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Objective: Glutamate is the principal excitatory neurotransmitter and is involved in normal brain function. Cognitive impairment is common in multiple sclerosis (MS), and understanding its mechanisms is crucial for developing effective treatments. We used structural and metabolic brain imaging to test two hypotheses: (i) glutamate levels in grey matter regions are abnormal in MS, and (ii) patients show a relationship between glutamate concentration and memory performance. \ud \ud Methods: Eighteen patients with relapsing-remitting MS and 17 healthy controls were cognitively assessed and underwent 1H-magnetic resonance spectroscopy at 3 T to assess glutamate levels in the hippocampus, thalamus, cingulate and parietal cortices. Regression models investigated the association between glutamate concentration and memory performance independently of magnetisation transfer ratio values and grey matter lesions withint he same regions, and whole-brain grey matter volume. \ud \ud Results: Patients had worse visual and verbal memory than controls. A positive relationship between glutamate levels in the hippocampal, thalamic and cingulate regions and visuospatial memory was detected in patients, but not in healthy controls. \ud \ud Conclusions: The relationship between memory and glutamate concentration, which is unique to MS patients, suggests the reliance of memory on glutamatergic systems in MS.

Molecular electronic spins are good candidates as qubits since they are characterized by a large tunability of their electronic and magnetic properties through a rational chemical design. Coordination compounds of light transition metals are promising systems for spin-based quantum information technologies, thanks to their long spin coherence times up to room temperature. Our work aims at presenting an in-depth study on how the spin-phonon coupling in vanadyl-acetylacetonate, [VO(acac)2], can change as a function of temperature using terahertz time-domain spectroscopy and density functional theory (DFT) calculations. Powder THz spectra were recorded between 10 and 300 K. The temperature dependence of vibrational frequencies was then accounted for in the periodic DFT calculations using unit-cell parameters measured at two different temperatures and the optimized ones, as usually reported in the literature. In this way, it was possible to calculate the observed THz anharmonic frequency shift with high accuracy. The overall differences in the spin-phonon coupling magnitudes as a function of temperature were also highlighted showing that the computed trends have to be ascribed to the anisotropic variation of cell parameters.

Carfilzomib is a last generation proteasome inhibitor (PI) with proven clinical efficacy in the treatment of relapsed/refractory multiple myeloma. This drug is considered to be extremely specific in inhibiting the chymotrypsin-like activity of the 20S proteasome, encoded by the β5 subunit, overcoming some bortezomib limitations, the first PI approved for multiple myeloma therapy which is however burdened by a significant toxicity profile, due also to its off-target effects. Here, molecular approaches coupled with molecular docking studies have been used to unveil that the Insulin-Degrading Enzyme, a ubiquitous and highly conserved Zn2+ peptidase, often found to associate with proteasome in cell-based models, is targeted by carfilzomib in vitro. The drug behaves as a modulator of IDE activity, displaying an inhibitory effect over 10-fold lower than for the 20S. Notably, the interaction of IDE with the 20S enhances in vitro the inhibitory power of carfilzomib on proteasome, so that the IDE-20S complex is an even better target of carfilzomib than the 20S alone. Furthermore, IDE gene silencing after delivery of antisense oligonucleotides (siRNA) significantly reduced carfilzomib cytotoxicity in rMC1 cells, a validated model of Muller glia, suggesting that, in cells, the inhibitory activity of this drug on cell proliferation is somewhat linked to IDE and, possibly, also to its interaction with proteasome.

The digitalization of clinical workflows and the increasing performance of deep learning algorithms are paving the way towards new methods for tackling cancer diagnosis. However, the availability of medical specialists to annotate digitized images and free-text diagnostic reports does not scale with the need for large datasets required to train robust computer-aided diagnosis methods that can target the high variability of clinical cases and data produced. This work proposes and evaluates an approach to eliminate the need for manual annotations to train computer-aided diagnosis tools in digital pathology. The approach includes two components, to automatically extract semantically meaningful concepts from diagnostic reports and use them as weak labels to train convolutional neural networks (CNNs) for histopathology diagnosis. The approach is trained (through 10-fold cross-validation) on 3’769 clinical images and reports, provided by two hospitals and tested on over 11’000 images from private and publicly available datasets. The CNN, trained with automatically generated labels, is compared with the same architecture trained with manual labels. Results show that combining text analysis and end-to-end deep neural networks allows building computer-aided diagnosis tools that reach solid performance (micro-accuracy = 0.908 at image-level) based only on existing clinical data without the need for manual annotations.

It is not known whether the current territorial organization for acute revascularization treatments in ischemic stroke patients guarantees similar time to treatment and functional outcomes among different levels of institutional stroke care. We aimed to assess the impact of time to treatment on functional outcomes in ischemic stroke patients who received intravenous thrombolysis (IVT) alone, bridging (IVT plus thrombectomy), or primary thrombectomy in level 1 and level 2 Stroke Units (SUs) in Triveneto, a geographical macroarea in Northeast of Italy. We conducted an analysis of data prospectively collected from 512 consecutive ischemic stroke patients who received IVT and/or mechanical thrombectomy in 25 SUs from September 17th to December 9th 2018. The favorable outcome measures were mRS score 0–1 and 0–2 at 3months. The unfavorable outcome measures were mRS score 3–5 and death at 3months. We estimated separately the possible association of each variable for time to treatment (onset-to-door, door-to-needle, onset-to-needle, door-to-groin puncture, needle-to-groin puncture, and onset-to-groin puncture) with 3-month outcome measures by calculating the odds ratios (ORs) with two-sided 95% confidence intervals (CI) after adjustment for pre-defined variables and variables with a probability value ≤ 0.10 in the univariate analysis for each outcome measure. Distribution of acute revascularization treatments was different between level 1 and level 2 SUs (p < 0.001). Among 182 patients admitted to level 1 SUs (n = 16), treatments were IVT alone in 164 (90.1%), bridging in 12 (6.6%), and primary thrombectomy in 6 (3.3%) patients. Among 330 patients admitted to level 2 SUs (n = 9), treatments were IVT alone in 219 (66.4%), bridging in 74 (22.4%), and primary thrombectomy in 37 (11.2%) patients. Rates of excellent outcome (51.4% vs 45.9%), favorable outcome (60.1% vs 58.7%), unfavorable outcome (33.3% vs 33.8%), and death (9.8% vs 11.3%) at 3months were similar between level 1 and 2 SUs. No significant association was found between time to IVT alone (onset-to-door, door-to-needle, and onset-to-needle) and functional outcomes. After adjustment, door-to-needle time ≤ 60min (OR 4.005, 95% CI 1.232–13.016), shorter door-to-groin time (OR 0.991, 95% CI 0.983–0.999), shorter needle-to-groin time (OR 0.986, 95% CI 0.975–0.997), and shorter onset-to-groin time (OR 0.994, 95% CI 0.988–1.000) were associated with mRS 0–1. Shorter door-to-groin time (OR 0.991, 95% CI 0.984–0.998), door-to-groin time ≤ 90min (OR 12.146, 95% CI 2.193–67.280), shorter needle-to-groin time (OR 0.983, 95% CI 0.972–0.995), and shorter onset-to-groin time (OR 0.993, 95% CI 0.987–0.999) were associated with mRS 0–2. Longer door-to-groin time (OR 1.007, 95% CI 1.001–1.014) and longer needle-to-groin time (OR 1.019, 95% CI 1.005–1.034) were associated with mRS 3–5, while door-to-groin time ≤ 90min (OR 0.229, 95% CI 0.065–0.808) was inversely associated with mRS 3–5. Longer onset-to-needle time (OR 1.025, 95% CI 1.002–1.048) was associated with death. Times to treatment influenced the 3-month outcomes in patients treated with thrombectomy (bridging or primary). A revision of the current territorial organization for acute stroke treatments in Triveneto is needed to reduce transfer time and to increase the proportion of patients transferred from a level 1 SU to a level 2 SU to perform thrombectomy.

Psoriasis is a major chronic inflammatory skin disease, affecting about 3% of the population in Italy, whose management require experienced specialists in order to guarantee high‐quality standards of care. The pandemic coronavirus (2019‐nCoV; COVID‐19) has changed the approach to all patients requiring close contact during a visit, including dermatologic consultations. In Italy, true outbreak begun in Lombardy, by February 21, 2020 with exponential contagion, surpassing China in the number of deaths.

Automatic music classification has been of interest since digital data about music became available within the Web. For this task, different automatic classification approaches have been proposed but all existing approaches are based on the analysis of sounds. To the best of our knowledge, there is no automatic solution that considers only the sheet music for classification. Therefore, within the following study, we introduce a machine-learning based approach in order to assign an author to new sheet music. Different features, that best represent the style of a writer has been extracted, and are given in input for training to a kNN algorithm. In addition, the article discusses the results and cases when the classifier fails to assign the right author.

Link Prediction (LP) on Knowledge Graphs (KGs) has re-cently become a sparkling research topic, benefiting from the explosion of machine learning techniques. Several relation-learning models are pub-lished every year, mostly relying on KG embeddings. So far, however, not much has been done to interpret the features they learn and predict, and the circumstances that allow them to achieve satisfactory performances. Our research aims at opening the black box of LP models, trying to explain their behaviors. In this work we first discuss the current lim-itations of LP benchmarks, showing how the use of global metrics on largely skewed datasets hinders our understanding of these models; we then report the main takeaways from our recent comparative analysis of state-of-the-art LP models [3], identifying the most inuential structural features of the graph for predictive effectiveness.

Bioimaging and in vivo imaging are cornerstone technologies in support of biomedical diagnosis. However, in some cases imaging methods have increased cancer risks for patients. Moreover, the most widely used diagnostic medical imaging technique, X-ray imaging, is the largest man-made source of radiation exposure to the general population. Thus, the research of new efficient and less invasive materials for imaging is quite urgent. Supramolecular hydrogels have recently proved to be promising biological carriers to load versatile bioimaging agents for in vitro or in vivo bioimaging, thanks to the ability to undergo reversible swelling and gel–sol transition in response to various physiological stimuli. In addition, the biodegradability and biocompatibility allowed the use of supramolecular gels also for cancer diagnosis, as they can be facilely endocytosed into cells [1]. Remembering the good biological response of some imidazolium derived hydrogels [2], fluorescent imidazolium organic salts, that should own the double function of gelator and bioimaging agent, have been synthesized. New fluorescent hydrogels with interesting physico-chemical properties (rheology, gel-sol temperature transition and optical properties) have been tested for anti-proliferative activity, in vitro bioimaging on cancer cells and controlled release of gelator in physiological medium. Results evidence how these hydrogels can be potentially investigated as new theranostic media for anticancer research

In a multicenter setting, we applied voxel‐based methods to different structural MR imaging modalities to define the relative contributions of focal lesions, normal‐appearing white matter (NAWM), and gray matter (GM) damage and their regional distribution to cognitive deficits as well as impairment of specific cognitive domains in multiple sclerosis (MS) patients. Approval of the institutional review boards was obtained, together with written informed consent from all participants. Standardized neuropsychological assessment and conventional, diffusion tensor and volumetric brain MRI sequences were collected from 61 relapsing‐remitting MS patients and 61 healthy controls (HC) from seven centers. Patients with ≥2 abnormal tests were considered cognitively impaired (CI). The distribution of focal lesions, GM and WM atrophy, and microstructural WM damage were assessed using voxel‐wise approaches. A random forest analysis identified the best imaging predictors of global cognitive impairment and deficits of specific cognitive domains. Twenty‐three (38%) MS patients were CI. Compared with cognitively preserved (CP), CI MS patients had GM atrophy of the left thalamus, right hippocampus and parietal regions. They also showed atrophy of several WM tracts, mainly located in posterior brain regions and widespread WM diffusivity abnormalities. WM diffusivity abnormalities in cognitive‐relevant WM tracts followed by atrophy of cognitive‐relevant GM regions explained global cognitive impairment. Variable patterns of NAWM and GM damage were associated with deficits in selected cognitive domains. Structural, multiparametric, voxel‐wise MRI approaches are feasible in a multicenter setting. The combination of different imaging modalities is needed to assess and monitor cognitive impairment in MS. Hum Brain Mapp 37:1627‐1644, 2016. © 2016 Wiley Periodicals, Inc.

This paper explores the genetic structure and signatures of natural selection in different sub-populations from the Island of Sardinia, exploiting information from nearly 700,000 autosomal SNPs genotyped with the Affymetrix Genome-Wide Human SNP 6.0 Array. The genetic structure of the Sardinian population and its position within the context of other Mediterranean and European human groups were investigated in depth by comparing our data with publicly available data sets. Principal components and admixture analyses suggest a clustering of the examined samples in two significantly differentiated sub-populations (Ogliastra and Southern Sardinia), as confirmed by AMOVA (F(ST)=0.011; P

The 1 H- and 13 C-NMR spectra of the ethyl and benzyl esters and the tetrabutylammonium and tetraethylammonium salts of hyaluronic acid { 2)-β- d -Glc p A-(1 → 3)-β- d -Glc p NAc-(1 n } in Me 2 SO- d 6 have been assigned using 1D and 2D techniques. The chemical shifts of the resonance of GlcNAc C-3 suggest that the relative orientations of the monosaccharides at the (1 → 3) linkage in the esters and salts are different. Small differences in the chemical shifts of the resonance GlcA C-4 suggest only a slight conformational variation around the (1 → 4) linkage. The 13 C-NMR data also suggest similarities in conformation between the esters in Me 2 SO- d 6 and the salts in water. The chemical shifts of the 1 H resonances for NH and OH groups and their temperature dependence for the esters and salts in Me 2 SO reveal markedly stronger inter-residue hydrogen bonds between the carboxyl and NH groups and between HO-4 of GlcA and O-5 of GlcNAc for the salts. The 3 J 2,NH values indicate a slightly different orientation for the acetamido group. For solutions in Me 2 SO, the higher segmental flexibility of the esters is supported by the line widths, whereas the reduced viscosity for the tetrabutylammonium salt showed a sigmoidal concentration dependence and suggests association of chains which could contribute to the segmental rigidity. The linear concentration dependence for the benzyl ester suggests a higher overall flexibility without chain association.

Neuropsychological deficits in patients with multiple sclerosis (MS) have been shown to be associated with the major pathological substrates of the disease, ie, inflammatory demyelination and neurodegeneration. Double inversion recovery sequences allow cortical lesions (CLs) to be detected in the brain of patients with MS. Modern postprocessing techniques allow cortical atrophy to be assessed reliably.To investigate the contribution of cortical gray matter lesions and tissue loss to cognitive impairment in patients with relapsing-remitting MS.Cross-sectional survey.Referral, hospital-based MS clinic. Patients Seventy patients with relapsing-remitting MS.Neuropsychological performance was tested using the Rao Brief Repeatable Battery of Neuropsychological Tests, version A. Patients who scored 2 SDs below the mean normative values on at least 1 test of the Rao Brief Repeatable Battery of Neuropsychological Tests, version A, were considered to be cognitively impaired. A composite cognitive score (the cognitive impairment index) was computed. T2 hyperintense white matter lesion volume, contrast-enhancing lesion number, CL number and volume, normalized brain volume, and normalized neocortical gray matter volume were also assessed.Twenty-four patients with relapsing-remitting MS (34.3%) were classified as cognitively impaired. T2 hyperintense white matter lesion volume and contrast-enhancing lesion number were not different between cognitively impaired and cognitively unimpaired patients. Cognitively impaired patients had a higher CL number (P = .01) and volume (P.001) and decreased normalized brain volume (P = .02) and normalized neocortical gray matter volume (P = .002) when compared with cognitively unimpaired patients. Multivariate analysis revealed that age (beta = 0.228; P = .02), CL volume (beta = 0.452; P.001), and normalized neocortical gray matter volume (beta = 0.349; P.001) were independent predictors of the cognitive impairment index (r(2) = 0.55; F = 23.903; P.001).The burden of CLs and tissue loss are among the major structural changes associated with cognitive impairment in relapsing-remitting MS.

Background: In primary progressive multiple sclerosis (PPMS), a discrepancy exists between the modest brain white matter (WM) lesion burden and the severity of neurologic disability. Double-inversion recovery (DIR) sequences have improved MRI sensitivity in the detection of cortical lesions (CLs) in patients with relapsing-onset MS. Objective: This 2-year longitudinal study was designed to assess the frequency, extent, and rate of formation of CLs in PPMS and their relationship with T2 lesion volume (LV), gray matter (GM) atrophy, and disability. Methods: Forty-eight patients with PPMS underwent clinical and magnetic resonance examinations at baseline and after 2 years. The number and volume of CLs, WM T2 LV, and GM fraction (GMf) were assessed at baseline and at follow-up. Results: At baseline, CLs were detected in 81.2% of patients with PPMS. At least one new CL was found in 28 patients during the follow-up. In patients with PPMS, CL and T2 WM LVs increased over the follow-up. At baseline, CL number and volumes were significantly correlated with T2 WM LV, GMf, disease duration, and Expanded Disability Status Scale score, as well as with increasing GM atrophy and disability during the follow-up. A multivariate analysis showed that CL volume at baseline was an independent predictor of percentage GM volume change and disability accumulation during the subsequent 2-year period. Conclusions: Cortical lesions are a frequent finding in primary progressive multiple sclerosis. The extent of such abnormalities is associated with the extent of cortical atrophy and clinical disability, and is able to predict their changes over a medium time period.

Background Using double inversion recovery (DIR) MRI, cortical lesions can be seen in the brain of patients with multiple sclerosis (MS). The burden of such lesions seems to be well correlated with the severity of MS-related disability. Objective To investigate whether the extent of cortical damage in patients with benign MS (BMS) might contribute to explain their favorable clinical status. Methods Forty-eight patients with BMS (Expanded Disability Status Scale [EDSS] score ≤3.0 and disease duration ≥15 years) and 96 patients with non-disabling, early relapsing–remitting (RR) MS (EDSS score ≤3.0 and disease duration ≤5 years) were studied. Brain MRI, including a DIR and a fluid-attenuated inversion recovery (FLAIR) sequence, was acquired at baseline and after 12 months. On DIR images, intracortical (ICL) and cortical-subcortical lesions (CSL) were identified and their number and volume calculated. Total white matter (WM) lesion volume was quantified on FLAIR images. Results Compared with early RRMS, patients with BMS had lower number of ICL at both study time points ( P ≤ 0.001 for both comparisons). At one-year follow-up, a significant increase of ICL and CSL number and total volume was observed only in early patients with RRMS. The number and volume of cortical lesions was not correlated with WM lesion volume. Total ICL number at baseline, total cortical lesion volume at baseline, and total cortical lesion volume change were independent predictors of MS phenotype. Conclusion In patients with BMS, the selective sparing of the cortex from disease-related focal pathology might be one of the factors associated to their favorable clinical status, independently of the (possible) accrual of WM lesions.

Cortical lesions (CLs) can be detected in the majority of patients with established multiple sclerosis (MS), but little is known about their evolution over time. This study was performed to investigate the short-term MRI evolution of CLs, with the ultimate aim to achieve a better in vivo understanding of their nature. Seven hundred and sixty-eight CLs from 107 MS patients (76 with relapsing-remitting [RR] and 31 with secondary progressive [SP] MS) were followed with brain MR examinations, including a double inversion recovery (DIR) sequence, every 6 months for 1 year. CLs' number, volume and morphological features were assessed at each time-point. Six hundred and eighty CLs (88.5%) remained morphologically unchanged during the follow-up period, while 74 (9.6%) showed an increase in size. Only 6 (0.8%) CLs seen at baseline (all in RRMS patients) disappeared at follow-up MRI scans. No enlarging CLs spread into the subcortical white matter. No CLs ever showed gadolinium enhancement. At baseline, the mean number of CLs was higher in SPMS than in RRMS patients (p

analisi del nesso memoria identità nelle società globali contemporanee

A series of oligosaccharides was prepared from hyaluronate by depolymerisation with bovine testicular hyaluronidase. Complete assignment of the 1 H and 13 C NMR spectra was obtained for the disaccharide, the tetrasaccharide, and the NaBH 4 -treated tetrasaccharide, by using various 1D and 2D NMR methods. The 1 H assignments for the tetrasaccharide differ from the incomplete data reported recently (ref. 11). The 13 C NMR spectra of the aqueous di, tetra-, hexa-, and octa-saccharides of this series show that all resonances, apart from those subject to obvious end effects, have chemical shifts comparable to those of the corresponding resonances of hyaluronate in D 2 O. The observed 13 C chemical shifts suggests that cooperative intramolecular hydrogen bonds probably play a minor role in determining the conformation of hyaluronate in water.