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A new thin-slab ceramic Nd:YAG laser is presented based on a non-conventional zig-zag configuration. The slab is shaped in such a way that the beam propagates internally bouncing on the thin lateral faces (Edge zig-zag). Preliminary experiments have demonstrated a power extraction of 170 W (CW) at an optical conversion efficiency of 36%. Measurements have also been performed to assess the propagation properties, at least in the thinner transverse direction, of the beam extracted with a simple stable resonator. This laser format appears as a good competitor of the more traditional face-pumped or edge-pumped zig-zag slab laser schemes.

In this manuscript, we consider well-known multi-task learning (MTL) models from the literature for linear regression problems, such as clustered MTL or weakly constrained MTL. We propose novel reformulations of the training problem for these models, based on mixed-integer quadratic programming (MIQP) techniques. We show that our approach allows to drive the optimization process up to certified global optimality, exploiting popular off-the-shelf software solvers. By computational experiments on both synthetic and real-world datasets, we show that this strategy generally leads to improvements in terms of the predictive performance of the models, if compared to the classical local optimization techniques, based on alternating minimization strategies, that are usually employed. We also suggest a number of possible extensions of our model that should further improve the quality of the obtained regressors, introducing, for example, sparsity and features selection elements.

Making use of an interferometric diagnostic system, we analyze the thermo-mechanical distortions taking place in the slab shaped ceramic Nd:YAG active medium of a 100 W class laser. These distortions are collected in different pumping regimes, both in static situations and during transient warm-up, and compared to the results of computer simulations. This procedure enables us to determine the relevance of different stress causes and thus to increase the specific power extraction of the active slab module.

Aberrant activation of Hedgehog (HH) signaling in cancer is the result of genetic alterations of upstream pathway components (canonical) or other oncogenic mechanisms (noncanonical), that ultimately concur to activate the zinc-finger transcription factors GLI1 and GLI2. Therefore, inhibition of GLI activity is a good therapeutic option to suppress both canonical and noncanonical activation of the HH pathway. However, only a few GLI inhibitors are available, and none of them have the profile required for clinical development due to poor metabolic stability and aqueous solubility, and high hydrophobicity. Two promising quinoline inhibitors of GLI were selected by virtual screening and subjected to hit-to-lead optimization, thus leading to the identification of the 4-methoxy-8-hydroxyquinoline derivative JC19. This molecule impaired GLI1 and GLI2 activities in several cellular models interfering with the binding of GLI1 and GLI2 to DNA. JC19 suppressed cancer cell proliferation by enhancing apoptosis, inducing a strong anti-tumor response in several cancer cell lines in vitro. Specificity towards GLI1 and GLI2 was demonstrated by lower activity of JC19 in GLI1- or GLI2-depleted cancer cells. JC19 showed excellent metabolic stability and high passive permeability. Notably, JC19 inhibited GLI1-dependent melanoma xenograft growth in vivo, with no evidence of toxic effects in mice. These results highlight the potential of JC19 as a novel anti-cancer agent targeting GLI1 and GLI2.

ObjectivesRecent studies supported coagulation involvement in multiple sclerosis, an inflammatory-demyelinating and degenerative disease of the central nervous system. The main objectives of this observational study were to identify the most specific pro-coagulative/vascular factors for multiple sclerosis pathogenesis and to correlate them with brain hemodynamic abnormalities.MethodsWe compared i) serum/plasma levels of complement(C)/coagulation/vascular factors, viral/microbiological assays, fat-soluble vitamins and lymphocyte count among people with multiple sclerosis sampled in a clinical remission (n=30; 23F/7M, 40 ± 8.14 years) or a relapse (n=30; 24F/6M, age 41 ± 10.74 years) and age/sex-matched controls (n=30; 23F/7M, 40 ± 8.38 years); ii) brain hemodynamic metrics at dynamic susceptibility contrast-enhanced 3T-MRI during relapse and remission, and iii) laboratory data with MRI perfusion metrics and clinical features of people with multiple sclerosis. Two models by Partial Least Squares Discriminant Analysis were performed using two groups as input: (1) multiple sclerosis vs. controls, and (2) relapsing vs. remitting multiple sclerosis.ResultsCompared to controls, multiple sclerosis patients had a higher Body-Mass-Index, Protein-C and activated-C9; and a lower activated-C4. Levels of Tissue-Factor, Tie-2 and P-Selectin/CD62P were lower in relapse compared to remission and HC, whereas Angiopoietin-I was higher in relapsing vs. remitting multiple sclerosis. A lower number of total lymphocytes was found in relapsing multiple sclerosis vs. remitting multiple sclerosis and controls. Cerebral-Blood-Volume was lower in normal-appearing white matter and left caudatum while Cerebral-Blood-Flow was inferior in bilateral putamen in relapsing versus remitting multiple sclerosis. The mean-transit-time of gadolinium-enhancing lesions negatively correlated with Tissue-Factor. The top-5 discriminating variables for model (1) were: EBV-EBNA-1 IgG, Body-Mass-Index, Protein-C, activated-C4 and Tissue-Factor whereas for model (2) were: Tissue-Factor, Angiopoietin-I, MCHC, Vitamin A and T-CD3.ConclusionTissue-factor was one of the top-5 variables in the models discriminating either multiple sclerosis from controls or multiple sclerosis relapse from remission and correlated with mean-transit-time of gadolinium-enhancing lesions. Tissue-factor appears a promising pro-coagulative/vascular biomarker and a possible therapeutic target in relapsing-remitting multiple sclerosis.Clinical trial registrationClinicalTrials.gov, identifier NCT04380220.

Understanding and monitoring the ecological quality of coastal waters is crucial for preserving marine ecosystems. Eutrophication is one of the major problems affecting the ecological state of coastal marine waters. For this reason, the control of the trophic conditions of aquatic ecosystems is needed for the evaluation of their ecological quality. This study leverages space-based Sentinel-3 Ocean and Land Color Instrument imagery (OLCI) to assess the ecological quality of Mediterranean coastal waters using the Trophic Index (TRIX) key indicator. In particular, we explore the feasibility of coupling remote sensing and machine learning techniques to estimate the TRIX levels in the Ligurian, Tyrrhenian, and Ionian coastal regions of Italy. Our research reveals distinct geographical patterns in TRIX values across the study area, with some regions exhibiting eutrophic conditions near estuaries and others showing oligotrophic characteristics. We employ the Random Forest Regression algorithm, optimizing calibration parameters to predict TRIX levels. Feature importance analysis highlights the significance of latitude, longitude, and specific spectral bands in TRIX prediction. A final statistical assessment validates our model’s performance, demonstrating a moderate level of error (MAE of 0.51) and explanatory power (R2 of 0.37). These results highlight the potential of Sentinel-3 OLCI imagery in assessing ecological quality, contributing to our understanding of coastal water ecology. They also underscore the importance of merging remote sensing and machine learning in environmental monitoring and management. Future research should refine methodologies and expand datasets to enhance TRIX monitoring capabilities from space.

To investigate whether inner nuclear layer (INL) thickness as assessed with optical coherence tomography differs between patients with progressive MS (P-MS) according to age and disease activity. In this retrospective longitudinal analysis, differences in terms of peripapillary retinal nerve fiber layer (pRNFL), ganglion cell layer + inner plexiform layer (GCIPL), INL and T1/T2 lesion volumes (T1LV/T2LV) were assessed between 84 patients with P-MS and 36 sex- and age-matched healthy controls (HCs) and between patients stratified according to age (cut-off: 51 years) and evidence of clinical/MRI activity in the previous 12 months RESULTS: pRNFL and GCIPL thickness were significantly lower in patients with P-MS than in HCs (p = 0.003 and p < 0.0001, respectively). INL was significantly thicker in patients aged < 51 years compared to the older ones and HCs (38.2 vs 36.5 and 36.7 μm; p = 0.038 and p = 0.04, respectively) and in those who presented MRI activity (new T2/gadolinium-enhancing lesions) in the previous 12 months compared to the ones who did not and HCs (39.5 vs 36.4 and 36.7 μm; p = 0.003 and p = 0.008, respectively). Recent MRI activity was significantly predicted by greater INL thickness (Nagelkerke R2 0.36, p = 0.001). INL thickness was higher in younger patients with P-MS with recent MRI activity, a criterion used in previous studies to identify a specific subset of patients with P-MS who best responded to disease-modifying treatment. If this finding is confirmed, we suggest that INL thickness might be a useful tool in stratification of patients with P-MS for current and experimental treatment choice.

Abstract Background In multiple sclerosis, the correlation between white matter lesion volumes (LV) and expanded disability status scale (EDSS) is at best moderate, leading to the “clinico-radiological paradox”, influenced by many factors, including the lack of information on the spatial localisation of each lesion on synthetic metrics such as LV. We used a probabilistic approach to provide the volume of WM tracts that may be disconnected by lesions and to evaluate its correlation with EDSS. Methods Forty-five patients (aged 37.4 ± 6.8 years, mean ± standard deviation; 30 females; 29 relapsing-remitting, 16 progressive) underwent 3-T magnetic resonance imaging. Both LV and the volume of the tracts crossing the lesioned regions (disconnectome volume, DV) were calculated using BCBtoolkit and correlated with EDSS. Results T1-weighted LV and DV significantly correlated with EDSS (p ≤ 0.006 r ≥ 0.413) as it was for T2-weighted LV and T2-weighted DV (p ≤ 0.004 r ≥ 0.430), but only T1-weighetd and T2-weighted DVs were EDSS significant predictors (p ≤ 0.001). The correlations of T1-weighted and T2-weighted LV with EDSS were significantly mediated by DV, while no effect of LV on the EDSS-DV correlation was observed. Conclusion The volume of disconnected WM bundles mediates the LV-EDSS correlation, representing the lonely EDSS predictor.

IntroductionThe subventricular zone (SVZ) represents one of the main adult brain neurogenesis niche. In-vivo imaging of SVZ is very challenging and little is known about MRI correlates of SVZ macro- and micro-structural injury in multiple sclerosis (MS) patients.MethodsThe aim of the present study is to evaluate differences in terms of volume and microstructural changes [as assessed with the novel Spherical Mean Technique (SMT) model, evaluating: Neurite Signal fraction (INTRA); Extra-neurite transverse (EXTRATRANS) and mean diffusivity (EXTRAMD)] in SVZ between relapsing-remitting (RR) or progressive (P) MS patients and healthy controls (HC). We are also going to explore whether SVZ microstructural injury correlate with caudate (a nucleus that is in the vicinity of the SVZ) or thalamus (another well-defined grey matter area which is further from SVZ than caudate) volume and clinical disability. Clinical and brain MRI data were prospectively acquired from 20 HC, 101 RRMS, and 50 PMS patients. Structural and diffusion metrics inside the global SVZ, normal appearing (NA-) SVZ, caudate and thalamus were collected.ResultsWe found a statistically significant difference between groups in terms of NA-SVZ EXTRAMD (PMS>RRMS>HC; p = 0.002), EXTRATRANS (PMS>RRMS>HC; pRRMS>PMS; p = 0.009). Multivariable models showed that NA-SVZ metrics significantly predicted caudate (R2 = 0.21, p

IntroductionThe Central Vein Sign (CVS) has been suggested as a potential biomarker to improve diagnostic specificity in multiple sclerosis (MS). Nevertheless, the impact of comorbidities on CVS performance has been poorly investigated so far. Despite the similar features shared by MS, migraine and Small Vessel Disease (SVD) at T2-weighted conventional MRI sequences, ex-vivo studies demonstrated their heterogeneous histopathological substrates. If in MS, inflammation, primitive demyelination and axonal loss coexist, in SVD demyelination is secondary to ischemic microangiopathy, while the contemporary presence of inflammatory and ischemic processes has been suggested in migraine. The aims of this study were to investigate the impact of comorbidities (risk factors for SVD and migraine) on the global and subregional assessment of the CVS in a large cohort of MS patients and to apply the Spherical Mean Technique (SMT) diffusion model to evaluate whether perivenular and non-perivenular lesions show distinctive microstructural features.Methods120 MS patients stratified into 4 Age Groups performed 3T brain MRI. WM lesions were classified in “perivenular” and “non-perivenular” by visual inspection of FLAIR* images; mean values of SMT metrics, indirect estimators of inflammation, demyelination and fiber disruption (EXTRAMD: extraneurite mean diffusivity, EXTRATRANS: extraneurite transverse diffusivity and INTRA: intraneurite signal fraction, respectively) were extracted.ResultsOf the 5303 lesions selected for the CVS assessment, 68.7% were perivenular. Significant differences were found between perivenular and non-perivenular lesion volume in the whole brain (p < 0.001) and between perivenular and non-perivenular lesion volume and number in all the four subregions (p < 0.001 for all). The percentage of perivenular lesions decreased from youngest to oldest patients (79.7%–57.7%), with the deep/subcortical WM of oldest patients as the only subregion where the number of non-perivenular was higher than the number of perivenular lesions. Older age and migraine were independent predictors of a higher percentage of non-perivenular lesions (p < 0.001 and p = 0.013 respectively). Whole brain perivenular lesions showed higher inflammation, demyelination and fiber disruption than non perivenular lesions (p = 0.001, p = 0.001 and p = 0.02 for EXTRAMD, EXTRATRANS and INTRA respectively). Similar findings were found in the deep/subcortical WM (p = 0.001 for all). Compared to non-perivenular lesions, (i) perivenular lesions located in periventricular areas showed a more severe fiber disruption (p = 0.001), (ii) perivenular lesions located in juxtacortical and infratentorial regions exhibited a higher degree of inflammation (p = 0.01 and p = 0.05 respectively) and (iii) perivenular lesions located in infratentorial areas showed a higher degree of demyelination (p = 0.04).DiscussionAge and migraine have a relevant impact in reducing the percentage of perivenular lesions, particularly in the deep/subcortical WM. SMT may differentiate perivenular lesions, characterized by higher inflammation, demyelination and fiber disruption, from non perivenular lesions, where these pathological processes seemed to be less pronounced. The development of new non-perivenular lesions, especially in the deep/subcortical WM of older patients, should be considered a “red flag” for a different -other than MS- pathophysiology.