Safety profile of recommended vaccinations in adolescents: Data from surveillance of adverse events following immunization in puglia (Italy), 2016–2020

Adolescence is a critical period for immunization, in which the adhesion rate to recommended vaccinations is often lower than desired. Since the safety of new vaccines is one of the most important factors determining vaccination hesitancy, post-marketing surveillance of adverse events following immunization (AEFIs) is recommended by the World Health Organization (WHO) to better understand the safety of these drugs. This report describes AEFIs notified in Puglia (Italy) after recommended vaccinations in adolescents aged 12 to 18 years in 2016–2020 to determine the safety profile of these products in a real-life scenario. This is a retrospective observational study. Data were gathered from the list of AEFIs notified in subjects between 12 and 18 years of age following administration of recommended vaccines in Puglia in 2016–2020. AEFIs were classified according to the WHO’s decisional algorithm, and causality assessment was carried out for serious AEFIs. From 2016 to 2020, 323,627 doses of vaccine were administered to adolescents in Puglia and 50 AEFIs were reported (reporting rate: 15.4 × 100,000 doses). Of these, 17 (34.0%) were classified as serious, and causality assessment identified 13 of them (76.5%) as vaccine related. The most common symptoms were local reactions, fever and neurological symptoms. No deaths were notified. The benefits of immunization in adolescents appear to be greater than the risk of AEFIs for all studied vaccines; in fact, AEFIs occur in less than 0.1‰ of patients and are generally mild and self-limiting

BNT162b2 mRNA COVID-19 vaccine effectiveness in the prevention of SARS-CoV-2 infection and symptomatic disease in five-month follow-up: A retrospective cohort study

To combat the COVID-19 pandemic, a mass vaccination campaign was initiated in Italy on December 27, 2020. The vaccine available to immunize Italian healthcare workers (HCWs) was the BNT162b2 mRNA COVID-19 vaccine (Comirnaty). This study evaluated the effectiveness of the vaccine against documented SARS-CoV-2 infection and symptomatic diseases in the medium- to long-term. HCWs at Bari Policlinico University-Hospital (Italy) who completed the vaccination schedule were matched with HCWs who had refused vaccination; the two groups were followed-up for 5 months (January–May 2021). Vaccine effectiveness (VE) against infection was 97.7% (95.4– 99.0%) at 14–34 days after the first dose, and 94.8% (87.0–97.8%), 83.0% (65.0–92.0%), and 81.0% (42.0–94.0%) at 14–41, 42–69, and >69 days, respectively, after the second dose. The estimated VE for documented symptomatic disease was 99.2% (96.4–99.8%) at 14–34 days after the first dose and 97.2% (90.3–99.2%), 85.0% (63.0–94.2%), and 88.0% (42.0–97.6%) at 14–41, 42–69, and >69 days, respectively, after the second dose. Efforts to increase vaccination rates should be strengthened, including mandatory vaccination for HCWs and greater incentives to increase vaccine acceptance by the general population

Knowledge and lifestyle behaviors related to covid-19 pandemic in people over 65 years old from southern Italy

Background: Control measures adopted during the COVID-19 pandemic had a considerable impact on human daily life and lifestyles. Adherence to the recommended measures is influenced by knowledge and attitudes towards the disease. This cross-sectional study aimed to assess the level of knowledge regarding COVID-19, the related control measures, and lifestyle behaviors adopted during the pandemic in a sample of elderly Italian people. Methods: A web-based questionnaire investigating socio-demographic characteristics, knowledge of COVID-19, the related preventive measures, and lifestyle changes that occurred during the pandemic, were distributed to ≥65 years old people living in South Italy. Results: A satisfactory level of knowledge about COVID-19 and the related control measures has been found in the enrolled sample. However, a decrease in physical activity, as well as worsening sleeping and dietary habits, were found in roughly 60% of participants. Females were impacted greater by these lifestyle changes. Conclusions: Participants in this study showed a good level of knowledge regarding COVID-19 and its prevention. Nevertheless, they reported an increase in unhealthy habits that may have important health consequences in the long term and should be addressed by public health interventions targeted at older people

Acceptance of covid-19 vaccination in the elderly: A cross-sectional study in Southern Italy

In Italy, at the end of 2020, a voluntary immunization plan against COVID-19 was in-troduced, involving elderly among the first target categories. The aim of this study was to assess, through an online questionnaire, the acceptance of COVID-19 vaccination in a sample of older adults from southern Italy. Of a total of 1041 respondents (41.7% males, mean age 76.6 ± 6.5), 965 (92.7%) were vaccinated or willing to be vaccinated against COVID-19, although less than half of the sample was favorable to vaccinations and agreed with mandatory immunization. Acceptance of COVID-19 vaccination was found to be positively related with higher educational level (OR = 1.875, CI95% = 1.113–3.161; p = 0.018) and having social/mass media as a main source of information (OR = 2.415 CI95% = 1.358–4.296, p = 0.003). On the contrary, an inverse relationship was found between acceptance of COVID-19 vaccination and having fulfilled the questionnaire after the intro-duction of green pass (OR = 0.218, CI95% = 0.129–0.369; p < 0.001). Therefore, although this evidence needs to be further confirmed, it is possible to agree with previous studies reporting that compulsory measures, such as green pass implementation, must be accompanied by effective education and information strategies of the target population

Cyclebase.org: version 2.0, an updated comprehensive, multi-species repository of cell cycle experiments and derived analysis results

Cell division involves a complex series of events orchestrated by thousands of molecules. To study this process, researchers have employed mRNA expression profiling of synchronously growing cell cultures progressing through the cell cycle. These experiments, which have been carried out in several organisms, are not easy to access, combine and evaluate. Complicating factors include variation in interdivision time between experiments and differences in relative duration of each cell-cycle phase across organisms. To address these problems, we created Cyclebase, an online resource of cell-cycle-related experiments. This database provides an easy-to-use web interface that facilitates visualization and download of genome-wide cell-cycle data and analysis results. Data from different experiments are normalized to a common timescale and are complimented with key cell-cycle information and derived analysis results. In Cyclebase version 2.0, we have updated the entire database to reflect changes to genome annotations, included information on cyclin-dependent kinase (CDK) substrates, predicted degradation signals and loss-of-function phenotypes from genome-wide screens. The web interface has been improved and provides a single, gene-centric graph summarizing the available cell-cycle experiments. Finally, key information and links to orthologous and paralogous genes are now included to further facilitate comparison of cell-cycle regulation across species. Cyclebase version 2.0 is available at http://www.cyclebase.org

Trend of sexually transmitted infections during the Covid-19 age. What was the impact of the pandemic and the social distancing measures?

Covid-19 pandemic has led to social distancing guidelines andresource allocation with subsequent impairment of sexual healthservices. The impact of such measures and the recommendationsregarding changes of sexual behaviour is a matter of debate

Predicting Protein Kinase Specificity: Predikin Update and Performance in the DREAM4 Challenge

Predikin is a system for making predictions about protein kinase specificity. It was declared the “best performer” in the protein kinase section of the Peptide Recognition Domain specificity prediction category of the recent DREAM4 challenge (an independent test using unpublished data). In this article we discuss some recent improvements to the Predikin web server — including a more streamlined approach to substrate-to-kinase predictions and whole-proteome predictions — and give an analysis of Predikin's performance in the DREAM4 challenge. We also evaluate these improvements using a data set of yeast kinases that have been experimentally characterised, and we discuss the usefulness of Frobenius distance in assessing the predictive power of position weight matrices

AMS 3.0: prediction of post-translational modifications

<p>Abstract</p> <p>Background</p> <p>We present here the recent update of AMS algorithm for identification of post-translational modification (PTM) sites in proteins based only on sequence information, using artificial neural network (ANN) method. The query protein sequence is dissected into overlapping short sequence segments. Ten different physicochemical features describe each amino acid; therefore nine residues long segment is represented as a point in a 90 dimensional space. The database of sequence segments with confirmed by experiments post-translational modification sites are used for training a set of ANNs.</p> <p>Results</p> <p>The efficiency of the classification for each type of modification and the prediction power of the method is estimated here using recall (sensitivity), precision values, the area under receiver operating characteristic (ROC) curves and leave-one-out tests (LOOCV). The significant differences in the performance for differently optimized neural networks are observed, yet the AMS 3.0 tool integrates those heterogeneous classification schemes into the single consensus scheme, and it is able to boost the precision and recall values independent of a PTM type in comparison with the currently available state-of-the art methods.</p> <p>Conclusions</p> <p>The standalone version of AMS 3.0 presents an efficient way to indentify post-translational modifications for whole proteomes. The training datasets, precompiled binaries for AMS 3.0 tool and the source code are available at <url>http://code.google.com/p/automotifserver</url> under the Apache 2.0 license scheme.</p

Evaluation of air contamination in orthopaedic operating theatres in hospitals in Southern Italy: The IMPACT project

Postoperative infections are a concern, especially in total knee and total hip arthroplasty. We evaluated the air quality in orthopaedic operating theatres in southeastern Italy to determine the level of bacterial contamination as a risk factor for postoperative infection. Thirty-five hospitals with operating theatres focused on total knee and total hip arthroplasty participated. We sampled the air passively and actively before surgeries began for the day (at rest) and 15 min after the surgical incision (in operation). We evaluated bacterial counts, particle size, mixed vs turbulent airflow systems, the number of doors, number of door openings during procedures and number of people in the operating theatre. We found no bacterial contamination at rest for all sampling methods, and significantly different contamination levels at rest vs in operation. We found no association between the number of people in the surgical team and bacteria counts for both mixed and turbulent airflow systems, and low bacterial loads, even when doors were always open. Overall, the air quality sampling method and type of ventilation system did not affect air quality

Identifying Human Kinase-Specific Protein Phosphorylation Sites by Integrating Heterogeneous Information from Various Sources

Phosphorylation is an important type of protein post-translational modification. Identification of possible phosphorylation sites of a protein is important for understanding its functions. Unbiased screening for phosphorylation sites by in vitro or in vivo experiments is time consuming and expensive; in silico prediction can provide functional candidates and help narrow down the experimental efforts. Most of the existing prediction algorithms take only the polypeptide sequence around the phosphorylation sites into consideration. However, protein phosphorylation is a very complex biological process in vivo. The polypeptide sequences around the potential sites are not sufficient to determine the phosphorylation status of those residues. In the current work, we integrated various data sources such as protein functional domains, protein subcellular location and protein-protein interactions, along with the polypeptide sequences to predict protein phosphorylation sites. The heterogeneous information significantly boosted the prediction accuracy for some kinase families. To demonstrate potential application of our method, we scanned a set of human proteins and predicted putative phosphorylation sites for Cyclin-dependent kinases, Casein kinase 2, Glycogen synthase kinase 3, Mitogen-activated protein kinases, protein kinase A, and protein kinase C families (avaiable at http://cmbi.bjmu.edu.cn/huphospho). The predicted phosphorylation sites can serve as candidates for further experimental validation. Our strategy may also be applicable for the in silico identification of other post-translational modification substrates