Miracle-dz/UniFAR-FTUs huggingface dataset:
Depolarization-Associated CircRNA Regulate Neural Gene Expression and in Some Cases May Function as Templates for Translation

Circular RNAs (circRNAs) are a relatively new class of RNA transcript with high abundance in the mammalian brain. Here, we show that circRNAs expression in differentiated neuroblastoma cells were significantly altered after depolarization with 107 upregulated and 47 downregulated circRNAs. This coincided with a global alteration in the expression of microRNA (miRNA) (n = 269) and mRNA (n = 1511) in depolarized cells, suggesting a regulatory axis of circRNA–miRNA–mRNA is involved in the cellular response to neural activity. In support of this, our in silico analysis revealed that the circular transcripts had the capacity to influence mRNA expression through interaction with common miRNAs. Loss-of-function of a highly expressed circRNA, circ-EXOC6B, resulted in altered expression of numerous mRNAs enriched in processes related to the EXOC6B function, suggesting that circRNAs may specifically regulate the genes acting in relation to their host genes. We also found that a subset of circRNAs, particularly in depolarized cells, were associated with ribosomes, suggesting they may be translated into protein. Overall, these data support a role for circRNAs in the modification of gene regulation associated with neuronal activity.
Acupuncture for hiccups

Abstract Background: A Hiccup is a common disease that often occurs along with other chronic or acute conditions. At present, there is a lack of feasible therapies for hiccups, and acupuncture is a treatment method with enormous clinical practice worldwide. Methods: Based on a pre-defined search strategy, we searched seven databases and screened them by two independent investigators, without language and publication status restriction from inception to date. We use the pre-set form to incorporate data and utilize Revman software to synthesize data. We will evaluate the risk of bias in the inclusion of the study based on the Cochrane ‘Risk of bias’ assessment tool. The quality of the evidence will be evaluated according to the GRADEpro software. Results: This systematic review will evaluate the efficacy and safety of acupuncture treatment for hiccups. The entire process will be referred to the Cochrane handbook recommended by the Cochrane Collaboration. Conclusion: This review will provide systematic evidence to summarize whether acupuncture is an effective intervention in the treatment of hiccup.
Poor nutrition for under-five children from poor households in Ethiopia: Evidence from 2016 Demographic and Health Survey

Background Ethiopia is commonly affected by drought and famine, and this has taken quite a toll on citizens of the country, particularly the under-five children. Undernutrition among under-five children in Ethiopia is a prominent public health concern, and it lacked attention for decades. However, the government of Ethiopia, together with other stakeholders, committed to overcoming the impact of malnutrition through the transformational plan. Here we show the magnitude of undernutrition among under-five children and the factors predicting the achievement of global nutrition targets set for 2025 at the World Health Assembly. Methods Ethiopian Demographic and Health Survey (EDHS) 2016 was used for this study. A total of 9494 child-mother pairs were included in this analysis. The nutritional status indicators (Height-for-age, Weight-for-height and Weight-for-age) of children were measured and categorized based on the World Health Organization child growth standards. A multilevel logistic regression model adjusted for clusters and sampling weights were used to identify factors associated with stunting, underweight, and wasting. The independent variables were assessed by calculating the odds ratios with 95% confidence interval (CI). Result The prevalence of stunting was 38.3% (95% CI: 36.4% to 40.2%), under-weight 23.3% (95%CI: 21.9% to 24.9%) and wasting 10.1% (95%, CI: 9.1% to 11.2%). Sex of the child (male), children older than 24 months, recent experience of diarrhea, household wealth index (poorest), and administrative regions (Tigray, Amhara and developing regions) had a higher risk of undernutrition. On the other hand, children born from overweight mothers and educated mother (primary, secondary or higher) had a lower risk of undernutrition. Conclusion The burden of undernutrition is still considerably high in Ethiopia. Implimentation of strategies and policies that focus on improving the socioeconomic educatiional status of the community need to be sustained. Generally, actions targeted on factors contributing to undernutrition among under-five children demands immediate attention to achieve national and global nutrition target.
Functional Genomic Identification of Cadmium Resistance Genes from a High GC Clone Library by Coupling the Sanger and PacBio Sequencing Strategies

Functional (meta) genomics allows the high-throughput identification of functional genes in a premise-free way. However, it is still difficult to perform Sanger sequencing for high GC DNA templates, which hinders the functional genomic exploration of a high GC genomic library. Here, we developed a procedure to resolve this problem by coupling the Sanger and PacBio sequencing strategies. Identification of cadmium (Cd) resistance genes from a small-insert high GC genomic library was performed to test the procedure. The library was generated from a high GC (75.35%) bacterial genome. Nineteen clones that conferred Cd resistance to Escherichia coli subject to Sanger sequencing directly. The positive clones were in parallel subject to in vivo amplification in host cells, from which recombinant plasmids were extracted and linearized by selected restriction endonucleases. PacBio sequencing was performed to obtain the full-length sequences. As the identities, partial sequences from Sanger sequencing were aligned to the full-length sequences from PacBio sequencing, which led to the identification of seven unique full-length sequences. The unique sequences were further aligned to the full genome sequence of the source strain. Functional screening showed that the identified positive clones were all able to improve Cd resistance of the host cells. The functional genomic procedure developed here couples the Sanger and PacBio sequencing methods and overcomes the difficulties in PCR approaches for high GC DNA. The procedure can be a promising option for the high-throughput sequencing of functional genomic libraries, and realize a cost-effective and time-efficient identification of the positive clones, particularly for high GC genetic materials.
The Spectrum of PAX6 Mutations and Genotype-Phenotype Correlations in the Eye

The transcription factor PAX6 is essential in ocular development in vertebrates, being considered the master regulator of the eye. During eye development, it is essential for the correct patterning and formation of the multi-layered optic cup and it is involved in the developing lens and corneal epithelium. In adulthood, it is mostly expressed in cornea, iris, and lens. PAX6 is a dosage-sensitive gene and it is highly regulated by several elements located upstream, downstream, and within the gene. There are more than 500 different mutations described to affect PAX6 and its regulatory regions, the majority of which lead to PAX6 haploinsufficiency, causing several ocular and systemic abnormalities. Aniridia is an autosomal dominant disorder that is marked by the complete or partial absence of the iris, foveal hypoplasia, and nystagmus, and is caused by heterozygous PAX6 mutations. Other ocular abnormalities have also been associated with PAX6 changes, and genotype-phenotype correlations are emerging. This review will cover recent advancements in PAX6 regulation, particularly the role of several enhancers that are known to regulate PAX6 during eye development and disease. We will also present an updated overview of the mutation spectrum, where an increasing number of mutations in the non-coding regions have been reported. Novel genotype-phenotype correlations will also be discussed.
Identification of the Pelvic Organ Prolapse/Incontinence Sexual Questionnaire—IUGA Revised (PISQ-IR) Cutoff Scores for Impaired Sexual Function in Women with Pelvic Floor Disorders

The aim of this cross-sectional study was to determine the cutoff scores for sexual dysfunction in disease-specific Pelvic Organ Prolapse/Incontinence Sexual Questionnaire—IUGA Revised (PISQ-IR) for women with pelvic floor disorders (PFD). Medical history and urogynecological data of 521 women with PFD were collected. The subjects provided information about their sexual activity and completed Female Sexual Function Index (FSFI) and PISQ-IR questionnaires. Sexually active (SA) women were further analyzed and categorized using their FSFI scores: <26.55—sexual dysfunction, >26.55—no sexual dysfunction. Receiver operating characteristics (ROC) curve tested how well PISQ-IR allowed to discriminate between patients with and without sexual disorders. Area under curve (AUC) was calculated to measure the PISQ-IR Summary Score efficiency in the prediction. The cutoff values which minimalize (1-specifity) and maximize sensitivity were selected. In the analyzed cohort, 250 (48%) women were SA and a total of 226 SA were recruited for the study: 143 (63.3%) with <26.55 FSFI and 83 (36.7%) with >26.55 FSFI (response rate: 90.4%). Using ROC curve analysis, PISQ-IR Summary Score of 2.68 was determined to be the optimal cutoff for distinguishing between dysfunctional and nondysfunctional women (AUC = 0.85), allowing to diagnose sexual dysfunction in SA women with PFD, with 90% sensitivity and 71% specificity.
Genomic analysis of carbapenemase-producing Enterobacteriaceae in Queensland reveals widespread transmission of bla IMP-4 on an IncHI2 plasmid

Carbapenemase-producing Enterobacteriaceae (CPE) are an increasingly common cause of healthcare-associated infections and may occasionally be identified in patients without extensive healthcare exposure. bla IMP-4 is the most frequently detected carbapenemase gene in Enterobacteriaceae within Australia, but little is known about the mechanisms behind its persistence. Here we used whole genome sequencing (WGS) to investigate the molecular epidemiology of bla IMP-4 in Queensland, Australia. In total, 107 CPE were collected between 2014 and 2017 and sent for WGS on an Illumina NextSeq500. Resistance genes and plasmid types were detected using a combination of read mapping and nucleotide comparison of de novo assemblies. Six isolates were additionally sequenced using Oxford Nanopore MinION to generate long-reads and fully characterize the context of the bla IMP-4 gene. Of 107 CPE, 93 carried the bla IMP-4 gene; 74/107 also carried an IncHI2 plasmid, suggesting carriage of the bla IMP-4 gene on an IncHI2 plasmid. Comparison of these isolates to a previously characterized IncHI2 plasmid pMS7884A (isolated from an Enterobacter hormaechei strain in Brisbane) suggested that all isolates carried a similar plasmid. Five of six representative isolates sequenced using Nanopore long-read technology carried IncHI2 plasmids harbouring the bla IMP-4 gene. While the vast majority of isolates represented ﻿ E. hormaechei , several other species were also found to carry the IncHI2 plasmid, including Klebsiella species, Escherichia coli and Citrobacter species. Several clonal groups of E. hormaechei were also identified, suggesting that persistence of bla IMP-4 is driven by both presence on a common plasmid and clonal spread of certain E. hormaechei lineages.
Comparative analysis of time-based and quadrat sampling in seasonal population dynamics of intermediate hosts of human schistosomes

Background Despite their importance for designing and evaluating schistosomiasis control trials, little attention in the literature has been dedicated to sampling protocols for the parasite’s snail intermediate hosts since their first development. We propose a comparative analysis of time-based and quadrat sampling protocols to quantify the seasonal variations in the abundance of these aquatic snail species of medical importance. Methodology/Principal findings Snail populations were monitored during 42 consecutive months in three types of habitats (ephemeral pond, ephemeral river and permanent stream) in two sites covering different climatic zones in Burkina Faso. We employed both a widely used time-based protocol of 30min of systematic collection at a weekly interval, and a quadrat protocol of 8 replicates per sample at a monthly interval. The correspondence between the two protocols was evaluated using an ensemble of statistical models including linear and saturating-type functional forms as well as allowing for count zero-inflation. The quadrat protocol yielded on average a relative standard error of 40%, for a mean snail density of 16.7 snails/m2 and index of dispersion of 1.51. Both protocols yielded similar seasonal patterns in snail abundance, confirming the asynchrony between permanent and ephemeral habitats with respect to the country’s seasonal rainfall patterns. Formal model comparison of the link between time vs. quadrat counts showed strong support of saturation for the latter and measurement zero-inflation, providing important evidence for the presence of density feedbacks in the snail’s population dynamics, as well as for spatial clustering. Conclusions/Significance In addition to the agreement with the time-based method, quadrat sampling provided insight into snail population dynamics and comparable density estimates across sites. The re-evaluation of these “traditional” sampling protocols, as well as the correspondence between their outputs, is of practical importance for the design and evaluation of schistosomiasis control trials.
Cross-Category Tea Polyphenols Evaluation Model Based on Feature Fusion of Electronic Nose and Hyperspectral Imagery

Tea polyphenols are important ingredients for evaluating tea quality. The rapid development of sensors provides an efficient method for nondestructive detection of tea polyphenols. Previous studies have shown that features obtained from single or multiple sensors yield better results in detecting interior tea quality. However, due to their lack of external features, it is difficult to meet the general evaluation model for the quality of the interior and exterior of tea. In addition, some features do not fully reflect the sensor signals of tea for several categories. Therefore, a feature fusion method based on time and frequency domains from electronic nose (E-nose) and hyperspectral imagery (HSI) is proposed to estimate the polyphenol content of tea for cross-category evaluation. The random forest and the gradient boosting decision tree (GBDT) are used to evaluate the feature importance to obtain the optimized features. Three models based on different features for cross-category tea (black tea, green tea, and yellow tea) were compared, including grid support vector regression (Grid-SVR), random forest (RF), and extreme gradient boosting (XGBoost). The results show that the accuracy of fusion features based on the time and frequency domain from the electronic nose and hyperspectral image system is higher than that of the features from single sensor. Whether based on all original features or optimized features, the performance of XGBoost is the best among the three regression algorithms (R2 = 0.998, RMSE = 0.434). Results indicate that the proposed method in this study can improve the estimation accuracy of tea polyphenol content for cross-category evaluation, which provides a technical basis for predicting other components of tea.
Predicting Topology Propagation Messages in Mobile Ad Hoc Networks: The Value of History

The mobile ad hoc communication in highly dynamic scenarios, like urban evacuations or search-and-rescue processes, plays a key role in coordinating the activities performed by the participants. Particularly, counting on message routing enhances the communication capability among these actors. Given the high dynamism of these networks and their low bandwidth, having mechanisms to predict the network topology offers several potential advantages; e.g., to reduce the number of topology propagation messages delivered through the network, the consumption of resources in the nodes and the amount of redundant retransmissions. Most strategies reported in the literature to perform these predictions are limited to support high mobility, consume a large amount of resources or require training. In order to contribute towards addressing that challenge, this paper presents a history-based predictor (HBP), which is a prediction strategy based on the assumption that some topological changes in these networks have happened before in the past, therefore, the predictor can take advantage of these patterns following a simple and low-cost approach. The article extends a previous proposal of the authors and evaluates its impact in highly mobile scenarios through the implementation of a real predictor for the optimized link state routing (OLSR) protocol. The use of this predictor, named OLSR-HBP, shows a reduction of 40–55% of topology propagation messages compared to the regular OLSR protocol. Moreover, the use of this predictor has a low cost in terms of CPU and memory consumption, and it can also be used with other routing protocols.
Lean Tissue and Protein in Health and Disease: Key Targets and Assessment Strategies

The 2015 Dudrick Research Symposium “Lean Tissue and Protein in Health and Disease: Key Targets and Assessment Strategies” was held on February 16, 2015, at Clinical Nutrition Week in Long Beach, California. The Dudrick Symposium honors the many pivotal and innovative contributions to the development and advancement of parenteral nutrition made by Dr Stanley J. Dudrick, physician scientist, academic leader, and a founding member of the American Society for Parenteral and Enteral Nutrition. As the 2014 recipient of the Dudrick award, Dr Carrie Earthman chaired the symposium and was the first of 3 speakers, followed by Dr Robert Wolfe and Dr Steven Heymsfield. The symposium addressed the importance of lean tissue to health and response to disease and injury, as well as the many opportunities and challenges in its assessment at the bedside. Lean tissue assessment is beneficial to clinical care in chronic and acute care clinical settings, given the strong relationship between lean tissue and outcomes, including functional status. Currently available bioimpedance techniques, including the use of bioimpedance parameters, for lean tissue and nutrition status assessment were presented. The connection between protein requirements and lean tissue was discussed, highlighting the maintenance of lean tissue as one of the most important primary end points by which protein requirements can be estimated. The various tracer techniques to establish protein requirements were presented, emphasizing the importance of practical considerations in research protocols aimed to establish protein requirements. Ultrasound and other new and emerging technologies that may be used for lean tissue assessment were discussed, and areas for future research were highlighted. (JPEN J Parenter Enteral Nutr. 2017;41:226-237)
Adverse Drug Reaction Detection in Social Media by Deep Learning Methods

Objective Health-related studies have been recently at the heart attention of the media. Social media, such as Twitter, has become a valuable online tool to describe the early detection of various adverse drug reactions (ADRs). Different medications have adverse effects on various cells and tissues, sometimes more than one cell population would be adversely affected. These types of side effect are occasionally associated with the direct or indirect influence of prescribed drugs but do not have general unfavorable mutagenic consequences on patients. This study aimed to demonstrate a quick and accurate method to collect and classify information based on the distribution of approved data on Twitter. Materials and Methods In this classification method, we selected "ask a patient" dataset and combination of Twitter "Ask a Patient" datasets that comprised of 6,623, 26,934, and 11,623 reviews. We used deep learning methods with the word2vec to classify ADR comments posted by the users and present an architecture by HAN, FastText, and CNN. Results Natural language processing (NLP) deep learning is able to address more advanced peculiarity in learning information compared to other types of machine learning. Moreover, the current study highlighted the advantage of incorporating various semantic features, including topics and concepts. Conclusion Our approach predicts drug safety with the accuracy of 93% (the combination of Twitter and "Ask a Patient" datasets) in a binary manner. Despite the apparent benefit of various conventional classifiers, deep learning- based text classification methods seem to be precise and influential tools to detect ADR.
Synthesis and Application of an Activity‐Based Peptide‐Peptoid Hybrid Probe for the Immunoproteasome

The immunoproteasome (iCP), a specific isoform of the proteasome's catalytic particle, is becoming an important protein complex of interest in various diseases. However, there is still much left to be learned about its activity in cells and how this can be altered by various endogenous conditions or with treatment with small molecules. Current strategies to investigate the iCP lack in their ability to be used in live, intact cells, limiting them to use in endpoint experiments. The iCP‐selective probe presented here has been shown to be compatible with various live‐cell assays, including monitoring iCP activity kinetically in a plate reader–based assay and observing single cells with confocal microscopy. A well‐studied iCP‐selective inhibitor, ONX‐0914, has also been demonstrated to decrease the fluorescence signal of the iCP probe in both of these assays, showing its potential function in investigating small‐molecule modulators of the iCP. © 2019 by John Wiley & Sons, Inc.
Exploring Variability in Landscape Ecological Risk and Quantifying Its Driving Factors in the Amu Darya Delta

Examining the drivers of landscape ecological risk can provide scientific information for planning and landscape optimization. The landscapes of the Amu Darya Delta (ADD) have recently undergone great changes, leading to increases in landscape ecological risks. However, the relationships between landscape ecological risk and its driving factors are poorly understood. In this study, the ADD was selected to construct landscape ecological risk index (ERI) values for 2000 and 2015. Based on a geographically weighted regression (GWR) model, the relationship between each of the normalized difference vegetation index (NDVI), land surface temperature (LST), digital elevation model (DEM), crop yield, population density (POP), and road density and the spatiotemporal variation in ERI were explored. The results showed that the ERI decreased from the periphery of the ADD to the centre and that high-risk areas were distributed in the ADD’s downstream region, with the total area of high-risk areas increasing by 86.55% from 2000 to 2015. The ERI was spatially correlated with Moran’s I in 2000 and 2015, with correlation of 0.67 and 0.72, respectively. The GWR model indicated that in most ADD areas, the NDVI had a negative impact on the ERI, whereas LST and DEM had positive impacts on the ERI. Crop yield, road density and POP were positively correlated with the ERI in the central region of the ADD, at road nodes and in densely populated urban areas, respectively. Based on the findings of this study, we suggest that the ecological constraints of the aforementioned factors should be considered in the process of delta development and protection.