Archivio Istituzionale della Ricerca - Università degli Studi di Pavia
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Serotonin Signaling Pathway Modulation Affects Retinal Neuron Survival in Experimental Model of Retinal Ischemia
No full textSerotonin is a key neurotransmitter involved in visual processing. Selective serotonin reuptake inhibitors (SSRIs), such as Escitalopram, enhance serotonergic transmission and exert neuroprotective effects. Although these actions are well established in the central nervous system, their influence on retinal neurons remains unclear. This study investigated whether Escitalopram provides neuroprotection to retinal neurons following ischemic injury. Rats received Escitalopram or vehicle for 12 weeks. Retinal ischemia was induced by unilateral episcleral vein cauterization. A subset of animals received a retrobulbar injection of meclofenamic acid (MFA). Retinal function was assessed using electroretinography, intraocular pressure (IOP) was monitored, and retinas were collected for immunofluorescence and Western blot. Cauterization increased IOP in both groups, inducing retinal blood flow disturbances. Immunofluorescence showed a reduced number of retinal ganglion cells after cauterization, which was alleviated by SSRI treatment. Escitalopram also elevated expression of the brain-derived neurotrophic factor. Electroretinography revealed improved photopic negative response (PhNR) amplitudes in Escitalopram-treated rats, indicating improved retinal ganglion cell function. Following MFA, PhNR remained stable in SSRI-treated animals, whereas a significant impairment was observed in the vehicle-treated group. These findings demonstrate that Escitalopram provides neuroprotection by reducing both functional and structural damage in the retina and may represent a promising therapeutic strategy for retinal neurodegeneration
Aggregating ESG scores: a Wasserstein distance-based method
No full textThe evaluation of the Environmental, Social and Governance (ESG) profile of companies is gaining more and more importance in the credit and financial system and is made more challenging by the availability of alternative - and often divergen t- ESG ratings. In addition, the contribution of the three dimensions (E, S and G) to the final evaluation is not disclosed by the raters. This paper proposes an approach for aggregating the three dimensions constituting ESG ratings by means of optimal transport from the perspective of the Wasserstein distance. An empirical exercise, conducted on a dataset related to Small and Medium Enterprises (SMEs), shows that the proposed aggregated indicator represents a statistically sound and explainable tool for the users of ESG ratings, especially when non-homogenous evaluations are provided. Our proposal is also compared to Principal Component Analysis (PCA), a state of the art machine learning algorithm widely employed in the literature concerning the building of synthetic indicators
Daily living computational skills: the correct answer is not always the exact one
No full textExact computation is the most popular and latest acquired calculation skill, while approximation (e.g., 28+17 50?) and magnitude estimation (e.g., How long is a high-speed train?) are based on early developed mechanisms. Yet, despite their ecological relevance, these skills remain overlooked in the education and clinical contexts. Our interest in exploring individual differences in estimation and approximation skills aims to provide new insight for the assessment of the daily living impact of dyscalculia in young adults.
We explored individual differences in exact (e.g., 34+8?) and approximate (e.g., 250+531≈760 or 870) computation, ecological estimation (e.g., ‘How much does a bicycle weigh?’), and non-symbolic comparison. Specific Learning Disabilities (SLD, e.g., Dyscalculia) and educational background (STEM, Humanities, etc.) were also considered as sources of variability.
Results show high internal variability, with estimation being particularly challenging. STEM and SLD participants exhibit extreme and opposite performances. Exact and non-exact tasks correlate, suggesting that although estimation and approximation are not formally acquired, they are grounded on formal calculation. The latter is a long-term trained ability across schooling. Still, everyday life requires much more: shifting the attention to everyday life computation is critical to redefine the focus of attention in a clinical setting
A cautionary case series: tafamidis mistreatment following erroneous diagnosis of transthyretin cardiac amyloidosis
No full textSelf-organized spatiotemporal quasi-phase-matching in microresonators
No full textQuasi-phase-matching (QPM) is a widely adopted technique for mitigating stringent momentum conservation in nonlinear optical processes such as second-harmonic generation (SHG). It effectively compensates for the phase velocity mismatch between optical harmonics by introducing a periodic spatial modulation to the nonlinear optical medium. Such a mechanism has been further generalized to the spatiotemporal domain, where a non-stationary spatial QPM can induce a frequency shift of the generated light. Here we demonstrate how a spatiotemporal QPM grating, consisting in a concurrent spatial and temporal modulation of the nonlinear response, naturally emerges through all-optical poling in silicon nitride microresonators. Mediated by the coherent photogalvanic effect, a traveling space-charge grating is self-organized, affecting momentum and energy conservation, resulting in a quasi-phase-matched and Doppler-shifted second harmonic. Our observation of the photoinduced spatiotemporal QPM expands the scope of phase matching conditions in nonlinear photonics
Disturbi dell’apprendimento o disturbi del sistema? Uno sguardo sui neo-immatricolati negli studi universitari
No full textNegli ultimi anni, ed in particolare dopo la pandemia, le università hanno registrato un incremento degli studenti con diagnosi di Disturbi Specifici dell’Apprendimento (DSA).
Nonostante gli aggiornamenti normativi e la condivisione di pratiche cliniche, tale crescita non è purtroppo accompagnata da una maggiore chiarezza dei profili funzionali.
Il presente lavoro di analisi documentale delle certificazioni DSA allegate al momento dell'iscrizione da 5 coorti di studenti ha messo in luce numerose criticità relative sia alle caratteristiche dei profili individuali sia delle pratiche cliniche. Le certificazioni presentano sempre più spesso comorbidità omotipica o eterotipica, non sempre risultano aggiornate e in alcuni casi sono qualitativamente deficitarie. La frequente complessità diagnostica e la presenza di inquadramenti sempre più tardivi impongono una riflessione sulla variabilità dei percorsi di identificazione e valutazione clinica, in particolare in età adolescenziale e nel giovane adulto
Long COVID’s Hidden Complexity: Machine Learning Reveals Why Personalized Care Remains Essential
No full textBackground: Long COVID can develop in individuals who have had COVID-19, regardless of the severity of their initial infection or the treatment they received. Several studies have examined the prevalence and manifestation of symptom phenotypes to comprehend the pathophysiological mechanisms associated with these symptoms. Numerous articles outlined specific approaches for multidisciplinary management and treatment of these patients, focusing primarily on those with mild acute illness. The various management models implemented focused on a patient-centered approach, where the specialists were positioned around the patient. On the other hand, the created pathways do not consider the possibility of symptom clusters when determining how to define diagnostic algorithms. Methods: This retrospective longitudinal study took place at the “Fondazione IRCCS Policlinico San Matteo”, Pavia, Italy (SMATTEO) and at the “Ospedale di Cremona”, ASST Cremona, Italy (CREMONA). Information was retrieved from the administrative data warehouse and from two dedicated registries. We included patients discharged with a diagnosis of severe COVID-19, systematically invited for a 3-month follow-up visit. Unsupervised machine learning was used to identify potential patient phenotypes. Results: Three hundred and eighty-two patients were included in these analyses. About one-third of patients were older than 65 years; a quarter were female; more than 80% of patients had multi-morbidities. Diagnoses related to the circulatory system were the most frequent, comprising 46% of cases, followed by endocrinopathies at 20%. PCA (principal component analysis) had no clustering tendency, which was comparable to the PCA plot of a random dataset. The unsupervised machine learning approach confirms these findings. Indeed, while dendrograms for the hierarchical clustering approach may visually indicate some clusters, this is not the case for the PAM method. Notably, most patients were concentrated in one cluster. Conclusions: The extreme heterogeneity of patients affected by post-acute sequelae of SARS-CoV-2 infection (PASC) has not allowed for the identification of specific symptom clusters with the most recent statistical techniques, thus preventing the generation of common diagnostic-therapeutic pathways
The X-rays detecting system of the FAMU experiment for the measurement of the muon transfer rate to carbon
No full textThe FAMU experiment is based on spectroscopy experiment. It uses exotic atoms to measure the proton Zemach radius, a convolution of the electronic and magnetic charge distribution. Specifically, there exists a direct correlation between the Zemach radius of the proton and the hyperfine splitting (HFS) in the muonic hydrogen energy ground level (μp). It is therefore a complementary way to study the proton compared to electron scattering experiments. The FAMU experimental technique takes advantage of the fact that, for given hydrogen gas mixtures, muons pass from the μp to the heavier gas atoms at a rate that is dependent on the μp energy. This results in X-rays counting rate from the heavier muonic atoms deexcitation cascade that depends on the energy of the μp. A fast detection system and excellent energy resolution in the 20-400 keV range are needed for this high precision experiment. The LaBr3(Ce) detectors are read by PMTs in this phase of the experiment. The behavior of the muon transfer rate from hydrogen to carbon has been evaluated using a detailed analysis of the performances of the detectors, which are presented below
Toward More Sustainable Solid-State Electrolytes: The Impact of Phosphorus Substitution on the Conductivity of Na4SiS4
No full textSulfide-based solid electrolytes for all-solid-state batteries (ASSBs) are known for their exceptional ionic conductivities and ease of manufacturing. In this study, the effects of aliovalent substitution of P for Si in the Na4-xSi1-xPxS4 series are investigated through a combination of structural characterization techniques (single crystal and powder X-ray diffraction, Raman spectroscopy), bond valence site energy (BVSE) analysis, and electrochemical performance assessments (electrochemical impedance spectroscopy and galvanostatic charge and discharge testing). A key contribution of this research is the determination of the optimal substitution level (x = 0.16) in the system that markedly improves conductivity of the doped samples up to 25 times compared to the parent Na4SiS4 phase. In an all-solid-state battery setup with TiS2 as the cathode and a Na-Sn alloy as the anode, this electrolyte maintains a steady performance, delivering a capacity of 100 mAh g-1. Modeling through the BVSE method highlights significant details of the mechanistic features of Na ion diffusion through Na vacancies in this system and suggests the potential of this quaternary solid electrolyte system for the design and optimization of more efficient, safer, and cost-effective ASSBs