Miracle-dz/UniFAR-FTUs huggingface dataset:
A branched extender unit shared between two orthogonal polyketide pathways in an endophyte.

The large polyketide family of natural products impressively demonstrates how nature generates a wealth of diverse and complex compounds from simple building blocks. During the past two decades, a large body of knowledge on the various types of polyketide synthases (PKS) and their modes of action has been gained. In almost all cases, the polyketide backbone is assembled exclusively from malonyl(MCoA) and methylmalonyl-CoA (mMCoA) units, and structural diversity is primarily governed through variations in chain length, processing of the b-keto group, versatile cyclizations, and numerous post-PKS tailoring reactions. While extender units other than MCoA and mMCoA are scarce, several complex polyketides in part composed of substituted malonyl building blocks have recently been discovered. Furthermore, it is known that modular polyketide synthases employ acyltransferase (AT) domains for the selection of the correct extender unit, and elegant studies have demonstrated that it is possible to graft alternative building blocks into complex polyketide backbones through domain swapping, mutagenesis, and mutasynthesis. Thus, with the aim to increase natural polyketide diversity, much effort is currently devoted to enlarging the repertoire of possible biosynthetic building blocks. Apart from ethylmalonyl-CoA and the recently discovered methoxymalonyl and hydroxyand aminomalonyl building blocks, there is evidence for the utilization of longer alkyl residues that account for the propenyl and hexyl side chains of FK506 and thuggacin, respectively. Although isotope labeling experiments have pointed to an a-methylbutyryl-derived extender in the polyoxypeptin pathway, to date the molecular basis for the formation of branched-chain malonyl units has remained fully unknown. Herein we report the discovery and biosynthetic origin of an unprecedented isobutylmalonyl (ibMCoA) extender unit, which is surprisingly employed in two unrelated polyketide pathways in an endophytic Streptomyces species. In the course of evaluating the metabolic capabilities of mangrove endophytes, we have discovered a set of unusual ansa macrolides, named divergolides, which differ markedly in their overall architecture but share an unprecedented branched side chain. This unusual residue suggested that the polyketide backbone has incorporated a novel type of branched extender unit that is likely derived from isobutyrate. Initial attempts to support this hypothesis through stableisotope labeling failed because of the minute amounts of divergolides produced. We eventually succeeded in feeding experiments with [D7]isobutyrate using a highly sensitive HPLC–HRMS (orbitrap) setup. In this way, we identified the expected mass shifts for the major components of the divergolide complex (e.g., divergolide C, 1), thus providing evidence that the extender unit originates from the branched isobutyrate precursor (Figure 1). Surprisingly, a closer inspection of the endophytes metabolome in the presence or absence of [D7]isobutyrate
Short-term traffic flow forecasting method based on interval type-2 fuzzy neural network

Interval type-2 fuzzy logic system cascaded with neural network, interval type-2 fuzzy neural system (IT2FNS), is proposed to handle complicated uncertainties in short-term traffic flow forecasting. A secondary membership function is obtained through fuzzy reasoning. The strong consistent estimates of the unknown parameters of the neural network structure are developed. The secondary membership function with upper and lower limit is utilized to create forecasting interval, which are suitable for handling complicated uncertainties. The efficiency and applicability of this forecasting technique is demonstrated by simulation results.
Financial Applications: Stock Markets

The integration of computer science, computer technology, and finance has given rise to the field known as computational finance. Depending on its involvement in economic theory and its contribution to economic theory, computational finance can be divided into financial engineering and agent-based computational finance. Financial engineering can be defined as the application of computational tools or algorithms to tackle some already existing financial optimization problems, such as forecasting, investment, portfolios, trading, and pricing. These applications usually do not challenge the fundamental principles (assumptions or axioms) from which the optimization problems are derived. They simply take advantage of the increasing computational power to address great technical difficulties inherent in financial optimization, such as nonlinearities and high dimensionality. Compared to financial engineering, agent-based computational finance has a more general goal. It questions the foundations up on which mainstream economics and finance are built, and it reexamines some missing elements, which were absent mainly due to the limited computational resources. Then, by bringing back these elements, agent-based computational finance attempts to provide us with a better understanding of the financial market dynamics. Keywords: agent-based financial markets; computational intelligence; financial engineering; financial agent engineering; financial econometrics; behavioral finance; social simulation; complex systems; emergent properties; adaptation
Characterization of wavefront errors in mouse cranial bone using second-harmonic generation

Abstract. Optical aberrations significantly affect the resolution and signal-to-noise ratio of deep tissue microscopy. As multiphoton microscopy is applied deeper into tissue, the loss of resolution and signal due to propagation of light in a medium with heterogeneous refractive index becomes more serious. Efforts in imaging through the intact skull of mice cannot typically reach past the bone marrow (∼150 μm of depth) and have limited resolution and penetration depth. Mechanical bone thinning or optical ablation of bone enables deeper imaging, but these methods are highly invasive and may impact tissue biology. Adaptive optics is a promising noninvasive alternative for restoring optical resolution. We characterize the aberrations present in bone using second-harmonic generation imaging of collagen. We simulate light propagation through highly scattering bone and evaluate the effect of aberrations on the point spread function. We then calculate the wavefront and expand it in Zernike orthogonal polynomials to determine the strength of different optical aberrations. We further compare the corrected wavefront and the residual wavefront error, and suggest a correction element with high number of elements or multiconjugate wavefront correction for this highly scattering environment.
Minimum Steiner Tree for Automatic SQL Query Generation Applied on a Medical Record Database

The size and complexity of medical record databases makes extracting information challenging. With the tables numbering in thousands, even database analysts have trouble finding important fields and discovering various associations between tables. This paper presents a case study of our initial method of finding minimum Steiner trees in the Epic Clarity Reporting database to solve this problem. In addition, we present a web service architecture that can be used to extend our approach to multiple databases.
Optimal distributed interconnectivity of multi-robot systems by spatially-constrained clustering

A spatially-constrained clustering algorithm is presented in this paper. This algorithm is a distributed clustering approach to fine-tune the optimal distances between agents of the system to strengthen the data passing among them using a set of spatial constraints. In fact, this method will increase interconnectivity among agents and clusters, leading to improvement of the overall communicative functionality of the multi-robot system. This strategy will lead to the establishment of loosely-coupled connections among the clusters. These implicit interconnections will mobilize the clusters to receive and transmit information within the multi-agent system. In other words, this algorithm classifies each agent into the clusters with the lowest cost of local communication with its peers. This research demonstrates that the presented decentralized method will actually boost the communicative agility of the swarm by probabilistic proof of the acquired optimality. Hence, the common assumption regarding the full-knowledge of the agents’ primary locations has been fully relaxed compared to former methods. Consequently, the algorithm’s reliability and efficiency is confirmed. Furthermore, the method’s efficacy in passing information will improve the functionality of higher-level swarm operations, such as task assignment and swarm flocking. Analytical investigations and simulated accomplishments, corresponding to highly-populated swarms, prove the claimed efficiency and coherence.
Boundary Conditions for the Computation of Thermoacoustic Modes in Combustion Chambers

In order to carry out reliable large-eddy simulation or Helmholtz solver computations in aeronautical combustion chambers, it is crucial to impose the right boundary conditions at both the inlet and outlet of the combustion system. This means providing acoustic boundary impedances that take into account all the stages in compressors and turbines. This study is a follow up of works in which the boundary conditions were derived from the isentropic and isenthalpic linearized Euler equations. Specific terms are added to the quasi-one-dimensional linearized Euler equation in order to account for enthalpy jumps induced by the rotor stages of the compressors and turbines. This system of equations also accounts for the entropy–acoustic coupling because, in addition to the continuity and momentum equations, the entropy equation is also considered. The numerical implementation is validated by comparing the numerical results with analytical solutions in several model problems. The effective impedance of the inlet ai.
Depletion of immature B cells during Trypanosoma cruzi infection: involvement of myeloid cells and the cyclooxygenase pathway

The ability of a microorganism to elicit or evade B cell responses represents a determinant factor for the final outcome of an infection. Although pathogens may subvert humoral responses at different stages of B cell development, most studies addressing the impact of an infection on the B cell compartment have focused on mature B cells within peripheral lymphoid organs. Herein, we report that a protozoan infection, i.e. a Trypanosoma cruzi infection, induces a marked loss of immature B cells in the BM, which also compromises recently emigrated B cells in the periphery. The depletion of BM immature B cells is associated with an increased rate of apoptosis mediated by a parasite‐indirect mechanism in a Fas/FasL‐independent fashion. Finally, we demonstrated that myeloid cells play an important role in B cell depletion, since CD11b+ BM cells from infected mice secrete a product of the cyclooxygenase pathway that eliminates immature B cells. These results highlight a previously unrecognized maneuver used by a protozoan parasite to disable B cell generation, limiting host defense and favoring its chronic establishment.
IL6 Receptor Blockade Enhances Chemotherapy Efficacy in Pancreatic Ductal Adenocarcinoma

Inflammation mediated by activation of JAK/STAT signaling is a major cause of chemotherapy resistance in cancer. We studied the impact of selectively blocking the IL6 receptor (IL6R) as a strategy to inhibit IL6-induced STAT activation and to overcome chemoresistance in pancreatic ductal adenocarcinoma (PDAC). To do this, STAT activation was investigated in tumors arising spontaneously in LSL-KrasG12D/+;LSL-Trp53R172H/+;Pdx-1Cre (KPC) mice. Plasma from patients with PDAC was assessed for its ability to activate STAT3/SOCS3 in human monocytes using immunofluorescence microscopy and quantitative gene expression assays. KPC mice and syngeneic mice (wild type and IL6−/−) implanted with KPC-derived cell lines were treated with an IL6R-blocking antibody (anti-IL6R). The impact of treatment on tumor growth in KPC mice and mice with KPC-derived tumor implants was monitored using ultrasonography and calipers, respectively. Tumors were analyzed by IHC to detect changes in STAT activation, tumor viability, and proliferation. We found that STAT3 was the most activated STAT protein in PDAC tumors from KPC mice. Plasma from patients with advanced PDAC stimulated STAT3/SOCS3 activation in human monocytes. In mice, anti-IL6R antibodies targeted Ly6Chi monocytes, inhibited STAT3 activation in tumor cells, and decreased tumor cell proliferation in vivo. IL6R blockade in combination with chemotherapy induced tumor cell apoptosis, tumor regressions, and improved overall survival. Overall, we show that IL6 signaling drives STAT3 activation in tumor cells and mediates chemoresistance in PDAC. Thus, disrupting IL6 signaling using anti-IL6R antibodies holds promise for improving chemotherapy efficacy in PDAC. Mol Cancer Ther; 16(9); 1898–908. ©2017 AACR.
A importância da mediação pedagógica transdisciplinar em EAD que se utiliza de imagens para a busca do conhecimento e da efetivação do aprendizado

A aprendizagem torna-se mais significativa a medida que o estudante detem ferramentas que o auxiliem a assimilar o conteudo, objeto de aprendizado, e que estas sejam motivadoras, inovadoras, de facil e rapido acesso – quando se trata de ambientes virtuais de aprendizagem – e, que viabilizem a busca do conhecimento. Entretanto, para que o aprendizado aconteca, e necessario que a motivacao e o estimulo estejam presentes, ainda mais tratando de EAD. Por isso, e necessario estimular o estudante de cursos virtuais, preparando o ambiente de aprendizagem com imagens e figuras sugestivas. Para isso, e preciso conceber os ambientes virtuais de aprendizagem como cenarios permeados por fluxos em redes ou campos de ressonância, como novos espacos energeticos e vibracionais, permeados por interacoes de natureza biopsicossocial, politico-cultural e espiritual, pois eles precisam ser trabalhados como cenarios vivos onde interagem professores, alunos, instrumentos tecnologicos e digitais que colaboram significativamente para o alcance do objetivo maior da educacao, que e a construcao do conhecimento e, portanto, a aprendizagem. Palavras-chave: Imagens. Transdisciplinaridade. Conhecimento e Ambiente Virtual.
An Assistive Indoor Navigation System for the Visually Impaired in Multi-Floor Environments

This paper presents an innovative wearable system to assist visually impaired people navigate indoors in real time. Our proposed system incorporates state-of-the-art handheld devices from Google's Project Tango and integrates path planner and obstacle avoidance submodules, as well as human-computer interaction techniques, to provide assistance to the user. Our system preprocesses a priori knowledge of the environment extracted from CAD files and spatial information from Google's Area Description Files. The system can then reallocate resources to navigation and human-computer interaction tasks during execution. The system is capable of exploring complex environments spanning multiple floors and has been tested and demonstrated in a variety of indoor environments.
Modelling Domain Knowledge of Speech and Language Therapy with an OWL Ontology and OpenEHR Archetypes

Researchers in the area of health informatics have made significant progress in the standardization of ICT tools to support the management, storage, retrieval and exchange of health-related data. However, the adoption of these advances is largely uneven across different areas. We present a comprehensive knowledge model for the realm of Speech and Language Therapy (SLT), based on an OWL ontology, normalized vocabularies and OpenEHR constructs. This model, validated by several collaborating institutions, is being used as the cornerstone to build a comprehensive framework with supporting tools for the different people involved in SLT, including therapists, patients and their relatives, and students.
Dual Screening

Summary. We discuss the problem of screening a general population for characteristics such as HIV or drug use. Our main approach is Bayesian, which allows for the incorporation of prior information about parameters. In the particular problem we consider, there is currently no information in the data for estimating the sensitivity of the screening test, and consequently, the prevalence of the characteristic among screened negatives cannot be estimated from the collected data alone. Our inferences are straightforward to obtain using Gibbs sampling techniques, and they are valid for large or small samples and for arbitrary prevalence or accuracy of screening tests. We also develop the maximum‐likelihood approach using the EM algorithm.
Multilabel feature selection: A comprehensive review and guiding experiments

Feature selection has been an important issue in machine learning and data mining, and is unavoidable when confronting with high‐dimensional data. With the advent of multilabel (ML) datasets and their vast applications, feature selection methods have been developed for dimensionality reduction and improvement of the classification performance. In this work, we provide a comprehensive review of the existing multilabel feature selection (ML‐FS) methods, and categorize these methods based on different perspectives. As feature selection and data classification are closely related to each other, we provide a review on ML learning algorithms as well. Also, to facilitate research in this field, a section is provided for setup and benchmarking that presents evaluation measures, standard datasets, and existing software for ML data. At the end of this survey, we discuss some challenges and open problems in this field that can be pursued by researchers in future. WIREs Data Mining Knowl Discov 2018, 8:e1240. doi: 10.1002/widm.1240
Olfactory Derived Stem Cells Delivered in a Biphasic Conduit Promote Peripheral Nerve Repair In Vivo

Peripheral nerve injury presents significant therapeutic challenges for recovery of motor and sensory function in patients. Different clinical approaches exist but to date there has been no consensus on the most effective method of treatment. Here, we investigate a novel approach to peripheral nerve repair using olfactory derived stem (ONS) cells delivered in a biphasic collagen and laminin functionalized hyaluronic acid based nerve guidance conduit (NGC). Nerve regeneration was studied across a 10‐mm sciatic nerve gap in Sprague Dawley rats. The effect of ONS cell loading of NGCs with or without nerve growth factor (NGF) supplementation on nerve repair was compared to a cell‐free NGC across a variety of clinical, functional, electrophysiological, and morphologic parameters. Animals implanted with ONS cell loaded NGCs demonstrated improved clinical and electrophysiological outcomes compared to cell free NGC controls. The nerves regenerated across ONS cell loaded NGCs contained significantly more axons than cell‐free NGCs. A return of the nocioceptive withdrawal reflex in ONS cell treated animals indicated an advanced repair stage at a relatively early time point of 8 weeks post implantation. The addition of NGF further improved the outcomes of the repair indicating the potential beneficial effect of a combined stem cell/growth factor treatment strategy delivered on NGCs. Stem Cells Translational Medicine 2017;6:1894–1904
The Influence of a Community Pharmacy Automatic Prescription Refill Program on Medicare Part D Adherence Metrics

BACKGROUND: The Centers for Medicare & Medicaid Services (CMS) include measures of medication adherence within its Medicare Part D star ratings program. These adherence measures have motivated the development of new methods to improve patient adherence. Automatic prescription refill programs in community pharmacies are an intervention that has seen widespread adoption in recent years. These automatic refill programs anticipate and initiate prescription refills on a standardized, recurrent basis. As a result, prescription refills may be filled before a patient typically might initiate a refill. This study measures the effect of an automatic prescription refill program on 3 adherence metrics used by CMS within Medicare Part D star ratings. OBJECTIVE: To compare the value of Medicare Part D adherence metrics for an automatic prescription refill program relative to standard prescription refills. METHODS: Prescription dispensing data (January 1, 2014-December 31, 2014) from a chain of 29 pharmacies in a midwestern state were used to conduct this analysis. A post-only, quasi-experimental design separated patients into automatic and standard prescription refill cohorts. Refill adherence was calculated using proportion of days covered (PDC) for each of the 3 adherence metrics used by CMS for statins, renin angiotensin aldosterone system antagonists (RASA), and noninsulin diabetes medications. The adherence rate was defined as the proportion of patients with a PDC ± 80%. Inclusion criteria for patients followed the Pharmacy Quality Alliance technical specifications. Chi-square analysis and multiple logistic regression were used to examine differences in PDC > 80% between the 2 study cohorts. RESULTS: There were 1,018, 1,006, and 368 patients for the automatic refill cohort and 3,928, 3,409, and 1,207 patients for the standard refill cohort in the statin, RASA, and diabetes adherence metrics, respectively. The mean age [SD] of patients was between 79.2 [±8.5] and 80.8 [±9.9] years across all cohorts. Patients in the automatic prescription refill program tended to take less than 1 additional chronic medication compared with the standard refill prescription cohort. The proportion of adherent patients ranged from 73.6% to 76.4% for standard refill cohorts and 77.5% to 83.6% for automatic refill cohorts. Differences between study cohorts were statistically significant for all the adherence metrics based on the chi-square test (P < 0.05). Patients enrolled in the automatic prescription refill program were more likely to be adherent to the statin (OR = 1.51, 95% CI = 1.26-1.82), RASA (OR = 1.20, 95% CI = 1.01-1.42), and diabetes (OR = 1.44, 95% CI = 1.06-1.96) metrics. CONCLUSIONS: Patients enrolled in the automatic prescription refill program were more likely to be adherent to their medications. Enrollment in automatic prescription refill programs could be encouraged by health plans and pharmacists because of their potential effect on Medicare Part D star ratings.
On the behavior of surface electromyographic variables during the menstrual cycle

The goal of this work is to study the behavior of electromyographic variables during the menstrual cycle. Ten female volunteers (24.0 ± 2.8 years of age) performed fatiguing isometric contractions, and electromyographic signals were measured on the biceps brachii in four phases of the menstrual cycle. Adaptations of classical algorithms were used for the estimation of the root mean square (RMS) value, absolute rectified value (ARV), mean frequency (MNF), median frequency (MDF), and conduction velocity (CV). The CV estimator had a higher (p = 0.002) rate of decrease at the end of the follicular phase and at the end of the luteal phase. The MDF (p = 0.002) and MNF (p = 0.004) estimators had a higher rate of decrease at the beginning of the follicular phase and at the end of the luteal phase. No significant differences between phases of the menstrual cycle were detected with the ARV and RMS estimators (p > 0.05). These results suggest that the behavior of the muscles in women presents different characteristics during different phases of the menstrual cycle. In particular, women were more susceptible to fatigue at the end of the luteal phase.