Scuola Superiore Sant'Anna
Recent publications
Crop germplasm collections are a key asset to support the resilience and productivity of cropping systems worldwide. In their diversity lays an oftentimes untapped reservoir of alleles that may enable breeding strategies targeting local adaptation, resulting in enhanced performance and higher varietal uptake. In the past five decades, the national genebank of Ethiopia actively collected and conserved thousands of teff ( Eragrostis tef ) accessions, a staple crop throughout the Horn of Africa at the basis of countless cultural uses and with high market relevance. This review article emphasizes the breeding significance of teff genetic resources, highlighting current challenges in teff farming and improvement that could be addressed further valorising germplasm collections. We collect data generated on the largest teff ex situ collections in the world to discuss opportunities to improve teff tolerance to stress and lodging, as well as to increase its productivity across its cropping area. In doing so, we highlight and critically revise current and past literature tapping in teff diversity to support teff improvement. This review starts providing a summary of teff characteristics, detailing the status and challenges of teff cultivation and breeding. It then follows describing the diversity existing in teff diversity collections and its relevance for teff improvement. The review concludes describing the molecular studies undertook on teff in the past two decades, highlighting the perspectives of molecular breeding for teff. The body of knowledge available on teff shows that there is large potential for improvement of this crop to target smallholder farming systems as well as international markets, and that improvement may start from the large diversity available in teff collections.
After initial strategies targeting inotropism and congestion, the neurohormonal interpretative model of heart failure (HF) pathophysiology has set the basis for current pharmacological management of HF, as most of guideline recommended drug classes, including beta-blockers, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and mineralocorticoid receptor antagonists, blunt the activation of detrimental neurohormonal axes, namely sympathetic and renin–angiotensin–aldosterone (RAAS) systems. More recently, sacubitril/valsartan, a first-in-class angiotensin receptor neprilysin inhibitor, combining inhibition of RAAS and potentiation of the counter-regulatory natriuretic peptide system, has been consistently demonstrated to reduce mortality and HF-related hospitalization. A number of novel pharmacological approaches have been tested during the latest years, leading to mixed results. Among them, drugs acting directly at a second messenger level, such as the soluble guanylate cyclase stimulator vericiguat, or other addressing myocardial energetics and mitochondrial function, such as elamipretide or omecamtiv-mecarbil, will likely change the therapeutic management of patients with HF. Sodium glucose cotransporter 2 inhibitors, initially designed for the management of type 2 diabetes mellitus, have been recently demonstrated to improve outcome in HF, although mechanisms of their action on cardiovascular system are yet to be elucidated. Most of these emerging approaches have shifted the therapeutic target from neurohormonal systems to the heart, by improving cardiac contractility, metabolism, fibrosis, inflammation, and remodeling. In the present paper, we review from a pathophysiological perspective current and novel therapeutic strategies in chronic HF.
The significant morbidity and mortality associated with heart failure with reduced (HFrEF) or preserved ejection fraction (HFpEF) justify the search for novel therapeutic agents. The nitric oxide (NO)–soluble guanylate cyclase (sGC)-cyclic guanosine monophosphate (cGMP) pathway plays an important role in the regulation of cardiovascular function. This pathway is disrupted in HF resulting in decreased protection against myocardial injury. The sGC activator cinaciguat increases cGMP levels by direct, NO-independent activation of sGC, and may be particularly effective in conditions of increased oxidative stress and endothelial dysfunction, and then reduced NO levels, but this comes at the expense of a greater risk of hypotension. Conversely, sGC stimulators (riociguat and vericiguat) enhance sGC sensitivity to endogenous NO, and then exert a more physiological action. The phase 3 VICTORIA trial found that vericiguat is safe and effective in patients with HFrEF and recent HF decompensation. Therefore, adding vericiguat may be considered in individual patients with HFrEF, particularly those at higher risk of HF hospitalization; the efficacy of the sacubitril/valsartan-vericiguat combination in HFrEF is currently unknown.
Cancer and cardiovascular diseases, including heart failure (HF), are the main causes of death in Western countries. Several anticancer drugs and radiotherapy have adverse effects on the cardiovascular system, promoting left ventricular dysfunction and ultimately HF. Nonetheless, the relationship between cancer and HF is likely not unidirectional. Indeed, cancer and HF share common risk factors, and both have a bidirectional relationship with systemic inflammation, metabolic disturbances, and neurohormonal and immune activation. Few studies have assessed the impact of untreated cancer on the heart. The presence of an active cancer has been associated with elevated cardiac biomarkers, an initial impairment of left ventricular structure and function, autonomic dysfunction, and reduced exercise tolerance. In turn, these conditions might increase the risk of cardiac damage from chemotherapy and radiotherapy. HF drugs such as beta-blockers or inhibitors of the renin–angiotensin–aldosterone system might exert a protective effect on the heart even before the start of cancer therapies. In this review, we recapitulate the evidence of cardiac involvement in cancer patients naïve from chemotherapy and radiotherapy and no history of cardiac disease. We also focus on the perspectives for an early diagnosis and treatment to prevent the progression to cardiac dysfunction and clinical HF, and the potential benefits of cardioactive drugs on cancer progression.
Cardiac allograft vasculopathy (CAV) is an obliterative and diffuse form of vasculopathy affecting almost 50% of patients after 10 years from heart transplant and represents the most common cause of long-term cardiovascular mortality among heart transplant recipients. The gold standard diagnostic technique is still invasive coronary angiography, which however holds potential for complications, especially contrast-related kidney injury and procedure-related vascular lesions. Non-invasive and contrast-sparing imaging techniques have been advocated and investigated over the past decades, in order to identify those that could replace coronary angiography or at least reach comparable accuracy in CAV detection. In addition, they could help the clinician in defining optimal timing for invasive testing. This review attempts to examine the currently available non-invasive imaging techniques that may be used in the follow-up of heart transplant patients, spanning from echocardiography to nuclear imaging, cardiac magnetic resonance and cardiac computed tomography angiography, weighting their advantages and disadvantages.
Background The literature on artificial intelligence (AI) in surgery has advanced rapidly during the past few years. However, the published studies on AI are mostly reported by computer scientists using their own jargon which is unfamiliar to surgeons. Methods A literature search was conducted in using PubMed following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. The primary outcome of this review is to provide a glossary with definitions of the commonly used AI terms in surgery to improve their understanding by surgeons. Results One hundred ninety-five studies were included in this review, and 38 AI terms related to surgery were retrieved. Convolutional neural networks were the most frequently culled term by the search, accounting for 74 studies on AI in surgery, followed by classification task ( n = 62), artificial neural networks ( n = 53), and regression ( n = 49). Then, the most frequent expressions were supervised learning (reported in 24 articles), support vector machine (SVM) in 21, and logistic regression in 16. The rest of the 38 terms was seldom mentioned. Conclusions The proposed glossary can be used by several stakeholders. First and foremost, by residents and attending consultant surgeons, both having to understand the fundamentals of AI when reading such articles. Secondly, junior researchers at the start of their career in Surgical Data Science and thirdly experts working in the regulatory sections of companies involved in the AI Business Software as a Medical Device (SaMD) preparing documents for submission to the Food and Drug Administration (FDA) or other agencies for approval.
N-terminal cysteine oxidases (NCOs) use molecular oxygen to oxidize the amino-terminal cysteine of specific proteins, thereby initiating the proteolytic N-degron pathway. To expand the characterization of the plant family of NCOs (PCOs), we performed a phylogenetic analysis across different taxa in terms of sequence similarity and transcriptional regulation. Based on this survey, we propose a distinction of PCOs into two main groups. A-type PCOs are conserved across all plant species and are generally unaffected at the mRNA level by oxygen availability. Instead, B-type PCOs differentiated in spermatophytes to acquire transcriptional regulation in response to hypoxia. The inactivation of two A-type PCOs in Arabidopsis thaliana, PCO4 and PCO5, is sufficient to activate the anaerobic response in young seedlings, whereas the additional removal of B-type PCOs leads to a stronger induction of anaerobic genes and impairs plant growth and development. Our results show that both PCO types are required to regulate the anaerobic response in angiosperms. Therefore, while it is possible to distinguish two clades within the PCO family, we conclude that they all contribute to restrain the anaerobic transcriptional program in normoxic conditions and together generate a molecular switch to toggle the hypoxic response.
In the past decades, bone tissue engineering developed and exploited many typologies of bioreactors, which, besides providing proper culture conditions, aimed at integrating those bio‐physical stimulations that cells experience in vivo, to promote osteogenic differentiation. Nevertheless, the highly challenging combination and deployment of many stimulation systems into a single bioreactor led to the generation of several unimodal bioreactors, investigating one or at mostly two of the required biophysical stimuli. These systems miss the physiological mimicry of bone cells environment and often produced contrasting results, and this makes the knowledge of bone mechanotransduction fragmented and often inconsistent. To overcome this issue, in this work we developed a perfusion and electroactive‐vibrational reconfigurable stimulation bioreactor to investigate the differentiation of SaOS‐2 bone‐derived cells, hosting a piezoelectric nanocomposite membrane as cell culture substrate. This multimodal perfusion bioreactor is designed based on a numerical (finite element) model aimed at assessing the possibility to induce membrane nano‐scaled vibrations (with ~12 nm amplitude at a frequency of 939 kHz) during perfusion (featuring 1.46 dyn cm‐2 wall shear stress), large enough for inducing a physiologically‐relevant electric output (in the order of 10 mV on average) on the membrane surface. This study explored the effects of different stimuli individually, enabling to switch on one stimulation at a time, and then, to combine them in order to induce a faster bone matrix deposition rate. Biological results demonstrate that the multimodal configuration is the most effective in inducing SaOS‐2 cell differentiation, leading to 20‐fold higher collagen deposition compared to static cultures, and to 1.6‐fold and 1.2‐fold higher deposition than the perfused‐ or vibrated‐only cultures. Our promising results concerning the deployment of multimodal bioreactors can provide tissue engineering scientists with a comprehensive and biomimetic stimulation platform for a better understanding of mechanotransduction phenomena beyond cells differentiation. This article is protected by copyright. All rights reserved.
This paper presents a principle to develop multi‐function dielectric elastomer actuators (DEAs) that can concurrently accomplish linear actuation and sound generation through a single electrical input. A centimeter‐scale cone‐shaped DEA is fabricated using silicone‐based dielectric and electrodes. Measurements of the vibro‐acoustic response reveal that the pumping deformation of the DEA contributes to a negligible extent in the sound generation, which is hence ascribable to higher order structural modes whose frequency pass‐band is highly uncoupled from that of the pumping mode. Exciting the DEA with a multi‐chromatic input voltage allows achieving strokes close to 1 mm or blocking forces over 0.5 N, while simultaneously generating sound pressure levels over 60 dB, regardless of possible forces and/or mechanical constraints on the DEA pumping motion. The ability of the DEA to concurrently generate linear actuation and sound is demonstrated via proof‐of‐concept tests: the DEA can reproduce music, while at the same time generating a deformation pulse or lifting a load comparable with its own blocking force. Furthermore, measuring the current generated by the DEA allows detecting deformations impressed by the exterior and use the DEA as an active audio‐tactile interface, which produces a combined vibro‐acoustic stimulus in response to a user's touch.
Articular cartilage is known to have limited intrinsic self-healing capacity when a defect or a degeneration process occurs. Hydrogels represent promising biomaterials for cell encapsulation and injection in cartilage defects by creating an environment that mimics the cartilage extracellular matrix. The aim of this study is the analysis of two different concentrations (1:1 and 1:2) of VitroGel® (VG) hydrogels without (VG-3D) and with arginine-glycine-aspartic acid (RGD) motifs, (VG-RGD), verifying their ability to support chondrogenic differentiation of encapsulated human adipose mesenchymal stromal cells (hASCs). We analyzed the hydrogel properties in terms of rheometric measurements, cell viability, cytotoxicity, and the expression of chondrogenic markers using gene expression, histology, and immunohistochemical tests. We highlighted a shear-thinning behavior of both hydrogels, which showed good injectability. We demonstrated a good morphology and high viability of hASCs in both hydrogels. VG-RGD 1:2 hydrogels were the most effective, both at the gene and protein levels, to support the expression of the typical chondrogenic markers, including collagen type 2, SOX9, aggrecan, glycosaminoglycan, and cartilage oligomeric matrix protein and to decrease the proliferation marker MKI67 and the fibrotic marker collagen type 1. This study demonstrated that both hydrogels, at different concentrations, and the presence of RGD motifs, significantly contributed to the chondrogenic commitment of the laden hASCs.
Background Stroke related motor function deficits affect patients' likelihood of returning to professional activities, limit their participation in society and functionality in daily living. Hence, robot-aided gait rehabilitation needs to be fruitful and effective from a motor learning perspective. For this reason, optimal human–robot interaction strategies are necessary to foster neuroplastic shaping during therapy. Therefore, we performed a systematic search on the effects of different control algorithms on quantitative objective gait parameters of post-acute stroke patients. Methods We conducted a systematic search on four electronic databases using the Population Intervention Comparison and Outcome format. The heterogeneity of performance assessment, study designs and patients’ numerosity prevented the possibility to conduct a rigorous meta-analysis, thus, the results were presented through narrative synthesis. Results A total of 31 studies (out of 1036) met the inclusion criteria, without applying any temporal constraints. No controller preference with respect to gait parameters improvements was found. However, preferred solutions were encountered in the implementation of force control strategies mostly on rigid devices in therapeutic scenarios. Conversely, soft devices, which were all position-controlled, were found to be more commonly used in assistive scenarios. The effect of different controllers on gait could not be evaluated since conspicuous heterogeneity was found for both performance metrics and study designs. Conclusions Overall, due to the impossibility of performing a meta-analysis, this systematic review calls for an outcome standardisation in the evaluation of robot-aided gait rehabilitation. This could allow for the comparison of adaptive and human-dependent controllers with conventional ones, identifying the most suitable control strategies for specific pathologic gait patterns. This latter aspect could bolster individualized and personalized choices of control strategies during the therapeutic or assistive path.
Background Rehabilitation medicine is facing a new development phase thanks to a recent wave of rigorous clinical trials aimed at improving the scientific evidence of protocols. This phenomenon, combined with new trends in personalised medical therapies, is expected to change clinical practice dramatically. The emerging field of Rehabilomics is only possible if methodologies are based on biomedical data collection and analysis. In this framework, the objective of this work is to develop a systematic review of machine learning algorithms as solutions to predict motor functional recovery of post-stroke patients after treatment. Methods We conducted a comprehensive search of five electronic databases using the Patient, Intervention, Comparison and Outcome (PICO) format. We extracted health conditions, population characteristics, outcome assessed, the method for feature extraction and selection, the algorithm used, and the validation approach. The methodological quality of included studies was assessed using the prediction model risk of bias assessment tool (PROBAST). A qualitative description of the characteristics of the included studies as well as a narrative data synthesis was performed. Results A total of 19 primary studies were included. The predictors most frequently used belonged to the areas of demographic characteristics and stroke assessment through clinical examination. Regarding the methods, linear and logistic regressions were the most frequently used and cross-validation was the preferred validation approach. Conclusions We identified several methodological limitations: small sample sizes, a limited number of external validation approaches, and high heterogeneity among input and output variables. Although these elements prevented a quantitative comparison across models, we defined the most frequently used models given a specific outcome, providing useful indications for the application of more complex machine learning algorithms in rehabilitation medicine.
Background Robot-assisted pancreatoduodenectomy (RPD) has shown some advantages over open pancreatoduodenectomy (OPD) but few studies have reported a cost analysis between the two techniques. We conducted a structured cost-analysis comparing pancreatoduodenectomy performed with the use of the da Vinci Xi, and the traditional open approach, and considering healthcare direct costs associated with the intervention and the short-term post-operative course.Materials and methodsTwenty RPD and 194 OPD performed between January 2011 and December 2020 by the same operator at our high-volume multidisciplinary center for robot-assisted surgery and for pancreatic surgery, were retrospectively analyzed. Two comparable groups of 20 patients (Xi-RPD-group) and 40 patients (OPD-group) were obtained matching 1:2 the RPD-group with the OPD-group. Perioperative data and overall costs, including overall variable costs (OVCs) and fixed costs, were compared.ResultsNo difference was reported in mean operative time: 428 min for Xi-RPD-group versus 404 min for OPD, p = 0.212. The median overall length of hospital stay was significantly lower in the Xi-RPD-group: 10 days versus 16 days, p = 0.001. In the Xi-RPD-group, consumable costs were significantly higher (€6149.2 versus €1267.4, p < 0.001), while hospital stay costs were significantly lower: €5231.6 versus €8180 (p = 0.001). No significant differences were found in terms of OVCs: €13,483.4 in Xi-RPD-group versus €11,879.8 in OPD-group (p = 0.076).Conclusions Robot-assisted surgery is more expensive because of higher acquisition and maintenance costs. However, although RPD is associated to higher material costs, the advantages of the robotic system associated to lower hospital stay costs and the absence of difference in terms of personnel costs thanks to the similar operative time with respect to OPD, make the OVCs of the two techniques no longer different. Hence, the higher costs of advanced technology can be partially compensated by clinical advantages, particularly within a high-volume multidisciplinary center for both robot-assisted and pancreatic surgery. These preliminary data need confirmation by further studies.
In this article I maintain that when employers could free workers from the space constraint of the office without incurring unbearable economic losses, it is morally wrong not to grant workers the possibility to work remotely, as this violates the humanity formulation of Kant’s categorical imperative. The article therefore aims to contribute to the development of Kantian business ethics, taking into account a series of empirical evidence gathered in the wake of the Covid-19 pandemic. I firstly discuss the Kantian concept of meaningful work and explain why, due to a prejudice that existed with respect to remote work before the Covid-19 pandemic, the issue of freedom from the office was not given normative relevance. I then introduce a Kantian argument in defence of remote work and proceed to discuss two objections. The first objection is that remote work may well foster productivity, but it creates problems in terms of innovation and training of new staff. The second objection is that remote work hinders rather than fosters meaningful work because it deprives employees of social relations and inhibits workplace identity. I conclude by explaining why neither objection undermines the normative argument that workers should be allowed to work remotely as long as the “bearable costs” clause is met.
A significantly high percentage of hospitalized COVID-19 patients with diabetes mellitus (DM) had severe conditions and were admitted to ICU. In this review, we have delineated the plausible molecular mechanisms that could explain why there are increased clinical complications in patients with DM that become critically ill when infected with SARS-CoV2. RNA viruses have been classically implicated in manifestation of new onset diabetes. SARS-CoV2 infection through cytokine storm leads to elevated levels of pro-inflammatory cytokines creating an imbalance in the functioning of T helper cells affecting multiple organs. Inflammation and Th1/Th2 cell imbalance along with Th17 have been associated with DM, which can exacerbate SARS-CoV2 infection severity. ACE-2-Ang-(1–7)-Mas axis positively modulates β-cell and cardiac tissue function and survival. However, ACE-2 receptors dock SARS-CoV2, which internalize and deplete ACE-2 and activate Renin-angiotensin system (RAS) pathway. This induces inflammation promoting insulin resistance that has positive effect on RAS pathway, causes β-cell dysfunction, promotes inflammation and increases the risk of cardiovascular complications. Further, hyperglycemic state could upregulate ACE-2 receptors for viral infection thereby increasing the severity of the diabetic condition. SARS-CoV2 infection in diabetic patients with heart conditions are linked to worse outcomes. SARS-CoV2 can directly affect cardiac tissue or inflammatory response during diabetic condition and worsen the underlying heart conditions.
Salinity is a serious environmental issue which can negatively affect crop growth and productivity worldwide. Lettuce is generally considered as a salt-sensitive crop; however, different cultivars may have different adaptive mechanisms to this environmental stress. The application of biostimulants has proven to be a strategic strategy to improve plant responses to abiotic stresses and to foster resilience of crops during cultivation. This study intended to explore the physiological mechanisms underlying Romaine lettuce plant responses to salt stress, also in combination with the exogenous application of glutamic acid. The glutamic acid treatment was applied as foliar spray for the first time before salt exposure, followed by three applications during the stress. To understand the effect of salinity and glutamic acid treatment, different physiological and molecular analytical determinations were performed. High salinity induced a general stimulation of PSII and chlorophyll content. In particular, the performance index (+102%) and the number of reaction centres per cross section (+75,7%) increased, whereas the energy dissipation as heat per reaction centres (-32,1%) and the net rate of the centres’ closure (Mo) (-39.4%) decreased. Moreover, a reduction of yield (-26,5%) was observed in plants grown under high salinity. The concentration of proline was stimulated by salinity whereas ABA levels were reduced. The analyses of the genes encoding for ROS scavenging enzymes showed a general downregulation in response to salinity with the only exception of LsSOD. The application of the glutamic acid did not show a clear effect of the amino acid on lettuce plants, regardless the different growing conditions.
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1,226 members
Philippe Velha
  • Institute of Communication, lnformation and Perception Technologies TECIP
Tommaso Cucinotta
  • Real-Time Systems Laboratory (RETIS Lab)
Koteswararao Kondepu
  • Institute of Communication, lnformation and Perception Technologies TECIP
Antonio Minnocci
  • Institute of Life Sciences
Anna Maria Murante
  • Institute of Management - EMBEDS
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