Is the natural feed the better nutritional therapy in patients with severe acquired brain injury? A retrospective study

SUMMARY: Background: This retrospective study aimed to assess whether the use of natural foods, also in combination with enteral nutrition, improves rehabilitative recovery in patients severe acquired brain injuries. Methods: 40 severe acquired brain injuries patients (75% males, aged 50.2 ± 16.6) were selected. The study population was divided into three groups based on the type of nutrition administered (enteral, oral, and mixed). Mini Nutritional Assessment and Level of Cognitive Functioning scales were used to assess changes from admission to discharge in each group. Multiple logistic regression model was performed to assess the association between the feeding typology and nutritional recovery. Results: At admission, about 97.5% of patients were malnourished. We found significant score changes from baseline to follow-up for both test used and in each subgroup, except for the subgroup that includes patients fed with enteral nutrition. There were significant differences in biochemical indicators, including levels of albumin (p < 0.01) and protein (p < 0.001), compared to baseline and follow-up. Oral nutrition resulted to be a significant predictor for nutritional improvement. Conclusions: Nutrition therapy within a multi-disciplinary team may improve both the hospital care and the recovery in severe acquired brain injuries population. Notably, our findings suggest that natural nutrition is superior to enteral nutrition in improving nutritional outcomes, which should be confirmed by further studies

Combining EEG signal processing with supervised methods for Alzheimer’s patients classification

Background Alzheimer’s Disease (AD) is a neurodegenaritive disorder characterized by a progressive dementia, for which actually no cure is known. An early detection of patients affected by AD can be obtained by analyzing their electroencephalography (EEG) signals, which show a reduction of the complexity, a perturbation of the synchrony, and a slowing down of the rhythms. Methods In this work, we apply a procedure that exploits feature extraction and classification techniques to EEG signals, whose aim is to distinguish patient affected by AD from the ones affected by Mild Cognitive Impairment (MCI) and healthy control (HC) samples. Specifically, we perform a time-frequency analysis by applying both the Fourier and Wavelet Transforms on 109 samples belonging to AD, MCI, and HC classes. The classification procedure is designed with the following steps: (i) preprocessing of EEG signals; (ii) feature extraction by means of the Discrete Fourier and Wavelet Transforms; and (iii) classification with tree-based supervised methods. Results By applying our procedure, we are able to extract reliable human-interpretable classification models that allow to automatically assign the patients into their belonging class. In particular, by exploiting a Wavelet feature extraction we achieve 83%, 92%, and 79% of accuracy when dealing with HC vs AD, HC vs MCI, and MCI vs AD classification problems, respectively. Conclusions Finally, by comparing the classification performances with both feature extraction methods, we find out that Wavelets analysis outperforms Fourier. Hence, we suggest it in combination with supervised methods for automatic patients classification based on their EEG signals for aiding the medical diagnosis of dementia

Efficacy of canakinumab in patients with Still's disease across different lines of biologic therapy: real-life data from the International AIDA Network Registry for Still's Disease

Introduction: The effectiveness of canakinumab may change according to the different times it is used after Still's disease onset. This study aimed to investigate whether canakinumab (CAN) shows differences in short- and long-term therapeutic outcomes, according to its use as different lines of biologic treatment.Methods: Patients included in this study were retrospectively enrolled from the AutoInflammatory Disease Alliance (AIDA) International Registry dedicated to Still's disease. Seventy-seven (51 females and 26 males) patients with Still's disease were included in the present study. In total, 39 (50.6%) patients underwent CAN as a first-line biologic agent, and the remaining 38 (49.4%) patients were treated with CAN as a second-line biologic agent or subsequent biologic agent.Results: No statistically significant differences were found between patients treated with CAN as a first-line biologic agent and those previously treated with other biologic agents in terms of the frequency of complete response (p =0.62), partial response (p =0.61), treatment failure (p &gt;0.99), and frequency of patients discontinuing CAN due to lack or loss of efficacy (p =0.2). Of all the patients, 18 (23.4%) patients experienced disease relapse during canakinumab treatment, 9 patients were treated with canakinumab as a first-line biologic agent, and nine patients were treated with a second-line or subsequent biologic agent. No differences were found in the frequency of glucocorticoid use (p =0.34), daily glucocorticoid dosage (p =0.47), or concomitant methotrexate dosage (p =0.43) at the last assessment during CAN treatment.Conclusion: Canakinumab has proved to be effective in patients with Still's disease, regardless of its line of biologic treatment

Clinical and laboratory features associated with macrophage activation syndrome in Still's disease: data from the international AIDA Network Still's Disease Registry

: To characterize clinical and laboratory signs of patients with still's disease experiencing macrophage activation syndrome (MAS) and identify factors associated with MAS development. patients with still's disease classified according to internationally accepted criteria were enrolled in the autoInflammatory disease alliance (AIDA) still's disease registry. clinical and laboratory features observed during the inflammatory attack complicated by MAS were included in univariate and multivariate logistic regression analysis to identify factors associated to MAS development. A total of 414 patients with Still's disease were included; 39 (9.4%) of them developed MAS during clinical history. At univariate analyses, the following variables were significantly associated with MAS: classification of arthritis based on the number of joints involved (p = 0.003), liver involvement (p = 0.04), hepatomegaly (p = 0.02), hepatic failure (p = 0.01), axillary lymphadenopathy (p = 0.04), pneumonia (p = 0.03), acute respiratory distress syndrome (p &lt; 0.001), platelet abnormalities (p &lt; 0.001), high serum ferritin levels (p = 0.009), abnormal liver function tests (p = 0.009), hypoalbuminemia (p = 0.002), increased LDH (p = 0.001), and LDH serum levels (p &lt; 0.001). at multivariate analysis, hepatomegaly (OR 8.7, 95% CI 1.9-52.6, p = 0.007) and monoarthritis (OR 15.8, 95% CI 2.9-97.1, p = 0.001), were directly associated with MAS, while the decade of life at Still's disease onset (OR 0.6, 95% CI 0.4-0.9, p = 0.045), a normal platelet count (OR 0.1, 95% CI 0.01-0.8, p = 0.034) or thrombocytosis (OR 0.01, 95% CI 0.0-0.2, p = 0.008) resulted to be protective. clinical and laboratory factors associated with MAS development have been identified in a large cohort of patients based on real-life data

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and objectives: It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19-related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population. Methods: Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score &gt; 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ2 test, and the risk excess was quantified by risk ratios (RRs). Results: The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p &lt; 0.001), RR = 2.19 for ICU admission (p &lt; 0.001), and RR = 2.43 for death (p &lt; 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04). Discussion: Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon

Ribosome-Inactivating Proteins: From Plant Defense to Tumor Attack

Ribosome-inactivating proteins (RIPs) are EC3.2.32.22 N-glycosidases that recognize a universally conserved stem-loop structure in 23S/25S/28S rRNA, depurinating a single adenine (A4324 in rat) and irreversibly blocking protein translation, leading finally to cell death of intoxicated mammalian cells. Ricin, the plant RIP prototype that comprises a catalytic A subunit linked to a galactose-binding lectin B subunit to allow cell surface binding and toxin entry in most mammalian cells, shows a potency in the picomolar range. The most promising way to exploit plant RIPs as weapons against cancer cells is either by designing molecules in which the toxic domains are linked to selective tumor targeting domains or directly delivered as suicide genes for cancer gene therapy. Here, we will provide a comprehensive picture of plant RIPs and discuss successful designs and features of chimeric molecules having therapeutic potential

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR&nbsp;=&nbsp;2.05, 95%CI&nbsp;=&nbsp;1.39–3.02, p&nbsp;&lt;&nbsp;0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR&nbsp;=&nbsp;0.42, 95%CI&nbsp;=&nbsp;0.18–0.99, p&nbsp;=&nbsp;0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

The Orderly Colored Longest Path Problem – a survey of applications and new algorithms

A concept of an Orderly Colored Longest Path (OCLP) refers to the problem of finding the longest path in a graph whose edges are colored with a given number of colors, under the constraint that the path follows a predefined order of colors. The problem has not been widely studied in the previous literature, especially for more than two colors in the color arrangement sequence. The recent and relevant application of OCLP is related to the interpretation of Nuclear Magnetic Resonance experiments for RNA molecules. Besides, an employment of this specific graph model can be found in transportation, games, and grid graphs. OCLP models the relationships between consecutive edges of the path, thus it appears very useful in representing the real problems with specific ties between their components. In the paper, we show OCLP’s correlation with similar issues known in graph theory. We describe the applications, three alternative models and new integer programming algorithms to solve OCLP. They are formulated by means of max flow problems in a directed graph with packing constraints over certain partitions of nodes. The methods are compared in a computational experiment run for a set of randomly generated instances