Miracle-dz/UniFAR-FTUs huggingface dataset:
The importance of genetic mutation screening to determine retransplantation following failed kidney allograft from recurrent atypical haemolytic ureamic syndrome

We report the case of a patient with familial atypical haemolytic uraemic syndrome (aHUS) who underwent successful retransplantation 30 months following his failed first kidney allograft from recurrent aHUS. He achieved excellent graft function (creatinine 90 μmol/L), with no evidence of disease recurrence on standard maintenance immunosuppression 9 months after his second deceased donor kidney transplantation. Genetic mutation testing was not available prior to first transplant but screening prior to retransplant identified the patient as having a newly discovered mutation, c.T3566A, within exon 23 of the complement factor H (CFH) gene. Currently, public financing and subsidisation for eculizumab, a costly but effect complement (C5) inhibitor for the treatment of aHUS is not available in Australia. The decision for retransplantation must balance between the risk of disease recurrence and greater risk of death on dialysis. The absence of a more severe CFH genotype assisted in the decision for retransplantation and suggests the importance of genetic mutation screening in order to stratify the risk of disease recurrence and graft loss versus the benefit of transplantation.
Steroid‐induced ocular hypertensive response in children and adolescents with acute lymphoblastic leukemia and non‐hodgkin lymphoma

The aim of this study was to evaluate intraocular pressure (IOP) associated with use of glucocorticoids in children and adolescents treated for acute lymphoblastic leukemia and non‐Hodgkin lymphoma. We carried out a prospective descriptive study with measurement of IOP before treatment (D0), 8th (D8), 14th (D14), and 28h days (D28) of treatment. We examined 12 patients, with two cases of ocular hypertension, and it was found a statistically significant difference between the means of IOP between D0 versus D8 and D0 versus D14 (P = 0.013). The possibility of silent ocular hypertension with irreversible blindness indicates the need of IOP verification. Pediatr Blood Cancer 2014;61:2083–2085. © 2014 Wiley Periodicals, Inc.
Bioequivalence in the Sheep of Two Tilmicosin Preparations

DOI : 10.26650/experimed.2019. 19005 Amac : Bu calismanin amaci, tilmikosin fosfat iceren bir jenerik urunun orijinal preparata biyoesdegerligini degerlendirmektir. Gerec ve Yontem : 20 adet Kivircik irki saglikli koyuna tek doz (10 mg/kg, s.c.) capraz tasarim esasina gore orijinal ve jenerik urun uygulandi. 0. dakika ve uygulama sonrasinda 15. , 30. dakika ile 1. ,2. , 3. , 4. , 6. , 8. , 12. , 24. , 48. , 72. ve 96. saatlerde kan ornekleri toplandi. Serum tilmikosin duzeyleri, ekstraksiyon islemini takiben yuksek basincli likit kromatografisi (HPLC) ile olculdu. Farmakokinetik parametreler non-kompartmantal model analizi kullanilarak hesaplandi. Biyoesdegerlik degerlendirilmesinde EAA(0-72) ve Cmax parametreleri temel alindi. Biyoesdegerlik kriteri EAA %80-125 (%90 guven araligi) olarak kabul edildi. Bulgular : Orijinal ilaca kiyasla jenerik ilacin EAA(0-72) orani % 105,7; Cmax orani ise %106,6 olarak saptandi. Sonuc : Sonuc olarak, iki urunun biyoesdeger oldugu ve endike olduklari alanlarda birbirlerinin yerine kullanabilecekleri soylenebilir. Cite this article as : Şahin E, Yildirim M. Bioequivalence in the Sheep of Two Tilmicosin Preparations. Experimed 2019; 9(1): 28-31.
Deep learning and radiomics in precision medicine

ABSTRACT Introduction: The radiological reading room is undergoing a paradigm shift to a symbiosis of computer science and radiology using artificial intelligence integrated with machine and deep learning with radiomics to better define tissue characteristics. The goal is to use integrated deep learning and radiomics with radiological parameters to produce a personalized diagnosis for a patient. Areas covered: This review provides an overview of historical and current deep learning and radiomics methods in the context of precision medicine in radiology. A literature search for ‘Deep Learning’, ‘Radiomics’, ‘Machine learning’, ‘Artificial Intelligence’, ‘Convolutional Neural Network’, ‘Generative Adversarial Network’, ‘Autoencoders’, Deep Belief Networks”, Reinforcement Learning”, and ‘Multiparametric MRI’ was performed in PubMed, ArXiv, Scopus, CVPR, SPIE, IEEE Xplore, and NIPS to identify articles of interest. Expert opinion: In conclusion, both deep learning and radiomics are two rapidly advancing technologies that will unite in the future to produce a single unified framework for clinical decision support with a potential to completely revolutionize the field of precision medicine.
Interference in wireless multihop networks: A model and its experimental evaluation

Interference is an inherent property of wireless multihop networks. Adding interference-awareness to their control functions can significantly enhance the overall network performance. In this paper we present an analytical model for the probability that a transmission destined to an arbitrary network node is successful in the presence of interference from other nodes in the network. We introduce the concept of interference areas and interference zones to express this probability as a function of the network density, node transmission probability, radio propagation environment, and network card reception sensitivity. Our derivation includes a simpleMAC model, which captures the carrier sense function of many MAC protocols. Contrary to measurementbased models, our derivation only requires information that is locally available to the nodes, avoiding all measurement-related pitfalls. The validation of our model against experiments in a real testbed, set up for this purpose in our indoor office environment, shows good match of the experimental results with the analytical predictions. Interestingly our model predictions follow closely those of more elaborate state-of-the-art analytical models. Finally, to demonstrate the real utility of our model, we have implemented on our testbed a routing metric that explicitly takes interference into account via our derivation. The throughputs of the resulting routes compare favorably with those achieved by a well-known probe-based routing metric.
Fifty years of invasion ecology – the legacy of Charles Elton

The publication, in 1958, of Charles Elton's book The ecology of invasions by animals and plants launched the systematic study of biological invasions. Invasion ecology has grown to become an important multi‐disciplinary subfield of ecology with growing links to many other disciplines. This paper examines the citation history of Elton's book using the Web of Science. We also examine Elton's influence in shaping the current research agenda in invasion ecology, for which we use the 28 papers in a special issue of Diversity and Distributions (Volume 14: 2) as a representative sample.
The Application of the ZCZ Sequence Pairs Set in QS-CDMA System

In this paper, the theory of ZCZ sequence pairs set is presented, and a class of ZCZ sequence pairs sets can be constructed based on perfect autocorrelation sequence pair and orthogonal matrix. Based on the system model presented in this paper, and through simulation on MATLAB platform, the performance of ZCZ sequence pairs in S-CDMA, QS-CDMA and A-CDMA system is analyzed. Compared with Gold sequence, ZCZ sequence pairs set has a long zero-correlation zone, and can be used in QS-CDMA system to obtain better system performance with great number of users.
Cost sensitive meta-learning

Classification is one of the primary tasks of data mining and aims to assign a class label to unseen examples by using a model learned from a training dataset. Most of the accepted classifiers are designed to minimize the error rate but in practice data mining involves costs such as the cost of getting the data, and cost of making an error. Hence the following question arises: Among all the available classification algorithms, and in considering a specific type of data and cost, which is the best algorithm for my problem? It is well known to the machine learning community that there is no single algorithm that performs best for all domains. This observation motivates the need to develop an “algorithm selector” which is the work of automating the process of choosing between different algorithms given a specific domain of application. Thus, this research develops a new meta-learning system for recommending cost-sensitive classification methods. The system is based on the idea of applying machine learning to discover knowledge about the performance of different data mining algorithms. It includes components that repeatedly apply different classification methods on data sets and measuring their performance. The characteristics of the data sets, combined with the algorithm and the performance provide the training examples. A decision tree algorithm is applied on the training examples to induce the knowledge which can then be applied to recommend algorithms for new data sets, and then active learning is used to automate the ability to choose the most informative data set that should enter the learning process. This thesis makes contributions to both the fields of meta-learning, and cost sensitive learning in that it develops a new meta-learning approach for recommending cost-sensitive methods. Although, meta-learning is not new, the task of accelerating the learning process remains an open problem, and the thesis develops a novel active learning strategy based on clustering that gives the learner the ability to choose which data to learn from and accordingly, speed up the meta-learning process. Both the meta-learning system and use of active learning are implemented in the WEKA system and evaluated by applying them on different datasets and comparing the results with existing studies available in the literature. The results show that the meta-learning system developed produces better results than METAL, a well-known meta-learning system and that the use of clustering and active learning has a positive effect on accelerating the meta-learning process, where all tested datasets show a decrement of error rate prediction by 75 %.
A multiplex polymerase chain reaction method for rapid identification of Citrobacter freundii and Salmonella species, including Salmonella Typhi.

BACKGROUND AND PURPOSE Salmonella enterica is one of the most common enteric pathogens worldwide. Conventional methods of isolation of Salmonella strains take 4-7 days to complete, are laborious and require substantial manpower. We devised a polymerase chain reaction (PCR) method that simultaneously uses three pairs of specific primers to detect inv, spv, and via genes of Salmonella. METHODS Three primer pairs were designed, including: SPVC-1 and SPVC-2, based on the nucleotide sequences of the spvC gene; INVA-1 and INVA-2, based on the invA gene; and VIAB-1 and VIAB-2, based on the viaB gene. PCR was performed using these three primers to identify 14 clinically important bacterial organisms, including Citrobacter freundii, S. enterica serovars Typhi and Paratyphi C, Dublin, and other non-typhoidal Salmonella that harbor a virulence plasmid. RESULTS The following strains were readily identified using the PCR: (1) C. freundii; (2) S. Typhi; and S. Paratyphi C; (3) S. Dublin (virulence antigen-positive); and (4) Salmonella serovars that harbor an spv-type virulence plasmid. S. enterica could also be identified, but required further testing to determine serovar. CONCLUSIONS This PCR method allows S. Typhi to be identified immediately so that appropriate antibiotic treatment can be initiated without delay.
Pulmonary hyperinflation due to gas trapping and pulmonary artery size: The MESA COPD Study

Background Pulmonary hypertension is associated with increased morbidity and mortality in chronic obstructive pulmonary disease (COPD). Since pulmonary artery (PA) size increases in pulmonary hypertension, we measured PA cross-sectional area using magnetic resonance imaging (MRI) to test the hypothesis that pulmonary hyperinflation due to gas trapping is associated with PA cross-sectional area in COPD. Methods The MESA COPD Study recruited participants with COPD and controls from two population-based cohort studies ages 50–79 years with 10 or more pack-years and free of clinical cardiovascular disease. Body plethysmography was performed according to standard criteria. Cardiac MRI was performed at functional residual capacity to measure the cross-sectional area of the main PA. Percent emphysema was defined as the percentage of lung voxels less than -950 Hounsfield units as assessed via x-ray computed tomography. Analyses were adjusted for age, gender, height, weight, race-ethnicity, the forced expiratory volume in one second, smoking status, pack-years, lung function, oxygen saturation, blood pressure, left ventricular ejection fraction and percent emphysema. Results Among 106 participants, mean residual volume was 1.98±0.71 L and the mean PA cross-sectional area was 7.23±1.72 cm2. A one standard deviation increase in residual volume was independently associated with an increase in main PA cross-sectional area of 0.55 cm2 (95% CI 0.18 to 0.92; p = 0.003). In contrast, there was no evidence for an association with percent emphysema or total lung capacity. Conclusion Increased residual volume was associated with a larger PA in COPD, suggesting that gas trapping may contribute to pulmonary hypertension in COPD.
The Hfq Homolog in Legionella pneumophila Demonstrates Regulation by LetA and RpoS and Interacts with the Global Regulator CsrA

ABSTRACT A gene in Legionella pneumophila that has significant homology to published hfq genes demonstrated regulation by RpoS and the transcriptional regulator LetA. Additionally, Hfq has a positive effect on the presence of transcripts of the genes for CsrA and the ferric uptake regulator Fur. Mutants lacking hfq demonstrate defects in growth and pigmentation and slight defects in virulence in both amoeba and macrophage infection models. Hfq appears to play a major role in exponential-phase regulatory cascades of L. pneumophila.
Characterization of the Functional MRI Response Temporal Linearity via Optical Control of Neocortical Pyramidal Neurons

The blood oxygenation level-dependent (BOLD) signal serves as the basis for human functional MRI (fMRI). Knowledge of the properties of the BOLD signal, such as how linear its response is to sensory stimuli, is essential for the design and interpretation of fMRI experiments. Here, we combined the cell-type and site-specific causal control provided by optogenetics and fMRI (opto-fMRI) in mice to test the linearity of BOLD signals driven by locally induced excitatory activity. We employed high-resolution mouse fMRI at 9.4 tesla to measure the BOLD response, and extracellular electrophysiological recordings to measure the effects of stimulation on single unit, multiunit, and local field potential activity. Optically driven stimulation of layer V neocortical pyramidal neurons resulted in a positive local BOLD response at the stimulated site. Consistent with a linear transform model, this locally driven BOLD response summated in response to closely spaced trains of stimulation. These properties were equivalent to responses generated through the multisynaptic method of driving neocortical activity by tactile sensory stimulation, and paralleled changes in electrophysiological measures. These results illustrate the potential of the opto-fMRI method and reinforce the critical assumption of human functional neuroimaging that—to first approximation—the BOLD response tracks local neural activity levels.
Tissue Microarrays: What Will They Bring to Molecular and Anatomic Pathology?

The analysis of a large number of tumor tissues with conventional techniques of molecular pathology is tedious and slow. The authors recently developed the tissue microarray technology that makes it possible to sample up to 1000 tumors on one glass slide, which then can be analyzed by fluorescence in situ hybridization, RNA in situ hybridization, or immunohistochemistry. The tissue microarray technology has the potential to significantly accelerate molecular studies that seek associations between molecular changes and clinicopathologic features of the cancer. Examples of potential applications for tissue microarrays include testing and optimization of probes and antibodies, the organization of large tissue repositories, and the facilitation of multicenter studies. Further, tissue microarrays can be used for educational purposes as well as to improve quality control and standardization of staining methods and interpretation. Tissue microarrays have become one of the most promising tools for the molecular and anatomic pathologist and will have many applications in cancer research, as well as in other fields of pathology. This review article gives an overview of current applications of tissue microarrays as well as possible future development of the technology.
A Variant of the Anomalous Motion Illusion Based upon Contrast and Visual Latency

We examined a variant of the anomalous motion illusion. In a series of experiments, we ascertained luminance contrast to be the critical factor. Low-contrast random dots showed longer latency than high-contrast ones, irrespective of whether they were dark or light (experiments 1–3). We conjecture that this illusion may share the same mechanism with the Hess effect, which is characterised by visual delay of a low-contrast, dark stimulus in a moving situation. Since the Hess effect is known as the monocular version of the Pulfrich effect, we examined whether illusory motion in depth could be observed if a high-contrast pattern was projected to one eye and the same pattern of low-contrast was presented to the other eye, and they were binocularly fused and swayed horizontally. Observers then reported illusory motion in depth when the low-contrast pattern was dark, but they did not when it was bright (experiment 4). Possible explanations of this inconsistency are discussed.
Toxin Isolation from a Kanagawa‐Phenomenon Negative Strain of Vibrio parahaemolyticus

Production of a toxin by Vibrio parahaemolyticus Kanagawa‐phenomenon negative strains was examined. Ammonium sulfate fractions of broth culture filtrates were dialyzed, concentrated by lyophilization, and tested for toxic effects by mouse intraperitoneal injection. One fraction, which we think is a toxin, was isolated from a broth culture filtrate of V. parahaemolyticus FC 1011 (a Kanagawa‐phenomenon negative strain) and consistently produced lethal effects in mice at high concentrations and diarrhea in lower concentrations. The toxin was assayed for mouse LD50 and ability to produce diarrhea via forced feeding in mice. V. parahaemolyticus FC 1011 toxin was found to be protein, to be inactivated by heat or trypsin hydrolysis, and to produce positive skin permeability reactions in rabbits. However, it failed to induce fluid accumulation in ligated ileal loops in rabbits.
School-age Children Born to Diabetic Mothers and to Mothers with Gestational Diabetes Exhibit a High Rate of Inattention and Fine and Gross Motor Impairment

OBJECTIVES To study the neurobehavioral effects that pregestational and gestational diabetes might have on offspring at school age. STUDY DESIGN We studied neurobehavioral function at school age of 57 children born to 48, well controlled, diabetic mothers and of 32 children born to 32 women with gestational diabetes. Their development was compared with 57 control children matched by age, birth order and parental socio-economic status, using a number of cognitive, behavioral, sensory and motor neurological tests. RESULTS The IQ scores on the WISC-R and Bender tests of the children born to diabetic mothers were similar to those of control children, but the Bender scores of the children born to mothers with gestational diabetes were slightly lower. No differences were found between the study groups in various sensory-motor functions in comparison to controls. However, both study group children performed less well than controls in fine and gross motor functions as observed on the Bruininks-Oseretzki test of motor proficiency. The scores of children born to the mothers with pregestational diabetes were higher than controls on the Touwen & Prechtl neurological examination (worse function). The children from both research groups also performed worse on the Pollack taper test that is designed to detect inattention and hyperactivity. The children of the two study groups also had slightly higher scores on the Conners abbreviated parents-teachers questionnaire measuring hyperactivity and inattention, but the differences from controls were not statistically significant. We found a negative correlation between the performance of the children born to mothers with pregestational diabetes on various neurodevelopmental and behavioral tests and the severity of maternal hyperglycemia as assessed by blood glycosylated hemoglobin levels and acetonuria. CONCLUSIONS Pregestational or gestational diabetes was found to adversely affect attention span and motor functions of offspring at school age, but not their cognitive ability. These effects were negatively correlated with the degree of maternal glycemic control, and were more pronounced in younger children.
GROUPKIT: a groupware toolkit for building real-time conferencing applications

Abstract This paper presents our approach to the design of groupware toolkits for real-time work, and how the design is instantiated in our toolkit, GROUPKIT. The design is based on both the technical underpinnings necessary for real-time groupware, and on user-centered features identified by existing CSCW human factors work. We also present three strategies for building GROUPKIT's components. First, an extendible, object-oriented run-time architecture supports managing distributed processes and the communication between them. Second, transparent overlays offer a convenient method for adding general components to various groupware applications, for example supporting gestures via multiple cursors and annotation via sketching. Third, open protocols allow the groupware designer to create a wide range of interface and interaction policies, accommodating group differences in areas such as conference registration and floor control.
survival with an asymmetrical brain: advantages and disadvantages of cerebral lateralization

recent evidence in natural and semi-natural settings has revealed a variety of left-right perceptual asymmetries among vertebrates. these include preferential use of the left or right visual hemifield during activities such as searching for food, agonistic responses, or escape from predators in animals as different as fish, amphibians, reptiles, birds, and mammals. there are obvious disadvantages in showing such directional asymmetries because relevant stimuli may be located to the animal's left or right at random; there is no a priori association between the meaning of a stimulus (e.g., its being a predator or a food item) and its being located to the animal's left or right. moreover, other organisms (e.g., predators) could exploit the predictability of behavior that arises from population-level lateral biases. it might be argued that lateralization of function enhances cognitive capacity and efficiency of the brain, thus counteracting the ecological disadvantages of lateral biases in behavior. however, such an increase in brain efficiency could be obtained by each individual being lateralized without any need to align the direction of the asymmetry in the majority of the individuals of the population. here we argue that the alignment of the direction of behavioral asymmetries at the population level arises as an “evolutionarily stable strategy” under “social” pressures occurring when individually asymmetrical organisms must coordinate their behavior with the behavior of other asymmetrical organisms of the same or different species.