Physics-Informed Neural Networks for 2nd order ODEs with sharp gradients

In this work, four different methods based on Physics-Informed Neural Networks (PINNs) for solving Differential Equations (DE) are compared: Classic-PINN that makes use of Deep Neural Networks (DNNs) to approximate the DE solution;Deep-TFC improves the efficiency of classic-PINN by employing the constrained expression from the Theory of Functional Connections (TFC) so to analytically satisfy the DE constraints;PIELM that improves the accuracy of classic-PINN by employing a single-layer NN trained via Extreme Learning Machine (ELM) algorithm;X-TFC, which makes use of both constrained expression and ELM. The last has been recently introduced to solve challenging problems affected by discontinuity, learning solutions in cases where the other three methods fail. The four methods are compared by solving the boundary value problem arising from the 1D Steady-State Advection–Diffusion Equation for different values of the diffusion coefficient. The solutions of the DEs exhibit steep gradients as the value of the diffusion coefficient decreases, increasing the challenge of the problem

Mapping host-related correlates of influenza vaccine-induced immune response: An umbrella review of the available systematic reviews and meta-analyses

Seasonal influenza is the leading infectious disease in terms of its health and socioeconomic impact. Annual immunization is the most efficient way to reduce this burden. Several correlates of influenza vaccine-induced protection are commonly used, owing to their ready availability and cheapness. Influenza vaccine-induced immunogenicity is a function of host-, virus-and vaccine-related factors. Host-related factors constitute the most heterogeneous group. The objective of this study was to analyze the available systematic evidence on the host factors able to modify influenza vaccine-induced immunogenicity. An umbrella review approach was undertaken. A total of 28 systematic reviews/meta-analyses were analyzed—these covered the following domains: intravenous drug use, psychological stress, acute and chronic physical exercise, genetic polymorphisms, use of pre-/pro-/symbiotics, previous Bacillus Calmette–Guérin vaccination, diabetes mellitus, vitamin D supplementation/deficiency, latent cytomegalovirus infection and various forms of immunosuppression. In order to present effect sizes on the same scale, all possible meta-analyses were re-performed and cumulative evidence synthesis ranking was carried out. The meta-analysis was conducted separately on each health condition category and virus (sub)type. A total of 97 pooled estimates were used in order to construct an evidence-based stakeholder-friendly map. The principal public health implications are discussed

Yb-1 oncoprotein controls pi3k/akt pathway by reducing pten protein level

YB-1 is a multifunctional protein overexpressed in many types of cancer. It is a crucial oncoprotein that regulates cancer cell progression and proliferation. Ubiquitously expressed in human cells, YB-1 protein functions are strictly dependent on its subcellular localization. In the cytoplasm, where YB-1 is primarily localized, it regulates mRNA translation and stability. However, in response to stress stimuli and activation of PI3K and RSK signaling, YB-1 moves to the nucleus acting as a prosurvival factor. YB-1 is reported to regulate many cellular signaling pathways in different types of malignancies. Furthermore, several observations also suggest that YB-1 is a sensor of oxidative stress and DNA damage. Here we show that YB-1 reduces PTEN intracellular levels thus leading to PI3K/Akt pathway activation. Remarkably, PTEN reduction mediated by YB-1 overexpression can be observed in human immortalized keratinocytes and HEK293T cells and cannot be reversed by proteasome inhibition. Real-time PCR data indicate that YB-1 silencing up-regulates the PTEN mRNA level. Collectively, these observations indicate that YB-1 negatively controls PTEN at the transcript level and its overexpression could confer survival and proliferative advantage to PTEN proficient cancer cells

Immunogenicity measures of influenza vaccines: A study of 1164 registered clinical trials

Influenza carries an enormous burden each year. Annual influenza vaccination is the best means of reducing this burden. To be clinically effective, influenza vaccines must be immunogenic, and several immunological assays to test their immunogenicity have been developed. This study aimed to describe the patterns of use of the various immunological assays available to measure the influenza vaccine-induced adaptive immune response and to determine its correlates of protection. A total of 76.5% of the studies included in our analysis measured only the humoral immune response. Among these, the hemagglutination-inhibition assay was by far the most widely used. Other, less common, humoral immune response assays were: virus neutralization (21.7%), enzyme-linked immunosorbent (10.1%), single radial hemolysis (4.6%), and assays able to quantify anti-neuraminidase antibodies (1.7%). By contrast, cell-mediated immunity was quantified in only 23.5% of studies. Several variables were significantly associated with the use of single assays. Specifically, some influenza vaccine types (e.g., adjuvanted, live attenuated and cell culture-derived or recombinant), study phase and study sponsorship pattern were usually found to be statistically significant predictors. We discuss the principal findings and make some suggestions from the point of view of the various stakeholders

Citizens' Attitudes, Knowledge, and Educational Needs in the Field of Omics Sciences: A Systematic Literature Review

Background: The huge development of omics sciences is changing the classical medical approach and making new technologies available. In this context, education of citizens is essential to allow appropriate decisions about their own health. Hence, we aimed to summarize existing literature regarding citizens' knowledge, attitudes, and educational needs on omics sciences. Methods: We performed a systematic literature review (SLR) using Pubmed, ISI Web of Science, and Embase databases. The eligibility criteria for inclusion in this review required that the studies investigated knowledge, attitudes, or educational needs regarding omics sciences among the general population. Results: We included 54 studies, published between 2006 and 2020. Most of the included studies (72%) investigated citizens' knowledge, half of them (56%) attitudes, and 20% educational needs in the field of omics sciences, while 52% investigated attitudes and perceptions about genetic and/or omics tests. Most studies (64%) reported a limited knowledge level among citizens, even though most (59%) reported participants understood the benefits of the use of omics sciences into medicine. As for omics tests, a controversial opinion toward their use into practice was reported among citizens. Most of the studies (82%) investigating citizens' educational needs highlighted a clear gap to be filled. Conclusions: Our SLR summarizes current knowledge on citizens' literacy, attitudes, and educational needs on omics science, underlining the need for strengthening public engagement on this topic. Further research is needed, however, to identify appropriate methods and models to achieve such an improvement

Mice, men, mustard and methylated xanthines: the potential role of caffeine and related drugs in the sensitization of human tumours to alkylating agents.

The relationships between DNA damage from UV radiation, alkylating drugs and the methylated xanthines (MX) have been studied in normal and malignant rodent and human cells. A comparison of the level of DNA excision repair (repair replication and unscheduled DNA synthesis) confirms that some forms of alkylating-agent damage (probably mono-filar DNA adducts) are less completely removed by both normal and malignant rodent cells than by their human counterparts, rendering rodent cells more susceptible to the toxic potential of unexcised lesions. The toxicity of alkylating agents can be increased by the presence of several MXs during the period of DNA replication which follows infliction of the damage. Human cells appear capable of excising more DNA damage, rendering them somewhat less susceptible to enhancement of cytotoxicity by MX. This resistance of human cells is only quantitative, however, since 2 human cancer cell lines (HeLa and HT-29) could be sensitized to a variety of alkylating agents by appropriate concentrations of MX. Trimethylxanthine (caffeine) and the 2 clinically useful dimethylxanthines (theophylline and theobromine) appeared equally effective in sensitizing cells. The sensitization was dependent upon a slightly cytotoxic concentration of the MX and a suitably prolonged period of post-damage MX exposure. Of these 3 classic MXs, only theobromine might be clinically useful. The levels required for alkylating-agent sensitization exceed the clinically tolerable level of theophylline, and probably approach the tolerance of man to caffeine. The most likely mechanism by which MX sensitization is achieved is reversal of the inhibition of DNA replicon initiation which follows the infliction of significant DNA damage. Through the selection of suitable clinically useful alkylating agents (those dependent on active cellular transport for cell penetration) and appropriate MX scheduling, an enhanced therapeutic ratio might be achieved, potentially increasing the clinical usefulness of these alkylating agents. MX would thus form a useful class of agents adjuvant to conventional anti-cancer drugs

A Web Screening on Educational Initiatives to Increase Citizens’ Literacy on Genomics and Genetics

Introduction: Population awareness and empowerment in omics sciences represent a fundamental driver to increase the adoption of evidence-based approaches in personalized medicine. In this context, a pivotal role is played by citizens’ literacy, and educational initiatives carried out in this context are key assets to drive future effective interventions. With the present study, we summarized the educational initiatives conducted worldwide aimed at increasing citizens’ literacy in omics sciences. Materials and Methods: We conducted a web search of the educational initiatives aimed at improving citizens’ literacy in omics sciences undertaken worldwide, by using three search engines (Google, Bing, and Yahoo Search), in English and in Italian languages. Results: We identified five initiatives in Europe, 22 in non-European countries, and 13 in Italy. Overall, the majority (69%) were web-based initiatives, while 31% required in-person attendance. The online initiatives included web pages for reading, online lessons/courses, web portals, videos/short movies, animations, and apps for mobile devices. The residential initiatives, on the other hand, included exhibitions, seminars, courses, symposia, information stands in public places, guided visits to research laboratories, and interactive laboratories. All the initiatives were highly heterogeneous in terms of methodologies and the topics addressed. Discussion and Conclusion: Overall, we identified a variety of initiatives aimed at improving citizens’ literacy in omics sciences, with the largest majority carried out in the United States and being web-based. Our results showed heterogeneity among the initiatives as to the dealt topics and the adopted methods. Further research is needed, however, to quantitatively assess the effectiveness of educational initiatives to improve citizens’ literacy in omics sciences

Precision medicine and machine learning towards the prediction of the outcome of potential celiac disease

Potential Celiac Patients (PCD) bear the Celiac Disease (CD) genetic predisposition, a significant production of antihuman transglutaminase antibodies, but no morphological changes in the small bowel mucosa. A minority of patients (17%) showed clinical symptoms and need a gluten free diet at time of diagnosis, while the majority progress over several years (up to a decade) without any clinical problem neither a progression of the small intestine mucosal damage even when they continued to assume gluten in their diet. Recently we developed a traditional multivariate approach to predict the natural history, on the base of the information at enrolment (time 0) by a discriminant analysis model. Still, the traditional multivariate model requires stringent assumptions that may not be answered in the clinical setting. Starting from a follow-up dataset available for PCD, we propose the application of Machine Learning (ML) methodologies to extend the analysis on available clinical data and to detect most influent features predicting the outcome. These features, collected at time of diagnosis, should be capable to classify patients who will develop duodenal atrophy from those who will remain potential. Four ML methods were adopted to select features predictive of the outcome; the feature selection procedure was indeed capable to reduce the number of overall features from 85 to 19. ML methodologies (Random Forests, Extremely Randomized Trees, and Boosted Trees, Logistic Regression) were adopted, obtaining high values of accuracy: all report an accuracy above 75%. The specificity score was always more than 75% also, with two of the considered methods over 98%, while the best performance of sensitivity was 60%. The best model, optimized Boosted Trees, was able to classify PCD starting from the selected 19 features with an accuracy of 0.80, sensitivity of 0.58 and specificity of 0.84. Finally, with this work, we are able to categorize PCD patients that can more likely develop overt CD using ML. ML techniques appear to be an innovative approach to predict the outcome of PCD, since they provide a step forward in the direction of precision medicine aimed to customize healthcare, medical therapies, decisions, and practices tailoring the clinical management of PCD children