Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolic Profiling for Detection of Staphylococcus aureus Infection and Antibiotic Resistance

Due to slow diagnostics, physicians must optimize antibiotic therapies based on clinical evaluation of patients without specific information on causative bacteria. We have investigated metabolomic analysis of blood for the detection of acute bacterial infection and early differentiation between ineffective and effective antibiotic treatment. A vital and timely therapeutic difficulty was thereby addressed: the ability to rapidly detect treatment failures because of antibiotic-resistant bacteria. Methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-sensitive S. aureus (MSSA) were used in vitro and for infecting mice, while natural MSSA infection was studied in humans. Samples of bacterial growth media, the blood of infected mice and of humans were analyzed with combined Gas Chromatography/Mass Spectrometry. Multivariate data analysis was used to reveal the metabolic profiles of infection and the responses to different antibiotic treatments. In vitro experiments resulted in the detection of 256 putative metabolites and mice infection experiments resulted in the detection of 474 putative metabolites. Importantly, ineffective and effective antibiotic treatments were differentiated already two hours after treatment start in both experimental systems. That is, the ineffective treatment of MRSA using cloxacillin and untreated controls produced one metabolic profile while all effective treatment combinations using cloxacillin or vancomycin for MSSA or MRSA produced another profile. For further evaluation of the concept, blood samples of humans admitted to intensive care with severe sepsis were analyzed. One hundred thirty-three putative metabolites differentiated severe MSSA sepsis (n = 6) from severe Escherichia coli sepsis (n = 10) and identified treatment responses over time. Combined analysis of human, in vitro, and mice samples identified 25 metabolites indicative of effective treatment of S. aureus sepsis. Taken together, this study provides a proof of concept of the utility of analyzing metabolite patterns in blood for early differentiation between ineffective and effective antibiotic treatment in acute S. aureus infections.
Dichlorodiphenyldichloroethane and Polychlorinated Biphenyls: Intraindividual Changes, Correlations, and Predictors in Healthy Women from the Southeastern United States

Dichlorodiphenyldichloroethane (DDE) and polychlorinated biphenyls (PCB) are widespread environmental contaminants that have been postulated to increase the risk of diseases such as non–Hodgkin's lymphoma, breast cancer, as well as lead to early menopause. Studies assessing the effect of organochlorine exposure often can only measure organochlorine levels once, such as at study enrollment, which may not be an etiologically relevant time period. We assessed the temporal changes in DDE and PCBs and the predictors of those changes using interview data and DDE and PCB measures collected from 123 women who were enrolled in a baseline study from 1978 to 1982 and followed up in 2003 to 2004. Baseline and follow-up organochlorine levels were compared using Spearman correlations (rs), and predictors of the rate of change in log concentration were evaluated using linear regression models. Although serum concentrations dramatically declined (median follow-up to baseline concentration ratio was 16% for DDE and 45% for PCB), baseline and follow-up measures were strongly correlated for DDE (rs = 0.72) and moderately correlated for PCBs (rs = 0.43). Prediction of follow-up PCB levels was substantially improved (rs = 0.75) with data on initial concentration, length of lactation, baseline body mass index, and percent change in body fat, whereas DDE prediction improved slightly (rs = 0.83) with data on lactation and baseline body mass index. These findings suggest that a single organochlorine measure provides considerable information on relative ranking at distant times and that the predictive power can be improved, particularly for PCBs, with information on a few predictors. (Cancer Epidemiol Biomarkers Prev 2008;17(10):2729–36)
Melatonin is more effective than taurine and 5‐hydroxytryptophan against hyperglycemia‐induced kidney‐cortex tubules injury a

Abstract: The antioxidative effects of melatonin (Mel), 5‐hydroxytryptophan (5‐HTP) and taurine (TAU) on hyperglycemia‐induced oxidative stress was investigated in primary cultures of kidney‐cortex tubule cells grown in metabolically and hormonally defined medium. In the presence of 30 mm glucose (hyperglycemic conditions), cell viability was decreased by about 35% in comparison with that estimated in the glucose‐depleted medium probably as a result of induction of apoptosis, as concluded from: (i) chromatin condensation and DNA fragmentation assays, (ii) a significant enhancement of reactive oxygen species (ROS) production, (iii) 8‐hydroxydeoxyguanosine (8‐OHdG) generation, (iv) an increased protein peroxidation and (v) a decline of reduced glutathione (GSH) levels leading to a disturbed glutathione redox state. The addition of 100 μm Mel to the hyperglycemic medium resulted in a twofold decrease in both 8‐OHdG accumulation and protein peroxidation as well as restoration of the control intracellular ROS levels accompanied by a substantial increase in GSH/oxidized glutathione (GSSG) ratio due to a decline in GSSG content. ROS elimination was also achieved in the presence of 1 mm TAU which diminished protein and DNA injuries by about 25% and 30%, respectively. On the contrary, the action of 100 μm 5‐HTP on ROS level, 8‐OHdG generation, protein peroxidation and GSH/GSSG ratio was negligible. Thus, in contrast to 5‐HTP and TAU, Mel might be considered as beneficial for diabetes therapy, particularly in terms of reduction of hyperglycemia‐induced kidney injury.
Prior Data and Kernel Conditional Random Fields for Obstacle Detection

We consider the task of training an obstacle detection (OD) system based on a monocular color camera using minimal supervision. We train it to match the performance of a system that uses a laser rangefinder to estimate the presence of obstacles by size and shape. However, the lack of range data in the image cannot be compensated by the extraction of local features alone. Thus, we investigate contextual technique s based on Conditional Random Fields (CRFs) that can exploit the global context of the image, and we compare them to a conventional learning approach. Furthermore, we describe a procedure for introducing prior data in the OD system to increase its performance in “familiar” terrains. Finally, we perform experiments using sequences of images taken from a vehicle for autonomous vehicle navigation applications.
EFFECTIVENESS OF INTEGRATED ACCIDENT PREVENTION STRATEGIES

There are potential interactions among approaches to reduce or prevent certain accident causes. Given the overlapped safety benefits of various measures for accident prevention, it is necessary to identify their interactions and quantify the safety effectiveness of combined accident prevention strategies. This study focuses on strategies to prevent broken rails and broken wheels, respectively. Improved wheel condition reduces the impact load on the rail, thereby may reduce broken-rail-caused derailments. In this paper, we propose a quantitative framework to assess the safety effectiveness of combined accident prevention strategies under various operational conditions. In the larger context of railroad hazardous materials risk management, integrated accident prevention can be compared to other means of risk reduction measures, such as tank car safety design enhancement or operational changes. INTRODUCTION Train accidents cause damage to infrastructure and rolling stock, disrupt service, and may cause casualties and harm the environment. Therefore, accident prevention is of great importance for the rail industry and government. An accurate assessment of the cost-effectiveness of accident prevention measures, individually or in combination, enables optimal allocation of resources for safety improvement. When multiple accident prevention strategies are applied, their safety benefits may overlap. For example, reducing wheel defects may not only prevent broken-wheel-caused derailments, but also reduce the likelihood of broken rails due to reduced impact load at the wheel-rail interface. A more detailed illustration of the interaction between track-related and rolling stock-related defects is presented in Fig.1. The interaction between accident causes makes it more complex to estimate the safety effectiveness of combined accident prevention strategies. The focus of this paper is to evaluate the safety benefits of a combination of broken rail prevention and broken wheel prevention.
TIALA — Time series alignment analysis

The analysis of time series expression data is widely employed for investigating biological mechanisms. Microarrays are often used to generate time series for several different experimental conditions. These time series then need to be compared to each other. For a successful comparison it is necessary to perform a time series alignment because the experiments can differ in the number of time points, as well as in the time points themselves. In this work we propose a novel visual analytics approach for the analysis of multiple time series experiments in parallel. Our time series alignment analysis tool Tiala allows one to align multiple time series experiments and to visually explore the aligned expression profiles. A two- and three-dimensional visualization strategy was implemented that is especially designed to enhance the display of multiple aligned time series expression profiles. Tiala is available as a part of the microarray data analysis software Mayday. Mayday itself is open source software distributed under the terms of the GNU General Public License. It is available from http://www.microarray-analysis.org. We apply our approach to time series showing abiotic stress responses of Arabidopsis thaliana and to data sets from two replicates of the antibiotics producing bacterium Streptomyces coelicolor.
Fuglede–Kadison determinant: theme and variations

We review the definition of determinants for finite von Neumann algebras, due to Fuglede and Kadison [Fuglede B, Kadison R (1952) Ann Math 55:520–530], and a generalization for appropriate groups of invertible elements in Banach algebras, from a paper by Skandalis and the author (1984). After some discussion of K-theory and Whitehead torsion, we indicate the relevance of these determinants to the study of -torsion in topology. Contents are as follows: 1. The classical setting. 2. On von Neumann algebras and traces. 3. Fuglede–Kadison determinant for finite von Neumann algebras. 4. Motivating question. 5. Brief reminder of , , , and Bott periodicity. 6. Revisiting the Fuglede–Kadison and other determinants. 7. On Whitehead torsion. 8. A few lines on -torsion.
Prevalence and antibiotic resistance of pathogenic Vibrios in shellfishes from Cochin market

V. parahaemolyticus (68.1%), V. alginolyticus (18.1%), V. vulnificus (2%), V. cholerae (1%), V. harveyi (1%) and V. mimicus (1%) were detected. Overall percentage of incidence was highest in clams (84.2%) followed by shrimps (63.8%) and crabs (37.5%). When isolates were tested for their susceptibility to various antibiotics, highest incidence of antibiotic resistance was evident against ampicillin and colistin followed by amoxycillin, carbenicillin, ceftazidime and cephalothin and lowest against chloramphenicol, tetracycline and nalidixic acid. Multiple drug resistance was prevalent among the isolates. Results indicate that the various seafood markets at the retail level in Cochin are contaminated with potentially pathogenic Vibrio species. If they survive insufficient processing/cooking conditions they would have an impact on safety of processed/cooked ready-to-eat food.
An experimental approach to relate a tumor-associated enzyme marker to tumor cell numbers.

Alkaline phosphatase was monitored in 17 mice with s.c. -implanted tumors to relate the total circulating alkaline phosphatase to the total number of tumor cells in each mouse. There was a semilogarithmic relationship between the alkaline phosphatase units and the number of tumor cells. A time-independent standard plot of alkaline phosphatase and the number of tumor cells was used to estimate the size of disseminated and localized tumors. In animals treated with cyclophosphamide, the alkaline phosphatase marker was used to monitor the regression and recurrence of the neoplasm in vivo.
Clinical values of urinary IL-6 in asymptomatic renal hematuria and renal hematuria with proteins

Renal hematuria is caused by glomerular disease. Under pathological conditions, the distribution of interleukin-6 (IL-6) in kidney tissue is abnormal and urinary IL-6 levels are increased. Abnormal IL-6 secretion promotes the hyperplasia of mesangial cells and matrix and, thus, affects the permeability of the glomerular filtration membrane. Therefore, the detection of urinary IL-6 levels in patients with renal hematuria is beneficial for disease evaluation. A total of 82 patients with primary renal hematuria were divided into group 1 (UPr/24 h < 150 mg; pure hematuria group), group 2 (150 mg ≤ UPr/24 h ≤ 1,000 mg) and group 3 (UPr/24 h > 1,000 mg). A total of 30 normal individuals were selected as the controls. The urinary IL-6 levels were detected by the enzyme-linked immunosorbent assay (ELISA) method and a renal biopsy was conducted. The urinary IL-6 levels and renal pathological damage scores in groups 1 and 2 were significantly reduced compared with those in group 3, (P<0.001 and 0.01, respectively), with no significant difference between groups 1 and 2 (P>0.05). The correlation coefficient (r) of urinary IL-6 with 24 h urinary protein (UPr/24 h) in groups 1, 2 and 3 was 0.017, 0.045 and 0.747, respectively, and that of urinary IL-6 with renal pathological damage score was 0.627, 0.199 and 0.119, respectively. The UPr/24 h was significantly correlated with IL-6 level (r=0.7320, P<0.000). In group 1, the urinary IL-6 levels were correlated with the degree of renal pathological damage. A positive correlation was observed between urinary IL-6 levels and UPr/24 h.
Comparison of the lightweight Camp Normal Activity Foot with other prosthetic feet in trans-tibial amputees: A pilot study

Clinically relevant information regarding the useability of prosthetic feet is scarce. The industry is not obliged to perform clinical studies before marketing the product. Clinicians however are limited in their possibilities (organisation and finance) to determine the useability of a technical product. This small study is an example of how in general the useability of a technical product is established in clinical practice. The Camp Normal Activity Foot (CNAF), a carbon prosthetic foot, was compared objectively and subjectively with a number of other prosthetic feet (same price bracket) in three subjects with trans-tibial (TT) amputations. The CNAF is low in weight and has favourable stiffness and hysteresis properties. The stiffness of the pylon of the CNAF seems to be limited as also is the possibility of adaptation of the CNAF. The CNAF distinguishes itself, in this study, but not convincingly with respect to the energy consumption in walking, the steptime parameters (symmetry) and the subjective judgement of the users. An additional virtue of the CNAF seems to be its light weight.
Role of Troposphere‐Convection‐Land Coupling in the Southwestern Amazon Precipitation Bias of the Community Earth System Model Version 1 (CESM1)

The Amazon forest plays an important role in the tropical circulation and global water and biogeochemical cycles. However, the common Amazon precipitation biases in global climate models undermine our ability to understand future changes in the Amazon and their global consequences. The Community Earth System Model exhibits a persistent wet season dry bias over the southwestern Amazon. The bias is also characterized by inaccurate diurnal timing and intensity of rainfall events. Analysis of a diverse set of simulations suggests that the bias originates from the land model and/or deep convection parameterization. A known land model bias in the partitioning of surface energy fluxes is found not to contribute significantly to the rainfall bias. Key model processes are identified to be the low‐level divergent circulation controlling horizontal moisture flow and the sensitivity of the modeled deep convection to the lower tropospheric moisture. The lower tropospheric moisture divergence dictates the spatiotemporal distributions of convective precipitation through parameterized entrainment mixing. While the entrainment effect improves the rainfall diurnal cycle, it suppresses convective precipitation under low‐level moisture divergence. Persistent moisture divergence is found over the southwestern Amazon and limits parameterized convective precipitation, particularly in the late afternoon, although uncertainty exists in the low‐level flow in the simulation and reanalyses. One way to sustain rainfall in the presence of low‐level divergence is a convective trigger based on both the moisture and temperature changes in the free troposphere, which is shown to help in reducing the dry bias.
Using value prediction to increase the power of speculative execution hardware

This article presents an experimental and analytical study of value prediction and its impact on speculative execution in superscalar microprocessors. Value prediction is a new paradigm that suggests predicting outcome values of operations (at run-time ) and using these predicted values to trigger the execution of true-data-dependent operations speculatively. As a result, stals to memory locations can be reduced and the amount of instruction-level parallelism can be extended beyond the limits of the program's dataflow graph. This article examines the characteristics of the value prediction concept from two perspectives: (1) the related phenomena that are reflected in the nature of computer programs and (2) the significance of these phenomena to boosting instruction-level parallelism of superscalar microprocessors that support speculative execution. In order to better understand these characteristics, our work combines both analytical and experimental studies.
Mobile Surface Reflectometry

We present two novel mobile reflectometry approaches for acquiring detailed spatially varying isotropic surface reflectance and mesostructure of a planar material sample using commodity mobile devices. The first approach relies on the integrated camera and flash pair present on typical mobile devices to support free‐form handheld acquisition of spatially varying rough specular material samples. The second approach, suited for highly specular samples, uses the LCD panel to illuminate the sample with polarized second‐order gradient illumination. To address the limited overlap of the front facing camera's view and the LCD illumination (and thus limited sample size), we propose a novel appearance transfer method that combines controlled reflectance measurement of a small exemplar section with uncontrolled reflectance measurements of the full sample under natural lighting. Finally, we introduce a novel surface detail enhancement method that adds fine scale surface mesostructure from close‐up observations under uncontrolled natural lighting. We demonstrate the accuracy and versatility of the proposed mobile reflectometry methods on a wide variety of spatially varying materials.
Understanding Cloud Computing Vulnerabilities

The current discourse about cloud computing security issues makes a well-founded assessment of cloud computing's security impact difficult for two primary reasons. First, as is true for many discussions about risk, basic vocabulary such as "risk," "threat," and "vulnerability" are often used as if they were interchangeable, without regard to their respective definitions. Second, not every issue that's raised is really specific to cloud computing. We can achieve an accurate understanding of the security issue "delta" that cloud computing really adds by analyzing how cloud computing influences each risk factor. One important factor concerns vulnerabilities: cloud computing makes certain well-understood vulnerabilities more significant and adds new vulnerabilities. Here, the authors define four indicators of cloud-specific vulnerabilities, introduce a security-specific cloud reference architecture, and provide examples of cloud-specific vulnerabilities for each architectural component.
Towards a FrameNet Resource for the Legal Domain

In the AI&Law community, the importance of frame–based ontologies has been acknowledged since the early 90’s with the Van Kralingen’s proposal of a frame language for legal knowledge representation. This still appears to be a strongly felt need within the community. In this paper, we propose to face this need by developing a FrameNet resource for the legal domain based on Fillmore’s Frame Semantics, whose final outcome will include a frame–based lexical ontology and a legal corpus annotated with frame information. In particular, the paper focuses on methodological and design issues, ranging from the customization and extension of the general FrameNet for the legal domain to the linking of the developed resource with already existing Legal Ontologies.
Exploring the impact of common buzzard Buteo buteo predation on red grouse Lagopus lagopus scotica

ii Dedication . iv Acknowledgements . v Collaborations . vi List of Tables and Figures . ix Chapter 1: Introduction . 1 1.1 Background . 2 1.2 Raptors and gamebirds. 3 1.3 Impact of raptors on gamebirds . 8 1.4 Buzzards . 11 1.5 Study site and approach . 13 1.6 Thesis aims . 20 1.7 Thesis outline . 20 Chapter 2. Prey delivered to common buzzard nests: comparing methods for assessing diet composition during the breeding season . 22 2.1 Abstract . 22 2.2 Introduction . 23 2.3 Methods . 25 2.4 Results . 29 2.5 Discussion . 34 2.6 Appendix . 38 Chapter 3. Numerical and functional responses of breeding common buzzards on Langholm Moor . 40 3.1 Abstract . 40 3.2 Introduction . 41 3.3 Methods . 44 3.4 Results . 53 3.5 Discussion . 58 3.6 Appendix . 62 Chapter 4. Correlates of common buzzard foraging patterns and relationships with mortality indices of red grouse . 68 4.1 Abstract . 68 4.2 Introduction . 69
The Roles of Annexins and Types II and X Collagen in Matrix Vesicle-mediated Mineralization of Growth Plate Cartilage*

Annexins II, V, and VI are major components of matrix vesicles (MV), i.e. particles that have the critical role of initiating the mineralization process in skeletal tissues. Furthermore, types II and X collagen are associated with MV, and these interactions mediated by annexin V stimulate Ca2+ uptake and mineralization of MV. However, the exact roles of annexin II, V, and VI and the interaction between annexin V and types II and X collagen in MV function and initiation of mineralization are not well understood. In this study, we demonstrate that annexin II, V, or VI mediate Ca2+ influx into phosphatidylserine (PS)-enriched liposomes, liposomes containing lipids extracted from authentic MV, and intact authentic MV. The annexin Ca2+ channel blocker, K-201, not only inhibited Ca2+ influx into fura-2-loaded PS-enriched liposomes mediated by annexin II, V, or VI, but also inhibited Ca2+ uptake by authentic MV. Types II and X collagen only bound to liposomes in the presence of annexin V but not in the presence of annexin II or VI. Binding of these collagens to annexin V stimulated its Ca2+ channel activities, leading to an increased Ca2+ influx into the liposomes. These findings indicate that the formation of annexin II, V, and VI Ca2+ channels in MV together with stimulation of annexin V channel activity by collagen (types II and X) binding can explain how MV are able to rapidly take up Ca2+ and initiate the formation of the first crystal phase.