Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of peripheral beta blockers on isoprenaline-induced fear conditioned rats

Anxiety disorders are the most prominent mental illness in the United States, affecting 18 percent of the population. Aversive memories, such as traumatic events, are associated with unconditioned stimuli. Few studies have shown that cardiovascular dysfunctions can be associated with aversive contexts or cues. However, preliminary results demonstrate that the beta-adrenergic agonist isoprenaline can induce defensive reactions in rats, which can promote aversive learning to the odors. The purpose of this study was to investigate whether aversive associations were prompted by activation of peripheral receptors. To test this, beta-blockers were injected 15 minutes before isoprenaline to induce fear. Male wistar rats (280-350g) were trained using an olfactory fear conditioning paradigm (OFC), consisting of 5 minute training and test sessions. Isoprenaline was used to arouse fear (unconditioned stimulus) and the neutral odor amyl acetate was used as the conditioned stimulus in an acquisition chamber, 24 h after a 3 min familiarization session. In the first experiment (during the training session), rats were injected with either saline or isoprenaline 15 min before conditioning to investigate whether isoprenaline promoted defensive behaviors (crouch sniffing, freezing and stretch ahead). Once isoprenaline was confirmed to promote fear, the second experiment used a pre-treatment of -blockers nadolol (10 mg/Kg, a peripheral non-selective beta-blocker) or atenolol (10 mg/Kg and 20 mg/Kg, a peripheral selective beta-1 blocker), which was injected 15 minutes before the isoprenaline treatment. The fear association was analyzed 24h later during the test session within a different context (odor box) composed of an enclosed and roofed zone as opposed to an open compartment where the odor was released after a minute of habituation. Defensive behaviors, as well as total time active, approach time, hide time, and crossings were observed in the odor box. Veronica Go, Biochemistry, Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37916 USA. yjk112@vols.utk. edu Carol Ferraz Webber, Eloisa Pavesi, and Antonio de Padua Carobrez, Departamento de Farmacologia, CCB, Universidade Federal de Santa Catarina, Florianpolis, SC 88040-900, Brazil Our results showed that nadolol attenuated isoprenalineinduced fear, while atenolol rats continued to display signs of fear during the training session. During the test, isoprenaline promoted aversive memories to odor, which was seen by increased defensive time during the odor test, while nadolol impaired this aversive association. Conversely, atenolol did not block the OFC induced by isoprenaline. These results suggest that fear memory can be induced by the peripheral beta receptor activation. While the beta-1 blocker was not able to prevent the odorassociation, the peripheral non-selective blocker could impair cardiovascular mal-dysfunctions responsible in the fear mechanisms, suggesting a potential anxiolytic compound.
The Smart Grid—State-of-the-art and future trends

This presentation introduces Smart Grid and associated technical, environmental and socio-economic, and other non-tangible benefits to society, and articulates the need for the concept and the fact that it is a dynamic interactive, real-time infrastructure that responds to the challenges of designing and building the power system of the future, rather than being simply a marketing term. To illustrate the diversity of terminology, we compare an Electric Power Research Institute (EPRI) definition with that suggested by a study group of the International Electrotechnical Commission (IEC). Next, a paper sponsored by the Canadian Electricity Association (CEA) that cites three example definitions to highlight the diversity of views of Smart Grid is briefly reviewed. Early misconceptions and characterizations of Smart Grid are discussed as a prelude to addressing challenging issues that motivate developing and implementing related innovative technologies, products and services. We then discuss the potential promise of the Smart Grid, which is embedded in its often-cited attributes of efficiency, accommodating, quality focus, enabling and self-healing to name some. The presentation then addresses some of the often-cited impediments to accepting Smart Grid which are based on concerns and issues confronting its forward progress, adoption and acceptance. Distribution Automation (DA) and embedded intelligence are discussed emphasizing self-healing, optimizing operation and facilitating recreation and recovery from abnormal events. Functional and integration requirements of Distributed Energy Resources (DER,) are detailed. Smart Consumption Infrastructure elements of Distribution Management Systems (DMS,) Automated Metering Infrastructure (AMI,) Smart Homes (SH), and Smart Appliances (SA,) are discussed. We discuss smart grid activities in China, India, and the development of a Smart Grid roadmap for the US State of Kentucky. The approaches of each of these cases reflect the diversity of policy initiatives in these jurisdictions. State of the art reviews of distribution network active management and future development trends in technologies and methods, where centralized and decentralized management frameworks and applying agent-based coordination are discussed. A review of smart home technologies and the goals of an energy management system (SHEMS) are also discussed.
Towards Optimality Conditions for Non-Linear Networks

Training non-linear neural networks is a challenging task, but over the years, various approaches coming from different perspectives have been proposed to improve performance. However, insights into what fundamentally constitutes \textit{optimal} network parameters remains obscure. Similarly, given what properties of data can we hope for a non-linear network to learn is also not well studied. In order to address these challenges, we take a novel approach by analysing neural network from a data generating perspective, where we assume hidden layers generate the observed data. This perspective allows us to connect seemingly disparate approaches explored independently in the machine learning community such as batch normalization, Independent Component Analysis, orthogonal weight initialization, etc, as parts of a bigger picture and provide insights into non-linear networks in terms of properties of parameter and data that lead to better performance.
Callose synthesis in higher plants

Callose is a polysaccharide in the form of β-1,3-glucan with some β-1,6-branches and it exists in the cell walls of a wide variety of higher plants. Callose plays important roles during a variety of processes in plant development and/or in response to multiple biotic and abiotic stresses. It is now generally believed that callose is produced by callose synthases and that it is degraded by β-1,3-glucanases. Despite the importance of callose in plants, we have only recently begun to elucidate the molecular mechanism of its synthesis. Molecular and genetic studies in Arabidopsis have identified a set of genes that are involved in the biosynthesis and degradation of callose. In this mini-review, we highlight recent progress in understanding callose biosynthesis and degradation and discuss the future challenges of unraveling the mechanism(s) by which callose synthase operate.
Insight-driven Crisis Information - Preparing for the Unexpected using Big Data

National information and situation centers are faced with rising information needs and the question of how to prepare for unexpected situations. One promising development is the access to vastly growing data produced by distributed sensors and a socially networked society. Current emergency information systems are limited in the amount of complex data they can process and interpret in real-time and provide only partially integrated prediction and alarming capabilities. In this paper we present a novel approach to build a new type of automated and scalable information systems that intelligently make use of massive streams of structured and unstructured data and incorporate human feedback for automated incident detection and learning. Big data technologies, uncertainty handling and privacyby-design are employed to match end-user system requirements. We share first experiences analyzing data from the centennial flood in Germany 2013.
Reversible ovarian failure induced by a Chinese herbal medicine: lei gong teng

A 36 year old Caucasian nulliparous woman being treated in the genitourinary medicine department for genital warts commented that she had not had a period for five months. Following referral to our gynaecology clinic and on further questioning, it became apparent that she had noticed vaginal dryness, reduced libido, hot flushes and night sweats over the previous few months. Before this her periods had been regular. The woman’s mother had reached her menopause in her early forties. Apart from mild psoriasis she had no past medical history and clinical examination was normal. The concentration of follicle stimulating hormone in her blood was 130 iu/L (normal range 3–35 iu/L), luteinising hormone 45 iu/L (normal range 3–17.6 iu/L) and 17h-oestradiol <50 pmol/L (normal premenopausal range 90–1470 pmol/L). Her concentration of prolactin and her thyroid function were normal. She did not have gastric parietal, smooth muscle or mitochondrial antibodies. It was thought that she had premature ovarian failure. At the time of her last period five months previously, she had started taking the Chinese herbal medicine lei gong teng, and then completed a four-month course of this for treatment of her psoriasis. After stopping the lei gong teng for two months, a repeat hormone profile indicated a falling follicle stimulating hormone concentration to 87 iu/L and luteinising hormone to 45 iu/L, with a corresponding rise in 17h-oestradiol concentration to 180 pmol/L. Three months after stopping lei gong teng, normal regular menstruation returned. Her plasma follicle stimulating hormone and her luteinising hormone were 3 and 12 iu/L, respectively. Discussion
Severe adverse cutaneous reactions to drugs.

Although the rate of acute severe adverse cutaneous reactions to medications is low, these reactions can affect anyone who takes medications and can result in death or disability1. Even a small number of cases associated with a particular drug may alter the recommendations for its use2–4. Prompt differentiation of severe adverse cutaneous reactions from less serious skin disorders may be difficult. Rapid recognition of severe reactions is essential. Prompt withdrawal of the offending drug is often the most important action to minimize morbidity. Adverse cutaneous reactions to drugs are frequent, affecting 2 to 3 percent of hospitalized .
Microinjection of NMDA-type glutamate receptor agonist NMDA and antagonist D-AP-5 into the central nucleus of the amygdale alters water intake rather than food intake.

OBJECTIVE To investigate the role of N-Methyl-D-aspartic acid (NMDA)-type glutamate receptors in the central nucleus of the amygdale (CeA) in food and water intake. METHODS Male Sprague-Dawley rats with stainless steel cannulae implanted unilaterally into the CeA were used. The prototypic NMDA receptor agonist NMDA, or the selective NMDA receptor antagonist D(-)-2-amino-5-phosphonopentanoic acid (D-AP-5) was microinjected into the CeA of satiated and euhydrated rats. RESULTS Intra-CeA injection of 8.50, 17.00, or 34.00 nmol NMDA did not alter food intake but significantly increased water intake 0-1 h after the injection (F(3,32)=3.191, P=0.037) independent of food intake. Without affecting the food intake, injection of 6.34, 12.70, or 25.40 nmol D-AP-5 into the CeA significantly decreased water intake 0-1 h after the injection (F(3,28)=3.118, P=0.042) independent of food intake. CONCLUSION NMDA receptors in the CeA may participate in the control of water intake rather than food intake.
A Privacy Assistant for the Internet of Things

Copyright is held by the author/owner. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee. Poster presented at the 13th Symposium on Usable Privacy and Security (SOUPS 2017). Abstract The rapid development of devices and sensors connected to the Internet of Things (IoT) is resulting in widespread collection of personally identifiable information. Since these devices and sensors are often small, embedded, and with no user interface, many people are unaware of the data collection, and are therefore unable to take control of their privacy in these contexts. Our work highlights the idea of an infrastructure which notifies users of data collection in heterogeneous IoT environments. We envision privacy assistants residing on individual smartphones, which selectively inform their owners about data collection in their vicinity. These assistants make invisible data collection visible, support users in configuring privacy settings, where available.
A Two Pressure Numerical Model of Two Fluid Mixing

We present a numerical model of two fluid mixing based on hyperbolic equations having complete state variables (velocity, pressure, temperature) for each fluid. The model is designed for the study of acceleration driven mixing layers in a chunk mix regime dominated by large scale coherent mixing structures. The numerical solution of the model is validated by comparison to the incompressible limit. For the purpose of this comparison, we present a newly obtained analytic solution of the pressure equation for this model and an analytic constraint derived from the asymptotic limit of the compressible pressures, which determines uniquely the incompressible pressure solution. The numerical solution is also validated by a mesh convergence study.
A mutation in Escherichia coli K-12 results in a requirement for thiamine and a decrease in L-serine deaminase activity

Mutants of Escherichia coli K-12 deficient in L-serine deaminase (L-SD) activity have been isolated. These strains required thiamine and grew normally when it was provided. The decrease in L-SD activity caused no obvious metabolic deficiency. A study of revertants and transductants showed that a single mutation was responsible for the thiamine requirement and for the decrease in L-SD activity.
Combining rules and machine learning for extraction of temporal expressions and events from clinical narratives

OBJECTIVE Identification of clinical events (eg, problems, tests, treatments) and associated temporal expressions (eg, dates and times) are key tasks in extracting and managing data from electronic health records. As part of the i2b2 2012 Natural Language Processing for Clinical Data challenge, we developed and evaluated a system to automatically extract temporal expressions and events from clinical narratives. The extracted temporal expressions were additionally normalized by assigning type, value, and modifier. MATERIALS AND METHODS The system combines rule-based and machine learning approaches that rely on morphological, lexical, syntactic, semantic, and domain-specific features. Rule-based components were designed to handle the recognition and normalization of temporal expressions, while conditional random fields models were trained for event and temporal recognition. RESULTS The system achieved micro F scores of 90% for the extraction of temporal expressions and 87% for clinical event extraction. The normalization component for temporal expressions achieved accuracies of 84.73% (expression's type), 70.44% (value), and 82.75% (modifier). DISCUSSION Compared to the initial agreement between human annotators (87-89%), the system provided comparable performance for both event and temporal expression mining. While (lenient) identification of such mentions is achievable, finding the exact boundaries proved challenging. CONCLUSIONS The system provides a state-of-the-art method that can be used to support automated identification of mentions of clinical events and temporal expressions in narratives either to support the manual review process or as a part of a large-scale processing of electronic health databases.
Generic Homonyms in the Colydiinae (Coleoptera: Zopheridae)

New replacement names are proposed: Megapnosaurus Ivie, Slipinski and Wegrzynowicz NEW REPLACEMENT NAME for Syniarsus Raath 1969 (Ceratosauria: Coelophysidae), not Syntarsus Fairmaire 1869 (Coleoptera: Zopheridae: Colydiinae); and Stephaniolus Ivie, Slipinski and Wegrzynowicz NEW REPLACEMENT NAME for Pseudotaphrus Stephan 1989 (Coleoptera: Zopheridae: Colydiinae) not Pseudotaphrus Cossmann 1888 (Mollusca: Rissoiidae). These result in the new combinations Megapnosaurus rhodesiensis (Raath 1961) NEW COMBINATION, Megapnosaurus kayentakatae (Rowe 1989) NEW COMBINATION and Stephaniolus longus (Stephan 1989) NEW COMBINATION.
A novel SAR imaging processing algorithm based on compressive sensing

Synthetic aperture radar (SAR) is a remote sensing system producing images with high resolution. It is not influenced by time and weather. As the increase of resolution and bandwidth, the volume of data augments sharply, bringing great difficulties to store, transmission and processing. Nowadays there is a novel theory named Compressive Sensing (CS) which can recover signal with few samples. Its sample rate is lower than Nyquist rate. In this paper, a novel CS-based SAR imaging algorithm is proposed, in which a random Gaussian measurement matrix, a constructed sparsity matrix and OMP algorithm are employed. The new algorithm can largely reduce the number of samples. The simulation results show the feasibility of the proposed algorithm.
A novel method for preparing liposome with a high capacity to encapsulate proteinous drugs: freeze-drying method.

A simple method for the preparation of liposome with high encapsulation efficiency was developed. A solution of L-asparaginase (A-ase) and a sonicated phospholipid were mixed together and the mixture was freeze-dried. The liposomes were regenerated by adding distilled water, followed by shaking with a Vortex mixer (FD method). Electron microscopic observation revealed that the liposomes prepared by this method have a multilamellar structure. The liposomes had approximately eight times as much encapsulating ability as those prepared by the ordinary thin film method.
Metal Phytoextraction—A Survey of Potential Risks

Metal phytoremediation, and more specifically, phytoextraction, utilizing hyperaccumulators is one of the most exciting new environmental technologies developed over the past decade (Baker et al., 1994; Chaney,1983a; Glass, 1999). Phytoremediation is the use of living plants, known as hyperaccumulators, which absorb unusually large amounts of metals in comparison to other plants (http://www.epa.gov/tio/download/remed/phytoresgude.pdf), for in situ remediation of contaminated soil, sludges, sediments, and groundwater through contaminant removal, degradation, or containment. Phytoextraction refers to the uptake and translocation of metal contaminants in the soil by plant roots into the aboveground portions of the plants. However, for these technologies to gain regulatory and community acceptance, there are risks that must be considered—only a few of which have received even modest examination. Therefore, the focus of this commentary is to explore specific risks associated with phytoextraction. Phytoextraction offers the possibility of addressing an intractable global problem by providing an alternative, cheap, and effective technology that could significantly improve the prospects of cleaning up metal-contaminated sites (Garbisu and Alkorta, 2001; Cunningham and Berti, 1993; Salt et al., 1995). The advantages of phytoextraction over traditional methods of remediation are well known. The many benefits of the technology have been reviewed by Wolfe and Bjornstad (2002). However, few attempts to assess the specific risks of the technology have been reported. Theoretical aspects of the risk analysis process were recently reviewed by Linacre et al. (2003). The primary conclusion of this article was that risks must be identified, quantified, managed, and communicated if phytoextraction is going to find broad public acceptance. Indeed, as a corollary, some of the current concerns related to use of genetically
Antibiotic susceptibility of bacteria infecting total joint arthroplasty sites.

BACKGROUND Currently, there is no consensus regarding the principles of empiric antibiotic treatment of suspected periprosthetic infection following total knee and hip arthroplasties. This study was undertaken to attempt to establish such principles. METHODS We performed a retrospective analysis of 146 patients who had had a total of 194 positive cultures of specimens obtained at the time of a reoperation following a total knee or total hip arthroplasty at one of two institutions. Patient demographic data, comorbid conditions, bacterial species, the antibiotic sensitivity profile, and the postoperative day on which the culture tested positive were recorded. RESULTS Specimens from 110 hips and eighty-four knees were positive on culture. Seventy percent of the infections were classified as chronic; 17%, as acute postoperative; and 13%, as acute hematogenous. The mean time between the operation and the positive culture results was three days. Gram-positive organisms caused the majority of the infections. In the series as a whole, 88% of the bacteria were sensitive to gentamicin; 96%, to vancomycin; and 61%, to cefazolin. The most antibiotic-resistant bacterial strains were from patients for whom prior antibiotic treatment had failed. Acute postoperative infections had a greater resistance profile than did chronic or hematogenous infections. Bacteria isolated from patients with a hematogenous infection had a high sensitivity to both cefazolin and gentamicin. CONCLUSIONS Empiric antibiotic treatment for suspected periprosthetic infection should be guided by the class of the infection and the findings of Gram staining. We believe that, until the final culture results are available, acute hematogenous infections should initially be treated by a combination of cefazolin and gentamicin therapy. All chronic and acute postoperative infections with Gram-positive bacteria and all cases in which a Gram stain fails to identify bacteria should be managed with vancomycin. Infections with Gram-negative bacteria should be managed with a third or fourth-generation cephalosporin. Infections with mixed Gram-positive and Gram-negative bacteria should be managed with a combination of vancomycin and a third or fourth-generation cephalosporin. Furthermore, we believe that if culture results and other confirmatory tests are not positive by the fourth postoperative day, termination of empiric antibiotic therapy should be considered.
High-resolution mapping of DNA hypermethylation and hypomethylation in lung cancer

Changes in DNA methylation patterns are an important characteristic of human cancer. Tumors have reduced levels of genomic DNA methylation and contain hypermethylated CpG islands, but the full extent and sequence context of DNA hypomethylation and hypermethylation is unknown. Here, we used methylated CpG island recovery assay-assisted high-resolution genomic tiling and CpG island arrays to analyze methylation patterns in lung squamous cell carcinomas and matched normal lung tissue. Normal tissues from different individuals showed overall very similar DNA methylation patterns. Each tumor contained several hundred hypermethylated CpG islands. We identified and confirmed 11 CpG islands that were methylated in 80–100% of the SCC tumors, and many hold promise as effective biomarkers for early detection of lung cancer. In addition, we find that extensive DNA hypomethylation in tumors occurs specifically at repetitive sequences, including short and long interspersed nuclear elements and LTR elements, segmental duplications, and subtelomeric regions, but single-copy sequences rarely become demethylated. The results are consistent with a specific defect in methylation of repetitive DNA sequences in human cancer.