Proper species identification from ancient DNA samples is a difficult task that sheds light on the evolutionary history of pathogenic microorganisms. The field of palaeomicrobiology has undoubtedly benefited from the advent of untargeted metagenomic approaches that use next-generation sequencing methodologies. Nevertheless, assigning ancient DNA at the species level is a challenging process. Recently, the gut microbiome analysis of three pre-Columbian Andean mummies [1](Santiago-Rodriguez et al. 2016) has called into question the identification of Leishmania in South America. Here, the metagenomic data filed in MG-RAST (Metagenomics RAST server) were used for a further attempt to identify members of the Trypanosomatidae family infecting these ancient remains. For this purpose, we used two metagenomic analysis tools. In the first step, data were analysed using the ultrafast metagenomic sequence classifier, based on exact alignment of k-mers (Kraken). In the second step, we used Bowtie2, an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. We then compared the output results. These approaches highlight some interesting findings on potential infections by human pathogenic trypanosomatids in these three pre-Columbian mummies.

The epidermal cells on the surface of the cotton ovules undergo differentiation to produce fibers, which are single-celled hair-like protrusions resembling the plant trichomes. The initiation of these unicellular fibers from the cotton ovule surface is a complex and tightly regulated process. The initiation step is the cell fate-determining stage, which leads to the commitment of cells that eventually developed into fibers, thus becomes the most crucial phase in fiber development. The in-depth knowledge of molecular regulation is a prerequisite to get a clear view of the fiber initiation process's genetic and epigenetic control. The identification and functional validation of cotton fiber initiation-related genes, few fibreless mutants, transcription factors, microRNAs, epigenetic regulators, as well as the elucidation of the role of phytohormones as signaling molecules, has played a significant role in understanding the cotton fiber initiation process at the molecular level. This review focuses on the comprehensive information regarding the genetic and epigenetic regulation of cotton fiber initiation. Thus, the review will provide readers insight into mechanistic details that operate during cotton fiber initiation.

Polymer-based piezoelectric biomaterials have already proven their relevance for tissue engineering applications. Further, the morphology of the scaffolds plays also an important role in cell proliferation and differentiation. The present work reports on poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV), a biocompatible, biodegradable and piezoelectric biopolymer that has been processed in different morphologies, including films, fibres, microspheres and 3D scaffolds. Further, the corresponding magnetically active PHBV-based composites were also produced. The effect of the morphology on physico-chemical, thermal, magnetic and mechanical properties of pristine and composites samples was evaluated, as well as their cytotoxicity. It was observed that the morphology does not strongly affect the properties of the pristine samples but the introduction of cobalt ferrites induces changes in the degree of crystallinity that could affect the applicability of prepared biomaterials. Young modulus is dependent of the morphology and also increases with the addition of cobalt ferrites. Both, pristine and PHBV/cobalt ferrite composite samples are no cytotoxic, indicating their suitability for tissue engineering applications.

There are two contrary opinions regarding the risk if mainland China (MC) moves away from its zero-COVID policy. Some experts think the risk shall be much lower than influenza as per MC’s own COVID-19 case fatality rate (CFR), while some other experts think the risk shall be much higher than influenza as per the COVID-19 CFRs of other regions. We elucidate here that this and multiple other striking differences in the CFR between various scenarios all support and substantially resulted from the view that good IDM is highly powerful to mitigate COVID-19, where IDM (isolation-disinfection-maintenance) means isolation of COVID-19 cases from other people, disinfection of their living environments, and health maintenance (e.g., rest, nutrition, breathing). The high effect of good IDM is also supported by the theoretic functions of IDM in minimizing co-infections and maintaining body functions, and the fact that all the 505 COVID-19 deaths reported in MC in 2022 before May 5 died directly of severe underlying diseases with COVID-19. Although it is tough for people in poverty to obtain good IDM, good IDM can be feasible at home for the most mild cases and in hospitals for the most severe cases. Therefore, good IDM can be crucial to mitigating COVID-19 worldwide. It also suggests that the risk for China to end its zero-COVID policy depends on China’s control policies or measures. Based on the effect of IDM, the cautious co-existence policy was proposed for COVID-19 control. This policy could reduce the whole death toll in MC because good IDM is non-specific and can reduce deaths of various other diseases. The cautious co-existence policy (non-specific) and the vaccination policy (specific) aid each other to mitigate COVID-19, and they cannot replace each other. Those who are qualified in health for vaccination should be vaccinated against COVID-19 timely.

Logistics Engineering has transcended over the decades into an approach for competitive benefits in organisational performance and logistics efficiency. Most industries are recognising that significant savings are available to companies that are able to ordinate and improve within their logistics operations. Companies today face great challenges because the successful supply of many products and services needs to the effective integration of logistics activities across a prolongation supply chain and an increasing geographical separation. Moreover, logistics integration approach involves both internal integration for an ordinated, unified process as well as relationships to react flexibly, changeability, and responsibility to customer's demands. In this study, by using of Fuzzy Vikor (F-Vikor), the best combination of RIR was selected and RIR Locating was done. The main aim of this paper is survey and design of the integrated operational logistics network (IOLN) and also, a proposed IOLN to integration of the Iran Khodro Co Supply Network.

To better understand the genes with altered expression caused by infection with the novel coronavirus strain SARS-CoV-2 causing COVID-19 infectious disease, a tensor decomposition (TD)-based unsupervised feature extraction (FE) approach was applied to a gene expression profile dataset of the mouse liver and spleen with experimental infection of mouse hepatitis virus, which is regarded as a suitable model of human coronavirus infection. TD-based unsupervised FE selected 134 altered genes, which were enriched in protein-protein interactions with orf1ab, polyprotein, and 3C-like protease that are well known to play critical roles in coronavirus infection, suggesting that these 134 genes can represent the coronavirus infectious process. We then selected compounds targeting the expression of the 134 selected genes based on a public domain database. The identified drug compounds were mainly related to known antiviral drugs, several of which were also included in those previously screened with an in silico method to identify candidate drugs for treating COVID-19.

This paper presents a new methodology that provides the analysis of surface texture changes in areas adjacent to the volcano and its impact product of volcanic activity. To do this, algorithms from digital image processing such as the co-occurrence matrix and the wavelet transform are used. These methods are working on images taken by the Landsat satellite platform sensor 5 TM and Landsat 7 ETM + sensor, and implemented with the purpose of evaluating superficial changes that can warn of surface movements of the volcano. The results were evaluated by similarity metrics for grayscale images, and validated in two different scenarios that have the same type of eruption, but differ, essentially, in climate and vegetation. Finally, the proposed algorithm is presented, setting the parameters and constraints for implementation and use.

Leucine-rich repeat receptor-like kinases (LRR-RLKs) have been reported to play important roles in plant growth, development and stress responses. However, no comprehensive analysis of this family has been performed in Gossypium, which are important economic crop and suffer various stresses in growth and development. Here we conducted a comprehensive analysis of LRR-RLK family in four Gossypium species (G. arboreum, G. barbadense, G. hirsutum and G. raimondii). A total of 1641 LRR-RLK genes were identified in the four Gossypium species involved in our study. Maximum-likelihood phylogenetic tree revealed that all the LRR-RLK genes were divided into 21 subgroups. Exon-intron organization structure of LRR-RLK genes kept relative conserved in subfamilies and between Arabidopsis and Gossypium. Subfamilies XI and XII were found dramatically expanded in Gossypium. Tandem duplication acted as an important mechanism in expansion of Gossypium LRR-RLK gene family. Function analysis suggested that plant hormone signaling and plant-pathogen interaction pathway were enriched in Gossypium LRR-RLK genes. Promoters analysis and expression profiles analysis revealed that Gossypium LRR-RLK genes were extensively regulated by TFs, phytohormone and various environmental stimuli, and play key roles in stress defense and diverse development processes. Our study provided valuable information for further function study of Gossypium LRR-RLK genes.

Contemporary literature dealing with the governance and exploitation of common-pool natural resources was initiated by Elinor Ostrom in 1990, and has been growing fast ever since. On the contrary, within the same research stream, the study of the presence and economic role of common resources in entrepreneurial organizations is, to date, under-researched. This work endeavors to fill some gaps in this research perspective by: (i) spelling out a new-institutionalist framework for the analysis of the accumulation and governance of common capital resources within organizational boundaries; (ii) considering co-operative enterprises as the organizational form that, on the basis of historical record, and of behavioral and institutional characteristics, demonstrated to be most compatible with a substantial role for common and non-divided asset-ownership and with its governance thereof; (iii) evidencing and explaining the strong connection between cooperative longevity and the presence of non-divided asset ownership. The economic forces influencing the optimal level of self-financed common capital resources in co-operatives are enquired. Conclusions to the paper evidence the main reasons why the new approach can better explain than preceding ones the economic sustainability and longevity of cooperative enterprises.

The devastating impact of the ongoing coronavirus disease 2019 (COVID-19) on public health, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has made fighting of the COVID-19 pandemic is a top priority in medical research and pharmaceutical development. Surveillance of SARS-CoV-2 mutations is essential for the comprehension of SARS-CoV-2 variant diversity and their impact on virulence and pathogenicity. The SARS-CoV-2 open reading frame 10 (ORF10) protein interacts with multiple human proteins CUL2, ELOB, ELOC, MAP7D1, PPT1, RBX1, THTPA, TIMM8B, and ZYG11B expressed in the lung tissues. Mutations and co-mutations in the emerging SARS-CoV-2 ORF10 variants are expected to impact the severity of the virus and its associated consequences. In this article, We highlight 128 single mutations and 35 co-mutations in the unique SARS-CoV-2 ORF10 variants in this article. The possible predicted effects of these mutations and co-mutations on the secondary structure of ORF10 variants and host protein interactomes are presented. The findings highlight the possible effects of mutations and co-mutations on the emerging 140 ORF10 unique variants from secondary structure and intrinsic protein disorder perspectives.

Loyalty is one of the greatest intangible assets that any organization can possess and improving client loyalty is a primary marketing goal that can have a significant financial impact on any business. This quantitative study examined the mediating role of communication on the relationship between satisfaction and loyalty (attitudinal and behavioral) in veterinary clinics, along with the moderating roles of trust, commitment, perceived value, and relational characteristics. Responses collected from 351 pet-owners through social media were analyzed using descriptive and inferential statistics. The results show that attitudinal loyalty (AL) has a strong positive relationship with communication at multiple points in a veterinary clinic whereas the relationship with behavioral loyalty was not as clear. Additional findings suggest that AL, which is influenced by trust in the veterinarian, communication from staff members and commitment, has a strong positive relationship with behavioral intentions, increases the number of products and services that a pet-owner consumes at his or her primary veterinary clinic, and attenuates the role of cost in receiving veterinary care. These findings can help veterinary clinic owners and managers in developing and implementing relationship strategies that improve pet-owner loyalty. The article that follows is a synopsis of the author’s dissertation.

To guide analysts to select the right tool and parameters in differential gene expression analysis of single-cell RNA sequencing (scRNA-seq) data, we developed a novel simulator that recapitulates the data characteristics of real scRNA-seq datasets while accounting for all the relevant sources of variation in a multi-subject, multi-condition scRNA-seq experiment: the cell-to-cell variation within a subject, the variation across subjects, the variability across cell types, the mean/variance relationship of gene expression across genes, library size effects, group effects, and covariate effects. By applying it to benchmark 12 differential gene expression analysis methods (including cell-level and pseudo-bulk methods) on simulated multi-condition, multi-subject data of the 10x Genomics platform, we demonstrated that methods originating from the negative binomial mixed model such as glmmTMB and NEBULA-HL outperformed other methods. Utilizing NEBULA-HL in a statistical analysis pipeline (https://github.com/interactivereport/scRNAseq_DE) for single cell analysis will enable scientists to better understand cell-type specific transcriptomic response to disease or treatment effects and to discover new drug targets. Further, application to two real datasets showed the outperformance of our differential expression (DE) pipeline, with unified findings of differentially expressed genes (DEG) and a pseudo-time trajectory transcriptomic result. In the end, we made recommendations of filtering strategies of cells and genes based on simulation results to achieve optimal experimental goals.

The study presents a mathematical modeling for supporting the premise that our body is composed of blockchain systems. A cell population is considered a space with peer-to-peer communication networks for applying blockchain protocol. Transaction is defined as gene expression that constantly occurs for protein synthesis in each cell. The transaction process proceeds according to the blockchain protocol with sharing and recording the data on the blockchain ledger. The premise comes from the clues of the previous research such that the cell population is a complex structured network system having cell-to-cell connections. Although individual cells exhibit stochastic nonlinear dynamic behavior, cell population shows consensus behavior that reaches to ensemble through interaction among cells. It is inferred that gene expression is not regulated by the corresponding cell only nor determined by external intelligence such as the brain. This is achieved through a consensus through stochastic interactions between cells over the whole cell population. These findings imply that mathematical blockchain modeling is a suitable for gene expression process. The original contribution of the study is a methodology for applying mathematically the blockchain protocol to the real biological gene expression process. In other words, the DNA sequence is converted into a numeral bit sequence that makes it possible to implement the blockchain protocol. A new DNA sequence scheme is proposed with adding methylated cytosine and adenine as the 5th and 6th bases for including epigenetic information which has profound effect on gene expression and regulation. The methodology was applied to the real biological synthesis process of protein samples. The protein is composed of amino acids that are encoded by triplet codons of 216 kinds with 6 base RNA sequence. The gene expression information is traced backward from a synthesized protein sample, amino acids of codons, RNA transcript up to DNA sequence. One of the results is a numeric value in the form of a bit sequence with which mathematical blockchain modeling is applicable. The cryptographic authentication and the consensus process are mathematically proven to work properly by the blockchain protocol. It implies that the same protein is synthesized, but with different epigenetic data, then protein's latent material properties will certainly be different. Although the result has not been justified by the biologic experiment yet, it is sure that the biological hidden algorithm inside DNA sequence will be revealed by the binary bit-logic with physical on/off states which is mathematically proven. The research will greatly contribute to disease treatment and medicine development as well as epigenetics in the future.

Background: The febrile patient from tropical areas, in which emerging arboviruses are endemic, represent a diagnostic challenge and potential co-infections with other pathogens (i.e bacteria or parasites) are usually overlooked. Objectives: We present a case of an elderly woman diagnosed with dengue, chikungunya and Leptospira interrogans co-infection. Study Design: Case report. Results: An 87-year old woman from Colombia complained of upper abdominal pain, arthralgia, myalgia, hyporexia, malaise and intermittent fever accompanied with progressive jaundice. She had a medical history of chronic heart failure (Stage C, NYHA III), without documented cardiac murmurs, right bundle branch block, non-valvular atrial fibrillation, hypertension, and chronic venous disease. Her cardiac and pulmonary status quickly deteriorated after 24 hours of her admission without electrocardiographic changes and she required ventilatory and vasopressor support. In the next hours the patient evolved to pulseless electrical activity and then she died. Dengue IgM, NS1 ELISA, MAT for Leptospira interrogans and RT-PCR for chikungunya, were positive. Discussion: This case illustrates a multiple co-infection in a febrile patient from a tropical area of Latin America that evolved to death.

This paper discusses the computer-aided (CAD) classification between Hepatocellular Carcinoma (HCC), i.e., the most common type of liver cancer, and Liver Abscess, based on ultrasound image texture features and Support Vector Machine (SVM) classifier. Among 79 cases of liver diseases, with 44 cases of HCC and 35 cases of liver abscess, this research extracts 96 features of Gray-Level Co-occurrence Matrix (GLCM) and Gray-Level Run-Length Matrix (GLRLM) from the region of interests (ROIs) in ultrasound images. Three feature selection models, i) Sequential Forward Selection, ii) Sequential Backward Selection, and iii) F-score, are adopted to determine the identification of these liver diseases. Finally, the developed system can classify HCC and liver abscess by SVM with the accuracy of 88.875%. The proposed methods can provide diagnostic assistance while distinguishing two kinds of liver diseases by using a CAD system.

Nowadays, we live in a world in which people are facing with a lot of data that should be stored or displayed. One of the key methods to control and manage this data refers to grouping and classifying them in clusters. Today, clustering has a critical role in information retrieval methods for organizing large collections inside a few significant clusters. One of the main motivations for the use of clustering is to determine and reveal the hidden and inherent structure of a set of data. Ensemble clustering algorithms combine multiple clustering algorithms to finally reach an overall clustering system. Ensemble clustering methods by lack of information fusing utilize several primary partitions of data to find better ways. Since various clustering algorithms look at the different data points, they can produce various partitions from such data. It is possible to create a partition with high performance by combining the partitions obtained from different algorithms, even if the clusters to be very dense from each other. Most studies in this area have examined all the initial clusters. In this study, a new method is used in which the most sustainable clusters are utilized instead of all primary produced clusters. Consensus function based on co-association matrixes used to select more stable clusters. The most stable clusters selection method is done by cluster stability criterion based on F-measure. Optimization functions are used to optimize the obtained final clusters. The genetic algorithm is the optimizer used in this article to find the ultimate clusters participated in a consensus. Experimental results on several datasets show that the output of proposed method is various clusters with high stability.

Successful engineering of a microbial host for efficient production of a target product from a given substrate can be viewed as an extensive optimization task. Such a task involves the selection of high activity enzymes as well as their gene expression regulatory control elements (i.e., promoters and ribosome binding sites). Finally, there is also the need to tune expression of multiple genes along a heterologous pathway to relieve constraints from rate-limiting step and help reduce metabolic burden on cells from unnecessary over-expression of high activity enzymes. While the aforementioned tasks could be performed through combinatorial experiments, such an approach incurs significant cost, time and effort, which is a handicap that can be relieved by application of modern machine learning tools. Such tools could attempt to predict high activity enzymes from sequence, but they are currently most usefully applied in classifying strong promoters from weaker ones as well as combinatorial tuning of expression of multiple genes. This perspective reviews the application of machine learning tools to aid metabolic pathway optimization through identifying challenges in metabolic engineering that could be overcome with the help of machine learning tools.

This initial report of a longitudinal study of 192 English hospital nurses has measured Nursing Values (the 6Cs of nursing); Personality, Self-Esteem and Depression; Burnout Potential; Work-Life Balance Stress; ‘Hardy Personality’; and Intention to Leave Nursing. Correlational, component and cluster analysis identifies four groups: “The Soldiers” (N = 79) , with medium scores on most measures, who bravely ‘soldier on’ in their nursing roles, in the face of numerous financial cuts to the National Health Service, and worsening nurse-patient ratios; “Cheerful Professionals” (N = 54), coping successfully with nursing roles, and a variety of challenges, in upwardly mobile careers; “High Achievers” (N = 39), senior nurses with strong profiles of a ‘hardy personality’, and commitment to fundamental nursing values; “Highly Stressed, Potential Leavers” (N = 20), with indicators of significant psychological distress, and difficulty in coping with nursing role challenges. We propose a model of co-counselling and social support for this distressed group, by nurses who are coping more successfully with multiple challenges. We discuss the role of nurse educators in fostering nursing values, and developing and supporting ‘hardy personality’ and emotional resilience in recruits to nursing. This study is framed within the disciplinary approach of Critical Realism, which identifies the value basis for research and dialogue in developing strategies for social change.

Directional protective relaying based on amplitude comparison of traveling wave on continuous co-phase auto-transformer(AT) power transmission system was proposed. Phase-model transformation is used for decoupling transient fault signals and get aerial mode component. The forward and backward traveling wave are obtained by calculating aerial mode component, then the intrinsic mode function(IMF) components can be obtained through Variational Mode Decomposition(VMD), the module maxima are obtained through calculating the IMF components. The fault direction is determined by the ratio of fault components. If two faults relays at the ends of electric traction networks detect a fault to be in the forward direction, the fault occurred in the internal area, the protection would operate properly. The simulation tests indicate that the protection scheme is feasible, and the proposed protection method can discriminate internal faults from external faults under various fault types, and its performances are immune to fault initial angle, ground resistance, etc.

Growth-regulating factor (GRF) is a plant-specific transcription factor family, which is involved in nearly all of the central developmental processes in plants. However, little is known about GRF family genes in cultivated sunflower. In this study, 17 GRF genes were identified and characterized from sunflower genome. Their gene structures, conserved motifs, chromosomal distributions and phylogenetic relationships were analyzed. The expression patterns of these genes were detected in various tissues of sunflower inbred line SK02R, which revealed that the 10 seed-specific GRF genes may play important roles during seed development in sunflower. Additionally, transcripts changes of the GRFs under two major abiotic stresses and phytohormones showed that most of the detected GRFs were reduced significantly by GA3 treatment, and other treatments(ABA, NaCl and PEG6000) differently regulated various sunflower growth-regulating factors at different time points. MiR396 target analysis indicated that there may exist a complicated homeostasis between miR396 and its targets GRF and WRKY transcription factor genes in cultivated sunflower. The phylogenetic and expression analyses of the GRF gene family in sunflower would be useful for further cloning and function exploration of the HaGRF genes.

The article is aimed at a brief comparison and analysis of the results of queries to IEEE Xplore and the leading abstract databases Scopus and Web of Science to identify research trends. Some errors in the Author Keywords in Web of Science have been revealed. Therefore, a more detailed analysis was conducted by comparing different types of key terms for IEEE Xplore and Scopus platforms only. I used IEEE Access journal metadata as indexed on both platforms. The sample match for IEEE Xplore and Scopus was achieved by comparing DOI. The IEEE Xplore metadata contains more types of key terms, which provides an advantage in analyzing research trends. Using NSPEC Controlled Terms from expert-compiled vocabulary provides a more stable data, which gives an advantage when considering the change of terms over time. Apriori, an algorithm for finding association rules, has been used to compare co-occurrence of terms for a more detailed description of sample subjects on both platforms. VOSviewer was used to analyze trends in scientific research based on IEEE Xplore data. The 2011-2021 ten-year period was divided into two sub-intervals for comparing the occurrence of Author Keywords, IEEE Terms, and NSPEC Controlled Terms. Using the IEEE conference proceedings bibliometric data, I illustrated the importance of context in estimating the rate of growth of publishing activity on a topic of interest.

Fear extinction requires coordinated neural activity within the amygdala and medial prefrontal cortex (mPFC). Any behavior has a transcriptomic signature that is modified by environmental experiences, and specific genes are involved in functional plasticity and synaptic wiring during fear extinction. Here, we investigated the effects of optogenetic manipulations of prelimbic (PrL) pyramidal neurons on amygdala gene expression to analyze the specific transcriptional pathways involved in adaptive and maladaptive fear extinction. To this aim, transgenic mice were (or not) fear-conditioned and during the extinction phase they received optogenetic (or sham) stimulations over PrL pyramidal neurons. At the end of behavioral testing, electrophysiological (neural cellular excitability and Excitatory Post-Synaptic Currents) and morphological (spinogenesis) correlates were evaluated in the PrL pyramidal neurons. Furthermore, transcriptomic cell-specific RNA-analyses (differential gene expression profiling and functional enrichment analyses) were performed in amygdala pyramidal neurons. Our results show that the optogenetic activation of PrL pyramidal neurons in fear-conditioned mice induces fear extinction deficits, reflected in an increase of cellular excitability, excitatory neurotransmission, and spinogenesis of PrL pyramidal neurons, and in strong modifications of the transcriptome of amygdala pyramidal neurons. Understanding the electrophysiological, morphological and transcriptomic architecture of fear extinction may facilitate the comprehension of fear-related disorders.

In December 2019, pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection emerged in Wuhan City, Hubei Province, China. Early in 2020, the World Health Organization (WHO) announced a new name for the 2019-nCoV-caused epidemic disease: coronavirus disease 2019 (COVID-19) and declared COVID-19 to be the sixth international public health emergency. Cellular co-infection is a critical determinant of both viral fitness and infection outcome and plays a crucial role in shaping the host immune response to infections. In this study, sixty-eight public next-generation sequencing libraries from SARS-CoV-2 infected patients were retrieved from the NCBI Sequence Read Archive database using SRA-Toolkit. Using an alignment-free method based on K-mer mapping and extension, SARS-CoV-2 was identified in all except three patients. Influenza A H7N9 (3/68), Human immunodeficiency virus 1 (1/68), rhabdovirus isolate (3/68), Human metapneumovirus (1/68), coronaviruses NL63 (1/68), Parvovirus (1/68), Simian virus 40 (1/68), and hepatitis virus (1/68) genome sequences were detected in SARS-CoV-2 infected patients.

The Brassica family contains several economically important crops, including rapeseed (Brassica napus, 2n = 38, AACC), the second largest source of seed oil and protein meal worldwide. However, research in rapeseed is hampered because it is complicated and time-consuming for researchers to access different types of expression data. We therefore developed the Brassica Expression Database (BrassicaEDB, https://biodb.swu.edu.cn/brassica/) for the research community. We conducted RNA sequencing (RNA-Seq) of 103 tissues from rapeseed cultivar ZhongShuang11 (ZS11) at seven developmental stages (seed germination, seedling, bolting, initial flowering, full-bloom, podding, and maturation). We determined the expression patterns of 101,040 genes via FPKM analysis and displayed the results using the eFP browser. We also analyzed transcriptome data for rapeseed from 70 BioProjects in the SRA database and obtained three types of expression level data (FPKM, TPM, and read counts). We used this information to develop the BrassicaEDB, including eFP, Treatment, Coexpression, and SRA Project modules based on gene expression profiles and Gene Feature, qPCR Primer, and BLAST modules based on gene sequences. The BrassicaEDB provides comprehensive gene expression profile information and a user-friendly visualization interface for Brassica crop researchers. Using this database, researchers can quickly retrieve the expression level data for target genes in different tissues and in response to different treatments to elucidate gene functions and explore the biology of rapeseed at the transcriptome level.

The purpose of this study is nutrient resources recovery by achieving the optimal chemical oxygen demand (COD) and carbon to nitrogen ratio (C/N) in co-composting wastewater treatment plant sludge with Municipal Solid Wastes (MSW). In this effort, the co-composting has been conducted in form of a case study in the northern region of Iran. In this research, 192 tests were carried out on four series of samples examined in terms of waste to sludge ratio, different aeration period, the percent of porous materials and the moisture content. This study was carried out at a temperature of 50 °C for a 15 day period by application of the in-vessel system and shows that the best ratio for waste to sludge is 2:1, while the 8 hour period is the best aeration period. The porous material which can be added to the composting process is limited to 15% in weight. In other words, any more or less amount of this material will adversely impact the process. Moreover, this research suggests that the sludge dewatering is not required in such processes. In Addition, the efficiency of both COD and C/N reductions equals to about 40%.

In 2023, the technological landscape witnessed an unprecedented surge of transformative innovations, including Web 3.0 and machine learning, poised to revolutionize various aspects of our daily lives. At the forefront of this revolution stands artificial intelligence (AI), which has evolved from a concept once confined to science fiction into an indispensable force reshaping industries on a global scale. Notably, recent years have seen remarkable strides in AI functionalities, particularly in machine learning, computer vision, and natural language processing. These advancements have empowered AI to generate diverse interactions and media autonomously. This study ultimately provides invaluable insights into the dynamic intersection of AI and Advertising, con-tributing to a deeper comprehension of this evolving field. This study conducts a comprehensive review of Artificial Intelligence within the advertising domain, employing network analysis. By meticulously examining the evolution of AI through co-occurrences of terms, keywords, and co-authorship analysis, we aim to unveil the relationship of AI & Advertising through the lens of Generative models to identify pivotal trends, core concepts, and seminal studies that have profoundly influenced the industry. The analysis charts the trajectory leading to the emergence of Generative Artificial Intelligence (GenAI), a transformative development poised to revolutionize advertising practices and consumer engagement. In tandem with these objectives, the results highlight vital trends, emphasizing the growing prominence machine learning tools and techniques such as deep learning techniques and advanced natural language processing methods like word2vec, GANs, and more in shaping the future of advertising practices.

Calcineurin B-like proteins (CBL)-interacting protein kinases (CIPKs) by interacting with CBLs regulate developmental processes, hormone signalling transduction and mediate stress responses in plants. Although the genome of chickpea is available, information of CIPK gene family has been missing in chickpea. Here, a total of 22 CIPK encoding genes were identified in chickpea and characterized by in silico methods. We found a high structural conservation in chickpea CIPK family. Our analysis showed that chickpea CIPKs have evolved with dicots from common ancestors, and extensive gene duplication events have played an important role in evolution and expansion of CIPK family in chickpea. Most chickpea CIPK proteins localize in cytoplasm and nucleus. Promoter analysis revealed various cis-regulatory elements related to plant development, hormone signaling and abiotic stresses. Expression analysis indicated that CIPKs are significantly expressed in a spectrum of developmental stages, tissue/organs that hinted their important role in plant development. Several CIPK genes had specific and overlapping expressions in different abiotic stresses and seed development stages, suggesting the important role of CIPK family in abiotic stress signaling, and seed development in chickpea. Thus, this study provides the avenue for detailed functional characterization of CIPK family in chickpea and other legume crops.

Background: Nodal peripheral T-cell lymphomas (nPTCLs) encompass a heterogeneous group of mature and aggressive lymphoid malignancies, including peripheral T-cell lymphoma, not otherwise specified (PTCL/NOS), angioimmunoblastic T-cell lymphoma (AITL) and anaplastic large cell lymphoma (ALCL) ALK-positive and ALK-negative. Their differential diagnosis and prognosis are an issue in the clinical practice. Accurate biomarkers to refine the different subtypes of nPTCLs and to stratify their prognosis are essential to improve their treatment approach. The aim of this study was to test the prognostic impact of GATA3 gene expression, and its capability to discriminate the different subtypes of nPTCLs. Patients and Methods: From 2000 to 2017, 80 patients with nPTCLs were eligible for GATA3 gene expression analysis that was assessed retrospectively by quantitative real time PCR (qRT-PCR) of neoplastic biopsies in Formalin-Fixed Paraffin-Embedded samples (FFPE). Results: Median age was 49 years old (IqR 34-59), 43/80 (53.7%) were male. Median follow-up was 1.72 years. Of them, 36.3% were classified as PTCL/NOS, 31.2% ALK-negative ALCL, 21.2% ALK-positive ALCL and 11.3% AITL. The majority of cases had advanced stage (III/IV). Two-year estimated overall survival (OS) and progression-free survival (PFS) were 52.2% and 39.5%, respectively. The median GATA3 gene expression level was 0.49% (range 0 – 7.07) in all cohort, it was 0.11% for ALK-positive ALCL, 0.46% for ALK-negative ALCL, 0.86% for PTCL/NOS and 0.67% for AITL. The difference of GATA3 gene expression among distinct variants of nPTCLs was statistically significant (p < 0.001). GATA3 gene expression levels ≥ 0.71% discriminate PTCL/NOS from ALK-negative ALCL and AITL with sensitivity of 62% and specificity of 80.3%. GATA3 gene expression levels ≥ median was associated with poor 2-year OS for PTCL/NOS (46.7% x 21.4%, p=0.04) and for ALK-negative ALCL (85.7% x 54.5%, p=0.04). Conclusion: Despite the relative small and heterogeneous group of patients with nPTCLs, GATA3 gene overexpression may be an important biomarker associated with poor prognosis in PTCL/NOS and ALK-negative ALCL. Moreover it may also discriminate different subtypes of nPTCLs. Further studies with larger series of patients should confirm our findings.

Membrane transporters (MTs) are mainly localized at the plasma membrane (PM), tonoplast and vacuolar membrane (VM) of cells in all plant organs. Their work is to maintain the cellular homeostasis by controlling ionic movements across PM channels from roots to upper plant parts, xylem loading and remobilization of sugar molecules from photosynthesis tissues in the leaf (source) to roots, stem and seeds (sink) via phloem loading. The plant’s whole source-to-sink relationship is regulated by multiple transporting proteins in a highly sophisticated manner and driven based on different stages of plant growth and development (PG&D), and environmental changes. The MTs play a pivotal role in PG&D in terms of increased plant height, branches/tiller numbers, enhanced numbers, length and filled panicles per plant, seed yield and grain quality. Dynamic climatic changes disturbed the ionic balance (salt, drought and heavy metals) and sugar supply (cold and heat stress). Due to poor selectivity, some of the MTs also uptake toxic elements in the roots that negatively impact on PG&D, later on also exported to upper parts and then deteriorate the grain quality. As an adaptive strategy, in response to salt and HMs plants activated PM and VM localized MTs that export toxic elements into vacuole, and also translocate in the root’s tips and shoot. However, in case of drought, cold and heat stresses, MTs increased the water and sugar supply to all organs. In this review, we mainly reviewed recent literature from Arabidopsis, halophytes, and major field crops such as rice, wheat, maize and oilseed rape to argue on the global role of MTs in PG&D and abiotic stress tolerance. We also discussed the gene expression level changes and genomic variations within a species as well as within a family in response to developmental and environmental cues.

Background: Ongoing molecular profiling studies enabled by advances in biomedical technologies are producing vast amounts of ‘omic’ data for early detection, monitoring, and prognosis of diverse diseases. A major common limitation is the scarcity of biological samples, necessitating integrative modeling frameworks that can make optimal use of available data for disease classification tasks. Related data sets are often available from different studies, but may have been generated using different technology platforms. Thus, there is a critical need for flexible modeling methods that can handle data from diverse sources to facilitate the discovery of robust biomarkers that underlie disease regulatory processes. Results: In this paper, we introduce a novel framework called Knowledge Augmented Rule Learning (KARL), which incorporates two sources of knowledge, domain, and data, for pattern discovery from small and high-dimensional datasets, such as transcriptomic data. We propose KARL as a transfer rule learning framework in which knowledge of the domain is transferred to the learning process on data in order to 1) improve the reliability of the discovered patterns, and 2) study the knowledge of the domain when used along with data for modeling. In this work, we generated KARL models on gene expression datasets for five types of cancer, including brain, breast, colon, lung, and prostate. As our knowledge of the domain, we used the Ingenuity Knowledge Base (IKB) to extract genes related to hallmarks of cancer and annotated these prior relationships before learning classifiers from these datasets. Conclusions: Our results show that KARL produces, on average, rule models that are more robust classifiers than the baseline without such background knowledge, for our tasks of cancer prediction using 25 publicly available gene expression datasets. Moreover, KARL helped us learn insights about previously known relationships in these gene expression datasets, along with new relationships not input as known, to enable informed biomarker discovery for cancer prediction tasks. KARL can be applied to modeling similar data from any other domain and classification task. Future work would involve extensions to KARL to handle hierarchical knowledge to derive more general hypotheses to drive biomedicine.

Low pasture biomass production and fodder scarcity are among the major challenges affecting productivity of dairy cattle farms in Sri Lanka. As a potential solution to this, two Napier hybrid cultivars CO-5 and Sampoorna were recently introduced and a field experiment was conducted to evaluate their growth, dry matter production and nutritional composition during May to September 2020. Plant measurements and samples were collected at five harvest intervals (4, 6, 8, 10 and 12 weeks after planting), with the plant samples subjected to biomass and nutritional assessments. The number of tillers and leaf length differed (P=0.01) between the two cultivars at 4 weeks harvesting interval (HI) whilst number of leaves differed at 12 HI respectively. Dry matter yield increased (P=0.16) almost linearly whilst crude protein declined exponentially with CO-5 greater than Sampoorna (P=0.057; 9.3% vs 8.7%), with increasing harvesting intervals respectively. In-vitro Organic Matter Digestibility and In-vitro Metabolizable Energy contents were similar across weeks 4, 6 and 8 but then decreased. This study demonstrates that higher dry matter yields (12.54 t/ha) can be obtained by harvesting both cultivars at 12 HI, but from a nutritional perspective harvesting at 6 HI during Yala season of the year would be optimum for farmers.

Suppressors of cytokine signaling (SOCS) influence cytokine and growth factor signaling by negatively regulating the JAK-STAT pathway. This maintains homeostasis during host immune response. However, functional characterization of SOCS family members in invertebrates is limited. In this study, we discovered the Type-I subfamily of the SOCS genes in the mealworm beetle, T. molitor. The full-length ORFs of TmSOCS5, TmSOCS6, and TmSOCS7 consisted of 1,389, 897 and 1,458 nucleotides, encoding polypeptides of 462, 297 and 485 amino acids, respectively, The C-terminal region of TmSOCS was highly conserved in the SH2 and SOCS box domains. Phylogenetic analysis revealed that the three SOCS genes clustered within the same sub-family and the highest amino acid identity was with the Tribolium castaneum SOCS genes (TcSOCS). While the expression of TmSOCS5 and TmSOCS6 was low in larval, pupal, and adult stages of the insect, TmSOCS7 showed higher expression. The expression of TmSOCS5 and TmSOCS6 was higher in larval hemocytes and adult ovary. The microbes expressed the three TmSOCS genes to varying degrees. C. albicans elicited the strongest response in the host with highest 15-fold expression in TmSOCS7 3 h post-inoculation. Collectively, these data suggest that the Type I TmSOCS could play a role in eliciting host immunity.

Background: COVID-19 is a critical pandemic that has affected human communities worldwide, and there is an urgent need to develop effective drugs. Although there are a large number of candidate drug compounds that may be useful for treating COVID-19, the evaluation of these drugs is time-consuming and costly. Thus, screening to identify potentially effective drugs prior to experimental validation is necessary. Method: In this study, we applied the recently proposed method tensor decomposition (TD)-based unsupervised feature extraction (FE) to gene expression profiles of multiple lung cancer cell lines infected with severe acute respiratory syndrome coronavirus 2. We identified drug candidate compounds that significantly altered the expression of the 163 genes selected by TD-based unsupervised FE. Results: Numerous drugs were successfully screened, including many known antiviral drug compounds such as C646, chelerythrine chloride, canertinib, BX-795, sorafenib, sorafenib, QL-X-138, radicicol, A-443654, CGP-60474, alvocidib, mitoxantrone, QL-XII-47, geldanamycin, fluticasone, atorvastatin, quercetin, motexafin gadolinium, trovafloxacin, doxycycline, meloxicam, gentamicin, and dibromochloromethane. The screen also identified ivermectin, which was first identified as an anti-parasite drug and recently the drug was included in clinical trials for SARS-CoV-2. Conclusions: The drugs screened using our strategy may be effective candidates for treating patients with COVID-19.

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.

Appropriate estimation of soil settlement is of significant importance since it directly influences the performance of building and infrastructures that are built on soil. In particular, the settlement of fine-grained soils is critical because of low permeability and continuous settlement with time. Coefficient of consolidation (Cc) is a key parameter to estimate settlement of fine-grained soil layers. However, estimation of this parameter is time consuming, needs skilled technicians, and specific equipment. In this study, Cc was estimated using several soil parameters such as liquid limit (LL), plastic limit (PL), and initial void ratio (e0). Estimating such parameters in laboratory is straight forward and needs substantially less time and cost compared to conventional tests to estimate Cc such as Oedometer test. This study presents a novel prediction model for Cc of fine-grained soils using gene-expression programming (GEP). GEP is a biologically inspired technique capable of offering closed-form solution for the optimal solution. A database consisted of 108 different data points was used to develop the model. A closed-form equation solution was derived to estimate Cc based on LL, PL, and e0. The performance of developed GEP-based model was evaluated through coefficient of determination (R2), root mean squared error (RMSE), and mean average error (MAE). High R2 and low error values indicated the descent performance of the model. Furthermore, the model was evaluated using the additional performance measures and met all the suggested criteria. Furthermore, the model had a better performance in terms of R2, RMSE, and MAE compared to most of existing models. It is expected that the developed model will decrease the time and cost associate with determining Cc of fine-grained soils.

Irish beef farms have experienced poor viability longitudinally, with officially acknowledged ‘crisis’ levels in 2013. In response, beef Producer Organisation (PO) legislation was introduced. Through the lens of international evidence in the literature about how POs function, this paper presents an analysis of Irish stakeholders’ views in the context of a public consultation process. While stakeholders indicate the need for individual POs to collaborate, little emphasis is placed on other factors necessary for success: collaboration with other chain actors; and market differentiation of products. Stakeholders identified primary threats as poor engagement on the part of both farmers and processors/purchasers.

Objective: Taiwan Government’s organizations have endeavored to promote the applications of big data and open data. The “My Health Bank” is one of the measures promoted by the National Health Administration, Ministry of Health and Welfare. This study proposes the perspective of the “value co-creation” with the attempt to extend the concept of service ecosystem and apply it on the platform of My Health Bank to examine whether people (patients, families, and caregivers) can promote their health literacy? Method: This cross-sectional study, with people that have registered at “My Health Bank” as subjects. Complying with the inclusion criteria, 401 questionnaires were delivered, with 391 valid ones, excluding those incompletely and inaccurately filled. Result: That the affecting factors of the co-creation of values: age, education level, annual income, and platform operation show to be significant ( p＜0.05); and gender, occupation, and resource exchange do not reach the significant level (p＞0.1). Conclusion: We found My Health Bank changed the inertia of “value creation” in the traditional medical value, it allows the traditional medical and healthcare industry to expose to the impacts of the mega trend of the internet, the transformation of the platform in a necessary trend.

Although the Slicing Method (SM) is effective for calculating the volume of point cloud objects (PCOs), it is restricted in terms of applicability and practicability because of a certain contingency and directional defects. The Co-Opposite-Direction Slicing Method (CODSM) proposed in this paper is an improved method for calculating PCO volume by increasing parallel (co-opposite-direction) observation and considering the two-way mean as the result. This method takes full advantage of the mutual offsetting of random errors and the compensation of systematic directional errors, which can effectively overcome (or mitigate) the effect of random errors and reduce the effect of systematic errors in SM. In this paper, two typical objects, a cone model and a stone lion base, are the examples for calculating PCO volume using CODSM. The results show that CODSM has all the inherent advantages of SM and effectively weakens the volatility of random errors and the directionality of systematic errors from SM. Therefore, CODSM is a robust configuration upgrade of SM.

The importance of genome organization at the supranucleosomal scale in the control of gene expression is increasingly recognized today. In mammals, Topologically Associating Domains (TADs) and the active / inactive chromosomal compartments are two of the main nuclear structures that contribute to this organization level. However, recent works reviewed here indicate that, at specific loci, chromatin interactions with nuclear bodies could also be crucial to regulate genome functions, in particular transcription. They moreover suggest that these nuclear bodies are membrane-less organelles dynamically self-assembled and disassembled through mechanisms of phase separation. We have recently developed a novel genome-wide experimental method, High-salt Recovered Sequences sequencing (HRS-seq), which allows the identification of chromatin regions associated with large ribonucleoprotein (RNP) complexes and nuclear bodies. We argue that the physical nature of such RNP complexes and nuclear bodies appears to be central in their ability to promote efficient interactions between distant genomic regions. The development of novel experimental approaches, including our HRS-seq method, is opening new avenues to understand how self-assembly of phase separated nuclear bodies possibly contributes to mammalian genome organization and gene expression.

Threats emerging from microplastics pollution in the marine environment have received much global attention. This review assessed sources, fate, and impacts of microplastics in marine ecosystems and identified gaps. Most studies document ubiquity of microplastics and associated environmental effects. Effects include impacts to marine ecosystems, risks to biodiversity, and threats to human health. Microplastic leakage into marine ecosystems arises from plastic waste mismanagement and a lack of effective mitigative strategies. This review identified a scarcity of microplastics mitigation strategies across different stakeholders. Lack of community involvement in microplastic monitoring or ecosystem conservation exists due to limited existence of stakeholder co-management initiatives. Although some management strategies exist for controlling the effects of microplastics (often implemented by local and global environmental groups); a standardized management strategy to mitigate microplastics in coastal areas is urgently required. There is a need to identify focal causes of microplastic pollution in the marine environment through further environmental research. This would extend to creating more effective policies as well as harmonized and extended efforts of educational campaigns and incentives for counteraction and plastic waste reduction, while mandating stringent penalties for polluting the marine environment. This will help reduce microplastic leakage into the environment.

Abstract: We review the development and application of an organic polymer-gel capable of producing fixed, three-dimensional fluorescent images of complex radiation fields. The gel consists for more than 99% of γ-ray-polymerized (~15% conversion) tertiary-butyl acrylate (TBA) containing ~100 ppm of a fluorogenic compound, e.g. maleimido-pyrene (MPy). The radio-fluorogenic effect depends on copolymerization of the MPy into growing chains of TBA on radiation-induced polymerization. This converts the maleimido residue, which quenches the pyrene fluorescence, into a succinimido moeity (SPy), which doesn't. The intensity of the fluorescence is proportional to the yield of free-radicals formed and hence to the local dose deposited. Because the SPy moieties are built into the cross-linked polymer matrix the image is fixed. The method of preparing the gel and imaging the radiation-induced fluorescence are presented and discussed. The effect is illustrated with fluorescent images of the energy deposited in the gel by beams of X-rays, electrons and protons as well as a radioactive isotope.

Renewable sources and electric distribution network can produce or make available a surplus of electric and thermal energies. The Intermediate Temperature Solid Oxide Electrolyzer (IT-SOE) fed by CO2-steam mixtures can store these electric and thermal energies producing CO-H2 mixtures with high conversion efficiency. Inside the IT-SOE, the CO2-steam mixtures are converted to CO-H2 mixtures and O2 through the cathode and anode electrochemical reactions and reverse water gas shift chemical reaction. In this article an IT-SOE stack fed by different types of steam mixtures was tested at different operating temperatures and the stack polarization and electric power curves were detected experimentally. At the highest hydrogen production operating temperature of the stack fed by steam mixtures, the experimental polarization and electric power curves of the stack fed by steam and CO2-steam mixtures were compared. A simulation model of the IT-SOE system (stack and furnace) fed by CO2-steam mixtures was formulated ad hoc and implemented in a Matlab environment and experimentally validated. At the highest hydrogen production stack operating temperature, the IT-SOE system thermal equilibrium current was evaluated through the simulation model. Moreover, the influence of this current on the IT-SOE system efficiency and the CO-H2 mixture degree of purity was highlighted.

The excellent properties of nanomaterials have been confirmed in many fields, but the effects on plants are still unclear. In this study, we have found that bismuth vanadium promoted the growth of taproots and the development of lateral roots, increased the roots activity by regulating the expression of polyamine or hormone-related genes and reducing the accumulation of reactive oxygen species in Arabisdopsis thaliana. Meantime, BV had higher antimicrobial effect than that of graphene oxide (GO). These results showed us a new perspective possibility of nanomaterials assisting the development of plants and crops, which is expected to become one of the ways to solve the problem of controlling and promoting the development of plants and crops.

Terpenoids are toxic compounds produced by plants as a defense strategy against insect herbivores. We tested the effect of Origanum vulgare terpenoids on the generalist herbivore Spodoptera littoralis and the response of the plant to herbivory. Terpenoids were analyzed by GC-FID and GC-MS and quantitative gene expression (qPCR) was evaluated on selected plant genes involved in both terpene biosynthesis. The insect detoxification response to terpenes was evaluated by monitoring antioxidant enzymes activity and expression of insect genes involved in terpene detoxification. O. vulgare terpenoid biosynthesis and gene expression was modulated by S. littoralis feeding. The herbivore-induced increased level of terpenoids (particularly carvacrol and p-cymene) interacted with the herbivore by decreasing larval survival and growth rate. The assimilation by S. littoralis of more than 50% of ingested terpenes correlated with the possible toxic effects of O. vulgare terpenoids. In choice test experiments, carvacrol and γ-terpinene mediated the larval feeding preferences, wherease the prolonged feeding on O. vulgare terpenoids (particularly on γ-terpinene) exerted relevant antinutritional effects on larvae. S. littoralis was found to react to O. vulgare terpenoids by increasing its antioxidant enzymes activities and gene expression, although this was not sufficient to sustain the toxicity of O. vulgare terpenoids.

Recently, Indium Tin Oxide, a highly transparent, well conductive, and CMOS-compatible material, has been paying strong attention to the thermo-optic controlled silicon photonics industry because it allows a miniature of the gap between the core silicon and the heater, thus enabling reducing the electric power consumption and enhancing the switching speed. In this article, we propose an ultralow loss and small-size ITO microheater for the phase shift tuning. The designated microheater is manipulated in realizing a numerical co-design of compact and high bandwidth three-mode converter and three-mode selective router. Simulation results illustrate the 3-dB bandwidth for the three-mode converter and three-mode selective router as much as 100-nm and 40-nm during crosstalk under -25 dB, respectively. Besides, co-designed devices attain relatively large fabrication tolerances corresponding to width and height tolerances of ±50 nm and ±5 nm. In addition, the proposed devices consumed less than 90 mW total power consumption and took a fast switching time below 8 μs. Moreover, both two co-designs can be integrated into an estimated compact footprint of 8 μm2160 μm. Such excellent performances demonstrate the attractive potential of ITO as low-loss thermo-optic phase shifters and open an alternative way for enabling ultrafast and high-speed mode division multiplexing systems and very large-scale photonic integrated circuits.

Cyanobacteria are highly diverse, widely distributed photosynthetic bacteria inhabiting various environments ranging from deserts to the cryosphere. Throughout this range of niches, they have to cope with various stresses and kinds of deprivation which threaten their growth and viability. In order to adapt to these stresses and survive, they have developed several global adaptive responses which modulate the patterns of gene expression and the cellular functions at work. Sigma factors, two-component systems, transcriptional regulators and small regulatory RNAs acting either separately or collectively, for example, induce appropriate cyanobacterial stress responses. The aim of this review is to summarize our current knowledge about the diversity of the sensors and regulators involved in the perception and transduction of light, oxidative and thermal stresses and nutrient starvation responses. The studies discussed here point to the fact that various stresses affecting the photosynthetic capacity are transduced by common mechanisms.

The rapid expansion of transcriptomics from increased affordability of next-generation sequencing (NGS) technologies generates rocketing amounts of gene expression data across biology and medicine, and notably in cancer research. Concomitantly, many bioinformatics tools were developed to streamline gene expression analysis and quantification. We tested the concordance of NGS RNA sequencing (RNA-seq) analysis outcomes between the two predominant programs for reads alignment, HISAT2 and STAR, and the two most popular programs for quantifying gene expression in NGS experiments, edgeR and DESeq2, using RNA-seq data from a series of breast cancer progression specimens, which include histologically confirmed normal, early neoplasia, ductal carcinoma in situ and infiltrating ductal carcinoma samples microdissected from formalin fixed, paraffin embedded (FFPE) breast tissue blocks. We identified significant differences in aligners’ performance: HISAT2 was prone to misalign reads to retrogene genomic loci, STAR generated more precise alignments, especially for early neoplasia samples. edgeR and DESeq2 produced similar lists of differentially expressed genes in stage comparisons, with edgeR producing more conservative, though shorter, lists of genes. Albeit, Gene Ontology (GO) enrichment analysis revealed no skewness in significant GO categories identified among differentially expressed genes by edgeR vs DESeq2. As transcriptome analysis of archived FFPE samples becomes a vanguard of precision medicine, identification and fine-tuning of bioinformatics tools becomes critical for clinical research. Our results indicate that STAR and edgeR are well-suited tools for differential gene expression analysis from FFPE samples.

The current global COVID-19 pandemic is compounding on populations susceptible to tropical illnesses like dengue in different developing countries like Bangladesh. The growing concern is that Bangladesh is a dengue-endemic zone and the peak transmission occurs in the monsoon season (June to October). In the most recent monsoon, a total of 354 dengue cases have been confirmed until 27^th July 2020, data-driven from only 41 hospitals alone. A fifty-three-year-old male patient was found to be co-infected with COVID-19 and dengue fever. Concerns arise as hospitals are increasingly denying to admit the patients. Moreover, reports of the false-positive results in dengue screening tests recorded in different countries further exacerbate the issue. These conditions could postpone the early diagnosis of COVID-19 cases and aggravate the situation. In addition, the overwhelming wave of the dengue cases would be a challenge for the vulnerable health care system of the country which is already under strain due to the COVID-19 pandemic. Failure to establish and implement proper policies might lead to the dengue outbreak with the burdens of the concurrent COVID pandemic, resulting in the collapse of the health and social system, as well as the economic growth of the country.

Background: Hypoxia-inducible factors (HIFs) are transcription factors that get activated and stabilized in the heterodimerized form under hypoxic conditions. The three members of the HIF alpha factors share high structural similarity but have tissue-specific expression patterns. A majority of studies have reported the importance of the HIF1A and HIF2A activity in the survival, proliferation, metastatic potential, and metabolic regulation of hypoxic cancer cells. However, the importance of the expression pattern and activity of HIF3A in a variety of cancers remains unknown. Method and materials: The expression profile of 13 different types of The Cancer Genome Atlas (TCGA) cancer samples were downloaded, normalized and differential gene expression analysis (DGE) was performed to compare the expression pattern of HIF alpha family members in cancer and adjacent normal tissues, as well as at different stages and tumor-sizes. Receiver operating characteristic (ROC) test and survival analysis were carried out to estimate the diagnostic potential of HIF alpha isomers in different cancers, as well as the survival rate of patients with the varying expression levels of HIF alpha factors. Results: The expression status of HIF3A was notably less in all cancer samples in contrast to their adjacent normal tissues. The expression degree of HIF1A varied among distinct types of cancer and the expression degree of HIF2A was lower in nearly all types of cancers. The expression level of HIF alpha isomers did not significantly correlate with different sizes of tumor samples and stages of different tumor tissue samples. HIF3A had very weak diagnostic potential, while HIF2A had better diagnostic potential in most types of cancers compared to HIF1A. Patients who had a higher level of HIF3A had better survival, while the higher expression levels of HIF1A and HIF2A were associated with worse survival in many types of cancers. Conclusion: Our study shows the heterogenous expression pattern of HIF alpha subunits in distinctive kinds of cancers and the influence of HIF3A expression level in the survival of patients with varying types of cancers.

HIV-1 is a complicated and perplexing virus. It infects T cells, reverse transcribes its RNA into DNA, utilizes its host DNA machinery to replicate its HIV-DNA, translates the HIV-DNA into proteins, assembles itself for a budding escape from the T cell, and rapidly mutates its conformation. Partially, due to its complexity, there remains no cure for HIV or AIDs. However, recently with the discovery of TALENs, the use of zinc fingers, and most of all the applications of CRISPR-Cas9 technology, has given researchers new hope in finding alternative gene therapies and treatments for diseases. With more focus on CRISPR-Cas9, this new and novel technology uses a guiding RNA, sgRNA, to lead a Cas9 nuclease to its target for deletion or to change that DNA site. CRISPR-Cas9 can delete point mutations and multiple DNA sites. Because CRISPR can alter DNA sequences, several scientists have conducted research into CRISPR, possibly treating more diseases such as cancer, diabetes, and even HIV. HIV-1 drew the focus of a researcher named Dr. Ebina in 2013 when he was the first to design and apply CRISPR-Cas9 to genes found in the binding sites of HIV-1, inhibiting HIV-1 gene expression. Since 2013, several other researchers have blocked HIV replication and infection through CRISPR-Cas9 targeting the receptors of T cells called the CC chemokine receptor 5 or CCR5. HIV-1 binds to the CD4 receptor of T cells, which consists of co-receptors CCR5 and CXCR4. If CCR5 expression can be removed, the HIV virus cannot bind to T-cells, blocking the initial attachment stage, and discontinuing the infection. However, there remain obstacles and issues for the CRISPR deletion of CCR5 for treating HIV-1. The issues include: 1) finding new and safe methods of CRISPR-Cas9 delivery, 2) clearing the latent HIV reservoirs, 3) improving the sgRNA design to avoid off-target mutations or deletions, and 4) effectively analyze the viral escape of HIV from CRISPR-Cas9 modifications. Therefore, the purpose of this review is to discuss possible techniques for removing the obstacles that can lessen the potential of CRISPR to delete CCR5, repressing HIV-1 into long-term remission or a functional cure.

Emotion recognition defined as identifying human emotion and is directly related to different fields such as human-computer interfaces, human emotional processing, irrational analysis, medical diagnostics, data-driven animation, human-robot communi- cation and many more. The purpose of this study is to propose a new facial emotional recognition model using convolutional neural network. Our proposed model, “ConvNet”, detects seven specific emotions from image data including anger, disgust, fear, happiness, neutrality, sadness, and surprise. This research focuses on the model’s training accuracy in a short number of epoch which the authors can develop a real-time schema that can easily fit the model and sense emotions. Furthermore, this work focuses on the mental or emotional stuff of a man or woman using the behavioral aspects. To complete the training of the CNN network model, we use the FER2013 databases, and we test the system’s success by identifying facial expressions in the real-time. ConvNet consists of four layers of convolution together with two fully connected layers. The experimental results show that the ConvNet is able to achieve 96% training accuracy which is much better than current existing models. ConvNet also achieved validation accuracy of 65% to 70% (considering different datasets used for experiments), resulting in a higher classification accuracy compared to other existing models. We also made all the materials publicly accessible for the research community at: https://github.com/Tanoy004/Emotion-recognition-through-CNN.

Pseudopterosin, produced by the sea whip of the genus Antillogorgia, possesses a variety of promising biological activities including potent anti-inflammatory effects. However, few studies examined pseudopterosin in the treatment of cancer cells and, to our knowledge, the ability to inhibit triple negative breast cancer (TNBC) proliferation or invasion has not been explored. Thus, we evaluated the as yet unknown mechanism of action of pseudopterosin: Pseudopterosin was able to inhibit proliferation of TNBC. Interestingly, analyzing breast cancer cell proliferation after knocking down glucocorticoid receptor α (GRα) revealed that anti-proliferative effects of pseudopterosin were significantly inhibited when GRα expression was reduced. Furthermore, pseudopterosin inhibited invasion of MDA-MB-231 3D tumor spheroids embedded in an extracellular-like matrix. Remarkably, the knockdown of GRα in 3D tumor spheroids revealed increased ability of cells to invade the surrounding matrix. In a co-culture, encompassing peripheral blood mononuclear cells (PBMC) and MDA-MB-231 cells, production of interleukin 6 (IL-6) and interleukin 8 (IL-8) significantly increased compared to monoculture. Notably, pseudopterosin proved to block cytokine elevation, representing key players in tumor progression, in the co-culture. Thus, our results reveal pseudopterosin treatment as a potential novel approach in TNBC therapy.

Transporter associated with antigen processing 1 (TAP1) gene codes for a transporter protein, which is responsible for tumor antigen presentation in the MHC I or HLA complex. A defect in the gene results in an inadequate tumor tracking. TAP1 may also influence multi drug resistance, which is an extreme threat in providing treatment by drugs which are chemotherapeutic. The gene of TAP1 was analyzed bioinformatically. It gave us prognostic data as a confirmation of whether it should be used as a biomarker. The expression level and pattern analysis were conducted using ONCOMINE, GENT2 and GEPIA2 online platforms. Samples with different clinical outcomes were investigated for expression and promoter methylation analysis was done in cancer vs normal tissues using UALCAN. The copy number alteration and mutation frequency and expression in different cancer studies were analyzed using cBioPortal. The PrognoScan and KM plotter survival analysis of significant data (p-value<0.05) was representing graphically. Pathway and Gene ontology analysis of gene correlated to TAP1 gene was presented using bar charts. After arranging the data in a single panel and correlating expression to prognosis, understanding mutational and alterations and comparing pathways, TAP1 may be a potential novel target to evade a threat against chemotherapy and the study gives new aspects to consider for immunotherapy in human breast, lung, liver and ovarian cancer.

It was recently demonstrated that a co-planar capacitive sensor could be applied to the evaluation of materials without the disadvantages associated with the other techniques. This technique effectively detects changes in the dielectric properties of the materials due to, for instance, imperfections or variations in the internal structure, by moving a set of simple electrodes on the surface of the specimen. An AC voltage is applied to one or more electrodes and signals are detected by others. This is a promising inspection method for imaging the interior structure of the numerous materials, without the necessity to be in contact with the surface of the sample. In this paper, Finite Element (FE) modelling was employed to simulate the electric field distribution from a co-planar capacitive sensor and the way it interacts with a non-conducting sample. Physical experiments with a prototype capacitive sensor were also performed on a Plexiglas sample with sub-surface defects, to assess the imaging performance of the sensor. A good qualitative agreement was observed between the numerical simulation and experimental result.

The social distancing as a response to COVID 19 pandemic has led to the exceptional reductions of daily routine people activities and vehicle uses mainly in city. This same situation was also experienced by several busy, large, and populous cities in Southeast Asia (SA) countries. Correspondingly, this study aimed to test the hypothesis that the social distancing implementation period has increased the air quality in the term of carbon monoxide (CO) emission reduction as drawn from Jakarta city as an example of the one of populated cities in SA region. The CO was measured in parts per billions (ppb) and monitored on the daily basis employing remote sensor platform. The monitor periods were started from January, February, March, and April 2020 with 10 measurement days for each month. The social distancing was implemented from mid of March to the recent April. The CO measurement data were statistically tested to justify the significant effects of social distancing on the CO levels. Based on the CO data analysis, the order of CO mean by months is February > January > March > April. The CO levels for January, February, March, and April were 87.46 ppb (95%CI: 83.54-91.37), 88.20 ppb (95%CI: 81.65-94.74), 86.38 (95%CI: 81.06-91.69), and 78.68 (95%CI: 74.03-83.32) respectively. This study also find significant difference (p<0.05) of CO levels especially in April when social distancing has been implemented. Hence, these findings illustrate the potential air pollutant reduction gained from implementing social distancing as can be seen in April.

The vast majority of patients with pancreatic ductal adenocarcinoma (PDAC) suffer cachexia. Although cachexia results from concurrent loss of adipose and muscle tissue, most studies focus on muscle alone. Emerging data demonstrate the prognostic value of fat loss in cachexia. Here we sought to identify the muscle and adipose gene profiles and pathways regulated in cachexia. Matched rectus abdominis muscle and subcutaneous adipose tissue were obtained at surgery from patients with benign conditions (n=11) and patients with PDAC (n=24). Self-reported weight loss and body composition measurements defined cachexia status. Gene profiling was done using Ion proton sequencing. Results were queried against external datasets for validation. 961 DE genes were identified from muscle and 2000 from adipose tissue, demonstrating greater response of adipose than muscle. In addition to known cachexia genes such as FOXO1, novel genes from muscle, including PPP1R8 and AEN correlated with cancer weight loss. All the adipose correlated genes including SCGN and EDR17 are novel for PDAC cachexia. Pathway analysis demonstrated shared pathways but largely non-overlapping genes in both tissues. Age related muscle loss predominantly had a distinct gene profiles compared to cachexia. This analysis of matched, externally validate gene expression points to novel targets in cachexia.

Angelica decursiva is one of the lending traditional Chinese medicinal plants producing coumarins. Notably, several studies have focused on the biosynthesis and not the qRT-PCR (quantitative real-time reverse transcription polymerase chain reaction) study of coumarins. This qRT-PCR technique has been extensively used to investigate gene expression levels in plants and the selection of reference genes which plays a crucial role in standardizing the data form the qRT-PCR analysis. In our study, 11 candidate reference genes were selected from the existing transcriptome data of Angelica decursiva. Here, four different types of statistical algorithms (geNorm, NormFinder, BestKeeper, and Delta Ct) were used to calculate and evaluate the stability of gene expression under different external treatments. Subsequently, RefFinder analysis was used to determine the geometric average of each candidate gene ranking, and to perform comprehensive index ranking. The obtained results showed that among all the 11 candidate reference genes, SAND family protein (SAND), protein phosphatase 2A gene (PP2A), and polypyrimidine tract-binding protein (PTBP) were the most stable reference genes, where Nuclear cap binding protein 2 (NCBP2), TIP41-like protein (TIP41), and Beta-6-tubulin (TUBA) were the least stable genes. To the best of our knowledge, this work is the first to evaluate the stability of reference genes in the Angelica decursiva which has provided an important foundation on the use of qRT-PCR for an accurate and far-reaching gene expression analysis in this medicinal plant.

The study explores antibacterial, antiinflammatory and cytoprotective capacity of Pelargonium sidoides DC root extract (PSRE) and proanthocyanidin fraction from PSRE (PACN) under conditions characteristic for periodontal disease. Following previous finding that PACN exerts stronger suppression of Porphyromonas gingivalis compared to the effect on commensal Streptococcus salivarius, the current work continues antibacterial investigation on Staphylococcus aureus, Staphylococcus epidermidis, Aggregatibacter actinomycetemcomitans and Escherichia coli. PSRE and PACN are also studied for their ability to prevent gingival fibroblast cell death in the presence of bacteria or bacterial lipopolysaccharide (LPS), to block LPS- or LPS+IFNγ-induced release of inflammatory mediators, gene expression and surface antigen presentation. Both PSRE and PACN were more efficient in suppressing Staphylococcus and Aggregatibacter compared to Escherichia, prevented A. actinomycetemcomitans- and LPS induced death of fibroblasts, decreased LPS-induced release of interleukin 8 and prostaglandin E2 from fibroblasts and IL-6 from leukocytes, blocked expression of IL-1β, iNOS, and surface presentation of CD80 and CD86 in LPS+IFNγ-treated macrophages, and IL-1β and COX-2 expression in LPS-treated leukocytes. None of the investigated substances affected either the level of secretion or expression of TNFα. In conclusion, PSRE, and especially PACN, possess strong antibacterial, antiinflammatory and gingival tissue protecting properties under periodontitis mimicking conditions and are suggestable candidates for treatment of the disease.

This study aimed to assess the ecotoxicological effects of the interaction of fullerene (C₆₀) and benzo[a]pyrene (B[a]P) on the marine mussel, Mytilus galloprovincialis. The uptake of nC₆₀, B[a]P and mixtures of nC₆₀ and B[a]P into tissues was confirmed by GC-MS, LC-HRMS and ICP-MS. Biomarkers of DNA damage as well as proteomics analysis were applied to unravel the toxic effect of B[a]P and C₆₀. Antagonistic responses were observed at the genotoxic and proteomic level. Differentially expressed proteins (DEPs) were only identified in the B[a]P single exposure and the B[a]P mixture exposure groups containing 1 mg/L of C₆₀, the majority of which were down-regulated (~52%). No DEPs were identified at any of the concentrations of nC₆₀ (p < 0.05, 1% FDR). Using DEPs identified at a threshold of (p < 0.05; B[a]P and B[a]P mixture with nC₆₀), gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis indicated that these proteins were enriched with a broad spectrum of biological processes and pathways, including those broadly associated with protein processing, cellular processes and environmental information processing. Among those significantly enriched pathways, the ribosome was consistently the top enriched term irrespective of treatment or concentration and plays an important role as the site of biological protein synthesis and translation. Our results demonstrate the complex multi-modal response to environmental stressors in M. galloprovincialis.

PHLNs (polymeric lipid hybrid nanoparticles) are core–shell nanoparticle structures made up of polymer cores and lipid shells that have properties similar to both polymeric nanoparticles and liposomes. Methotrexate (MTX) loaded PLHNPs containing tween 80, phosphatidylcholine, poly D, L-lactic-co-glycolic acid (PLGA) & glyceryl tripalmitate prepared using solvent injection & homogenization method for glioblastoma treatment option. The MTX loaded PLHNPs optimized by Box–Behnken design to minimize particle size, higher entrapment efficacy, and maximize MTX concentration in the brain at 4h. The particle size, entrapment efficacy, concentration of drug in brain at 4h, zeta potential and AUC(Brain)/AUC(Plasma) ratio were in the range of 173.51-233.37nm, 70.56-86.34%, 6.38-12.38 μg/mL, 25.78-36.31mV & 1.02-5.32. in-vitro drug release studies, cellular internalization of optimized formulation against U-87 MG shows good anticancer effects.

Although wheat is a staple food for most of human population, some of its components trigger adverse reactions. Among wheat components, the alpha-amylase/trypsin inhibitors (ATI) are important triggers of several allergies and activators of innate immunity. ATI are a group of exogenous protease inhibitors and include several polypeptides. The three ATI polypeptides named CM3, CM16 and 0.28 are considered major allergens, and might also play a role in other common wheat-related pathologies, such as Non Celiac Wheat Sensitivity and even Celiac Disease. On this basis, we pointed to obtain high amounts of them in purity and evaluating their allergenicity potential. We thus isolated the mRNA corresponding to the three ATI genes CM3, CM16 and 0.28 from 28 days post-anthesis wheat kernels and the corresponding cDNAs were used for heterologous expression in Pichia pastoris. The three purified proteins were tested in degranulation assay against human sera of patients with food allergy to wheat. A large range of degranulation values was observed for each protein according to the sera tested. All the three purified proteins CM3, CM16 and 0.28 were active as allergens because able to induce basophils degranulation on wheat allergic patients’ sera, but the highest values of β-hexosaminidase release were observed for CM3 protein.

Magneto-optic surface plasmon resonance (MOSPR) based sensors are highly attractive as next generation biosensors. However, these sensors suffer from oxidation leading to degradation of performance, reproducibility of the sensor surface because of the difficulty of removing adsorbed materials, and degradation of sensor surface during surface cleaning, and these limit their applications. In this paper, I propose MOSPR-based biosensors with 0 to 15 nm thick inert polycarbonate laminate plastic as a protective layer and theoretically demonstrate the practicability of our approach in water-medium for three different probing samples: ethanol, propanol, and pentanol. I also investigate microstructure and magnetic properties. The chemical composition and layered information of the sensor are investigated using X-ray reflectivity and X-ray diffraction analyses and these show distinct fcc-Au (111) phases, as dominated by the higher density of conduction electrons in Au as compared to Co. The magnetic characterization measured with the in-plane magnetic field to the sensor surface for both the as-deposited and annealed multilayers showed isotropic easy axis magnetization parallel to the multilayer interface at a saturating magnetic field of <100 Oe. The sensor showed a maximum sensitivity of 5.5 × 10⁴%/RIU for water-ethanol media and the highest detection level of 2.5 × 10⁻⁸ for water-pentanol media as the protective layer is increased from 0 to 15 nm.c

Enhancing the effectiveness of search and rescue operation at sea is always a duty of utmost importance of the coastal states. The search area for distressed objects can be determined by using Monte Carlo simulation, combined with the Median-Filter. Once the search area has been identified, the success of search and rescue operations depends on the sweeping ability of search and rescue vessel at the probability area of the distress object with the minimum time. This is the important element to the success of the search and rescue operation as it minimizes the risk and cost for Search and rescue team. In this article, the authors study and propose the use of Bacterial Foraging Optimization Algorithm (BFOA) to calculate the optimal search and co-ordination route for many search and rescue vessels in Vietnam sea. The simulation results show that it is quite consistent with reality and BFOA can be effectively applied to determine a quick search.

Molecular mechanisms associated with the pathogenesis of Vesicular stomatitis virus (VSV) in livestock remain poorly understood. Several studies have highlighted the relevant role of macrophages in controlling the systemic dissemination of VSV during infection in different animal models, including mice, cattle and pigs. To gain more insight on the molecular mechanisms used by VSV to impair the immune response in macrophages, we used microarrays to determine the transcriptomic changes produced by VSV infection in primary cultures of porcine macrophages. The results indicated that VSV infection induced the massive expression of multiple anorexic, pyrogenic, proinflammatory and immunosuppressive genes. Overall, the interferon (IFN) response appeared suppressed, leading to the absence of stimulation of interferon-stimulated genes (ISG). Interestingly, VSV infection promoted the expression of several genes known to downregulate the expression of IFNb. This represents an alternate mechanism for VSV control of the IFN response, beyond the recognized mechanisms mediated by the matrix protein. Although there was no significant differential gene expression in macrophages infected with a highly virulent epidemic strain compared to a less virulent endemic strain, the endemic strain consistently induced higher expression of all upregulated cytokines and chemokines. Collectively, this study provides novel insights into VSV molecular pathogenesis and immune evasion that warrants further investigation

Triple negative breast cancer (TNBC) is the most aggressive breast cancer accounting for around 15% of identified breast cancer cases. TNBC, by lacking estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), is unresponsive to current targeted therapies. Existing treatment relies on chemotherapeutic treatment but, despite an initial response to chemotherapy, the inception of resistance and relapse is unfortunately common. Dasatinib is an approved second-generation inhibitor of multiple tyrosine kinases and literature data strongly support its use in the management of TNBC. However, dasatinib binds to plasma proteins and undergoes extensive metabolism through oxidation and conjugation. To protect dasatinib from fast pharmacokinetic degradation and to prolong its activity, it was encapsulated on poly(styrene-co-maleic acid) (SMA) micelles. The obtained SMA-dasatinib nanoparticles (NPs) were evaluated for their physicochemical properties, in vitro antiproliferative activity in different TNBC cell lines, and in vivo anticancer activity in a syngeneic model of breast cancer. Obtained results showed that SMA-dasatinib is more potent against 4T1 TNBC tumor growth in vivo compared to free drug. This enhanced effect was ascribed to the encapsulation of the drug protecting it from a rapid metabolism. Our finding highlights the often-overlooked value of nanoformulations in protecting its cargo from degradation. Overall, results may provide an alternative therapeutic strategy for TNBC management.

Biofilm-mediated infection is a major cause of bone prosthesis failure. The lack of molecules able to act in biofilms has driven research aimed at identifying new anti-biofilm agents via chemical screens. However, to be able to accommodate a large number of compounds, the testing conditions of these screenings end up being typically far from the clinical scenario. In this study, we assess the potential applicability of three anti-biofilm compounds (based on natural compounds) as part of implanted medical devices by testing them on in vitro systems that more faithfully resemble the clinical scenario. To that end, we used a competition model based on the co-culture of SaOS-2 mammalian cells and Staphylococcus aureus (collection and clinical strains) on a titanium surface. Additionally, we studied whether these derivatives of natural compounds enhance the previously proven protective effect of pre-incubating the titanium surface with SaOS-2 cells. Out of the three tested leads, one showed the highest potential, and can be regarded as a promising agent for incorporation into bone implants. This study emphasizes and demonstrates the importance of using meaningful experimental models, where potential antimicrobials ought to be tested for protection of biomaterials in translational applications.

In the implementation of thermal enhanced oil recovery (TEOR) techniques, the temperature impact on relative permeability in oil - water systems is of special concern. Hence, developing a fast and reliable tool to model the temperature effect on two-phase oil - water relative permeability is still a major challenge for precise studying and evaluation of TEOR processes. To reach the goal of this work, two promising soft-computing algorithms, namely Group Method of Data Handling (GMDH) and Gene Expression Programming (GEP) were employed to develop reliable, accurate, simple and quick to use paradigms to predict the temperature dependency of relative permeability in oil - water systems (K_rw and K_ro). To do so, a large database encompassing wide-ranging temperatures and fluids/rock parameters, including oil and water viscosities, absolute permeability and water saturation, was considered to establish these correlations. Statistical results and graphical analyses disclosed the high degree of accuracy for the proposed correlations in emulating the experimental results. In addition, GEP based correlations were found to be the most consistent with root mean square error (RMSE) values of 0.0284 and 0.0636 for K_rw and K_ro, respectively. Lastly, the comparison of the performances of our correlations against those of the preexisting ones indicated the large superiority of the introduced correlations compared to previously published methods. The findings of this study can help for better understanding and studying the temperature dependency of oil - water relative permeability in thermal enhanced oil recovery processes.

The Neurodegenerative Diseases are, according to recent studies, one of the main causes of disability and death worldwide. Interest in molecular genetics has started to have an exponential growth thanks to numerous advancements in tech, shifts in the understanding of the disease as a phenomenon, and the change of perspective regarding gene editing and the upsides of this action. The aim of this paper is to analyse the newest approaches in genetics and molecular sciences regarding four of the most important neurodegenerative disorders: Alzheimer’s Disease, Parkinson’s Disease, Huntington’s Disease and Amyotrophic Lateral Sclerosis. We intend through this review to focus on the newest treatment, diagnosis and predictions plans regarding this large group of diseases, in order to obtain a better accuracy analysing and spotting the emerging signs that could lead to a better outcome in order to increase both the quality and the life span of the patient. Moreover, this review could provide future evidence of possible novelty therapies that target the specific genes and could be useful to be taken into consideration when the classical approaches fail to shed light.

Epithelial characteristics underlying the differential susceptibility of chronic asthma to SARS-CoV-2 (COVID-19) and other viral infections are currently unclear. By revisiting transcriptomic data from patients with Th2 low versus Th2 high asthma, as well as mild, moderate and severe asthmatics, we characterized the changes in expression of human coronavirus and influenza viral entry genes relative to sex, airway location and disease endotype. We found sexual dimorphism in expression of COVID-19 genes ACE2, TMPRSS2, TMPRSS4, and SLC6A19. ACE2 receptor downregulation occurred specifically in females in Th2 high asthma, while proteases broadly assisting coronavirus and influenza viral entry, TMPRSS2 and TMPRSS4, were highly upregulated in both sexes. Overall, changes in COVID-19 gene expression were specific to Th2 high molecular endotype of asthma, and different by asthma severity and airway location. The downregulation of ACE2 (COVID-19, SARS) and ANPEP (HCoV-229E) viral receptors correlated with loss of club and ciliated cells in Th2 high asthma, while the increase in DPP4 (MERS-CoV), ST3GAL4, and ST6GAL1 (influenza) associated with an increase in goblet and basal activated cells. Overall, this study elucidates sex, airway location, disease endotype and changes in epithelial heterogeneity as factors underlying asthmatic susceptibility, or lack thereof, to COVID-19.

We assessed the growth performance, physiological traits, and gene expressions in steers fed with dietary rumen-protected L-tryptophan (RPT) under cold environment. Eight Korean native steers were assigned to two dietary groups, no RPT (Control) and RPT (0.1% RPT supplementation on a dry matter basis), 6 wks. Maximum and minimum temperatures throughout the experiment were 6.7°C and -7.0°C, respectively. Supplementation of 0.1% RPT to a total mixed ration did not increase body weight but had positive effects of elevating average daily gain (ADG) and reducing the feed conversion ratio (FCR) at day 27 and 48. Metabolic parameter showed higher glucose level (at day 27) in the 0.1% RPT group compared to the control group. Real-time PCR analysis showed no significant differences in the expression of muscle (MYF6, MyoD, and Desmin) metabolism genes between the two groups, whereas the expression of fat (PPARγ, C/EBPα, and FABP4) metabolism genes was lower in the 0.1% RPT group than in the control group. Thus, we demonstrate that long-term (6 wks) dietary supplementation of 0.1% RPT was beneficial owing to enhanced growth performance by increasing ADG and glucose level, decreasing FCR, and maintaining homeostasis in immune responses in beef steers during cold environment.

This pot-based study investigated the influence of co-composted wood-derived biochar on lettuce growth performance under salinity and drought stress conditions. Biochar of two particle sizes; > 2 mm and < 1 mm were co-composted with the mixture (1:1 ratio of dry weight) of cow and poultry manures. Co-composted biochars were applied at 5% and 7% rates in soil. Control treatments included the amendment of mixture of biochar with manure in soil. Pots were subjected to slight drought (48-55% water filled pore space (WFPS) of soil) and non-drought conditions (60% WFPS) and under 0 and 1.3 dS m-1 salinity. Results revealed that plants growth performance was significantly better under treatments of co-composted biochar and no salt stress conditions, than when mixture of biochar and manure was applied to soil as non-composted fertilizer. Under no stress condition, small particle-sized co-composted biochar increased root biomass by 786.2% than the large particle-sized co-composted biochar at same application rate. As compared to large-sized co-composted biochar, small sized co-composted biochar at high application rates increased root biomass by 167 – 245% but not leaf biomass under both stress conditions. Small particle-sized co-composted biochar amendment also increased the phosphorus use efficiency (PUE) of lettuce leaves than large particle-sized co-composted biochar under no stress condition. The amendment of small-sized co-composted biochar also increased significantly the concentration of Olsen phosphorus in soil than the amendment of large-particle-sized co-composted biochar. In conclusion, amendment of small particle-sized co-composted biochar has the potential of attenuating salinity and drought stress in lettuce and promoting P cycling in soil.

Studies on the influence of dietary components and their effects are fundamental for nutrigenomics, or the study of how nutrients can be cellular sensors, how they affect biological processes and gene expression in different tissues. Lipids are an important source of fatty acids (FA) and energy and are fundamental to biological processes and influence the regulation of transcription. Pigs are excellent model to study nutrigenomics, particularly lipid metabolism because the deposition and composition of FA in their tissues reflect the composition of FA in their diet. Recent studies show that FA supplementation is important in production systems, such as growing and finishing pigs, as it can improve the energy value of the feed, help reduce costs, improve animal welfare, and influence the nutritional value of the meat. Studies show that oleic (OA), linoleic (LA), docosahexaenoic (DHA), and eicosapentaenoic (EPA) acids are associated with the regulation of transcription in tissues such as muscle, liver, adipose tissue, and brain. Other studies indicate that EPA and DHA are associated with changes in specific signaling pathways, altering gene expression and biophysical properties of membranes. This review, therefore, focuses on the current knowledge of the effects of dietary FA on production traits and gene expression.

Obesity is a problem in the last decades since the development of different technologies forced the submission of a faster pace of life, resulting in nutrition style changes. In turn, domestic pigs are an excellent animal model in recognition of adiposity-related processes, corresponding to the size of individual organs, the distribution of body fat in the organism, and similar metabolism. The present study applied the next-generation sequencing method to identify adipose tissue (AT) transcriptomic signals related to increased fat content by identifying differentially expressed genes (DEGs), included long-non coding RNA molecules. The Freiburg RNA tool was applied to recognise predicting hybridisation energy of RNA-RNA interactions. The results indicated several long non-coding RNAs (lncRNAs) whose expression was significantly positively or negatively associated with fat deposition. lncRNAs play an essential role in regulating gene expression by sponging miRNA, binding transcripts, facilitating translation, or coding other smaller RNA regulatory elements. In the pig fat tissue of obese group, increased expression of lncRNAs corresponding to human MALAT1 was observed that previously recognised in the obesity-related context. Moreover, hybridisation energy analyses pinpointed numerous potential interactions between identified differentially expressed lncRNAs, and obesity-related genes and miRNAs expressed in AT.

In the present paper, Co-B/SiC composite coatings were obtained via electrodeposition from colloidal suspensions with different concentrations of SiC particles and subsequent heat treatments at 350 °C. The composition, morphology and structure of the Co-B/SiC composite coatings were analyzed using glow discharge spectrometry (GDS), scanning electron microscopy (SEM) coupled with energy-dispersive spectroscopy (EDS) and X-ray diffraction (XRD). Hardness and tribological properties were also studied. The results showed that an increase in the SiC concentration in the colloidal suspensions resulted in both an increase in the SiC content and a decrease in the B content in the obtained Co-B/SiC coatings. The Co-B/SiC coatings were adherent, glossy and soft and exhibited a homogeneous composition in all thicknesses. By contrast, an increase in the SiC particle content of the Co-B/SiC composite coating from 0 to 2.56 at.% SiC reduced the hardness of the film from 680 to 360 HV and decreased the wear volume values from 1180 to 23 mm³ N^-1 m^-1, respectively (that is, the wear resistance increased). Moreover, when the Co-B/SiC coatings with SiC content ranging from 0 to 2.56 at.% SiC were subjected to a heat treatment process, the obtained coating hardness values were in the range of 1200 to 1500 HV and the wear volume values were in the range of 382 to 19 mm³ N^-1 m^-1.

Assessment of drugs toxicity and associated biomarker genes is one of the most important tasks in the pre-clinical phase of drug development pipeline as well as in the toxicogenomic studies. There are few statistical methods for the assessment of doses of drugs (DDs) toxicity and their associated biomarker genes. However, these methods consume more time for computation of the model parameters using the EM (Expectation-Maximization) based iterative approaches. To overcome this problem, in this paper, an attempt is made to propose an alternative approach based on hierarchical clustering (HC) for the same purpose. There are several types of HC approaches whose performance depends on different similarity/distance measures. Therefore, we explored suitable combinations of distance measures and HC methods based on Japanese Toxicogenomics Project (TGP) datasets for better clustering/co-clustering between DDs and genes as well as to detect toxic DDs and their associated biomarker genes. We observed that Word’s HC method with each of Euclidean, Manhattan and Minkowski distance measures produces better clustering/co-clustering results. For an example, in case of glutathione metabolism pathway (GMP) dataset LOC100359539/Rrm2, Gpx6, RGD1562107, Gstm4, Gstm3, G6pd, Gsta5, Gclc, Mgst2, Gsr, Gpx2, Gclm, Gstp1, LOC100912604/Srm, Gstm4, Odc1, Gsr, Gss are the biomarker genes and Acetaminophen_Middle, Acetaminophen_High, Methapyrilene_High, Nitrofurazone_High, Nitrofurazone_Middle, Isoniazid_Middle, Isoniazid_High are their regulatory (associated) DDs explored by our proposed co-clustering algorithm based on the distance and HC method combination Euclidean: Word. Similarly, for the PPAR signaling pathway (PPAR-SP) dataset Cpt1a, Cyp8b1, Cyp4a3, Ehhadh, Plin5, Plin2, Fabp3, Me1, Fabp5, LOC100910385, Cpt2, Acaa1a, Cyp4a1, LOC100365047, Cpt1a, LOC100365047, Angptl4, Aqp7, Cpt1c, Cpt1b, Me1 are the biomarker genes and Aspirin_Low, Aspirin_Middle, Aspirin_High, Benzbromarone_Middle, Benzbromarone_High, Clofibrate_Middle, Clofibrate_High, WY14643_Low, WY14643_High, WY14643_Middle, Gemfibrozil_Middle, Gemfibrozil_High are their regulatory DDs. These results are validated by the available literature and functional annotation.

A sustainable solution for crack maintenance in geopolymers is necessary if they are to be the future of modern green construction. This study thus aimed to develop self-healing biogeopolymers that could potentially rival bioconcrete. First, a suitable healing agent was selected from Bacillus subtilis, B. sphaericus, and B. megaterium by directly adding their spores in the geopolymers and subsequently exposing them to a large amount of nutrients for 14 days. SEM-EDX analysis revealed the formation of biominerals for B. subtilis and B. sphaericus. Next, the effect of biochar-immobilization and co-culturing (B. sphaericus and B. thuringiensis) on the healing efficiencies of the geopolymers were tested and optimized by measuring their ultrasonic pulse velocities weekly over a 28-day healing period. The results show that using co-cultured bacteria significantly improved the observed efficiencies, while biochar-immobilization had a weak effect but yielded an optimum response between 0.3-0.4 g/mL. The maximum crack width sealed was 0.65 mm. Through SEM-EDX and FTIR analyses, the biominerals precipitated in the cracks were identified to be mainly CaCO3. Furthermore, image analysis of the XCT scans of some of the healed geopolymers confirmed that their pulse velocities were indeed improving due to the filling of their internal spaces with biominerals. With that, there is potential in developing self-healing biogeopolymers using biochar-immobilized spores of bacterial cultures.

Single-level Principal Components Analysis (PCA) and multi-level PCA (mPCA) methods are applied here to a set of (2D frontal) facial images from a group of 80 Finnish subjects (34 male; 46 female) with two different facial expressions (smiling and neutral) per subject. Inspection of eigenvalues gives insight into the importance of different factors affecting shapes, including: biological sex, facial expression (neutral versus smiling), and all other variations. Biological sex and facial expression are shown to be reflected in those components at appropriate levels of the mPCA model. Dynamic 3D shape data for all phases of a smile made up a second dataset sampled from 60 adult British subjects (31 male; 29 female). Modes of variation reflected the act of smiling at the correct level of the mPCA model. Seven phases of the dynamic smiles are identified: rest pre-smile, onset 1 (acceleration), onset 2 (deceleration), apex, offset 1 (acceleration), offset 2 (deceleration), and rest post-smile. A clear cycle is observed in standardized scores at an appropriate level for mPCA and in single-level PCA. mPCA can be used to study static shapes and images, as well as dynamic changes in shape. It gave us much insight into the question “what’s in a smile?”

Antibiotic inefficacy in treating bacterial infections is largely studied in the context of developing resistance mechanisms. However, little attention has been paid to combined diseases mechanisms, interspecies pathogenesis and the resulting impact on antimicrobial treatment. This review will consider the co-infections of Salmonella and Schistosoma mansoni. It summarises the protective mechanisms that the pathophysiology of the two infections confer, which leads to an antibiotic protection phenomenon. This review will elucidate the functional characteristics of the gut microbiota in the context of these co-infections, the pathogenicity of these infections in infected mice, and the efficacy of the antibiotics used in treatment of these co-infections over time. Salmonella-Schistosoma interactions and the mechanism for antibiotic protection are not well established. However, antimicrobial drug inefficacy is an existing phenomenon in these co-infections. The treatment of schistosomiasis to ensure the efficacy of antibiotic therapy for bacterial infections should be considered in co-infected patients.

The purpose of this study is to explore conceptual approaches in co-production studies and to examine current research trends of the study. The conceptual paper includes research articles related to co-production in public administration field. By thoroughly scrutinizing 32 research works of co-production, this study highlights major loopholes in the field of the study. The contributions of the study are: (1) identifying two common characteristics of co-production, (2) categorising three types of co-producing by end-users, and (3) finding that goals and success of co-production are more beneficial for service providers though its initial approach is citizen-centric approach. We suggest that future studies should be (1) to focus on reasons for co-production failures or success, (2) to discover further hindrances for co-production in service production, (3) to examine influencing factors on service providers as well as institutional impacts on co-production process, and (4) to include practical assessment in co-production study.

Artificially designed, chimeric peptide-based recombinant vaccines are novel approaches to combat the phylogenetically diverse Foot and Mouth Disease (FMD) Virus (FMDV) strains. Among seven distinct serotypes, only serotype O and A are dominantly circulating in Bangladesh and neighbouring countries of Asia, where transboundary transmission, recurrent outbreaks and emergence of novel lineages FMDV are highly prevalent. The objective of this study was to develop multi-epitope recombinant peptides, procuring immunogenicity against circulating diverse subtypes of FMDV serotype O and A. Two chimeric peptides, named B1 (41.0 kDa) and B3 (39.3 kDa), have been designed to incorporate potential B-cell and T-cell epitopes selected from multiple FMDV strains, including previously reported and newly emerged sub-lineages. After expression, characterization and immunization of guineapigs with considerable antigen load of B1 and B3 followed by the serological assays revealed the significant protective immunogenicity, developed from the higher (100 µg) doses of both antigens, against most of the currently prevalent serotype O and A strains of FMDV. The efficient expression, antigenic stability, and multivalent immunogenic potency of the chimeric peptides strongly indicate their credibility as novel vaccine candidates for FMDV serotypes O and A circulating in Bangladesh and surrounding territories.

Background: The demand in the development of cancer nanomedicine has increased due to various limitations in conventional cancer therapy. This study assessed the mRNA transcriptomic profiling of human HepG2 cells exposed to C. roseus-AgNPs. Methods: The proliferative activity of hepatocellular carcinoma (HepG2) and normal human liver (THLE3) cells treated with C. roseus‑AgNPs were measured using MTT assay. The RNA samples were extracted and sequenced using BGIseq500 platform. This is followed by data filtering, mapping, gene expression analysis, DEG analysis, GO analysis, and pathway analysis. Results: The mean IC₅₀ values of C. roseus‑AgNPs on HepG2 was 4.38±1.59 µg/mL while on THLE3 cells was 800±1.55 µg/mL. Transciptomic profiling revealed an alteration of 296 genes. C. roseus‑AgNPs induced the expression of stress-associated genes such as MT, HSP and HMOX-1. Cellular signaling pathways were potentially activated through MAPK, TNF and TGF pathways that responsible for apoptosis and cell cycle arrest. The alteration of ARF6, EHD2, FGFR3, RhoA, EEA1, VPS28, VPS25, TSG101 indicated the uptake of C. roseus-AgNPs via both clathrin-dependent and clathrin-independent endocytosis. Conclusions: This study provides the new insights on gene expression study of biosynthesized AgNPs on cancer cells. The cytotoxicity effect is mediated by the aberrant gene alteration, and more interestingly the unique selective antiproliferative properties indicates the C. roseus‑AgNPs as an ideal anticancer candidate.

Remaining service life (RSL) of pavement, as a sign of future pavement performance, has always received growing attention from pavement engineers. The RSL describes the time from the moment of pavement inspection until such a time when a major repair or reconstruction is required. The conventional approach to determining RSL involves using non-destructive tests. These tests, in addition to being costly, interfere with traffic flow and compromise users' safety. In this paper, surface distresses of pavement have been used to estimate the pavement’s RSL in order to eliminate the aforementioned problems and challenges. To implement the proposed theory, 105 flexible pavement segments were taken from Shahrood-Damghan Highway (Highway 44) in Iran. For each pavement segment, the type, severity, and extent of surface damage and pavement condition index (PCI) were determined. The pavement RSL was then estimated using non-destructive tests include Falling Weight Deflectometer (FWD) and Ground Penetrating Radar (GPR). After completing the dataset, the modeling was conducted to predict RSL using three techniques include Support Vector Regression (SVR), Support Vector Regression Optimized by Fruit Fly Optimization Algorithm (SVR-FOA), and Gene Expression Programming (GEP). All three techniques estimated the RSL of the pavement by selecting the PCI as input. The Correlation Coefficient (CC), Nash-Sutcliffe efficiency (NSE), Scattered Index (SI), and Willmott’s Index of agreement (WI) criteria were used to examine the performance of the three techniques adopted in this study. In the end, it was found that GEP with values of 0.874, 0.598, 0.601, and 0.807 for CC, SI, NSE, and WI criteria, respectively, had the highest accuracy in predicting the RSL of pavement.

A simplified nonlinear dispersive system of BBM-type, initially derived by D. Mitsotakis, is employed here in order to model the generation and propagation of surface water waves over variable bottom. The simplification consists in applying the so-called Boussinesq approximation. Using the finite element method and the FreeFem++ software, we solve numerically this system for three different complexities for the bathymetry function: a flat bottom case, a variable bottom in space, and a variable bottom both in space and in time. The last case is illustrated with the Java 2006 tsunami event. This article is designed rather as a tutorial paper even if it contains the description of completely new adaptation techniques.

Identification of the differentially-expressed genes is important for clarification of the complex molecular mechanisms under drought conditions. In this experiment, transcriptome profiles of sensitive and tolerant tomato genotypes under drought stress were analyzed. Three up-regulated genes were selected, included CAB3 (Chlorophyll a-b binding protein3), SAMDC (S-adenosylmethionine decarboxylase proenzyme), and ACS9 (1-aminocyclopropane-1-carboxylate synthase 9). After bioinformatics analysis, tomato genotypes were subjected to drought stress and gene expression was determined using Real-Time-PCR. Physiological parameters of genotypes were also measured by spectrophotometer-based methods. According to the results, these three genes play a key role in stress tolerance. Expression of the CAB3 gene in both sensitive and tolerant genotypes was not significantly different compared to the control, but the SAMDC gene decreased in both genotypes and the ACS9 gene decreased in sensitive genotype and increased in tolerant genotype. The physiological analysis also showed that under stress conditions, the photosynthetic system of the plant was disrupted and the chlorophyll content was reduced, but, proline content and antioxidant enzymes activity increased, in which their quantity in the tolerant genotype was significantly higher than sensitive. Under drought stress, due to damage to the lipid membrane, Malondialdehyde content also increased, in which the sensitive genotype was more affected.

Spatial planning holds a key role in preventing or mitigating the impacts of climate change on both cities and rural areas, taking a forward-thinking and holistic approach to urban and regional development. As such, spatial planning deals with challenges occurring at different scales and across sectors. The international literature points out the need for horizontal and vertical cooperation to tackle climate change impacts. While there is abundant knowledge regarding the challenges related to climate change at different spatial levels, procedural integration into planning frameworks and practice is currently under-researched. This paper presents a novel theoretical framework that integrates various steps towards a holistic, integrative and adaptive climate proofing process. An iterative process was used for conceptual development, based on literature review followed by external feedback meetings and two workshops with the core team of planning experts responsible for exchange across federal states. By specifically addressing the challenges relating to cross-regional and cross-sectoral planning, this novel framework attempts to (i) facilitate a hierarchy of measures, (ii) maximise co-benefits for various adaptation purposes and climate change mitigation and (iii) foster the long-term institutionalisation of integrative processes across sectors, planning areas and policy levels.

Inorganic polyphosphate (polyP) is an important factor of stress tolerance in microbial cells. In yeast, the major enzyme of polyP biosynthesis is Vtc4, a subunit of the vacuole transporter chaperone (VTC) complex. In this study, we demonstrated that Vtc4 knockout in Saccharomyces cerevisiae not only decreased polyP content but also caused shifts in the composition of the intracellular polyP pool and changed the stress tolerance profile. In the mutant S. cerevisiae, the level of short-chain acid-soluble polyPs was decreased nearly 10-fold, whereas that of longer acid-insoluble polyPs was decreased only 2-fold, suggesting the existence of other enzymes compensating the production of long-chain polyPs. The Δvtc4 mutant showed inhibition of Mg2+-dependent phosphate uptake and decreased resistance to alkaline stress but increased tolerance to oxidation and heavy metal ions, especially Mn2+. Quantitative PCR revealed the upregulation of the DDR2 gene implicated in multiple stress responses and downregulation of PHO84 encoding a phosphate and Mn2+ transporter, which could account for the effects on phosphate uptake and Mn2+-related stress response in the Δvtc4 mutant. Our study indicates that short-chain polyPs, plays an important role in the regulation of stress response in yeast.

Carbon dioxide has become a global challenge, where the emissions have become more than what could be handled. In this regard, conversion of CO2 to value added chemicals and thus recycling CO2 became a viable option. One of these options is the use of a process in strong development: oxycombustion. However, the gases resulting from this process contain some traces of impurities that can hinder the recovery of CO2 such as NO and CO. This work has therefore focused on the study of the reaction of NO reduction by CO in an oxidizing medium, using catalytic materials based on various supported noble metals. These materials were extensively characterized by a variety of methods including BET surface area measurements, hydrogen chemisorption, Transmission Electron Microscopy (TEM) and H2 temperature programmed reduction (H2-TPR). The obtained results show that the catalytic behaviour of M/Al2O3 catalysts in CO oxidation and NO reduction with CO in oxidative conditions depends mainly on the nature of the metal. The best result for these both reactions is obtained with Pt/Al2O3 catalyst. The Pt nanoparticles existing in the metallic form (Pt°) showed by TPR could explain the activity.

Poliovirus 2A protease (PV2Apro) plays a vital role in viral replication and down-regulation of host cell protein synthesis. In order to understand more concerning PV2Apro, the protein was over-expressed in bacteria following amplification using sense and antisense primers and cloning in pET15b. Several expression hosts were tested and BL21 (DE3) pLysS cells gave the best expression of PV2Apro with minimal unwanted protein expression following IPTG induction. The 2Apro protein was purified to homogeneity using column chromatography, its solubility determined and its molecular weight and composition determined by MALDI-TOF mass spectrometry. The protease was found in the insoluble fraction and the purified protein had a slightly lower molecular weight than predicted. Moreover, three dimensional structure was modelled using template 1z8r with 58% identity and validated using ramachandran plot. Results revealed that most of the residues lie in favoured and allowed regions. These findings could help in a better understanding of PV2Apro structure and inhibition thus, highlighting potential targets for antiviral drug development.

Strigolactones (SLs) are a novel emerging plant hormones, which play important roles in regulating plant organ development and environmental stress tolerance. Even though the SL related genes have been identified and well characterized in some plants. The information of SL related genes in soybean is not fully established yet, especially in response to salt stress. In this study, we identified nine SL biosynthesis genes: two D27, two CCD7, two CCD8, and three MAX1, and seven SL signaling genes: two D14, two MAX2 and three D53 in soybean genome. We found that SL biosynthesis and signaling genes are conserved during evolution in different species. Syntenic analysis of these genes revealed their location on nine chromosomes as well as existence of ten pairs of duplication genes. Moreover, plant hormone and stress-responsive elements were identified in the promoter regions of SL biosynthesis and signaling genes. By using quantitative real-time PCR (qRT-PCR), we confirmed that SL genes have different tissue expression in roots, stems and leaves. Further, we also explored the expression profiles of SL biosynthesis and signaling genes under salt stress. These results suggested that SL signaling genes may play important regulatory roles in response to salt stress. In conclusion, we identified and provided valuable information on the soybean SL biosynthesis and signaling genes, and established a foundation for further functional analysis of soybean SL related genes in response to salt stress.

Classical models of gene expression were built using genetics and biochemistry. Although these approaches are powerful, they have very limited consideration of the spatial and temporal organization of gene expression. Although the spatial organization and dynamics of RNA polymerase II (RNAPII) transcription machinery has fundamental functional consequences for gene expression, its detailed studies have been for long time abrogated by the limits of classical light microscopy. The advent of super-resolution microscopy (SRM) techniques allowed for the visualization of the RNAPII transcription machinery with nanometer resolution and millisecond precision. In this review, we summarize the recent methodological advances in SRM, focus on its application for studies of the nanoscale organization in space and time of RNAPII transcription, and discuss its consequences for the mechanistic understanding of gene expression.

Cysteine cathepsins, a class of proteinaceous enzymes, regulate a wide variety of metabolic processes in human including protein breakdown and turnover and immune functions. Eleven cysteine cathepsins have been identified so far and a wide array of studies related to identifying their specific functions, regulation and distribution patterns in tissues have been conducted. However, in recent past, the association of cysteine cathepsins in occurrence and progression of cancers have been identified and this has caused unrest in scientists triggering them to investigate the physiology, biochemical pathways and interactions of these cathepsins in cancer metastasis and therefore has become a noteworthy topic of intensive research. This review focusses and collects together the published work on molecular functional and structural characterization studies that have been done so far on in vitro expression of genes encoding for cysteine cathepsins in the Escherichia coli bacterial expression system. Accordingly, it was found out that all cathepsins except for cathepsins K, C, H, X and W have been expressed this way and the majority of them were found to be expressed in E. coli BL21(DE3) pLysS expression host via pET3 expression vector. In addition, it was also noted that in most of the expression studies, the substrate that was used to validate the enzymatic activity of the recombinant enzyme that was produced was a cysteine residue along with a benzyloxy-carbonyl salt. Through this review, the authors suggest that there is a very high need that all cysteine cathepsins need to be characterized both structurally and functionally on a molecular platform to better understand their interactions including the biochemical pathways. It is also momentous that the mass production of the recombinant forms of these enzymes are facilitated via expression in such bacterial expression systems and in turn, would also provide a strong platform for the development and progression of studies related to human physiology including oncological studies such as cancer metastasis. Moreover, as per biochemical features of the enzymes that could be identified, the production of efficient inhibitors or inducers as per the necessity to improve health and promote wellbeing among the mankind could be facilitated.

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors influence COVID-19 by applying the Adverse Outcome Pathway (AOP) framework well-established in regulatory toxicology. This framework aims to model the sequence of events starting from an initial interaction of a stressor with the organism and the progress through key biological events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 patients have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues.

The fusion of "innovation theory" and "ecology" gave birth to a large number of studies on "innovation ecology", which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy to take the path of sustainable innovation. This type of research borrows a lot of concepts from ecology, and very vividly describes the competition and cooperation relationships formed by various agents in the innovation system, laying a good foundation for qualitative analysis of the inherent dynamics of innovation development. However, many studies focus on the analogous description of ecosystems and economic systems, lacking scientifically and rigorously quantitative empirical research as a support. This paper uses network-based indicators such as degree, cluster coefficient, and betweenness centrality to measure the function and position of high-tech enterprises in the Z-Park in a business environment, so as to clarify the socio-economic meaning of the topological structure of the regional innovation system. On this basis, it provides theoretical references for regional innovation development and sustainable development policy formulation.

Inherent low soil fertility status limits productivity of rice in the lowland ecologies in Northern Ghana. Combining organic and inorganic N fertilizers could help to maintain the fertility of lowland soils for rice production. A screen house pot experiment was carried out to investigate the combined effect of biochar-compost and inorganic N fertilizer on the nitrogen uptake and agronomic performance of rice plants grown on Eutric Gleysol lowland soil. Inorganic N fertilizer alone and its combinations with different types of biochar-compost (based on the proportions of biochar and compost) were used as treatment. A control (unamended soil) was also included. The incorporation of biochar-compost and inorganic N fertilizer improved the growth parameters and yield components of rice plants. The combination of biochar-compost and inorganic nitrogen fertilizer was also found to improve nitrogen uptake and nutrient use efficiency (NUE) in rice plants. This practice could be the most likely viable option for alleviating lowlands soil fertility issues and increasing rice productivity in Northern Ghana.

This work presents an approach for detecting mathematical formulas in scanned document images. The proposed approach is end-to-end trainable. Since many OCR engines cannot reliably work with the formulas, it is essential to isolate them to obtain the clean text for information extraction from the document. Our proposed pipeline comprises a hybrid task cascade network with deformable convolutions and a Resnext101 backbone. Both of these modifications help in better detection. We evaluate the proposed approaches on the ICDAR-2017 POD and Marmot datasets and achieve an overall accuracy of 96% for the ICDAR-2017 POD dataset. We achieve an overall reduction of error of 13%. Furthermore, the results on Marmot datasets are improved for the isolated and embedded formulas. We achieved an accuracy of 98.78% for the isolated formula and 90.21% overall accuracy for embedded formulas. Consequently, it results in an error reduction rate of 43% for isolated and 17.9% for embedded formulas.

The Pashmina and Barbari are two famous goat breeds found in the wide areas of the Indo-Pak region. Pashmina is famous for its long hair-fiber (Cashmere) production while Barbari is not-selected for this trait. So, the mRNA expression profiling in the skin samples of both breeds would be an attractive and judicious approach for detecting putative genes involved in this valued trait. Here, we performed differential gene expression analysis on publicly available RNA-Seq data from both breeds. Out of 44,617,994 filtered reads of Pashmina and 55,995,999 of Barbari which are 76.48% and 73.69% mapped to the ARS1 reference transcriptome assembly respectively. A pairwise comparison of both breeds resulted in 47,159 normalized expressed transcripts while 8,414 transcripts are differentially expressed above the significant threshold. Among these, 4,788 are upregulated in Pashmina while 3,626 transcripts are upregulated in Barbari. Fifty-nine transcripts harbor 57 genes including 32 LOC genes and 24 are annotated genes which were selected on the basis of TMM counts > 500. Genes with ectopic expressions other than uncharacterized and LOC symbol genes are Keratins (KRT) and Keratin Associated Proteins (KRTAPs), CystatinA&6, TCHH, SPRR4, PPIA, SLC25A4, S100A11, DMKN, LOR, ANXA2, PRR9 and SFN. All of these genes are likely to be involved in keratinocyte differentiation, sulfur matrix proteins, dermal papilla cells, hair follicles proliferation, hair curvature, wool fiber diameter, hair transition, hair shaft differentiation and its keratinization. These differentially expressed reported genes are critically valuable for enhancing the quality and quantity of the pashmina fiber and overall breed improvement. This study will also provide important information on hair follicle differentiation for further enrichment analyses and introducing this valued trait to other goat breeds as well.

Aedes aegypti (L.) is the primary vector of chikungunya, dengue, yellow fever and Zika viruses. The leucine-rich repeats (LRR)-containing domain is evolutionarily conserved in many proteins associated with innate immunity in invertebrates and vertebrates, as well as plants. We focused on the AaeLRIM1 and AaeAPL1 gene expressions in response to Zika virus (ZIKV) and Chikungunya virus (CHIKV) infection using a time course study, as well as the developmental expressions in the eggs, larvae, pupae, and adults. RNA-seq analysis data provided 60 leucine-rich repeat related transcriptions in Ae. aegypti in response to Zika virus (Accession number: GSE118858, https://www.ncbi.nlm.nih.gov/gds/?term=GSE118858). RNA-seq analysis data showed that AaeLRIM1 (AAEL012086-RA) and AaeAPL1 (AAEL009520-RA) were significantly upregulated 2.5 and 3-fold during infection by ZIKV 7-days post infection (dpi) of an Ae. aegypti Key West strain compared to an Orlando strain. The qPCR data showed that LRR-containing proteins AaeLRIM1, AaeAPL1 and five paralogues were expressed 100-fold lower than other nuclear genes, such as defensin, during all developmental stages examined. Together, these data provide insights into transcription profiles of LRR proteins of Ae. aegypti during its development and in response to infection with emergent arboviruses.

Whole-genome DNA sequencing of Lactobacillus D75 and D76 strains (Vitaflor, Russia) was performed using the PacBio RS II platform, followed by de novo assembly with SMRT Portal 2.3.0. The average nucleotide identity (ANI) test showed that both strains belong to the Lactobacillus helveticus, but not the L. acidophilus as previously assumed. 31 exopolysaccharide (EPS) production genes (nine of which form a single genetic cluster), 13 adhesion genes, 38 milk protein and 11 milk sugar utilization genes, 13 genes for and against specific antagonistic activity, aight antibiotic resistance genes, and also three CRISPR blocks and eight Cas I-B system genes were identified in the genomes of the both strains. The expression of some genes was confirmed. In fact, the presence of identified genes suggests that L. helveticus D75 and D76 are able to form biofilms on the outer mucin layer, inhibit the growth of pathogens and pathobionts, utilize milk substrates with the formation of digestible milk sugars and bioactive peptides, resist bacteriophages and show some genome-determined resistance to antibiotics, stimulate the host’s immune system. Pathogenicity genes have not been identified. The study results confirm the safety and high probiotic potential of the strains.

The spatial distribution of elements can be regarded as a numerical field of concentration values with a continuous spatial coverage. An active area of research is to discover geologically meaningful relationships among elements from their spatial distribution. To solve this problem, we propose an association rule mining method based on clustered events of spatial auto-correlation and applied it to the polymetallic deposits of the Chahanwusu River area, Qinghai Province, China. The elemental data for stream sediments were first clustered into HH (high-high), LL (low-low), HL (high-low), and LH (low-high) groups by using local Moran’s I clustering map (LMIC). Then the Apriori algorithm was used to mine the association rules among different elements in these clusters. More than 86% of the mined rule points are located within 1000 m of faults and near known ore occurrences, and occur in the upper reaches of the stream and catchment areas. In addition, we found that the Indosinian granodiorite is enriched in sulfophile elements, e.g., Zn, Ag and Cd, and the Variscan granite quartz diorite (P1γδο) coexists with Cu and associated elements. Therefore, the proposed algorithm is an effective method for mining co-existence patterns of elements and provides an insight into their enrichment mechanisms.

In recent years, hetero atom incorporated specially structured metal-free carbon nanomaterials have drawn huge attention among researchers. In comparison to the un-doped carbon nanomaterials, hetero atoms like nitrogen, sulphur, boron, phosphorous etc. incorporated nanomaterials become well-accepted as potential electrocatalysts in water splitting, supercapacitors and dye-sensitized solar cells. This review emphasizes on the mostly popular synthetic strategies utilized in last two decades and their excellent performance in electrocatalytic studies.