Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic review of the systemic concentrations of local anaesthetic after transversus abdominis plane block and rectus sheath block

Background. Safe and efficacious modalities of perioperative analgesia are essential for enhanced recovery after surgery. Truncal nerve blocks are one potential adjunct for analgesia of the abdominal wall, and in recent years their popularity has increased. Transversus abdominis plane block (TAPB) and rectus sheath block (RSB) have been shown to reduce morphine consumption and improve pain relief after abdominal surgery. These blocks typically require large volumes of local anaesthetic (LA). We aimed to synthesize studies evaluating systemic concentrations of LA after perioperative TAP and RSB to enhance our understanding of systemic LA absorption and the risk of systemic toxicity. Methods. An independent literature review was performed in accordance with the methods outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. An electronic search of four databases (MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and PubMed) was conducted. Primary articles measuring systemic concentrations of LA after single-shot bolus TAPB or RSB were included. Results. Fifteen studies met the inclusion criteria. Rapid systemic LA absorption was observed in all studies. Of a total of 381 patients, mean peak concentrations of LA exceeded toxic thresholds in 33 patients, of whom three reported mild adverse effects. The addition of epinephrine reduced systemic absorption of LA. No instances of seizure or cardiac instability were observed. Conclusions. Local anaesthetic in TAPB and RSB can lead to detectable systemic concentrations that exceed commonly accepted thresholds of LA systemic toxicity. Our study highlights that these techniques are relatively safe with regard to LA systemic toxicity.
A few sequence polymorphisms among isolates of Maize bushy stunt phytoplasma associate with organ proliferation symptoms of infected maize plants

Background and Aims Maize bushy stunt phytoplasma (MBSP) is a bacterial pathogen of maize (Zea mays L.) across Latin America. MBSP belongs to the 16SrI‐B sub‐group within the genus ‘Candidatus Phytoplasma’. MBSP and its insect vector Dalbulus maidis (Hemiptera: Cicadellidae) are restricted to maize; both are thought to have coevolved with maize during its domestication from a teosinte‐like ancestor. MBSP‐infected maize plants show a diversity of symptoms. and it is likely that MBSP is under strong selection for increased virulence and insect transmission on maize hybrids that are widely grown in Brazil. In this study it was investigated whether the differences in genome sequences of MBSP isolates from two maize‐growing regions in South‐east Brazil explain variations in symptom severity of the MBSP isolates on various maize genotypes. Methods MBSP isolates were collected from maize production fields in Guaíra and Piracicaba in South‐east Brazil for infection assays. One representative isolate was chosen for de novo whole‐genome assembly and for the alignment of sequence reads from the genomes of other phytoplasma isolates to detect polymorphisms. Statistical methods were applied to investigate the correlation between variations in disease symptoms of infected maize plants and MBSP sequence polymorphisms. Key Results MBSP isolates contributed consistently to organ proliferation symptoms and maize genotype to leaf necrosis, reddening and yellowing of infected maize plants. The symptom differences are associated with polymorphisms in a phase‐variable lipoprotein, which is a candidate effector, and an ATP‐dependent lipoprotein ABC export protein, whereas no polymorphisms were observed in other candidate effector genes. Lipoproteins and ABC export proteins activate host defence responses, regulate pathogen attachment to host cells and activate effector secretion systems in other pathogens. Conclusions Polymorphisms in two putative virulence genes among MBSP isolates from maize‐growing regions in South‐east Brazil are associated with variations in organ proliferation symptoms of MBSP‐infected maize plants.
Identification and functional analysis of the risk microRNAs associated with cerebral low-grade glioma prognosis

Low-grade gliomas (LGGs) are associated with neurological disability. The present study used microRNA (miRNA) expression profiles to identify risk miRNAs for potential prognosis of cerebral LGGs. miRNA expression profiles and clinical data from 408 patients with cerebral LGGs were obtained from the Cancer Genome Atlas database. Risk miRNAs were identified by plotting Kaplan-Meier curves and Cox proportional hazard regression analysis with the survival and KMsurv packages in R. A regulatory network of miRNA-targets was constructed, followed by gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of miRNA targets was built using Search Tool for the Retrieval of Interacting Genes software, and sub-pathway identification was performed using the iSubpathwayMiner package in R. In total, 39 miRNAs had significant effect on survival curves. Following the Cox analysis and construction of miRNA-targets regulatory network, hsa-miRNA (miR)-326 was identified to regulate 397 target genes. Additionally, targets of miR-326 were primarily enriched in the GO terms of cell proliferation, epithelial growth factor receptor and nerve growth factor signaling pathways. Additionally, son of sevenless homolog 1 (SOS1), neuroblastoma RAS viral oncogene homolog (NRAS), vitamin D receptor (VDR) and mothers against decapentaplegic family member 3 (SMAD3) were most enriched in the PPI network. Targets of miR-326 were primarily enriched in sub-pathways including sphingolipid metabolism and arachidonic acid metabolism, in which sphingomyelin synthase 1 (SGMS1) and hematopoietic prostaglandin D synthase (HPGDS) were screened out. Hsa-miR-326 was identified as a risk miRNA for prognosis and may improve the outcome prediction of patients with cerebral LGG. This miRNA may regulate cancer cell proliferation by targeting SOS1, NRAS, VDR, SMAD3, SGMS1 and HPGDS.
Cloud-based adaptive exon prediction for DNA analysis

Cloud computing offers significant research and economic benefits to healthcare organisations. Cloud services provide a safe place for storing and managing large amounts of such sensitive data. Under conventional flow of gene information, gene sequence laboratories send out raw and inferred information via Internet to several sequence libraries. DNA sequencing storage costs will be minimised by use of cloud service. In this study, the authors put forward a novel genomic informatics system using Amazon Cloud Services, where genomic sequence information is stored and accessed for processing. True identification of exon regions in a DNA sequence is a key task in bioinformatics, which helps in disease identification and design drugs. Three base periodicity property of exons forms the basis of all exon identification techniques. Adaptive signal processing techniques found to be promising in comparison with several other methods. Several adaptive exon predictors (AEPs) are developed using variable normalised least mean square and its maximum normalised variants to reduce computational complexity. Finally, performance evaluation of various AEPs is done based on measures such as sensitivity, specificity and precision using various standard genomic datasets taken from National Center for Biotechnology Information genomic sequence database.
A Comprehensive Definition for Integrative Oncology.

Background Integrative oncology, which is generally understood to refer to the use of a combination of complementary medicine therapies in conjunction with conventional cancer treatments, has been defined in different ways, but there is no widely accepted definition. We sought to develop and establish a consensus for a comprehensive definition of the field of integrative oncology. Methods We used a mixed-methods approach that included a literature analysis and a consensus procedure, including an interdisciplinary expert panel and surveys, to develop a comprehensive and acceptable definition for the term "integrative oncology. " Results The themes identified in the literature and from the expert discussion were condensed into a two-sentence definition. Survey respondents had very positive views on the draft definition, and their comments helped to shape the final version. The final definition for integrative oncology is: "Integrative oncology is a patient-centered, evidence-informed field of cancer care that utilizes mind and body practices, natural products, and/or lifestyle modifications from different traditions alongside conventional cancer treatments. Integrative oncology aims to optimize health, quality of life, and clinical outcomes across the cancer care continuum and to empower people to prevent cancer and become active participants before,during, and beyond cancer treatment. " Conclusions This short and comprehensive definition for the term integrative oncology will facilitate a better understanding and communication of this emerging field. This definition will also drive focused and cohesive effort to advance the field of integrative oncology.
Regulation of Noncoding Transcriptome in Developing Photoreceptors by Rod Differentiation Factor NRL

Purpose Transcriptome analysis by next generation sequencing allows qualitative and quantitative profiling of expression patterns associated with development and disease. However, most transcribed sequences do not encode proteins, and little is known about the functional relevance of noncoding (nc) transcriptome in neuronal subtypes. The goal of this study was to perform a comprehensive analysis of long noncoding (lncRNAs) and antisense (asRNAs) RNAs expressed in mouse retinal photoreceptors. Methods Transcriptomic profiles were generated at six developmental time points from flow-sorted Nrlp-GFP (rods) and Nrlp-GFP;Nrl−/− (S-cone like) mouse photoreceptors. Bioinformatic analysis was performed to identify novel noncoding transcripts and assess their regulation by rod differentiation factor neural retina leucine zipper (NRL). In situ hybridization (ISH) was used for validation and cellular localization. Results NcRNA profiles demonstrated dynamic yet specific expression signature and coexpression clusters during rod development. In addition to currently annotated 586 lncRNAs and 454 asRNAs, we identified 1037 lncRNAs and 243 asRNAs by de novo assembly. Of these, 119 lncRNAs showed altered expression in the absence of NRL and included NRL binding sites in their promoter/enhancer regions. ISH studies validated the expression of 24 lncRNAs (including 12 previously unannotated) and 4 asRNAs in photoreceptors. Coexpression analysis demonstrated 63 functional modules and 209 significant antisense-gene correlations, allowing us to predict possible role of these lncRNAs in rods. Conclusions Our studies reveal coregulation of coding and noncoding transcripts in rod photoreceptors by NRL and establish the framework for deciphering the function of ncRNAs during retinal development.
3D-GNOME: an integrated web service for structural modeling of the 3D genome

Recent advances in high-throughput chromosome conformation capture (3C) technology, such as Hi-C and ChIA-PET, have demonstrated the importance of 3D genome organization in development, cell differentiation and transcriptional regulation. There is now a widespread need for computational tools to generate and analyze 3D structural models from 3C data. Here we introduce our 3D GeNOme Modeling Engine (3D-GNOME), a web service which generates 3D structures from 3C data and provides tools to visually inspect and annotate the resulting structures, in addition to a variety of statistical plots and heatmaps which characterize the selected genomic region. Users submit a bedpe (paired-end BED format) file containing the locations and strengths of long range contact points, and 3D-GNOME simulates the structure and provides a convenient user interface for further analysis. Alternatively, a user may generate structures using published ChIA-PET data for the GM12878 cell line by simply specifying a genomic region of interest. 3D-GNOME is freely available at http://3dgnome.cent. uw.edu. pl/.
BRIDG: a domain information model for translational and clinical protocol-driven research

Background It is critical to integrate and analyze data from biological, translational, and clinical studies with data from health systems; however, electronic artifacts are stored in thousands of disparate systems that are often unable to readily exchange data. Objective To facilitate meaningful data exchange, a model that presents a common understanding of biomedical research concepts and their relationships with health care semantics is required. The Biomedical Research Integrated Domain Group (BRIDG) domain information model fulfills this need. Software systems created from BRIDG have shared meaning "baked in," enabling interoperability among disparate systems. For nearly 10 years, the Clinical Data Standards Interchange Consortium, the National Cancer Institute, the US Food and Drug Administration, and Health Level 7 International have been key stakeholders in developing BRIDG. Methods BRIDG is an open-source Unified Modeling Language-class model developed through use cases and harmonization with other models. Results With its 4+ releases, BRIDG includes clinical and now translational research concepts in its Common, Protocol Representation, Study Conduct, Adverse Events, Regulatory, Statistical Analysis, Experiment, Biospecimen, and Molecular Biology subdomains. Interpretation The model is a Clinical Data Standards Interchange Consortium, Health Level 7 International, and International Standards Organization standard that has been utilized in national and international standards-based software development projects. It will continue to mature and evolve in the areas of clinical imaging, pathology, ontology, and vocabulary support. BRIDG 4.1. 1 and prior releases are freely available at https://bridgmodel.nci. nih.gov .
Enabling FPGA-as-a-Service in the Cloud with hCODE Platform

SUMMARY Major cloud service providers, including Amazon and Microsoft, have started employing ﬁeld-programmable gate arrays (FPGAs) to build high-performance and low-power-consumption cloud capability. However, utilizing an FPGA-enabled cloud is still challenging because of two main reasons. First, the introduction of software and hardware co-design leads to high development complexity. Second, FPGA virtualization and accelerator scheduling techniques are not fully researched for cluster deployment. In this paper, we propose an open-source FPGA-as-a-service (FaaS) platform, the hCODE, to simplify the design, management and deployment of FPGA accelerators at cluster scale. The proposed platform implements a Shell-and-IP design pattern and an open accelerator repository to reduce design and management costs of FPGA projects. E ﬃ cient FPGA virtualization and accelerator scheduling techniques are proposed to deploy accelerators on the FPGA-enabled cluster easily. With the proposed hCODE, hardware designers and accelerator users can be organized on one platform to e ﬃ ciently build open-hardware ecosystem.
Iron and Zinc Regulate Expression of a Putative ABC Metal Transporter in Corynebacterium diphtheriae

ABSTRACT Corynebacterium diphtheriae, a Gram-positive, aerobic bacterium, is the causative agent of diphtheria and cutaneous infections. While mechanisms required for heme iron acquisition are well known in C. diphtheriae, systems involved in the acquisition of other metals such as zinc and manganese remain poorly characterized. In this study, we identified a genetic region that encodes an ABC-type transporter (iutBCD) and that is flanked by two genes (iutA and iutE) encoding putative substrate binding proteins of the cluster 9 family, a related group of transporters associated primarily with the import of Mn and Zn. We showed that IutA and IutE are both membrane proteins with comparable Mn and Zn binding abilities. We demonstrated that the iutABCD genes are cotranscribed and repressed in response to iron by the iron-responsive repressor DtxR. Transcription of iutE was positively regulated in response to iron availability in a DtxR-dependent manner and was repressed in response to Zn by the Zn-dependent repressor Zur. Electrophoretic mobility shift assays showed that DtxR does not bind to the iutE upstream region, which indicates that DtxR regulation of iutE is indirect and that other regulatory factors controlled by DtxR are likely responsible for the iron-responsive regulation. Analysis of the iutE promoter region identified a 50-bp sequence at the 3′ end of the iutD gene that is required for the DtxR-dependent and iron-responsive activation of the iutE gene. These findings indicate that transcription of iutE is controlled by a complex mechanism that involves multiple regulatory factors whose activity is impacted by both Zn and Fe. IMPORTANCE Vaccination against diphtheria prevents toxin-related symptoms but does not inhibit bacterial colonization of the human host by the bacterium. Thus, Corynebacterium diphtheriae remains an important human pathogen that poses a significant health risk to unvaccinated individuals. The ability to acquire iron, zinc, and manganese is critical to the pathogenesis of many disease-causing organisms. Here, we describe a gene cluster in C. diphtheriae that encodes a metal importer that is homologous to broadly distributed metal transport systems, some with important roles in virulence in other bacterial pathogens. Two metal binding components of the gene cluster encode surface exposed proteins, and studies of such proteins may guide the development of second-generation vaccines for C. diphtheriae.
Multi-class active learning: A hybrid informative and representative criterion inspired approach

Labeling each instance in a large-scale data set is extremely labor- and time-consuming. One way to alleviate this problem is active learning, which aims to discover the most valuable instances for labeling to construct a powerful classifier with low generalization error. Considering both informativeness and representativeness provides a promising way to design a practical active learning. However, most existing active learning methods select instances favoring either informativeness or representativeness. Meanwhile, many are designed based on the binary class, so that they may present suboptimal solutions on the data sets with multiple classes. In this paper, a hybrid informative and representative criterion based multi-class active learning approach is proposed. We combine the informativeness and representativeness into one formulation, which can be solved under a unified framework. The informativeness is measured by the margin minimum while the representative information is measured by the maximum mean discrepancy. By minimizing the loss risk, we generalize the loss risk minimization principle to the multi-class active learning setting. Hence, the proposed method is not only suitable to the binary class but also the multiple classes. We conduct our experiments on twelve benchmark UCI data sets, and the experimental results demonstrate that the proposed method performs better than some state-of-the-art methods.
Evolutionary Multiobjective Optimization including Practically Desirable Solutions

In many practical situations the decision-maker has to pay special attention to decision space to determine the constructability of a potential solution, in addition to its optimality in objective space. Practically desirable solutions are those around preferred values in decision space and within a distance from optimality. This work investigates two methods to find simultaneously optimal and practically desirable solutions. The methods expand the objective space by adding fitness functions that favor preferred values for some variables. In addition, the methods incorporate a ranking mechanism that takes into account Pareto dominance in objective space and desirability in decision space. One method searches with one population in the expanded space, whereas the other one uses two populations to search concurrently in the original and expanded space. Our experimental results on benchmark and real world problems show that the proposed method can effectively find optimal and practically desirable solutions.
Decision-Making in Emotion Model

Having emotions is essential for robots to understand and sympathize with the feelings of people. In addition, it may allow the robots to be accepted into human society. The role of emotions in decision-making is another important perspective. In this paper, a model of emotions based on various neurological and psychological findings that are related to empathic communication between humans and robots is proposed. Subsequently, a mechanism of decision-making that is based on affects using convolutional LSTM and deep Q-network is examined.
MicroRNA duplication accelerates the recruitment of new targets during vertebrate evolution

The repertoire of miRNAs has considerably expanded during metazoan evolution, and duplication is an important mechanism for generating new functional miRNAs. However, relatively little is known about the functional divergence between paralogous miRNAs and the possible coevolution between duplicated miRNAs and the genomic contexts. By systematically examining small RNA expression profiles across various human tissues and interrogating the publicly available miRNA:mRNA pairing chimeras, we found that changes in expression patterns and targeting preferences are widespread for duplicated miRNAs in vertebrates. Both the empirical interactions and target predictions suggest that evolutionarily conserved homo-seed duplicated miRNAs pair with significantly higher numbers of target sites compared to the single-copy miRNAs. Our birth-and-death evolutionary analysis revealed that the new target sites of miRNAs experienced frequent gains and losses during function development. Our results suggest that a newly emerged target site has a higher probability to be functional and maintained by natural selection if it is paired to a seed shared by multiple paralogous miRNAs rather than being paired to a single-copy miRNA. We experimentally verified the divergence in target repression between two paralogous miRNAs by transfecting let-7a and let-7b mimics into kidney-derived cell lines of four mammalian species and measuring the resulting transcriptome alterations by extensive high-throughput sequencing. Our results also suggest that the gains and losses of let-7 target sites might be associated with the evolution of repressiveness of let-7 across mammalian species.
Generating Multicompartmental 3D Biological Constructs Interfaced through Sequential Injections in Microfluidic Devices

A novel technique is presented for molding and culturing composite 3D cellular constructs within microfluidic channels. The method is based on the use of removable molding polydimethylsiloxane (PDMS) inserts, which allow to selectively and incrementally generate composite 3D constructs featuring different cell types and/or biomaterials, with a high spatial control. The authors generate constructs made of either stacked hydrogels, with uniform horizontal interfaces, or flanked hydrogels with vertical interfaces. The authors also show how this technique can be employed to create custom‐shaped endothelial barriers and monolayers directly interfaced with 3D cellular constructs. This method dramatically improves the significance of in vitro 3D biological models, enhancing mimicry and enabling for controlled studies of complex biological districts.