An entire 1-kilobit crossbar device based upon SiOx resistive memories with integrated diodes has been made. The SiOx -based one diode-one resistor device system has promise to satisfy the prerequisite conditions for next generation non-volatile memory applications.
Tissue microarrays were originally developed to enable alignment of multiple tissue cores in a single paraffin block and to enable high-throughput laboratory analysis. However, a major drawback is the loss of tissue cores during slide preparation, especially when sectioning the tissue block. Tissue cylinders directly aligned in the metal box without preheating tend to detach from the surrounding paraffin, which results in incomplete or folded tissue sections. The proposed solution is preheating all tissue cylinders on a hot plate to facilitate fusion between the paraffin within the core and the paraffin surrounding the core. In this study, 6 tissue microarray blocks were constructed from 528 tissue cores extracted from various formalin-fixed, paraffin-embedded human tissue samples. The tissue cores in the arrays revealed good homogenization with the surrounding paraffin wax, and the tissue sections were obtained intact. Both hematoxylin-eosin and immunohistochemical staining confirmed satisfactory results. This simple and economical method is easily performed in the laboratory without expensive instrumentation.
A microfabricated platform was developed for highly parallel and efficient colony picking, splitting and clone identification. A pallet array provided patterned cell colonies which mated to a second printing array composed of bridging microstructures formed by a supporting base and attached post. The posts enabled mammalian cells from colonies initially cultured on the pallet array to migrate to corresponding sites on the printing array. Separation of the arrays simultaneously split the colonies creating a patterned replica. Optimization of array elements provided transfer efficiencies greater than 90% using bridging posts of 30 µm diameter and 100 µm length and total colony numbers of 3000. Studies using five mammalian cell lines demonstrated that a variety of adherent cell types could be cultured and effectively split with printing efficiencies of 78-92%. To demonstrate the technique’s utility, clonal cell lines with siRNA knockdown of Coronin 1B were generated using the arrays and compared to a traditional FACS/Western Blotting-based approach. Identification of target clones required a destructive assay to identify cells with an absence of Coronin 1B brought about by the successful infection of interfering shRNA construct. By virtue of miniaturization and its parallel format, the platform enabled the identification and generation of 12 target clones from a starting sample of only 3900 cells and required only 5-man hours over 11 days. In contrast, the traditional method required 500,000 cells and generated only 5 target clones with 34-man hours expended over 47 days. These data support the considerable reduction in time, manpower and reagents using the miniaturized platform for clonal selection by destructive assay versus conventional approaches.
The purpose of this study was to develop novel dissolving microneedle arrays fabricated from hyaluronic acid (HA) as a material and to improve the transdermal permeability of relatively high molecular weight drugs. In this study, fluorescein isothiocyanate-labeled dextran with an average molecular weight of 4 kDa (FD4) was used as a model drug with a relatively high molecular weight. The microneedle arrays significantly increased transepidermal water loss (TEWL) and reduced transcutaneous electrical resistance (TER), indicating that they could puncture the skin and create drug permeation pathways successfully. Both TEWL and TER almost recovered to baseline levels in the microneedle array group, and relatively small pathways created by the microneedles rapidly recovered as compared with those created by a tape stripping treatment. These findings confirmed that the microneedle arrays were quite safe. Furthermore, we found that the transdermal permeability of FD4 using the microneedle arrays was much higher than that of the FD4 solution. Furthermore, we found that the microneedle arrays were much more effective for increasing the amount of FD4 accumulated in the skin. These findings indicated that using novel microneedle arrays fabricated from HA is a very useful and effective strategy to improve the transdermal delivery of drugs, especially relatively high molecular weight drugs without seriously damaging the skin.
Identification of Transcription factors and Co-activators Affected by Dibutyl Phthalate Interactions in Fetal Rat Testes
- Toxicological sciences : an official journal of the Society of Toxicology
- Published almost 5 years ago
Previous analysis of in utero dibutylphthalate (DBP)-exposed fetal rat testes indicated that DBP’s anti-androgenic effects were mediated in part by indirect inhibition of SF1 suggesting that PPARα might be involved through coactivtor (CBP) sequestration. To test this hypothesis we have performed ChIP microarray analysis to assess the DNA-binding of PPARα, SF1, CBP and RNApol11 in dibutylphthalate-induced testicular mal-development target genes. Pathways analysis of expression array data in fetal rat testes examined at GD15, 17 or 19 indicated lipid metabolism genes regulated by SF1 and PPARα, respectively, were over-represented and the time-dependency of changes to PPARα-regulated lipid metabolism genes correlated with DBP-mediated repression of SF1-regulated steroidogenesis genes. ChIP microarrays were used to investigate whether DBP-mediated repression of SF1-regulated genes was associated with changes in SF1 binding to genes involved in dibutylphthalate-induced testicular mal-development. DBP-treatment caused reductions in SF1 binding in CYP11a, StAR and CYP17a. FSHR, regulated by SF1 but unaffected by DBP-treatment, also contained SF1 binding peaks, but DBP did not change this compared to control. GD15 and GD19 fetal testes contained PPARα protein-binding peaks in CYP11a, StAR and CYP17a regulatory regions. In contrast to its repressive effect on SF1, DBP-treatment caused increases in these peaks compared to control. PPARα binding-peaks in the FSHR promoter were not detected in GD15 samples. Hence the repressive effect of DBP on SF1 regulated steroidogenic genes correlates with inhibition of SF1-DNA binding and increased PPARα-DNA binding. The data indicate that PPARα may act as an indirect transrepressor of SF-1 on steroidogenic genes in fetal rat testes in response to DBP treatment.
The ability to fabricate nanoscale domains of uniform size in two-dimensional materials could potentially enable new applications in nanoelectronics and the development of innovative metamaterials. However, achieving even minimal control over the growth of two-dimensional lateral heterostructures at such extreme dimensions has proven exceptionally challenging. Here we show the spontaneous formation of ordered arrays of graphene nano-domains (dots), epitaxially embedded in a two-dimensional boron-carbon-nitrogen alloy. These dots exhibit a strikingly uniform size of 1.6 ± 0.2 nm and strong ordering, and the array periodicity can be tuned by adjusting the growth conditions. We explain this behaviour with a model incorporating dot-boundary energy, a moiré-modulated substrate interaction and a long-range repulsion between dots. This new two-dimensional material, which theory predicts to be an ordered composite of uniform-size semiconducting graphene quantum dots laterally integrated within a larger-bandgap matrix, holds promise for novel electronic and optoelectronic properties, with a variety of potential device applications.The nanoscale patterning of two-dimensional materials offers the possibility of novel optoelectronic properties; however, it remains challenging. Here, Camilli et al. show the self-assembly of large arrays of highly-uniform graphene dots imbedded in a BCN matrix, enabling novel devices.
Highly mineralized natural materials such as teeth or mollusk shells boast unusual combinations of stiffness, strength and toughness currently unmatched by engineering materials. While high mineral contents provide stiffness and hardness, these materials also contain weaker interfaces with intricate architectures, which can channel propagating cracks into toughening configurations. Here we report the implementation of these features into glass, using a laser engraving technique. Three-dimensional arrays of laser-generated microcracks can deflect and guide larger incoming cracks, following the concept of ‘stamp holes’. Jigsaw-like interfaces, infiltrated with polyurethane, furthermore channel cracks into interlocking configurations and pullout mechanisms, significantly enhancing energy dissipation and toughness. Compared with standard glass, which has no microstructure and is brittle, our bio-inspired glass displays built-in mechanisms that make it more deformable and 200 times tougher. This bio-inspired approach, based on carefully architectured interfaces, provides a new pathway to toughening glasses, ceramics or other hard and brittle materials.
We propose and demonstrate a novel physical computing paradigm based on an engineered unipolar memristor that exhibits symmetric SET switching with respect to voltage polarity. A one-dimensional array of these devices was sufficient to demonstrate an efficient Hamming distance comparator for two strings of analog states represented by voltages from the physical world. The comparator first simultaneously applies the two sets of voltages to the array of memristors, each of which is initially in its high resistance state and switches to its low resistance state only if the two voltages applied on that memristor differ by more than the switching threshold. An accurate analog representation of the Hamming distance is then obtained by applying a reading voltage to the memristors and summing all the resultant currents. The comparator with a small footprint can directly process analog signals and store computation results without power, representing a promising application for analog computing based on memristor crossbar arrays.
Autoantibodies against cytokines, chemokines, and growth factors inhibit normal immunity and are implicated in inflammatory autoimmune disease and diseases of immune deficiency. In an effort to evaluate serum from autoimmune and immunodeficient patients for Abs against cytokines, chemokines, and growth factors in a high-throughput and unbiased manner, we constructed a multiplex protein microarray for detection of serum factor-binding Abs and used the microarray to detect autoantibody targets in SLE. We designed a nitrocellulose-surface microarray containing human cytokines, chemokines, and other circulating proteins and demonstrated that the array permitted specific detection of serum factor-binding probes. We used the arrays to detect previously described autoantibodies against cytokines in samples from individuals with autoimmune polyendocrine syndrome type 1 and chronic mycobacterial infection. Serum profiling from individuals with SLE revealed that among several targets, elevated IgG autoantibody reactivity to B cell-activating factor (BAFF) was associated with SLE compared with control samples. BAFF reactivity correlated with the severity of disease-associated features, including IFN-α-driven SLE pathology. Our results showed that serum factor protein microarrays facilitate detection of autoantibody reactivity to serum factors in human samples and that BAFF-reactive autoantibodies may be associated with an elevated inflammatory disease state within the spectrum of SLE.
The current rapid growth of Internet of Things (IoT) in various commercial and non-commercial sectors has led to the deposition of large-scale IoT data, of which the time-critical analytic and clustering of knowledge granules represent highly thought-provoking application possibilities. The objective of the present work is to inspect the structural analysis and clustering of complex knowledge granules in an IoT big-data environment. In this work, we propose a knowledge granule analytic and clustering (KGAC) framework that explores and assembles knowledge granules from IoT big-data arrays for a business intelligence (BI) application. Our work implements neuro-fuzzy analytic architecture rather than a standard fuzzified approach to discover the complex knowledge granules. Furthermore, we implement an enhanced knowledge granule clustering (e-KGC) mechanism that is more elastic than previous techniques when assembling the tactical and explicit complex knowledge granules from IoT big-data arrays. The analysis and discussion presented here show that the proposed framework and mechanism can be implemented to extract knowledge granules from an IoT big-data array in such a way as to present knowledge of strategic value to executives and enable knowledge users to perform further BI actions.