Improving the Quality of Hospital Antibiotic Use: Impact on Multidrug-Resistant Bacterial Infections in Children

Antimicrobial resistance (AMR) is considered a rapidly growing global public health emergency. Neonates and children are among patients for whom antibiotics are largely prescribed and for whom the risk of AMR development is high. The phenomenon of increasing AMR has led to the need to develop measures aimed at the rational and effective use of the available drugs also in children and antimicrobial stewardship (AS), which is one of the measures that in adults has showed the highest efficacy in reducing antibiotic abuse and misuse, appears as an attractive approach. The aim of this manuscript is to analyze the basic principles and strategies of pediatric AS. To this end, we searched in PubMed articles published in years 2000 to 2019 containing “antimicrobial resistance,” “antibiotic use,” “antimicrobial stewardship,” and “children” or “pediatric” as keywords. Our review showed that the balance between multi-resistant organisms and new antimicrobials is extremely precarious. The AS tools are the most important weapon at our disposal to stem the phenomenon. Careful monitoring of prescriptions, continuous training of prescribing physicians and collaboration with highly qualified multidisciplinary staff, creation of local and national guidelines, use of rapid diagnostic tests, technological means of support, and research activities by testing new broad-spectrum antibiotics are mandatory. However, all of these measures must be supported by adequate investment by national and international health organizations. Only by making AS daily practice, through the use of financial resources and dedicated staff, we can fight AMR to ensure safe and effective care for our young patients

Should we be concerned when COVID-19-positive patients take opioids to control their pain? Insights from a pharmacological point of view

Objective: The purpose of this narrative review is to discuss the available information regarding the currently utilized COVID-19 therapies (and the evidence level supporting them) and opioids for chronic pain with a focus on warnings of potential interactions between these two therapeutic approaches. Materials and methods: Papers were retrieved from a PubMed search, using different combinations of keywords [e.g., pain treatment AND COVID-19 AND drug-drug interaction (DDI)], without limitations in terms of publication date and language. Results: Remdesivir is an inhibitor of CYP3A4 and may increase the plasma concentration of CYP3A4 substrates (e.g., fentanyl). Dexamethasone is an inducer of CYP3A4 and glycoprotein P, thus coadministration with drugs metabolized by this isoform will lead to their increased clearance. Dexamethasone may cause hypokalemia, thus potentiating the risk of ventricular arrhythmias if it is given with opioids able to prolong the QT interval, such as oxycodone and methadone. Finally, the existing differences among opioids with regard to their impact on immune responses should also be taken into account with only tapentadol and hydromorphone appearing neutral on both cytokine production and immune parameters. Conclusions: Clinicians should keep in mind the frequent DDIs with drugs extensively metabolized by the CYP450 system and prefer opioids undergoing a limited hepatic metabolism. Identification and management of DDIs and dissemination of the related knowledge should be a major goal in the delivery of chronic care to ensure optimized patient outcomes and facilitate updating recommendations for COVID-19 therapy in frail populations, namely comorbid, poly-medicated patients or individuals suffering from substance use disorder

Role of artificial intelligence in fighting antimicrobial resistance in pediatrics

Artificial intelligence (AI) is a field of science and engineering concerned with the computational understanding of what is commonly called intelligent behavior. AI is extremely useful in many human activities including medicine. The aim of our narrative review is to show the potential role of AI in fighting antimicrobial resistance in pediatric patients. We searched for PubMed articles published from April 2010 to April 2020 containing the keywords “artificial intelligence”, “machine learning”, “antimicrobial resistance”, “antimicrobial stewardship”, “pediatric”, and “children”, and we described the different strategies for the application of AI in these fields. Literature analysis showed that the applications of AI in health care are potentially endless, contributing to a reduction in the development time of new antimicrobial agents, greater diagnostic and therapeutic appropriateness, and, simultaneously, a reduction in costs. Most of the proposed AI solutions for medicine are not intended to replace the doctor’s opinion or expertise, but to provide a useful tool for easing their work. Considering pediatric infectious diseases, AI could play a primary role in fighting antibiotic resistance. In the pediatric field, a greater willingness to invest in this field could help antimicrobial stewardship reach levels of effectiveness that were unthinkable a few years ago

The Tachyon Inflationary Models with Exact Mode Functions

We show two analytical solutions of the tachyon inflation for which the spectrum of curvature (density) perturbations can be calculated exactly to linear order, ignoring both gravity and the self-interactions of the tachyon field . The main feature of these solutions is that the spectral indices are independent with scale.Comment: 5 pages, no figure, to appear in Phys. Rev.

Semi-supervised protein subcellular localization

<p>Abstract</p> <p>Background</p> <p>Protein subcellular localization is concerned with predicting the location of a protein within a cell using computational method. The location information can indicate key functionalities of proteins. Accurate predictions of subcellular localizations of protein can aid the prediction of protein function and genome annotation, as well as the identification of drug targets. Computational methods based on machine learning, such as support vector machine approaches, have already been widely used in the prediction of protein subcellular localization. However, a major drawback of these machine learning-based approaches is that a large amount of data should be labeled in order to let the prediction system learn a classifier of good generalization ability. However, in real world cases, it is laborious, expensive and time-consuming to experimentally determine the subcellular localization of a protein and prepare instances of labeled data.</p> <p>Results</p> <p>In this paper, we present an approach based on a new learning framework, semi-supervised learning, which can use much fewer labeled instances to construct a high quality prediction model. We construct an initial classifier using a small set of labeled examples first, and then use unlabeled instances to refine the classifier for future predictions.</p> <p>Conclusion</p> <p>Experimental results show that our methods can effectively reduce the workload for labeling data using the unlabeled data. Our method is shown to enhance the state-of-the-art prediction results of SVM classifiers by more than 10%.</p

Deployment of AI-based RBF network for photovoltaics fault detection procedure

In this paper, a fault detection algorithm for photovoltaic systems based on artificial neural networks (ANN) is proposed. Although, a rich amount of research is available in the field of PV fault detection using ANN, this paper presents a novel methodology based on only two inputs for the training, validating and testing of the Radial Basis Function (RBF) network achieving unprecedented detection accuracy of 98.1%. The proposed methodology goes beyond data normalisation and implements a ‘mapping of inputs’ approach to the data set before exposing it to the network for training. The accuracy of the proposed network is further endorsed through testing of the network in partial shading and overcast conditions

Is transcranial direct current stimulation (tDCS) effective for chronic low back pain? A systematic review and meta-analysis

Transcranial direct current stimulation (tDCS) has been used to reduce pain in range of chronic pain states. The aim of this review is to evaluate the effectiveness of tDCS on pain reduction and related disability in patients with non-specific chronic low back pain (CLBP). A computer-based systematic literature search was performed in five databases according to PRISMA guidelines. Randomized controlled trials (RCTs) that assessed the effects of tDCS on pain and related disability in patients with non-specific CLBP were included. Modified Jadad scale and Cochrane's risk of bias assessment were used to determine the studies’ quality and risk of bias. Meta-analyses were performed by calculating the standardized mean difference (SMD) at 95% confidence interval (CI). Nine RCTs (411 participants) were included in the systematic review according to inclusion criteria, while only five studies could be included in the meta-analysis. The primary motor cortex (M1) was the main stimulated target. The meta-analysis showed non-significant effect of multiple sessions of tDCS over M1 on pain reduction and disability post-treatment respectively, (SMD = 0.378; 95% CI = − 0.264–1.020; P = 0.249), (SMD = 0.143; 95% CI = − 0.214–0.499; P = 0.434). No significant adverse events were reported. The current results do not support the clinical use of tDCS for the reduction of pain and related disability in non-specific CLBP. However, the limited number of available evidence limits our conclusions on the effectiveness of these approaches

67-kD laminin receptor expression correlates with worse prognostic indicators in non-small cell lung carcinomas.

Tumor samples obtained from 72 patients resected for non-small cell lung cancer were stained immunohistochemically using an immunoperoxidase method and the MLuC5 monoclonal antibody specific for the 67-kDa laminin receptor. Sixty-one of 72 patients (84.7%) displayed a MLuC5-positive reaction, which was usually localized in both the inner surface of the plasmatic membranes and the cytoplasm of neoplastic cells. When we compared the laminin receptor expression with clinicopathological and biological parameters such as histotype, grading, T status, N status, ploidy, proliferative activity, vessel invasion, and p53 protein accumulation, the following results were observed: (a) the mean expression of the receptor was higher in the group of patients with metastatic nodal involvement than in those with uninvolved lymph nodes (P = 0.02); (b) a high Ki-67 score (>13% of positive cells) was observed in tumors with a higher mean value of laminin receptor (P = 0.004); (c) the tumors harboring neoplastic emboli in their vessels showed a higher laminin receptor immunoreactivity (P = 0.02); and (d) a borderline association was found between the high mean value of laminin receptor immunopositivity and p53 accumulation in neoplastic cell nuclei (P = 0.05). Our observations indicate that detection of high tissue levels of 67-kDa laminin receptor is associated with an invasive phenotype in non-small cell lung cancer and may provide further information in the biological characterization of this type of cancer

Vascular endothelial growth factor is associated with neovascularization and influences progression in Non Small Cell lung Carcinoma (NSCLC)

Vascular endothelial growth factor (VEGF) plays a pivotal role in the development of neovascularization in both physiological and pathological processes, e,g., developmental and reproductive angiogenesis, proliferative retinopathies, and cancers, Several solid tumors produce ample amounts of VEGF, which stimulates proliferation and migration of endothelial cells, thereby inducing neovascularization by a paracrine mechanism, Recently, VEGF expression has been shown to significantly affect the prognosis of different kinds of human cancer. Because neoangiogenesis represents an important prognostic indicator of poor prognosis in nonsmall cell lung cancer (NSCLC), we investigated the influence of VEGF during progression of this type of cancer and its relationship to tumoral neovascularization, VEGF expression was significantly associated with new vessel formation (r = 0.44; P < 0.0001), Moreover, in univariate analysis, VEGF expression significantly affected overall and disease-free survival (P = 0.00003 and P = 0.0004, respectively), Backward stepwise regression analysis indicated that VEGF expression was an independent prognostic factor in patients with NSCLC, These findings support the hypothesis that VEGF is an important angiogenic factor in primary NSCLC and may help in predicting the outcome of this group of cancers

Thrombospondins I and II messenger RNA expression in lung carcinoma: Relationship with p53 alterations, angiogenic growth factors, and vascular density

Thrombospondin (TSP) is a M-r 450,000 multifunctional matrix glycoprotein that interferes with tumor growth, angiogenesis, and metastasis, It has recently been shown that TSP expression is enhanced by the product of the p53 gene and that a down-regulation of TSP may be observed when alterations of the p53 protein occur. Moreover, a number of studies have demonstrated a regulatory activity of p53 on human vascular endothelial growth factor (VEGF), although additional investigations mill be necessary to understand their relationship. In non-small cell lung carcinoma (NSCLC), neoangiogenesis, p53 alterations, and VEGF expression seem to have meaningful implications in the development and progression of this type of cancer. The aim of this study is to identify and quantitate TSP I and TSP II mRNA in NSCLCs with respect to p53 alterations, angiogenic growth factor expression, and microvascular density. A series of 24 cases of NSCLC were analyzed. Eleven of 24 of the cases were positive for TSP II mRNA, whereas 8 of 24 showed TSP I mRNA expression. A significant inverse association was found between TSP I mRNA and fibroblast growth factor (FGF) protein expression (P = 0.00001), Tumors with low FGF protein expression (less than or equal to 40% of positive cells) presented a number of TSP I cDNA molecules, significantly higher than tumors expressing high levels of FGF protein. No association was found between TSP mRNA expression and other angiogenic growth factors (i.e., VEGF) or tumoral neovascularization. On the contrary, tumors with high levels of FGF showed a higher number of microvessels (P = 0.05), By PCR-single-strand conformational polymorphism analysis, we observed aberrations of the p53 gene in 19 of the 24 tumor samples. No association was found between p53 alterations and TSP mRNA expression, Instead, an interestingly significant association was found between the presence of p53 mutations and high VEGF protein expression (P = 0.01) and neovascularization (P = 0.03), Highly vascularized tumors showed higher VEGF protein expression (r = 0.45; P = 0.02), These data support the concept that in NSCLC, p53 exerts an important role in the control of neoangiogenesis. This influence is probably mediated by VEGF, The inverse association we found between TSP I and basic FGF suggests a different role of TSP I and TSP II in the angiogenic "switch," supporting the hypothesis that especially TSP I may have a significant function in tumor angiogenesis