Adaptive data synchronization algorithm for IoT-oriented low-power wide-area networks

The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications

Protein-Protein Interaction Prediction via Graph Signal Processing

This paper tackles the problem of predicting the protein-protein interactions that arise in all living systems. Inference of protein-protein interactions is of paramount importance for understanding fundamental biological phenomena, including cross-species protein-protein interactions, such as those causing the 2020-21 pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, it is relevant also for applications such as drug repurposing, where a known authorized drug is applied to novel diseases. On the other hand, a large fraction of existing protein interactions are not known, and their experimental measurement is resource consuming. To this purpose, we adopt a Graph Signal Processing based approach modeling the protein-protein interaction (PPI) network (a.k.a. the interactome) as a graph and some connectivity related node features as a signal on the graph. We then leverage the signal on graph features to infer links between graph nodes, corresponding to interactions between proteins. Specifically, we develop a Markovian model of the signal on graph that enables the representation of connectivity properties of the nodes, and exploit it to derive an algorithm to infer the graph edges. Performance assessment by several metrics recognized in the literature proves that the proposed approach, named GRAph signal processing Based PPI prediction (GRABP), effectively captures underlying biologically grounded properties of the PPI network

Looking Beyond the Glioblastoma Mask: Is Genomics the Right Path?

Glioblastomas are the most frequent and malignant brain tumor hallmarked by an invariably poor prognosis. They have been classically differentiated into primary isocitrate dehydrogenase 1 or 2 (IDH1 -2) wild-type (wt) glioblastoma (GBM) and secondary IDH mutant GBM, with IDH wt GBMs being commonly associated with older age and poor prognosis. Recently, genetic analyses have been integrated with epigenetic investigations, strongly implementing typing and subtyping of brain tumors, including GBMs, and leading to the new WHO 2021 classification. GBM genomic and epigenomic profile influences evolution, resistance, and therapeutic responses. However, differently from other tumors, there is a wide gap between the refined GBM profiling and the limited therapeutic opportunities. In addition, the different oncogenes and tumor suppressor genes involved in glial cell transformation, the heterogeneous nature of cancer, and the restricted access of drugs due to the blood–brain barrier have limited clinical advancements. This review will summarize the more relevant genetic alterations found in GBMs and highlight their potential role as potential therapeutic targets

Efficacy and safety of ketamine and esketamine for unipolar and bipolar depression: an overview of systematic reviews with meta-analysis

Background Unipolar and bipolar depression present treatment challenges, with patients sometimes showing limited or no response to standard medications. Ketamine and its enantiomer, esketamine, offer promising alternative treatments that can quickly relieve suicidal thoughts. This Overview of Reviews (OoR) analyzed and synthesized systematic reviews (SRs) with meta-analysis on randomized clinical trials (RCTs) involving ketamine in various formulations (intravenous, intramuscular, intranasal, subcutaneous) for patients with unipolar or bipolar depression. We evaluated the efficacy and safety of ketamine and esketamine in treating major depressive episodes across various forms, including unipolar, bipolar, treatment-resistant, and non-resistant depression, in patient populations with and without suicidal ideation, aiming to comprehensively assess their therapeutic potential and safety profile. Methods Following PRIOR guidelines, this OoR's protocol was registered on Implasy (ID:202150049). Searches in PubMed, Scopus, Cochrane Library, and Epistemonikos focused on English-language meta-analyses of RCTs of ketamine or esketamine, as monotherapy or add-on, evaluating outcomes like suicide risk, depressive symptoms, relapse, response rates, and side effects. We included studies involving both suicidal and non-suicidal patients; all routes and formulations of administration (intravenous, intramuscular, intranasal) were considered, as well as all available comparisons with control interventions. We excluded meta-analysis in which the intervention was used as anesthesia for electroconvulsive therapy or with a randomized ascending dose design. The selection, data extraction, and quality assessment of studies were carried out by pairs of reviewers in a blinded manner. Data on efficacy, acceptability, and tolerability were extracted. Results Our analysis included 26 SRs and 44 RCTs, with 3,316 subjects. The intervention is effective and well-tolerated, although the quality of the included SRs and original studies is poor, resulting in low certainty of evidence. Limitations This study is limited by poor-quality SRs and original studies, resulting in low certainty of the evidence. Additionally, insufficient available data prevents differentiation between the effects of ketamine and esketamine in unipolar and bipolar depression. Conclusion While ketamine and esketamine show promising therapeutic potential, the current evidence suffers from low study quality. Enhanced methodological rigor in future research will allow for a more informed application of these interventions within the treatment guidelines for unipolar and bipolar depression

Treatment persistence with aripiprazole once monthly: a 4-year follow-up

Objectives: Treatment persistence refers to the act of continuing a treatment as prescribed and reflects the patient's or doctor's judgment about efficacy, tolerability, and acceptability. In patients with schizophrenia, antipsychotic persistence is often poor, because of issues such as lack or loss of efficacy, side effects, and poor adherence, which is often related to the degree to which patients find the medication and overall intervention to be helpful, tolerable, fair, reasonable, appropriate, and consistent with expectations of treatment. Despite the poor antipsychotic persistence that has been reported to date in patients with schizophrenia, we previously observed a relatively high (86%) 6 months persistence with aripiprazole once-monthly (AOM) in a group of patients with schizophrenia, treated in the real world Italian clinical practice. The present study explores the longer term persistence with AOM, over a mean follow-up period of 48 months. Methods: This was a multicenter, retrospective, non-interventional follow-up study, aimed at evaluating the longer term persistence with AOM in a group of patients with schizophrenia who had already shown persistence over a period of at least 6 months. The study included 161 individuals who had participated in our previous study, where 86% of participating individuals had shown persistence with AOM for at least 6 months. Non-persistence was defined as discontinuing the medication for any reason. Baseline demographic and clinical characteristics of patients who continued AOM were then compared to those of patients who discontinued the medication. Results: Study subjects were predominantly male (64.4%) and their mean age was 39.7 (SD: 12.24). Treatment persistence with AOM was 69.6% and 112 out of 161 patients were still receiving AOM treatment at the last follow-up visit. The mean duration of AOM treatment until the last recorded observation was 55.87 months (median 56.17, SD6.23) for the 112 persistent patients and 32.23 (median 28.68.SD 15.09) months for the 49 non-persistent individuals. The mean observation period for all patients (persistent and non-persistent) was 48.78 months (median 52.54, SD 14.64). For non-persistent subjects, the observation period ended with the discontinuation of AOM. Subjects treated with AOM at 400 mg presented a 69.6% lower risk of all-cause treatment discontinuation when compared with patients treated with 300 mg (HR: 0.314; 95% confidence interval [CI] 0.162-0.608; P = 0.001). The main reasons for discontinuation were lack of efficacy (30.6%), patient/caregiver choice (18.4%), physician's choice (16.3%), non-adherence (12.2%) and inconvenience (6.1%). Only 3 patients (6.1%) discontinued AOM for tolerability issues. Conclusions: In subjects with schizophrenia, who had already shown a 6 months persistence with AOM, a high number of patients (69.6%) continued to be persistent over a 4-year follow-up period. This may reflect a favourable profile of efficacy, tolerability, and acceptability. Larger and prospective studies are warranted to confirm our observations

COVID-19-associated vasculitis and thrombotic complications: from pathological findings to multidisciplinary discussion

Neutrophilic arterial vasculitis in COVID-19 represents a novel finding and could be responsible for thrombotic complications

Tocilizumab in patients with severe COVID-19: a retrospective cohort study

Background: No therapy is approved for COVID-19 pneumonia. The aim of this study was to assess the role of tocilizumab in reducing the risk of invasive mechanical ventilation and death in patients with severe COVID-19 pneumonia who received standard of care treatment. Methods: This retrospective, observational cohort study included adults ( 6518 years) with severe COVID-19 pneumonia who were admitted to tertiary care centres in Bologna and Reggio Emilia, Italy, between Feb 21 and March 24, 2020, and a tertiary care centre in Modena, Italy, between Feb 21 and April 30, 2020. All patients were treated with the standard of care (ie, supplemental oxygen, hydroxychloroquine, azithromycin, antiretrovirals, and low molecular weight heparin), and a non-randomly selected subset of patients also received tocilizumab. Tocilizumab was given either intravenously at 8 mg/kg bodyweight (up to a maximum of 800 mg) in two infusions, 12 h apart, or subcutaneously at 162 mg administered in two simultaneous doses, one in each thigh (ie, 324 mg in total), when the intravenous formulation was unavailable. The primary endpoint was a composite of invasive mechanical ventilation or death. Treatment groups were compared using Kaplan-Meier curves and Cox regression analysis after adjusting for sex, age, recruiting centre, duration of symptoms, and baseline Sequential Organ Failure Assessment (SOFA) score. Findings: Of 1351 patients admitted, 544 (40%) had severe COVID-19 pneumonia and were included in the study. 57 (16%) of 365 patients in the standard care group needed mechanical ventilation, compared with 33 (18%) of 179 patients treated with tocilizumab (p=0\ub741; 16 [18%] of 88 patients treated intravenously and 17 [19%] of 91 patients treated subcutaneously). 73 (20%) patients in the standard care group died, compared with 13 (7%; p<0\ub70001) patients treated with tocilizumab (six [7%] treated intravenously and seven [8%] treated subcutaneously). After adjustment for sex, age, recruiting centre, duration of symptoms, and SOFA score, tocilizumab treatment was associated with a reduced risk of invasive mechanical ventilation or death (adjusted hazard ratio 0\ub761, 95% CI 0\ub740\u20130\ub792; p=0\ub7020). 24 (13%) of 179 patients treated with tocilizumab were diagnosed with new infections, versus 14 (4%) of 365 patients treated with standard of care alone (p<0\ub70001). Interpretation: Treatment with tocilizumab, whether administered intravenously or subcutaneously, might reduce the risk of invasive mechanical ventilation or death in patients with severe COVID-19 pneumonia. Funding: None

Machine learning in predicting respiratory failure in patients with COVID-19 pneumonia - challenges, strengths, and opportunities in a global health emergency.

Aims- The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia. Methods- This was an observational study that comprised consecutive patients with COVID-19 pneumonia admitted to hospital from 21 February to 6 April 2020. The patients\u2019 medical history, demographic, epidemiologic and clinical data were collected in an electronic patient chart. The dataset was used to train predictive models using an established machine learning framework leveraging a hybrid approach where clinical expertise is applied alongside a data-driven analysis. The study outcome was the onset of moderate to severe respiratory failure defined as PaO 2 /FiO 2 ratio &lt;150 mmHg in at least one of two consecutive arterial blood gas analyses in the following 48 hours. Shapley Additive exPlanations values were used to quantify the positive or negative impact of each variable included in each model on the predicted outcome. Results- A total of 198 patients contributed to generate 1068 usable observations which allowed to build 3 predictive models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth \u201cboosted mixed model\u201d included 20 variables was selected from the model 3, achieved the best predictive performance (AUC=0.84) without worsening the FN rate. Its clinical performance was applied in a narrative case report as an example. Conclusion- This study developed a machine model with 84% prediction accuracy, which is able to assist clinicians in decision making process and contribute to develop new analytics to improve care at high technology readiness levels

Effects of cytokine blocking agents on hospital mortality in patients admitted to ICU with acute respiratory distress syndrome by SARS-CoV-2 infection: Retrospective cohort study

Background: The use of cytokine-blocking agents has been proposed to modulate the inflammatory response in patients with COVID-19. Tocilizumab and anakinra were included in the local protocol as an optional treatment in critically ill patients with acute respiratory distress syndrome (ARDS) by SARS-CoV-2 infection. This cohort study evaluated the effects of therapy with cytokine blocking agents on in-hospital mortality in COVID-19 patients requiring mechanical ventilation and admitted to intensive care unit. Methods: The association between therapy with tocilizumab or anakinra and in-hospital mortality was assessed in consecutive adult COVID-19 patients admitted to our ICU with moderate to severe ARDS. The association was evaluated by comparing patients who received to those who did not receive tocilizumab or anakinra and by using different multivariable Cox models adjusted for variables related to poor outcome, for the propensity to be treated with tocilizumab or anakinra and after patient matching. Results: Sixty-six patients who received immunotherapy (49 tocilizumab, 17 anakinra) and 28 patients who did not receive immunotherapy were included. The in-hospital crude mortality was 30,3% in treated patients and 50% in non-treated (OR 0.77, 95% CI 0.56-1.05, p=0.069). The adjusted Cox model showed an association between therapy with immunotherapy and in-hospital mortality (HR 0.40, 95% CI 0.19-0.83, p=0.015). This protective effect was further confirmed in the analysis adjusted for propensity score, in the propensity-matched cohort and in the cohort of patients with invasive mechanical ventilation within 2 hours after ICU admission. Conclusions: Although important limitations, our study showed that cytokine-blocking agents seem to be safe and to improve survival in COVID-19 patients admitted to ICU with ARDS and the need for mechanical ventilation

Chronic constipation diagnosis and treatment evaluation: The "CHRO.CO.DI.T.E." study

Background: According to Rome criteria, chronic constipation (CC) includes functional constipation (FC) and irritable bowel syndrome with constipation (IBS-C). Some patients do not meet these criteria (No Rome Constipation, NRC). The aim of the study was is to evaluate the various clinical presentation and management of FC, IBS-C and NRC in Italy. Methods: During a 2-month period, 52 Italian gastroenterologists recorded clinical data of FC, IBS-C and NRC patients, using Bristol scale, PAC-SYM and PAC-QoL questionnaires. In addition, gastroenterologists were also asked to record whether the patients were clinically assessed for CC for the first time or were in follow up. Diagnostic tests and prescribed therapies were also recorded. Results: Eight hundred seventy-eight consecutive CC patients (706 F) were enrolled (FC 62.5%, IBS-C 31.3%, NRC 6.2%). PAC-SYM and PAC-QoL scores were higher in IBS-C than in FC and NRC. 49.5% were at their first gastroenterological evaluation for CC. In 48.5% CC duration was longer than 10 years. A specialist consultation was requested in 31.6%, more frequently in IBS-C than in NRC. Digital rectal examination was performed in only 56.4%. Diagnostic tests were prescribed to 80.0%. Faecal calprotectin, thyroid tests, celiac serology, breath tests were more frequently suggested in IBS-C and anorectal manometry in FC. More than 90% had at least one treatment suggested on chronic constipation, most frequently dietary changes, macrogol and fibers. Antispasmodics and psychotherapy were more frequently prescribed in IBS-C, prucalopride and pelvic floor rehabilitation in FC. Conclusions: Patients with IBS-C reported more severe symptoms and worse quality of life than FC and NRC. Digital rectal examination was often not performed but at least one diagnostic test was prescribed to most patients. Colonoscopy and blood tests were the "first line" diagnostic tools. Macrogol was the most prescribed laxative, and prucalopride and pelvic floor rehabilitation represented a "second line" approach. Diagnostic tests and prescribed therapies increased by increasing CC severity