Biorefining by enzymatic hydrolysis (EH) of lignocellulosic waste material due to low costs and affordability has received enormous interest amongst scientists as a potential strategy suitable for the production of bioactive ingredients and chemicals. In the present study, a sustainable and eco-friendly approach to the extraction of bound ferulic acid (FA) has been demonstrated using a single-step EH by a mixture of lignocellulose-degrading enzymes. For comparative purposes of the efficiency of EH, an online SFE-SFC-MS extraction and analysis approach was applied. The experimental results demonstrated up to 369.3 mg 100 g−1 FA released from rye bran after 48 h EH with Viscozyme L. The EH of wheat and oat bran with Viscoferm for 48 h resulted in 255.1 and 33.5 mg 100 g−1 of FA, respectively. The extraction of FA from bran matrix using the SFE-CO2-EtOH delivered up to 464.3 mg 100 g−1 of FA, though the extractability varied depending on the parameters used. The 10-fold and 30-fold scale-up experiments confirmed the applicability of EH as a bioprocessing method valid for industrial-scale. The highest yield of FA in both scale-up experiments was obtained from rye bran after 48 h of EH with Viscozyme L. In purified extracts, the absence of xylose, arabinose, and glucose as final degradation products of lignocellulose was proven by a HPLC-RID system. Up to 94.0% purity of FA was achieved by SPE using the polymeric reversed-phase Strata X column and 50% EtOH as eluent.

A major problem in the post-inversion geophysical interpretation is the extraction of geological information from inverted physical property models, which do not necessarily represent all underlying geological features. No matter how accurate the inversions are, each inverted physical property model is sensitive to limited aspects of subsurface geology and is insensitive to other geological features that are otherwise detectable with complementary physical property models. Therefore, specific parts of the geological model can be reconstructed from different physical property models. To show how this reconstruction works, we simulated a complex geological system that comprises an original layered earth model that has passed several geological deformations and alteration overprints. Linear combination of complex geological features comprised three physical property distributions: Electrical resistivity, induced polarization chargeability, and magnetic susceptibility models. This study proposes a multivariate feature extraction approach to extract information about the underlying geological features comprising the bulk physical properties. We evaluated our method in numerical simulations and compared three feature extraction algorithms to see the tolerance of each method to the geological artifacts and noises. We show that the fast-independent component analysis (fast-ICA) algorithm by negentropy maximization is a robust method in the geological feature extraction that can handle the added unknown geological noises. The post-inversion physical properties are also used to reconstruct the underlying geological sources. We show that the sharpness of the inverted images is an important constraint on the feature extraction process. Our method successfully separates geological features in multiple 3D physical property models. This methodology is reproducible for any number of lithologies and physical property combinations and can recover the latent geological features, including the background geological patterns from overprints of chemical alteration.

Existing methods for building extraction from remotely sensed images strongly rely on aerial or satellite-based images with very high resolution, which are usually limited by spatiotemporally accessibility and cost. In contrast, relatively low-resolution images have better spatial and temporal availability but cannot directly contribute to fine- and/or high-resolution building extraction. In this paper, based on image super-resolution and segmentation techniques, we propose a two-stage framework (SRBuildingSeg) for achieving super-resolution (SR) building extraction using relatively low-resolution remotely sensed images. SRBuildingSeg can fully utilize inherent information from the given low-resolution images to achieve high-resolution building extraction. In contrast to the existing building extraction methods, we first utilize an internal pairs generation module (IPG) to obtain SR training datasets from the given low-resolution images and an edge-aware super-resolution module (EASR) to improve the perceptional features, following the dual-encoder building segmentation module (DES). Both qualitative and quantitative experimental results demonstrate that our proposed approach is capable of achieving high-resolution (e.g. 0.5 m) building extraction results at 2×, 4× and 8× SR. Our approach outperforms 8 other methods with respect to the extraction result of mean Intersection over Union (mIoU) values by a ratio of 9.38%, 8.20% and 7.89% with SR ratio factors of 2, 4, and 8, respectively. The results indicate that the edges and borders reconstructed in super-resolved images serve a pivotal role in subsequent building extraction and reveal the potential of the proposed approach to achieve super-resolution building extraction. Our code is available at https://github.com/xian1234/SRBuildSeg.

Atlantic salmon (Salmo Salar) is one of the fish species that rich in omega-3 fatty acids. Consumption of omega-3 fatty acids can lower down the risk of cardiovascular disease and coronary heart disease. The extraction of omega-3 fish oil from Atlantic salmon by using hexane and isopropanol was conducted in this research. Response Surface Methodology (RSM) was used to study the impact of parameters which were temperature (50-90°C), centrifuge speed (1000-3000rpm) and solvent ratio of hexane to isopropanol (0.5-1.5) to the percentage of oil yield. The results obtained shows that 15.23%± 0.61 of oil yield from Atlantic salmon under an optimum condition of 70°C, 3000 rpm and solvent ratio of hexane to isopropanol of 1.5. The acid value, peroxide value and p-anisidine value of the fish oil obtained were 7.48 mg KOH/g, 1.94 meq/kg and 5.56 respectively which were all within the acceptable limit which stipulated by Global Organization for EPA and DHA (GOED) and Food and Agricultural Organization of the United Nations (FAO). The FTIR analysis proved the presence of alkane and carboxylic acid in the fish oil. Furthermore, GC-MS analysis showed that the fish oil contains higher monounsaturated fatty acids (MUFA) contents followed by polyunsaturated fatty acids (PUFA) and 4.5525% of total omega-3 fatty acids.

Many classic visual monocular SLAM systems have been developed over the past decades, however, most of them will fail when dynamic scenarios dominate. DM-SLAM is proposed for handling dynamic objects in environments based on ORB-SLAM. The article mainly concentrates on two aspects. Firstly, DLRSAC is proposed to extract static features from the dynamic scene based on awareness of nature difference between motion and static, which is integrated into initialization of DM-SLAM. Secondly, we design candidate map points selection mechanism based on neighborhood mutual exclusion to balance the accuracy of tracking camera pose and system robustness in motion scenes. Finally, we conduct experiments in the public dataset and compare DM-SLAM with ORB-SLAM. The experiments verify the superiority of the DM-SLAM.

Many corner detector techniques have already been used in extracting information from UAV images to perform various photogrammetric and mapping activities. Among these techniques is the Feature from Accelerated Segment Test (FAST) and the Harris corner detector. It is widely agreed that the evaluation of detectors is of great importance because it evaluates and enhances the accuracy of the detected features. This research evaluates the performance of FAST-9 and FAST-12 as well as the Harris detector in terms of the repeatability rate, completeness, and correctness under different threshold values. Each method is evaluated in terms of its ability for detection UAV objects (crowd and cars features). Then the common detected features between both FAST versions and the Harris detector are extracted. This is to determine which method performs best under different image conditions (e.g., illumination variations, camera position and orientation, and image noise). The results show that the size of the threshold plays a crucial role in determining the number of detected feature points. An increase in the threshold value leads to a decrease in the number of detected points and vice versa. Thus, the correctness decreases whereas the completeness increases as a function of the threshold values. Furthermore, the relationship between the FAST-9 and the Harris detector is slightly better than those between the FAST-12 and the Harris detector. This is because the number of common features between the FAST-9 and the Harris detector are relatively higher than those between the FAST-12 and the Harris detector.

The objective to fast-track the mapping and registration of large numbers of unrecorded land rights globally, leads to the experimental application of Artificial Intelligence (AI) in the domain of land administration, and specifically the application of automated visual cognition techniques for cadastral mapping tasks. In this research, we applied and compared the ability of rule-based systems within Object Based Image Analysis (OBIA), as opposed to human analysis, to extract visible cadastral boundaries from Very high resolution (VHR) World View-2 image, in both rural and urban settings. From our experiments, machine-based techniques were able to automatically delineate a good proportion of rural parcels with explicit polygons where the correctness of the automatically extracted boundaries was 47.4% against 74.24% for humans and the completeness of 45% for machine, as against 70.4% for humans. On the contrary, in the urban area, automatic results were counterintuitive: even though urban plots and buildings are clearly marked with visible features such as fences, roads and tacitly perceptible to eyes, automation resulted in geometrically and topologically poorly structured data, that could neither be geometrically compared with human digitised, nor actual cadastral data from the field. These results provide an updated snapshot with regards to the performance of contemporary machine-drive feature extraction techniques compared to conventional manual digitising.

Bauxite residue is the voluminous by-product of alumina production after Bayer process. Its high alkalinity causes disposal problems and harmful environmental impacts. However, the residue contains significant amounts of valuable elements such as rare earth elements including scandium. Greek bauxite residue contains a high amount of scandium close to its main resources. Taking into account scandium limited availability coupled with its high demand in modern technology, bauxite residue could be considered as a potential resource for scandium recovery. In this study, the optimization of scandium extraction from bauxite residue with sulfuric acid is investigated using Taguchi methodology. Based on previous studies acid molarity, leaching time, solid/liquid ratio and reaction temperature were selected as control parameters for the selective Sc recovery. Method optimization targeted the highest concentration of scandium combined with the lowest concentration of iron without taking into account applications constraints. The predicted values resulted by Taguchi methodology were affirmed by a confirmation experiment conducted at optimal conditions. Regression analysis provided the respective equations to be applied on several conditions depending on different applications.

Introduction: Novel robotic surgery systems (da Vinci Xi) are superior to classical open and laparoscopic techniques with its clear and three-dimensional view. We aimed to present the first case low anterior resection of rectal cancer and vaginal specimen extraction with Da Vinci Xi.Case: A 75-year-old female patient with rectum adenocarcinoma was undergone robotic-assisted low anterior resection (LAR) of the rectum, vaginal removal of the specimen, colorectal anastomosis and loop ileostomy. The operation time was 190 minutes. There were no postoperative complications. Pathological tumor stage was stage pT1N0 with negative proximal, distal and radial resection margins. The patient was discharged on the third postoperative day.Conclusion: Robot-assisted LAR, total mesorectal excision, vaginal removal of the specimen, colorectal anastomosis, and loop ileostomy can be performed easily and safely with Da Vinci Xi at early stage rectal cancer. And the vaginal extraction of the specimen avoids us from a traditional abdominal incision.

Numerous protocols have been published for extracting DNA from phlebotomines. Nevertheless, their small size is generally an issue in terms of yield, efficiency, and purity, for large-scale individual sand fly DNA extractions when using traditional methods. Even though this can be circumvented with commercial kits, these are generally cost-prohibitive for developing countries. We encountered these limitations when analysing parasite infection in Lutzomyia spp. by PCR [1] and, for this reason, we evaluated various modifications on a previously published protocol ([2] and Acardi personal communication). The most significant variation was the use of a different lysis buffer [3] to which added Ca2+ (buffer TESCa), because this ion protects proteinase K against autolysis, increases its thermal stability, and could have a regulatory function for its substrate-binding site [4]. Individual sand fly DNA extraction success was confirmed by amplification reactions using internal control primers that amplify a fragment of the cacophony gene [5,6]. To the best of our knowledge, this is the first time a lysis buffer containing Ca2+ has been reported for the extraction of DNA from sand flies.

The aim of this paper is to develop an intelligent event-driven Electrocardiogram (ECG) processing module in order to achieve an efficient solution for diagnosis of the cardiac diseases. The suggested method acquires the signal with an event-driven A/D converter (EDADC). The output of EDADC is passed through the activity selection and interpolation blocks. It allows focusing only on the important signal parts and resampling it uniformly. Later on, the signal is de-noised. The autoregressive (AR) method is used to extract the classifiable features of the de-noised signal. Afterwards, the output is classified by employing different robust classification techniques such as support vector machines (SVMs), K- Nearest Neighbor (KNN) and Artificial Neural Network (ANN). The event-driven feature enables to adapt the system processing load according to the signal temporal variations. This interesting feature of the devised system aptitudes a drastic reduction in its processing activity and therefore in the power consumption as compared to the traditional ones. A comparison of the performance of different classifiers is also made in terms of accuracy. Results show that the proposed system is a potential candidate for an automatic diagnosis of the cardiac diseases.

Sports video analysis is an interesting and emerging field in the domain of computer vision. It has become a very popular subject among scholars all over the world in the last decade due to the need of automated classification of events such as offsides, in/out situations, goals and so on. The most important problem in sports video analysis is detection and tracking of ball and players. Extraction of court lines is also another important problem since it is necessary in the classification of aforementioned events. In this study, considering some of the previous work on the subject, we develop a method for tracking the ball and players in tennis videos where the camera position and orientation is supposed fixed.

Saliency detection in synthetic aperture radar (SAR) image is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR image. Firstly, we extract four features of SAR image as the input of the MSD model, which include the intensity, orientation, uniqueness and global contrast. Then, the saliency map is generated by the multitask sparsity pursuit (MTSP) which integrates the multiple features collaboratively. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps of the source images, an image fusion method is proposed for the SAR and color optical image fusion. The experimental results of real data show the proposed image fusion method is superior to the presenting methods in terms of several universal quality evaluation indexes, as well as in the visual quality. The salient areas in the SAR image can be highlighted and the spatial and spectral details of color optical image can also be preserved in the fusion result.

Comparative metatranscriptomics of bacterial and yeast communities of two milk kefir beverages (MKAA1 and MKAA2) obtained by fermentation with two different frozen stocks of the kefir grain CIDCA AGK1, and differing in rheological features and organic acid amounts production was carried out to figure out the relation between differences in physicochemical and rheological properties of kefir and the microbial active profile associated with each product. The dominance of lactic acid bacteria and yeast and a marginal amount of acetic acid bacteria marked the microbiome. The bacterial families Lactobacillaceae and Streptococcaceae account for almost all bacterial gene transcripts, with Lactobacillus helveticus, L. kefiranofaciens, L. gallinarum and Lactococcus lactis being most frequent in the microbiome of MKAA1 beverage, and L. kefiranofaciens, Lc. lactis and Leuconostoc mesenteroides being most prevalent in the MKAA2. Dipodascaceae and Saccharomycetaceae were the leading yeast families represented by Yarrowia lipolytica, Saccharomyces unisporus, and Kluyveromyces marxianus. The MKAA1 and MKAA2 shared >75% KEGG Ortologs (KO) in bacteria and yeast libraries. Considerable decreases in total expressed genes (KEGG Ortolog) assigned to Lactobacillus helveticus and L. gallinarum might be related to the variations in rheological features of the beverages, probably by compromising the interrelations with L. kefiranofaciens which might explain the variations in rheological features of the beverages.

Equine herpesvirus-1 (EHV-1) causes respiratory diseases, abortion, and encephalomyelitis in horses. EHV-1 immediate-early (IE) protein, essential for viral replication, is transactivated by the binding of a multiprotein complex including the open reading frame 12 (ORF12) and some host factors to the IE promoter region. Promoter-associated non-coding RNAs (pancRNAs), which are transcribed from bidirectional promoters, regulate the transcription of neighboring genes in mammals and pathogens. In this study, we identified a novel pancRNA transcribed from across the areas of the 5’-untranslated region and promoter of EHV-1 IE and named it IE pancRNA. IE pancRNA and mRNA were simultaneously expressed in EHV-1-infected RN33B-A68B2M cells. This pancRNA was also transcribed in RK13 and E. Derm cells, which are highly susceptible to EHV-1 infection. Furthermore, IE pancRNA upregulated IE gene expression in the presence of ORF12, and stable expression of IE pancRNA increased the number of EHV-1-infected RN33B-A68B2M cells. These results suggest that IE pancRNAs facilitate EHV-1 proliferation by promoting IE gene expression.

The incidence of hepatocellular carcinoma (HCC) is increasing and 40% of patients are diagnosed at advanced stages. Over the past 5 years, the number of clinical available treatments have dramatically increased for HCC, making patient management particularly complex. Immune checkpoint inhibitors (ICIs) have improved the overall survival of patients showing a durable treatment benefit over time, and a different response pattern with respect to tyrosine kinase inhibitors (TKIs). Although improved survival in responder cases, a sizeable group of patients are primary progressors or are ineligible for immunotherapy. Indeed, patients with non-viral etiologies, such non-alcoholic steatohepatitis (NASH), and alterations in specific driver genes might be less responsive to immunotherapy. Therefore, improving the comprehension of mechanisms of drug resistance and identifying biomarkers informative of the best treatment approach are required actions to improve patient survival. Numerous evidence indicated non-coding RNAs (ncRNAs) as pivotal players in cancer. Molecular mechanisms through which ncRNAs exert their effects in cancer progression and drug resistance have been widely investigated. Nevertheless, there are no studies summarizing the synergistic effect between ncRNA-based strategies and TKIs or ICIs in the preclinical setting. This review aims to provide up-to-date information regarding the possible use of ncRNAs as therapeutic targets in association with molecular targeted agents and immunotherapies and as predictive tools for the selection of optimized treatment options in advanced HCCs.

The Jeryak, a hybrid offspring of Gannan yak and Jersey cattle, exhibits evident hybrid advantages over the Gannan yak in terms of production performance and other various aspects. The small non-coding RNAs known as miRNAs exert a significant regulatory influence on gene expression post-transcriptionally. However, the regulatory mechanism of miRNA associated with muscle development in Jeryak remains elusive. To elucidate the regulatory role of miRNAs in orches-trating the skeletal muscle development in Jeryak, we selected dorsal longissimus muscle tissues from Gannan yak and Jeryak for transcriptome sequencing analysis. A total of 230 (DE)miRNAs and 1819 differentially expressed mRNAs (DEMs) were identified in the longest dorsal muscle of Gannan yak and Jeryak. The functional enrichment analysis revealed a significantly enrichment of target genes from differentially expressed (DE)miRNAs and DEMs in signaling pathways associ-ated with muscle growth, such as the Ras signaling pathway and the MAPK signaling pathway. The network of interactions between miRNA and mRNA suggested that some differentially ex-pressed miRNAs, including miR-2478-z, miR-339-x, novel-m0036-3p and novel-m0037-3p, played a pivotal role in facilitating muscle development. These findings help us to deepen our under-standing of the hybrid dominance of Jeryaks and provide a theoretical basis for further research on the regulatory mechanisms of miRNAs associated with Jeryak muscle growth and development.

Epitranscriptomics refers to post-transcriptional regulation of gene expression via RNA modifications and editing that affect RNA functions. Many kinds of modifications of mRNA have been described, among which N6-Methyladenosine (m6A), N1-methyladenosine (m1A), 7-methylguanosine (m7G), pseudouridine (Ψ), 5-methylcytidine (m5C). They alter mRNA structure and consequently stability, localization and translation efficiency. Perturbation of the epitranscriptome is associated with human diseases, thus opening the opportunity for potential manipulations as therapeutic approach. In this review, we overview the functional roles of epitranscriptomic marks in the skeletal muscle system, in particular in embryonic myogenesis, muscle cell differentiation and muscle homeostasis processes. Further, we explored high throughput epitranscriptome sequencing data to identify RNA chemical modifications in muscle-specific genes and we discuss the possible functional role and the potential therapeutic applications.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Abstract: Autophagy has a dual role in gliomagenesis in a microRNA-modulated environment. We investigated the potential relevance of autophagy in glioma development and survival by exploring the association of autophagy-associated genes and microRNAs in low- and high-grade gliomas. Real-time PCR (qPCR) was used to determine the expression of genes and microRNAs in 50 fresh glioma tissues while Formalin-fixed paraf-fin-embedded tissues of the same patients were used for immunohistochemistry. The Mann-Whitney U-test test, Spearman correlation test, and Kaplan-Meier survival analysis were performed to evaluate the expression, association, and overall survival in patients respectively. The expression of LC3, AKT, and miR-21 was increased in high-grade glioma compared to low-grade glioma while ULK2 expression was decreased in high-grade glioma. A strong positive correlation was observed for ULK2 with UVRAG, PTEN, miR-7, and miR-100, while the moderate correlation with mTOR, Beclin1, miR-30, miR-204, miR-374, miR-21 and miR-126 in low-grade glioma, while a moderate positive correlation between ULK2 and PI3K, PTEN, ULK1, VPS34, mTOR, Beclin1, UVRAG, AKT and miR-374, and between AKT and ULK1, VPS34, UVRAG, and miR-7 in high-grade gliomas. The low ULK2 and LC3 expression group was significantly associated with better overall survival in gliomas while miR-21 overexpression showed a poor prognosis in glioma patients. Therefore, miR-21, ULK2, and LC3 may serve as prognostic biomarkers for survival outcomes in glioblastoma.

Keywords: Y RNA; Canine hepatocellular carcinoma, canine hepatocellular adenoma

Inflammatory activation within the brain was linked to a decrease in cognitive abilities, however the molecular mechanisms implicated in the development of inflammatory-related cognitive dysfunction and its prevention are poorly understood. This study compared responses of hippocampal transcriptomes 3 months after the striatal infusion of lipopolysaccharide, alone (LPS; 30 µg) resulting in memory loss, or with dexamethasone (DEX; 5 mg/kg intraperitoneal) pretreatment, which abolished the long-term LPS-induced memory impairment. After LPS alone, a significant elevation in the expression of immunity/inflammatory-linked genes, including chemokine (Cxcl13), cytokines (Il1b, Tnfsf13b), and major histocompatibility complex (MHC) class II members (Cd74, RT1-Ba, RT1-Bb, RT1-Da, RT1-Db1) was revealed. DEX pretreatment did not change expression of these genes, but significantly affected expression of genes encoding ion channels, primarily calcium and potassium channels, regulators of glutamate (Slc1a2, Grm5, Grin2a) and GABA (Gabrr2, Gabrb2) neurotransmission which enriched in such GO biological processes as “Regulation of transmembrane transport”, “Cognition”, “Learning”, “Neurogenesis”, and “Nervous system development”. Taken together, the data suggest that: (1) pretreatment with DEX did not markedly affect LPS-induced prolonged inflammatory response; (2) DEX pretreatment can affect processes associated with glutamatergic signaling and nervous system development, possibly involved by that in the recovery of memory impairment induced by LPS

Kiwifruit is a perennial horticultural crop species with high nutritional and economic value. However, various pathogens stress brings a serious threat to kiwifruit. Pentatricopeptide repeat proteins (PPRs) are characterized by tandem repetitions of 35 amino acid motifs, and have been found to function in plant RNA editing. However, the roles of PPRs in plant development and disease resistance remain unclear. In this study, we performed a genome-wide identification and characterization of PPR gene family in two kiwifruit species (Actinidia chinensis (Ach), and Actinidia eriantha (Ace)) with markedly different disease resistance. A total of 497 and 499 PPRs were identified in Ach and Ace, respectively. All the kiwifruit PPRs could be phylogenetically divided into four subfamilies. There were about 40.68% PPRs predicted to be localized to mitochondria or chloroplasts. Synteny analysis showed that the expansion of kiwifruit PPRs mainly came from segmental duplication. Based on RNA-seq data from the fruit during 12 periods of development and maturity, weighted correlation network analysis suggested that two PPRs Actinidia20495.t1 and Actinidia15159.t1 were involved in the fruit development and maturation. In addition, we observed different gene expression of PPRs and chloroplast RNA editing profiles between resistant and susceptible kiwifruits after pathogen infection, indicating the roles of PPRs in stress response by modulating the editing extend of mRNA. The differentially expressed upstream transcription factors of PPRs were further identified, they may regulate resistance adaption by modulating the PPRs expression. These results provide a solid foundation for further analyses of the functions and molecular evolution of PPRs, in particular, for clarifying the resistance mechanisms in kiwifruits and breeding new cultivars with high resistance.

Background: It is assumed that the prevalence of hepatitis D in HBsAg-positive individuals reaches 4.5-13% in the world, and on average about 3% in Europe. Data from several European countries, including Slovakia, are missing or are from an older period. Methods: We analyzed all available data on hepatitis D from Slovakia, including reports from the Slovak Public Health Authority and the results of one prospective study, and three smaller surveys. The determination of anti-HDV IgG and IgM antibodies and/or HDV RNA was used to detect hepatitis D. Results: In the years 2005-2022, no confirmed case of acute or chronic HDV infection was reported in Slovakia. The presented survey includes a total of 343 patients, of which 126 were asymptomatic HBsAg carriers, 33 acute hepatitis B, and 184 chronic hepatitis B cases. In a recent prospective study of 206 HBsAg-positive patients who were completely serologically and virologically examined for hepatitis B and D, only 1 anti-HDV IgG positive and no anti-HDV IgM or HDV RNA positive cases were detected. In other smaller surveys, 2 anti-HDV IgG positive patients were found without the possibility of HDV RNA confirmation. In total, only 3 of 329 HBsAg-positive patients (0.91%) tested positive for anti-HDV IgG antibodies and none of 220 tested positive for HDV RNA. Conclusion: The available data show that Slovakia is one of the countries with a very low prevalence of HDV infection reaching less than 1% in HBsAg-positive patients. Routine testing for hepatitis D is lacking in Slovakia, and therefore it is necessary to implement testing of all HBsAg-positive individuals according to international recommendations.

The formation and development of potato tissues and organs is a complex process regulated by a variety of genes and environmental factors. However, the regulatory mechanisms underlying the growth and development are still unclear. In this study, we used autotetraploid potato JC14 as experimental subject to analyze the transcriptome of root, stem and leaf at seedling, tuber formation and tuber expansion stages to explore the spatio-temporal expression pattern of genes and genetic development characteristics. The results identified thousands of differentially expressed genes and KEGG pathway enrichment analysis showed that these genes were mainly involved in defense response and carbohydrate metabolism pathways. A total of 12 co-expressed Gene modules were identified by Weighted Gene Co-expression Network Analysis (WGCNA), and 4 modules were screened out with the highest correlation with potato stem developmental traits. Core genes in the network were further investigated and functionally annotated by computing the connectivity of genes within the module. The results unveiled number of hub genes in stems at different developmental stages, including carbohydrate metabolism related genes, the defense response related genes, and transcription factors. These findings provide important leads for further understanding of the molecular regulation and genetic mechanisms of potato tissue development.

Small RNAs (sRNA) are epigenetic regulators of essential biological processes that have been linked to the onset and progression of leukemia, including acute adult T-cell leukemia-lymphoma (ATLL) caused by the retrovirus Human T-lymphotropic virus type 1. Here, we describe the sRNA profile of a 30-year-old female with ATLL at diagnosis and after maintenance therapy, with the goal of correlating their expression levels with response to therapy.

Iron is the most abundant micronutrient in plant mitochondria and it has a crucial role in biochemical reactions involving electron transfer. It has been described in Oryza sativa that Mitochondrial Iron Transporter (MIT) is an essential gene and that knockdown mutant rice plants have a decreased amount of iron in mitochondria, strongly suggesting that OsMIT is involved in mitochondrial iron uptake. In Arabidopsis thaliana, two genes encode MIT homologues. In this study, we analyzed different AtMIT1 and AtMIT2 mutant alleles, confirming that individually AtMIT1 nor AtMIT2 genes are essential. When we generated crosses between Atmit1 and Atmit2 alleles we were able to isolate homozygous double mutant plants. Interestingly, homozygous double mutant plants were obtained only when mutant alleles of Atmit2 with the T-DNA insertion in the intron region were used for crossings, and in these cases a correctly spliced AtMIT2 mRNA was generated, although at a low level. Atmit1 Atmit2 double homozygous mutant plants, which were knockout for AtMIT1 and knockdown for AtMIT2, were grown and chacterised in iron sufficient conditions. Pleiotropic developmental defects were observed including abnormal seeds, increased number of cotyledons, slow growth rate, pinoid stems, defects in flower structures and reduced seed set. We observed a possible phenomenon of T-DNA suppression in the next generation of Atmit1 Atmit2 double homozygous mutant plants, correlating with an increased splicing of the AtMIT2 intron containing the T-DNA. Molecular analysis of gene expression markers for mitochondrial and oxidative stress showed that Atmit1 Atmit2 double homozygous mutant plants express a degree of mitochondrial perturbation. A RNA-Seq study was performed and we could identify more than 760 genes differentially expressed in Atmit1 Atmit2, including genes involved in iron transport, coumarin metabolism, and hormones metabolism, transport and signaling. Our data suggest that some of the phenotypes observed in Atmit1 Atmit2 double homozygous mutant plants are mediated by defects in auxin homeostasis.

Multisubunit RNA polymerases (RNAP) carry out transcription in all domains of life; during vi-rus infection, RNAPs are targeted by transcription factors encoded by either the cell or the virus, resulting in the global repression of transcription with distinct outcomes for different host-virus combinations. These repressors serve as versatile molecular probes to study RNAP mechanisms, as well as they aid the exploration of druggable sites for the development of new antibiotics. Here, we review the mechanisms and structural basis of RNAP inhibition by the viral repressor RIP and the crenarchaeal negative regulator TFS4, which follow distinct strategies. RIP operates by occluding the DNA-binding channel and mimicking the initiation factor TFB/TFIIB. RIP binds tightly to the clamp and locks it into one fixed position, thereby preventing conformational oscil-lations that are critical for RNAP function as it progresses through the transcription cycle. TFS4 engages with RNAP in a similar manner to transcript cleavage factors such as TFS/TFIIS through the NTP-entry channel; TFS4 interferes with the trigger loop and bridge helix within the active site by occlusion and allosteric mechanisms, respectively. The conformational changes of RNAP described above are universally conserved and are also seen in inactive dimers of eukaryotic RNAPI and several inhibited RNAP complexes of both bacterial and eukaryotic RNA polymer-ases, including inactive states that precede transcription termination. A comparison of target sites and inhibitory mechanisms reveals that proteinaceous repressors and RNAP-specific antibiotics use surprisingly common ways to inhibit RNAP function.

Cutaneous Melanoma (CM) is the most lethal form of skin cancer if it becomes metastatic, where treatment options and survival chances decrease dramatically. Immunotherapy treatments based on the immunologic checkpoint inhibitors (PD-1 and CTLA4) constituted a main breakthrough in the treatment of metastatic CM, particularly in the long-term benefit. However, several molecular pathways are responsible for the failure of this strategy in about 50-70% of CM patients. Some Long Non-coding RNAs (lncRNAs), and circular RNAs (circRNA) are implicated in triggering pro- and antitumorigenic responses to various cancer treatments. The relationship between lncRNA, circRNA and Immune Checkpoint Blockade (ICB) immunotherapy is not extensively explored in cutaneous metastatic melanoma (CMM). The aim of this study is to evaluate the potential role of both circRNA and lncRNA as a predictive immunotherapy biomarker in CMM. RNA-seq from 12 FFPE samples from the metastatic biopsy of metastatic melanoma patients treated with Nivolumab were analyzed. Our findings indicate that specific lncRNA and circRNA are involved in regulatory networks of the immune response against metastatic melanoma under treatment with nivolumab. Moreover, we have established a risk score that allows the prediction of Overall survival (OS) and Progression-free survival (PFS) of CMM patients with high accuracy. This proof of principle work provides a possible insight on the function of ceRNA, contributing to decipher the complex molecular mechanism of ICB cancer treatment response.

The mosaic disease in maize is caused by Sugarcane mosaic virus (SCMV), a member of the Potyviridae family. The best strategy to cope with viral infections is the use of disease-resistant maize lines. To better understand the resistance response to SCMV, we analyzed differentially expressed genes among a resistant line (CI-RL1), a susceptible line (B73), and the F1 progeny from a cross between both lines using RNA-Seq data. We also analyzed transcript expression pattern clustering to allocate previously reported resistance candidate genes. GO enrichment analysis of biological processes highlighted a strong regulation in ROS detoxification in both the susceptible and resistant lines. The enrichment of cellular components led to the identification of an integral component of the plasma membrane in the RL line. Transcript expression patterns provide evidence of the importance of host translation in virus response, showing the diverse and complex behavior of eIF4E homologs and the presence of eleven eEF1α factors in maize. In addition, we identified two genes putatively implied in long-distance movement: ZmPiezo and ZmPVIP1. Finally, we propose an ABC transporter to be associated with viral resistance.

The provenance of the aminoacyl-tRNA synthetases (aaRS) poses challenging questions because of their role in the emergence and evolution of genetic coding. We investigate evidence about their ancestry from curated structure-based multiple sequence alignments of a structurally invariant “scaffold” shared by all 10 canonical Class I aaRS. Three uncorrelated phylogenetic metrics—residue-by-residue conservation, its variance, and row-by-row cladistic congruence—imply that the Class I scaffold is a mosaic assembled from distinct, successive genetic sources. These data are especially significant in light of: (i) experimental fragmentations of the Class I scaffold into three partitions that retain catalytic activities in proportion to their length; and (ii) evidence that two of these partitions arose from an ancestral Class I aaRS gene encoding a Class II ancestor in frame on the opposite strand. Phylogenetic metrics of different modules vary in accordance with their presumed functionality. A 46-residue Class I “protozyme” roots the Class I molecular tree prior to the adaptive radiation of the Rossmann dinucleotide binding fold that refined substrate discrimination. Such rooting is consistent with near simultaneous emergence of genetic coding and the origin of the proteome, resolving a conundrum posed by previous inferences that Class I aaRS evolved long after the genetic code had been implemented in an RNA world. Further, pinpointing discontinuous enhancements of aaRS fidelity establishes a timeline for the growth of coding from a binary amino acid alphabet.

MiRNAs are 20-22 nucleotide long single-stranded non-coding RNA sequences, which can regulate post transcriptional activity of mRNA by binding with it at 3’UTR region (untranslated region). Thus deregulation of miRNA expression is responsible for dysregulating mRNA function which contributes in developing various diseases as well as cancerous phenotypes. Alteration of single nucleotide in miRNA sequence is one of the reasons behind deregulation of miRNA expression. The most frequent carcinoma in current day is breast cancer which causes a high mortality among women around the world as well as India. Despite of the advancement of diagnostic tools, strategies and treatment, the cases of breast cancer is increasing every year. There are plenty of biomarkers like ER, PR, Her2, Ki-67, etc available which are frequently used in diagnosis and treatment of breast cancer. After the discovery of MiRNA in 1993 in Caenorhabiditis elegans, it is attracting all the limelight in diagnosis and treatment of different carcinomas as well as breast cancer. In this review we will discuss on involvement of different types of MiRNAs and miR SNPs in breast cancer occurrence and susceptibility in a detailed manner.

The advancement of precision medicine critically depends on the robustness and specificity of the carriers used for the targeted delivery of effector molecules in the human body. Numerous nanocarriers have been explored in vivo, to ensure the precise delivery of molecular cargos via tissue-specific targeting, including the endocrine part of the pancreas, thyroid, and adrenal glands. However, even after reaching the target organ, the cargo-carrying vehicle needs to enter the cell and then escape from lysosomal destruction. Most of artificial nanocarriers suffer from intrinsic limitations that either prevent them from completing the specific delivery of the cargo. In this respect, extracellular vesicles (EVs) seem to be the natural tool for payload delivery due to their versatility and low toxicity. However, EV-mediated delivery is not selective and usually short-ranged. By inserting the viral membrane fusion proteins into exosomes, it is possible to increase the efficiency of membrane recognition and also ease the process of membrane fusion. This review describes the molecular details of the viral-assisted interaction between the target cell and extracellular vesicles. We also discuss the question of the usability of viral fusion proteins in developing extracellular vesicle-based nanocarriers with higher efficacy of payload delivery. Finally, this review specifically highlights the role of Gag and RNA binding proteins in RNA sorting into extracellular vesicles.

The major threats to the sustainable supply of forest tree products are adverse climate, pests and diseases. Climate change, exemplified by increased drought, poses a unique threat to global forest health. This is attributed to the unpredictable behavior of forest pathosystems, which can favor fungal pathogens over the host under persistent drought stress conditions in the future. Currently, the effects of drought on tree resistance against pathogens are hypothetical, thus research is needed to identify these correlations. Norway spruce (Picea abies) is one of the most economically important tree species in Europe, and is considered highly vulnerable to changes in climate. Dedicated experiments to investigate how disturbances will affect the Norway spruce - Heterobasidion sp. pathosystem are important, in order to develop different strategies to limit the spread of H. annosum s.l. under the predicted climate change. Here, we report a transcriptional study to compare Norway spruce gene expressions to evaluate the effects of water availability and the infection of Heterobasidion parviporum. We performed inoculation studies of three-year-old saplings in a greenhouse (purchased from a nursery). Norway spruce saplings were treated in either high (+) or low (-) water groups: high water group received double the water amount than the low water group. RNA was extracted and sequenced. Similarly, we quantified gene expression levels of candidate genes in biotic stress and jasmonic acid (JA) signaling pathways using qRT-PCR, through which we discovered a unique preferential defense response of H. parviporum-infected Norway spruce under drought stress at the molecular level. Disturbances related to water availability, especially low water conditions can have negative effects on the tree host and benefit the infection ability of the pathogens in the host. From our RNA-seq analysis, 114 differentially expressed gene regions were identified between high (+) and low (-) water groups under pathogen attack. None of these gene pathways were identified to be differentially expressed from both non-treated and mock-control treatments between high (+) and low (-) water groups. Finally, only four genes were found to be associated with drought in all treatments.

In this letter we investigate if SARS-CoV-2 RNA is involved in the increased ageing of alveolar cells. Our in silico study is explorative. With the results we are able to outline experiments with AEC2 repair of bleomycin damaged alveolar cells. If AEC2 repair capability is diminished by spike RNA then perhaps this result provides a first step on a route to treat immortal lung cancer cells.

Muscle is one of the most critical organs for mammals, which governs multiple movement and physiological functions. Circular RNA (circRNA) is a kind of novel endogenous RNA without 5'-Caps and 3'-poly(A) structures formed by pre-mRNA's back-splicing. RNA binding proteins (RBPs) control the production and degradation of circRNA, help nucleus-cytoplasm transport and locate circRNA, and regulate circRNA translation. Therefore, circRNAs and the chaperoned RBPs play critical roles in muscle growth, development, and disease progression. In this review, we systematically characterize the possible molecular mechanism of circRNA-protein interactions. Also, we summarize the latest researches on circRNA-protein interactions in muscle development and diseases. Besides, we provide several valid prediction methods and experimental verification approaches. Our review reveals the importance of circRNAs and their protein chaperones and provides a reference for further study in this field.

Many positive sense RNA viruses, especially those infecting plants, are known to experience stringent, stochastic population bottlenecks inside the cells they invade, but exactly how and why these populations become bottlenecked are unclear. A model proposed ten years ago advocates that such bottlenecks are evolutionarily favored because they cause the isolation of individual viral variants in separate cells. Such isolation in turn allows the viral variants to manifest the phenotypic differences they encode. Recently published observations lend mechanistic support to this model, and prompt us to refine the model with novel molecular details. The refined model, designated Bottleneck, Isolate, Amplify, Select (BIAS), postulates that these viruses impose population bottlenecks on themselves by encoding bottleneck-enforcing proteins (BNEPs) that function in a concentration-dependent manner. In cells simultaneously invaded by numerous virions of the same virus, BNEPs reach the bottleneck-ready concentration sufficiently early to arrest nearly all internalized viral genomes. As a result, very few (as few as one) viral genomes stochastically escape to initiate reproduction. Repetition of this process in successively infected cells isolate viral genomes with different mutations in separate cells. This isolation prevents mutant viruses encoding defective viral proteins from hitchhiking on sister genome-encoded products, leading to the swift purging of such mutants. Importantly, genome isolation also ensures viral genomes harboring beneficial mutations accrue the cognate benefit exclusively to themselves, leading to the fixation of such beneficial mutations. Further interrogation of the BIAS hypothesis promises to deepen our understanding of virus evolution, and inspire new solutions to virus disease mitigation.

Streptococcus suis is a zoonotic pathogen causing serious infections in both swine and humans. Although metals are essential for life, excess amounts of metals they are toxic to bacteria. when accumulated in excess amounts. Except for zinc, Transcriptome-level data of the mechanisms for resistance to metal-induced toxicity in S. suis are available for no metals other than zinc. have not been investigated from the transcriptome level in S. suis. Herein, we explored the transcriptome-level changes of in S. suis in response to ferrous iron and cobalt toxicity by RNA sequencing. Many A lot of genes were differentially expressed in the presence of excess ferrous iron and cobalt. Most of the genes in response to cobalt toxicity showed the same expression trends as those were expressed in the same trend in response to ferrous iron toxicity. qRT-PCR analysis of the selected genes confirmed the accuracy of RNA sequencing results. Bioinformatics analysis of the differentially expressed genes indicated that ferrous iron and cobalt have similar impacts effects on the cellular processes of S. suis. Treatment with ferrous Ferrous iron treatment resulted in down-regulation of several oxidative stress tolerance-related genes involved in oxidative stress tolerance and up-regulation of the genes in an amino acid ABC transporter operon. Expression of the several genes in the arginine deiminase system was down-regulated in the presence of after ferrous iron and cobalt treatment. Collectively, our results suggested that S. suis alters the expression of a lot of multiple genes to respond to ferrous iron and cobalt toxicity.

Abstract: Long noncoding RNAs (lncRNAs) are deregulated in human cancers and are associated with disease progression. Plasmacytoma Variant Translocation 1 (PVT1), an lncRNA, is located adjacent to MYC, linked to multiple myeloma (MM). PVT1 is expressed in MM and is associated with carcinogenesis, however, its role and regulation machinery remain uncertain. We examined PVT1/MYC expression through real time PCR in plasma cells purified from 59 MGUS and 140 MM patients. MM cell lines KMS11, KMS12PE, OPM2, and RPMI8226 were treated with JQ1, a MYC superenhancer inhibitor, or MYC inhibitor 10058-F4. The expression levels of PVT1 and MYC were significantly higher in MM than in MGUS (p < 0.0001), and showed positive correlation with disease progression (r = 0.394, p < 0.0001). JQ1 inhibited cell proliferation and decreased the expression levels of MYC and PVT1. However, 10054-F4 did not alter the expression level of PVT1. The positive correlation between MYC and PVT1 in patients, synchronous downregulation of MYC and PVT1 by JQ1, and no effect of MYC inhibitor on PVT1 expression suggest that the expression of these two genes is coregulated by a superenhancer. Cooperative effects between these two genes may contribute to MM pathogenesis and progression.

Long non-coding RNA (lncRNA) can regulate several aspects of gene expression, being associated with complex phenotypes in humans and livestock species. In taurine beef cattle, recent evidence points to the involvement of lncRNA in feed efficiency (FE), a proxy for increased productivity and sustainability. Here, we hypothesized specific regulatory roles of lncRNA in FE of indicine cattle. Using RNA-Seq data from liver, muscle, hypothalamus, pituitary and adrenal gland from Nellore bulls with divergent FE, we submitted new transcripts to a series of filters to confidently predict lncRNA. Then, we identified lncRNA that were differentially expressed (DE) and/or key regulators of FE. Finally, we explored lncRNA genomic location and interactions with miRNA and mRNA to infer potential function. We were able to identify 126 relevant lncRNA for FE in Bos indicus, some with high homology to previously identified lncRNA in Bos taurus and some possible specific regulators of FE in indicine cattle. Moreover, lncRNA identified here were linked to previously described mechanisms related to FE in hypothalamus-pituitary-adrenal axis and are expected to help elucidate this complex phenotype. This study contributes to expanding the catalogue of lncRNA, particularly in indicine cattle, and identifies candidates for further studies in animal selection and management.

This study aimed to rank cancers by the strength of relationship between comprehensive mRNA expression of the most harmful or protective genes and patient survival. Using TCGA dataset including RNA-SEQ and clinical data, we investigated not only gene specific prognostic availability, but also comprehensive prognostic availability of prognostic genes filtered by cox coefficient, and ranked cancers by specially designed prognostic indicator. Through Kaplan-Meier plots, we checked that cancers vary in the strength of influence of prognostic genes, and they follow as the rank. Developing treatment with method to reduce or increase expression of biomarkers for specific cancer which ranked bottom, it would be not efficient in high probability. The results of this study can be a scientific evidence for that.

Chronic gastro-abdominal pain with altered bowel habits are associated with pathologies including gastroenteritis, autoimmune and inflammatory bowel disease, and irritable bowel syndrome (IBS). In IBS, diagnostic evidence of infection or inflammation are absent, yet symptoms nonetheless include chronic abdominal pain and alterations of stool frequency and consistency, with most common subtypes including diarrhea-predominant (IBS-D) or constipation predominant (IBS-C). [1, 2] IBS is a common clinical complaint in westernized nations, with females more frequently diagnosed than males [3]. Obesity is also associated with increased likelihood of chronic pain [4], and is associated with intestinal dysbiosis, and systemic inflammatory signatures [5]. Improving personalized medicine therefore requires patient stratification based on a combination of biological factors contributing to the individual’s symptom and biomarker spectrum. The “buffy coat” method isolates leukocytes and PBMCs from whole blood, comprises the immune cell population in peripheral blood. These cells are relatively inactive but are primed to respond to generalized and localized immune activation signals; they are under active investigation as diagnostic biomarkers [6]. Collection of buffy coat is a standard method in clinical laboratories; detection of immune activation via RNA expression biomarkers will be informative of differential biological response, and be tractable to collect in clinical settings. Results of differential expression, pathway analysis, and cell-type abundance analysis from buffy coat RNA, is presented here using variables for BMI, Gender, and IBS-subtype from publicly available Nanostring RNA expression and phenotypic data from the NCBI GEO database.

Removal of the proliferation component of gene expression by PCNA adjustment has been addressed in numerous survival prediction studies for breast cancer and all cancers in the TCGA. These studies indicate that widespread co-regulation of proliferation upwardly biases survival prediction when gene selection is performed on a genome-wide basis. In addition, removal of the correlative effects of proliferation does not reduce the random bias associated with survival prediction using random gene selection. Since most cancers become addicted to DNA repair as a result of forced cellular replication, increased oxidation, and repair deficiencies from oncogenic loss or genetic polymorphisms, we pursued an investigation to remove the proliferation component of expression in DNA repair genes to determine survival prediction. This translational hypothesis-driven focus on DNA repair genes is directly amenable to finding new sets of DNA repair genes that could potentially be studied for inhibition therapy. Overall survival (OS) prediction was evaluated in 18 cancers by using normalized RNA-Seq data for 126 DNA repair genes with expression available in TCGA. Transformations for normality and adjustments for age at diagnosis, stage, and PCNA metagene expression were performed for all DNA repair genes. We also analyzed genomic event rates (GER) for somatic mutations, deletions, and amplification in driver genes and DNA repair genes. After performing empirical p-value testing with use of randomly selected gene sets, it was observed that OS could be predicted significantly by sets of DNA repair genes for 61% (11/18) of the cancers. Interestingly, PARP1 was not a significant predictor of survival for any of the 11 cancers. Results from cluster analysis of GERs indicates that the most opportunistic cancers for inhibition therapy may be AML, colorectal, and renal papillary, because of potentially less confounding due to lower GERs for mutations, deletions, and amplifications in DNA repair genes. However, the most opportunistic cancer for inhibition therapy is likely to be AML, since it showed the lowest GERs for mutations, deletions, and amplifications in DNA repair genes. In conclusion, our hypothesis-driven focus to target DNA repair gene expression adjusted for the PCNA metagene as a means of predicting OS in various cancers resulted in statistically significant sets of genes.

Peanut (Arachis hypogaea) is a crop plant with high economic value, but the epigenetic regulation of its growth and development has only rarely been studied. The peanut histone deacetylase 1 gene (AhHDA1) has been isolated and is known to be ABA- and drought-responsive. In this paper, we investigate the role of AhHDA1 in more detail, focussing on the effect of altered AhHDA1 expression in hairy roots at both the phenotypic and transcriptional levels. Agrobacterium rhizogenes-mediated transformation of A. hypogaea hairy roots was used to analyse how overexpression or RNA interference of AhHDA1 affects this tissue. In both types of transgenic hairy root, RNA sequencing was adopted to identify genes that were differentially expressed, and these genes were assigned to specific metabolic pathways. AhHDA1-overexpressing hairy roots were growth-retarded after 20 d in vitro cultivation, and superoxide anions and hydrogen peroxide accumulated to a greater extent than in control or RNAi groups. Overexpression of AhHDA1 is likely to accelerate flux through various secondary synthetic metabolic pathways in hairy roots, as well as reduce photosynthesis and oxidative phosphorylation. Genes encoding the critical enzymes caffeoyl-CoA O-methyltransferase (Araip.XGB85) and caffeic acid 3-O-methyltransferase (Araip.Z3XZX) in the phenylpropanoid biosynthesis pathway, chalcone synthase (Araip.B8TJ0) and polyketide reductase (Araip.MKZ27) in the flavonoid biosynthesis pathway, and hydroxyisoflavanone synthase (Araip.0P3RJ) and isoflavone 2'-hydroxylase (Araip.S5EJ7) in the isoflavonoid biosynthesis pathway were significantly upregulated by AhHDA1 overexpression, while their expression in AhHDA1-RNAi and control hairy roots remained at a lower level or was unchanged. Our results suggest that alteration of secondary metabolism activities is related to overexpression of AhHDA1, which is mainly reflected in phenylpropanoid, flavonoid and flavonoid biosynthesis. Future studies will focus on the function of AhHDA1 interacting proteins and their action on cell growth and stress responses.

Recently, selection in pigs has been focused on improving the lean meat content in carcasses; this focus has been most evident in breeds constituting a paternal component in breeding. Such sire-breeds are used to improve the meat quantity of cross-breed pig lines. However, even in one breed, a significant variation in the meatiness level can be observed. In the present study, the comprehensive analysis of genes and microRNA expression profiles in porcine muscle tissue was applied to identify the genetic background of meat content. The comparison was performed between whole gene expression and miRNA profiles of muscle tissue collected from two sire-line pig breeds (Piertain, Hampshire). The RNA-seq approach allowed the identification of 627 and 416 differentially expressed genes (DEGs) between pig groups differing in terms of loin weight between Pietrain and Hampshire breeds, respectively. The comparison of miRNA profiles showed differential expression of 57 microRNAs for Hampshire and 34 miRNAs for Pietrain pigs. Next, 43 genes and 18 miRNAs were selected as differentially expressed in both breeds and potentially related to muscle development. According to Gene Ontology analysis, identified DEGs and microRNAs were involved in the regulation of the cell cycle, fatty acid biosynthesis and regulation of the actin cytoskeleton. The most deregulated pathways dependent on muscle mass were the Hippo signalling pathway connected with the TGF-beta signalling pathway and controlling organ size via the regulation of ubiquitin-mediated proteolysis, cell proliferation and apoptosis. The identified target genes were also involved in pathways such as the FoxO signalling pathway, signalling pathways regulating pluripotency of stem cells and the PI3K-Akt signalling pathway. The obtained results indicate molecular mechanisms controlling porcine muscle growth and development. Identified genes (SOX2, SIRT1, KLF4, PAX6 and genes belonging to the transforming growth factor beta superfamily) could be considered candidate genes for determining muscle mass in pigs.

Non-coding RNA regions have long been considered the "dark matter" of the genome, with their significance in gene regulation remaining enigmatic. However, recent advances in genomics and molecular biology have illuminated the pivotal role that non-coding RNA regions play in the fine-tuned orchestration of hemoglobin expression. Hemoglobin, the oxygen-carrying protein vital for life, is tightly regulated, and any disruption in its production can lead to severe medical conditions, such as hemoglobinopathies. This review delves into the intricate world of non-coding RNA regions, exploring how they act as master conductors in controlling hemoglobin gene expression. We will discuss various classes of non-coding RNAs, including long non-coding RNAs, microRNAs, and circular RNAs, and their specific mechanisms in fine-tuning hemoglobin levels. Additionally, we will highlight emerging therapeutic approaches that target non-coding RNA regions to ameliorate hemoglobin-related disorders. Understanding the critical role of non-coding RNA regions in hemoglobin regulation opens new avenues for precision medicine and gene therapies, offering hope for those affected by hemoglobinopathies and related conditions. This comprehensive review sheds light on the significance of these non-coding RNA regions, demonstrating that the "silent" players in the genome are, in fact, the conductors of harmony in the symphony of hemoglobin regulation.

RNA polymerase II (RNAPII) frequently transcribes non-protein coding DNA sequences in eukaryotic genomes into long non-coding RNA (lncRNA). Here, we focus on the impact of the act of lncRNA transcription on nearby functional DNA units. Distinct molecular mechanisms linked to the position of lncRNA relative to the coding gene illustrate how non-coding transcription controls gene expression. We review the biological significance of the act of lncRNA transcription on DNA processing, highlighting common themes, such as mediating cellular responses to environmental changes. This review presents the background in chromatin signaling to appreciate examples in different organisms where we can interpret functions of non-coding DNA through the act of RNAPII transcription.

To examine the role of RNA silencing in defense against viroid, a Dicer-like 2 and 4 (DCL2&4)—double knockdown transgenic tomato line 72E was created. The expression of endogenous DCL2 and DCL4 in line 72E decreased to about a half of the empty cassette line EC. When challenged with potato spindle tuber viroid (PSTVd), 72E allowed significantly higher level of PSTVd accumulation early in infection and showed lethal systemic necrosis. The size distribution of PSTVd-derived small RNA was significantly changed: the numbers of 21 and 22 nucleotides (nt) species in line 72E was approximately 66.7% and 5% of those in line EC, respectively. Conversely, the numbers of 24-nt species increased by 1100%. Furthermore, expression of miR398a-3p and miR398 increased 770–868% in the PSTVd-infected 72E, compared to the PSTVd-infected EC. In parallel, superoxide dismutase (SOD1) in PSTVd-infected 72E showed higher expression levels. In concert with miR398a-3p, SOD1 controls detoxification of reactive oxygen species (ROS) generated in cells. Since high levels of ROS production and its scavenging activity were observed in PSTVd-infected 72E, the lack of full-activity of DCLs was thought to have made the plant incapable to control excessive ROS production and thus resulted in to develop lethal systemic necrosis.

Blackcurrant leaf chlorosis associated virus (BCLCaV) was detected recently by next-generation sequencing (NGS) and proposed as a new and distinct species in the genus Idaeovirus. Genomic components of BCLCaV that were detected and confirmed include: 1) RNA-1 that is monocistronic and encodes the replicase complex; 2) a bicistronic RNA-2 that encodes a movement protein (MP) and the coat protein (CP) of the virus, with open reading frames (ORF) that overlap by a single adenine (A) nucleotide (nt) representing the third position of an opal stop codon of the MP ORF2a and the first position of the start codon of the CP ORF2b; 3) a subgenomic form of RNA-2 (RNA-3) that contains ORF2b; and 4) a concatenated form of RNA-2 that consists of a complementary and inverted RNA-3 conjoined to the full-length RNA-2. Analysis of NGS-derived paired-end reads revealed the existence of bridge reads encompassing the 3’-terminus and 5’-terminus of RNA-2 or RNA-3 of BCLCaV. The full RNA-2 or RNA-3 could be amplified using outward facing or abutting primers; also RNA-2/RNA-3 could be detected even after three consecutive RNase R enzyme treatments with denaturation at 95 ^oC preceding each digestion. Evidence was obtained indicating that there are circular forms of BCLCaV RNA-2 and RNA-3.

In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.

Lavander distillation leads to huge quantities of solid waste produced yearly. This waste is usually discarded resulting in serious environmental issues. However, it still contains residual essential oil and other bioactive compounds. This research reports on the development and comparison of optimized solid-liquid separation methods, i.e. microwave (MAE) and ultrasound assisted extraction (UAE) of phenolic compounds from lavender distillation waste. Optimal pretreatment conditions, such as waste moisture content and particle size were also determined. The extracts were spray or freeze-dried and the resulting powders were characterized for their physicochemical properties. The majority of the original phenolic compounds in lavender were found in the leachate fraction after distillation (61%), while 43% in the solid waste. Drying of the solid waste before extraction affected the process efficiency. UAE led to higher phenolic content and antioxidant properties compared to MAE. Drying (spray or freeze) the extracts did not significantly affect their phenolic content, while the use of maltodextrin as a drying agent improved the drying process yield especially in the freeze-drying method. It is concluded that valorization of lavender distillation wastes can be achieved via an integrated process consisting of a green extraction method and a consequent drying process that result in a stable bioactive powder.

German chamomile galenic preparations are used to treat mild skin diseases, inflammation and spasms, and they have also reported to have anxiolytic and sedative effects. The medicinal use of chamomile is well-known in ethnomedicine. Since chamomile has shown to have some adverse effects, there is a need to develop new formulations, such as dry extracts, for the present herb. The aims of this study were (1) to develop a novel method for preparing essential oils and dry extracts from German chamomile flowers, (2) to reveal the phytochemical composition of such extracts, and (3) to verify the analgesic and soporific activity of extracts in vivo with a rodent animal model. Furthermore, our study aims to gain knowledge of the ethnomedical status of chamomile in the past and presence. Essential oils and dry extracts were successfully prepared from the tincture and aqueous extracts obtained after hydrodistillation and from a tincture powder. Total 22 phenolic compounds (7 hydroxycinnamic acids, 13 flavonoids and 2 phenolic acids), were found in the dry extracts by using UPLC-MS/MS. Total 9 main terpenoids were identified in the chamomile oil, and these terpenoids represent the chemotype rich in bisabolol oxides A and B. In the highest yield, the ratio of phenolic compounds and extract was in the range of 1:14-1:16 and triple extraction was performed. In in-vivo studies with mice and rats, the extracts showed analgesic activity and improvements in sleep. The highest sedative effect in rodents was found with the extract prepared by using a 70% aqueous ethanol solution for extraction. The administration of such extract at the dose of 50 mg/kg significantly prolonged the sleeping time in rats.

Biomass as a whole offers a more diverse potential for valorisation than any other renew-able energy source. As one of the stages in the separation of bio-oil involves the liquid mixture of acetol and acetic acid, and as both components are particularly well suited for valorisation, a hybrid method has been developed for their separation with a high purity level through an approach combining liquid-liquid extraction and rectification. In order to design and simulate the flowsheet, the ChemCAD 7.0 simulation software has been used. Sensitive analyses have been carried out to investigate the influence of the different pa-rameters in the rectification columns such as the reflux ratio, the feed stage location, and the vapour/bottom molar flow ratio. The effect of different extractants and of their excess on the separation process as well as the possibility of regenerating the extractant has also been studied. Tri-n-octylamine has accordingly been selected as a separating agent which has been fully recycled. The end result for separating an initial 48/52 wt% ace-tol/acetic-acid liquid mixture has been acetol with a purity of 99.4 wt% and acetic acid with a purity of 100 wt%.

Fire outbreaks continue to cause damage despite the improvements in fire-detection tools and algorithms. It is still challenging to implement a well performing and optimized approach, which is sufficiently accurate, and has tractable complexity and low false alarming rate. Small amount of fire and identification of fire from a long distance is also a challenge in previously proposed techniques. In this study, we propose a novel hybrid model based on Convolutional Neural Networks (CNN) to detect and analyze fire intensity. 21 convolutional layers, 24 Rectified Linear Unit (ReLU) layers, 6 pooling layers, 3 fully connected layers, 2 dropout layers, and a softmax layer are included in the proposed 57-layer CNN model. Our proposed model performs instance segmentation in order to distinguish between fire and non-fire events. To reduce the intricacy of the proposed model, we also propose a key-frame extraction algorithm. The proposed model uses Internet of Things (IoT) devices to alert the relevant person by calculating the severity of fire. Our proposed model is tested on a publicly available dataset having fire and normal videos. The achievement of 95.25 % classification accuracy, 0.09% False Positive Rate (FPR), 0.65 percent False Negative Rate (FNR), and a prediction time of 0.08 seconds validates the proposed system.

Machinery degradation assessment can offer meaningful prognosis and health management in-formation. Although numerous machine prediction models based on artificial intelligence have emerged in recent years, they still face a series of challenges: (1) Many models continue to rely on manual feature extraction. (2) Deep learning models still struggle with long sequence prediction tasks. (3) Health indicators are inefficient for remaining useful life (RUL) prediction with cross-operational environments when dealing with high-dimensional datasets as inputs. This research proposes a health indicator construction methodology based on a transformer self-attention transfer network (TSTN). This methodology can directly deal with the high-dimensional raw dataset and keep all the information without missing when the signals are taken as the input of the diagnosis and prognosis model. First, we design an encoder with a long-term and short-term self-attention mechanism to capture crucial time-varying information from a high-dimensional dataset. Second, we propose an estimator that can map the embedding from the encoder output to the estimated degradation trends. Then, we present a domain dis-criminator to extract invariant features from different machine operating conditions. The case studies with the FEMTO-ST bearing dataset and the Monte Carlo method for RUL prediction during the degradation process are conducted. The experiment results fully exhibited the signif-icant advantages of the proposed method compared to other state-of-the-art techniques.

Human Action Recognition is widely used in multiple fields to recognize activities and extract spatial and temporal information. This paper focuses on analyzing various methods as well as provides extensive knowledge of the foundational concepts of the HAR. A dataset is also very crucial for any research study so we discussed the popular dataset and its features in this paper.

To address the deficiency of existing relation extraction models in effectively extracting relational triplets pertaining to railway traffic knowledge in Tibet, this paper constructs a Tibet Railway Traffic text dataset and provides an enhanced relation extraction model. The proposed model incorporates subject feature enhancement and relational attention mechanisms. It leverages a pre-trained model as the embedding layer to obtain vector representations of text. Subsequently, the subject is extracted and its semantic information is augmented using an LSTM neural network. Furthermore, during object extraction, the multi-head attention mechanism enables the model to prioritize relations associated with the aforementioned features. Finally, objects are extracted based on the subjects and relations. The proposed method has been comprehensively evaluated on multiple datasets, including the Tibet Railway Traffic text dataset and two public datasets. The results on the Tibet dataset achieves an F1-score of 93.3\%, surpassing the baseline model CasRel by 0.8\%, indicating a superior applicability of the proposed model. On the other hand, the model achieves F1-scores of 91.1\% and 92.6\% on two public datasets, NYT and WebNLG, respectively, outperforming the baseline CasRel by 1.5\% and 0.8\%, which highlights the good generalization ability of the proposed model.

The reagents and raw materials used, as well as the products obtained (bio-oil, reaction condensates, polyols and sugar phases) were characterized by elemental analysis, infrared spectroscopy, thermogravimetry and high performance liquid chromatography with mass spectrometry. The heating value of the bio-oils is higher than that of the original biomass (higher heating value of Eucalyptus sawdust bio-oil 29 MJ/kg versus 19.5 MJ/kg of the original Eucalyptus sawdust). The analyses of the bio-oils allowed to identify the presence of high added-value compounds, such as levulinic acid and furfural. Finally, a study of the accelerated aging of the liquefied biomass showed that the biofuel density increases with the storage time due to the occurrence of repolymerization reactions.

Deep convolutional neural networks (CNN) are favored methods widely used in medical image processing due to their assured shown performance. Recently, the emergence of new lung diseases and the possibility of early detection of their symptoms has attracted many researchers to classify diseases by training deep CNNs on lung CT images. The trained networks are expected to distinguish between lung indications in different diseases, especially at the early stages of them. With the hope of achieving this purpose, we proposed an efficient deep CNN called AFEX-Net with adaptive feature extraction layers that successfully extract distinguishing features and classify chest CT images. The efficiency of the proposed network has two aspects: it is a lightweight network with low number of parameters and fast training and it has adaptive pooling layers and adaptive activation functions to increase its level of compatibility to the input data. The proposed network has been evaluated on a dataset with more than 10K chest CT slices, while an efficient pre-processing method is developed to remove any bias from the images. Additionally, we evaluated the performance of the proposed model on the public COVID-CTset dataset to prove the generalisability of our model. The obtained results confirm the competence of the proposed network in confronting medical images, where prompt and accurate learning is required.

Proso millet starch (PMS) as an unconventional and underutilized cereal starch is becoming increasingly popular worldwide due to its health-promoting properties. This review summarizes research progress in the isolation, characterization, modification, and applications of PMS. PMS can be isolated from proso millet grains by acidic, alkaline, or enzymatic extraction. PMS exhibits typical A-type polymorphic diffraction patterns and shows polygonal and spherical granular structures with a granule size of 0.3-17 µm. PMS is modified by chemical, physical, and biological methods. The native and modified PMS are analyzed for swelling power, solubility, pasting properties, thermal properties, retrogradation, freeze-thaw stability, and in vitro digestibility. The improved physicochemical, structural, and functional properties and digestibility of modified PMS are discussed in terms of their suitability for specific applications. The potential applications of native and modified PMS in food and non-food products are presented. Future prospects for research and commercial use of PMS in the food industry are also highlighted.

This article presents a state-of-the-art system to extract and synthesize causal statements from company reports into a directed causal graph. The extracted information is organized by the relevance to different stakeholder groups’ benefits (customers, employees, investors, and the community/environment). The presented method of synthesizing extracted data into a knowledge graph comprises a framework that can be used for similar tasks in other domains, e.g. medical information. The current work addresses the problem of finding, organizing, and synthesizing a view of the cause-and-effect relationships based textual data, in order to inform and even prescribe the best actions that may affect target business outcomes related to different stakeholders’ benefits (customers, employees, investors, and the community/environment).

A rapid and efficient method using an alkyl functionalized magnetic nanoparticles-based extraction technique combined with Ultra-High Performance Liquid Chromatography was developed for the detection of trace amounts of polycystic aromatic hydrocarbons in tea leaves. As a popular coating for chromatographic column packing materials, C18-alkyl has been demonstrated to be effective in separating polycystic aromatic hydrocarbons. And the magnetism of the nanomaterials accelerates the extraction process while their high surface ratio enables desirable dispersity in the sample matrix. Meanwhile, the adsorbents can be washed and reused 30 times without compromise on recovery, which greatly reduced the budget. The effects of various parameters were investigated and optimized, and the recoveries for five analytes were in the range of 84.8–103.7%. The reproducibility rate of intra-day and inter-day were below 7.1% and 11.3% respectively. The limits of detection and limits of quantification ranged from 1.69–9.97 ng g-1 and 5.12–30.21 ng g-1, indicating satisfactory sensitivity. Thus, the proposed methodology is rapid, highly efficient, and economical, and it expands the application of magnetic cleanup approaches in complex food matrices.

In the era of big data, feature engineering has proved its efficiency and importance in dimensionality reduction and useful information extraction from original features. Feature engineering can be expressed as dimensionality reduction and is divided into two types of methods such as feature selection and feature extraction. Each method has its pros and cons. There are a lot of studies to combine these methods. Sparse autoencoder (SAE) is a representative deep feature learning method that combines feature selection with feature extraction. However, existing SAEs do not consider the feature importance during training. It causes extracting irrelevant information. In this paper, we propose a parallel guiding sparse autoencoder (PGSAE) to guide the information by two parallel guiding layers and sparsity constraints. The parallel guiding layers keep the main distribution using Wasserstein distance which is a metric of distribution difference, and it suppresses the leverage of guiding features to prevent overfitting. We perform our experiments using four datasets that have different dimensionality and number of samples. The proposed PGSAE method produces a better classification performance compared to other dimensionality reduction methods.

In the chemical processing industries, sensors for pumps are among the most commonly used machinery. Condition-based maintenance (CBM) and prognosis health management (PHM) determine the most cost-effective time to overhaul pumps. In order to determine the status of the pump, a signal-emitting accelerometer is employed. Stationarity-based feature extraction from amplitude signals is used to process the signal. Utilizing the time-domain function, multiple statistical results were produced. Eight fault codes were classified using support vector machine method. The enormous amount of data points necessitated the use of feature selection. In terms of accuracy, precision, recall, and F1 score, the Chi-square feature selection method exceeds other approaches.

Deep learning (DL) models have been recently widely used to extract task-oriented patterns from large scale of datasets, and to improve the data image understanding and analysis accuracy in many different decision-making processes for tasks such as image classification, segmentation, detection, and so on. However, in practice, the performances of DL models are easily affected by environmental illumination conditions. Conversely, DL models can also be utilized for extracting the illumination hints from the images, and these hints are critically useful for improving the model robustness, classifying the environmental scenes, estimating scene depth information, and rendering 3D objects. In this study, an extensive and exhaustive review is carried out for DL based color constancy, indoor and outdoor illumination estimation, and image depth estimations with the considerations of strengths and weaknesses of DL models. This study also explores the different network designs and the paradoxes in parameter optimization during the model training. Current technology barriers involved in implementing these models and recommendations to overcome these barriers are also suggested in the review.

A model for the simulation of ion beam extraction from an electron cyclotron resonance ion source is proposed. It is based on the simple fact that charged particles follow magnetic field lines. Therefore magnetic field lines are used to generate initial conditions for ray-tracing. This model reproduces in simulation experimentally obtained results. The importance of correlations in phase-space caused by the magnetic field is shown in simulation. This model also describes the physics of space-charge and its compensation in the extracted (fast) ion beam by low energy electrons. Simulation provides the possibility to test theoretical assumptions, as well as to optimize technical designs.

Genomics involving tens of thousands of genes is a complex system determining phenotype. An interesting and vital issue is that how to integrate highly sparse genetic genomics data with a mass of minor effects into prediction model for improving prediction power. We find that deep learning method can work well to extract features by transforming highly sparse dichotomous data to lower dimensional continuous data in a non-linear way. This idea may provide benefits in risk prediction based on genome-wide data associated e.g. integrating most of the information in the genotype data. Hence, we developed a multi-stage strategy to extract information from highly sparse binary genotype data and applied it for risk prediction. Specifically, we first reduced the number of biomarkers via a univariable regression model to a moderate size. Then a trainable auto-encoder was used to extract compact representations from the reduced data. Next, we performed a LASSO problem process over a grid of tuning parameter values to select the optimal combination of extracted features. Finally, we applied such feature combination to two prognostic models, and evaluated predictive effect of the models. The results of simulation studies and real data applying indicated that these highly compressed transformation features could better improve predictive performance and did not easily lead to over-fitting.

The ionic liquid A327H+Cl- is generated by reaction of the tertiary amine A327 (industrial mixture of tri-octil and tri-decyl amines) and hydrochloric acid solutions. Further, the extraction of Au(III) by A327H+Cl- ionic liquid under various variables, including metal and ionic liquid concentrations, has been investigated. Results indicate that A327H+AuCl4- is formed, by an exothermic (ΔHº= -3 kJ/mol) reaction, in the organic solution. Aqueous ionic strength influences the formation constants values and the specific interaction theory (SIT) is used to estimate the interaction coefficient between AuCl4- and H+. Gold (III) is stripped using thiocyanate media, and from the strip solutions, gold is precipitated as gold nanoparticles.

A renewable cyclic monoterpene obtained from citrus peel, limonene is widely used as a fra-grance, nutraceutical ingredient, antibacterial, biopesticide, and green extraction solvent. Indus-trial demand largely exceeds supply. After reviewing recent advances in the recovery of limonene from citrus peel and residues with a particular attention to benign-by-design extractive processes, we focus on the latest results in its dehydrogenation to p-cymene via heterogeneous catalysis.

Asphalt binder requires more investigation to be accurately and precisely extracted since it is a significant procedure for quality control quality assurance (QC/QA) and subsequent binder characterization. In this research, the authors provided a hands-on experience with binder extraction to deliver recommendations concerning the sensitive steps that may affect the outcomes (extracted binder content, P_be%). Based on the extraction by the centrifuge method, two mineral matter determination methods (ashing and centrifuge) were addressed. Field cores were investigated with comparing the P_be% to the actual binder content, P_ba%. Analysis of variance (ANOVA) and Tukey Post-Hoc statistical analyses, in addition to linear least square regression analysis, were used to show the significance of difference according to 38 variant cores randomly obtained from the field segments (in-service roads) via the first two weeks from the construction date. Such cores involved reclaimed asphalt pavement (RAP), reclaimed asphalt shingles (RAS), and a wide range of additives. The two extraction methods were compared with concluding that the centrifuge method was highly recommended based on a quantitative evaluation, which delivered the same average P_ba% based on the 38 cores. Furthermore, the centrifuge method provided much saving in the experimental time (almost half the time required for the ashing method). It was found that the ashing outcomes were equal to the centrifuge outcomes with disregarding the ammonium carbonate addition. Thus, it could be recommended to reassess the ammonium carbonate addition as it might excessively compensate for fake minerals that have not been lost by the ignition oven.

Despite the long and extensive history of 3D technology, it has recently attracted the attention of researchers. This technology has become the center of interest of young people because of the real feelings and sensations it creates. People see their environment as 3D because of their eye structure. In this study, it is hypothesized that people lose their perception of depth during sleepy moments and that there is a sudden transition from 3D vision to 2D vision. Regarding these transitions, the EEG signal analysis method was used for deep and comprehensive analysis of 2D and 3D brain signals. In this study, a single-stream anaglyph video of random 2D and 3D segments was prepared. After watching this single video, the obtained EEG recordings were considered for two different analyses: the part involving the critical transition (transition-state) and the state analysis of only the 2D versus 3D or 3D versus 2D parts (steady-state). The main objective of this study is to see the behavioral changes of brain signals in 2D and 3D transitions. To clarify the impacts of the human brain’s power spectral density (PSD) in 2D-to-3D (2D_3D) and 3D-to-2D (3D_2D) transitions of anaglyph video, 9 visual healthy individuals were prepared for testing in this pioneering study. Spectrogram graphs based on Short Time Fourier transform (STFT) were considered to evaluate the power spectrum analysis in each EEG channel of transition or steady-state. Thus, in 2D and 3D transition scenarios, important channels representing EEG frequency bands and brain lobes will be identified. To classify the 2D and 3D transitions, the dominant bands and time intervals representing the maximum difference of PSD were selected. Afterward, effective features were selected by applying statistical methods such as standard deviation (SD), maximum (max), and Hjorth parameters to epochs indicating transition intervals. Ultimately, k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) algorithms were applied to classify 2D_3D and 3D_2D transitions. The frontal, temporal, and partially parietal lobes show 2D_3D and 3D_2D transitions with a good classification success rate. Overall, it was found that Hjorth parameters and LDA algorithms have 71.11% and 77.78% classification success rates for transition and steady-state, respectively.

The procedures for the extraction and separation of lipids and nutraceutics from microalgae using classic solvents have been used many times. However, these production methods usually require expensive and toxic solvents. Based on our studies involving the use of eco-sustainable methodologies and alternative solvents, we select ethanol (EtOH) and cyclopentyl methyl ether (CPME) for extracting bio-oil and lipids from algae. Different percentage of EtOH in CPME favors the production of an oil rich of SFA useful to production biofuel or rich of compounds bioactive. The proposed method for obtain a rich extract of saturated or unsaturated fatty acids from dry algal biomass is disclosed is eco-friendly and allows a good extraction yield. The method is compared both in extracted oil percentage yield and in extracted fatty acids selectivity to extraction by supercritical carbon dioxide.

The aim of this study was to examine brightness effect, which is the perceptual property of visual stimuli, on brain responses obtained during visual processing of these stimuli. For this purpose, brain responses of the brain to changes in brightness were explored comparatively using different emotional images (pleasant, unpleasant and neutral) with different luminance levels. Moreover, electroencephalography recordings from 12 different electrode sites of 31 healthy participants were used. The power spectra obtained from the analysis of the recordings using short time Fourier transform were analyzed, and a statistical analysis was performed on features extracted from these power spectra. Statistical findings obtained from electrophysiological data were compared with those obtained from behavioral data. The results showed that the brightness of visual stimuli affected the power of brain responses depending on frequency, time and location. According to the statistically verified findings, the distinctive effect of brightness occurred in the parietal and occipital regions for all the three types of stimuli. Accordingly, the increase in the brightness of pleasant and neutral images increased the average power of responses in the parietal and occipital regions whereas the increase in the brightness of unpleasant images decreased the average power of responses in these regions. However, the increase in brightness for all the three types of stimuli reduced the average power of frontal and central region responses (except for 100-300 ms time window for unpleasant stimuli). The statistical results obtained for unpleasant images were found to be in accordance with the behavioral data. The results also revealed that the brightness of visual stimuli could be represented by changing the activity power of the brain cortex. The main contribution of this research was to comprehensively examine brightness effect on brain activity for images with different emotional content and different frequency bands at different time windows of visual processing for different brain regions. The findings emphasized that the brightness of visual stimuli should be viewed as an important parameter in studies using emotional image techniques such as image classification, emotion evaluation and neuro-marketing.

In this paper we propose a novel self-supervised approach of keywords and keyphrases retrieval and extraction by an end-to-end deep learning approach, which is trained by contextually self-labelled corpus. Our proposed approach is novel to use contextual and semantic features to extract the keywords and has outperformed the state of the art. Through the experiment the proposed approach has been proved to be better in both semantic meaning and quality than the existing popular algorithms of keyword extraction. In addition, we propose to use contextual features from bidirectional transformers to automatically label short-sentence corpus with keywords and keyphrases to build the ground truth. This process avoids the human time to label the keywords and do not need any prior knowledge. To the best of our knowledge, our published dataset in this paper is a fine domain-independent corpus of short sentences with labelled keywords and keyphrases in the NLP community.

Weed seedbank is an indication of future weed infestation potential of the species and is essential for making strategic planning for its sustainable management. Parthenium weed (Parthenium hysterophorus L.) is an invasive alien species threatening the biodiversity and the environment in Malaysia. A study was, therefore, conducted to estimate the soil seedbank of the weed at four soil depths of four villages of Kuala Muda, Kedah. The aim was to indicate the critical s of parthenium weed seedbank in Malaysia. Soil samples were collected from the sites using a soil core. The seeds were extracted from the soil samples with sieve shaker at the Universiti Malaysia Kelantan laboratory, Jeli Campus. The study indicates that the weed seedbank is in critical level at the area. The highest number of weed seeds (6915/m2) was found in Kg. Kongsi 6, followed by Kg. Sungai Tok Rawang (4481 seeds/m2). The top layer of soil, 0-5 cm, contained the maximum number of weed seeds (4878 seeds/m2) and a significant number of seeds (316 seeds/m2) were noticed at 10-15 cm soil depth. The study suggests the Malaysian government to take immediate action to control parthenium weed seedbank of the sites.

During the last few years, advancement in the area of biochemistry, science of the material world, engineering and computer-aided testing has directed towards advancement of high-throughput tools for the sake of profiling information encoded in a gene. Single-cell RNA-sequencing (scRNA-seq) tools capable to examine the sequence data from each individual cells and it shows within population variety and permit exploring of cell conditions and transformation by extreme resolution, possibly give out cell sub-types or gene expression fluctuations that are shaded in mass sequencing processes, which shows population-averaged evaluations. Yet, the major disadvantage for this tool is the lack of success to pick out location related details of the RNA transcriptome, as this needs tissue detachment and cell isolation. Location based transcript determination is among the advancements in the area of medical biotechnology as this can find out the molecules like RNA dataset in their intact physical placement in tissue segment with spatial context at the scale of a single-cell, which is very advantageous as compare to single-cell sequencing techniques. These approaches give key observation in the areas of biomedical field sub-disciplines like neurology, embryology, carcinoma study, immune cell investigation and histological activities. Generally, this review mainly focused towards single-cell sequencing methods, technology development, its challenges observed, different expression data analysis mechanisms and their applications in different areas, such as in cancer research, microbes, central nervous system, sex organs and immune-biology, intensifying the essentiality of sequencing tools at single-cell level for the characterization of extremely dynamic individual cells.

It is generally accepted that atherosclerosis is a chronic inflammatory disease. The link between atherosclerosis and other inflammatory diseases such as psoriasis, type 2 diabetes mellitus (T2DM), and rheumatoid arthritis (RA) via metabolic, inflammatory, and immunoregulatory pathways is well established. The aim of our review was to summarize the associations between selected microRNAs (miRs) and long non-coding RNAs (lncRNAs) and atherosclerosis, psoriasis, T2DM, and RA. MicroRNAs are short noncoding RNA molecules involved in cell signaling, intracellular communication, and gene expression. We reviewed the role of miR-146a, miR-210, miR-143, miR-223, miR-126, miR-21, miR-155, miR-145, miR-200, miR-133, miR-135, miR-221, miR-424, and let-7 in atherosclerosis, psoriasis, T2DM, and RA. LncRNAs are RNA transcripts longer than 200 nucleotides that are involved in cellular processes such as apoptosis, metabolism, inflammation, cell differentiation, and proliferation. We evaluated the role of lncRNA-H19, lncRNA-MEG3, lncRNA-UCA1, and lncRNA-XIST in atherosclerosis and psoriasis, T2DM, and RA. Extracellular vesicles (EVs) are a method of intracellular signal transduction. Their function depends on surface expression, cargo, and the cell from which they originate.

Parkinson's disease (PD) stands as the most prevalent degenerative movement disorder, characterized by the loss of dopaminergic neurons in the substantia nigra of the midbrain. In this study, we assessed the transcriptome by analyzing post-mortem mRNA extracted from the substantia nigra of individuals with PD and healthy controls. A total of 16,148 transcripts were identified, with 92 mRNAs displaying differential expression between PD and control groups. Specifically, 33 mRNAs were significantly upregulated, while 59 mRNAs were downregulated in PD compared to controls. The identification of statistically significant signaling pathways, with an adjusted p-value threshold of 0.05, unveiled noteworthy insights. Particularly, enriched categories included cardiac muscle contraction (involving genes such as ATPase Na+/K+ transporting subunit beta 2 (ATP1B2), solute carrier family 8 member A1 (SLC8A1), and cytochrome c oxidase subunit II (COX2)), GABAergic synapse (involving GABA type A receptor-associated protein like 1 (GABARAPL1), G protein subunit beta 5 (GNB5), and solute carrier family 38 member 2 (SLC38A2)), autophagy (involving GABARAPL1 and tumor protein p53-inducible nuclear protein 2 (TP53INP2)), and Fc gamma R-mediated phagocytosis (involving amphiphysin (AMPH)). These findings uncover new pathophysiological dimensions underlying PD, including the involvement of cardiac muscle contraction and specific mitochondrial activity. This knowledge not only contributes to better diagnostic precision but also paves the way for the development of new targeted therapies.Keywords: mRNAs; RNA sequencing; Parkinson’s disease; transcriptome analysis; substantia nigra

Background: We investigated the tumor immune response in gastric cancer patients receiving third line nivolumab monotherapy to identify immune-related biomarkers for better patient se-lection. Methods: Nineteen patients (10 males, median age 67 years) who received nivolumab as a third or later line therapy were enrolled. We analyzed the tumor immune response in durable clinical benefit (DCB) and non-DCB patients. Pre-treatment and early-on-treatment tumor transcriptomes were examined, and gene expression profiles, immunograms, and T cell receptor (TCR) repertoire were analyzed. Results: DCB was observed in 15.8% of patients, with comparable secondary endpoints (ORR, OS, PFS) to previous trials. Individual immunograms showed no significant changes before and ear-ly-on-treatment, nor consistent alterations among DCB cases. The intratumoral immune response was suppressed by previous treatments in most third or later line nivolumab recipients. TCR repertoire analysis revealed newly emerged clonotypes in on-treatment tumors, but clonal re-placement did not impact efficacy. High T cells/Tregs ratios and a low UV radiation response gene signature were linked to DCB and treatment response. Conclusions: This study emphasizes the tumor immune response's importance in nivolumab ef-ficacy for gastric cancer. High T cells/Tregs ratios and specific gene expression signatures show promise as potential biomarkers for treatment response. Larger cohort validation is crucial to optimize immune checkpoint inhibitors in gastric cancer treatment.

Cerebral palsy (CP) is the most common movement disorder in children with a prevalence rang-ing from 1.5 to 4 per 1000 live births. CP is caused by a non-progressive lesion of the developing brain, leading to progressive alterations of the musculoskeletal system, including spasticity, often leading to the development of fixed contractures, necessitating tendon lengthening surgery. Total RNA-sequencing analysis was performed on semitendinosus tendons from diplegic and tetraple-gic CP patients subjected to tendon lengthening surgery compared to control patients undergoing anterior cruciate ligament reconstructive surgery. Tetraplegic CP patients showed increased ex-pression of genes implicated in collagen synthesis and extracellular matrix (ECM) turnover, while only minor changes were observed in diplegic CP patients. In addition, tendons from tetra-plegic CP patients showed an enrichment for upregulated genes involved in vesicle-mediated transport and downregulated genes involved in cytokine and apoptotic signaling. Overall, our results indicate increased ECM turnover with increased net synthesis of collagen in tetraplegic CP patients without activation of inflammatory and apoptotic pathways similar to observations in athletes where ECM remodeling results in increased tendon stiffness and tensile strength. Never-theless, the resulting increased tendon stiffness is an important issue in clinical practice, where surgery is often required to restore joint mobility.

During the recent pandemics of COVID-19, sequencing technics became powerful tool for gaining information about the SARS-CoV-2 virus and using this knowledge in our advantage. Thanks to this advantage, scientists over the world were able to search for emerging variations, watching the virus evolving in real time. Assembly of the virus genomes is crucial part of getting this kind of useful information. In our study, we sequenced 79 samples from nasopharyngeal swabs of COVID-19 patients. Positivity on disease was evaluated by qRT-PCR. By studying assembly success rate, we noticed, that Ct-value of qRT-PCR can predict success of genome assembly and SARS-CoV-2 lineage assignment. In this work we described the relationship between Ct-value and further steps of genome construction and its assignment to specific viral strain.

Obesity has become a global epidemic, contributing to the development of numerous chronic diseases, including diabetes, chronic kidney disease (CKD) and cardiovascular disorders. MicroRNAs (miRNAs) have emerged as key regulators in various biological processes, including metabolism, inflammation, and tissue remodeling, making them pivotal players in obesity-related pathologies. This review aims to provide comprehensive insights into the roles of miRNAs in obesity, with a particular emphasis on their involvement in the pathogenesis of CKD and cardiovascular disorders. We highlight the involvement of specific miRNAs in adipose tissue development, energy homeostasis, inflammation, and insulin resistance, contributing to the pathogenesis of obesity. Moreover, we explore the impact of miRNAs on renal fibrosis, and inflammation, giving clues on their roles in the development and progression of CKD. Additionally, we discuss the influence of miRNAs on endothelial dysfunction, atherosclerosis, and cardiac remodeling, emphasizing their contribution to obesity-related cardiovascular disorders. Understanding the regulatory functions of miRNAs in these interconnected conditions holds promise for improved diagnosis, prognosis, and therapeutic interventions. Indeed, miRNAs are potential diagnostic biomarkers for obesity-related diseases although challenges remain to be elucidated before their clinical translation. Furthermore, we highlight the emerging strategies that target miRNAs as therapeutic interventions to mitigate the detrimental effects of obesity on kidney and cardiovascular health.

The achievement of reproductive competence in male mammals is dependent on the testis. Goat testis’ development and spermatogenesis involve physiological events with high complexity. In the current work, 6 testes were respectively collected from immature, sexually mature and physically mature Qianbei Ma goats (1, 6 and 12 months old, respectively). RNA-Seq was carried out to reveal changes in testis mRNA expression levels in Qianbei Ma goats at various developmental stages, and gene expression profiling at different ages was established. Totally 18 libraries were established for screening genes and pathways associated with testis development and spermatogenic processes. Totally 9,724 upregulated and 4,153 downregulated genes were identified between immature (I) and sexually mature (S) testes; 7 upregulated and 3 downregulated genes were detected between sexually mature (S) and physically mature (P) testes, and approximately 4% of genes were alternately spliced between the I and S groups. Selected genes were verified by qRT-PCR, in agreement with sequencing data indicating their reliability. Those genes have critical functions in various developmental stages of goat testicular development and spermatogenesis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were carried out to evaluate differentially expressed genes (DEGs). GO analysis suggested DEGs were involved in “reproduction process”, “channel activity” and “cell periphery part” between I and S, and in “ion transport process”, “channel activity” and “transporter complex part” between S and P. KEGG analysis indicated that pathways such as “glycerolipid metabolism”, “steroid hormone biosynthesis” and “MAPK signaling pathway” may be involved in testis development and spermatogenesis. Genes including IGF1, TGFB1, TGFBR1 and EGFR may regulate the development of the testis from immature to sexually mature, which may be key candidate genes for the development of goat testis. These findings provide novel insights into goat testicular development and spermatogenesis.

This paper presents results of the experiments performed on a nonconventional and extremely interesting in regard to evolution, creature, the European river lamprey Lampetra fluviatilis (Petromyzontiformes, Cyclostomata), one of the oldest taxa of vertebrates. We present detailed immunocytochemical and electron microscopy analyses of chromosome synapsis, the transcription process, and chromatin dynamics in lamprey prophase I, which is the first time for science. We found that not all chromosomes complete synapsis. Rounded structures were detected in chromatin and in some synaptonemal complexes but their nature could not be determined conclusively. An analysis of RNA polymerase II distribution led to the conclusion that transcriptional reactivation in lamprey prophase I is not associated with the completion of chromosome synapsis. Monomethylated histone H3K4 is localized to meiotic chromatin throughout prophase I, and this pattern has not been previously detected in the animals. Thus, the findings made it possible to identify synaptic and epigenetic patterns specific for this group, and to add new pieces of the puzzle to the discussions of the scientific issues under study. The research on lamprey meiotic chromatin and chromosomal dynamics raises many questions leading to new discoveries.

Human T-lymphotropic virus type 1 (HTLV-1)–associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a slowly progressive spinal cord disorder with no effective treatment. There is much of interest in developing potential biomarkers for predicting the pathogenesis of HAM/TSP disorder. This study used Illumina massive parallel sequencing (MPS) technology to assess the cellular global noncoding RNAome expression profile in HAM/TSP patients (n = 10), asymptomatic HTLV-1 infected carriers (ASP, n = 8), and a second group of healthy controls (n = 5). Using various bioinformatics tools, the sRNA MPS reads were aligned, annotated, and profiled. There were 251 known and 50 potential novel sRNAs among the 402 detected sRNAs in the HAM and ASP groups versus the HC group. Sixty-eight known sRNAs were found to be significantly different between the ASP and HAM groups. In HAM vs ASP subjects, 88 mature miRNAs were downregulated. Three of these miRs (hsa-miR-185-5p, 32-5p, and 192-5p) have the potential to be used as biomarkers for predicting the pathogenesis of HAM/TSP. The top seven deregulated miRS target genes were linked to a variety of biological processes and molecular functions. Relevant reactome pathways to our findings provide a rich source of data and an opportunity to further understand sRNA regulation and function in HTLV-1 pathophysiology.

Rose (Rosa spp.), especially R. hybrida, is one of the most popular ornamental plants in the world and the third largest cut flower crop in Taiwan. Rose mosaic disease (RMD), showing mosaic, line patterns and ringspots on leaves, is a common rose disease caused by complex infection of various viruses. Due to pests and diseases, the rose planting area in Taiwan has been decreasing since 2008; however, no rose virus disease has been reported in the past five decades. In the spring of 2020, rose samples showing RMD-like symptoms were observed at an organic farm in Chiayi, central Taiwan. The virome in the farm was analyzed by RNA-seq. Rose genomic sequences were filtered from the obtained reads. The remaining reads were de novo assembled to generate 294 contigs, 50 of which were annotated as viral sequences corresponding to 10 viruses. Through reverse transcription-polymerase chain reaction validation, a total of seven viruses were detected, including six known rose viruses, namely apple mosaic virus, prunus necrotic ringspot virus, rose partitivirus, apple stem grooving virus, rose spring dwarf-associated virus and rose cryptic virus 1, and a novel ilarvirus. After completing the whole genome sequencing and sequence analysis, the unknown ilarvirus was demonstrated as a new species, tentatively named rose ilarvirus 2. This is the first report of the rose viruses in Taiwan.

The objective of this study was to identify key transcription factors involved in lipid metabolism and immune response related to the differentially expressed genes (DEG) from the liver samples of 35 pig model for metabolic diseases fed diets containing either 1.5 or 3.0% soybean oil (SOY1.5 or SOY3.0). A total of 281 DEG between SOY1.5 and SOY3.0 diets (log2fold-change ≥ 1 or ≤ −1; FDR-corrected p-value < 0.1) were identified, in which 129 were down-regulated and 152 were up-regulated in SOY1.5 group. The functional annotation analysis detected transcription factors linked to lipid homeostasis and immune response, such as RXRA, EGFR, and SREBP2 precursor. These findings demonstrated that key transcription factors related to lipid metabolism could be modulated by dietary inclusion of soybean oil. It could contribute to nutrigenomics research field that aims to elucidate dietary interventions in animal and human health, as well as to drive the food technology and science.

The ongoing COVID-19 pandemic dictated new priorities in biomedicine research. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, is a single-stranded positive-sense RNA virus. In this pilot study, we optimized our padlock assay to visualize genomic/subgenomic regions using formalin-fixed paraffin-embedded placental samples obtained from a confirmed case of COVID-19. SARS-CoV-2 RNA was localized in trophoblastic cells. We also checked the presence of the virion by immunolocalization of its glycoprotein spike. In addition, we imaged mitochondria of placental villi keeping in mind that the mitochondrion has been suggested as a potential residence of the SARS-CoV-2 genome. Indeed, we observed a substantial overlapping of SARS-CoV-2 RNA and mitochondria in trophoblastic cells. This intriguing linkage correlated with an aberrant mitochondrial network. Overall, to our knowledge, this is the first study that provides the evidence of a co-localization of the SARS-CoV-2 genome and mitochondria in SARS-CoV-2 infected tissue. These findings also support the notion that SARS-CoV-2 infection could reprogram mitochondrial activity in highly specialized maternal/fetal interface.

Background: Jerusalem artichoke (Helianthus tuberosus L.) is tolerant to salinity stress and has high economic value. The salt tolerance mechanisms of Jerusalem artichoke are still unclear. Especially in the early stage of Jerusalem artichoke exposure to salt stress, the plant physiology, biochemistry and gene transcription are likely to undergo large changes. Elucidating these changes may be of great significance to understanding the salt tolerance mechanisms of it. Results: We obtained high-quality transcriptome from leaves and roots of Jerusalem artichoke exposed to salinity (300 mM NaCl) for 0 h, 6 h, 12 h, 24 h and 48 h, with 150,129 unigenes and 9023 DEGs (Differentially Expressed Genes). The RNA-seq data were clustered into time-dependent groups (nine clusters each in leaves and roots); gene functions were distributed evenly among the groups convergence. KEGG enrichment analysis showed the genes related to plant hormone signal transduction were enriched in almost all treatment comparisons. Under salt stress, genes belongs to PYL (abscisic acid receptor PYR / PYL family), PP2C (Type 2C protein phosphatases), GH3 (Gretchen Hagen3), ETR (ethylene receptor), EIN2/3 (ethylene-insensitive protein 2/3), JAZ (Genes such as jasmonate ZIM-domain gene) and MYC2 (Transcription factor MYC2) had extremely similar expression patterns. The results of qPCR of 12 randomly selected genes confirmed the accuracy of RNA-seq. Conclusions: Under the impact of high salinity (300mM) environment, Jerusalem artichoke in the seedling stage was difficult to survive for a long time, and the phenotype was severe in the short term. Based on the expression of genes on the time scale, we found that the distribution of gene functions in time is relatively even. Upregulation of the phytohormone signal transduction had a crucial role in the response of Jerusalem artichoke seedlings to salt stress, the genes of abscisic acid, auxin, ethylene, and jasmonic acid had the most obvious change pattern.

In recent years, the role of non-coding RNAs (ncRNAs) in regulating cell physiology has begun to be better understood. Recent discoveries in viral molecular biology have revealed that such cellular functions are disturbed during viral infections mainly due to host cell ncRNAs, cellular factors, and virus-derived ncRNAs. Apart from the interplay between those molecules, other interactions derive from the specific folding of RNA virus genomes. These fulfill canonical regulation functions such as replication, translation, and viral packaging. In some cases, folds serve as precursors of small viral RNAs whose biogenesis is not yet clearly understood. Since ncRNAs and RNA viral genomes modulate complex molecular and cellular processes in viral infections, a new taxonomy is being proposed here overarching three main categories, considering the current information about ncRNA interactions in some well-known viral infections. The first category shows examples of host ncRNAs associated with the trigger of the immune response under viral infections. The second category describes interactions between the virus and host ncRNAs. The last category shows how the shape of the RNA viral genome is essential in processing RNAs derived from viruses. Finally, we introduce evidence of how these three categories can also work as a framework in order to organize known interactions of ncRNAs and cellular factors under DENV infection. This new taxonomy of interactions provides a comprehensive framework for organizing the ncRNA regulatory roles in the context of viral interactions and an RNA world.

Cesiumtrifluoroacetate (CsTFA) is a key chemical for RNA-based stable isotope analyses to link the structure and function of microbial communities. We report a protocol to easily synthesize CsTFA from Cesiumcarbonate (Cs₂CO₃₎ and Trifluoroacetate (TFA) and show that self-synthesized CsTFA behaves similar to commercial CsTFA in the separation of isotopically labelled and unlabelled E. coli RNA.

The rise of data science in biology stimulates interdisciplinary collaborations to address fundamental questions. Here, we report the outcome of the first SINFONIA symposium focused on revealing the mechanisms governing plant reproductive development across biological scales. The intricate and dynamic target networks of known regulators of flower development remain poorly understood. To analyze development from the genome to the final floral organ morphology, high-resolution data that capture spatiotemporal regulatory activities are necessary and require advanced computational methods for analysis and modeling. Moreover, frameworks to share data, practices and approaches that facilitate the combination of varied expertise to advance the field are called for. Training young researchers in interdisciplinary approaches and science communication offers the opportunity to establish a collaborative mindset to shape future research.

Single cell RNA-seq (scRNA-seq) profiles conceal temporal and spatial tissue developmental information. De novo reconstruction of single cell temporal trajectory has been fairly addressed, but reverse engineering single cell 3D spatial tissue localization is hitherto landmark based, and de novo spatial reconstruction is a compelling computational open problem. Here we show that a new algorithm - named D-CE - for coalescent embedding of single cell transcriptomic networks can address this open problem. We rely merely on the spatial information encoded in the expression patterns of developmental signal transcription factor (DST) genes, and we find that D-CE of cell-cell association DST-transcriptomic networks reliably reconstructs the Geo-seq or single cell samples’ 3D spatial tissue distribution. Comparison to the novoSpaRC and CSOmap (recent and only available de novo 3D spatial reconstruction methods) on 16 datasets and 681 reconstructions, reveals a significantly distinctive superior performance of D-CE.

Zika virus (ZIKV), without a vaccine or no effective treatment approved as yet, have globally spread since the past century. The infection caused by ZIKV in humans has changed progressively from mild to subclinical in the last years, causing epidemics with greater infectivity, tropism towards new tissues, and other related symptoms as a product of various emergent ZIKV-host cell interactions. However, it is still unknown why or how the RNA genome structure impacts those interactions in differential evolutionary origin strains. Moreover, genomic comparison of ZIKV strains from the sequence-based phylogenetic analysis is well known, but differences from RNA structure comparisons are less known. Thus, in order to understand the RNA genome variability of lineages of various geographic distributions better, 412 complete genomes in a phylogenomic scanning were used for studying the conservation of structured RNAs. We found specific genomic regions, which highlight their patterns of conserved RNA structures at the level of inter-geographical comparisons. We have proposed these structures as candidates for further experimental validation to establish their potential role in vital functions of the viral cycle of ZIKV and their possible associations with the singularities of different outbreaks that occurred in specific geographic regions.

Long noncoding RNA (lncRNA) are implicated in various genetic diseases and cancer, attributed to their critical role in gene regulation. RNA sequencing is used to capture their transcripts from certain cell types or conditions. For some studies, lncRNA interactions with other biomolecules have also been captured, which can give clues to their mechanisms of action. Complementary \textit{in silico} methods have been proposed to predict non-coding nature of transcripts and to analyze available RNA interaction data. Here we provide a critical review of such methods and identify associated challenges. Broadly, these can be categorized as reference-based and reference-free or \textit{ab initio}, with the former category of methods requiring a comprehensive annotated reference. The \textit{ab initio} methods can make use of machine learning classifiers that are trained on features extracted from sequences, making them suitable to predict novel transcripts, especially in non-model species. Machine learning approaches such as Logistic Regression, Support Vector Machines, Random Forest, and Deep Learning are commonly used. Initial approaches relied on basic sequential features to train the model, whereas the use of secondary structural features appears to be a promising approach for functional annotation. However, adding secondary features will result in model complexities, thus demanding an algorithm that can handle it and furthermore, considerably increasing the utilization of computation resources. Computational strategies combining identification and functional annotation which can be easily customized are currently lacking. These can be of immense value to accelerate research in this class of RNAs.

Background: DSCAM-AS1 is a cancer-related long noncoding RNA with higher expression levels in Luminal A, B and HER2-positive Breast Cancer (BC), where its expression is strongly dependent on Estrogen Receptor Alpha (ERα). Methods: To decipher its function, DSCAM-AS1 expression was measured by qRT-PCR in tissue samples from 93 BC patients in addition to a meta-analysis of 30 gene expression datasets, together with the evaluation of its association with clinical data. By computational analyses of our RNA-Seq in MCF-7 cells, we investigated the DSCAM-AS1 knock-down effects at both gene and isoform levels. Results: We confirmed DSCAM-AS1 overexpression in high grade Luminal A, B and HER2+ BCs and found a significant correlation with disease relapse. 908 genes were regulated by DSCAM-AS1-silencing, primarily involved in cell cycle and inflammatory response. Noteworthy, the analysis of alternative splicing and isoform regulation revealed 2,085 splicing events regulated by DSCAM-AS1, enriched in differential polyadenylation sites and 3’UTR shortening events. Finally, the DSCAM-AS1-interacting splicing factor hnRNPL was predicted as the most enriched RBP for exon skipping and 3’UTR events. Conclusion: The relevance of DSCAM-AS1 overexpression in BC is confirmed by clinical data and further enhanced by its possible involvement in the regulation of RNA processing, which is emerging as one of the most important dysfunctions in cancer.

Cervical cancer is known as one of the most important cancers in women worldwide. Chemotherapy is a standard treatment for advanced/recurrent cervical cancer in which the prognosis of the disease is really poor and the 1-year survival chance in these patients is maximally 20%. However, resistance to anticancer drugs is a major problem in treating cancer. Cervical cancer stem cells are considered as a fundamental cause of chemo and radio-resistance and also relapse after primary successful treatment. Signaling pathways include a wide range of molecular mechanisms contribute to drug resistance. Recently, microRNAs (miRNAs) are announced as a group of molecular biomarkers involving in response to chemotherapy in cancer patients. As the miRNAs, there are some long non-coding RNAs (LncRNAs) which their aberrant expression is considered as a biomarker for monitoring chemoresistance. In this review, we summarized current reports about the involvement of signaling pathways during chemoresistance in cervical cancer. Then, genes that have been demonstrated their involvement during drug resistance in cervical cancer were tabulated. Further, miRNAs that have been reported as biomarkers during treatment are listed. By bioinformatic analysis, we predictedmiR-335-5p and miR-16-5p as the most potential biomarkers for monitoring resistance to chemotherapy. Finally, long non-coding RNAs that have been introduced in recent studies as novel biomarkers during the response to chemotherapy were mentioned.

Emergence of zoonotic-human pathogens is proven to be a lethal threat to public health, and RNA virus including influenza viruses, severe acute respiratory syndrome coronavirus, middle east respiratory syndrome coronavirus, Wuhan coronavirus (COVID-19), plays a pivotal role. As those viruses as airborne microorganisms spread mainly by tiny airborne particles, it is important to de-active those airborne particles before their entry into human bodies. In this study, we investigated the effect of far infrared (FIR) radiation on inhibition of airborne microorganisms. The result confirmed that double stand DNA from airborne microorganisms were stable under mild FIR radiation. However, single strand RNA from them was found to be sensitive to FIR radiation, indicating that RNA virus in airborne particles is instable under FIR radiation. Based on this observation, two models on usage of FIR radiation to prevent RNA virus transmission and cure RNA virus infection were proposed, implying that FIR radiation might be a cheap, convenient, and efficient method in clinic to treat RNA virus.

Powdery mildew caused by Blumeria graminis f. sp. tritici (Bgt) is one of many severe diseases that threaten bread wheat (Triticum aestivum L.) yield and quality worldwide. The discovery and deployment of powdery mildew resistance genes (Pm) can prevent this disease epidemic in wheat. In a previous study, we transferred the powdery mildew resistance gene Pm57 from Aegilops searsii into common wheat and cytogenetically mapped the gene in a chromosome region with the fraction length (FL) 0.75-0.87, which represents 12% of 2Ss#1 segment on the long arm of chromosome 2Ss#1. In this study, we performed RNA-Seq on three infected and mock-infected wheat-Ae. searsii 2Ss#1 introgression lines with Bgt-isolates inoculation at 0, 12, 24, and 48 hours after inoculation. Then we designed 79 molecular markers based on transcriptome sequences and physically mapped them to Ae. searsii chromosome 2Ss#1- in seven intervals. We used these markers to identify 46 wheat-Ae. searsii 2Ss#1 recombinants induced by ph1b, a deletion mutant of pairing homoelogous (Ph) genes. Analysis of the 46 ph1b-induced 2Ss#1L recombinants with different Bgt-responses using 28 2Ss#1L-specific molecular markers in the interval FL0.72-0.87 where Pm57 is located, and the flanking intervals, we physically mapped Pm57 gene on the long arm of 2Ss#1 in a 5.13 Mb genomic region, which was flanked by markers X67593 (773.72 Mb) and X62492 (778.85 Mb). By comparative synteny analysis of the corresponding region on chromosome 2B in Chinese spring (T. aestivum L.) with other model species we identified ten genes that are putative plant defense-related (R) genes which includes six coiled-coil nucleotide-binding site-leucine-rich repeat (CNL), three nucleotide-binding site-leucine-rich repeat (NL) and a leucine-rich receptor-like repeat (RLP) encoding proteins. This study will lay a foundation for further cloning of Pm57, and benefit the understanding of interactions between resistance genes of wheat and powdery mildew pathogens.

Although there is a several array of diagnostic and therapeutic choices for pancreatic cancer in recent years, a crucial medical approach for the refractory disease is still needed. Oligonucleotide therapeutics, such as those based on antisense RNAs, RNA interference, aptamers and decoys, are promising agents against pancreatic cancer because they identify a specific nucleotide sequence or protein and interfere with gene expression as molecular-targeted agents. Within just the past quarter-century, the diversity and feasibility of these drugs as diagnostic or therapeutic tools have dramatically increased. Actually, there have been several clinical and preclinical studies of oligonucleotides for patients with pancreatic cancer so far. To support the discovery of effective diagnostic or therapeutic options by using oligonucleotide-based strategies in the absence of satisfactory therapies for long-term survival and the rising trend of diseases, we summarize the current clinical trials of oligonucleotide therapeutics for pancreatic cancer patients with underlying preclinical or scientific data and focus on the possibility of oligonucleotides to target pancreatic cancer in clinical implications.