Identification of spatial PH quintic Hermite interpolants with near-optimal shape measures

The problem of specifying the two free parameters that arise in spatial Pythagorean-hodograph (PH) quintic interpolants to given first-order Hermite data is addressed. Conditions on the data that identify when the “ordinary” cubic interpolant becomes a PH curve are formulated, since it is desired that the selection procedure should reproduce such curves whenever possible. Moreover, it is shown that the arc length of the interpolants depends on only one of the parameters, and that four (general) helical PH quintic interpolants always exist, corresponding to extrema of the arc length. Motivated by the desire to improve the fairness of interpolants to general data at reasonable computational cost, three selection criteria are proposed. The first criterion is based on minimizing a bivariate function that measures how “close” the PH quintic interpolants are to a PH cubic. For the second criterion, one of the parameters is fixed by first selecting interpolants of extremal arc length, and the other parameter is then determined by minimizing the distance measure of the first method, considered as a univariate function. The third method employs a heuristic but efficient procedure to select one parameter, suggested by the circumstances in which the “ordinary” cubic interpolant is a PH curve, and the other parameter is then determined as in the second method. After presenting the theory underlying these three methods, a comparison of empirical results from their implementation is described, and recommendations for their use in practical design applications are made.     

Color changes in architectural limestones from pollution and cleaning

This article investigates the impact of sulfur dioxide attack, deposition of dark particles in urban environments and laser cleaning with Nd:YAG 1064 nm on color change in a range of ornamental limestones. We have used the CIELAB and CIELCH systems to compare the relative importance of the variation of each coordinate for the color change. Sulfur dioxide and dark particle deposition seems to increase the chroma, most particularly in the yellow component. Particle deposition also leads to an obvious darkening of stone surfaces. Laser irradiation at 1064 nm affects the red component of limestone, particularly if they already possess a reddish color. In general, the more intense the original color of the stone the greater are the chromatic changes, but the direction change of the color‐parameter affected by a particular process remains the same. It has always been apparent in an atmosphere heavily polluted with soot that the main changes to light‐colored stones are the exponential decrease in the parameter L* (darkening–blackening). This has important aesthetic and social implications. However, in the near future it may be that in cleaner atmospheres, perhaps more dominated by organic pollutants, a yellowing process may be of greater concern. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 320–331, 2007     

Physical,Chemical, and Biological Characterization of Veiled Extra Virgin Olive Oil Turbidity for Degradation Risk Assessment

Six different 300 kg batches of olive fruits are processed and the resulting six 20 kg batches of oil are collected at the end of the “decanter.” These batches of oil are subjected to four different water and solid particle separation treatments so as to obtain the following oil samples: veiled oil, filtered oil, “solid particle‐only” oil, and “water‐only” oil. The applied separation treatments show that water content has an important role in the degree of turbidity. High water content values (>0.2% w/w) are related to water activity values of >0.6 which are suitable for chemical and enzymatic reactions. The veiled oil samples are contaminated by microorganisms, but non‐proportional behavior occurs between the microbial cell count and the water and solid particle contents. Practical Applications: The results of this study recommend a multi‐approach method to characterize turbidity, based on control markers such as the degree of turbidity, water content and water activity, solid particle content, microbial contamination, and phenolic compound content. In this way, each degree of turbidity can be associated with a different level of risk of veiled extra virgin olive oil degradation during shelf life.     

Innovation and market structure in the dynamics of the pharmaceutical industry and biotechnology: towards a history-friendly model

This paper is a first attempt at modelling the long-term dynamicsof market structure and innovation in the pharmaceutical industryin a history-friendly way. The model examines the relationshipsbetween the nature of the search space, demand, the patternsof competition, and industry evolution in the age of randomscreening and in the age of molecular biology, and shows thatconcentration in the pharmaceutical industry is shaped by lackof cumulativeness in innovative activities and market fragmentation.The model conforms to our appreciative understanding and respondsto changes in parameters concerning demand, costs, economiesof scale, opportunity conditions and the relative advantagesof new biotechnology firms (NBFs) vis-à-vis incumbents.With the exception of cost increases, the model is quite robustto these changes in its essential features: it is quite difficultto raise substantially concentration and to have NBFs displacingincumbents.     

Volatile components of artemisia vallesiaca all. (Mountain wormwood)

Summary The essential oil obtained by steam distillation of the leaves and flowers ofArtemisia vallesiaca All., a plant widely employed in the liqueur making industry and of almost completely unknown chemical composition, after separation on a silica gel column, was investigated by means of GLC, IR and mass spectrometry. Camphene, 1,8-cineole, camphor and borneol accounted for 67–68% of the oil. Over one hundred minor compounds were found by capillary gas chromatography and 52 were identified (Table 1).

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Die flüchtigen Aromastoffe von Artemisia vallesiaca All. (Berg-Genippi)

Zusammenfassung Das ätherische Öl — erhalten durch Wasserdampfdistillation aus Blättern und Blüten derArtemisia vallesiaca All., einer Pflanze, die in der Wermut-und Likörproduktion viel verwendet wird, aber chemisch fast unbekannt ist — wurde nach Säulenchromatographie an Kieselgel analysiert mittels GLC, IR und GLC-MS. Camphen, 1,8-Cineol, Campher und Borneol bilden 67–68% des ätherischen Öl. Mehr als 100 weitere Bestandteile wurden durch GLC gefunden und 52 von diesen wurden identifiziert (Tabelle 1).

     

Anticancer agents that counteract tumor glycolysis

Can we consider cancer to be a “metabolic disease”? Tumors are the result of a metabolic selection, forming tissues composed of heterogeneous cells that generally express an overactive metabolism as a common feature. In fact, cancer cells have increased needs for both energy and biosynthetic intermediates to support their growth and invasiveness. However, their high proliferation rate often generates regions that are insufficiently oxygenated. Therefore, their carbohydrate metabolism must rely mostly on a glycolytic process that is uncoupled from oxidative phosphorylation. This metabolic switch, also known as the Warburg effect, constitutes a fundamental adaptation of tumor cells to a relatively hostile environment, and supports the evolution of aggressive and metastatic phenotypes. As a result, tumor glycolysis may constitute an attractive target for cancer therapy. This approach has often raised concerns that antiglycolytic agents may cause serious side effects toward normal cells. The key to selective action against cancer cells can be found in their hyperbolic addiction to glycolysis, which may be exploited to generate new anticancer drugs with minimal toxicity. There is growing evidence to support many glycolytic enzymes and transporters as suitable candidate targets for cancer therapy. Herein we review some of the most relevant antiglycolytic agents that have been investigated thus far for the treatment of cancer.     

MicroRNAs as Innovative Biomarkers for Inflammatory Bowel Disease and Prediction of Colorectal Cancer

Inflammatory bowel disease (IBD) includes ulcerative colitis (UC) and Crohn’s disease (CD). These are autoimmune diseases of the gastrointestinal tract with a chronic relapsing and remitting course. Due to complex interactions between multiple factors in the etiology of IBD, the discovery of new predictors of disease course and response to therapy, and the development of effective therapies is a significant challenge. The dysregulation of microRNAs (miRNAs), a class of conserved endogenous, small non-coding RNA molecules with a length of 18–25 nucleotides, that regulate gene expression by an RNA interference process, is implicated in the complex pathogenetic context of IBD. Both tissue-derived, circulating, and fecal microRNAs have been explored as promising biomarkers in the diagnosis and the prognosis of disease severity of IBD. In this review, we summarize the expressed miRNA profile in blood, mucosal tissue, and stool and highlight the role of miRNAs as biomarkers with potential diagnostic and therapeutic applications in ulcerative colitis and Crohn’s disease. Moreover, we discuss the new perspectives in developing a new screening model for the detection of colorectal cancer (CRC) based on fecal miRNAs.     

Semi-supervised classification based on random subspace dimensionality reduction

Graph structure is vital to graph based semi-supervised learning. However, the problem of constructing a graph that reflects the underlying data distribution has been seldom investigated in semi-supervised learning, especially for high dimensional data. In this paper, we focus on graph construction for semi-supervised learning and propose a novel method called Semi-Supervised Classification based on Random Subspace Dimensionality Reduction, SSC-RSDR in short. Different from traditional methods that perform graph-based dimensionality reduction and classification in the original space, SSC-RSDR performs these tasks in subspaces. More specifically, SSC-RSDR generates several random subspaces of the original space and applies graph-based semi-supervised dimensionality reduction in these random subspaces. It then constructs graphs in these processed random subspaces and trains semi-supervised classifiers on the graphs. Finally, it combines the resulting base classifiers into an ensemble classifier. Experimental results on face recognition tasks demonstrate that SSC-RSDR not only has superior recognition performance with respect to competitive methods, but also is robust against a wide range of values of input parameters.     

Radiosensitizing Effect of Trabectedin on Human Soft Tissue Sarcoma Cells

Trabectedin is used for the treatment of advanced soft tissue sarcomas (STSs). In this study, we evaluated if trabectedin could enhance the efficacy of irradiation (IR) by increasing the intrinsic cell radiosensitivity and modulating tumor micro-environment in fibrosarcoma (HS 93.T), leiomyosarcoma (HS5.T), liposarcoma (SW872), and rhabdomyosarcoma (RD) cell lines. A significant reduction in cell surviving fraction (SF) following trabectedin + IR compared to IR alone was observed in liposarcoma and leiomyosarcoma (enhancement ratio at 50%, ER50: 1.45 and 2.35, respectively), whereas an additive effect was shown in rhabdomyosarcoma and fibrosarcoma. Invasive cells’ fraction significantly decreased following trabectedin ± IR compared to IR alone. Differences in cell cycle distribution were observed in leiomyosarcoma and rhabdomyosarcoma treated with trabectedin + IR. In all STS lines, trabectedin + IR resulted in a significantly higher number of γ-H2AX (histone H2AX) foci 30 min compared to the control, trabectedin, or IR alone. Expression of ATM, RAD50, Ang-2, VEGF, and PD-L1 was not significantly altered following trabectedin + IR. In conclusion, trabectedin radiosensitizes STS cells by affecting SF (particularly in leiomyosarcoma and liposarcoma), invasiveness, cell cycle distribution, and γ-H2AX foci formation. Conversely, no synergistic effect was observed on DNA damage repair, neoangiogenesis, and immune system.     

Circulating Endothelial Cells: A New Possible Marker of Endothelial Damage in Kawasaki Disease,Multisystem Inflammatory Syndrome in Children and Acute SARS-CoV-2 Infection

Background: Kawasaki Disease (KD) and Multisystem Inflammatory Syndrome in Children (MIS-C) are pediatric diseases characterized by systemic inflammation and vascular injury, potentially leading to coronary artery lesions (CALs). Data on vascular injury occurring during acute COVID-19 (AC19) in children are still lacking. The aim of our study was to investigate endothelial injury in KD-, MIS-C- and AC19-dosing circulating endothelial cells (CECs). Methods: We conducted a multicenter prospective study. CECs were enumerated by CellSearch technology through the immunomagnetic capture of CD146-positive cells from whole blood. Results: We enrolled 9 KD, 20 MIS-C and 10 AC19. During the acute stage, the AC19 and KD patients had higher CECs levels than the MIS-C patients. From the acute to subacute phase, a significant CEC increase was observed in the KD patients, while a mild decrease was detected in the MIS-C patients. Cellular clusters/syncytia were more common in the KD patients. No correlation between CECs and CALs were found in the MIS-C patients. The incidence of CALs in the KD group was too low to investigate this correlation. Conclusions: Our study suggests a possible role of CECs as biomarkers of systemic inflammation and endothelial dysfunction in KD and MIS-C and different mechanisms of vascular injury in these diseases. Further larger studies are needed.