Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuroendocrine Mechanisms Governing Sex Differences in Hyperalgesic Priming Involve Prolactin Receptor Sensory Neuron Signaling

Many clinical and preclinical studies report higher prevalence and severity of chronic pain in females. We used hyperalgesic priming with interleukin 6 (IL-6) priming and PGE2 as a second stimulus as a model for pain chronicity. Intraplantar IL-6 induced hypersensitivity was similar in magnitude and duration in both males and females, while both paw and intrathecal PGE2 hypersensitivity was more persistent in females. This difference in PGE2 response was dependent on both circulating estrogen and translation regulation signaling in the spinal cord. In males, the duration of hypersensitivity was regulated by testosterone. Since the prolactin receptor (Prlr) is regulated by reproductive hormones and is female-selectively activated in sensory neurons, we evaluated whether Prlr signaling contributes to hyperalgesic priming. Using ΔPRL, a competitive Prlr antagonist, and a mouse line with ablated Prlr in the Nav1.8 sensory neuronal population, we show that Prlr in sensory neurons is necessary for the development of hyperalgesic priming in female, but not male, mice. Overall, sex-specific mechanisms in the initiation and maintenance of chronic pain are regulated by the neuroendocrine system and, specifically, sensory neuronal Prlr signaling. SIGNIFICANCE STATEMENT Females are more likely to experience chronic pain than males, but the mechanisms that underlie this sex difference are not completely understood. Here, we demonstrate that the duration of mechanical hypersensitivity is dependent on circulating sex hormones in mice, where estrogen caused an extension of sensitivity and testosterone was responsible for a decrease in the duration of the hyperalgesic priming model of chronic pain. Additionally, we demonstrated that prolactin receptor expression in Nav1.8+ neurons was necessary for hyperalgesic priming in female, but not male, mice. Our work demonstrates a female-specific mechanism for the promotion of chronic pain involving the neuroendrocrine system and mediated by sensory neuronal prolactin receptor.
Journal of Reproduction and Development

Circular RNA (circRNA) plays a key role in the development and progression of several diseases; however, its role in intrauterine adhesions (IUAs) is not well understood. This study aims to investigate the expression profiles and potential role of circRNA in IUA. RNA-sequencing was performed to screen for abnormally expressed circRNAs in TGFβ1-induced IUA endometrial stromal cell (ESC) model (IUA group) and an SMAD3 inhibitor, SIS3-treated IUA ESC model (SIS3 group). Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed to uncover the key functions and pathways. Interaction networks were constructed and analyzed based on the competing endogenous RNA hypothesis of circRNA. CircRNAs were validated by Sanger sequencing and quantitative polymerase chain reaction (qPCR). Cell proliferation and apoptosis were measured using MTS and flow cytometry, respectively. The protein and mRNA expression levels of fibrosis-related proteins were measured using western blotting and reverse transcription– qPCR, respectively. A total of 66 circRNAs were differentially expressed between the IUA and SIS3 groups. CircPlekha7 was identified as one of the significantly upregulated circRNAs in the SIS3 group. Overexpression of circPlekha7 enhanced apoptosis, decreased the viability of ESCs, and suppressed the expression of α-SMA, collagen I, and SMAD3 in ESCs; whereas knockdown of circPlekha7 exhibited opposite results. Altogether, the results indicate that circPlekha7 plays an antifibrotic role in IUA and may serve as a promising prognostic biomarker for patients with IUA. Therefore, overexpression of circPlekha7 could be a potential treatment strategy for IUA.
Assessment of Hepatocellular Carcinoma Response to 90Y Radioembolization Using Dynamic Contrast Material-enhanced MRI and Intravoxel Incoherent Motion Diffusion-weighted Imaging.

Purpose To quantify diffusion and perfusion changes in hepatocellular carcinoma (HCC) induced by yttrium 90 (90Y) radioembolization and to assess the value of dynamic contrast material-enhanced (DCE) MRI and intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for predicting HCC response. Materials and Methods Institutional review board approval was obtained for this prospective study (clinical trial registry NCT01871545). Twenty-four participants with HCC (mean age, 69 years ± 9 [standard deviation], 18 men) underwent multiparametric MRI, including IVIM DWI and gadoxetic acid DCE MRI before (n = 24) and 6 weeks (n = 21) after radioembolization. IVIM DWI and DCE MRI histogram parameters were quantified in HCCs and liver parenchyma. HCC response was assessed by using modified Response Evaluation Criteria in Solid Tumors at 6 weeks and 6-12 months after radioembolization. Logistic regression analysis was used to evaluate the diagnostic performance of baseline MRI and clinical parameters for prediction of response. Results Twenty-five HCCs were analyzed (mean size, 3.6 cm ± 1.9). Radioembolization resulted in significantly decreased perfusion (DCE MRI arterial flow, P = .002; IVIM pseudodiffusion coefficient [D*], P = .014). Multivariate logistic regression selected combined serum α-fetoprotein and portal flow (F p ) skewness (area under the curve [AUC] = 0.924) and combined D* standard deviation and F p kurtosis (AUC = 0.916) for prediction of objective and complete response at 6 weeks, respectively. Standard deviation of DCE MRI parameter arterial fraction was selected as the optimal predictor for complete response at 6-12 months (AUC = 0.857). Conclusion Diffusion and perfusion MRI can be used to evaluate the response of HCC to radioembolization. Pretreatment DCE MRI histogram parameters may be useful for radioembolization treatment stratification. Supplemental material is available for this article. © RSNA, 2020.
Sampling Strategy Within a Wild Soybean Population Based on Its Genetic Variation Detected by ISSR Markers

In order to determine an appropriate sampling strategy for the effective conservation of wild soybean (Glycine soja Sieb. et Zucc.) in China, a natural population from Jiangwan Airport in Shanghai was studied for its genetic diversity through the inter-simple sequence repeat (ISSR) marker analysis of a sample set consisting of 100 randomly collected individuals. A relatively large genetic diversity was detected among the samples based on estimation of DNA products amplified from 15 selected ISSR primers, with the similarity coefficient varying from 0.17 to 0.89. The mean expected heterozygosity (He) was 0.171 4 per locus, and Shannon index (1) was 0.271 4. The Principal Coordinate Analysis (PCA) further indicated that genetic diversity of the Jiangwan wild soybean population was not evenly distributed, instead, was presented by a mosaic or clustered distribution pattern. Correlation study between genetic diversity and number of samples demonstrated that genetic diversity increased dramatically with the increase of number of samples within 40 individuals, but the increase became slow and rapidly reached a plateau when more than 40 individuals were included in the analysis. It is concluded that (i) a sample set of approximately 35-45 individuals should be included to represent possibly high genetic diversity when conservation of a wild soybean population ex situ is undertaken; and (ii) collection of wild soybean samples should be spread out as wide as possible within a population, and a certain distance should be kept as intervals among individuals for sampling.
Is Narcissism a Slow Life History Strategy Indicator?: The Answer Depends on the LHS Instrument

The dark triad (DT) traits are differentially related to psychometrically assessed life history strategy (LHS), such that psychopathy is strongly associated with a faster LHS, whereas narcissism appears to be, if anything, a slow LHS indicator. However, the research supporting these generalizations has been based largely on undergraduate samples in which LHS has been measured using the Arizona Life History Battery (ALHB; or its short version the Mini-K), an instrument that arguably lacks adequate coverage of low-extroversion content linked to a slower LHS. In this study, 929 U.S. MTurk workers completed a set of DT instruments, a 10-item Big Five Inventory, a 42-item version of the ALHB (K-SF-42), and the life history rating form (LHRF), which is less weighted toward high extroversion content than the ALHB. Factor analysis of the DT instruments yielded factors corresponding to callousness, secondary psychopathy, and socially adaptive narcissism (leadership/authority and grandiose exhibitionism). Callousness and secondary psychopathy were fast LHS indicators with respect to both LHS instruments. Socially adaptive narcissism appeared as a slow LHS indicator with respect to the K-SF-42 but as a fast LHS indicator with respect to the LHRF. Variation in extroversion accounted entirely for the K-SF-42’s positive association with socially adaptive narcissism. This study suggests that narcissism’s apparent status as a slow LHS indicator may be more a matter of measurement than of substance.
Reuterin disrupts Clostridioides difficile metabolism and pathogenicity through reactive oxygen species generation

ABSTRACT Antibiotic resistance is one of the world’s greatest public health challenges and adjunct probiotic therapies are strategies that could lessen this burden. Clostridioides difficile infection (CDI) is a prime example where adjunct probiotic therapies could decrease disease incidence through prevention. Human-derived Lactobacillus reuteri is a probiotic that produces the antimicrobial compound reuterin known to prevent C. difficile colonization of antibiotic-treated fecal microbial communities. However, the mechanism of inhibition is unclear. We show that reuterin inhibits C. difficile outgrowth from spores and vegetative cell growth, however, no effect on C. difficile germination or sporulation was observed. Consistent with published studies, we found that exposure to reuterin stimulated reactive oxygen species (ROS) in C. difficile, resulting in a concentration-dependent reduction in cell viability that was rescued by the antioxidant glutathione. Sublethal concentrations of reuterin enhanced the susceptibility of vegetative C. difficile to vancomycin and metronidazole treatment and reduced toxin synthesis by C. difficile. We also demonstrate that reuterin is protective against C. difficile toxin-mediated cellular damage in the human intestinal enteroid model. Overall, our results indicate that ROS are essential mediators of reuterin activity and show that reuterin production by L. reuteri is compatible as a therapeutic in a clinically relevant model.
The Text-Score Allocation Model : Finding Latent Topics of Online Review Documents and Multi-Item Ratings

This study focuses on online review data in which comments are written in natural languages and evaluations are attached as integers. This study develops a topic model incorporating both natural languages and evaluation scores, expanding latent Dirichlet allocation (LDA). The model consists of two components: LDA and a Dirichlet-binomial clustering model. The latter assumes binomial distributions for the review scores. Since the model assumes conjugate distributions, we can apply a fast and stable estimator based on collapsed Gibbs sampling to estimate the parameters. Further, the model enables us to examine the relationship between vocabulary words and review scores based on the topic allocation results.
Multilocus Sequence Typing of Commensal and Enteropathogenic Escherichia Coli from Domestic and Wild Lagomorphs in Italy

The aim of the study was to determine the multilocus sequence types of Escherichia coli from diseased farm rabbits and apparently healthy wild lagomorphs, and the genetic relatedness among them. Fifty-five enteropathogenic E. coli from reared rabbits and 32 from wild rabbits and hares were characterised by multilocus sequence typing (MLST) according to the Michigan State University Ec MLST scheme. Isolates were differentiated into 37 sequence types (STs), which were grouped into 8 clonal complexes (CCs). The most common ST was ST140 (CC31), followed by ST238 and ST119 (CC17). MLST analysis revealed 22 novel STs. Phylogenetic analyses showed a heterogeneous distribution of STs into 3 clusters of genetically related strains. The genetic relationship among STs of different origin and the detection of new, as well as previously described STs as human pathogens, indicate a widespread distribution and adaptability of particular lineages to different hosts. These findings highlight the need for further research to improve the knowledge about E. coli populations colonising the gut of lagomorphs and their zoonotic potential.
COMPARISON OF STATCOM AND TCSC ON VOLTAGE STABILITY USING MLP INDEX

Traditionally shunt and series compensation is used to maximize the transfer capability of a transmission line. By using FACTS controllers one can control the variables such as voltage magnitude and phase angle at chosen bus and line impedance. There are five well known FACTS devices utilized by the utilities for this purpose. These FACTS devices are Static Var Compensator (SVC), Static Synchronous Compensator (STATCOM), Thyristor Controlled Series Capacitor (TCSC), Static Synchronous Series Compensator (SSSC) and Unified Power Flow Controller (UPFC). The voltage collapse occurs when a system is loaded beyond its maximum loadability point. Many analysis methods have been proposed and currently used for the study of this problem. Most of these techniques are based on the identification of system equilibrium where the corresponding jacobians become singular. These equilibrium points are typically referred to as points of voltage collapse and can be mathematically associated to saddle-node bifurcation. The voltage collapse points are also known as maximum loadability
Analysis on Energy-Efficient Protocols for Wireless Sensor Networks

Wireless Sensor Network (WSN) is a Wireless Network in which a sensor or a group of sensors communicate with each other as well as the surroundings to gather information about it and transmit it to the receiver of the Base Station (BS). The operations in a WSN is usually carried out with the help of finite sources of energy such as battery. Therefore, these networks constantly need the replacement of batteries. But the replacement of the batteries is quite a complicated task because of the complexity of the structure. So it is quite a critical issue while designing such Networks. In order to solve this issue, the wireless networks must be energy-efficient and durable to sustain for longer durations. Here, two types of Wireless Networks Protocols have been introduced and explained – LEACH (Low-Energy Adaptive Clustering Hierarchy) Protocol and EAMMH (Energy Aware Multi-Hop Multi-Path Hierarchical) Protocol. They are explained in both Homogeneous as well as Heterogeneous Systems and are simulated using MATLAB.
Influence of Fermentation Condition and Alkali Treatment on the Porosity and Thickness of Bacterial Cellulose Membranes

The object of the present study was to produce bacterial cellulose (BC) membranes and studying the effect of carbon source, time and conditions of inoculation, type of alkali used for purification and the method of drying on its porosity and thickness of the resultant membranes. Acetobacter xylinum was isolated from local rotten juice, and used for membrane production. The highest porosity was attained when sucrose was used as a source of carbon compared to glucose, fructose and glycerol. However, fructose, glucose and glycerol resulted in higher pH value for the medium used as medium for bacterial growth. Using glycerol as the sole carbon source gave the highest bacterial cellulose and biomass (g/l) as compared to glucose, fructose and sucrose. Small inoculation led to high porosities and lowest thickness of the resultant membranes. Porosity of membranes was affected by the type of alkali used for the purification of the membranes. Application of K 2 CO 3 for purification gave the highest porosity while Na OH gave the lowest porosity. Hot air- drying of the membrane resulted in the lowest porosity as compared with freeze drying method which did not cause any damage to the porosity of the membrane.
A new approach to stochastic modeling and fitting mortality risk

Most mortality models often suffer from one problem or another which in turn make them inappropriate for a particular country or for a particular age group. In this paper, we proposed three new models alongside with new fittin g method using Ridge regression. The models captured the developed countries mortali ty improvement structure and the developing countries limited data mortality structu re. To demonstrate the new approach, a review of some robust existing models was done an d quantitative comparison between the proposed models and the existing models was also achieved. Results from monte-carlo simulation revealed the supremacy of th e proposed models over the existing models. The Bayesian Information Criteria (BIC), Lo g-likelihood and Root Mean Square error of Prediction (RMSEP) were used for the model comparison.
A proposal of a methodology for technology roadmapping for SMEs

Innovation requires an interdisciplinary approach, knowledge processing, diversity and openness to collaboration that in general SMEs struggle to access. The paper contributes to foresight and technology management, proposing a methodology to implement technological roadmapping for SMEs. The research strategy is an action research in a S&T park, Area Science Park.
Classification of Arabic Tweets for Damage Event Detection

This paper proposes a model to analyze Arabic tweets to harness valuable information for first responders during an emergency e.g. Flood disaster. Our proposed model is designed to detect floods and assess damage during disasters using Tweets to concentrate on rescue operations. For this, we used the common classification algorithms such as SVM, RF, J48 and NB in order to classify these tweets and detect those with relevant information regarding damage. We have conducted two experiments. In the first experiment, we have implemented two classification models A and B . Model A classifies the tweets into relevant and non-relevant , while model B classifies the relevant tweets into damage or not damage (where the former refers to tweets that have information about damage and the later refers to tweets that do not have such information). Our obtained results show that Random Forest achieves best accuracy in classifying tweets into relevant and non-relevant of 83.95%, while SVM achieves the best accuracy in classifying tweets into damage or not damage of 93.39%. In the experiment B, we re-implement the two classification models of the first experiment, but we increase the size of the datasets used with both models. Therefore, we generate other two classification models C and D . We compare the performance of learning model A and C and the performance of learning model B and D in the first and second experiments respectively. Our results show that learning model A achieves accuracy of 83.95%, while learning model C
Information Theoretic Approaches for Testing Missingness in Predictive Models

In predictive modeling, missing data can often result in learning biased models despite application of imputation approaches. Therefore, it is important to assess the missingness process of the data. We present hypothesis tests for assessing these dependencies: MI-MCAR (mutual information for missing completely at random) and MI-US (mutual information for unobserved sources). MI-MCAR tests marginal independence between the missingness pattern and the the data matrix, while MI-US is a conditional randomization test (CRT) to test the dependence of the missingness pattern on unobserved sources. These methods can be applied to heterogeneous data types and can serve to identify missingness pathologies in data which speciﬁcally affect performance for regression tasks. We evaluate our methods on simulated and pseudo-simulated datasets and show that we are able to identify data which suffers from miss-ingness due to unobserved sources.
A Survey on Ontology Building Methodologies and Tools for Indian Languages

—Ontology is one of the central areas in natural language processing (NLP) and artificial intelligence. Ontology is important for exploring the information for an efficient and useful management of knowledge and establishing communication between different entities such as human and application for understanding as well as reusing and sharing of knowledge. This paper reviews about the use of different ontology building approaches in NLP and their usage in Indian languages. The paper presents a survey of approaches for ontology building and its use in Indian regional language as well as challenges regarding Indian language usage of ontology mainly due to Indian languages being morphologically rich, resource constraint, lack of expertise and knowledge in building ontology.
A TIME SLOT AND COST NEGOTIATION METHOD FOR CLOUD SERVICES

When we are going to make booking for Cloud services, then the customer and service suppliers have to create service level contracts during negotiation. Where it is significant for equally a customer and a service supplier to reach an agreement on the cost of a services while they are going to cloud services, to time, there is little or no negotiation maintain for mutually Time Slot and Cost Negotiations ( TSCNs ) for cloud service reserving. This editorial presents a many issue negotiation method to make possible the following: 1) TSCNs between Cloud mediators and 2) tradeoff between Time Slot and Cost effectiveness. Unlike several previous negotiation scheme in which a negotiation mediator build only one offer at a time. In our effort, mediator constructs several offers in a negotiation round that produce the similar collective utility, differing only in terms of individual Time Slot and Cost effectiveness. An additional innovation of effort is formulating a new time-slot usefulness function which differentiates preferences for dissimilar time slots.
[Unveiling Macro Momentum.]

In the multi-asset realm, risk factors are extensively used by portfolio managers as generators of risk premia. In [5], AQR Capital Management reveals its usage as a strong indicator to generate returns. In this context, the following paper focuses on a preponderant factor — momentum — applied to macroeconomic indicators. The resulting investment strategy, referred to as macro momentum, involves the implementation of a macro signals analysis, and its translation into tactical allocations within a multi-asset portfolio framework.
Quercetin Fatty Acid Esters: from Synthesis to the Mushroom Tyrosinase Inhibition

New complexes of quercetin esterification with alpha linolenic acid (ALA) and linoleic acid (LA) were applied as inhibitor of tyrosinase as the main melanogenesis.enzyme The most abundant flavonoid compound, quercetin was considered as the base of esterification with poly unsaturated fatty acids (PUFA). The new derivatives including quercetin- ALA (complex I) and quercetin- LA (complex II) were designed and their impacts on mushroom tyrosinase (MT) were assessed by experimental and theoretical studies. The new complexes I and II were induced competitive inhibition on tyrosinase enzyme with Ki of 0.59 and 0.40 mM, respectively. The molecular analysis of docking revealed that the complex II has a better ability to interact with enzyme than the complex I and the nature of interactions was obeyed from hydrophobic manner. So, the esterification of quercetin by above mentioned fatty acids achieved strength inhibitors against tyrosinase and because of their abundant in natural sources and importance in lifestyle, it is proposed to utilize them in medicine, cosmetics, agriculture and food industries. Their other biological properties need more investigations.