Archivio Istituzionale della Ricerca - Università degli Studi di Pavia
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GMSR: Gradient-integrated mamba for spectral reconstruction from RGB images
No full textMainstream approaches to spectral reconstruction primarily focus on Convolution- and Transformer-based architectures. However, CNN methods fall short in handling long-range dependencies, whereas Transformers are constrained by computational efficiency limitations. Therefore, constructing a efficient spectral reconstruction network while ensuring the quality of reconstructed hyperspectral images (HSIs) has become a major challenge. Recent breakthroughs in the state-space model (e.g., Mamba) have attracted significant attention from natural language processing to vision tasks due to its near-linear computational efficiency and superior performance, prompting our investigation into its potential for spectral reconstruction problems. To this end, we introduce the Gradient-integrated Mamba for Spectral Reconstruction from RGB Images, dubbed GMSR-Net. GMSR-Net is a lightweight model characterized by a global receptive field and linear computational complexity. Its core comprises multiple stacked Gradient Mamba (GM) blocks, each featuring a tri-branch structure. Building upon the efficient global feature representation from the Mamba, we further innovatively propose spatial gradient attention and spectral gradient attention to guide the reconstruction of spatial and spectral cues. GMSR-Net demonstrates a significant accuracy-efficiency trade-off, achieving state-of-the-art performance while markedly reducing the number of parameters and computational burdens. Compared to existing approaches, GMSR-Net slashes parameters and FLOPs by substantial margins of 8 times and 20 times, respectively. Code is available at https://github.com/wxy11-27/GMSR
Sr2+ hydroxyapatite and polylactic acid nanoparticles doped antimicrobial bioactive chitosan-based coating for medical device osteointegration
No full textBioactive coatings that combine antibacterial and pro-osteogenic components are gaining increasing attention for their ability to prevent bacterial adhesion and surface colonization while promoting integration with host tissues. This study focused on designing and developing antimicrobial nanoparticle (NP)-loaded chitosan films doped with Sr2+-enriched hydroxyapatite (SrHA) as bioactive coatings for orthopaedic medical devices. At this purpose, blank and thymol-loaded PLA nanoparticles were produced by microfluidics techniques, and the impact of the different process parameters was evaluated. The results show that nanosized particles ranging from 150 to 250 nm were produced across all PLA concentrations tested and thymol was delivered into the nanoparticles with a drug loading (DL%) of 5.8% (+/- 0.7 SD). Moreover, the SrHA was synthetized and characterized comparing it's physical-chemical properties with that of a commercial HA. In detail, the results confirm the incorporation of Sr2+ within the apatite structure with a weight ratio % around the 30%. Then, the crystalline pattern of SrHA was also investigated resulting in a crystalline structure with higher amorphous domains than those of the HA structure highlighted by the broadened peaks to the XRPD pattern due to the substitution of Ca2+ with Sr2+ characterized by larger atomic radius. Chitosan films incorporating thymol-loaded NPs and SrHA were produced using solvent casting technique and characterized through a multidisciplinary approach. The mechanical properties, along with the favourable morphology and topography of the coatings, appeared to enhance the biological response. The resulting systems supported mesenchymal stem cell proliferation and promoted the expression of genes related to osteoinduction while also exhibiting antimicrobial activity against both Grampositive and Gram-negative bacterial strains. Preclinical evaluations provided sufficient evidence of efficacy and safety, paving the way for their use as pro-osteogenic and antimicrobial coatings for orthopaedic devices as hybrid multifunctional coatings providing antimicrobial protection and pro-osteogenic stimulation offering a novel route to address two major clinical challenges such as early-stage bacterial contamination and insufficient osteointegration
The high prevalence of Whipple's disease in patients with inflammatory rheumatic diseases
No full textOBJECTIVES: Whipple's disease (WD) is a rare systemic chronic infection with a large diagnostic delay that favours immunomediated complications. Rheumatological symptoms mimicking rheumatological conditions (RC) usually appear first. However, prevalence of WD among patients with RC is still unknown, therefore, we aimed to study the prevalence of WD in a rheumatological setting and identify clinical/laboratory parameters that detect RC patients at high risk of WD. METHODS: Data of 23,094 patients attending a rheumatological outpatient clinic between 6/2019 and 8/2023 were retrospectively analysed. Clinical features of WD patients in this cohort were compared with a separate retrospective cohort of 55 WD patients for validation. RESULTS: Due to unsatisfactory response to disease-modifying anti-rheumatic drugs (DMARDs) and/or development of gastrointestinal/systemic symptoms, 38 patients were referred for duodenal biopsy and WD was diagnosed in 6/38. Thus, prevalence of WD was 6/23,094 (0.03%, 95% CI 0.01-0.06%). Considering patients with a clinical suspicion of WD, prevalence rose to 6/38 (15.78%, 95% CI 6.02-31.25%), and over 20% in males (5/21, 23.81%, 95% CI 8.22-47.2%). Interestingly, at diagnosis, erythrocyte sedimentation rate and C-reactive protein were elevated in all patients with WD. This finding was confirmed in the separate cohort of 55 patients with WD. CONCLUSIONS: WD is rare but in a rheumatological setting its prevalence is much higher than expected. Physicians should be aware of this condition and investigate its presence to reduce diagnostic delay, unnecessary DMARDs and risk of complications. Correct interpretation of clinical picture, including erythrocyte sedimentation rate and C-reactive protein, is the key to reach this diagnosis
An isotope mixing-based clustering approach for an improved apportionment of nitrate sources in groundwater systems
No full textSeveral groundwater nitrate (NO3−) studies have focused on apportioning NO3− sources for various sets of groundwater samples statistically clustered (i.e., grouped) based on hydrochemical data. This can be useful when NO3− concentrations in groundwater systems are influenced by the aquifer aqueous geochemistry. Nonetheless, several studies observed independent behavior of NO3− reflected by its insignificant correlation with most major ions in groundwater. Therefore, this study introduces a novel clustering approach using NO3− concentrations and δ15NNO3 values for classifying samples controlled by common mixing of NO3−-containing groundwaters. This clustering, constituting a first step of an approach allowing an improved apportionment of NO3− sources by MixSIAR modeling, is followed by (ii) NO3− source identification based not only on δ15NNO3 and δ18ONO3 tracers, but also on δ11B, which is particularly able to distinguish manure from sewage; (iii) constraining the model by selected NO3− sources and site-specific isotope fractionation effects; and (vi) a separate NO3− sources apportionment processing step for different clustered groundwater samples. The approach is applied to a dataset from a coastal Mediterranean agricultural area affected by several sources of NO3−. Two mixing scenarios with independent clusters were established, and the most realistic one that integrates four different clusters was retained for the subsequent steps. Mixing in three clusters is controlled by two NO3− sources (i.e., manure/sewage for two clusters, and manure/synthetic fertilizers for one cluster), whereas the fourth cluster is governed by mixing of three NO3− sources (i.e., manure, sewage, and synthetic fertilizers). MixSIAR modeling reveals manure as the major source contributing NO3− to groundwater according to the four clusters, but with different contributions varying from 61 to 71 %; consistent with differences in land use of the study area. Ultimately, the approach presented in this study provides a process to implement selective NO3− mitigation strategies, adapted to discriminated sites, rather than a general NO3− mitigation strategy applied to the whole study area
The living stones. Reassessing the Lombard group of megalithic monuments in the Copper Age
No full textThe Copper Age (European Late Neolithic) in northern Italy was marked by the involvement in the megalithic phenomenon. Various groups associated with this cultural trend emerged in the Alpine Arc, sharing common features while also displaying distinct regional characteristics. This paper presents an updated view of the Lombard group, which has benefited in recent years from several new finds, extensive archaeological research in the primary sites such as the ceremonial areas where these monoliths were positioned, and new iconographic interpretations and technological approaches. The statue-menhirs of the Lombard Group are an important ensemble of stelae, boulder-menhirs and portable objects created by selection, extraction and carving since the Late Neolithic to the end of the Copper Age. This paper argues that these monuments were not just part of a general phenomenon, but that each of the monuments had a life of its own during which they sometimes underwent significant changes
COMPUTATIONALLY-BASED DEVELOPMENT OF A MICROFLUIDIC PLATFORM FOR NANOPARTICLE SYNTHESIS: FROM DESIGN TO PRODUCTION
No full textNanomedicine is a new branch of medicine in which nanotechnologies are employed to prevent and treat diseases in an improved and personalized way. Drug-loaded nanoparticles (NPs) fall in this category and have become especially interesting following the COVID-19 pandemic, during which lipid-based NPs served as carriers to deliver pharmaceutical payloads (mRNA) into patients, improving efficiency and reducing side effects through targeted delivery. However, the synthesis of NPs is currently mainly done by bulk methods, where small variations in environmental conditions can lead to sub-optimal characteristics and high inter-batch variability.
Since NPs are formed by the mixing of different fluids, microfluidic technologies are being investigated as promising alternatives to produce polymeric and lipidic NPs. The micrometric dimensions of the channels and the laminarity of the flows employed in these techniques enable highly repeatable production processes, ensuring stable environmental parameters both locally and globally, resulting in uniform conditions throughout the entire volume involved. In this context, engineering strategies can be exploited to describe and deepen what happens in the fluid-dynamic process during the formation of NPs, revealing peculiar fluidic characteristics that may help researchers in the optimization and scaling-up of the manufacturing process. Numerical strategies (e.g., computational fluid dynamics simulations, CFD) have proved to be able to provide valuable insight into the mixing patterns involved in the formation phases. However, when optimizing new formulations, the classical characterization methods lack the mechanistic aspect of NPs assembly.
In this context, the first part of my PhD path focused on the adoption of numerical strategies to reproduce, understand, and predict the mixing process and NPs formation within microfluidic channels. To achieve this aim, three crucial aspects were addressed: i) constant comparison of numerical results with qualitative and quantitative experimental evidence; ii) introduction of novel mechanistic evidence connecting NPs formation with the constitutive elements of binary mixtures; iii) design of novel numerical variables to give insight into the impact of fluid-dynamic working conditions on the mixing process.
From a practical perspective, the accurate handling of fluids is essential to guarantee a reproducible manufacturing process able to synthetize homogeneous NPs. Hence, in recent years, microfluidic-based production stations have become accurate and reliable instruments for NPs synthesis. Even though the promising results allow rapid market growth, the high costs and limited customization of commercial devices hinder widespread adoption of such devices. In this PhD project, different microfluidic-based platforms were developed adopting syringe and peristaltic pumps.
Since each commercial microfluidic platform employs proprietary chip designs, the development of new NPs formulations becomes instrument- and chip-specific, limiting any possible transfer of know-how between laboratories. Hence, a new Design of Experiments (DoE) should be implemented, requiring extensive experimental effort and, in some cases, a novel experimental set-up to achieve an equivalent formulation. In this PhD thesis, this problem was addressed by adopting a novel numerical framework to translate an optimized liposome formulation between two distinct microfluidic chip geometries without requiring extensive experimental investigation. This approach enabled an increase in the total flow rate (TFR), thereby enhancing production throughput while preserving excellent and comparable morphological characteristics of the synthesized NPs
Biologic therapies for severe pediatric asthma: efficacy, safety, and biomarker-guided selection
No full textBackground: Severe pediatric asthma is a heterogeneous, high-burden disease marked by variable corticosteroid responsiveness, frequent exacerbations, and substantial impairment in quality of life. Advances in airway immunobiology, particularly the delineation of type-2 (T2) pathways (IgE, IL-5, IL-4/IL-13) and epithelial alarmins, have enabled the development of targeted biologic therapies for biomarker-defined patient subgroups.
Objective: To synthesize current evidence on the efficacy and safety of biologic therapies for severe pediatric asthma and to translate biomarker-driven selection into practical clinical guidance, while outlining emerging therapeutic directions.
Summary of findings: Targeted biologics, anti-IgE (omalizumab), anti-IL-5/IL-5Rα (mepolizumab, benralizumab; pediatric data for reslizumab remain limited), anti-IL-4Rα (dupilumab), and anti-TSLP (tezepelumab) improve disease control, reduce severe exacerbations, and enable steroid-sparing in appropriately selected children. Benefits are greatest in T2-high profiles, particularly with elevated blood eosinophils and/or fractional exhaled nitric oxide (FeNO), while tezepelumab shows efficacy across biomarker strata. Lung-function gains are modest to moderate but clinically meaningful. Persisting gaps include optimal treatment duration, stopping rules, long-term safety, cost, and equitable access.
Conclusions: Biologic therapies have reshaped the care of severe pediatric asthma, operationalizing precision medicine through immunologic endotyping and biomarker-guided selection. Priorities now include standardized definitions of response and remission, robust long-term safety data, and strategies to ensure equitable access across diverse pediatric populations