention of hearing loss. In this paper, we review the mechanism of action of miRNAs in the auditory system. We present an overview about the role of miRNAs in inner ear development, summarize the current research on the role of miRNAs in gene regulation, and discuss the effects of both miRNA mutations as well as overexpression. We discuss the crucial role of miRNAs in ensuring normal physiological development of the inner ear. Any deviation from the proper function of miRNA in the cochlea seems to contribute to deleterious damage to the structure of the auditory system and subsequently results in hearing loss. As interest for miRNA research increases, this paper serves as a platform to review current understandings and postulate future avenues for research. A better knowledge about the role of miRNA in the auditory system will help in developing novel treatment modalities for restoring hearing function based on regeneration of damaged inner ear hair cells. Highlights • MicroRNAs (miRNAs) plays a crucial role in inner ear development. • Abnormal function of miRNAs in the auditory system has been associated with hearing loss. • A better knowledge about the miRNA regulated signaling pathways will pave the way for developing novel treatment modalities for hearing loss. [ABSTRACT FROM AUTHOR]

Abstract Identification of significant interactions between genes and chemical compounds/drugs is an important issue in toxicogenomic studies as well as in drug discovery and development. There are some online and offline computational tools for toxicogenomic data analysis to identify the biomarker genes and their regulatory chemical compounds/drugs. However, none of the researchers has considered yet the identification of significant interactions between genes and compounds. Therefore, in this paper, we have discussed two approaches namely moving range chart (MRC) and logistic moving range chart (LMRC) for the identification of significant up-regulatory (UpR) and down-regulatory (DnR) gene-compound interactions as well as toxicogenomic biomarkers and their regulatory chemical compounds/drugs. We have investigated the performance of both MRC and LMRC approaches using simulated datasets. Simulation results show that both approaches perform almost equally in absence of outliers. However, in presence of outliers, the LMRC shows much better performance than the MRC. In case of real life toxicogenomic data analysis, the proposed LMRC approach detected some important down-regulated biomarker genes those were not detected by other approaches. Therefore, in this paper, our proposal is to use LMRC for robust identification of significant interactions between genes and chemical compounds/drugs. [ABSTRACT FROM AUTHOR]

Abstract This paper addresses the problem of establishing the asymptotic stability criteria for genetic regulatory networks with discrete time delays. First, the system model is simplified to a reduced-order system with bounded uncertain parameters and distributed delays by exploiting calculus's properties and Lagrange's mean–value theorem. Second, the relationship between the asymptotic stability of the primal system and the robust asymptotic stability of the reduced-order one is investigated. Third, a new reduced-order approach is proposed to derive a sufficient condition for the robust asymptotic stability of the reduced-order system (i.e., the asymptotic stability of the primal system). At last, a numerical example illustrates the effectiveness of the theoretical results obtained in this paper. [ABSTRACT FROM AUTHOR]

[Display omitted] Despite fluctuations in embryo size within a species, the spatial gene expression pattern and hence the embryonic structure can nonetheless maintain the correct proportion to the embryo size. This is known as the scaling phenomenon. For morphogen-induced patterning of gene expression, the positional information encoded in the local morphogen concentrations is decoded by the downstream genetic network (the decoder). In this paper, we show that the requirement of scaling sets severe constraints on the geometric structure of such a local decoder, which in turn enables deduction of mutants' behavior and extraction of regulation information without going into any molecular details. We demonstrate that the Drosophila gap gene system achieves scaling in the way consistent with our theory—the decoder geometry required by scaling correctly accounts for the observed gap gene expression pattern in nearly all maternal morphogen mutants. Furthermore, the regulation logic and the coding/decoding strategy of the gap gene system can also be revealed from the decoder geometry. Our work provides a general theoretical framework for a large class of problems where scaling output is achieved by non-scaling inputs and a local decoder, as well as a unified understanding of scaling, mutants' behavior, and gene regulation for the Drosophila gap gene system. [ABSTRACT FROM AUTHOR]

[Display omitted] • PTEN gene expression is epigenetically controlled by circular RNAs from transcription to post-translation. • Most regulatory circRNAs exert their function through sponging miRNAs that target PTEN. • CircPTENs directly derived from PTEN mRNA negatively affect cancer progression. • CircPTENs suppress tumors by regulating PTEN function or affecting TGF-β and AKT pathways. Epigenetic regulation of gene expression, without altering the DNA sequence, is involved in many normal cellular growth and division events, as well as diseases such as cancer. Epigenetics is no longer limited to DNA methylation, and histone modification, but regulatory non-coding RNAs (ncRNAs) also play an important role in epigenetics. Circular RNAs (circRNAs), single-stranded RNAs without 3′ and 5′ ends, have recently emerged as a class of ncRNAs that regulate gene expression. CircRNAs regulate phosphatase and tensin homolog (PTEN) expression at various levels of transcription, post-transcription, translation, and post-translation under their own regulation. Given the importance of PTEN as a tumor suppressor in cancer that inhibits one of the most important cancer pathways PI3K/AKT involved in tumor cell proliferation and survival, significant studies have been conducted on the regulatory role of circRNAs in relation to PTEN. These studies will be reviewed in this paper to better understand the function of this protein in cancer and explore new therapeutic approaches. [ABSTRACT FROM AUTHOR]

The Chinese soft-shelled turtle (Pelodiscus sinensis) is a medicine-food homology aquatic product and has a long growth cycle. In this paper, the compound features and its accumulation mechanisms in male P. sinensis muscle from 3 to 6 years of age (M3 to M6) were clarified based on metabolomic and transcriptomic. 261 metabolites identified are meat matrices in P. sinensis. In M3, IMP and GMP were most abundant. Free amino acid, monosaccharides, and highly unsaturated fatty acid (HUFA) accumulation are respectively dominant between sequential ever two groups from M3 to M6 by collagen synthesis genes down-regulated, glycogen synthesis inhibited, and fatty acid highly desaturated enhancement. col1a1 , col1a2 , and col6a2 were identified as arachidic acid-related genes. Overall, nutrients and antioxidants were utmost in oldest ones of 6 years of age, though flavoring substances abundant in M3 and M4, which was inextricably associated with diverse gene regulation in different ages P. sinensis. • Glutathione and anserine are potential active ingredients in male Pelodiscus sinensis. • IMP, GMP, and free animo acid are most in the youth, while DHA, EPA, VB3, and VB5 are utmost in old-ages male individuals. • Protein, saccharides, and unsaturated fatty acids metabolism are characteristic pathways from M3 to M6. • col1a1 , col1a2 , and col6a2 are related to arachidic acid accumulation. [ABSTRACT FROM AUTHOR]

Forward genetic screens are invaluable in describing gene function. CRISPR has reinvigorated phenotypic screens in Toxoplasma – a model apicomplexan parasite. Two recent papers by Smith et al. and Li et al. take the next big leap in performing forward genetic screens in Toxoplasma by combining conditional gene regulation with CRISPR. [ABSTRACT FROM AUTHOR]

Grapes are one of the highly valued non-climacteric fruits that can be consumed fresh or used to produce numerous food products and dietary supplements. Inadvertent fungal infections cause substantial economic and commodity loss in the grape industry. However, control measures have been developed and widely used to combat pathogenic fungal attacks in grapes, most of which are indiscriminate towards the pathogenic fungi. Precise interactions between various pathogenic fungi and grapes have not been fully explored. In the past decade, advanced molecular technics and 'omics' approaches have allowed progress to understand such interactions. Discoveries regarding pathogen entry, optimal conditions for pathogenesis, virulence factors, mycotoxin production, fungal genes involved in pathogenesis, quiescent and necrotrophic lifestyles of pathogenic fungi, and grape fruit's response towards the pathogen attack have been published. This review paper summarizes the possible pathways of fungal pathogenesis in grapes and environmental factors influencing fungal infections. We emphasize the molecular aspects of fungal invasions and the transition between quiescent and necrotrophic lifestyles of grape fungal pathogens and the grape's immune response against pathogen attack and genes involved in the defence mechanism. We pinpoint the recent innovations in control strategies and prospective developments in the field. This review aims to reduce the knowledge gap between the fungal disease progression mechanisms and the development of various disease control strategies in grape production. • Physiological pathogenesis mechanism includes environmental factors and inocula. • Quiescent to necrotrophic transition comprised complex genetic regulation. • Pathogenic fungi reprogram the molecular networks of grape berries. • We emphasized the molecular aspects of the grape's defence response. • Recent progress in grape disease control strategies are discussed. [ABSTRACT FROM AUTHOR]

Gene regulatory networks represent the interactions among genes regulating the activation of specific cell functionalities. They have been successfully modelled using Boolean networks, where a set of Boolean variables model the activation state of each gene, and Boolean functions model positive and negative influences among genes. Moreover, when the effect of such influences is additive, threshold Boolean networks, in which Boolean functions are replaced by simpler threshold functions, turned out to be particularly effective. In this paper we propose a systematic translation of threshold Boolean networks into Ehrenfeucht and Rozenberg's reaction systems. Our translation produces a non redundant set of reactions, each using a minimal set of objects. This translation allows us to simulate the behaviour of a general threshold Boolean network by simply executing the (closed) reaction system we obtain, and to investigate causality relations among genes by applying tools available for reaction systems. We implemented our translation in an open-source tool and applied it in two case studies: the gene regulation network of segment polarity in Drosophila melanogaster and the one controlling the differentiation of Th cells in the immune system. In both case studies, we investigate causalities among genes in the reaction system obtained from the translation by applying a tool for the computation of formula based predictors. In the context of the second case study, we show that also Boolean networks with non-additive influences and modelling genes with multiple expression levels can be dealt with by our approach. [ABSTRACT FROM AUTHOR]

Nuclear receptors (NRs) are a family of transcription factors that are regulated endogenously by small lipophilic ligands. Recently, liquid-liquid phase separation (LLPS) has appeared as a new aspect of NR function. In the human retinoid X receptor γ (h RXRγ), the inherently disordered AB region undergoes LLPS via homotypic multivalent interactions. To better understand the functions of liquid condensates, a clear view of the molecular interactions underlying the LLPS are required. The phase separation propensity of the AB region of h RXRγ (AB_ h RXG) at a high NaCl concentration, a lower critical solution temperature behavior, and also sensitivity to kosmotropic salts and 1,6-hexanediol, which all indicate the importance of hydrophobic interactions in the formation of AB_ h RXG liquid condensates, is presented in the paper. Additionally, molecular crowding agents and TMAO shift the equilibrium, in turn enabling phase transition at lower AB_ h RXG concentrations. Although the LLPS of the proteins can lead to aggregation, AB_ h RXG liquid condensates are not aggregation prone. Interestingly, the formation of AB_ h RXG liquid condensates has an impact on the rest of the receptor, as AB_ h RXG liquid condensates recruit the remaining fragment of h RXRγ into the droplets. The ability of AB_ h RXG to undergo LLPS might be important for gene expression regulation. [ABSTRACT FROM AUTHOR]

Background and objective Classification of gene expression data is the common denominator of various biomedical recognition tasks. However, obtaining class labels for large training samples may be difficult or even impossible in many cases. Therefore, semi-supervised classification techniques are required as semi-supervised classifiers take advantage of unlabeled data. Methods Gene expression data is high-dimensional which gives rise to the phenomena known under the umbrella of the curse of dimensionality , one of its recently explored aspects being the presence of hubs or hubness for short. Therefore, hubness-aware classifiers have been developed recently, such as Naive Hubness-Bayesian k -Nearest Neighbor (NHBNN). In this paper, we propose a semi-supervised extension of NHBNN which follows the self-training schema. As one of the core components of self-training is the certainty score, we propose a new hubness-aware certainty score. Results We performed experiments on publicly available gene expression data. These experiments show that the proposed classifier outperforms its competitors. We investigated the impact of each of the components (classification algorithm, semi-supervised technique, hubness-aware certainty score) separately and showed that each of these components are relevant to the performance of the proposed approach. Conclusions Our results imply that our approach may increase classification accuracy and reduce computational costs (i.e., runtime). Based on the promising results presented in the paper, we envision that hubness-aware techniques will be used in various other biomedical machine learning tasks. In order to accelerate this process, we made an implementation of hubness-aware machine learning techniques publicly available in the PyHubs software package ( http://www.biointelligence.hu/pyhubs ) implemented in Python, one of the most popular programming languages of data science. [ABSTRACT FROM AUTHOR]

Poplar, as a typical woody plant, is an ideal raw material for the production of lignocellulose biofuel. However, the longer life cycle is not conducive to the rapid identification of poplar genes. At present, protoplasts have been used for gene function identification and high-throughput analysis in many model plants. In this paper, a simplified and efficient protoplast isolation and transient expression system of Populus (Populus × xiaohei T. S. Hwang et Liang) is described. Firstly, we proposed an efficient enzyme hydrolysis method for isolating protoplasts from leaves of Populus × xiaohei. Secondly, we optimized the conditions of protoplast transformation mediated by PEG, and established an efficient transient expression system of protoplasts of Populus × xiaohei. Finally, the subcellular localization of three identified Dof transcription factors (PnDof19, PnDof20 and PnDof30) was also observed in the nucleus by using this scheme, which proved that the method was feasible. In general, this efficient method of protoplast isolation and transformation can be used for the study of protein subcellular localization and can be applied to other fields of molecular biology, such as protein interaction, gene activation and so on. The isolation of protoplasts from Populus × xiaohei were carried out by enzymatic digestion. The protoplast culture conditions were optimized to establish a high-efficiency transient expression system. [ABSTRACT FROM AUTHOR]

Protein acetylation modifications play a central and pivotal role in a myriad of biological processes, spanning cellular metabolism, proliferation, differentiation, apoptosis, and beyond, by effectively reshaping protein structure and function. The metabolic state of cells is intricately connected to epigenetic modifications, which in turn influence chromatin status and gene expression patterns. Notably, pathological alterations in protein acetylation modifications are frequently observed in diseases such as metabolic syndrome, cardiovascular disorders, and cancer. Such abnormalities can result in altered protein properties and loss of function, which are closely associated with developing and progressing related diseases. In recent years, the advancement of precision medicine has highlighted the potential value of protein acetylation in disease diagnosis, treatment, and prevention. This review includes provocative and thought-provoking papers outlining recent breakthroughs in acetylation modifications as they relate to cardiovascular disease, mitochondrial metabolic regulation, liver health, neurological health, obesity, diabetes, and cancer. Additionally, it covers the molecular mechanisms and research challenges in understanding the role of acetylation in disease regulation. By summarizing novel targets and prognostic markers for the treatment of related diseases, we aim to contribute to the field. Furthermore, we discuss current hot topics in acetylation research related to health regulation, including N4-acetylcytidine and liquid-liquid phase separation. The primary objective of this review is to provide insights into the functional diversity and underlying mechanisms by which acetylation regulates proteins in disease contexts. [Display omitted] • Enrichment of Nε-acetylation-specific sites is an early clue to disease development. • Non-histone acetylation also emerges as a key 'enforcer' of altered gene regulation. • Chromatin recruits acetylation effectors, crucial for precise gene expression control. • Exploring the key site acetylation elucidates disease-metabolic causal links. [ABSTRACT FROM AUTHOR]

Highlights: [•] The manuscript describes our view on hemocyte subsets, lineages and compartments. [•] The paper details the plasticity of plasmatocyte/macrophage lineages. [•] One of the main points of the paper is the regulation of the cell mediated immunity. [•] Phenotypic and functional changes upon effector cell differentiation are described. [•] The ontogenesis of the hematopoietic compartments is presented. [ABSTRACT FROM AUTHOR]

Abstract: This paper is concerned with the problem of global asymptotical stability for a class of delayed genetic regularity networks (GRNs), where the time delays belong to given intervals and assumed to be time-varying. By choosing an appropriate and novel Lyapunov functional and utilizing M-matrix theory, we derive an M-matrix-based delay-range-dependent sufficient condition under which the class of considered GRNs has unique nonnegative equilibrium point which is globally asymptotically stable. The sufficient condition given here is to check whether a constructed constant matrix is a nonsingular M-matrix. This can be easily done, since there are more than 50 equivalent conditions of nonsingular M-matrix, and hence the stability criterion obtained in this paper is different from existing ones in the form of linear matrix inequality (LMI). Finally, several examples and their simulations are presented to show the effectiveness of the proposed approach. [Copyright &y& Elsevier]

Abstract: MicroRNAs (miRNAs) play important roles in gene regulatory networks. In this paper, we propose a probabilistic topic model to infer regulatory networks of miRNAs and their target mRNAs for specific biological conditions at the post-transcriptional level, so-called functional miRNA–mRNA regulatory modules (FMRMs). The probabilistic model used in this paper can effectively capture the relationship between miRNAs and mRNAs in specific cellular conditions. Furthermore, the proposed method identifies negatively and positively correlated miRNA–mRNA pairs which are associated with epithelial, mesenchymal, and other condition in EMT (epithelial–mesenchymal transition) data set, respectively. Results on EMT data sets show that the inferred FMRMs can potentially construct the biological chain of ‘’ at the post-transcriptional level. [Copyright &y& Elsevier]

Abstract: Since Boolean network is a powerful tool in describing the genetic regulatory networks, accompanying the development of systems biology, the analysis and control of Boolean networks have attracted much attention from biologists, physicists, and systems scientists. From mathematical point of view, the dynamics of a Boolean (control) network is a discrete-time logical dynamic process. This paper surveys a recently developed technique, called the algebraic approach, based on semi-tensor product. The new technique can deal with not only Boolean networks, which allow each node to take two values, but also k-valued networks, which allow each node to take k different values, and mix-valued networks, which allow nodes to take different numbers of values. The paper provides a comprehensive introduction to the new technique, including (1) mathematical background of this new technique – semi-tensor product of matrices and the matrix expression of logic; (2) dynamic models of Boolean networks, and general (multi- or mix-valued) logical networks; (3) the topological structure of Boolean networks and general networks; (4) the basic control problems of Boolean/general control networks, which include the controllability, observability, realization, stability and stabilization, disturbance decoupling, identification and optimization, etc.; (5) some other related applications. [Copyright &y& Elsevier]

Graphical abstract Highlights • RNA editing is an attractive, complementing alternative to gene editing. • Several RNA-guided editases have been engineered all suffering from off-targets. • dCas13-based editases do not seem superior to other solutions. • Certain pitfalls should be avoided during the characterization of new editases. • Genomic integration of editases seem best to obtain specific and efficient editing. The game-changing role of CRISPR/Cas for genome editing draw interest to programmable RNA-guided tools in general. Currently, we see a wave of papers pioneering the CRISPR/Cas system for RNA targeting, and applying them for site-directed RNA editing. Here, we exemplarily compare three recent RNA editing strategies that rely on three distinct RNA targeting mechanisms. We conclude that the CRISPR/Cas system seems not generally superior to other RNA targeting strategies in solving the most pressing problem in the RNA editing field, which is to obtain high efficiency in combination with high specificity. However, once achieved, RNA editing promises to complement or even outcompete DNA editing approaches in therapy, and also in some fields of basic research. [ABSTRACT FROM AUTHOR]

Abstract How complex traits arise within organisms over evolutionary time is an important question that has relevance both to the understanding of biological systems and to the design of bio-inspired computing systems. This paper investigates the process of acquiring complex traits within epiNet, a recurrent connectionist architecture capable of adapting its topology during execution. Inspired by the biological processes of gene regulation and epigenetics, epiNet captures biological organisms' ability to alter their regulatory topologies according to environmental stimulus. By applying epiNet to a series of computational tasks, each requiring a range of complex behaviours to solve, and capturing the evolutionary process in detail, we can show not only how the physical structure of epiNet changed when acquiring complex traits, but also how these changes in physical structure affected its dynamic behaviour. This is facilitated by using a lightweight optimisation method which makes minor iterative changes to the network structure so that when complex traits emerge for the first time, a direct lineage can be observed detailing exactly how they evolved. From this we can build an understanding of how complex traits evolve and which regulatory environments best allow for the emergence of these complex traits, pointing us towards computational models that allow more swift and robust acquisition of complex traits when optimised in an evolutionary computing setting. [ABSTRACT FROM AUTHOR]

Abstract: Identification of transcription factor binding sites is a key task to understand gene regulation mechanism to discover gene networks and functions. Clustering approach is proved to be useful when finding such patterns residing in promoter regions of co-regulated genes. Four clustering algorithms, Self-Organizing Map, K-Means, Fuzzy C-Means and Expectation-Maximization are studied in this paper to discover motifs in datasets extracted from Saccharomyces cerevisiae, Escherichia coli, Droshophila melanogaster and Homo sapiens DNA sequences. Required modifications to clustering algorithms in order to adapt them to motif finding task are presented through the paper. Then, their motif-finding performances are discussed carefully and evaluated against a popular motif-finding method, MEME. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the existence conditions of periodic oscillations in large-scale cyclic gene regulatory networks. Using the Poincaré–Bendixson theorem for cyclic systems, we first show that the local instability of an equilibrium point implies the existence of periodic oscillations. We then derive the graphical and its equivalent analytic criteria for the existence of periodic oscillations based on local instability analysis. These criteria have a remarkable feature that they can be applied systematically to a large-scale cyclic gene regulatory network consisting of any number of genes. The latter part of this paper is devoted to analyze the relation between an equilibrium point and the biochemical parameters. This leads to an analytic existence criterion that explicitly takes the dependence of the equilibrium state on biochemical parameters into account, which is often overlooked in nonlinear system analyses. In particular, the novel physical quantities that are essential for determining the existence of periodic oscillations are obtained based on the rigorous analytic criterion. [Copyright &y& Elsevier]

Abstract: A fundamental problem in systems biology consists of investigating robustness properties of genetic regulatory networks (GRNs) with respect to model uncertainty. This paper addresses this problem for GRNs where the coefficients are rationally affected by polytopic uncertainty, and where the saturation functions are not exactly known. First, it is shown that a condition for ensuring that the GRN has a globally asymptotically stable equilibrium point for all admissible uncertainties can be obtained in terms of a convex optimization problem with linear matrix inequalities (LMIs), hence generalizing existing results that mainly consider only the case of GRNs where the coefficients are linearly affected by the uncertainty and the regulatory functions are in SUM form. Second, the problem of estimating the worst-case convergence rate of the trajectories to the equilibrium point over all admissible uncertainties is considered, and it is shown that a lower bound of this rate can be computed by solving a quasi-convex optimization problem with LMIs. Third, the paper considers the problem of estimating the set of uncertainties for which the GRN has a globally asymptotically stable equilibrium point. This problem is addressed, first, by showing how one can compute estimates with fixed shape by solving a quasi-convex optimization problem with LMIs, and second, by deriving a procedure for computing estimates with variable shape. Numerical examples illustrate the use of the proposed techniques. [Copyright &y& Elsevier]

Abstract: The problem of how the dynamics of the smooth gene networks is related to the simplified dynamics of the Boolean networks is studied. The emphasis is put on the gene regulatory networks with delay. Asymptotic analysis which is applied in the paper goes back to Tikhonov’s theory of singular perturbed differential equations and a modified algorithm of reducing delay equations to ordinary differential equations. A number of illustrative examples complements the theory which is offered in the paper. [Copyright &y& Elsevier]

Abstract: Dynamical modeling has proven useful for understanding how complex biological processes emerge from the many components and interactions composing genetic regulatory networks (GRNs). However, the development of models is hampered by large uncertainties in both the network structure and parameter values. To remedy this problem, the models are usually developed through an iterative process based on numerous simulations, confronting model predictions with experimental data and refining the model structure and/or parameter values to repair the inconsistencies. In this paper, we propose an alternative to this generate-and-test approach. We present a four-step method for the systematic construction and analysis of discrete models of GRNs by means of a declarative approach. Instead of instantiating the models as in classical modeling approaches, the biological knowledge on the network structure and its dynamics is formulated in the form of constraints. The compatibility of the network structure with the constraints is queried and in case of inconsistencies, some constraints are relaxed. Common properties of the consistent models are then analyzed by means of dedicated languages. Two such languages are introduced in the paper. Removing questionable constraints or adding interesting ones allows to further analyze the models. This approach allows to identify the best experiments to be carried out, in order to discriminate sets of consistent models and refine our knowledge on the system functioning. We test the feasibility of our approach, by applying it to the re-examination of a model describing the nutritional stress response in the bacterium Escherichia coli. [Copyright &y& Elsevier]

Abstract: In this paper we propose to use association rules to mine the association relationships among different genes under the same experimental conditions. These kinds of relations may also exist across many different experiments with various experimental conditions. In this paper, a new approach, called FIS-tree mining, is proposed for mining the microarray data. Our approach uses two new data structures, BSC-tree and FIS-tree, and a data partition format for gene expression level data. Based on these two new data structures it is possible to mine the association rules efficiently and quickly from the gene expression database. Our algorithm was tested using the two real-life gene expression databases available at Stanford University and Harvard Medical School and was shown to perform better than the two existing algorithms, Apriori and FP-Growth. [Copyright &y& Elsevier]

Molecular biology techniques like gene editing have altered the specific genes in micro-organisms to increase their efficiency to produce biofuels. This review paper investigates the outcomes of Clustered regularly interspaced short palindromic repeats (CRISPR) for gene editing in extremophilic micro-organisms to produce biofuel. Commercial production of biofuel from lignocellulosic waste is limited due to various constraints. A potential strategy to enhance the capability of extremophiles to produce biofuel is gene-editing via CRISPR-Cas technology. The efficiency of intracellular enzymes like cellulase, hemicellulose in extremophilic bacteria, fungi and microalgae has been increased by alteration of genes associated with enzymatic activity and thermotolerance. extremophilic microbes like Thermococcus kodakarensis, Thermotoga maritima, Thermus thermophilus, Pyrococcus furiosus and Sulfolobus sp. are explored for biofuel production. The conversion of lignocellulosic biomass into biofuels involves pretreatment, hydrolysis and fermentation. The challenges like off-target effect associated with use of extremophiles for biofuel production is also addressed. The appropriate regulations are required to maximize effectiveness while minimizing off-target cleavage, as well as the total biosafety of this technique. The latest discovery of the CRISPR-Cas system should provide a new channel in the creation of microbial biorefineries through site- specific gene editing that might boost the generation of biofuels from extremophiles. Overall, this review study highlights the potential for genome editing methods to improve the potential of extremophiles to produce biofuel, opening the door to more effective and environmentally friendly biofuel production methods. [ABSTRACT FROM AUTHOR]

Jasmine oil is used as an antispasmodic, aphrodisiac, antibacterial, and wound-healing agent in traditional medicine. Based on existing studies, phytochemical analyses of the plant's extracts and pharmacologic activities of its bioactive substances are explored to better understand its therapeutic potential. Our research looked at trends in the literature written between 1960 and 2022 on the genus Jasminum using the bibliometric method. The study's main aim is to highlight and assess information on the work done on different aspects of the genus Jasminum. Literature was analysed and represented using bibliometric analysis; programme R and the bibliometrix codes were used to conduct a descriptive bibliometric analysis and generate a matrix including all of the documents. Our final data set consisted of 244 publications with 1 194 author-defined keywords published between 1960 and 2022. The present work highlights the focus of the literature on the genus Jasminum. India's independent papers account for the second-largest percentage of all publications. Besides, phytochemical studies have been extensively utilised for conducting pharmacologic studies and phytotherapy. In the current scenario, research on Jasminum and its gene expression regulation has gained a lot of traction. This publication provides an overview of the work done on various aspects of the genus Jasminum to aid scientific studies in this area. Furthermore, the analysis may be of benefit to various workers in this field. [ABSTRACT FROM AUTHOR]

This paper introduces a mathematical framework for modelling genome expression and regulation. Starting with a philosophical foundation, causation is identified as the principle of explanation of change in the realm of matter. Causation is, therefore, a relationship, not between components, but between changes of states of a system. We subsequently view genome expression (formerly known as ‘gene expression’) as a dynamic process and model aspects of it as dynamic systems using methodologies developed within the areas of systems and control theory. We begin with the possibly most abstract but general formulation in the setting of category theory. The class of models realised are state-space models, input–output models, autoregressive models or automata. We find that a number of proposed ‘gene network’ models are, therefore, included in the framework presented here. The conceptual framework that integrates all of these models defines a dynamic system as a family of expression profiles. It becomes apparent that the concept of a ‘gene’ is less appropriate when considering mathematical models of genome expression and regulation. The main claim of this paper is that we should treat (model) the organisation and regulation of genetic pathways as what they are: dynamic systems. Microarray technology allows us to generate large sets of time series data and is, therefore, discussed with regard to its use in mathematical modelling of gene expression and regulation. [Copyright &y& Elsevier]

Abstract Maintenance of genome integrity under the stressed condition is paramount for normal functioning of cells in the multicellular organisms. Cells are programmed to protect their genome through specialized adaptive mechanisms which will help decide their fate under stressed conditions. These mechanisms are the outcome of activation of the intricate circuitries that are regulated by the p53 master protein. In this paper, we provided a comprehensive review on p53, p53 homologues and their isoforms, including a description about the ubiquitin-proteasome system emphasizing its role in p53 regulation. p53 induced E3(Ub)-ligases are an integral part of the ubiquitin-proteasome system. This review outlines the roles of important E3(Ub)-ligases and their splice variants in maintaining cellular p53 protein homeostasis. It also covers up-to-date and relevant information on small molecule Mdm2 inhibitors originated from different organizations. The review ends with a discussion on future prospects and investigation directives for the development of next-generation modulators as p53 therapeutics. Graphical abstract Image 1 Highlights • The p53 transcription factor is a powerful tumor suppressor protein. • The roles of p53 and its homologs, as well as their splice variants, have been thoroughly discussed. • Regulation of p53 functions and its overall turnover by the upstream and downstream regulatory circuits has been outlined. • Reviewed p53 inducing E3 (Ub)-ligases and their splice variants which take part in the tumorigenesis. • An overview on development and optimization of small molecule inhibitors of Mdm2 discovered to date has been outlined. [ABSTRACT FROM AUTHOR]

Lung cancer, the leading cause of cancer deaths worldwide, is characterized with malignant cell growth. Advances in next-generation sequencing has helped us further understand RNA and identify novel circular RNAs (circRNAs) that may be useful in the early diagnosis and treatment of lung cancer. Similar to other noncoding RNAs, circRNAs present diverse biological functions in normal and disease states, including various types of cancers. This review focuses mainly on the poorly understood functions of circRNA in lung cancer. This paper also summarizes the recent advances in circRNA biogenesis, analyzes the role of circRNAs in cancers, and discusses the potential mechanisms of circRNAs in lung cancer. [ABSTRACT FROM AUTHOR]

In this paper, a label boundary node algorithm (LBN) based on boundary nodes and label propagation is proposed. The algorithm reduces the update randomness in label propagation, which leads to the lack of stability in a community network. A core node can be found by traversing every node and calculating their values. Then, label propagation begins using the label to identify boundary nodes, so that the community division can be realized by giving weight to boundary nodes and deleting those boundary nodes by comparing their values. Finally, typical test data from the British college student clubs network dataset and the American university football game dataset are acquired. We also conducted an experimental comparison on the algorithm between the LBN and a label propagation algorithm (LPA). The comparison result demonstrates that the proposed algorithm is efficient, and that community division becomes more stable when the LBN algorithm maintains the original time efficiency. [ABSTRACT FROM AUTHOR]

In this paper we introduce a new likelihood ratio method for evaluating mixed Y-STR profiles that is based on the premise that, given a haplotype has been seen in the person of interest, the most likely source of a second haplotype, matching at all or most loci, is in an individual with a recent common ancestor. We have called the new method the “Haplotype centred” (HC) method for likelihood ratio derivation. For single source, unambiguous haplotypes the HC method performs identically with the Kappa method proposed by Brenner. When attention is turned to mixtures we are required to assign a probability to many haplotypes seen neither in the database nor any person typed in the case. We derive a likelihood ratio formula in a way that allows a locus by locus approach. We demonstrate the application of the HC method on a series of Y-STR mixtures, originating from two to four individuals, in a manner that is still calculated locus-by-locus in nature. [ABSTRACT FROM AUTHOR]

Purpose The heavy subunit of the iron storage protein ferritin (FHC) is essential for the intracellular iron metabolism and, at the same time, it represents a central hub of iron-independent pathways, such as cell proliferation, angiogenesis, p53 regulation, chemokine signalling, stem cell expansion, miRNAs expression. In this work we have explored the ability of FHC to modulate gene expression in K562 cells, through the up-regulation of the lncRNA H19 and its cognate miR-675. Materials and methods Targeted silencing of FHC was performed by lentiviral-driven shRNA strategy. FHC reconstitution was obtained by full length FHC cDNA transfection with Lipofectamine 2000. ROS amounts were determined with the redox-sensitive probe H2DCFDA. H19, miR-675, miR-107, Twist1, ID3, EPHB6, GNS, ANK1 and SMAD6 mRNA amounts were quantified by Taqman assay and qPCR analysis. Results FHC silencing in K562 cells modulates gene expression through the up-regulation of the lncRNA H19 and its cognate miR-675. Experimental findings demonstrate that the molecular mechanism underlying this phenomenon is represented by an FHC knock-down-triggered increase in reactive oxygen species (ROS) production. Conclusions In this paper we uncover a so far not described function of the ferritin heavy subunit in the control of lncRNA pathways. [ABSTRACT FROM AUTHOR]

This paper investigates the use of the hierarchical mixture of linear regressions (HMLR) and variational inference for multivariate spectroscopic calibration. The performance of HMLR is compared to the classical methods: partial least squares regression (PLSR), and PLS embedded locally weighted regression (LWR) on three different NIR datasets, including a publicly accessible one. In these tests, HMLR outperformed the other two benchmark methods. Compared to LWR, HMLR is parametric, which makes it interpretable and easy to use. In addition, HMLR provides a novel calibration scheme to build a two-tier PLS regression model automatically. This is especially useful when the investigated constituent covers a large range. [ABSTRACT FROM AUTHOR]

This paper is concerned with the stochastic stabilization for genetic regulatory networks. Based on the Lyapunov stability theory in combination with certain convex algorithm, we obtain the sufficient condition under which the unstable genetic regulatory network can be stabilized by using Brownian motion. Finally, a numerical illustrative example is provided to show the effectiveness and correctness of the proposed method. [ABSTRACT FROM AUTHOR]

In recent years, breakthroughs in bioinformatics have been made with the discovery of many functionally significant non-coding RNAs (ncRNAs). The discovery of these ncRNAs has further demonstrated the multi-level characteristics of intracellular gene expression regulation, which plays an important role in assisting diagnosis, guiding clinical drug use and determining prognosis in the treatment process of various diseases. microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) are the three major types of ncRNAs that interact with each other. Studies have shown that lncRNAs and circRNAs can sponge miRNAs, thereby influencing normal physiological processes and regulating mRNA expression and, thus, the physiological state of cells. This paper summarizes the mechanism of action and research progress of the three ncRNA and seven types of modalities. This summary is intended to provide new ideas for diagnosing and treating diseases and researching and developing new drugs. [Display omitted] [ABSTRACT FROM AUTHOR]

In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors’ discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results. [ABSTRACT FROM AUTHOR]