Istituto Italiano di Tecnologia
Recent publications
Circular RNAs (circRNAs) are expressed and are regulated in many biological processes but little is known about their ability to directly control mRNA homeostasis. We show that circRNA zinc finger protein 609 (circZNF609) interacts with several mRNAs increasing the final protein levels, which in the case of the cytoskeleton-associated protein 5 (CKAP5) leads to a stabilized microtubule cytoskeleton and an enhanced tumor cell proliferation.
Background We propose an efficient method to modify B-cell derived EVs by loading them with a nanotherapeutic stimuli-responsive cargo and equipping them with antibodies for efficient targeting of lymphoma cells. Results The post-isolation engineering of the EVs is accomplished by a freeze–thaw method to load therapeutically-active zinc oxide nanocrystals (ZnO NCs), obtaining the so-called TrojanNanoHorse (TNH) to recall the biomimetism and cytotoxic potential of this novel nanoconstruct. TNHs are further modified at their surface with anti-CD20 monoclonal antibodies (TNH CD20 ) achieving specific targeting against lymphoid cancer cell line. The in vitro characterization is carried out on CD20+ lymphoid Daudi cell line, CD20-negative cancerous myeloid cells (HL60) and the healthy counterpart (B lymphocytes). The TNH shows nanosized structure, high colloidal stability, even over time, and good hemocompatibility. The in vitro characterization shows the high biocompatibility, targeting specificity and cytotoxic capability. Importantly, the selectivity of TNH CD20 demonstrates significantly higher interaction towards the target lymphoid Daudi cell line compared to the CD20-negative cancerous myeloid cells (HL60) and the healthy counterpart (lymphocytes). An enhanced cytotoxicity directed against Daudi cancer cells is demonstrated after the TNH CD20 activation with high-energy ultrasound shock-waves (SW). Conclusion This work demonstrates the efficient re-engineering of EVs, derived from healthy cells, with inorganic nanoparticles and monoclonal antibodies. The obtained hybrid nanoconstructs can be on-demand activated by an external stimulation, here acoustic pressure waves, to exploit a cytotoxic effect conveyed by the ZnO NCs cargo against selected cancer cells. Graphical Abstract
The ongoing trend toward Industry 4.0 has revolutionised ordinary workplaces, profoundly changing the role played by humans in the production chain. Research on ergonomics in industrial settings mainly focuses on reducing the operator’s physical fatigue and discomfort to improve throughput and avoid safety hazards. However, as the production complexity increases, the cognitive resources demand and mental workload could compromise the operator’s performance and the efficiency of the shop floor workplace. State-of-the-art methods in cognitive science work offline and/or involve bulky equipment hardly deployable in industrial settings. This paper presents a novel method for online assessment of cognitive load in manufacturing, primarily assembly, by detecting patterns in human motion directly from the input images of a stereo camera. Head pose estimation and skeleton tracking are exploited to investigate the workers’ attention and assess hyperactivity and unforeseen movements. Pilot experiments suggest that our factor assessment tool provides significant insights into workers’ mental workload, even confirmed by correlations with physiological and performance measurements. According to data gathered in this study, a vision-based cognitive load assessment has the potential to be integrated into the development of mechatronic systems for improving cognitive ergonomics in manufacturing.
Targeting fatty acid amide hydrolase (FAAH) is a promising therapeutic strategy to combat certain forms of pain, including migraine headache. FAAH inhibitors, such as the O -biphenyl-3-yl carbamate URB597, have been shown to produce anti-hyperalgesic effects in animal models of migraine. The objective of this study was to investigate the behavioral and biochemical effects of compounds ARN14633 and ARN14280, two URB597 analogs with improved solubility and bioavailability, in a migraine-specific rat model in which trigeminal hyperalgesia is induced by nitroglycerin (NTG) administration. ARN14633 (1 mg/kg, i.p.) and ARN14280 (3 mg/kg, i.p.) were administered to adult male Sprague-Dawley rats 3 hours after NTG injection. One hour after the administration of either compound, rats were subjected to the orofacial formalin test. ARN14633 and ARN14280 attenuated NTG-induced nocifensive behavior and reduced transcription of genes encoding neuronal nitric oxide synthase, pain mediators peptides (calcitonin gene-related peptide, substance P) and pro-inflammatory cytokines (tumor necrosis factor-alpha, interleukin-1beta and 6) in the trigeminal ganglion, cervical spinal cord and medulla. Finally, both compounds strongly elevated levels of endocannabinoids and/or other FAAH substrates in cervical spinal cord and medulla, and, to a lesser extent, in the trigeminal ganglia. The results indicate that the novel global FAAH inhibitors ARN14633 and ARN14280 elicit significant anti-hyperalgesic effects in a migraine-specific animal model and inhibit the associated peptidergic-inflammatory response. Although the precise mechanism underlying these effects remains to be elucidated, our results support further investigational studies of FAAH blockade as a potential therapeutic strategy to treat migraine conditions.
TiO2 based-photocatalysts doped with Fe and/or Cr was evaluated as pre- and post-treatment method of a moving bed biofilm reactor (MBBR) as possible solution for the treatment of real olive oil mill wastewater (OMW). Photocatalysts were synthesized by wet chemical method and their chemical-physical properties were accurately investigated through X-ray diffraction (XRD), Raman spectroscopy, UV–Vis diffuse reflectance spectroscopy (UV–Vis DRS) and specific surface area measurements. UV–Vis DRS measurements evidenced that the simultaneous doping of TiO2 lattice with Fe and Cr improves the optical absorption into the visible region leading to a narrow band gap (2.1 eV) with respect to undoped TiO2 (3.2 eV) and Fe-doped TiO2 (2.8 eV) while, Cr-doped TiO2 showed the lowest bandgap value (1.9 eV). XRD patterns and Raman spectra showed that anatase is the predominant crystalline phase for all the prepared photocatalysts and Fe and Cr ions were effectively inserted into the TiO2 lattice. The TiO2 doping with Cr did not change the average crystallites size that was equivalent to that of TiO2 (8 nm), whereas, for Fe- doped TiO2, it was lower than the others and equal to 6 nm. The specific surface area values of doped catalysts were higher than TiO2 and the value for Fe-Cr-codoped TiO2 resulted to be 97 m² g⁻¹. Photocatalytic treatment of OMW was evaluated in terms of total polyphenols (TPHs), Chemical Oxygen Demand (COD), Biological Oxygen Demand (BOD5) and biodegradability (as BOD5/COD ratio) in 3 h of treatment under simulated solar light irradiation. Fe-doped TiO2 showed the highest TPHs removal for both un-treated and biologically treated OMW. When H2O2 was added (optimum dosage 0.5 g L⁻¹), Fe-Cr-TiO2 resulted in the best photocatalytic performance with TPHs removal as high as 97% and increased biodegradability (0.22 to 0.33), making the effluent suitable for the subsequent biological process. When photocatalytic process was investigated as post-treatment of OMW, Fe-TiO2 showed the best activity and the addition of 0.5 g L⁻¹ of H2O2 was sufficient to make the effluent in compliance with Italian regulation for effluent disposal into surface water.
Background Pathogenic variants in PEX -genes can affect peroxisome assembly and function and cause Zellweger spectrum disorders (ZSDs), characterized by variable phenotypes in terms of disease severity, age of onset and clinical presentations. So far, defects in at least 15 PEX -genes have been implicated in Mendelian diseases, but in some of the ultra-rare ZSD subtypes genotype–phenotype correlations and disease mechanisms remain elusive. Methods We report five families carrying biallelic variants in PEX13. The identified variants were initially evaluated by using a combination of computational approaches. Immunofluorescence and complementation studies on patient-derived fibroblasts were performed in two patients to investigate the cellular impact of the identified mutations. Results Three out of five families carried a recurrent p.Arg294Trp non-synonymous variant. Individuals affected with PEX13 -related ZSD presented heterogeneous clinical features, including hypotonia, developmental regression, hearing/vision impairment, progressive spasticity and brain leukodystrophy. Computational predictions highlighted the involvement of the Arg294 residue in PEX13 homodimerization, and the analysis of blind docking predicted that the p.Arg294Trp variant alters the formation of dimers, impairing the stability of the PEX13/PEX14 translocation module. Studies on muscle tissues and patient-derived fibroblasts revealed biochemical alterations of mitochondrial function and identified mislocalized mitochondria and a reduced number of peroxisomes with abnormal PEX13 concentration. Conclusions This study expands the phenotypic and mutational spectrum of PEX13 -related ZSDs and also highlight a variety of disease mechanisms contributing to PEX13 -related clinical phenotypes, including the emerging contribution of secondary mitochondrial dysfunction to the pathophysiology of ZSDs.
The electrochemical reduction of CO2 to value-added products is hindered by its thermodynamic stability and by the large energy required to chemically activate the molecule. With this respect, forcing CO2 in a non-linear geometry would induce an internal electron charge rearrangement which would facilitate further electrochemical transformations. In this work, we achieved this goal through the design of a dual function electro-organocatalyst, which exploits the ability of the imidazolate (Im⁻) lone pair to bind CO2 via nucleophilic attack and then electrochemically reduce it. To give structural stability to the Im⁻ based catalyst, the imidazoles species are incorporated into a solid structure, namely ZIF-8. Once activated by the organic Im⁻ ligand, CO2 is electrochemically reduced to CO when a bias is applied to ZIF-8. The catalyst proposed in our study was first devised by computer aided design based on Density functional Theory simulations and then realized in laboratory. Our results demonstrate that ZIF-8 supported on conductive CNTs presents surface Im⁻ active sites which convert CO2 into CO with a high faradaic efficiency (70.4 %) at −1.2 V vs reversible hydrogen electrode, by combining chemical activation with electrochemical catalysis.
When we read fiction, we encounter characters that interact in the story. As such, we encode that information and comprehend the stories. Prior studies suggest that this comprehension process is facilitated by taking the perspective of characters during reading. Thus, two questions of interest are whether people take the perspective of characters that are not perceived as capable of experiencing perspectives (e.g., robots), and whether current models of language comprehension can explain these differences between human and nonhuman protagonists (or lack thereof) during reading. The study aims to (1) compare the situation model (i.e., a model that factors in a protagonist's perspective) and the RIVAL model (which relies more on comparisons of newly acquired information with information stored in long term memory) and (2) investigate whether differences in accessibility of information differ based on adopting the intentional stance towards a robot. To address the aims of our study, we designed a preregistered experiment in which participants read stories about one of three protagonists (an intentional robot, a mechanistic robot and a human) and answered questions about objects that were either occluded or not occluded from the protagonist's view. Based on the situation model, we expected faster responses to items that were not occluded compared to those that were occluded (i.e., the occlusion effect). However, based on the RIVAL model, we expected overall differences between the protagonists would arise due to inconsistency with general world knowledge. The results of the pre-registered analysis showed no differences between the protagonists, nor differences in occlusion. However, a post-hoc analysis showed that the occlusion effect was shown only for the intentional robot but not for the human, nor mechanistic robot. Results also showed that depending on the age of the readers, the RIVAL or the situation model is able to explain the results such that older participants "simulated" the situation about which they read (situation model), while younger adults compared new information with information stored in long-term memory (RI-VAL model). This suggests that comparing to information in long term memory is cognitively more costly. Therefore, with older adults used less cognitively demanding strategy of simulation.
Reactive oxygen species (ROS) are a common hallmark of many degenerative diseases, developing in all those cases where a failure of physiological antioxidant mechanisms occurs (in particular, antioxidant enzymes and the glutathione system), or in case of exposure to an extremely high level of oxidants. In this regard, antioxidant natural extracts are promising compounds as preventive or therapeutic agents against ROS-dependent degenerations. In this study, a deep investigation of hazelnut (Corylus avellana) extract has been performed in terms of mass spectroscopy, evaluation of phenolic content, and antioxidant capacity. Then, nanostructured lipid carriers (NLCs) have been exploited for encapsulation of the hazelnut extracts in order to achieve prolonged bioactivity, increased stability, and targeting through a sustainable delivery approach. The hazelnut extract-loaded NLCs (NE_NLCs) have been deeply characterized for their stability, production yield, and encapsulation efficiency. Moreover, NE_NLCs showed optimal cytocompatibility on human dermal fibroblast (HDF) cells, as well as excellent antioxidant activity, upon pro-oxidant stimulus on HDF cells.
Present-day atomistic simulations generate long trajectories of ever more complex systems. Analyzing these data, discovering metastable states, and uncovering their nature are becoming increasingly challenging. In this paper, we first use the variational approach to conformation dynamics to discover the slowest dynamical modes of the simulations. This allows the different metastable states of the system to be located and organized hierarchically. The physical descriptors that characterize metastable states are discovered by means of a machine learning method. We show in the cases of two proteins, chignolin and bovine pancreatic trypsin inhibitor, how such analysis can be effortlessly performed in a matter of seconds. Another strength of our approach is that it can be applied to the analysis of both unbiased and biased simulations.
Ultrasmall (<5 nm diameter) noble metal nanoparticles with a high fraction of {111} surface domains are of fundamental and practical interest as electrocatalysts, especially in fuel cells; the nanomaterial surface structure dictates its catalytic properties, including kinetics and stability. However, the synthesis of size-controlled, pure Pt-shaped nanocatalysts has remained a formidable chemical challenge. There is an urgent need for an industrially scalable method for their production. Here, a one-step approach is presented for the preparation of single-crystal pyramidal nanocatalysts with a high fraction of {111} surface domains and a diameter below 4 nm. This is achieved by harnessing the shape-directing effect of citrate molecules, together with the strict control of oxidative etching while avoiding polymers, surfactants, and organic solvents. These catalysts exhibit significantly enhanced durability while, providing equivalent current and power densities to highly optimized commercial Pt/C catalysts at the beginning of life (BOL). This is even the case when they are tested in full polymer electrolyte membrane fuel cells (PEMFCs), as opposed to rotating disk experiments that artificially enhance electrode kinetics and minimize degradation. This demonstrates that the {111} surface domains in pyramidal Pt nanoparticles (as opposed to spherical Pt nanoparticles) can improve aggregation/corrosion resistance in realistic fuel cell conditions, leading to a significant improvement in membrane electrode assembly (MEA) stability and lifetime.
Plasmonic systems, such as metal nanoparticles, are widely used in different application areas, going from biology to photovoltaics.The modeling of the optical response of such systems is of fundamental importance to analyze their behavior and to design new systems with required properties.When the characteristic sizes/distances reach a few nanometers, non-local and spill-out effects become relevant and conventional classical electrodynamics models are no more appropriate. Methods based on the Time-Dependent Density-Functional Theory (TD-DFT) represent the current reference for the description of quantum effects. However, TD-DFT is based on knowledge of all occupied orbitals whose calculation is computationally prohibitive to model large plasmonic systems of interest for applications.On the other hand, methods based on the Orbital-Free (OF) formulation of TD-DFT, can scale linearly with the system size.In this Review, OF methods ranging from semiclassical models to the quantum hydrodynamic theory, will be derived from the linear response TD-DFT, so that the key approximations and properties of each method can be clearly highlighted. The accuracy of the various approximations will be then validated for the linear optical properties of jellium nanoparticles, the most relevant model system in plasmonics. OF methods can describe the collective excitations in plasmonic systems with great accuracy andwithout system-tuned parameters. The accuracy on these methods depends only on the accuracy on the (universal) kinetic energy functional of the ground-state electronic density. Current approximations and future development directions will be indicated.
Short hemp fibers, an agricultural waste, were used for producing biochar by pyrolysis at 1000 °C. The so-obtained hemp-derived carbon fibers (HFB) were used as filler for improving the properties of an epoxy resin using a simple casting and curing process. The addition of HFB in the epoxy matrix increases the storage modulus while damping factor is lowered. Also, the incorporation of HFB induces a remarkable increment of electrical conductivity reaching up to 6 mS/m with 10 wt% of loading. A similar trend is also observed during high-frequency measurements. Furthermore, for the first time wear of these composites has been studied. The use of HFB is an efficient method for reducing the wear rate resistance and the friction coefficient (COF) of the epoxy resin. Excellent results are obtained for the composite containing 2.5 wt% of HFB, for which COF and wear rate decrease by 21% and 80%, respectively, as compared with those of the unfilled epoxy resin. The overall results prove how a common waste carbon source can significantly wide epoxy resin applications by a proper modulation of its electrical and wear properties. Graphical abstract
Conventional drug delivery systems are challenged by concerns related to systemic toxicity, repetitive doses, drug concentrations fluctuation, and adverse effects. Various drug delivery systems have been developed to overcome these limitations. Nanomaterials are employed in a variety of biomedical applications such as therapeutics delivery, cancer therapy, and tissue engineering. Physiochemical nanoparticle assembly techniques involve the application of solvents and potentially harmful chemicals, commonly at high temperatures. Genetically engineered organisms have the potential to be used as promising candidates for greener, efficient, and more adaptable platforms for the synthesis and assembly of nanomaterials. Genetically engineered carriers are precisely designed and constructed in shape and size, enabling precise control over drug attachment sites. The high accuracy of these novel advanced materials, biocompatibility, and stimuli‐responsiveness, elucidate their emerging application in controlled drug delivery. The current article represents the research progress in developing various genetically engineered carriers. Organic‐based nanoparticles including cellulose, collagen, silk‐like polymers (SLP), elastin‐like protein (ELP), silk‐like elastane (SELP), and inorganic‐based nanoparticles are discussed in detail. Afterwards, viral‐based carriers are classified, and their potential for targeted therapeutics delivery is highlighted. Finally, the challenges and prospects of these delivery systems are concluded. This article is protected by copyright. All rights reserved
We propose and analyze a randomized zeroth-order optimization method based on approximating the exact gradient by finite differences computed in a set of orthogonal random directions that changes with each iteration. A number of previously proposed methods are recovered as special cases including spherical smoothing, coordinate descent, as well as discretized gradient descent. Our main contribution is proving convergence guarantees as well as convergence rates under different parameter choices and assumptions. In particular, we consider convex objectives, but also possibly non-convex objectives satisfying the Polyak-Łojasiewicz (PL) condition. Theoretical results are complemented and illustrated by numerical experiments.
Existing neuropsychological tests of executive function often manifest a difficulty pinpointing cognitive deficits when these are intermittent and come in the form of omissions. We discuss the hypothesis that two partially interrelated reasons for this failure stem from relative inability of neuropsychological tests to explore the cognitive space and to explicitly take into account strategic and opportunistic resource allocation decisions, and to address the temporal aspects of both behaviour and task-related brain function in data analysis. Criteria for tasks suitable for neuropsychological assessment of executive function, as well as appropriate ways to analyse and interpret observed behavioural data are suggested. It is proposed that experimental tasks should be devised which emphasize typical rather than optimal performance, and that analyses should quantify path-dependent fluctuations in performance levels rather than averaged behaviour. Some implications for experimental neuropsychology are illustrated for the case of planning and problem-solving abilities and with particular reference to cognitive impairment in closed-head injury.
Schizophrenia is a disorder characterized by cognitive impairment and psychotic symptoms that fluctuate over time and can only be mitigated with the chronic administration of antipsychotics. Here, we propose biodegradable microPlates made of PLGA for the sustained release of risperidone over several weeks. Two microPlate configurations – short: 20 × 20 × 10 μm; tall: 20 × 20 × 20 μm – are engineered and compared to conventional ~ 10 μm PLGA microspheres in terms of risperidone loading and release. Tall microPlates realize the slowest release documenting a 35% risperidone delivery at 100 days with a residual rate of 30 ng/ml. Short microPlates and microspheres present similar release profiles with over 50% of the loaded risperidone delivered within the first 40 days. Then, the therapeutic efficacy of one single intraperitoneal injection of risperidone microPlates is compared to the daily administration of free risperidone in heterozygous knockout mice for dysbindin-1, a clinically relevant mouse model of cognitive and psychiatric liability. In temporal order object recognition tasks, mice treated with risperidone microPlates outperform those receiving free risperidone up to 2, 4, 8, and 12 weeks of observation. This suggests that the sustained release of antipsychotics from one-time microPlate deposition can rescue cognitive impairment in dysbindin mice for up to several weeks. Overall, these results demonstrate that risperidone-loaded microPlates are a promising platform for improving cognitive symptoms associated to schizophrenia. Moreover, the long-term efficacy with one single administration could be of clinical relevance in terms of patient’s compliance and adherence to the treatment regimen. Graphical abstract Single injection of long-acting risperidone-loaded µPL ameliorates the dysbindin-induced deficit in a clinically relevant mouse model of cognitive and psychiatric liability for up to 12 weeks
In laparoscopic surgery, image quality is often degraded by surgical smoke or by side effects of the illumination system, such as reflections, specularities, and non-uniform illumination. The degraded images complicate the work of the surgeons and may lead to errors in image-guided surgery. Existing enhancement algorithms mainly focus on enhancing global image contrast, overlooking local contrast. Here, we propose a new Patch Adaptive Structure Decomposition utilizing the Multi-Exposure Fusion technique to enhance the local contrast of laparoscopic images for better visualization. The set of under-exposure level images is obtained from a single input blurred image by using gamma correction. Spatial linear saturation is applied to enhance image contrast and to adjust the image saturation. The Multi-Exposure Fusion (MEF) is used on a series of multi-exposure images to obtain a single clear and smoke-free fused image. MEF is applied by using adaptive structure decomposition on all image patches. Image entropy based on the texture energy is used to calculate image energy strength. The texture entropy energy determined the patch size that is useful in the decomposition of image structure. The proposed method effectively eliminate smoke and enhance the degraded laparoscopic images. The qualitative results showed that the visual quality of the resultant images is improved and smoke-free. Furthermore, the quantitative scores computed of the metrics: FADE, Blur, JNBM, and Edge Intensity are significantly improved as compared to other existing methods.
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1,327 members
Giuseppe Vecchio
  • Center for Biomolecular Nanotechnologies
Virgilio Brunetti
  • Center for Biomolecular Nanotechnologies
Stefano Palagi
  • Center for Micro-BioRobotics
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