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Gene expression responses of paper birch (Betula papyrifera) leaves to elevated concentrations of CO2 and O3 were studied with microarray analyses from three time points during the summer of 2004 at Aspen FACE. Microarray data were analyzed with clustering techniques, self-organizing maps, K-means clustering and Sammon''s mappings, to detect similar gene expression patterns within sampling times and treatments. Most of the alterations in gene expression were caused by O3, alone or in combination with CO2. O3 induced defensive reactions to oxidative stress and earlier leaf senescence, seen as decreased expression of photosynthesis- and carbon fixation-related genes, and increased expression of senescence-associated genes. The effects of elevated CO2 reflected surplus of carbon that was directed to synthesis of secondary compounds. The combined CO2 +O3 treatment resulted in differential gene expression than with individual gas treatments or in changes similar to O3 treatment, indicating that CO2 cannot totally alleviate the harmful effects of O3. [Copyright &y& Elsevier]

Abstract: Dried blood spot samples (DBSS) on filter paper offer several advantages compared to conventional serum/plasma samples: they do not require any phlebotomy or separation of blood by centrifugation; they are less invasive; they allow sample stability and shipment at room temperature; and they pose a negligible risk of infection with blood-borne viruses, such as HIV, HBV and HCV, to those who handle them. Therefore dried blood spot samples (DBSS) on filter paper can be a quick, convenient and inexpensive means of obtaining blood samples for biomarker discovery, disease screening, diagnosis and treatment monitoring in non-hospitalized, public health settings. In this study, we investigated for the first time the potential application of dried blood spot samples (DBSS) in protein expression profiling using antibody array technology. First, optimal conditions for array assay performance using dried blood spot samples (DBSS) was established, including sample elution buffer, elution time, elution temperature and assay blocking buffer. Second, we analyzed dried blood spot samples (DBSS) using three distinct antibody array platforms, including sandwich-based antibody arrays, quantitative antibody arrays and biotin-label-based antibody arrays. In comparison with paired serum samples, detection of circulating proteins in dried blood spot samples (DBSS) correlated well for both low- and high-abundance proteins on all three antibody array platforms. In conclusion, our study strongly indicates the novel application of multiplex antibody array platforms to analyze dried blood spot samples (DBSS) on filter paper represents a viable, cost-effective method for protein profiling, biomarker discovery and disease screening in a large, population-based survey. [Copyright &y& Elsevier]

Abstract: The toxicity of pulp and paper mill effluents (PPMEs) has been greatly decreased, yet some continue to negatively affect fish reproduction. We hypothesized that PPMEs are affecting the brain resulting in decreased reproductive performance. Our goal was to use gene expression profiling to test the hypothesis that PPMEs are having an effect on neural systems in the fathead minnow (FHM; Pimephales promelas) in vivo. Sexually mature male and female FHM were exposed to 100% final biotreated PPMEs from 5 different sources for 5 days. Using an oligo-array (15K genes) we examined the effect of PPMEs on gene expression in the hypothalamus of female fish. We validated selected genes (cholecystokinin, RevErbβ2, and urotensin I) that were identified by microarray analysis using real-time reverse-transcriptase polymerase chain reaction (RT-PCR). We compared the FHM microarray dataset to multiple microarray datasets from experiments conducted with goldfish injected with different dopaminergic pharmaceuticals to examine whether PPMEs could be affecting the dopamine system. Exposure of FHM to PPMEs resulted in varying degrees of spawning inhibition. Microarray analysis revealed surprisingly few genes in the brain that were commonly affected by the different PPMEs. Real-time RT-PCR confirmed the changes in expression for cholecystokinin, RevErbβ2, and urotensin I. Comparison of the FHM and goldfish microarray datasets suggest that some PPMEs may be acting on the dopamine system. We show that PPMEs are neuroactive in fish and may be acting through some of the pathways in a manner similar to dopamine. [ABSTRACT FROM AUTHOR]

Abstract: This study investigates the predictive ability of gene-expression programming (GEP) in the estimation of methane yield (Y m ) and effluent substrate (S e ) produced by two anaerobic filters. The modeling study was carried out using the data obtained from two upflow anaerobic filters – one mesophilic (35°C) and one thermophilic (55°C) – operated for the treatment of paper-mill wastewater under varying organic loadings. The GEP model was composed of three inputs, hydraulic retention time (T hr ), organic loading rate (R ol ), and influent substrate (S i ), and one output, either S e or Y m . The Stover–Kincannon model was also used for data analysis and to evaluate the prediction ability. Three statistical criteria, root mean square error (RMSE), determination coefficient (R 2), and Akaike''s information criteria (AIC), were the means used for comparison. The results showed that the GEP approach predicted the performance of both anaerobic filters much better than the Stover–Kincannon model. [Copyright &y& Elsevier]

Pathotyping and subtyping of influenza A virus were performed with a packaged paper fluidic-based analytical microdevice (PFAM) after one-step reverse transcription-polymerase chain reaction (RT-PCR). The PFAM contains two test lines: one for detecting M gene to identify the influenza A virus and another for haemagglutinin subtyping to determine the viral strain among H1N1, H3N2, and H5N1. The M gene and the haemagglutinin gene (H1, H3, and H5 genes) were amplified by using the Digoxigenin and the Texas Red modified primers, respectively, in the multiplex RT-PCR. The amplicon products were loaded in the conjugate pad of the PFAM in which the streptavidin coated gold nanoparticles were linked with the biotin moieties that were incorporated in the middle of the DNA strands, and then captured by the anti-Digoxigenin and anti-Texas Red immobilized on the test lines. Influenza A H1N1, H3N2, and H5N1 could be identified with a limit of detection of 102 copies of RNA templates in 10min. Pathotyping and subtyping of the clinical nasopharyngeal swab samples were also analyzed whose results were confirmed by real-time RT-PCR. [ABSTRACT FROM AUTHOR]

Abstract: The presence of unidentified estrogens and androgens in effluents from pulp and paper mills is well documented. However, their role in effluent effects on fish reproduction remains unclear. The objective of this study was to investigate the hypothesis that reproductive impacts of a modern pulp mill effluent are mediated by androgens and/or estrogens in the effluent. Male and female threespine stickleback were exposed to biologically treated Canadian bleached kraft mill effluent under flow-through conditions in the laboratory at 0, 1, 10 and 100% (v/v) dilutions. After 7 and 21 d of exposure, steroidogenesis was assessed using in vitro incubations of gonadal tissue in both males and females. mRNA expression of the estrogen-regulated gene vitellogenin, and the androgen-responsive gene spiggin were assessed using quantitative RT-PCR in the livers of male and posterior kidneys of female stickleback, respectively. Hepatic 7-ethoxyresorufin-O-deethylase (EROD) activity was assessed in both sexes. Effluent extracts were examined for estrogenic and androgenic bioactivity using receptor binding bioassays, and were screened for pulp and paper related extractives and steroidal androgens using GC–MS. This effluent up-regulated spiggin mRNA in the kidney of female stickleback at 10% and 100% (v/v) effluent at 21 d, but not at 7 d of exposure. This change at the mRNA expression of the gene was associated with an increase in cell height in kidney proximal tubule epithelial cells at 100% effluent after both 7 and 21 d. Liver vitellogenin mRNA in male stickleback was not induced at either 7 or 21 d. EROD was induced at 10 and 100% after 21 d of exposure in both sexes, but not after 7 d of exposure. Despite evidence of exposure to androgens, there was no reduction in steroidogenic capacity at any effluent dilution. Effluent extracts were capable of eliciting the displacement of androgens and estrogens from receptors, but androgenic potency was 4-fold greater. A screen of more than 30 androgenic androstane steroids showed no detections. Hence, the androgenic constituents in this particular effluent remain unknown. [Copyright &y& Elsevier]

Abstract: A xylanase gene (xynG1-1) from Paenibacillus campinasensis G1-1 was expressed in Bacillus megaterium MS941 and a high level of extracellular xylansae activity (304.26IU/mL) was achieved after induction with 0.5% xylose. The purified recombinant xylanase (XynG1-1R) revealed optimal activity at 60°C and pH 7.0 and retained 79% and 81% activity after incubation without substrate at 60°C, pH 5.0 and pH 8.0 for 3h, respectively. Application of XynG1-1R (15IU/g pulp) to cotton stalk pulp bleaching increased brightness by 3.65% over that of the control without the xylanase and reduced the need for chlorine compounds by 50% without loss of brightness and pulp fiber qualities. When XynG1-1R (80IU/g paper sludge) was used in combination with mixed cellulolytic enzymes, the saccharification efficiency of recycled paper sludge was increased by 10%. These results indicated that XynG1-1R is a promising candidate for various industrial applications such as biobleaching and bioenergy conversion. [Copyright &y& Elsevier]

Abstract: We evaluated plasma testosterone (T) and 17β-estradiol (E2) levels and ovarian aromatase CYP19a gene expression following a single intraperitoneal injection of Chilean pulp and paper mill effluent extracts into juvenile triploid rainbow trout. Fish injected with untreated effluent extracts had increased plasma T after 4 days, while plasma E2 concentration was increased in fish injected with both primary and secondary treated effluent extracts at the same sampling period. Ovarian CYP19a gene expression as measured by qRT-PCR was significantly induced in fish injected with the untreated, primary and secondary treated pulp and paper mill effluent extracts. Similar induction of CYP19a expression was found in fish injected with the androgens androstenedione (ADD) and T. A Principal Component Analysis (PCA) was conducted in order to identify structure in relationships between all measured variables and identifying which factors were most responsible for the variance observed within the plasma steroid levels, upregulation of ovarian CYP19a gene expression and the final estrogenic effect of increased plasma VTG levels. This analysis indicated a cluster correlation between plasma T levels and CYP19a gene expression (Factor 1, explaining 27.2% of total variance), a cluster including condition factor and liver somatic index (Factor 2, explaining 17.3%) and an additional cluster including plasma E2 and vitellogenin levels (Factor 3, explaining an additional 15.8%). The present results indicate that Chilean pulp and paper mill effluent extracts cause estrogenic effects in triploid rainbow trout. These effects could be related to the compounds present in the effluent that act as estrogen receptor agonists, or that induce changes leading to increased amounts of endogenous estrogens, reflected by increased E2 levels and induced aromatase expression/activity. [Copyright &y& Elsevier]

Effluents from pulp and paper mills that historically have used elemental chlorine in the bleaching process have been implicated in inhibiting reproduction in fish. Compounds with estrogenic and androgenic binding affinities have been found in these effluents, suggesting that the impairment of reproduction is through an endocrine-related mode of action. To date, a great deal of attention has been paid to phytoestrogens and resin acids that are present in mill process streams as a result of pulping trees. Estrogen and estrogen mimics interact directly with the estrogen receptor and have near immediate effects on gene transcription by turning on the expression of a unique set of genes. Using differential display (DD) RT-PCR, we examined changes in gene expression induced by exposure to paper mill effluents. Largemouth bass were exposed to 0, 10, 20, 40, and 80% paper mill effluent concentrations in large flow-through tanks for varied periods of time including 7, 28 or 56 days. Plasma hormone levels in males and females and plasma vitellogenin (Vtg) in females decreased with dose and time. Measurements of changes in gene expression using DD RT-PCR suggest that the gene expression patterns of male fish do not change much with exposure, except for the induction of a few genes including CYP 1A, a protein that is induced through the action of the Ah receptor in response to dioxin and similar polyaromatic hydrocarbons. However, in the case of females, exposure to these effluents resulted in an up-regulation of CYP 1A that was accompanied by a generalized down-regulation of genes normally expressed during the reproductive season. These antiestrogenic changes are in agreement with previous studies in bass exposed to these effluents, and could result in decreased reproductive success in affected populations. [Copyright &y& Elsevier]

Abstract: To improve the β-glucosidase yield and total cellulase activity of Trichoderma reesei, extracellular β-glucosidase (BGLI) was overexpressed under the control of the modified four-copy cbh1 promoter. Three transformants B2, B12 and B15 with successful integration of the bgl1 gene expression cassette were obtained, which exhibited 3.7-, 2.0- and 1.8-fold increase in β-glucosidase activity than the parental strain RUT C30, respectively. The filter paper activities of the productive transformants B12 and B15 were improved by up to 130% and 55%, respectively. Saccharification of corncob residue with the crude enzyme dosages showed that the reducing sugar yields of B12 (5.59mg/ml) and B15 (4.80mg/ml) were 29% and 11% higher than that of RUT C30 (4.34mg/ml), respectively. The present results proved that the modified four-copy cbh1 promoter was a useful tool for improving the cellulase activity of T. reesei, and the engineering strains developed in this study could be potentially used as promising cell factories for β-glucosidase or cellulase production. [ABSTRACT FROM AUTHOR]

• Different cultivars exhibited different sensitivity to light. • Different phenolics showed different sensitivity to light. • Bagging inhibited the synthesis of most phenolics in peach fruit. • Bagging suppressed the expression of most structural genes and transcription factors. • PpHY5 homolog PpHYH was induced by high light. Bagging is a vital cultivation measure for producing high-quality peach fruit, which affects the appearance and internal quality of the fruit by mainly intervening in its exposure to light. However, it is not entirely clear whether bagging affects the content of phenolic compounds or which compounds are most sensitive to bagging treatment, and the regulatory role of bagging on phenolic synthetic-related genes is also unknown. In this experiment, four peach cultivars, 'BJ', 'XH', 'RG', and 'HYT', were bagged with four different types of bags at 50 days after full bloom, with no bag as control, and all fruits were harvested at the commercial maturation stage. The study found that bagged fruits had higher L*, b*, and h° values but lower a* and C* values than non-bagged fruits. Different cultivars and different phenolics exhibited different sensitivities to bagging treatments. Light intensity not only played a decisive role in the accumulation of anthocyanins in peach fruit but also had a strong and widespread impact on other phenolic substances. Overall, light not onlly significantly promoted the accumulation of cyanidin 3-glucoside, cyanidin 3-rutinoside, epicatechin, and rutin but also increased the accumulation of catechin, chlorogenic acid, and neochlorogenic acid to some extent, while shading by bagging inhibited the accumulation of these phenolics. Correspondingly, high light induced the upregulation of most structural genes and transcription factors, including PpPAL1, PpC3H1, PpC3H2, PpDFR, PpLDOX, PpUFGT, and PpMYB10.1 , while low light inhibited the expression of these genes in the four varieties. In addition, PpHY5 homolog PpHYH was induced by high light, which might participate in the biosynthesis of the light-regulated phenolic in peach fruit. This study lays the foundation for further analysis of the regulation mechanism of light on the synthesis of phenolic compounds in peach fruit. [ABSTRACT FROM AUTHOR]

A recent article in Gene highlighted potential function of miR-346 in human breast cancer (Yang et al., 2017). We request an explanation or correction of the report. In its current state, the text will certainly create confusion in the field and lead to incorrect assumptions. The authors made several critical errors. The abstract stated “we found that the expression of miR-346 was higher in breast cancer tissues than in their paired corresponding non-cancerous tissues” and the main text and legend for Fig. 1A stated “miR-346 expression was significantly higher in breast cancer tissues than in their paired corresponding non-cancerous tissues (Fig. 1A, Yang et al., 2017)” and “miR-346 was upregulated in breast cancer tissues and cell lines. (A)”, respectively. It was also stated that “SRCIN1 expression levels were significantly down-regulated in breast cancer compared to the adjacent normal tissues (Fig. 5B, Yang et al., 2017)”. The problem with these statements is that they contradict the actual data presented in the paper! This misrepresentation of the effects of miR-346 in breast cancer could prove harmful by sidetracking future research. Further, clinical trials may be incorrectly directed towards lowering miR-346 without a complete and fair assessment of the internal contradictions in the data. Inaccurately-presented data impede progress of biomedical research, deplete scientific resources and compromise public trust. [ABSTRACT FROM AUTHOR]

• Inheritance of organisms is introduced into innovation design. • Computer digital coding technology is introduced into intelligent innovative design process. • Histogram similarity algorithm intelligently identifies functional genes. The inheritance and variation of functional knowledge is an important way to achieve product innovation. Analogous biological genetic inheritance can solve the problems with the inheritance and variation of functional knowledge. However, the different expressions of functional knowledge in different domains lead designers to consuming a lot of time for functional knowledge characterization and identification, which reduces the efficiency of functional knowledge application. Therefore, in order to solve the problem of inefficient application of functional knowledge in the genetic process caused by irregular expression of functional knowledge, the paper proposes a digital characterization and identification process model of functional genes for product intelligent innovative design. The process model enables product intelligent innovative design through digital characterization of functional genes and rapid identification of functional genes using computer assistance. The process model consists of four following steps. First, extract functional knowledge from patents and perform preliminary functional gene characterization. Second, characterize functional genes digitally by using computerized digital coding techniques. Third, identify the required functional genes by using image similarity matching algorithm. It assists designers to quickly identify the functional genes required for the target system. Fourth, obtain the target product design scheme. By "transcribing" and "translating" the required functional genes and using TRIZ tools to solve the translated scheme, the product innovative design scheme is finally obtained. The feasibility and effectiveness of the model are verified by the intelligent innovative design of shared bicycle parking management device. [ABSTRACT FROM AUTHOR]

The mechanisms modulated by periodontal pathogens in atherosclerosis are not fully understood. Aim: to perform an integrative analysis of gene and protein expression modulated by periodontal pathogens in cells and animal models for atherosclerosis. Cochrane, PRISMA and AMSTAR2 guidelines for systematic reviews were followed. Data search was conducted in Pub-med, LILACS and Science Direct databases. Gene and protein expression data were collected from the included papers to perform an overrepresentation analysis using the Reactome Pathway Analysis tool and the KEGG database. Thirty-two papers were included in the review, they analyzed the effect of Fusobacterium nucleatum , Porphyromonas gingivalis , Streptococcus anginosus , Streptococcus sanguinis , Tannerella forsythia , and Treponema denticola or/and their virulent factors on gene and protein expression in human cells and animal models of atherosclerosis. Some of the modulated pathways include the immune system, programmed cell death, cellular responses to external stimuli, transport of small molecules, and signal transduction (p < 0.05). Those pathways are known to be involved in different stages of atherosclerosis progression. Based on the performed analysis, it is possible to state that periodontal pathogens have the potential to be a contributing factor for atherosclerosis even in absence of a high-fat diet or high shear stress. [ABSTRACT FROM AUTHOR]

To achieve the high-level stable expression of chlorothalonil hydrolytic dehalogenase (Chd), the gene chd was first integrated into the chromosome of Bacillus subtilis WB800. High generation stability was achieved by almost no gene lost after six generations but Chd activity decreased. aprE promoter alteration, translation initiation region modification and multi-copy chromosome integration were studied and these modifications could increase Chd activity by 270%, 2304% and 25%. Chlorothalonil residual exhibited inhibition on bioconversion of lignocellulosic biomass. The addition of Chd crude enzyme (60 μL per g wheat straw) could increase glucose production by 36.10% and 39.65% in synergistic hydrolysis and separate hydrolysis by laccase and cellulase with 120 mg/L residual chlorothalonil. Filter paper activity and carboxymethyl cellulase activity were enhanced by 12.84% and 23.95%, and biomass of Trichoderma reesei was increased by 76.67% under 50 μg chlorothalonil/g dry straw in solid-state fermentation. Thus, the high-level stable expressed Chd effectively eliminated chlorothalonil inhibition on enzymatic hydrolysis and solid-state fermentation. It showed promising potential for bioremediation of chlorothalonil pollution and improving conversion efficiency of lignocellulose. [ABSTRACT FROM AUTHOR]

The applications of clustering in biomedical is pervasive and ubiquitous. A typical example is gene expression data analysis, where clustering is emerging as a powerful solution for uncovering cancer-related insights. Neutrosophic c -means (NCM) clustering has advantages over other conventional clustering methods in characterizing the uncertainty and imprecision caused by cluster overlap and identifying outliers. Nonetheless, NCM and its derivatives equally treat the contribution of each attribute to the cluster. In biomedical applications, genes (i.e. attributes) should take different importance in identifying different clusters. In this paper, we first propose a self-adaptive attribute-weighted neutrosophic c -means (AWNCM) clustering method to overcome the above defects. Moreover, a new objective function is designed to obtain optimal neutrosophic partition, cluster centers and attribute weights. Since AWNCM tends to be more effective against spherical data, we further develop a kernelized version of AWNCM, called KAWNCM, in order to better satisfy the clustering of some complex data (i.e. non-spherical data). We employ the iterative optimization strategy to obtain the optimal solutions for AWNCM and KAWNCM. The advantage of AWNCM and KAWNCM is to improve performance by learning the importance of each attribute to the cluster while maintaining an efficient solution to cluster overlap and outliers. Extensive experimental results using synthetic data and gene expression data demonstrate the feasibility and effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Expression quantitative trait locus (eQTL) analysis is a useful tool to identify genetic loci that are associated with gene expression levels. Large collaborative efforts such as the Genotype-Tissue Expression (GTEx) project provide valuable resources for eQTL analysis in different tissues. Most existing methods, however, either focus on one tissue at a time, or analyze multiple tissues to identify eQTLs jointly present in multiple tissues. There is a lack of powerful methods to identify eQTLs in a target tissue while effectively borrowing strength from auxiliary tissues. In this paper, we propose a novel statistical framework to improve the eQTL detection efficacy in the tissue of interest with auxiliary information from other tissues. This framework can enhance the power of the hypothesis test for eQTL effects by incorporating shared and specific effects from multiple tissues into the test statistics. We also devise data-driven and distributed computing approaches for efficient implementation of eQTL detection when the number of tissues is large. Numerical studies in simulation demonstrate the efficacy of the proposed method, and the real data analysis of the GTEx example provides novel insights into eQTL findings in different tissues. • Identify eQTLs in a target tissue while effectively borrowing strength from auxiliary tissues. • A novel mFDR-control procedure is proposed to maximize the mTPR. • Propose distributed computing approach for efficient eQTL detection. [ABSTRACT FROM AUTHOR]

Periostin is a matricellular protein known to be alternatively spliced to produce ten isoforms with a molecular weight of 78–91 kDa. Within the extracellular matrix, periostin attaches to cell surfaces to induce signaling via integrin-binding and actively participates in fibrillogenesis, orchestrating the arrangement of collagen in the extracellular environment. In atopic diseases such as atopic dermatitis (AD) and asthma, periostin is known to participate in driving the disease-causing type 2 inflammation. The periostin isoforms expressed in these diseases and the implication of the alternative splicing events are unknown. Here, we present two universal assays to map the expression of periostin isoforms at the mRNA (RT-qPCR) and protein (PRM-based mass spectrometry) levels. We use these assays to study the splicing profile of periostin in AD lesions as well as in in vitro models of AD and asthma. In these conditions, periostin displayed overexpression with isoforms 3 and 5 standing out as highly overexpressed. Notably, isoforms 9 and 10 exhibited a divergent pattern relative to the remaining isoforms. Isoforms 9 and 10 are often overlooked in periostin research and this paper presents the first evidence of their expression at the protein level. This underlines the necessity to include isoforms 9 and 10 in future research addressing periostin splice isoforms. The assays presented in this paper hold the potential to improve our insight into the splicing profile of periostin in tissues and diseases of interest. The application of these assays to AD lesions and in vitro models demonstrated their potential for identifying isoforms of particular significance, warranting a further in-depth investigation. [Display omitted] • The study presents two new methods for mapping and measuring periostin splice isoforms in human samples. • The analyses show that isoforms 3 and 5 are significantly overexpressed while isoforms 9 and 10 are downregulated in the diseases studied. • This is the first experimental proof of the existence of isoforms 9 and 10 at the protein level. • The results demonstrate that these methods have the potential to identify isoforms that are particularly significant. • Our research accurately maps periostin isoform expression in human samples, providing the basis for further understanding. [ABSTRACT FROM AUTHOR]

Lithium-ion battery is a kind of energy storage devices with complex internal reaction and many factors affecting its performance. Accurate prediction of its SOH (State of Health) is of great significance to prolong its service life and improve safety performance. However, the current prediction for SOH has the difficulties of selecting health factors and using data-driven methods with opaque mechanisms. In this paper, a data-driven model will be established with the capacity change during aging of lithium-ion batteries as a health indicator to realize precise prediction of capacity degradation. Firstly, the feature parameters were extracted and analyzed from the battery cyclic aging test dataset. Two in-situ nondestructive characterization methods, incremental capacity analysis curve and differential thermal voltammetry curve, were utilized to resolve the evolution paths of the feature parameters. After that, a data-driven battery capacity degradation estimation is realized based on the GEP (Gene Expression Programming) algorithm, the performance is compared with the existing vehicle-end and cloud-end models, and a higher-accuracy SOH stacking model is developed with an increase of less than 1 ms in computational time. The results indicated that the GEP model proposed in this paper has obvious advantages in terms of physical explain-ability, computational efficiency and robustness. • Establishing a high-precision battery SOH estimation model based on the GEP algorithm. • The relationship between ICA and DTV curves with aging evolution laws is revealed. • Fusion of GEP model with existing vehicle-end and cloud-end models using stacking strategy. [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]

Cel12A , a gene that encodes an endocellulase of Bacillus licheniformis , was cloned and overexpressed in E. coli DE3. The rBLCel (wild-type recombinant cellulase) enzyme was assayed and characterized for its physical properties, including its optimum pH (9.0), temperature (50 °C), thermostability (175 h) and kinetic parameters ( K m 16.38 ± 0.550 mg ml −1 ; k cat 134.91 ± 0.377 min −1 and k cat /K m 8.23 ± 0.026 ml min −1  mg −1 ). To determine the role of conserved amino acids in the substrate binding pocket, five single mutations and one double mutation were studied for their effects on substrate specificity. All six purified engineered enzymes were assayed and compared to rBLCel regarding their catalytic activity with a specific substrate (CMC). All of the recombinant enzymes (wild type and engineered) were also assayed with non-specific substrates, such as xylan, avicel and filter paper (FP). Out of five point-mutant enzymes, three mutants (W197A, W98A and Y89A) showed reduced specific activity compared to rBLCel. However, the W139A and W53A mutants exhibited a 67% and 4% relative increase in their specific activity with a specific substrate (CMC), respectively. After replacing aromatic residues, the affinity towards the CMC increased in the case of the W139A and W53A mutants, indicating that the aromatic residues play a key role in substrate affinity and binding. One of the significant results that we obtained was that the increase in activity was additive in the double mutant enzyme, W139A_W53A, which showed 1216% higher activity than rBLCel on filter paper (FP). The activity of all of the mutated enzymes with non-specific substrates indicates that the substrate binding pocket is altered and has become flexible toward other substrates after mutation. Moreover, given the importance of the two enzymes in degrading lignocellulose, one bifunctional enzyme endowed with the two catalytic activities may be of great advantage. Despite the broad spectrum of cellulases being isolated, no single enzyme is completely suitable as it is, for the hydrolysis of lignocellulose. These enzymes have been used due to their biotechnological applications in several industries, including bio pulping wood, treatment of animal feed to increase digestibility, agro-processing, juice processing and baking. [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]

Genomic biomarkers of cancer are based on changes in nucleic acids, which include abnormal expression levels of some miRNAs, point mutations in DNA sequences, and altered levels of DNA methylation. The presence of tumor-related nucleic acids in body fluids (blood, saliva, or urine) makes it possible to achieve a non-invasive early-stage cancer diagnosis. Currently existing techniques for the discovery of nucleic acids require complex, time-consuming, costly assays and have limited multiplexing abilities. Surface-enhanced Raman spectroscopy (SERS) is a vibrational spectroscopy technique that is able to provide molecular specificity combined with trace sensitivity. SERS has gained research attention as a tool for the detection of nucleic acids because of its promising potential: label-free SERS can decrease the complexity of assays currently used with fluorescence-based detection due to the absence of the label, while labeled SERS may outperform the gold standard in terms of the multiplexing ability. The first papers about SERS-based methods for the measurement of genomic biomarkers were written in 2008, and since then, more than 150 papers have been published. The aim of this paper is to review and evaluate the proposed SERS-based methods in terms of their level of development and their potential for liquid biopsy application, as well as to contribute to their further evolution by attracting research attention to the field. This goal will be reached by grouping, on the basis of their experimental protocol, all the published manuscripts on the topic and evaluating each group in terms of its limit of detection and applicability to real body fluids. Thus, the methods are classified according to their working principles into five main groups, including capture-based, displacement-based, sandwich-based, enzyme-assisted, and specialized protocols. [Display omitted] • SERS-based detection of miRNA level changes, DNA point mutations, and DNA methylation level alterations in body fluids have good potential for early-stage cancer diagnosis. • Biological protocols designed for the selective detection of the target DNAs/miRNAs have been reviewed and grouped into the following categories: capture, displacement, sandwich, cleavage, and specific protocols. • The protocols have been arranged according to the increasing complexity of the assays and evaluated in terms of their performance for liquid biopsy application. As a result, one-to-step protocols have shown good LODs, applicability in body fluids, and multiplexing abilities, especially for miRNA detection. • In general, labeled protocols outperform label-free assays by reaching the LODs as low as 10 − 16 M and detecting the target miRNA/DNA in the complex matrices, such as total RNAs/DNAs and real body fluids. However, the performance of the label-free protocols can be improved by developing highly sensitive SERS substrates. • Thus, there is a potential to develop relatively simple SERS-based protocols for liquid biopsy applications with promising LODs and multiplexing abilities, but more work should be conducted in this direction. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the analysis and the numerical solution of the time-space fractional Schnakenberg reaction-diffusion model with a fixed time delay. This model is a natural system of autocatalysis, which often occurs in a variety of biological systems. The numerical solutions are obtained by constructing an efficient numerical algorithm to approximate Riesz-space and Caputo-time fractional derivatives. More precisely, the L 1 approximation is applied to discretize the temporal Caputo fractional derivative, while the Legendre-Galerkin spectral method is used to approximate the spatial fractional operator. The described method is shown to be unconditionally stable, with a 2 − β convergent order in time and an exponential rate of convergence in space in case of the smoothness of the solution. The error estimates for the obtained solution are derived by applying a proper discrete fractional Grönwall inequality. Moreover, we offer numerical simulations that demonstrate a close match with the theoretical study to evaluate the efficacy of our methodology. [ABSTRACT FROM AUTHOR]

Humans evolve from a single-cell to 37 trillion cells. Next-generation sequencing advances help the sequencing of cells at the resolution of single-cell. Single-cell datasets are produced at various geographical locations, time-points, laboratories, and by distinct experimenters, using different sequencing machines and protocols. Integration of different samples can reveal more insights into the interplay of cells that define the state and function of tissues and organs. Several methods for integratiion of single-cell datasets have been developed. Choosing an appropriate integration method for the task at hand is a difficult decision to make. In this paper, a comparitive evaluation of five integration methods is presented using two batches of gene expression and chromatin accessibility data. The methods are evaluated for three tasks: integration and batch removal, cell-type clustering, and trajectory conservation using five evaluation metrics. For cell-type clustering, this study finds LMDS and MNN perform well, while preserving biology. Furthermore, trVAE outperforms all other models in batch effect removal and trajectory conservation (TC) tasks, where as totalVI does not perform well across all the tasks. [ABSTRACT FROM AUTHOR]

Gene Expression Data is the biological data to extract meaningful hidden information from the gene dataset. This gene information is used for disease diagnosis especially in cancer treatment based on the variations in gene expression levels. DNA microarray is an efficient method for gene expression classification and prediction of cancer disease for specific types of cancer. Due to the abundance of computing power, deep learning (DL) has become a widespread technique in the healthcare sector. The gene expression dataset has a limited number of samples but a large number of features. Data augmentation is needed for gene expression datasets to overcome the dimensionality problem in gene data. It is a technique to generating the synthetic samples to increase the diversity of data. Deep learning methods are designed to learn and extract the features that come from the raw input data in the form of multidimensional arrays. This paper reviews the existing research in deep learning techniques like Feed Forward Neural Network (FFN), Convolutional Neural Network (CNN), Autoencoder (AE) and Recurrent Neural Network (RNN) for the classification and prediction of cancer disease and its types through gene expression data analysis. [ABSTRACT FROM AUTHOR]

Due to the lack of available episomal plasmid, the improvement of many industrial strains, especially exogenous gene expression, is severely restricted. The failure of autonomous replication or low copy number of episomal plasmids is the main reason for the failure of many episomal plasmids construction. In this paper, Candida glycerinogenes , an industrial strain lacking episomal plasmids, was employed as the topic. A series of GFP-based plasmids containing autonomously replicating sequence (ARS) from different strain sources were constructed and analyzed for performance, and it was found that only the panARS from Kluyveromyces lactis compared with other nine low capacity ARSs proved to have the best performance and could be used to construct episomal plasmid. Further, the dual-ARS strategy was used to optimize the episomal plasmid, and the results indicated that only the dual-ARS plasmid +PPARS2 with double different ARSs, not the dual-ARS plasmid +panARS with double same ARSs, showed an improvement in all properties, with an increase in transformation efficiency of about 36% and a synchronous trend of fluorescence intensity and copy number, both by about 40%. In addition, constructed episomal plasmids were used to express the exogenous gene CrGES , and the fact that geraniol was found proved the versatility of the plasmids. The successful construction of episomal plasmids will also substantially facilitate genetic engineering research and industrial use of C. glycerinogenes in the future, as well as providing a feasible approach to create episomal plasmids for industrial strains. [ABSTRACT FROM AUTHOR]

Abstract: A novel β-mannanase gene (CsMan5A) was cloned from Chaetomium sp. CQ31 and expressed in Pichia pastoris. It had an open reading frame of 1251bp encoding 416 amino acids and contained two introns. The deduced amino acid sequence shared the highest similarity (73%) with the β-mannanase from Emericella nidulans and belongs to glycosyl hydrolase family 5. The recombinant β-mannanase (CsMan5A) was secreted at extremely high levels of 50,030UmL−1 and 6.1mgmL−1 in high cell density fermentor. The purified enzyme was optimally active at pH 5.0 and 65°C and displayed broad pH stability (pH 5.0–11.0) and exhibited specificity towards locust bean gum (K m =3.1mgmL−1), guar gum (K m =9.3mgmL−1) and konjac powder (K m =10.5mgmL−1). It efficiently degraded mannan polysaccharides into mannose and mannooligosacccharides, and also hydrolyzed mannotriose and mannotetraose. These properties make CsMan5A highly useful in food, feed and paper/pulp industries. [Copyright &y& Elsevier]

Abstract: The alkaline stability of the xylanase from Thermomyces lanuginosus was further improved by directed evolution using error-prone PCR mutagenesis. Positive clones were selected by their ability to produce zones of clearing on pH 9 and 12 xylan agar plates. Variant NC38 was able to withstand harsh alkaline conditions retaining 84% activity after exposure at pH 10 for 90min at 60°C, while the parent enzyme had 22% activity after 60min. The alkaline stable variant NC38 was cloned into pBGP1 under the control GAP promoter and pET22b(+) for expression in Pichia pastoris and Escherichia coli BL21, respectively. Best extracellular expression of the recombinant xylanase was observed in P. pastoris (261.7±0.61Uml−1) whereas intracellular activity was observed in E. coli (47.9±0.28Uml−1) was low. Total activity obtained in P. pastoris was 545-fold higher than E. coli. The mutated alkaline stable xylanase from P. pastoris was secreted into the culture medium with little or no contamination by host proteins, which favours the application of this enzyme in the pulp and paper industry. [Copyright &y& Elsevier]

• This paper reports the first attempt in integrating multiobjective opti- mization (MOO) and genomic structure for solving the subspace clustering problem. • Multiobjective optimization framework is utilized to simultaneously opti- mize several sub-space cluster quality measures. • The existing cluster quality measures are modified to handle subspace clustering problem. • As a part of the experiments, the proposed algorithm is applied on the bi-clustering of gene expression data to show the efficacy of the existing technique in solving some real-life problem. Bi-clustering of gene expres- sion data is a sub-space clustering problem where a subset of rows and a subset of columns need to be selected. Subspace clustering techniques become paramount in pattern recognition for detecting local variations from high dimensional data. Several techniques exist in the recent literature for subspace clustering, majority of which optimize implicitly or explicitly a single cluster quality measure. Inspired by the success of multi-objective optimization in solving clustering problem, we developed a multi-objective based subspace clustering technique in this paper. The proposed technique simultaneously optimizes two subspace cluster quality measures, capable of capturing different cluster shapes/properties. Two existing cluster quality measures, XB-index and PBM-index, are modified to develop subspace cluster validity indices, and then those are used as optimization criteria. These cluster validity indices measure the appropriateness of generated subspace clusters in terms of intra-subspace cluster similarity and separation between subspace clusters. The proposed approach utilizes a new evolvable genome structure which stores the information about subspaces in its phenotype and genotype and evolves this genome structure with the help of different genetic operators. The developed algorithm is applied on ten standard real-life data sets and sixteen synthetic datasets for identifying different subspace clusters. The results obtained by this algorithm are compared against some state-of-the-art techniques with respect to different performance metrics. Experimentation reveals that the proposed algorithm is able to take advantages of its evolvable genomic structure and multi-objective based framework and it can be applied to any data set. In a part of the paper, the efficacy of the proposed technique is also shown for bi-clustering of gene-expression data sets. [ABSTRACT FROM AUTHOR]

The real-time reverse-transcript polymerase chain reaction (RT-PCR) test is a widely used laboratory technique that is highly sensitive and reliable for measuring the quantification of gene expression levels and diagnosing various of diseases, including COVID-19. The RT-PCR experiments often have correlated technical replicates of a small number of samples. However, current statistical analysis of RT-PCR assumes a large sample size and does not account for correlated structure across the replicates. In this paper, we review popular statistical methods for analyzing RT-PCR data and propose a permutation method that accounts for the small sample size and the correlated structure of RT-PCR data. Our proposed method provides a more accurate and efficient analysis of RT-PCR data. We provide an R program to implement our method for practitioners. • Current statistical analysis of RT-PCR assumes a large sample size and does not account for correlated structure across the replicates. • We propose a permutation method that accounts for both the small sample size and replicated structure of the RT-PCR data. • We have created a Github website where practitioners can obtain an R program used in this paper. [ABSTRACT FROM AUTHOR]

Nucleolar dominance is one of the epigenetic phenomena that refers to the dominance effect exhibited by the suppression of ribosomal RNA gene loci from one parent in heterozygous organisms. In this paper, the genetic and expression changes of 45S rRNA genes in different generations of the crucian carp-like homodiploid fish lineage (2nNCRC, F 1 , F 2 , F 3 , F 5) and the autotetraploid carp lineage (4nNC, F 1 -F 3) formed by distant hybridization of common carp (Cyprinus carpio , COC) (♀) × blunt snout bream (Megalobrama amblycephala , BSB) (♂) were mainly studied. The results showed that the nucleolar dominance patterns were different in different generations of the 2nNCRC lineage and the 4nNC lineage. In the different generations of the 2nNCRC lineage, 2nNCRC-F 1 (F 3 , F 5) exhibited the phenomenon of nucleolar dominance, while 2nNCRC-F 2 did not and expressed the mutant 45S rRNA. The establishment of the nucleolar dominance pattern presented a more complicated situation, which may be related to the inconsistent coping mechanism among different generations after suffering the effect of "genome shock" at the early stage of the formation of the 2nNCRC lineage. Among the different generations of the 4nNC lineage, 4nNC-F 2 existed the phenomenon of nucleolar dominance and expressed mutant 45S rRNA. However, 4nNC-F 1 (F 3) did not exist in the phenomenon of nucleolar dominance. The establishment of the nucleolar dominance pattern showed a process of instability-stability-instability, revealing the epigenetic instability of this lineage. This result may be related to the comprehensive effect caused by the continuous "genome shock" at the early stage of the formation of the 4nNC lineage, which can provide clues for further revealing the possible mechanism of occurrence and survival of polyploidization vertebrates. Moreover, this study found that the nucleolar dominance was biased towards BSB in the 2nNCRC lineage, while it was biased towards COC in the 4nNC lineage. The inconsistent results appeared in the different ploidy lineages formed by the same distant hybridization combination, which further verified that the dominance of transcription advantages species did not necessarily determine the biased characteristics of nucleolar dominance. Two lineages derived a mutant ITS1 sequence, which the mechanism may be related to some mechanisms triggered by the "genome shock" effect. This study will further fill a gap in studying nucleolar dominance in the early stage of the formation of homodiploid and polyploid vertebrates and provide important experimental data for studying fish epigenetics, which is of great significance in fish genetic breeding and biological evolution. • This paper fills a gap in the study of nucleolar dominance (ND) in homodiploids. • ND pattern of homodiploids is more complex than that of allodiploids. • This study reveals a more complex ND pattern in the autotetraploid species. • Transcription advantage species do not determine the biased feature of ND. [ABSTRACT FROM AUTHOR]

Sugarcane, a prominent global crop utilized for sugar, bioethanol, and renewable bioenergy production, holds significant importance in Colombia. In 2022, it contributed to the production of 2.1 million tons of sugar, 347 million liters of bioethanol, and 1745 GWh of electrical energy. The cultivation of sugarcane worldwide faces vulnerability to drought stress induced by climate change, which significantly affects yields. Understanding how plants respond to drought involves complex interactions among genes, morphology, physiology, and biochemistry. However, these factors are often analyzed separately using methods such as Differentially Expressed Genes, comparative physiology, or metabolomics, thereby restricting the potential for broader insights that could arise from their further integration. This paper uses an improved version of Control-Stress data Integration with Overlapping Clustering (CSI-OC), a methodology that provides a comprehensive perspective by integrating diverse data types, in which a Lasso-based network helps in pinpointing stress-responsive genes. The objective of this study is to utilize CSI-OC to identify genes relevant to drought stress in Colombian sugarcane cultivars. To accomplish this goal, the study analyzes both leaf and root expression data, alongside four physiological parameters associated with leaf responses across different levels of drought stress. Computational evaluation indicates that the datasets are effectively processed using the CSI-OC workflow. This methodology demonstrates good performance in identifying genes strongly correlated with both the stress condition and the considered phenotypic traits. As stress levels increase, the number of genes selected by CSI-OC displays a contrasting pattern between leaves and roots. This observation implies a coordinated cascade of gene responses from leaves to roots with escalating stress levels, indicating a holistic adaptation strategy within the plant. Overall, the findings of this study underscore the effectiveness of CSI-OC as a comprehensive approach for identifying pertinent genes linked to drought stress in sugarcane. [Display omitted] • Stress genes were found via interactions in overlapping modules influencing phenotype. • Genes can be stress-relevant even without differential expression or hub node status. • Merging control-stress data for Lasso-based networks boosts large dataset efficiency. • Findings suggest coordinated gene response from leaves to roots with increased stress. [ABSTRACT FROM AUTHOR]

[Display omitted] Healthy aging results in cardiac structural and electrical remodeling that increase susceptibility to cardiovascular diseases. Relaxin has shown broad cardioprotective effects including anti-fibrotic, anti-arrhythmic and anti-inflammatory outcomes in multiple models. This paper focuses on the cardioprotective effects of Relaxin in a rat model of aging. Sustained atrial or ventricular fibrillation are readily induced in the hearts of aged but not young control animals. Treatment with Relaxin suppressed this arrhythmogenic response by increasing conduction velocity, decreasing fibrosis and promoting substantial cardiac remodeling. Relaxin treatment resulted in a significant increase in the levels of: Nav1.5, Cx43, βcatenin and Wnt1 in rat hearts. In isolated cardiomyocytes, Relaxin increased Nav1.5 expression. These effects were mimicked by CHIR 99021, a pharmacological activator of canonical Wnt signaling, but blocked by the canonical Wnt inhibitor Dickkopf1. Relaxin prevented TGF-β-dependent differentiation of cardiac fibroblasts into myofibroblasts while increasing the expression of Wnt1; the effects of Relaxin on cardiac fibroblast differentiation were blocked by Dickkopf1. RNASeq studies demonstrated reduced expression of pro-inflammatory cytokines and an increase in the expression of α- and β-globin in Relaxin-treated aged males. Relaxin reduces arrhythmogenicity in the hearts of aged rats by reduction of fibrosis and increased conduction velocity. These changes are accompanied by substantial remodeling of the cardiac tissue and appear to be mediated by increased canonical Wnt signaling. Relaxin also exerts significant anti-inflammatory and anti-oxidant effects in the hearts of aged rodents. The mechanisms by which Relaxin increases the expression of Wnt ligands, promotes Wnt signaling and reprograms gene expression remain to be determined. [ABSTRACT FROM AUTHOR]

Knowledge discovery from big datasets is one of the most important challenges in the pattern recognition field. More important than this is how much the extracted information and created models are reliable. Studies have shown that these models are usually highly dependent on the samples, features, data, and structure of the models. In general, the issue of stability is very important in creating models. This paper presents a method that not only considers the effect of different known classifiers but also tries to achieve a stable model for separating samples by combining different feature selection methods and considering the criterion of stability. Briefly, our contributions to the proposed method include 1) analyzing the ability of features in sample classification individually with different well-known classifiers, 2) estimating the probability of the features that could be selected in high-impact sets of features, and 3) applying the stability concept to increase the weight of the robust sets of the features. The proposed algorithm is used to select the high-impact genes of microarray datasets. Three high-dimensional gene expressions of cancerous tissues are used as benchmarks. The results obtained show relative superiority compared to other methods. [ABSTRACT FROM AUTHOR]

To explore the expression of HAUS6 in squamous cell carcinoma of the tongue (TSCC) and its relationship with the clinicopathological features of patients, and to further provide new ideas and therapeutic targets for curing TSCC. The Cancer Genome Atlas (TCGA) database was used to screen for differentially expressed genes (DEGs) between TSCC and normal tissues and survival analysis. DEGs of HAUS6 were screened and analyzed for GO, KEGG and GSEA enrichment. Exploring the correlation of HAUS6 with immune cell infiltration and immune checkpoint-related genes. The expression of HAUS6 in tumor and paraneoplastic tissues was confirmed by immunohistochemistry and Western Blot. Analysis of the TCGA database results showed that expression of HAUS6 mRNA was significantly enhanced and correlated with overall survival (OS, p < 0.05) in TSCC. HAUS6 expression correlated with the level of immune cell infiltration and immune checkpoint-related genes. Immunohistochemistry and Western Blot confirmed that the expression level of HAUS6 protein was significantly higher in tumor tissues than in paraneoplastic tissues, and that tumor size and hypo-differentiation were higher in the HAUS6 high expression group than in the low expression group in TSCC (p < 0.05). In conclusion, these analyses suggest that HAUS6 can act as an independent predictor of prognosis (p < 0.05) and high HAUS6 expression is strongly associated with poor prognosis. • The link between TSCC differential gene HAUS6 expression and its clinicopathologic features and prognosis was identified by TCGA. • In this paper, the HAUS6 gene was studied for the first time in TSCC. • HAUS6 was found to be highly expressed in tumour tissues and was strongly associated with poor prognosis. • The combination of bioinformatics and experiments provided a potential target for the diagnosis and treatment of TSCC. [ABSTRACT FROM AUTHOR]

Aquaculture has emerged as a crucial sector in many countries. In the Recirculating Aquaculture System (RAS), Dissolved Oxygen (DO) levels are critical to the health of aquatic animals. As DO sensors are costly, a number of studies have proposed a soft sensor technique utilizing machine learning for estimating DO levels in water. However, the existing research work mainly focuses on black-box approaches, which do not provide numerical analysis between the DO levels and the related parameters. To solve this issue, a sequential Genetic Programming (GP) approach with an evolutionary refinement method is proposed to generate a mathematical expression that represents DO levels in water. In particular, a coarse mathematical model is generated using GP and subsequently fine-tuned using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). As a study case, the Klamath River dataset is used to generate the model. The evaluation of our proposed method uses datasets from both the Klamath River and the Fanno Creek. Two models are generated in this paper; one model uses six features, while the other only employs three. The results indicate that the model with six features exhibits relatively higher accuracy. However, it is worth noting that a smaller dataset of features is also capable of achieving generalization of the model. [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]

A makiang seed powder (MSP) feeding trial was performed on Nile tilapia (Oreochromis niloticus) for eight weeks to evaluate the effects on growth performance, immune response, and gene expression. Three hundred fingerlings (13.20 ± 0.04 g) were fed five diets with various amounts of MSP at 0, 5, 10, 20 and 40 g kg−1. After four and eight weeks of the feeding trial, growth rates and immune responses were tested, while relative immune and antioxidant gene expression were performed after eight weeks of MSP feeding. Accordingly, the growth indices (SGR, WG) and immune activity (skin mucus and serum lysozyme, skin mucus and serum peroxidase, alternative complement, phagocytosis and respiratory burst activities) in Nile tilapia were significantly increased in the treated diets compared with the control diet (P < 0.05). The maximum (P ≤ 0.05) growth and immune activity values were noted in fish fed 5 g kg−1 MSP. IL1, IL8, LBP, GPX, GSTa and GSR gene expressions were also shown to be upregulated in fish on MSP diets, with the highest value reported in fish fed 5 g kg−1 MSP. Finally, MSP has the potential to be employed as a feed supplement in the biofloc system for the cultivation of Nile tilapia. Visual representation of the results obtained in our paper by supplementing Nile Tilapia diet with MSP for a period of 8 weeks. Image created with biorender.com. [Display omitted] • MSP is a promising feed additive for the aquacultural practices of Nile tilapia. • MSP5 (5 g kg−1) can enhance growth performance and feed conversion ratio. • MSP5 boosts the skin mucus and serum immune responses of Nile tilapia. • MSP5 induces increased expression of immune response and antioxidant-relate genes. [ABSTRACT FROM AUTHOR]

[Display omitted] This review signifies the role of circular RNAs (circRNAs) in tuberculosis (TB) and lung cancer (LC), focusing on pathogenesis, diagnosis, and treatment. CircRNAs, a newly discovered type of non-coding RNA, have emerged as key regulators of gene expression and promising biomarkers in various bodily fluids due to their stability. The current review discusses circRNA biogenesis, highlighting their RNase-R resistance due to their loop forming structure, making them effective biomarkers. It details their roles in gene regulation, including splicing, transcription control, and miRNA interactions, and their impact on cellular processes and diseases. For LC, the review identifies circRNA dysregulation affecting cell growth, motility, and survival, and their potential as therapeutic targets and biomarkers. In TB, it addresses circRNAs' influence on host anti-TB immune responses, proposing their use as early diagnostic markers. The paper also explores the interplay between TB and LC, emphasizing circRNAs as dual biosignatures, and the necessity for differential diagnosis. It concludes that no single circRNA biomarker is universally applicable for both TB and LC. Ultimately, the review highlights the pivotal role of circRNAs in TB and LC, encouraging further research in biomarker identification and therapeutic development concomitant for both diseases. [ABSTRACT FROM AUTHOR]

In recent years, there has been a growing interest in modulating the performance of probiotic, mainly Lactic Acid Bacteria (LAB), in the field of probiotic food. Attenuation, induced by sub-lethal stresses, delays the probiotic metabolism, and induces a metabolic shift as survival strategy. In this paper, RNA sequencing was used to uncover the transcriptional regulation in Lacticaseibacillus casei ATCC 393 after ultrasound-induced attenuation. Six (T) and 8 (ST) min of sonication induced a significant differential expression of 742 and 409 genes, respectively. We identified 198 up-regulated and 321 down-regulated genes in T, and similarly 321 up-regulated and 249 down-regulated in ST. These results revealed a strong defensive response at 6 min, followed by adaptation at 8 min. Ultrasound attenuation modified the expression of genes related to a series of crucial biomolecular processes including membrane transport, carbohydrate and purine metabolism, phage-related genes, and translation. Specifically, genes encoding PTS transporters and genes involved in the glycolytic pathway and pyruvate metabolism were up-regulated, indicating an increased need for energy supply, as also suggested by an increase in the transcription of purine biosynthetic genes. Instead, protein translation, a high-energy process, was inhibited with the down-regulation of ribosomal protein biosynthetic genes. Moreover, phage-related genes were down-regulated suggesting a tight transcriptional control on DNA structure. The observed phenomena highlight the cell need of ATP to cope with the multiple ultrasound stresses and the activation of processes to stabilize and preserve the DNA structure. Our work demonstrates that ultrasound has remarkable effects on the tested strain and elucidates the involvement of different pathways in its defensive stress-response and in the modification of its phenotype. [ABSTRACT FROM AUTHOR]

High dimensional and small samples characterize gene expression data and contain a large number of genes unrelated to disease. Feature selection improves the efficiency of disease diagnosis by selecting a small number of important genes. Unfortunately, existing algorithms do not consider the correlation between features, and search algorithms tend to fall into the local optimal solution in the feature search process. To this end, this paper proposes a feature filter and group evolution hybrid feature selection algorithm (FG-HFS) for high-dimensional gene expression data. Unlike existing algorithms, we propose using spectral clustering to group redundant features into a group. Then, we propose a redundant feature filter algorithm. According to the principle of approximate Markov blanket, grouped feature groups are filtered to delete these redundant features. Among them, filtered features are evenly divided by density according to the feature exponential strategy. Most importantly, we propose using the group evolution multi-objective genetic algorithm to search the filtered feature subsets and evaluate the candidate feature subsets according to the in-group and out-group so as to select the feature subsets with the highest accuracy and the least number. Experimental results show that the average accuracy (ACC) and Matthews correlation coefficient (MCC) indexes of the selected feature subsets (FSs) by the FG-HFS algorithm on 5 gene expression datasets are 92.76% and 88.76%, respectively, which are significantly better than the existing algorithms. In addition, the FSs and ACC/FSs indexes of the FG-HFS algorithm are also better than the existing algorithms, which fully proves the superiority of the FG-HFS algorithm. More importantly, the Wilcoxon and Friedman statistical experiments results show that the feature selection effect of FG-HFS algorithm is significantly better than that of existing algorithms, no matter in pairwise comparison or multiple comparison. • We propose using spectral clustering to group the features so that the in-group feature similarity is extremely high. • We propose a redundant feature filter algorithm since existing algorithms cannot filter redundant features. • we propose using the group evolution multi-objective genetic algorithm to search the filtered feature subsets. [ABSTRACT FROM AUTHOR]

The paper aims to evaluate the efficacy and safety of 223Ra in patients who progressed after first-line androgen deprivation therapy. EXCAAPE (NCT03002220) was a multicentre, single-arm, open-label, non-controlled phase IIa trial in 52 patients with metastatic castration-resistant prostate cancer and asymptomatic bone metastases who have progressed on abiraterone acetate or enzalutamide, up to six doses of 223Ra (55 kBq/kg of body weight per month). The primary end-point was radiographic progression-free survival (rPFS). Secondary end-points included rPFS based on androgen receptor splice variant 7 (AR-V7) expression in circulating tumour cells (CTCs), overall survival, and safety. Median rPFS was 5.5 months (95% CI 5.3–5.5). Median rPFS of patients with AR-V7(−) CTCs was longer than that of patients with AR-V7(+) CTCs (5.5 versus 2.2 months, respectively; P = 0.056). Median overall survival was 14.8 months (95% CI 11.2–not reached) and was significantly greater for AR-V7(−) patients than for AR-V7(+) patients (14.8 months versus 3.5 months, respectively; P < 0.01). 223Ra was well tolerated; anaemia and thrombocytopenia were the most common grade 3/4 adverse events (5.8% and 11.5%, respectively). 223Ra seems to be a reasonable treatment for patients with metastatic castration-resistant prostate cancer and asymptomatic bone metastases progressing on novel hormonal therapy and had an acceptable safety profile. • 223Ra had a promising antitumour activity in patients with metastatic castration-resistant prostate cancer with asymptomatic bone metastases. • 223Ra showed an acceptable safety profile similar to that reported in other studies. • Overall survival of androgen receptor splice variant 7 (−) patients was significantly higher than androgen receptor splice variant 7 (+) patients. [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]

Non-parametric tests are often used in feature selection of gene expression data. In order to achieve feature selection and redundancy removal of gene expression data and obtain feature subsets with higher classification accuracy, this paper proposes a feature selection algorithm based on Jonckheere-Terpstra test for the characteristics of high noise and high redundancy in gene expression data, and applies the algorithm to both binary and multiclassified gene expression datasets. The algorithm first uses Jonckheere-Terpstra test to perform feature selection on the datasets to initially reduce the data dimension, and then uses Pearson correlation test to remove the redundancy of the selected data sets to obtain the final feature subset. In order to test its classification performance, support vector machine and k-nearest neighbor were used for classification experiments respectively. The experimental results show that the algorithm has high classification accuracy for both feature selection and redundancy removal of binary and multiclassified datasets. [ABSTRACT FROM AUTHOR]

Abstract Background and objective: Finding combinations (i.e., pairs, or more generally, q -tuples with q ≥ 2) of genes whose behavior as a group differs significantly between two classes has received a lot of attention in the quest for the discovery of simple, accurate, and easily interpretable decision rules for disease classification and prediction. For example, the Top Scoring Pair (TSP) method seeks to find pairs of genes so that the probability of the reversal of the relative ranking of the expression levels of the genes in the two classes is maximized. The computational cost of finding a q -tuple of genes that scores highest under a given metric is O (Gq), where G is the total number of genes. This cost is often problematic or prohibitive in practice (even for q = 2), as the number of genes G is often in the order of tens of thousands. Methods: In this paper, we show that this computational cost can be significantly reduced by excluding from consideration genes whose behavior is almost identical in the two classes and therefore their inclusion in any q -tuple is rather non-informative. Our criterion for the exclusion of genes is supported by a statistically robust metric, the Area Under the Curve (AUC) of the corresponding Receiver Operating Characteristic (ROC) curve. By filtering out genes whose AUC value is below a user-chosen threshold, as determined by a procedure that we describe in the paper, dramatic reductions in the run times are obtained while maintaining the same classification accuracy. Results: We have experimentally verified the gains of this approach on several case studies involving ovarian, colon, leukemia, breast and prostate cancers, and diffuse large b-cell lymphoma. Conclusions: The proposed method is not only faster (for example, we observed an average 78.65% reduction over the run time of TSP) while maintaining the same classification accuracy, but it can even result in better classification accuracy due to its inherent ability to avoid the so-called "pivot" (non-informative) genes that may intrude in q -tuples chosen otherwise. [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]