Impact of individual molecular components in determining primary sensitization to latex.

Allergy to natural rubber latex emerged as one of the main allergies at the beginning among some professional groups and the general population. Sensitization and development of latex allergy have been attributed to exposure to products containing residual latex proteins. The prevailing cross-reactivity of latex proteins with other food allergens is of great concern. Numerous purified allergens are currently available, which greatly help in patient management, thus determining their specific profile. We conducted a multicenter study to investigate changes, from the ROC analysis, in the characteristics of patients with latex allergy by measuring its major protein components. Sensitization to latex proteins is crucial because it highlights the cross reactivity to inhalants (pollen) and food (fruit). It is very essential in an accurate and specific clinical setting.

Improving Keyword-Based Topic Classification in Cancer Patient Forums with Multilingual Transformers.

Online forums play an important role in connecting people who have crossed paths with cancer. These communities create networks of mutual support that cover different cancer-related topics, containing an extensive amount of heterogeneous information that can be mined to get useful insights. This work presents a case study where users' posts from an Italian cancer patient community have been classified combining both count-based and prediction-based representations to identify discussion topics, with the aim of improving message reviewing and filtering. We demonstrate that pairing simple bag-of-words representations based on keywords matching with pre-trained contextual embeddings significantly improves the overall quality of the predictions and allows the model to handle ambiguities and misspellings. By using non-English real-world data, we also investigated the reusability of pretrained multilingual models like BERT in lower data regimes like many local medical institutions.

Experimental analysis of the influence of cortical bone layers and bone quantity on implant primary stability.

The systematic analysis of parameters impacting implant primary stability is difficult to achieve with human cadavers or animal models, particularly for complex trans-sinus procedures to determine the effects of cortical layers and bone engagement on implant stability before and after a simulated load in vitro. Solid rigid polyurethane blocks, partially intersected by an 8-mm-thick space, were created to imitate tri-cortical situations, the presence of the sinus cavity, and the posterior maxilla with different degrees of bone atrophy. Implants were inserted through the cavity at an angle of 30˚ (scenarios 1 and 2) to imitate the clinical protocol. Controls simulating uni-cortical anchorage and no sinus cavity were also included (controls 1 and 2). Four parameters were measured: peak insertion torque, insertion work, resistance to lateral bending loads and extraction torque. Scenarios 1 and 2 displayed similar peak insertion torque to control 2, where all three groups anchored equal amounts of bone surrogate. The distribution of surrogate bone in contact with trans-cavity implants influenced both extraction torque and the degree of lateral bending. Sufficient peak insertion torque can be attained with a trans-sinus tricortical implant anchorage providing sufficient apical and coronal bone is engaged.

Management of the delicate phase of the temporary crown: an in vitro study.

The fundamental moment of prosthetic rehabilitation is the "temporary". Although the meaning of the term diminishes its importance, the provisional has fundamental biological, aesthetic and functional functions. The oral cavity must maintain an adequate level of oral hygiene to carry out this delicate phase in the best possible way; a result achieved only with the collaboration of the prosthetic dentist with the hygienist and the patient, as if they were a biological system in motion. The different methods of hygiene are effective in maintaining a good level of oral health; but they could, if too aggressive, affect the prosthetic restoration. Our objective in vitro is to understand, after applying a known bacterial load, which hygiene method is the most effective in removing bacterial biofilm but at the same time is less aggressive towards resinous material.

Immediate versus delayed loading of post-extraction implants in the aesthetic zone: a prospective longitudinal study with 4-year follow-up.

The aim of this randomized clinical trial was to compare the outcome of immediate versus delayedloading protocol using a new conical connection implant in post-extractive sockets with 4-year followup. Patients requiring single-tooth extraction for root fractures or periodontal disease in the maxillary or mandibular anterior or premolar areas were selected for the present study. After extraction, implants were placed immediately in fresh sockets. After randomization process, in group A immediate loading was performed while in group B a delayed loading protocol was followed. In both groups mean marginal bone loss was measured through intraoral digital radiographs at 3, 6, 12, 24, 36 and 48 months from loading. After a 48-month follow-up period, a success and survival rate of 96.55% was found in both groups. At 48-month follow-up, for group A a mean marginal bone loss of 0.14 ± 0.15mm was found, while for group B a value of 0.12 ± 0.12 mm was measured. No statistically significant differences between groups were found at each time point (P>0.05). When used in post-extractive immediate and delayed loading implant rehabilitations, the new conical connection implant showed a predictable outcome at 48-month follow-up. However, further clinical studies are needed to evaluate soft tissues adaptation, patient satisfaction, and long-term follow-up.

Ontology-Driven Real World Evidence Extraction from Clinical Narratives.

Unstructured clinical notes contain a huge amount of information. We investigated the possibility of harvesting such information through an NLP-based approach. A manually curated ontology is the only resource required to handle all the steps of the process leading from clinical narrative to a structured data warehouse (i2b2). We have tested our approach at the Papa Giovanni XXIII hospital in Bergamo (Italy) on pathology reports collected since 2008.

Patient similarity for precision medicine: A systematic review.

Evidence-based medicine is the most prevalent paradigm adopted by physicians. Clinical practice guidelines typically define a set of recommendations together with eligibility criteria that restrict their applicability to a specific group of patients. The ever-growing size and availability of health-related data is currently challenging the broad definitions of guideline-defined patient groups. Precision medicine leverages on genetic, phenotypic, or psychosocial characteristics to provide precise identification of patient subsets for treatment targeting. Defining a patient similarity measure is thus an essential step to allow stratification of patients into clinically-meaningful subgroups. The present review investigates the use of patient similarity as a tool to enable precision medicine. 279 articles were analyzed along four dimensions: data types considered, clinical domains of application, data analysis methods, and translational stage of findings. Cancer-related research employing molecular profiling and standard data analysis techniques such as clustering constitute the majority of the retrieved studies. Chronic and psychiatric diseases follow as the second most represented clinical domains. Interestingly, almost one quarter of the studies analyzed presented a novel methodology, with the most advanced employing data integration strategies and being portable to different clinical domains. Integration of such techniques into decision support systems constitutes and interesting trend for future research.

Secondary Use and Analysis of Big Data Collected for Patient Care.

Objectives: To identify common methodological challenges and review relevant initiatives related to the re-use of patient data collected in routine clinical care, as well as to analyze the economic benefits derived from the secondary use of this data. Through the use of several examples, this article aims to provide a glimpse into the different areas of application, namely clinical research, genomic research, study of environmental factors, and population and health services research. This paper describes some of the informatics methods and Big Data resources developed in this context, such as electronic phenotyping, clinical research networks, biorepositories, screening data banks, and wide association studies. Lastly, some of the potential limitations of these approaches are discussed, focusing on confounding factors and data quality. Methods: A series of literature searches in main bibliographic databases have been conducted in order to assess the extent to which existing patient data has been repurposed for research. This contribution from the IMIA working group on "Data mining and Big Data analytics" focuses on the literature published during the last two years, covering the timeframe since the working group's last survey. Results and Conclusions: Although most of the examples of secondary use of patient data lie in the arena of clinical and health services research, we have started to witness other important applications, particularly in the area of genomic research and the study of health effects of environmental factors. Further research is needed to characterize the economic impact of secondary use across the broad spectrum of translational research.

Temporal electronic phenotyping by mining careflows of breast cancer patients.

In this work we present a careflow mining approach designed to analyze heterogeneous longitudinal data and to identify phenotypes in a patient cohort. The main idea underlying our approach is to combine methods derived from sequential pattern mining and temporal data mining to derive frequent healthcare histories (careflows) in a population of patients. This approach was applied to an integrated data repository containing clinical and administrative data of more than 4000 breast cancer patients. We used the mined histories to identify sub-cohorts of patients grouped according to healthcare activities pathways, then we characterized these sub-cohorts with clinical data. In this way, we were able to perform temporal electronic phenotyping of electronic health records (EHR) data.

Progress in Biomedical Knowledge Discovery: A 25-year Retrospective.

OBJECTIVES: We sought to explore, via a systematic review of the literature, the state of the art of knowledge discovery in biomedical databases as it existed in 1992, and then now, 25 years later, mainly focused on supervised learning. METHODS: We performed a rigorous systematic search of PubMed and latent Dirichlet allocation to identify themes in the literature and trends in the science of knowledge discovery in and between time periods and compare these trends. We restricted the result set using a bracket of five years previous, such that the 1992 result set was restricted to articles published between 1987 and 1992, and the 2015 set between 2011 and 2015. This was to reflect the current literature available at the time to researchers and others at the target dates of 1992 and 2015. The search term was framed as: Knowledge Discovery OR Data Mining OR Pattern Discovery OR Pattern Recognition, Automated. RESULTS: A total 538 and 18,172 documents were retrieved for 1992 and 2015, respectively. The number and type of data sources increased dramatically over the observation period, primarily due to the advent of electronic clinical systems. The period 1992- 2015 saw the emergence of new areas of research in knowledge discovery, and the refinement and application of machine learning approaches that were nascent or unknown in 1992. CONCLUSIONS: Over the 25 years of the observation period, we identified numerous developments that impacted the science of knowledge discovery, including the availability of new forms of data, new machine learning algorithms, and new application domains. Through a bibliometric analysis we examine the striking changes in the availability of highly heterogeneous data resources, the evolution of new algorithmic approaches to knowledge discovery, and we consider from legal, social, and political perspectives possible explanations of the growth of the field. Finally, we reflect on the achievements of the past 25 years to consider what the next 25 years will bring with regard to the availability of even more complex data and to the methods that could be, and are being now developed for the discovery of new knowledge in biomedical data.

Personalization and Patient Involvement in Decision Support Systems: Current Trends.

OBJECTIVES: This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. METHODS: We considered papers published on scientific journals, by querying PubMed and Web of ScienceTM. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. RESULTS: We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. CONCLUSIONS: Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large.

UceWeb: a web-based collaborative tool for collecting and sharing quality of life data.

OBJECTIVES: This work aims at building a platform where quality-of-life data, namely utility coefficients, can be elicited not only for immediate use, but also systematically stored together with patient profiles to build a public repository to be further exploited in studies on specific target populations (e.g. cost/utility analyses). METHODS: We capitalized on utility theory and previous experience to define a set of desirable features such a tool should show to facilitate sound elicitation of quality of life. A set of visualization tools and algorithms has been developed to this purpose. To make it easily accessible for potential users, the software has been designed as a web application. A pilot validation study has been performed on 20 atrial fibrillation patients. RESULTS: A collaborative platform, UceWeb, has been developed and tested. It implements the standard gamble, time trade-off and rating-scale utility elicitation methods. It allows doctors and patients to choose the mode of interaction to maximize patients' comfort in answering difficult questions. Every utility elicitation may contribute to the growth of the repository. CONCLUSION: UceWeb can become a unique source of data allowing researchers both to perform more reliable comparisons among healthcare interventions and build statistical models to gain deeper insight into quality of life data.

From data to the decision: A software architecture to integrate predictive modelling in clinical settings.

The application of statistics and mathematics over large amounts of data is providing healthcare systems with new tools for screening and managing multiple diseases. Nonetheless, these tools have many technical and clinical limitations as they are based on datasets with concrete characteristics. This proposition paper describes a novel architecture focused on providing a validation framework for discrimination and prediction models in the screening of Type 2 diabetes. For that, the architecture has been designed to gather different data sources under a common data structure and, furthermore, to be controlled by a centralized component (Orchestrator) in charge of directing the interaction flows among data sources, models and graphical user interfaces. This innovative approach aims to overcome the data-dependency of the models by providing a validation framework for the models as they are used within clinical settings.

Template for preparation of papers for IEEE sponsored conferences & symposia.

To improve the access to medical information is necessary to design and implement integrated informatics techniques aimed to gather data from different and heterogeneous sources. This paper describes the technologies used to integrate data coming from the electronic medical record of the IRCCS Fondazione Maugeri (FSM) hospital of Pavia, Italy, and combines them with administrative, pharmacy drugs purchase coming from the local healthcare agency (ASL) of the Pavia area and environmental open data of the same region. The integration process is focused on data coming from a cohort of one thousand patients diagnosed with Type 2 Diabetes Mellitus (T2DM). Data analysis and temporal data mining techniques have been integrated to enhance the initial dataset allowing the possibility to stratify patients using further information coming from the mined data like behavioral patterns of prescription-related drug purchases and other frequent clinical temporal patterns, through the use of an intuitive dashboard controlled system.

Workers of the printing industry and hepatic damage.

BACKGROUND: Typesetting industry is still the primary instrument of communication, despite the development of new technological systems. This study focuses on the analysis of the hepatic effects induced by the use of some organic solvents employed in the printing industry. METHODS: We studied a group of 194 workers: 93 exposed and 101 not exposed. The level of the exposure to chemical pollutants were assessed through the environmental monitoring of blood concentrations and the analysis of airborne substances. The health survey was performed through the collection of the medical history and the use of hepatic tests, which were evaluated by calculating Mean, Standard Deviation, Student's t-test and X² test with Yates Correction, to investigate statistically significant differences in some hepatic parameters: AST, ALT, ALP, GGT, fractional and total bilirubin. The environmental data sometimes exceeded the TLV-TWA. RESULTS: The clinical evaluation of the hepatic parameters showed statistically significant differences as to the hematic concentrations of AST, ALT, GGT. CONCLUSIONS: The results we obtained support the hypothesis of a risk among the printing industrial workers attributable to the hepatotoxic solvents. This risk seems to be related to the use of a mixture of solvents, although at low doses, and the analysis of the results obtained confirms the validity of the investigation for the health screening protocol adopted in order to identify subjects and/or population at risk of hepatotoxicity.

The genomic and proteomic blueprint of mouse megakaryocytes derived from embryonic stem cells.

BACKGROUND: Platelets are specialized cells, produced by megakaryocytes (MKs) in the bone marrow, which represent the first defense against hemorrhage. There are many diseases where platelet production or function is impaired, with severe consequences for patients. Therefore, new insights into the process of MK differentiation and platelet formation would have a major impact on both basic and clinical research. OBJECTIVES: Embryonic stem (ES) cells represent a good in vitro model to study the differentiation of MKs, with the possibility of being genetically engineered and constituting an unlimited source of MKs. However, lack of knowledge about the molecular identity of ES-derived MKs (ES-MKs) may prevent any further development and application of this model. METHODS: This paper presents the first comprehensive transcriptional and proteome profile analyses of mouse ES-MKs in comparison with MKs derived from mouse fetal liver progenitors (FL-MKs). RESULTS: In ES-MKs we found a down-regulation of cytoskeleton proteins, specific transcription factors and membrane receptors at both transcriptional and protein levels. At the phenotypic level, this molecular blueprint was displayed by ES-MKs' lower polyploidy, lower nuclear/cytoplasm ratio and reduced capacity to form proplatelets and releasing platelets. CONCLUSIONS: Overall our data demonstrate that ES-MKs represent a useful model to clarify many aspects of both MK physiology and pathological conditions where impaired MK functions are related to defective MK development, as in inherited thrombocytopenias and primary myelofibrosis.

Mining health care administrative data with temporal association rules on hybrid events.

OBJECTIVE: The analysis of administrative health care data can be helpful to conveniently assess health care activities. In this context temporal data mining techniques can be suitably exploited to get a deeper insight into the processes underlying health care delivery. In this paper we present an algorithm for the extraction of temporal association rules (TARs) on sequences of hybrid events and its application on health care administrative databases. METHODS: We propose a method that extends TAR mining by managing hybrid events, namely events characterized by a heterogeneous temporal nature. Hybrid events include both point-like events (e.g. ambulatory visits) and interval-like events (e.g. drug consumption). The definition of user-defined rule templates can be optionally used to constrain the search only to the extraction of a subset of interesting rules. A TAR post-pruning strategy, based on a case-control approach, is also presented. RESULTS: We analyzed the administrative database of diabetic patients in charge to the regional health care agency (ASL) of Pavia. TAR mining allowed to find patterns specifically related to the diabetic population in comparison with a control group, as well as to check the compliance of the actual clinical careflow with the ASL recommendations. CONCLUSION: The experimental results highlighted the main potentials of the algorithm, such as the opportunity to detect interesting temporal relationships between diagnostic or therapeutic patterns, or to check the adherence of past temporal behaviors to specific expected paths (e.g. guidelines) or to discover new knowledge that could be implicitly hidden in the data.

Experimental infections of baboons (Papio spp.) and vervet monkeys (Cercopithecus aethiops) with Trichinella zimbabwensis and successful treatment with ivermectin.

Experimental Trichinella zimbabwensis infections were established in three baboons (Papio sp.) and four vervet monkeys (Cercopithecus aethiops) and the clinical-pathological manifestations assessed. The infected animals showed clinical signs ranging from fever, diarrhoea, periorbital oedema and muscular pain in varying degrees. One baboon became blind due to the infection. Levels of creatinine phosphokinase and lactate dehydrogenase increased to reach a peak on Day 42 post-infection (pi) for both baboons and monkeys. Blood parameters such as packed cell volume, levels of red blood cells and white blood cells did not change significantly from the normal ranges except for the levels of eosinophils which peaked above the normal ranges at Day 28 and 56 pi in baboons and at Day 56 pi in monkeys. Two baboons and two monkeys died during the course of the experiment. They were emaciated and showed lesions such as ascites, hydropericardium, congested liver and enlarged gall bladder. Histopathological findings of various muscles included a basophilic transformation of muscle cells, the disappearance of sarcomere myofibrils and basophilic sarcoplasm with the presence of Trichinella larvae in the sarcoplasm. These changes were mainly in the massetter and were of various intensities in the tail, gastrocnemius and biceps muscles. Five consecutive treatments with an oxfendazole-levamisole combination on surviving animals failed to clear the infection whereas ivermectin cleared the infection after one treatment in two monkeys and after two treatments in a baboon.