bluuebunny/crossref_metadata_2025_split huggingface dataset:
La nécropole de Louroux (Creuse)
Authors: Autexier Jean-Yves , Moret Serge , Roche Jean-Louis 
Published: May 2010

La petite nécropole de Louroux, commune de St-Priest-d'Evaux (Creuse) avait déjà livré antérieurement plusieurs ossaria. Les fouilles de 1971-1972, effectuées d'une façon méthodique suivant une technique particulière, ont permis la mise au jour de quatre tombes en coffre cinéraire et de quatre sépultures en fosse, sans coffre ni urne.
Pour chacune d'elles a été examiné systématiquement le matériel céramique (sigillée, mêtallescente, commune), le verre, les clous.
L'étude de ces sépultures lémoviques a permis des séries d'observations, concernant le mobilier et le rituel funéraires, — la signification des clous disposés en couronne autour des coffres, ainsi que la diversité des modes de sépulture et leur datation.
Echanges et frontières : problèmes posés par la fouille d'Argentomagus
Authors: Allain Jacques 
Published: May 2010

L'ampleur et la précocité des importations céramiques, arrétines en particulier, l'abondance du monnayage exogène et spécialement Massaliète, confirment qu'Argentomagus était une importante plateforme d'échanges.
Le volume considérable des scories de forges utilisées pour l'empierrement des voies romaines du voisinage atteste la prééminence des exportations sidérurgiques, historiquement connue.
Comment apprécier la part du Limousin dans l'activité économique d'Argentomagus ? Pour sortir des suppositions gratuites, il faudra par des analyses pétrographiques déterminer si les calcaires importés en Limousin sont berrichons ou poitevins, si les raies d'absorption propres à l'étain de Montebras (Creuse) sont présentes dans les bronzes d'Argentomagus.
Quant à la relative rareté des espèces Lémovices en milieu biturige, elle traduit sans l'expliquer un fait beaucoup plus général.
A propos de l'étude de la céramique recueillie dans la fouille archéologique des habitats médiévaux
Authors: Schweitz Daniel 
Published: May 2010

La céramique recueillie sur les sites d'habitats médiévaux n'est généralement considérée que comme « fossile directeur » pour la datation des stratigraphies. A l'inverse, son importance dans l'équipement domestique est parfois exagérée, principalement du fait de son importance quantitative dans l'ensemble du matériel documentaire archéographique recueilli.
Il parait donc intéressant de souligner quelques-uns des apports et des limites documentaires de son étude en tant qu'élément de la culture matérielle médiévale. L'application des techniques d'étude de sa répartition au sol dans les habitats médiévaux, qui est susceptible de fournir des données documentaires de type « ethnographique » sur son rôle culturel, amène quelques remarques méthodologiques.
99mTc reduziert nach intrazellulärer Aufnahme in NIS-positiven Zellen in vitro das klonogene Überleben stärker als 131I
Authors: Wendisch M. , Freudenberg R. , Drechsel J. , Runge R. , Wunderlich G. , Kotzerke J. 
Published: May 2010

Summary
Aim: In addition to gamma radiation of 140 keV 99mTc emits during the transition to 99Tc electrons of low energy and tiny path-lengths. These Auger electrons cannot be utilized in diagnostic procedures. However, they were discussed frequently for therapeutic application. Hitherto proof of effect of the Auger electrons from 99mTc is missing which is supplied now in an in vitro-system in comparison to beta-emitter 131I. Methods: The thyroid cell line PC Cl3 (sodium iodide symporter (NIS)-positive) was incubated with 131I-sodium iodide (131I) or 99mTc-pertechnetate (99mTc) in presence or absence of perchlorate. For comparison the amount of radioactivity was adjusted to obtain the same dose from extracellular irradiation for both radionuclides. The colony forming assay detects the clonogenic cell survival as surviving fraction. In addition, intracellular radionuclide uptake was quantified. Results: Dose effect curves were established for 131I and 99mTc for variable extra- and intracellular distribution of the radioactivity. In presence of perchlorate no cellular uptake of radioactivity was detectable. Survival curves were largely comparable confirming the dosimetric calculations. In absence of perchlorate cellular radiotracer uptake varied from 1.39% (131I) to 1.90% 99mTc). Effects on survival were twice for the beta-emitter and ten-fold higher for 99mTc. Conclusions: Intracellular uptake of 131I and 99mTc increases DNA-damage compared to strict extracellular radiotracer distribution which was demonstrated by means of colony forming assay. Increasing radiotoxicity from intracellular 99mTc is explained most likely by increased dose deposition in cellular structures due to Auger- and conversion-electrons of low range and high local energy deposition.
Information Transfer through the Spontaneous Baroreflex in Healthy Humans
Authors: Catai A. M. , Takahashi A. C. M. , Magagnin V. , Bassani T. , Tobaldini E. , Montano N. , Porta A. 
Published: May 2010

Summary
Objectives: This study assesses the information transfer through the spontaneous baroreflex (i.e. through the pathway linking systolic arterial pressure to heart period) during an experimental condition soliciting baroreflex (i.e. head-up tilt).
Methods: The information transfer was calculated as the conditional entropy of heart period given systolic arterial pressure using a mutual neighbor approach and uniform quantization. The information transfer was monitored as a function of the forecasting time k.
Results: We found that during head-up tilt the information transfer at k = 0 decreased but the rate of rise of information transfer as a function of k was faster.
Conclusions: We suggest that the characterization of the information transfer from systolic arterial pressure to heart period might complement the traditional characterization of the spontaneous baroreflex based on transfer function analysis.
ML Segmentation Strategies for Object Interference Compensation in FDG-PET Lesion Quantification
Authors: Bernardi E. , Gallotta F. , Gianoli C. , Zito F. , Gerundini P. , Baselli G. 
Published: May 2010

Summary
Background: Quantification of lesion activity by FDG uptake in oncological PET is severely limited by partial volume effects. A maximum likelihood (ML) expectation maximization (EM) algorithm considering regional basis functions (AWOSEM-region) had been previously developed. Regional basis functions are iteratively segmented and quantified, thus identifying the volume and the activity of the lesion.
Objectives: Improvement of AWOSEM-region when analyzing proximal interfering hot objects is addressed by proper segmentation initialization steps and models of spill-out and partial volume effects. Conditions relevant to lung PET-CT studies are considered: 1) lesion close to hot organ (e.g. chest wall, heart and mediastinum), 2) two close lesions.
Methods: CT image was considered for pre-segmenting hot anatomical structures, never for lesion identification, solely defined by iterations on PET data. Further resolution recovery beyond the smooth standard clinical image was necessary to start lesion segmentation. A watershed algorithm was used to separate two close lesions. A subtraction of the spill-out from a nearby hot organ was introduced to enhance a lesion for the initial segmentation and start the further quantification steps. Biograph scanner blurring was modeled from phantom data in order to implement the procedure for 3D clinical lung studies.
Results: In simulations, the procedure was able to separate structures as close as one pixel-size (2.25 mm). Robustness against the input segmentation errors defining the addressed objects was tested showing that convergence was not sensitive to initial volume overestimates up to 130%. Poor robustness was found against underestimates. A clinical study of a small lung lesion close to chest wall displayed a good recovery of both lesion activity and volume.
Conclusions: With proper initialization and models of spill-out from hot organs, AWOSEM-region can be successfully applied to lung oncological studies.
Synaptic Integration
Authors: Etherington Sarah J , Atkinson Susan E , Stuart Greg J , Williams Stephen R 
Published: May 2010

Abstract

Neurons in the brain receive thousands of synaptic inputs from other neurons. Synaptic integration is the term used to describe how neurons ‘add up’ these inputs before the generation of a nerve impulse, or action potential. The ability of synaptic inputs to effect neuronal output is determined by a number of factors, including the size, shape and relative timing of electrical potentials generated by synaptic inputs, the geometric structure of the target neuron, the physical location of synaptic inputs within that structure, as well as the expression of voltage‐gated channels in different regions of the neuronal membrane. The process of synaptic integration is therefore modulated at multiple levels, contributing to the diverse and complex computational powers of the functioning brain.

Key Concepts:

Neurons within a neural network receive information from, and send information to, many other cells, at specialised junctions called synapses.

Synaptic integration is the computational process by which an individual neuron processes its synaptic inputs and converts them into an output signal.

Neurons are specialised for electrical signalling, with the main neuronal input signal (synaptic potentials) and the main neuronal output signal (action potentials) both involving transient changes in the size of the electrical potential across the neuronal membrane.

Synaptic potentials occur when neurotransmitter binds to and opens ligand‐operated channels in the dendritic membrane, allowing ions to move into or out of the cell according to their electrochemical gradient.

Synaptic potentials can be either excitatory (increasing the probability of action potential firing) or inhibitory (reducing the probability of action potential firing) depending on the direction and charge of ion movement.

Action potentials occur if the summed synaptic inputs to a neuron reach a threshold level of depolarisation and trigger regenerative opening of voltage‐gated ion channels.

Synaptic potentials are often brief and of small amplitude, therefore summation of inputs in time (temporal summation) or from multiple synaptic inputs (spatial summation) is usually required to reach action potential firing threshold.

Nonlinear summation of synaptic potentials occurs when a synaptic potential changes the driving force for ion movement and therefore the amplitude of subsequent synaptic potentials.

The impact of a synaptic input on neuronal output depends on its location within the dendritic tree, because synaptic potentials are attenuated as they spread passively through neuronal processes.

Dendritic voltage‐gated ion channels may open or close in response to the membrane potential change during a synaptic potential, thereby altering (amplifying or attenuating) the potential's amplitude or time course.
Cytochrome
c
Oxidase
Authors: Wikström Mårten 
Published: May 2010

Abstract

Cytochrome
c
oxidase

is the key enzyme of cell respiration in all eukaryotes and many prokaryotes. The

cytochrome
c
oxidases

belong to the haem–copper superfamily of structurally and functionally related enzymes; though related in structure, some bacterial variants lack amino acid residues that are known to be obligatory for the function of the members of the main family. All
haem–copper oxidases
have a unique bimetallic active site catalysing reduction of dioxygen (O
2
) to water and an adjacent second haem group that donates electrons to this site. Here, the mechanism of O
2
reduction is reviewed. The membrane‐bound enzyme couples this reaction to translocation of protons across the membrane, and thus functions as a primary energy transducer that contributes to the formation of ATP (adenosine triphosphate) in aerobic life. The most recent knowledge of the function of this ‘proton pump’ is discussed. It is concluded that

cytochrome
c
oxidase

is an electrostatic energy‐transducing machine with high efficiency.

Key Concepts:

Cytochrome
c
oxidase is an electrostatically coupled energy transducer.

The high affinity for O
2
is due to kinetic ligand trapping.

O
2
reduction in cell respiration yields no reactive oxygen species.
Starch and Starch Granules
Authors: Smith Alison M 
Published: May 2010

Abstract

Starch is the main form in which plants store carbon. It occurs as semi‐crystalline granules composed of two polymers of glucose, called amylose and amylopectin. Depending on the plant organ, it can act as a store of carbon for lengths of time as short as a day (e.g. in leaves) or as long as many years (e.g. in dormant seeds). Starch granules are characterised by internal growth rings. There is enormous variation in granule size and shape between plant organs, and between species. Starch is the major carbohydrate of nutritional importance in the diet: it is degraded to glucose by amylases in the mouth and small intestine. When cooked in water, starch forms gels or pastes that have a wide range of industrial applications in both food and nonfood industries.

Key Concepts:

Starch is the main form in which plants store carbon.

Starch occurs as semicrystalline granules, composed of branched and linear polymers of glucose.

Starch granules vary in size and shape between plant organs and between species.

The distinctive morphology and anatomy of starch granules enables the identification of plant remains in food, forensic and archaeological samples.

Starch is the main component of the harvested parts of many crops, including cereals, peas and beans, potatoes and cassava.

Starch is the main carbohydrate of nutritional importance in the human diet.

When cooked in water, starch granules swell to form gels or pastes that are widely used in food and nonfood industries.

Major uses for starch include a thickener in processed foods, and in the manufacture of paper, biodegradable plastics and adhesives.

Starch is often modified after extraction to generate properties desirable for specific industrial purposes: there is interest in breeding new crops in which the native starch already has these properties.
Protein–Ligand Interactions: Thermodynamic Basis and Mechanistic Consequences
Authors: Fisher Harvey F 
Published: May 2010

Abstract

It is difficult to imagine any biological process that is not initiated by the binding of some chemical entity (or ‘ligand’) to a protein. Thus, enzymatic catalysis, signal transduction, ion channel activity, immune responses and the various events involved in genetic expression are all obvious examples of events which, at the molecular level, must begin with the binding of some ligand to a specific binding site on a protein molecule. Furthermore, as each one of these processes proceeds along its reaction pathway, modulation of the affinities of such ligands, positive and negative interactions caused by the binding of other ligands and the release of these ligands either in their original or in altered form constitute obligatory steps in the driving forces and controlling restraints that adapt them to their specific tasks. We extend the basic conceptions set forth in this article to a more detailed level focused on the fundamental nature of ligand–ligand interactions of a protein–ligand complex and the energetic mechanistic consequences to which they lead.

Key Concepts:

Every biological reaction is initiated by a protein–ligand binding step.

Such reactions never involve the binding of only a single ligand or a single step.

The binding of two ligands to the same protein always involves a mutual interaction.

The product of a ligand‐binding reaction is a new entity in itself; its structure and its properties may differ substantially from the simple sum of those of its initial components.

The concept of G Weber's ‘thermodynamic square’ permits the evaluation of a variety of interaction parameters.

Patterns of interaction parameters provide a basis for exploring ligand‐binding energy transduction.

Measurement of ligand‐binding heat by techniques using higher levels of mathematical integration provide more detailed dissection into parameters such as enthalpy, entropy, heat capacity and their corresponding interaction terms.

The ‘fluctuating protein’ concept suggests that protein reactions proceed as multiple traces on multidimensional free‐energy landscapes.

Consequences of the thermodynamic complexity of ligand binding suggest new views of such processes as enzymatic catalysis, signalling events and evolutionary aspects.
Silica
Authors: Perry Carole C 
Published: May 2010

Abstract

The element silicon (Si) is used by all living organisms either in molecular processes or in the formation of the mineral silica. The mineral is found in single cell organisms (e.g. radiolarian, diatoms, dinoflagellates and algae) through molluscs (e.g. limpets) to higher plants and primitive animals such as sponges. It is formed from an environment that is undersaturated with respect to Si and under conditions of around neutral pH and low temperature,
c
. 4–40°C. The mineral can be formed both intra‐ or extracellularly and specific biochemicals involved with mineral deposition include lipids, proteins (including heavily posttranslationally modified proteins), long‐change polyamines and carbohydrates. Knowledge of the complete genome for some species is providing opportunities to uncover the precise mechanisms of element uptake, transport and deposition although much still remains to be understood.

Key Concepts:

Silicon is an essential element for many if not all organisms.

A range of biomolecules/biopolymers are used to control and regulate silica precipitation in the natural environment.

The presence of biogenic silica in an organism confers functional properties on that organism which may include structural/mechanical support and/or defence against biotic or abiotic environmental stresses.

Much remains to be understood in respect of how the element is transported, concentrated and spatially organised within organisms as well as the effect the presence of the element/mineral has on other cellular functions.
Acute Myelogenous Leukaemia
Authors: Lichtman Marshall A 
Published: May 2010

Abstract

Acute myelogenous leukaemia is the result of a malignant transformation of a single primitive multipotential marrow haematopoietic cell, converting it to a leukaemic stem cell. This neoplastic transformation imparts a growth and survival advantage to the cell clone that emerges. Leukaemic cells fill the haematopoietic cords of marrow. The functional result of this alteration is to impair normal blood cell production in the marrow, leading to a profound decrease in normal red cells (anaemia), white cells (leucopaenia) and platelets or thrombocytes (thrombocytopaenia) in the blood. The disease is rapidly progressive, unless treated promptly. Therapy usually consists of at least two drugs, cytosine arabinoside and an anthracycline antibiotic (e.g. daunomycin). The response of the disease to treatment is dependent on several factors but the two most compelling are the age at diagnosis and the cytogenetic and genetic features of the cells with older age and unfavourable chromosomal karyotypes decreasing the proportion of long‐term remissions.

Key Concepts:

Cancer of any type is the result of a series of gene mutations in a single tissue cell.

Acute myelogenous leukaemia, like all cancers, originates in a single tissue cell, in this case within haematopoietic tissue.

The incidence of acute myelogenous leukaemia can be increased by the inheritance of predisposition genes that are unapparent (nonsyndromic familial cases) or apparent as manifest by syndromic cases, such as Fanconi anaemia.

Leukaemic cells accumulate because they have a proliferative and survival advantage compared to normal cells.

It is estimated that approximately one trillion leukaemic cells are present at diagnosis.

Very small proportions of these cells are leukaemic stem cells, which sustain leukaemic haematopoiesis.

Acute myelogenous leukaemia stem cells have multipotential haematopoietic lineage potential. Thus, they can differentiate into leukaemic precursor cells of all haematopoietic lineages. The predominance of one or two leads to the phenotypic classification of acute myelogenous leukaemia (e.g. erythroid, monocytic, megakaryocytic and myelomonocytic).

The accumulation of leukaemic cells in the marrow secondarily suppresses normal blood cell development.

Chemotherapy is predicated on the coexistence of normal haematopoietic stem cells and leukaemic stem cells in the marrow.

Suppression of leukaemic cell accumulation by at least three logs by chemotherapy can, in many cases, result in the release of inhibition of normal stem cells and a return of normal haematopoiesis for a variable time.
Permeabilised Mammalian Cell Systems for Protein Synthesis
Authors: Tavender Timothy J 
Published: May 2010

Abstract

The use of semipermeabilised cells allows the study of complex intracellular processes such as protein translocation, folding, glycosylation, disulfide bond formation and degradation in a system amenable to experimental manipulation. Semipermeabilised cells can be combined with an

in vitro

translation system to synthesise endoplasmic reticulum (ER) targeted proteins from custom made messenger
ribonucleic acid
(mRNA). The ability to manipulate the translated protein means that the effect of changes to the primary amino acid sequence on protein folding and assembly can be readily assessed. Semipermeabilised cells can be prepared from cell lines expressing elevated or diminished levels of ER‐resident proteins and can also be pretreated with chemical modifiers of ER processes. Using such approaches, it is possible to examine the influence of various ER pathways on folding and posttranslational modification of individual secretory proteins.

Key concepts:

Semipermeabilised cells possess an intact, functional endoplasmic reticulum and are free of cytosol and endogenous mRNA.

Secretory proteins translated in the presence of semipermeabilised cells are translocated and posttranslationally modified as in intact cells.

Use of an
in vitro
translation system allows complete user manipulation of translated protein sequences.