Nanoroughness, Surface Chemistry and Drug Delivery Control by Atmospheric Plasma Jet on Implantable Devices

Implantable devices need specific tailored surface morphologies and chemistries to interact with the living systems or to actively induce a biological response also by the release of drugs or proteins. These customised requirements foster technologies that can be implemented in additive manufacturing systems. Here we present a novel approach based on spraying processes that allows to control separately topographic features in the submicron range ( 3d 60 nm - 2 \ub5m), ammine or carboxylic chemistry and fluorophore release even on temperature sensitive biodegradable polymers such as polycaprolactone (PCL). We developed a two-steps process with a first deposition of 220 nm silica and poly(lactic-co-glycolide) (PLGA) fluorescent nanoparticles by aerosol followed by the deposition of a fixing layer by atmospheric pressure plasma jet (APPJ). The nanoparticles can be used to create the nano-roughness and to include active molecule release, while the capping layer ensures stability and the chemical functionalities. The process is enabled by a novel APPJ which allows deposition rates of 10 - 20 nm\ub7s-1 at temperatures lower than 50 \ub0C using argon as process gas. This approach was assessed on titanium alloys for dental implants and on PCL films. The surfaces were characterized by FT-IR, AFM and SEM. Titanium alloys were tested with pre-osteoblasts murine cells line, while PCL film with fibroblasts. Cell behaviour was evaluated by viability and adhesion assays, protein adsorption, cell proliferation, focal adhesion formation and SEM. The release of a fluorophore molecule was assessed in the cell growing media, simulating a drug release. Osteoblast adhesion on the plasma treated materials increased by 20% with respect to commercial titanium alloys implants. Fibroblast adhesion increased by a 100% compared to smooth PCL substrate. The release of the fluorophore by the dissolution of the PLGA nanoparticles was verified and the integrity of the encapsulated drug model confirmed

In-memory eigenvector computation in time O(1)

In-memory computing with crosspoint resistive memory arrays has gained enormous attention to accelerate the matrix-vector multiplication in the computation of data-centric applications. By combining a crosspoint array and feedback amplifiers, it is possible to compute matrix eigenvectors in one step without algorithmic iterations. In this work, time complexity of the eigenvector computation is investigated, based on the feedback analysis of the crosspoint circuit. The results show that the computing time of the circuit is determined by the mismatch degree of the eigenvalues implemented in the circuit, which controls the rising speed of output voltages. For a dataset of random matrices, the time for computing the dominant eigenvector in the circuit is constant for various matrix sizes, namely the time complexity is O(1). The O(1) time complexity is also supported by simulations of PageRank of real-world datasets. This work paves the way for fast, energy-efficient accelerators for eigenvector computation in a wide range of practical applications.Comment: Accepted by Adv. Intell. Sys

Time complexity of in-memory solution of linear systems

In-memory computing with crosspoint resistive memory arrays has been shown to accelerate data-centric computations such as the training and inference of deep neural networks, thanks to the high parallelism endowed by physical rules in the electrical circuits. By connecting crosspoint arrays with negative feedback amplifiers, it is possible to solve linear algebraic problems such as linear systems and matrix eigenvectors in just one step. Based on the theory of feedback circuits, we study the dynamics of the solution of linear systems within a memory array, showing that the time complexity of the solution is free of any direct dependence on the problem size N, rather it is governed by the minimal eigenvalue of an associated matrix of the coefficient matrix. We show that, when the linear system is modeled by a covariance matrix, the time complexity is O(logN) or O(1). In the case of sparse positive-definite linear systems, the time complexity is solely determined by the minimal eigenvalue of the coefficient matrix. These results demonstrate the high speed of the circuit for solving linear systems in a wide range of applications, thus supporting in-memory computing as a strong candidate for future big data and machine learning accelerators.Comment: Accepted by IEEE Trans. Electron Devices. The authors thank Scott Aaronson for helpful discussion about time complexit

Physical–chemical properties of biogenic selenium nanostructures produced by Stenotrophomonas maltophilia SeITE02 and Ochrobactrum sp. MPV1

Stenotrophomonas maltophilia SeITE02 and Ochrobactrum sp. MPV1 were isolated from the rhizosphere soil of the selenium-hyperaccumulator legume Astragalus bisulcatus and waste material from a dumping site for roasted pyrites, respectively. Here, these bacterial strains were studied as cell factories to generate selenium-nanostructures (SeNS) under metabolically controlled growth conditions. Thus, a defined medium (DM) containing either glucose or pyruvate as carbon and energy source along with selenite (www.frontiersin.org) was tested to evaluate bacterial growth, oxyanion bioconversion and changes occurring in SeNS features with respect to those generated by these strains grown on rich media. Transmission electron microscopy (TEM) images show extra- or intra-cellular emergence of SeNS in SeITE02 or MPV1 respectively, revealing the presence of two distinct biological routes of SeNS biogenesis. Indeed, the stress exerted by www.frontiersin.org upon SeITE02 cells triggered the production of membrane vesicles (MVs), which surrounded Se-nanoparticles (SeNPsSeITE02-G_e and SeNPsSeITE02-P_e with average diameter of 179 ± 56 and 208 ± 60 nm, respectively), as highlighted by TEM and scanning electron microscopy (SEM), strongly suggesting that MVs might play a crucial role in the excreting mechanism of the SeNPs in the extracellular environment. On the other hand, MPV1 strain biosynthesized intracellular inclusions likely containing hydrophobic storage compounds and SeNPs (123 ± 32 nm) under pyruvate conditioning, while the growth on glucose as the only source of carbon and energy led to the production of a mixed population of intracellular SeNPs (118 ± 36 nm) and nanorods (SeNRs; average length of 324 ± 89). SEM, fluorescence spectroscopy, and confocal laser scanning microscopy (CLSM) revealed that the biogenic SeNS were enclosed in an organic material containing proteins and amphiphilic molecules, possibly responsible for the high thermodynamic stability of these nanomaterials. Finally, the biogenic SeNS extracts were photoluminescent upon excitation ranging from 380 to 530 nm, whose degree of fluorescence emission (λem = 416–640 nm) was comparable to that from chemically synthesized SeNPs with L-cysteine (L-cys SeNPs). This study offers novel insights into the formation, localization, and release of biogenic SeNS generated by two different Gram-negative bacterial strains under aerobic and metabolically controlled growth conditions. The work strengthens the possibility of using these bacterial isolates as eco-friendly biocatalysts to produce high quality SeNS targeted to possible biomedical applications and other biotechnological purposes

Integration profile of retroviral vector in gene therapy treated patients is cell-specific according to gene expression and chromatin conformation of target cell

The analysis of genomic distribution of retroviral vectors is a powerful tool to monitor ‘vector-on-host’ effects in gene therapy (GT) trials but also provides crucial information about ‘host-on-vector’ influences based on the target cell genetic and epigenetic state. We had the unique occasion to compare the insertional profile of the same therapeutic moloney murine leukemia virus (MLV) vector in the context of the adenosine deaminase-severe combined immunodeficiency (ADA-SCID) genetic background in two GT trials based on infusions of transduced mature lymphocytes (peripheral blood lymphocytes, PBL) or a single infusion of haematopoietic stem/progenitor cells (HSC). We found that vector insertions are cell-specific according to the differential expression profile of target cells, favouring, in PBL-GT, genes involved in immune system and T-cell functions/pathways as well as T-cell DNase hypersensitive sites, differently from HSC-GT. Chromatin conformations and histone modifications influenced integration preferences but we discovered that only H3K27me3 was cell-specifically disfavoured, thus representing a key epigenetic determinant of cell-type dependent insertion distribution. Our study shows that MLV vector insertional profile is cell-specific according to the genetic/chromatin state of the target cell both in vitro and in vivo in patients several years after GT

miRNA Signatures in Sera of Patients with Active Pulmonary Tuberculosis.

Several studies showed that assessing levels of specific circulating microRNAs (miRNAs) is a non-invasive, rapid, and accurate method for diagnosing diseases or detecting alterations in physiological conditions. We aimed to identify a serum miRNA signature to be used for the diagnosis of tuberculosis (TB). To account for variations due to the genetic makeup, we enrolled adults from two study settings in Europe and Africa. The following categories of subjects were considered: healthy (H), active pulmonary TB (PTB), active pulmonary TB, HIV co-infected (PTB/HIV), latent TB infection (LTBI), other pulmonary infections (OPI), and active extra-pulmonary TB (EPTB). Sera from 10 subjects of the same category were pooled and, after total RNA extraction, screened for miRNA levels by TaqMan low-density arrays. After identification of "relevant miRNAs", we refined the serum miRNA signature discriminating between H and PTB on individual subjects. Signatures were analyzed for their diagnostic performances using a multivariate logistic model and a Relevance Vector Machine (RVM) model. A leave-one-out-cross-validation (LOOCV) approach was adopted for assessing how both models could perform in practice. The analysis on pooled specimens identified selected miRNAs as discriminatory for the categories analyzed. On individual serum samples, we showed that 15 miRNAs serve as signature for H and PTB categories with a diagnostic accuracy of 82% (CI 70.2-90.0), and 77% (CI 64.2-85.9) in a RVM and a logistic classification model, respectively. Considering the different ethnicity, by selecting the specific signature for the European group (10 miRNAs) the diagnostic accuracy increased up to 83% (CI 68.1-92.1), and 81% (65.0-90.3), respectively. The African-specific signature (12 miRNAs) increased the diagnostic accuracy up to 95% (CI 76.4-99.1), and 100% (83.9-100.0), respectively. Serum miRNA signatures represent an interesting source of biomarkers for TB disease with the potential to discriminate between PTB and LTBI, but also among the other categories

Parameter space exploration within dynamic simulations of signaling networks

n/

The global emergency of novel coronavirus (SARS-CoV-2). An update of the current status and forecasting

Over the past two decades, there have been two major outbreaks where the crossover of animal Betacoronaviruses to humans has resulted in severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). In December 2019, a global public health concern started with the emergence of a new strain of coronavirus (SARS-CoV-2 or 2019 novel coronavirus, 2019-nCoV) which has rapidly spread all over the world from its origin in Wuhan, China. SARS-CoV-2 belongs to the Betacoronavirus genus, which includes human SARS-CoV, MERS and two other human coronaviruses (HCoVs), HCoV-OC43 and HCoV-HKU1. The fatality rate of SARS-CoV-2 is lower than the two previous coronavirus epidemics, but it is faster spreading and the large number of infected people with severe viral pneumonia and respiratory illness, showed SARS-CoV-2 to be highly contagious. Based on the current published evidence, herein we summarize the origin, genetics, epidemiology, clinical manifestations, preventions, diagnosis and up to date treatments of SARS-CoV-2 infections in comparison with those caused by SARS-CoV and MERS-CoV. Moreover, the possible impact of weather conditions on the transmission of SARS-CoV-2 is also discussed. Therefore, the aim of the present review is to reconsider the two previous pandemics and provide a reference for future studies as well as therapeutic approaches

Resistive Switching Device Technology Based on Silicon Oxide for Improved ON-OFF Ratio--Part II: Select Devices

The cross-point architecture for memory arrays is widely considered as one of the most attractive solutions for storage and memory circuits thanks to simplicity, scalability, small cell size, and consequently high density and low cost. Cost-scalable vertical 3-D cross-point architectures, in particular, offer the opportunity to challenge Flash memory with comparable density and cost. To develop scalable cross-point arrays, however, select devices with sufficient ON-OFF ratio, current capability, and endurance must be available. This paper presents a select device technology based on volatile resistive switching with Cu and Ag top electrode and silicon oxide (SiOₓ) switching materials. The select device displays ultrahigh resistance window and good current capability exceeding 2 MAcm⁻². Retention study shows a stochastic voltage-dependent ON-OFF transition time in the 10 μs-1 ms range, which needs to be further optimized for fast memory operation in storage class memory arrays