Cadmium-free quantum dots in aqueous solution: potential for fingermark detection, synthesis and an application to the detection of fingermarks in blood on non-porous surfaces

The use of quantum dots (QDs) in the area of fingermark detection is currently receiving a lot of attention in the forensic literature. Most of the research efforts have been devoted to cadmium telluride (CdTe) quantum dots often applied as powders to the surfaces of interests. Both the use of cadmium and the nano size of these particles raise important issues in terms of health and safety. This paper proposes to replace CdTe QDs by zinc sulphide QDs doped with copper (ZnS:Cu) to address these issues. Zinc sulphide-copper doped QDs were successfully synthesized, characterized in terms of size and optical properties and optimized to be applied for the detection of impressions left in blood, where CdTe QDs proved to be efficient. Effectiveness of detection was assessed in comparison with CdTe QDs and Acid Yellow 7 (AY7, an effective blood reagent), using two series of depletive blood fingermarks from four donors prepared on four non-porous substrates, i.e. glass, transparent polypropylene, black polyethylene and aluminium foil. The marks were cut in half and processed separately with both reagents, leading to two comparison series (ZnS:Cu vs. CdTe, and ZnS:Cu vs. AY7). ZnS:Cu proved to be better than AY7 and at least as efficient as CdTe on most substrates. Consequently, copper-doped ZnS QDs constitute a valid substitute for cadmium-based QDs to detect blood marks on non-porous substrates and offer a safer alternative for routine use.

Determination of the size of quantum dots by fluorescence spectroscopy.

There has been a lack of quick, simple and reliable methods for determination of nanoparticle size. An investigation of the size of hydrophobic (CdSe) and hydrophilic (CdSe/ZnS) quantum dots was performed by using the maximum position of the corresponding fluorescence spectrum. It has been found that fluorescence spectroscopy is a simple and reliable methodology to estimate the size of both quantum dot types. For a given solution, the homogeneity of the size of quantum dots is correlated to the relationship between the fluorescence maximum position (FMP) and the quantum dot size. This methodology can be extended to the other fluorescent nanoparticles. The employment of evolving factor analysis and multivariate curve resolution-alternating least squares for decomposition of the series of quantum dots fluorescence spectra recorded by a specific measuring procedure reveals the number of quantum dot fractions having different diameters. The size of the quantum dots in a particular group is defined by the FMP of the corresponding component in the decomposed spectrum. These results show that a combination of the fluorescence and appropriate statistical method for decomposition of the emission spectra of nanoparticles may be a quick and trusted method for the screening of the inhomogeneity of their solution.

Toxicity screenings of nanomaterials: challenges due to interference with assay processes and components of classic in vitro tests.

Given the multiplicity of nanoparticles (NPs), there is a requirement to develop screening strategies to evaluate their toxicity. Within the EU-funded FP7 NanoTEST project, a panel of medically relevant NPs has been used to develop alternative testing strategies of NPs used in medical diagnostics. As conventional toxicity tests cannot necessarily be directly applied to NPs in the same manner as for soluble chemicals and drugs, we determined the extent of interference of NPs with each assay process and components. In this study, we fully characterized the panel of NP suspensions used in this project (poly(lactic-co-glycolic acid)-polyethylene oxide [PLGA-PEO], TiO2, SiO2, and uncoated and oleic-acid coated Fe3O4) and showed that many NP characteristics (composition, size, coatings, and agglomeration) interfere with a range of in vitro cytotoxicity assays (WST-1, MTT, lactate dehydrogenase, neutral red, propidium iodide, (3)H-thymidine incorporation, and cell counting), pro-inflammatory response evaluation (ELISA for GM-CSF, IL-6, and IL-8), and oxidative stress detection (monoBromoBimane, dichlorofluorescein, and NO assays). Interferences were assay specific as well as NP specific. We propose how to integrate and avoid interference with testing systems as a first step of a screening strategy for biomedical NPs.

RNA interference screening identifies a novel role for PCTK1/CDK16 in medulloblastoma with c-Myc amplification.

Medulloblastoma (MB) is the most common malignant brain tumor in children and is associated with a poor outcome. cMYC amplification characterizes a subgroup of MB with very poor prognosis. However, there exist so far no targeted therapies for the subgroup of MB with cMYC amplification. Here we used kinome-wide RNA interference screening to identify novel kinases that may be targeted to inhibit the proliferation of c-Myc-overexpressing MB. The RNAi screen identified a set of 5 genes that could be targeted to selectively impair the proliferation of c-Myc-overexpressing MB cell lines: AKAP12 (A-kinase anchor protein), CSNK1α1 (casein kinase 1, alpha 1), EPHA7 (EPH receptor A7) and PCTK1 (PCTAIRE protein kinase 1). When using RNAi and a pharmacological inhibitor selective for PCTK1, we could show that this kinase plays a crucial role in the proliferation of MB cell lines and the activation of the mammalian target of rapamycin (mTOR) pathway. In addition, pharmacological PCTK1 inhibition reduced the expression levels of c-Myc. Finally, targeting PCTK1 selectively impaired the tumor growth of c-Myc-overexpressing MB cells in vivo. Together our data uncover a novel and crucial role for PCTK1 in the proliferation and survival of MB characterized by cMYC amplification.

Toward on-the-fly quantum mechanical/molecular mechanical (QM/MM) docking: development and benchmark of a scoring function.

We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.

Microstructure of the superior longitudinal fasciculus predicts stimulation-induced interference with on-line motor control.

A cortical visuomotor network, comprising the medial intraparietal sulcus (mIPS) and the dorsal premotor area (PMd), encodes the sensorimotor transformations required for the on-line control of reaching movements. How information is transmitted between these two regions and which pathways are involved, are less clear. Here, we use a multimodal approach combining repetitive transcranial magnetic stimulation (rTMS) and diffusion tensor imaging (DTI) to investigate whether structural connectivity in the 'reaching' circuit is associated to variations in the ability to control and update a movement. We induced a transient disruption of the neural processes underlying on-line motor adjustments by applying 1Hz rTMS over the mIPS. After the stimulation protocol, participants globally showed a reduction of the number of corrective trajectories during a reaching task that included unexpected visual perturbations. A voxel-based analysis revealed that participants exhibiting higher fractional anisotropy (FA) in the second branch of the superior longitudinal fasciculus (SLF II) suffered less rTMS-induced behavioral impact. These results indicate that the microstructural features of the white matter bundles within the parieto-frontal 'reaching' circuit play a prominent role when action reprogramming is interfered. Moreover, our study suggests that the structural alignment and cohesion of the white matter tracts might be used as a predictor to characterize the extent of motor impairments.

A comprehensive model for quantum noise characterization in digital mammography.

NlmCategory="UNASSIGNED">A version of cascaded systems analysis was developed specifically with the aim of studying quantum noise propagation in x-ray detectors. Signal and quantum noise propagation was then modelled in four types of x-ray detectors used for digital mammography: four flat panel systems, one computed radiography and one slot-scan silicon wafer based photon counting device. As required inputs to the model, the two dimensional (2D) modulation transfer function (MTF), noise power spectra (NPS) and detective quantum efficiency (DQE) were measured for six mammography systems that utilized these different detectors. A new method to reconstruct anisotropic 2D presampling MTF matrices from 1D radial MTFs measured along different angular directions across the detector is described; an image of a sharp, circular disc was used for this purpose. The effective pixel fill factor for the FP systems was determined from the axial 1D presampling MTFs measured with a square sharp edge along the two orthogonal directions of the pixel lattice. Expectation MTFs were then calculated by averaging the radial MTFs over all possible phases and the 2D EMTF formed with the same reconstruction technique used for the 2D presampling MTF. The quantum NPS was then established by noise decomposition from homogenous images acquired as a function of detector air kerma. This was further decomposed into the correlated and uncorrelated quantum components by fitting the radially averaged quantum NPS with the radially averaged EMTF(2). This whole procedure allowed a detailed analysis of the influence of aliasing, signal and noise decorrelation, x-ray capture efficiency and global secondary gain on NPS and detector DQE. The influence of noise statistics, pixel fill factor and additional electronic and fixed pattern noises on the DQE was also studied. The 2D cascaded model and decompositions performed on the acquired images also enlightened the observed quantum NPS and DQE anisotropy.