ABSTRACT Introduction: Helicobacter pylori infection results in chronic gastritis, peptic ulcer, or gastric cancer; therefore, eradication of this bacterium is essential. The strategy for developing effective vaccines against H. pylori entails immunization of mice with a combination of classical and recombinant H. pylori antigens, but this has proven to be onerous in all cases. Areas covered: We have reviewed literature databases in PubMed and Scopus using the key words H. pylori, vaccine, and vaccination and have conducted a systematic review of published clinical trials and animal model studies on vaccines against H. pylori and have tried to summarize why the vaccines are not effective or only partially effective. Expert commentary: This is the perfect time to review vaccine development against H. pylori as, after several failed attempts, promising results were reported by Zeng et al. in 2015. Successful vaccine development requires knowledge of both the immune mechanisms active during natural infection by H. pylori, owing to the complicated host response against the pathogen, and the factors that allow the persistence of bacteria, such as genetic diversity of H. pylori. Moreover, various clinical trials are needed to prove vaccine efficacy.

Biomaterial strategies focused on designing scaffolds with physiologically relevant gradients provide a promising means for elucidating 3D vascular cell responses to spatial and temporal variations in matrix properties. In this study, we present a photopolymerization approach, ascending photofrontal free-radical polymerization, to generate proteolytically degradable hydrogel scaffolds of poly(ethylene) glycol with tunable continuous gradients of (1) elastic modulus (slope of 80 Pa/mm) and uniform immobilized RGD concentration (2.06 ± 0.12 mM) and (2) immobilized concentration of the RGD cell-adhesion peptide ligand (slope of 58.8 μM/mm) and uniform elastic modulus (597 ± 22 Pa). Using a coculture model of vascular sprouting, scaffolds embedded with gradients of elastic modulus induced increases in the number of vascular sprouts in the opposing gradient direction, whereas RGD gradient scaffolds promoted increases in the length of vascular sprouts toward the gradient. Furthermore, increases in vascular sprout length were found to be prominent in regions containing higher immobilized RGD concentration.

Abstract Trigeminal neuralgia is a chronic pain disorder affecting the face. In approximately 80% of cases, it is most commonly caused, when the root entry zone (REZ) of the trigeminal nerve is compressed by the superior cerebellar artery (SCA). The etiology of the remaining 20% of cases is distributed among venous, arteriovenous malformations, posterior fossa tumors, multiple sclerosis plaque compressions, and other pathologies. Combinations of those compressive factors are very rare.1 2 3 4 Herein, we present a video clip of microvascular decompression (MVD) in a 73-year-old female, who has failed conservative treatment with 6 medications over 10 years. She was affected by a unique triple compression of the right REZ by the SCA, anterior inferior cerebellar artery (AICA), and petrosal vein complex (Fig. 1A). Right-sided microsurgical decompression of the REZ of the trigeminal nerve through standard retrosigmoid craniotomy was performed by the senior author (K.I.A.). The SCA and AICA were separated from the nerve using Teflon pledgets. The petrosal vein complex was coagulated and divided, freeing up the right trigeminal nerve (Fig. 1B). The patient was discharged home on the third postoperative day with complete resolution of trigeminal neuralgia. The link to the Video can be found at: https://youtu.be/PYVvImGW0yE.

BackgroundThe effectiveness trial “Stress echo (SE) 2020” evaluates novel applications of SE in and beyond coronary artery disease. The core protocol also includes 4-site simplified scan of B-lines by lung ultrasound, useful to assess pulmonary congestion.PurposeTo provide web-based upstream quality control and harmonization of B-lines reading criteria.Methods60 readers (all previously accredited for regional wall motion, 53 B-lines naive) from 52 centers of 16 countries of SE 2020 network read a set of 20 lung ultrasound video-clips selected by the Pisa lab serving as reference standard, after taking an obligatory web-based learning 2-h module (http://se2020.altervista.org). Each test clip was scored for B-lines from 0 (black lung, A-lines, no B-lines) to 10 (white lung, coalescing B-lines). The diagnostic gold standard was the concordant assessment of two experienced readers of the Pisa lab. The answer of the reader was considered correct if concordant with reference standard reading ±1 (for instance, reference standard reading of 5 B-lines; correct answer 4, 5, or 6). The a priori determined pass threshold was 18/20 (≥ 90%) with R value (intra-class correlation coefficient) between reference standard and recruiting center) > 0.90. Inter-observer agreement was assessed with intra-class correlation coefficient statistics.ResultsAll 60 readers were successfully accredited: 26 (43%) on first, 24 (40%) on second, and 10 (17%) on third attempt. The average diagnostic accuracy of the 60 accredited readers was 95%, with R value of 0.95 compared to reference standard reading. The 53 B-lines naive scored similarly to the 7 B-lines expert on first attempt (90 versus 95%, p = NS). Compared to the step-1 of quality control for regional wall motion abnormalities, the mean reading time per attempt was shorter (17 ± 3 vs 29 ± 12 min, p < .01), the first attempt success rate was higher (43 vs 28%, p < 0.01), and the drop-out of readers smaller (0 vs 28%, p < .01).ConclusionsWeb-based learning is highly effective for teaching and harmonizing B-lines reading. Echocardiographers without previous experience with B-lines learn quickly.

Background/Aim: Pulmonary function tests are used for screening respiratory insufficiency in patients with myotonic dystrophy (DM). We analysed the agreement between two different approaches in assessment of abnormal findings of forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP), in DM patients. Methods: We used Cohen’s κ- and Bangdiwala’s B- statistic to compare the agreement between different cut-off values recommended by experts (ENMC) and the cut-off values based on the reference range (RR). We further analysed their sensitivity (Sn) and specificity (Sp) in detecting symptoms associated with respiratory insufficiency. Results: The observed agreement was: 1) for FVC: κ= –0.002, B = 0.406; 2) for FEV1: κ= 0.944, B = 0.946; 3) for MIP: κ= 0.625, B = 0.674; and 4) for MEP: κ= 0.241, B = 0.373. Overall, RR cut-off values showed higher sensitivity, whereas the ENMC values showed higher specificity in detecting symptoms of respiratory involvement. Conclusions: The two approaches showed perfect agreement in assessment of FEV1, substantial agreement for MIP, and weak agreement for FVC and MEP. RR is an established method of assessment for spirometry and should be favoured because it takes variability within the population into account. Further development and validation of regression equations for RR calculations of predicted maximal respiratory pressures, with corresponding lower limits of normal, is required. The B statistic is more robust in assessing agreement between two diagnostic methods, resolving the issue of the κ paradox.

The success of any business depends fundamentally on the possibility of balancing (symmetry) needs and their satisfaction, that is, the ability to properly define a set of success indicators. It is necessary to continuously monitor and measure the indicators that have the greatest impact on the achievement of previously set goals. Regarding transportation companies, the rationalization of transportation activities and processes plays an important role in ensuring business efficiency. Therefore, in this paper, a model for evaluating performance indicators has been developed and implemented in three different countries: Bosnia and Herzegovina, Libya and Serbia. The model consists of five phases, of which the greatest contribution is the development of a novel rough additive ratio assessment (ARAS) approach for evaluating measured performance indicators in transportation companies. The evaluation was carried out in the territories of the aforementioned countries in a total of nine companies that were evaluated on the basis of 20 performance indicators. The results obtained were verified throughout a three-phase procedure of a sensitivity analysis. The significance of the performance indicators was simulated throughout the formation of 10 scenarios in the sensitivity analysis. In addition, the following approaches were applied: rough WASPAS (weighted aggregated sum product assessment), rough SAW (simple additive weighting), rough MABAC (multi-attributive border approximation area comparison) and rough EDAS (evaluation based on distance from average solution), which showed high correlation of ranks by applying Spearman's correlation coefficient (SCC).

The regulation of functions such as respiratory or heart rate in human body as well as the control of motor movements are under the control of nervous system. As these actions and correlated tasks are directly influenced by the brain, the brain monitoring gives the possibility to differentiate the tasks, enabling at the same time the prediction of further actions. In this contribution, publicly available electroencephalography (EEG) datasets are analyzed with respect to the detection of epileptic seizure occurrence and BCI-related actions (here: cued motor imagery). For these purposes, timefrequency- based feature extraction alongside different classification methods is used. To perform the classification, Artificial Neural Network (ANN) and Support Vector Machine (SVM) are utilized and compared with previously obtained results. The feasibility of particular features for the detection of epileptic seizures and BCI-related tasks is discussed. Four different feature vectors per analyzed problem are identified. Acceptable accuracy of classification using ANN- and SVMbased classifiers is achieved using identified feature vectors.

BACKGROUND: AFP serum levels are considered as diagnostic and specific for hepatocellular carcinoma (HCC) in patients with liver cirrhosis (LC). AIM: This study aimed to examine the diagnostic value of AFP in the distinguishing of patients with HCC from patients with LC, and to analyse the potential correlation between AFP levels and liver disease stages. MATERIAL AND METHODS: Fifty patients with LC and fifty patients with HCC were included in this study. The majority of the patients were males, while the HBV aetiology was dominant. RESULTS: Significant differences between LC and HCC patients were detected for AST, ALT, GGT, bilirubin, AFP and AP. Patients with HCC had higher AFP values compared to LC. There was no significant correlation between the size of the tumour lesion and serum AFP levels. A positive correlation between AFP concentration and GGT activity was determined, as was the negative correlation between AFP and age of the subjects. The AFP value of 23.34 ng/m showed high sensitivity (84%) and specificity (82%). CONCLUSION: The size of the surface below the ROC curve (AUC) was 0.877 (0.80-0.95), which makes AFP a good biomarker and this diagnostic test is sufficient to separate patients with HCC and LC.