Miracle-dz/UniFAR-FTUs huggingface dataset:
Class 1 integron element in Thai Acinetobacter baumannii reveals a linkage to the European clone I

BACKGROUND: Class 1 integron element is innate to most of the multidrug resistant Acinetobacter baumannii and its spread is common among international clones worldwide. The aim of this study was to document the presence of bla VEB-1 harboring class 1 integron element and its gene cassettes in Thai A. baumannii in relation to A. baumannii European clone I, AYE strain. MATERIALS AND METHODS: Thirty seven carbapenem resistant A. baumannii isolates identified in routine microbiology laboratory of Siriraj Hospital, Bangkok were studied. The dot blot hybridization was performed to detect class 1 integron element integrase gene. PCR was used to amplify bla VEB-1 , arr2 , cmlA , bla OXA-10 resistance cassettes, and variable region of class 1 integron element. bla VEB-1 gene was localized by southern blot hybridization. RESULTS: The prevalence of class 1 integron element was 86.48% in the isolates studied. The bla VEB-1 was present in 7 isolates however the location of bla VEB-1 gene was different in different isolate. Four isolates (Ab03-168, Ab04-28, Ab08-20, and Ab08-22) harbored calss 1 integron element variable region sized 5.5 kb as described in strain AYE. However, bla VEB-1 was only amplified from Ab03-168. The cassette organization in this isolate was 5’CS-aadB -bla VEB-1 - arr2 - cmlA-bla OXA- 10 -aadA1-3’CS. The class 1 integron element similar to the element identified in genomic resistance island, AbaRI of European clone I, AYE was identified in Thai A. baumannii . CONCLUSIONS: bla VEB-1 harboring class 1 integron element with minor cassette variation was identified in Thai A. baumanni isolate which might suggest the spread of this resistant cassette or the spread of the European clone I in Thailand. Monitoring of the global spread of multi-resistant A. baumannii is mandatory to control the spread of resistant genes and this multi-resistant pathogen. DOI: http://dx.doi. org/10.3126/ijim.v1i1. 6715 Int J Infect Microbiol 2012;1(1):24-28
Rejoinder

Romer, C. D. , and Romer, D. H. (2000), “Federal Reserve Information and the Behavior of Interest Rates,” The American Economic Review, 90, 429–457. [510] Rossi, B. (2013), “Advances in Forecasting Under Model Instability,” in Handbook of Economic Forecasting, eds. G. Elliottand A. Timmermann, (Vol. 2B), pp. 1203–1324, Amsterdam: Elsevier Publications. [513] Rossi, B. , and Sekhposyan, T. (2011), “Forecast Optimality Tests in the Presence of Instabilities,” mimeo, Duke University. [510] ——— (2013a), “Alternative Tests for Correct Specification of Conditional Forecast Densities,” mimeo, Universitat Pompeu Fabra and Texas A&M. [512,513] ——— (2013b), “Conditional Predictive Density Evaluation in the Presence of Instabilities,” Journal of Econometrics, 177, 199–212. [513] West, K. D. , and McCracken, M. W. (1998), “Regression-Based Tests of Predictive Ability,” International Economic Review, 39, 817– 840. [510]
Comment

Let me begin by congratulating the authors on the substantial progress that they have made on an important and challenging problem in classification. They provide penetrating insight into the reasons why the most obvious methods for constructing confidence intervals for the test error have poor coverage properties, and propose an innovative and effective solution that can be readily adopted in practice. The focus of the article is on linear classifiers. Although this is certainly an important family, it of course has limitations in terms of the complexity of the boundaries that can be handled. Here we make a first attempt at extending the scope of the methodology presented in the article to other types of classifiers.
Data Mining and Uncertain Reasoning

not have a speci c condition. Is a test result really accurate? How can the accuracy be quanti ed and compared? This book presents a comprehensive discussion of the accuracy of diagnostic tests. The book comprises two parts. Part I, “Basic Concepts and Methods,” begins by de ning the measures of diagnostic accuracy, such as sensitivity, speci city, and the receiver operating curve (ROC). This curve plots sensitivity, or the ability to detect a condition, versus its false positive rate (FPR). The next chapter deals with the design of diagnostic accuracy studies. There follow chapters on estimation and hypothesis testing, the comparison of the accuracy of two different diagnostic tests for the same condition, sample size calculations, and the use of meta-analyses. Part II of the book presents more advanced methods. Chapter 8 is concerned with the regression methods that quantify the effects of patient characteristics on the diagnostic accuracy of a test. Chapter 9 deals with correlated ROC curves, which might arise if there were multiple tests on the same patient or multiple readers for the same test result. The related topic of veri cation bias is the subject of Chapter 10, which gives methods for correcting results. Chapter 11 deals with correction when there is no good standard of comparison for accuracy. The  nal chapter presents statistical methods for meta-analysis. The medical value of this statistical methodology should be apparent to anyone. This material is not extensively covered in medical statistics textbooks. The comprehensive new textbook by Feinstein (2001), reported by Ziegel (2003), contains just a single chapter on diagnostic medicine. A typical book on biomedical statistics, the large new edition of the text by Woolson and Clarke (2002), reported by Ziegel (2003), does not directly discuss diagnostic testing.
Comment

The basic topic of this article is still timely and important and the article makes a welcome contribution. It is still the case that the fundamental role of prediction is not sufficiently emphasized in both statistical research and education. See Kass (2011) for a great discussion of how “estimation” is emphasized at the expense of modeling and prediction in statistical education. Seymour Geisser was my adviser, so clearly I was inculcated with this attitude at an early age. However, all of my subsequent statistical endeavors have reinforced this viewpoint. We collect data and learn to decide how to act and our actions are based on predictions about the consequences. I cannot see how this does not cover all applications. In some applications, a stage of the investigation may be sufficiently far removed from our ultimate decision that the predictive nature is not apparent. For example, clustering is a popular technique that is not obviously predictive in motivation. Why do we cluster? If we can uncover a group structure, ultimately, this may help us to predict better. If households cluster into groups, maybe our model for how they respond to a targeted promotion should take that into account. Even in informal investigations (undirected in machine learning lingo), the ultimate goal is prediction. In this regard, you have to give the machine learning/computer science communities credit for keeping their eye on the ball. Directed machine learning just means prediction and much of the research in this area is on this topic. The current article very correctly notes that while some of the best research in this area has an “algorithmic” flavor, there is still, and always will be, an important role for more traditional statistical modeling. Note that modern Bayesian work captures the best of both worlds by entertaining models with variable dimension as in the classic Escobar and West (1995). Much of my own recent research has been in this vein in that we try to use a model-based approach to tree-based methods (Chipman, George, and McCulloch 2010). We try to use a full Bayesian model to infer tree structures, allowing for the possibility that size of the tree may depend on the data. For a fantastic reference on modern machine learning with a statistical modeling bent, I recommend Murphy (2012). A major advantage of the Bayesian approach is that it lends itself very naturally to prediction. In Geisser (1971), Seymour says
Comment

International Warfarin Pharmacogenetics Consortium (2009), “Estimation of the Warfarin Dose With Clinical and Pharmacogenetic Data,” The New England Journal of Medicine, 360, 753–764. [1530,1531] Murphy, S. (2005), “A Generalization Error for Q-Learning,” Journal of Machine Learning Research, 6, 1073–1097. [1530] Robins, J. M. (2004), “Optimal Structural Nested Models for Optimal Sequential Decisions,” in Proceedings of the Second Seattle Symposium onBiostatistics, eds. D. Lin, and P.Heagerty, NewYork: Springer-Verlag, pp. 189–326. [1530,1531] Zhao, Y. , Zeng, D. , Rush, A. , and Kosorok, M. (2012), “Estimating Individual Treatment Rules UsingOutcomeWeighted Learning,” Journal of the American Statistical Association, 107, 1106–1118. [1530]
Magainins, a class of antimicrobial peptides from Xenopus skin: isolation, characterization of two active forms, and partial cDNA sequence of a precursor

Abstract A family of peptides with broad-spectrum antimicrobial activity has been isolated from the skin of the African clawed frog Xenopus laevis. It consists of two closely related peptides that are each 23 amino acids and differ by two substitutions. These peptides are water soluble, nonhemolytic at their effective antimicrobial concentrations, and potentially amphiphilic. At low concentrations they inhibit growth of numerous species of bacteria and fungi and induce osmotic lysis of protozoa. The sequence of a partial cDNA of the precursor reveals that both peptides derive from a common larger protein. These peptides appear to represent a previously unrecognized class of vertebrate antimicrobial activities.
Comment

strategic network formation are still in their infancy (Christakis et al. 2010; Mele 2011; Chandrasekhar and Jackson 2012; Leung 2013). The very important lesson that we should take from the analysis of Goldsmith-Pinkham and Imbens is that accounting for the endogeneity of relationships in analyses of peer effects is feasible, and can provide substantial new insights, for example, into unobserved characteristics that might correlate both with behavior and friendship formation. The specifications that are needed to properly model both network formation and peer effects require careful additional analysis in context, and provide us with a rich agenda going forward.
Pattern Recognition Algorithms for Data Mining

possible to address. In risk management, knowledge from several disciplines is necessary: finance, statistics, probability, and computer science. This is a book on simulation, where the necessary background from other disciplines is reviewed with applications to risk management in mind. The prerequisites are an undergraduate course in probability and the basic notions from finance. Although it covers the basics of simulation and risk management, the book also provides insights into current academic research. An example of this is the use of extreme value theory in the computation of valueat-risk. I consider this book to be a very useful addition to the literature on quantitative risk management.
Percutaneous Absorption of Parathion and Its Metabolites, Paraoxon and p-Nitrophenol, Administered Alone or in Combination: In Vitro Flow-Through Diffusion Cell Studies

Abstract The percutaneous absorption of individual pesticides has been well studied. However, the absorption of a mixture of pesticides and decomposition products or metabolites has not received attention. The percutaneous absorption of parathion (PA) relative to its two metabolites, paraoxon (PO) and p -nitrophenol (PNP), was studied in vitro using weanling pig skin in a flow-through diffusion cell system. Concentrations of 4, 40, or 400 μg/cm 2 of PA, PO, PNP, PA + PO (1:1), PA + PNP (1:1), and PO + PNP (1:1) in ethanol were applied topically. Environmental conditions such as air and perfusate temperature (37°C), relative humidity (60%), and flow rate (4 ml/hr) were controlled, and Kreb′s-Ringer bicarbonate buffer with 4.5% bovine serum albumin media was used. The total absorption of PA, PO, and the mixed compounds increased as the dose increased, whereas the absorption efficiency (percentage of applied dose absorbed) decreased as the doses increased. For the most water-soluble metabolite, PNP, both total absorption and absorption efficiency increased as the dose increased. Except for the 4 μg/cm 2 dose, the individual compounds followed the absorption order of PNP > PO > PA. For the mixed compounds, the rate of absorption followed the order PO + PNP > PA + PNP > PA + PO for all three dose combinations. However, after HPLC analysis of the perfusate, the amount of absorption of each component (PA, PO, and PNP) in mixed compounds was significantly different ( p
Comment

We appreciate the opportunity to discuss the substantial body of work conducted by the authors of this article as well as the companionpiece by Pesaran, Schuermann,Treutler, and Weiner (PSTW; 2003). The authors state that their motivationfor developing the GVAR model was to create a concrete link between credit risk modelingand businesscycle  uctuationsso as to provide tools for better credit risk measurement and management. They also state that the GVAR model could perhaps be used by central banks, ostensibly for their monetary policy responsibilities. Hence the authors clearly view their work on the GVAR model as having various policy applications. Because we are research economists at a public institution that is intimately involvedin the policy issues of banking supervision and monetary policy, our comments on the article focus on these possible applications. On the whole, we agree with the authors that the GVAR model has many potentially fruitful applications in the  eld of credit risk measurement and management, but we are less optimistic about its usefulness with respect to macroeconomic and monetary policy applications.
Encyclopedia of Biostatistics, Six Volumes

This volume contains papers from the 5th International Workshop on Model-Oriented Data Analysis, which was held in June 1998 at Marseilles in France. These conferences intend to bring eastern and western statisticians together to exchange ideas on the theory and practice of statistics, especially experimental design. This is demonstrated by the following listing of the sections in the book, with the number of papers in parentheses:
GROWTH PATTERNS OF FIRST-CROSS COWS UNDER TWO ENVIRONMENTS

Growth patterns of 1000 first-cross females produced by mating Charolais, Limousin, and Simmental sires with Angus. Hereford, and Shorthorn dams were compared on 503 females under extensive range conditions at Manyberries, Alberta, and 497 females under semi-intensive farm conditions at Brandon, Manitoba. Three input groups born in 1970, 1971, and 1972 were involved. Hereford × Angus (HA) females. 75 at each location, served as a control population. Location difference in initial weight (12 mo of age) and in final weaning weight taken in 1979 were negligible and all input groups at each station were equivalent in weight at 7.5 yr of age. However, large annual fluctuations occurred in weights at Manyberries with breeding weights in 1974 averaging 86, 93, and 99% of those taken 24 mo previously for females born in 1970, 1971, and 1972. Females at Brandon gained weight during gestation and usually lost weight during nursing. Those at Manyberries invariably gained weight during nursing with substantial gestat.
Plastid differentiation and chlorophyll biosynthesis in different leaf layers of white cabbage (Brassica oleracea cv. capitata)

The contents of protochlorophyllide, protochlorophyll and chlorophyll together with the native arrangements of the pigments and the plastid ultrastructure were studied in different leaf layers of white cabbage (Brassica oleracea cv. capitata) using absorption, 77 K fluorescence spectroscopy and transmission electron microscopy. The developmental stage of the leaves was determined using the differentiation of the stoma complexes as seen by scanning electron microscopy and light microscopy. The pigment content showed a gradual decrease from the outer leaf layer towards the central leaves. The innermost leaves were in a primordial stage in many aspects; they were large but had typical proplastids with few simple inner membranes, and contained protochlorophyllide and its esters in a 2 : 1 ratio and no chlorophyll. Short-wavelength, not flash-photoactive protochlorophyllide and/or protochlorophyll forms emitting at 629 and 636 nm were dominant in the innermost leaves. These leaves also had small amounts of the 644 and 654 nm emitting, flash-photoactive protochlorophyllide forms. Rarely prolamellar bodies were observed in this layer. The outermost leaves had the usual characteristics of fully developed green leaves. The intermediary layers contained chlorophyll a and chlorophyll b besides the protochlorophyll(ide) pigments and had various intermediary developmental stages. Spectroscopically two types of intermediary leaves could be distinguished: one with only a 680 nm emitting chlorophyll a form and a second with bands at 685, 695 and 730 nm, corresponding to chlorophyll–protein complexes of green leaves. In these leaves, a large variety of chloroplasts were found. The data of this work show that etioplasts, etio-chloroplasts or chloro-etioplasts as well as etiolated leaves do exist in the nature and not only under laboratory conditions. The specificity of cabbage leaves compared with those of dark-grown seedlings is the retained primordial or intermediary developmental stage of leaves in the inner layers for very long (even for a few month) period. This opens new developmental routes leading to formation of specially developed plastids in the various cabbage leaf layers. The study of these plastids provided new information for a better understanding of the plastid differentiation and the greening process.
Gain of Function Effects of Z Alpha-1 Antitrypsin

The serine proteinase inhibitor alpha-1 antitrypsin (AAT) is produced principally by the liver from where it is secreted into the circulation and provides an antiprotease protective screen throughout the body. Mutations leading to deficiency in AAT are associated with liver and lung disease. The most notable is the Z mutation, which encodes a misfolded variant of the AAT protein in which the glutamic acid at position 342 is replaced by a lysine. ZAAT is not secreted effectively and accumulates intracellularly in the endoplasmic reticulum (ER) of hepatocytes and other AAT-producing cells. The ER has evolved a number of elegant mechanisms to manage the accumulation of incorrectly folded proteins; ZAAT interferes with this function and promotes ER stress responses and inflammation. Until recently it was thought that gain of function was the major cause of the liver disease whilst the lung disease was entirely due to loss of antiprotease protection in the lung. This belief is now being challenged with the discovery that ER stress is also activated in bronchial epithelial cells and inflammatory cells normally resident in the lung in ZAAT deficient individuals. Here we describe the gain of function effects of ZAAT. In particular we highlight the signalling pathways that are activated during ER stress in response to accumulation of ZAAT and how these events are linked to inflammation and may contribute to disease pathogenesis.
EFFICIENCY OF RESPIRATION AND ENERGY-REQUIREMENTS OF N ASSIMILATION IN ROOTS OF PISUM-SATIVUM

The function of alternative path respiration in roots was investigated in pea plants (Pisum sativum L. cv. Rondo). Plants were grown in symbiosis with Rhizobium leguminosarum (strain PF2), completely dependent on N2 fixation, or non-nodulated, receiving nitrate or ammonium at the same rate as N2 was fixed in symbiosis. Under these conditions, relative growth rates of plants grown with N2, NO-3 or NH+4 were the same. This facilitated interpretation of the effect of the N source on the efficiency of root respiration, as determined by the relative activity of the non-phosphorylating alternative path. The ‘wasteful’ oxidation of carbohydrate via this pathway was defined as the glucose equivalent of the difference between the amounts of ATP (mol O2)-1 produced in cytochrome and alternative path respiration. ‘Wasteful’ carbohydrate oxidation maximally amounted to 4% (N2), 15% (NO-3) and 25% (NH+4) of the daily carbohydrate oxidation in the roots. It is concluded that the ‘wasteful’ oxidation of carbohydrate via the alternative path is of minor importance for the adaptation of root respiratory metabolism to different energy requirements of N assimilation. The total carbohydrate import by roots fixing N2 was ca 60 and 30% higher than the import by roots assimilating NO-3 or NH+4, respectively. Two factors are shown to account for these differences: the high carbohydrate cost of N2 fixation, and the small contribution (30%) of the roots to NO-3 reduction by the plant. The high carbohydrate requirements of roots fixing N2 were met by higher rates of photosynthesis as compared with plants utilizing NO-3 or NH+4.
The effect of a carotenoid-rich diet on immunocompetence and behavioural performances in Moorhen chicks

Carotenoids have attracted the attention of behavioural ecologists because of their modulatory effects on the immune system, colour expression and several physiological functions affecting body conditions. To evaluate whether carotenoid abundance influences growth, behavioural performance, immunocompetence and bill colour, we raised two groups of Moorhen chicks for 1 month with different food intakes (control diet versus carotenoid-rich diet). The two groups did not show significant differences in growth rate, nor in the red or yellow colouration of the bill, although there was a greater immune response in the carotenoid-rich group. Locomotor activity, tested in an open-field apparatus, did not differ between the two groups, but carotenoid-fed chicks showed more intense pecking at a model mimicking the parents. In this experiment, we demonstrated that carotenoid abundance can influence both immune and behavioural responses, with a greater availability of carotenoids being reflected in improved behavioural performance and immunocompetence.
Genetic divergence among and within four Italian populations of Aphanius fasciatus (Teleostei, Cyprinodontiformes)

Due to the natural fragmentation of its habitats, Aphanius fasciatus, a Cyprininodontid living in coastal brackish‐water habitats, is distributed discontinuously with considerable isolation of its populations, and characterized by a high degree of osteological and genetic differentiation among them. The genetic relationships in four different Italian populations were studied using the control region (D‐loop) mitochondrial DNA sequence and the polymorphisms generated by RAPD‐PCR. The results revealed a well‐defined genetic structuring, that was also confirmed by the high Gst and Fst values, and a close relationship between the populations of Ganzirri and Lesina, as well as the isolation of the other two Sicilian populations. Moreover, with respect to the mitochondrial DNA analyses, the total genetic variance was higher among populations, but lower in the case of the RAPD polymorphisms.
Thymocyte Transfer to Enucleated Oocytes in the Mouse

Thymocytes from fetal, newborn, and adult mice were transferred into enucleated oocytes by standard micromanipulation. The developmental ability of oocytes receiving a thymocyte was examined in vitro. Most of the reconstituted eggs were successfully activated and formed a pronucleus-like structure. The percentage of reconstituted eggs developing to the 2-cell stage was high, 75-84%, but development of embryos to more advanced stages was limited. Only 8 and 1% of the reconstituted eggs receiving a thymocyte from fetal and newborn mice developed to the blastocyst stage, respectively. None developed to the 8-cell stage when a thymocyte from adult mice was transferred. Analysis of newly synthesized proteins of the reconstituted embryos showed that 68-70 kDa heat shock proteins, initial markers of embryonic genome activation, were synthesized at the late 2-cell stage.