Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of drug-metabolizing enzyme activity in vivo: pharmacokinetic and statistical issues.

ethnic dia erences in the in vivo metabolism of drugs and other xenobiotics. The key issues in assessing drug-metabolizing enzyme activity in vivo include separation (with the aid of genotyping) of risk and exposure; choice of the best experimental index to use, the selection and number of subjects for study, and the use of objective criteria for assessing multimodality in frequency distributions of in vivo data. To avoid misinterpretation and overinterpretation of data, it is essential to have a good understanding of the pharmacokinetic basis of indirect measures of in vivo drugmetabolizing activity, and of appropriate statistical procedures for the analysis of frequency distributions. Pharmacokinetic basis for using indirect induces of drug metabolism Partial intrinsic clearance In theory, the closest in vivo measure of the activity of the gene product, that is the enzyme, ea ecting a particular metabolic pathway, i, of a drug is its intrinsic clearance down that route. This partial intrinsic clearance is de® ned in terms of unbound drug concentration in plasma ( CLu int, mi ), and can be viewed as the quotient of the apparent V max and K m of the drug with respect to the enzyme (Wilkinson and Shand 1975). Calculation of partial intrinsic clearance after oral drug administration requires measurement of the urinary recovery of the metabolite [Ae(mi) po ], the AUC (total area under the plasma drug concentration± time curve), plasma binding (indicated by fu, the free fraction) and renal clearance ( CL R ) of the
Viral Vaccines for Dengue: The Present and the Future

Infection with dengue viruses, of which there are four antigenically distinct serotypes, has re- emerged as a significant global public health threat. Sequential infection in areas of hyperendemicity, where multiple serotypes co-circulate, has the potential to trigger life-threatening disease. Therefore, a safe and effective dengue vaccine must be 'tetravalent' capable of providing solid and long-lasting immunity to all four serotypes. The development of a vaccine against dengue has been a high priority of the World Health Organization (WHO) for decades. Currently, six different virus-based vaccines are in various stages of development. Two of these are traditional tissue culture-based live attenuated vaccines whereas the remaining four are chimeric recombinant vaccine viruses developed using infectious clone technology. In all these instances, the vaccine viruses are monovalent in that each one is specific to one dengue serotype. A tetravalent dengue vaccine is based on producing vaccine formulations by mixing all four monovalent vaccine viruses. Recent studies in both monkeys and man have shown that such tetravalent formulations can elicit unbalanced immune responses due to the phenomenon of viral interference. While efforts are under way to optimize the tetravalent formulations, the inherent risk of viral interference associated with the current strategy of producing tetravalent dengue vaccine warrants investigation of other recombinant viral systems that eliminate this risk, especially the replication-defective adenovirus- based vector system that may permit the creation of a single vaccine vector capable of conferring tetravalent protection.
Sufficient Condition for Pooling Data from different Distributions

We consider the problems arising from using sequences of experiments to discover the causal structure among a set of variables, none of whom are known ahead of time to be an “outcome”. In particular, we present various approaches to resolve conflicts in the experimental results arising from sampling variability in the experiments. We provide a sufficient condition that allows for pooling of data from experiments with different joint distributions over the variables. Satisfaction of the condition allows for more powerful independence tests that may resolve some of the conflicts in the experimental results. The pooling condition has its own problems, but should – due to its generality – be informative to techniques for meta-analysis.
Multidimensional proteomic analysis of photosynthetic membrane proteins by liquid extraction‐ultracentrifugation‐liquid chromatography‐mass spectrometry

The membrane protein components of photosystem I (PSI) and II (PSII) from different species were prefractionated by liquid extraction and sucrose gradient ultracentrifugation and subsequently analyzed by reversed‐phase high‐performance liquid chromatography‐electrospray ionization‐mass spectrometry (RP‐HPLC‐ESI‐MS) using poly‐(styrene‐divinylbenzene)‐based monolithic capillary columns. The analytical method was shown to be very flexible and enabled the identification of antenna proteins as well as most of the proteins of the reaction center from PSI and PSII in various plant species with few RP‐HPLC‐ESI‐MS analyses necessitating only minor adaptations in the gradients of acetonitrile in 0.05% aqueous trifluoroacetic acid. The membrane proteins, ranging in molecular mass (Mr) from 4196 (I protein) to more than 80 000 (PSI A/B) as well as isoforms were identified on the basis of their intact Mr and comparison with Mr deduced from known DNA or protein sequences. High quality mass spectra enabled the identification and quantitation of the nonphosphorylated and phosphorylated reaction center subunits D1, D2, and CP43 of PSII, containing five to seven membrane‐spanning α‐helices. Because of its high flexibility and suitability for proteins having a very wide range of Mr and hydrophobicities, the method is generally applicable to the analysis of complex mixtures of membrane proteins.
A Comparison of Ratios and Data Envelopment Analysis: Efficiency Assessment of Taiwan Public Listed Companies

The need to assess business firm’s efficiency is important for all players involved in a business. Efficiency assessment has previously been conducted using financial ratio analysis. However, it failed when simultaneously considering multiple inputs and outputs. Because of this difficulty the data envelopment analysis (DEA) is proposed as an alternative approach for handling multiple inputs and outputs. This study introduces financial ratio analysis and the DEA model for assessing performance and uses panel data of 24 Taiwan public listed companies to demonstrate the merit of the model in assessing efficiency with quantitative guidance for policy formulation.
Evidence for a remodelling of DNA-PK upon autophosphorylation from electron microscopy studies

The multi-subunit DNA-dependent protein kinase (DNA-PK), a crucial player in DNA repair by non-homologous end-joining in higher eukaryotes, consists of a catalytic subunit (DNA-PKcs) and the Ku heterodimer. Ku recruits DNA-PKcs to double-strand breaks, where DNA-PK assembles prior to DNA repair. The interaction of DNA-PK with DNA is regulated via autophosphorylation. Recent SAXS data addressed the conformational changes occurring in the purified catalytic subunit upon autophosphorylation. Here, we present the first structural analysis of the effects of autophosphorylation on the trimeric DNA-PK enzyme, performed by electron microscopy and single particle analysis. We observe a considerable degree of heterogeneity in the autophosphorylated material, which we resolved into subpopulations of intact complex, and separate DNA-PKcs and Ku, by using multivariate statistical analysis and multi-reference alignment on a partitioned particle image data set. The proportion of dimeric oligomers was reduced compared to non-phosphorylated complex, and those dimers remaining showed a substantial variation in mutual monomer orientation. Together, our data indicate a substantial remodelling of DNA-PK holo-enzyme upon autophosphorylation, which is crucial to the release of protein factors from a repaired DNA double-strand break.
Interleukin-17 A during Local and Systemic Staphylococcus aureus-Induced Arthritis in Mice

Interleukin-17A during Local and Systemic Staphylococcus aureus-Induced Arthritis in Mice Louise Henningsson,* Pernilla Jirholt, Catharina Lindholm, Tove Eneljung, Elin Silverpil, Yoichiro Iwakura, Anders Linden, and Inger Gjertsson Department of Rheumatology and Inflammation Research and Department of Internal Medicine/Respiratory Medicine and Allergology, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden, and Center for Experimental Medicine and Systems Biology, Institute of Medical Science, University of Tokyo, and Core Research for Evolutional Science and Technology (CREST), Tokyo, Japan
Evaluation of Virtual Screening as a Tool for Chemical Genetic Applications

A collection of over 50,000 functionally annotated drugs, clinical candidates, and endogenous ligands was docked in silico against nine binding sites from seven protein targets, representing diverse function and structure, namely the sulfotransferases SULT1E1 and SULT1A3, the histone methyltransferase EHMT1, the histone acetyltransferase MYST3, and the nuclear hormone receptors ERalpha, PPARgamma, and TRbeta. For 5 of the 9 virtual screens, compounds that docked best to the receptors clearly recapitulated known biological functions of the genes or identified novel biology subsequently validated in a separate experimental study. In two cases, the hit list indicated some relevant but isolated biological functions which would probably have been ignored a priori, and selected compounds were completely unrelated to gene function for the last two virtual screens. This study demonstrates that virtual screening of pharmacologically annotated compound libraries can be used to derive target biology.
Trials and tribulations of skin iontophoresis in therapeutics

Iontophoresis is a method of non‐invasive transdermal drug delivery based on the transfer of charged molecules using a low‐intensity electric current. Both local and systemic administration are possible; however, the skin pharmacokinetics of iontophoretically delivered drugs is complex and difficult to anticipate. The unquestionable theoretical advantages of the technique make it attractive in several potential applications. After a brief review of the factors influencing iontophoresis, we detail the current applications of iontophoresis in therapeutics and the main potential applications under investigation, including systemic and topical drugs and focusing on the treatment of scleroderma‐related ulcerations. Finally, we address the issue of safety, which could be a limitation to the routine clinical use of iontophoresis.
FFT and Convolution Performance in Image Filtering on GPU

Many contemporary visualization tools comprise some image filtering approach. Since image filtering approaches are very computationally demanding, the acceleration using graphics-hardware (GPU) is very desirable to preserve interactivity of the main visualization tool itself. In this article we take a close look on GPU implementation of two basic approaches to image filtering -fast Fourier transform (frequency domain) and convolution (spatial domain). We evaluate these methods in terms of the performance in real time applications and suitability for GPU implementation. Convolution yields better performance than fast Fourier transform (FFT) in many cases; however, this observation cannot be generalized. In this article we identify conditions under which the FFT gives better performance than the corresponding convolution and we assess the different kernel sizes and issues of application of multiple filters on one image
No Packet Left Behind: Avoiding Starvation in Dynamic Topologies

Backpressure schemes are known to stabilize stochastic networks through the use of congestion gradients in routing and resource allocation decisions. Nonetheless, these schemes share a significant drawback, namely, the delay guarantees are obtained only in terms of average values. As a result, arbitrary packets may never reach their destination due to both the starvation and last-packet problems. These problems occur because in backpressure schemes, packet scheduling needs a subsequent stream of packets to produce the required congestion gradient for scheduling. To solve these problems, we define a starvation-free stability criterion that ensures a repeated evacuation of all network queues. Then, we introduce SF-BP, the first backpressure routing and resource allocation algorithm that is starvation-free stable. We further present stronger per-queue service guarantees and provide tools to enhance weak streams. We formally prove that our algorithm ensures that all packets reach their destination for wide families of networks. Finally, we verify our results by extensive simulations using challenging topologies as well as random static and dynamic topologies.
A revisit to voltage partitioning problem

We revisit voltage partitioning problem when the mapped voltages of functional units are predetermined. If energy consumption is estimated by formulation E=CV2,a published work claimed this problem was NP-hard. We clarify that it is polynomial solvable, then propose an optimal algorithm, its time complexity is O(nk+k2d) which is best so far, where n, k, and d are respectively the numbers of functional units, available supply voltages, and voltages employed in the final design. In reality, considering leakage power the energy-voltage curve is not simply monotonically increasing and there is still no optimal polynomal polynomial time algorithm. However, under the assumption that energy-voltage curve is quasiconvex, which is also a good approximation to actual situation, the optimal solution can be got in time O(nk2). Experimental results show that our algorithms are more efficient than previous works.
Adhesion of 10-MDP containing resin cements to dentin with and without the etch-and-rinse technique

PURPOSE This study evaluated the adhesion of 10-MDP containing self-etch and self-adhesive resin cements to dentin with and without the use of etch-and-rinse technique. MATERIALS AND METHODS Human third molars (N=180) were randomly divided into 6 groups (n=30 per group). Conventional (Panavia F2.0, Kuraray-PAN) and self-adhesive resin cements (Clearfil SA, Kuraray-CSA) were bonded to dentin surfaces either after application of 3-step etch-and-rinse (35% H3PO4 + ED Primer) or two-step self-etch adhesive resin (Clearfil SE Bond). Specimens were subjected to shear bond strength test using the universal testing machine (0.5 mm/min). The failure types were analyzed using a stereomicroscope and quality of hybrid layer was observed under a scanning electron microscope. The data (MPa) were analyzed using two-way ANOVA and Tukey's tests (α=.05). RESULTS Overall, PAN adhesive cement showed significantly higher mean bond strength (12.5 ± 2.3 - 14.1 ± 2.4 MPa) than CSA cement (9.3 ± 1.4 - 13.9 ± 1.9 MPa) (P<.001). Adhesive failures were more frequent in CSA cement groups when used in conjunction with two-step self-adhesive (68%) or no adhesive at all (66%). Hybrid layer quality was inferior in CSA compared to PAN cement in all conditions. CONCLUSION In clinical situations where bonding to dentin substrate is crucial, both conventional and self-adhesive resin cements based on 10-MDP can benefit from etch-and-rinse technique to achieve better quality of adhesion in the early clinical period.
Spatiotemporal response of the water cycle to land use conversions in a typical hilly–gully basin on the Loess Plateau, China

The hydrological effects of the “Grain for Green” project (GFGP) on the Loess Plateau have been extensively debated due to the complexity of the water system and its multiple driving factors. The aim of this study was to investigate the response of the hydrological cycle to the GFGP measures based in a case study of the Yanhe Basin, a typical hilly–gully area on the Loess Plateau of China. First, we analyzed the land use and land cover (LULC) changes from 1990 to 2010. Then, we evaluated the effects of LULC changes and sloping land conversion on the main hydrological components in the basin using the Soil and Water Assessment Tool (SWAT). The results indicated that cropland exhibited a decreasing trend, declining from 40.2 % of the basin area in 1990 to 17.6 % in 2010, and that the woodland and grassland areas correspondingly increased. With the land use changes from 1990 to 2010, the water yield showed a decreasing trend which was mainly due to decrease in surface runoff. In contrast, evapotranspiration (ET) showed an increasing trend over the same period, resulting in a persistent decrease in soil water. The conversion of sloping cropland to grassland or woodland exerted negative effects on water yield and soil water. Compared with the land use condition in 2010, the negative effects were most evident where cropland with a slope ≥ 15 was converted to woodland, with decreases in surface runoff and soil water of 17.1 and 6.4 %, respectively. These results suggest that the expansive reforestation on sloping land in the loess hilly–gully region decreased water yield and increased ET, resulting in reduced soil water. The results of this study can be used to support sustainable land use planning and water resource management on the Loess Plateau in China.
Reinforcement Learning for Port-Hamiltonian Systems

Passivity-based control (PBC) for port-Hamiltonian systems provides an intuitive way of achieving stabilization by rendering a system passive with respect to a desired storage function. However, in most instances the control law is obtained without any performance considerations and it has to be calculated by solving a complex partial differential equation (PDE). In order to address these issues we introduce a reinforcement learning (RL) approach into the energy-balancing passivity-based control (EB-PBC) method, which is a form of PBC in which the closed-loop energy is equal to the difference between the stored and supplied energies. We propose a technique to parameterize EB-PBC that preserves the systems's PDE matching conditions, does not require the specification of a global desired Hamiltonian, includes performance criteria, and is robust. The parameters of the control law are found by using actor-critic (AC) RL, enabling the search for near-optimal control policies satisfying a desired closed-loop energy landscape. The advantage is that the solutions learned can be interpreted in terms of energy shaping and damping injection, which makes it possible to numerically assess stability using passivity theory. From the RL perspective, our proposal allows for the class of port-Hamiltonian systems to be incorporated in the AC framework, speeding up the learning thanks to the resulting parameterization of the policy. The method has been successfully applied to the pendulum swing-up problem in simulations and real-life experiments.
Effects of Population Structure and Sex on Association Between Serotonin Receptors and Drosophila Heart Rate

As a first step toward population and quantitative genetic analysis of neurotransmitter receptors in Drosophila melanogaster, we describe the parameters of nucleotide variation in three serotonin receptors and their association with pupal heart rate. Thirteen kilobases of DNA including the complete coding regions of 5-HT1A, 5-HT1B, and 5-HT2 were sequenced in 216 highly inbred lines extracted from two North American populations in California and North Carolina. Nucleotide and amino acid polymorphism is in the normal range for Drosophila genes and proteins, and linkage disequilibrium decays rapidly such that haplotype blocks are typically only a few SNPs long. However, intron 1 of 5-HT1A consists of two haplotypes that are at significantly different frequencies in the two populations. Neither this region of the gene nor any of the common amino acid polymorphisms in the three loci associate with either heart rate or heart rate variability. A cluster of SNPs in intron 2 of 5-HT1A, including a triallelic site, do show a highly significant interaction between genotype, sex, and population. While it is likely that a combination of weak, complex selection pressures and population structure has helped shape variation in the serotonin receptors of Drosophila, much larger sampling strategies than are currently adopted in evolutionary genetics will be required to disentangle these effects.
Classifying Product Reviews from Balanced Datasets for Sentiment Analysis and Opinion Mining

The Online reviews provided for a product enables web user to make decisions appropriately. These reviews may be positive, negative or neutral in nature. Analyzing and classifying such product reviews have attracted reasonable interest. It has become quite hard to make decisions since we aren't able to obtain the decisions quickly. Hence it is required to classify the reviews from balanced data sets for analysis and opinion mining of any applications. The reason for considering balanced data sets is that the decision will not be biased on the category of reviews considered. We have carried out investigations using similarity measures to categorize the reviews correctly. Experiments reveal that the reviews that were mixed in nature were able to be grouped correctly.
Base Station clustering in heterogeneous network with finite backhaul capacity

This paper considers the Base Station (BS) clustering in a downlink heterogeneous network with finite backhaul capacity. We consider a tree structure network where each BS has only one incoming link and several outgoing links. The objective is to maximize the minimum rate among all users while satisfying the backhaul capacity constraint and the per-BS power constraint. We propose an algorithm that combines the bisection and the Alternating Direction Method of Multipliers (ADMM). The bisection search is conducted for the minimum rate. When it is given, we use ADMM to check the feasibility of the network while obeying the backhaul and power constraints. There are two steps involved in ADMM: i) a second order conic programming is used to calculate the beamformer; ii) a closed-form rule is used to determine the BS clustering. Due to the non-convexity and the non-smoothness, ADMM is not guaranteed to solve the problem. Therefore, we propose a revise step to further improve the performance. The simulation results show that the proposed algorithm outperforms the heuristic method and the revise step does improve the performance in all considered scenarios.
How do resting state changes in depression translate into psychopathological symptoms? From ‘Spatiotemporal correspondence’ to ‘Spatiotemporal Psychopathology’

Purpose of review To review the recent findings in resting-state activity in major depressive disorder (MDD) and link them to psychopathological symptoms. Recent findings MDD shows changes in resting state functional connectivity (rsFC) mainly within the default-mode network with a focus on especially the perigenual anterior cingulate cortex. rsFC in perigenual anterior cingulate cortex is abnormally high in MDD and decreased in the lateral prefrontal cortex with the central executive network (CEN). rsFC in other networks like the salience network, including the insula, amygdala, and supragenual anterior cingulate cortex and the sensorimotor network is also affected in MDD. Summary Resting-state activity in MDD shows abnormal topographical and spatiotemporal pattern. The spatiotemporal alterations in resting state may translate into corresponding spatiotemporal changes underlying the sensorimotor, affective, and cognitive functions, and thus, the various symptoms. Such spatiotemporal correspondence between resting state changes and psychopathological symptoms may make necessary the development of what I describe as ‘Spatiotemporal Psychopathology’.