Design and Characterization of New Luminescent Sensors and Labels

The aim of this Ph.D. project has been the design and characterization of new and more efficient luminescent tools, in particular sensors and labels, for analytical chemistry, medical diagnostics and imaging. Actually both the increasing temporal and spatial resolutions that are demanded by those branches, coupled to a sensitivity that is required to reach the single molecule resolution, can be provided by the wide range of techniques based on luminescence spectroscopy. As far as the development of new chemical sensors is concerned, as chemists we were interested in the preparation of new, efficient, sensing materials. In this context, we kept developing new molecular chemosensors, by exploiting the supramolecular approach, for different classes of analytes. In particular we studied a family of luminescent tetrapodal-hosts based on aminopyridinium units with pyrenyl groups for the detection of anions. These systems exhibited noticeable changes in the photophysical properties, depending on the nature of the anion; in particular, addition of chloride resulted in a conformational change, giving an initial increase in excimeric emission. A good selectivity for dicarboxylic acid was also found. In the search for higher sensitivities, we moved our attention also to systems able to perform amplification effects. In this context we described the metal ion binding properties of three photoactive poly-(arylene ethynylene) co-polymers with different complexing units and we highlighted, for one of them, a ten-fold amplification of the response in case of addition of Zn2+, Cu2+ and Hg2+ ions. In addition, we were able to demonstrate the formation of complexes with Yb3+ an Er3+ and an efficient sensitization of their typical metal centered NIR emission upon excitation of the polymer structure, this feature being of particular interest for their possible applications in optical imaging and in optical amplification for telecommunication purposes. An amplification effect was also observed during this research in silica nanoparticles derivatized with a suitable zinc probe. In this case we were able to prove, for the first time, that nanoparticles can work as “off-on” chemosensors with signal amplification. Fluorescent silica nanoparticles can be thus seen as innovative multicomponent systems in which the organization of photophysically active units gives rise to fruitful collective effects. These precious effects can be exploited for biological imaging, medical diagnostic and therapeutics, as evidenced also by some results reported in this thesis. In particular, the observed amplification effect has been obtained thanks to a suitable organization of molecular probe units onto the surface of the nanoparticles. In the effort of reaching a deeper inside in the mechanisms which lead to the final amplification effects, we also attempted to find a correlation between the synthetic route and the final organization of the active molecules in the silica network, and thus with those mutual interactions between one another which result in the emerging, collective behavior, responsible for the desired signal amplification. In this context, we firstly investigated the process of formation of silica nanoparticles doped with pyrene derivative and we showed that the dyes are not uniformly dispersed inside the silica matrix; thus, core-shell structures can be formed spontaneously in a one step synthesis. Moreover, as far as the design of new labels is concerned, we reported a new synthetic approach to obtain a class of robust, biocompatible silica core-shell nanoparticles able to show a long-term stability. Taking advantage of this new approach we also showed the synthesis and photophysical properties of core-shell NIR absorbing and emitting materials that proved to be very valuable for in-vivo imaging. In general, the dye doped silica nanoparticles prepared in the framework of this project can conjugate unique properties, such as a very high brightness, due to the possibility to include many fluorophores per nanoparticle, high stability, because of the shielding effect of the silica matrix, and, to date, no toxicity, with a simple and low-cost preparation. All these features make these nanostructures suitable to reach the low detection limits that are nowadays required for effective clinical and environmental applications, fulfilling in this way the initial expectations of this research project.

A hybrid technology for parallel recording of single ion channels

Hybrid technologies, thanks to the convergence of integrated microelectronic devices and new class of microfluidic structures could open new perspectives to the way how nanoscale events are discovered, monitored and controlled. The key point of this thesis is to evaluate the impact of such an approach into applications of ion-channel High Throughput Screening (HTS)platforms. This approach offers promising opportunities for the development of new classes of sensitive, reliable and cheap sensors. There are numerous advantages of embedding microelectronic readout structures strictly coupled to sensing elements. On the one hand the signal-to-noise-ratio is increased as a result of scaling. On the other, the readout miniaturization allows organization of sensors into arrays, increasing the capability of the platform in terms of number of acquired data, as required in the HTS approach, to improve sensing accuracy and reliabiity. However, accurate interface design is required to establish efficient communication between ionic-based and electronic-based signals. The work made in this thesis will show a first example of a complete parallel readout system with single ion channel resolution, using a compact and scalable hybrid architecture suitable to be interfaced to large array of sensors, ensuring simultaneous signal recording and smart control of the signal-to-noise ratio and bandwidth trade off. More specifically, an array of microfluidic polymer structures, hosting artificial lipid bilayers blocks where single ion channel pores are embededed, is coupled with an array of ultra-low noise current amplifiers for signal amplification and data processing. As demonstrating working example, the platform was used to acquire ultra small currents derived by single non-covalent molecular binding between alpha-hemolysin pores and beta-cyclodextrin molecules in artificial lipid membranes.

Development of bionanotechnological strategies for signal enhancement in nucleic acids biosensors

Nucleic acid biosensors represent a powerful tool for clinical and environmental pathogens detection. For applications such as point-of-care biosensing, it is fundamental to develop sensors that should be automatic, inexpensive, portable and require a professional skill of the user that should be as low as possible. With the goal of determining the presence of pathogens when present in very small amount, such as for the screening of pathogens in drinking water, an amplification step must be implemented. Often this type of determinations should be performed with simple, automatic and inexpensive hardware: the use of a chemical (or nanotechnological) isothermal solution would be desirable. My Ph.D. project focused on the study and on the testing of four isothermal reactions which can be used to amplify the nucleic acid analyte before the binding event on the surface sensor or to amplify the signal after that the hybridization event with the probe. Recombinase polymerase amplification (RPA) and ligation-mediated rolling circle amplification (L-RCA) were investigated as methods for DNA and RNA amplification. Hybridization chain reaction (HCR) and Terminal deoxynucleotidil transferase-mediated amplification were investigated as strategies to achieve the enhancement of the signal after the surface hybridization event between target and probe. In conclusion, it can be said that only a small subset of the biochemical strategies that are proved to work in solution towards the amplification of nucleic acids does truly work in the context of amplifying the signal of a detection system for pathogens. Amongst those tested during my Ph.D. activity, recombinase polymerase amplification seems the best candidate for a useful implementation in diagnostic or environmental applications.

Inibizione selettiva del gene MYCN mediante PNA (acidi peptido nucleici) anti-gene nel rabdomiosarcoma umano

MYCN oncogene amplification/expression is a feature of many childhood tumors, and some adult tumors, and it is associated with poor prognosis. While MYC expression is ubiquitary, MYCN has a restricted expression after birth and it is an ideal target for an effective therapy. PNAs belong to the latest class of nucleic acid-based therapeutics, and they can bind chromosomal DNA and block gene transcription (anti-gene activity). We have developed an anti-gene PNA that targets specifically the MYCN gene to block its transcription. We report for the first time MYCN targeted inhibition in Rhabdomyosarcoma (RMS) by the anti-MYCN-PNA in RMS cell lines (four ARMS and four ERMS) and in a xenograft RMS mouse model. Rhabdomyosarcoma is the most common pediatric soft-tissue sarcoma, comprising two main subgroups [Alveolar (ARMS) and Embryonal (ERMS)]. ARMS is associated with a poorer prognosis. MYCN amplification is a feature of both the ERMS and ARMS, but the MYCN amplification and expression levels shows a significant correlation and are greater in ARMS, in which they are associated with adverse outcome. We found that MYCN mRNA and protein levels were higher in the four ARMS (RH30, RH4, RH28 and RMZ-RC2) than in the four ERMS (RH36, SMS-CTR, CCA and RD) cell lines. The potent inhibition of MYCN transcription was highly specific, it did not affect the MYC expression, it was followed by cell-growth inhibition in the RMS cell lines which correlated with the MYCN expression rate, and it led to complete cell-growth inhibition in ARMS cells. We used a mutated- PNA as control. MYCN silencing induced apoptosis. Global gene expression analysis (Affymetrix microarrays) in ARMS cells treated with the anti-MYCN-PNA revealed genes specifically induced or repressed, with both genes previously described as targets of N-myc or Myc, and new genes undescribed as targets of N-myc or Myc (mainly involved in cell cycle, apoptosis, cell motility, metastasis, angiogenesis and muscle development). The changes in the expression of the most relevant genes were confirmed by Real-Time PCR and western blot, and their expression after the MYCN silencing was evaluated in the other RMS cell lines. The in vivo study, using an ARMS xenograft murine model evaluated by micro-PET, showed a complete elimination of the metabolic tumor signal in most of the cases (70%) after anti-MYCN-PNA treatment (without toxicity), whereas treatment with the mutated-PNA had no effect. Our results strongly support the development of MYCN anti-gene therapy for the treatment of RMS, particularly for poor prognosis ARMS, and of other MYCN-expressing tumors.

Fault detection in rotating machines by vibration signal processing techniques

Machines with moving parts give rise to vibrations and consequently noise. The setting up and the status of each machine yield to a peculiar vibration signature. Therefore, a change in the vibration signature, due to a change in the machine state, can be used to detect incipient defects before they become critical. This is the goal of condition monitoring, in which the informations obtained from a machine signature are used in order to detect faults at an early stage. There are a large number of signal processing techniques that can be used in order to extract interesting information from a measured vibration signal. This study seeks to detect rotating machine defects using a range of techniques including synchronous time averaging, Hilbert transform-based demodulation, continuous wavelet transform, Wigner-Ville distribution and spectral correlation density function. The detection and the diagnostic capability of these techniques are discussed and compared on the basis of experimental results concerning gear tooth faults, i.e. fatigue crack at the tooth root and tooth spalls of different sizes, as well as assembly faults in diesel engine. Moreover, the sensitivity to fault severity is assessed by the application of these signal processing techniques to gear tooth faults of different sizes.

Trasduzione del segnale inositide-dipendente nel carcinoma della mammella

Breast carcinoma, one of the most frequent malignancies in women, is a complex disease in which a number of different factors combine to drive pathogenesis. The biopathological characterization of these tumors is essential to determine their aggressiveness and to find the most appropriate therapy. As in others neoplasms, the deregulation of signal transduction pathways is frequently responsible for conferring selective biological advantages to the tumor. Phosphoinositides play an essential role in diverse cellular functions, their metabolism is highly active, and is tightly controlled. Among the enzymes implicated in this pathway, phospholipase C beta 1 (PLCβ1) is one of the key regulators, both at the cytoplasmic and the nuclear level. The PLCβ1 gene maps onto the short arm of chromosome 20, a region that has been shown to be altered in several solid tumors, including breast cancer. In the present study a FISH approach was used to investigate the genetic alterations of the PLCβ1 gene in various classes of breast cancer which differ in their invasiveness and proliferation status, according to their mitotic index. The overall aim was to find out whether this enzyme could be a suitable prognostic marker for this neoplasm. Our results show that 83% of cases had aneusomies at the 20p12 level, and the most frequent alteration is a gain in this specific locus. Indeed, we found that this amplification is not related to the invasion status since there were no differences in amplified tumor frequencies between in situ and invasive breast cancer. On the contrary, the gain of PLCβ1 was significantly related to the mitotic index (p = 0.001). To verify if the change in genetic dosage influences the expression of PLCβ1 we performed Real Time PCR and Immunohystochemical analysis. Our results confirmed that amplified tumors have higher levels of PLCβ1 mRNA, which is the sum of the two splicing isoforms 1a and 1b. On the other hand, even if protein levels were higher in the majority of cases compared to the nontumoral specimens, there were no significant associations between gain and overexpression. Finally, the significant association between the amplification of PLCβ1 and others important clinicopathological parameters, such as grading and hormonal receptors status, confirmed a correlation of this enzyme with the aggressiveness of breast cancer. This suggests that PLCβ1 has the potential to be a prognostic marker in these tumors. However, further work needs to be carried out to validate these preliminary findings.

Adaptive multiscale biological signal processing

Biological processes are very complex mechanisms, most of them being accompanied by or manifested as signals that reflect their essential characteristics and qualities. The development of diagnostic techniques based on signal and image acquisition from the human body is commonly retained as one of the propelling factors in the advancements in medicine and biosciences recorded in the recent past. It is a fact that the instruments used for biological signal and image recording, like any other acquisition system, are affected by non-idealities which, by different degrees, negatively impact on the accuracy of the recording. This work discusses how it is possible to attenuate, and ideally to remove, these effects, with a particular attention toward ultrasound imaging and extracellular recordings. Original algorithms developed during the Ph.D. research activity will be examined and compared to ones in literature tackling the same problems; results will be drawn on the base of comparative tests on both synthetic and in-vivo acquisitions, evaluating standard metrics in the respective field of application. All the developed algorithms share an adaptive approach to signal analysis, meaning that their behavior is not dependent only on designer choices, but driven by input signal characteristics too. Performance comparisons following the state of the art concerning image quality assessment, contrast gain estimation and resolution gain quantification as well as visual inspection highlighted very good results featured by the proposed ultrasound image deconvolution and restoring algorithms: axial resolution up to 5 times better than algorithms in literature are possible. Concerning extracellular recordings, the results of the proposed denoising technique compared to other signal processing algorithms pointed out an improvement of the state of the art of almost 4 dB.

Statistical methods for biomedical signal analysis and processing

Statistical modelling and statistical learning theory are two powerful analytical frameworks for analyzing signals and developing efficient processing and classification algorithms. In this thesis, these frameworks are applied for modelling and processing biomedical signals in two different contexts: ultrasound medical imaging systems and primate neural activity analysis and modelling. In the context of ultrasound medical imaging, two main applications are explored: deconvolution of signals measured from a ultrasonic transducer and automatic image segmentation and classification of prostate ultrasound scans. In the former application a stochastic model of the radio frequency signal measured from a ultrasonic transducer is derived. This model is then employed for developing in a statistical framework a regularized deconvolution procedure, for enhancing signal resolution. In the latter application, different statistical models are used to characterize images of prostate tissues, extracting different features. These features are then uses to segment the images in region of interests by means of an automatic procedure based on a statistical model of the extracted features. Finally, machine learning techniques are used for automatic classification of the different region of interests. In the context of neural activity signals, an example of bio-inspired dynamical network was developed to help in studies of motor-related processes in the brain of primate monkeys. The presented model aims to mimic the abstract functionality of a cell population in 7a parietal region of primate monkeys, during the execution of learned behavioural tasks.

Maremoti in bacini limitati

The work of my thesis is focused on the impact of tsunami waves in limited basins. By limited basins I mean here those basins capable of modifying significantly the tsunami signal with respect to the surrounding open sea. Based on this definition, we consider limited basins not only harbours but also straits, channels, seamounts and oceanic shelves. I have considered two different examples, one dealing with the Seychelles Island platform in the Indian Ocean, the second focussing on the Messina Strait and the harbour of the Messina city itself (Italy). The Seychelles platform is differentiated at bathymetric level from the surrounding ocean, with rapid changes from 2 km to 70 meters over short horizontal distances. The study of the platform response to the tsunami propagation is based on the simulation of the mega-event occurred on 26 December 2004. Based on a hypothesis for the earthquake causative fault, the ensuing tsunami has been numerically simulated. I analysed synthetic tide gauge records at several virtual tide gauges aligned along the direction going from the source to the platform. A substantial uniformity of tsunami signals in all calculated open ocean tide-gauge records is observed, while the signals calculated in two points of the Seychelles platform show different features both in terms of amplitude and period of the perturbation. To better understand the content in frequency of different calculated marigrams, a spectral analysis was carried out. In particular the ratio between the calculated tide-gauge records spectrum on the platform and the average tide-gauge records in the open ocean was considered. The main result is that, while in the average spectrum in the open ocean the fundamental peak is related to the source, the platform introduces further peaks linked both to the bathymetric configuration and to coastal geometry. The Messina Strait represents an interesting case because it consists in a sort of a channel open both in the north and in the south and furthermore contains the limited basin of the Messina harbour. In this case the study has been carried out in a different way with respect to the Seychelles case. The basin was forced along a boundary of the computational domain with sinusoidal functions having different periods within the typical tsunami frequencies. The tsunami has been simulated numerically and in particular the tide-gauge records were calculated for every forcing function in different points both externally and internally of the channel and of the Messina harbour. Apart from the tide-gauge records in the source region that almost immediately reach stationarity, all the computed signals in the channel and in the Messina harbour present a transient variable amplitude followed by a stationary part. Based exclusively on this last part, I calculated the amplification curves for each site. I found that the maximum amplification is obtained for forcing periods of approximately 10 minutes.

Heterogeneous multicore systems for signal processing

This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.

Ruolo delle specie reattive dell'ossigeno e di caveole/raft lipidici nella biosegnalazione in linee cellulari umane

Membrane lipid rafts are detergent-resistant microdomains containing glycosphingolipids, cholesterol and glycosylphosphatidylinositol-linked proteins; they seem to be actively involved in many cellular processes including signal transduction, apoptosis, cell adhesion and migration. Lipid rafts may represent important functional platforms where redox signals are produced and transmitted in response to various agonists or stimuli. In addition, a new concept is emerging that could be used to define the interactions or amplification of both redox signalling and lipid raft-associated signalling. This concept is characterized by redox-mediated feed forward amplification in lipid platforms. It is proposed that lipid rafts are formed in response to various stimuli; for instance, NAD(P)H oxidase (Nox) subunits are aggregated or recruited in these platforms, increasing Nox activity. Superoxide and hydrogen peroxide generation could induce various regulatory activities, such as the induction of glucose transport activity and proliferation in leukaemia cells. The aim of our study is to probe: i) the involvement of lipid rafts in the modulation of the glucose transporter Glut1 in human acute leukemia cells; ii) the involvement of plasma membrane caveolae/lipid rafts in VEGF-mediated redox signaling via Nox activation in human leukemic cells; iii) the role of p66shc, an adaptor protein, in VEGF signaling and ROS production in endothelial cells (ECs); iv) the role of Sindecan-2, a transmembrane heparan sulphate proteoglycan, in VEGF signaling and physiological response in ECs and v) the antioxidant and pro-apoptotic activities of simple dietary phenolic acids, i. e. caffeic, syringic and protocatechuic acids in leukemia cells, characterized by a very high ROS content. Our results suggest that the role played by NAD(P)H oxidase-derived ROS in the regulation of glucose uptake, proliferation and migration of leukaemia and endothelial cells could likely occur through the control of lipid raft-associated signalling.

Advanced signal and receiver design for next generation OFDM systems

This thesis deal with the design of advanced OFDM systems. Both waveform and receiver design have been treated. The main scope of the Thesis is to study, create, and propose, ideas and novel design solutions able to cope with the weaknesses and crucial aspects of modern OFDM systems. Starting from the the transmitter side, the problem represented by low resilience to non-linear distortion has been assessed. A novel technique that considerably reduces the Peak-to-Average Power Ratio (PAPR) yielding a quasi constant signal envelope in the time domain (PAPR close to 1 dB) has been proposed.The proposed technique, named Rotation Invariant Subcarrier Mapping (RISM),is a novel scheme for subcarriers data mapping,where the symbols belonging to the modulation alphabet are not anchored, but maintain some degrees of freedom. In other words, a bit tuple is not mapped on a single point, rather it is mapped onto a geometrical locus, which is totally or partially rotation invariant. The final positions of the transmitted complex symbols are chosen by an iterative optimization process in order to minimize the PAPR of the resulting OFDM symbol. Numerical results confirm that RISM makes OFDM usable even in severe non-linear channels. Another well known problem which has been tackled is the vulnerability to synchronization errors. Indeed in OFDM system an accurate recovery of carrier frequency and symbol timing is crucial for the proper demodulation of the received packets. In general, timing and frequency synchronization is performed in two separate phases called PRE-FFT and POST-FFT synchronization. Regarding the PRE-FFT phase, a novel joint symbol timing and carrier frequency synchronization algorithm has been presented. The proposed algorithm is characterized by a very low hardware complexity, and, at the same time, it guarantees very good performance in in both AWGN and multipath channels. Regarding the POST-FFT phase, a novel approach for both pilot structure and receiver design has been presented. In particular, a novel pilot pattern has been introduced in order to minimize the occurrence of overlaps between two pattern shifted replicas. This allows to replace conventional pilots with nulls in the frequency domain, introducing the so called Silent Pilots. As a result, the optimal receiver turns out to be very robust against severe Rayleigh fading multipath and characterized by low complexity. Performance of this approach has been analytically and numerically evaluated. Comparing the proposed approach with state of the art alternatives, in both AWGN and multipath fading channels, considerable performance improvements have been obtained. The crucial problem of channel estimation has been thoroughly investigated, with particular emphasis on the decimation of the Channel Impulse Response (CIR) through the selection of the Most Significant Samples (MSSs). In this contest our contribution is twofold, from the theoretical side, we derived lower bounds on the estimation mean-square error (MSE) performance for any MSS selection strategy,from the receiver design we proposed novel MSS selection strategies which have been shown to approach these MSE lower bounds, and outperformed the state-of-the-art alternatives. Finally, the possibility of using of Single Carrier Frequency Division Multiple Access (SC-FDMA) in the Broadband Satellite Return Channel has been assessed. Notably, SC-FDMA is able to improve the physical layer spectral efficiency with respect to single carrier systems, which have been used so far in the Return Channel Satellite (RCS) standards. However, it requires a strict synchronization and it is also sensitive to phase noise of local radio frequency oscillators. For this reason, an effective pilot tone arrangement within the SC-FDMA frame, and a novel Joint Multi-User (JMU) estimation method for the SC-FDMA, has been proposed. As shown by numerical results, the proposed scheme manages to satisfy strict synchronization requirements and to guarantee a proper demodulation of the received signal.

Analog Signal Acquisition and Conditioning for Near-Field Capacitive Communication and Active Combined EEG-EIT Monitoring

The work of the present thesis is focused on the implementation of microelectronic voltage sensing devices, with the purpose of transmitting and extracting analog information between devices of different nature at short distances or upon contact. Initally, chip-to-chip communication has been studied, and circuitry for 3D capacitive coupling has been implemented. Such circuits allow the communication between dies fabricated in different technologies. Due to their novelty, they are not standardized and currently not supported by standard CAD tools. In order to overcome such burden, a novel approach for the characterization of such communicating links has been proposed. This results in shorter design times and increased accuracy. Communication between an integrated circuit (IC) and a probe card has been extensively studied as well. Today wafer probing is a costly test procedure with many drawbacks, which could be overcome by a different communication approach such as capacitive coupling. For this reason wireless wafer probing has been investigated as an alternative approach to standard on-contact wafer probing. Interfaces between integrated circuits and biological systems have also been investigated. Active electrodes for simultaneous electroencephalography (EEG) and electrical impedance tomography (EIT) have been implemented for the first time in a 0.35 um process. Number of wires has been minimized by sharing the analog outputs and supply on a single wire, thus implementing electrodes that require only 4 wires for their operation. Minimization of wires reduces the cable weight and thus limits the patient's discomfort. The physical channel for communication between an IC and a biological medium is represented by the electrode itself. As this is a very crucial point for biopotential acquisitions, large efforts have been carried in order to investigate the different electrode technologies and geometries and an electromagnetic model is presented in order to characterize the properties of the electrode to skin interface.