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Online users often search public health websites to examine health-related issues, including diagnosis and symptomatic behaviours; however, the quality and reliability of health websites still pose significant challenges for medical societies. Thus, we conducted a quality check of international aesthetic medicine society (UIME) websites. All websites reporting health-related information should identify a specific organisation as the reporting authority, and the accuracy of their content must be verified. The analysis was conducted by considering 31 national societies, and a quality assessment was performed using a tailor-made questionnaire with three criteria: design (70 points), reliability (85 points) and privacy (15 points). According to the results, only two of the websites fulfil the threshold score of 130/170 (76.4%). Seven societies do not have responsive websites, and only five sites achieved ≥50 points for the design criterion. The American society websites met the reliability parameter and achieved ≥70 points, and 11 sites achieved a minimum score of 10 points for privacy. This study reveals that major health societies in public healthcare must be improved to meet user needs and catalyse positive change in the distribution of health information.

Aims and Objectives. This study aims to assess the knowledge, attitude, and perceptions of dental asepsis and sterilization among dental assistants in Pakistan. Materials and Methods. A cross-sectional study was carried out. A 27-item prepilot tested close-ended questionnaire was designed and administered online to collect data on knowledge of asepsis, sterilization, instrument handling, disinfection, hand-hygiene practices, dental practice, age, education, and experience level from March 2020 to June 2020. Results. Out of 70 dental assistants, the majority were aged between 21 and 29 years (44.30%), more than two-thirds (85.41%) of the dental assistants were working in a hospital, while 14.29% were working in private clinics, only 7.1% had a diploma in the dental assistant program, and 74% had more than 2 years of experience in practice. Dental assistants working in private practice (76.30) had a higher mean knowledge scores compared to those working in hospital (74.25), while those with less than 2 years of experience (75.61) had a higher scores compared to those with 2–5 years of experience (73.96). Conclusion. Better compliance with recommended infection control and waste management practices is needed for all dental assistants. Continuing education programs targeting such awareness are vital to improve the management of hazardous waste practices among dental assistants.

Training and coaching are cited frequently to achieve different goals, by different people, across different fields. "Who" provides training and coaching and "where" and "how" they are provided may influence the effectiveness of the training and coaching efforts, making the clear identification of these contextual features of paramount importance to successful implementation and dissemination of training and coaching programs. First, we propose a framework for elucidating these contextual features, and then we apply this framework to a circumscribed review of the literature on parent training and coaching in early intervention services to assess its utility. We discuss the extent to which contextual features have been described in this body of research, offer additional considerations for applying the framework based on this review, and propose possible implications of our findings for implementation, dissemination, and future research efforts.

The COVID-19 pandemic has shocked the world causing more victims than the latest global epidemics such as Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) in 2003, and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2012. Italy has been one of the most affected countries, and it had to deal with an already weak economic condition and cuts to public health services due to budgetary requirements from the last decade—something that made the situation even more dramatic. Deaths have exceeded 600.000 worldwide. During the emergency, regulatory measures were taken to counter the situation. This study highlights the main anti-COVID-19 government measures to support doctors and healthcare professionals, and it analyzes how to respond to the many requests complaining about neglectful healthcare professionals during the spread of the infection. For all those healthcare workers who died on duty, a compensation plan is assumed through a solidarity fund. The same solution cannot be granted to all patients, given the difficulty in assessing the responsibility of the doctor not only during an emergency but with insufficient instruments to cope with it as well.

In general merchant ships do not have medical facilities on board. When seafarer got sickness or accident, either ship captain or officers who are in charge will assist them, but these people do not have enough medical knowledge. To overcome this, we developed a Seafarer Health Expert System (SHES) that can facilitate telemedical services in an emergency. A comprehensive analysis of seafarers’ medical issues that were conducted from medical records of patients assisted on board ships by the International Radio Medical Center (C.I.R.M.), Italy. Data mining techniques are involved to manage epidemiological data analysis in a two-phase setup. In the first phase, the common pathologies that occurred onboard were analyzed, later a detailed questionnaire for each medical problem was developed to provide precise symptomatic information to the onshore doctor. In this paper, we mainly highlighted the SHES framework, design flow, and functionality. Besides, nine designing policies and three actors with separate working panels were clearly described. The proposed system is easy and simple to operate for anyone of no computer experience and create medical requests for the fast delivery of symptomatic information to an onshore doctor.

Introduction: In biobanks, participants’ biological samples are stored for future research. The application of artificial intelligence (AI) involves the analysis of data and the prediction of any pathological outcomes. In AI, models are used to diagnose diseases as well as classify and predict disease risks. Our research analyzed AI’s role in the development of biobanks in the healthcare industry, systematically. Methods: The literature search was conducted using three digital reference databases, namely PubMed, CINAHL, and WoS. Guidelines for preferred reporting elements for systematic reviews and meta-analyses (PRISMA)-2020 in conducting the systematic review were followed. The search terms included “biobanks”, “AI”, “machine learning”, and “deep learning”, as well as combinations such as “biobanks with AI”, “deep learning in the biobanking field”, and “recent advances in biobanking”. Only English-language papers were included in the study, and to assess the quality of selected works, the Newcastle–Ottawa scale (NOS) was used. The good quality range (NOS ≥ 7) is only considered for further review. Results: A literature analysis of the above entries resulted in 239 studies. Based on their relevance to the study’s goal, research characteristics, and NOS criteria, we included 18 articles for reviewing. In the last decade, biobanks and artificial intelligence have had a relatively large impact on the medical system. Interestingly, UK biobanks account for the highest percentage of high-quality works, followed by Qatar, South Korea, Singapore, Japan, and Denmark. Conclusions: Translational bioinformatics probably represent a future leader in precision medicine. AI and machine learning applications to biobanking research may contribute to the development of biobanks for the utility of health services and citizens.

Obesity is a risk factor for cardiovascular diseases, frequently related to oxidative stress and inflammation. Dietary antioxidant compounds improve heart health. Here, we estimate the oxidative grade and inflammation in the heart of dietary-induced obese (DIO) rats after exposure to a high-fat diet compared to a standard diet. The effects of tart cherry seed powder and seed powder plus tart cherries juice were explored. Morphological analysis and protein expressions were performed in the heart. The oxidative status was assessed by the measurement of protein oxidation and 4-hydroxynonenal in samples. Immunochemical and Western blot assays were performed to elucidate the involved inflammatory markers as proinflammatory cytokines and cellular adhesion molecules. In the obese rats, cardiomyocyte hypertrophy was accompanied by an increase in oxidative state proteins and lipid peroxidation. However, the intake of tart cherries significantly changed these parameters. An anti-inflammatory effect was raised from tart cherry consumption, as shown by the downregulation of analyzed endothelial cell adhesion molecules and cytokines compared to controls. Tart cherry intake should be recommended as a dietary supplement to prevent or counteract heart injury in obese conditions.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor impairment, as well as tremors, stiffness, and rigidity. Besides the typical motor symptomatology, some Parkinsonians experience non-motor symptoms such as hyposmia, constipation, urinary dysfunction, orthostatic hypotension, memory loss, depression, pain, and sleep disturbances. The correct diagnosis of PD cannot be easy since there is no standard objective approach to it. After the incorporation of machine learning (ML) algorithms in medical diagnoses, the accuracy of disease predictions has improved. In this work, we have used three deep-learning-type cascaded neural network models based on the audial voice features of PD patients, called Recurrent Neural Networks (RNN), Multilayer Perception (MLP), and Long Short-Term Memory (LSTM), to estimate the accuracy of PD diagnosis. A performance comparison between the three models was performed on a sample of the subjects’ voice biomarkers. Experimental outcomes suggested that the LSTM model outperforms others with 99% accuracy. This study has also presented loss function curves on the relevance of good-fitting models to the detection of neurodegenerative diseases such as PD.

Generally, seafarers face a higher risk of illnesses and accidents than land workers. In most cases, there are no medical professionals on board seagoing vessels, which makes disease diagnosis even more difficult. When this occurs, onshore doctors may be able to provide medical advice through telemedicine by receiving better symptomatic and clinical details in the health abstracts of seafarers. The adoption of text mining techniques can assist in extracting diagnostic information from clinical texts. We applied lexicon sentimental analysis to explore the automatic labeling of positive and negative healthcare terms to seafarers’ text healthcare documents. This was due to the lack of experimental evaluations using computational techniques. In order to classify diseases and their associated symptoms, the LASSO regression algorithm is applied to analyze these text documents. A visualization of symptomatic data frequency for each disease can be achieved by analyzing TF-IDF values. The proposed approach allows for the classification of text documents with 93.8% accuracy by using a machine learning model called LASSO regression. It is possible to classify text documents effectively with tidy text mining libraries. In addition to delivering health assistance, this method can be used to classify diseases and establish health observatories. Knowledge developed in the present work will be applied to establish an Epidemiological Observatory of Seafarers’ Pathologies and Injuries. This Observatory will be a collaborative initiative of the Italian Ministry of Health, University of Camerino, and International Radio Medical Centre (C.I.R.M.), the Italian TMAS.

Multi-wall carbon nanotubes (MWCNTs) exhibit exceptional mechanical and electrical properties and can be used to improve the mechanical and piezoelectric properties of cement-based materials. In the present study, the effect of different MWCNT concentrations as well as different types of surfactants and a superplasticizer were examined to reinforce, at the nanoscale, a white cement mortar typically used for the restoration of monuments of cultural heritage. It was shown that sodium dodecylbenzenesulfonate (SDBS) and Triton X-100 surfactants slightly decreased the white cement mortars’ electrical resistivity (by an average of 10%), however, the mechanical properties were essentially decreased by an average of 60%. The most suitable dispersion agent for the MWCNTs proved to be the superplasticizer Ceresit CC198, and its optimal concentration was investigated for different MWCNT concentrations. Carboxylation of the MWCNT surface with nitric acid did not improve the mechanical performance of the white cement nanocomposites. The parametric experimental study showed that the optimum combination of 0.8 wt% of cement superplasticizer and 0.2 wt% of cement MWCNTs resulted in a 60% decrease in the electrical resistivity; additionally, the flexural and compressive strengths were both increased by approximately 25% and 10%, respectively.

A link between obesity and cerebral health is receiving growing recognition. Here, we investigate in the frontal cortex and hippocampus the potential involvement of cholinergic markers in brain alterations previously reported in rats with obesity induced by diet (DIO) after long-term exposure (17 weeks) to a high-fat diet (HFD) in comparison with animals fed with a standard diet (CHOW). The obesity developed after 5 weeks of HFD. Bodyweight, systolic blood pressure, glycemia, and insulin levels were increased in DIO rats compared to the CHOW group. Measurements of malondialdehyde (MDA) provided lipid peroxidation in HFD-fed rats. Western blot and immunohistochemical techniques were performed. Our results showed a higher expression of choline acetyltransferase (ChAT) and vesicular acetylcholine transporter (VAChT) in obese rats but not the VAChT expression in the frontal cortex after 17 weeks of HFD. Furthermore, the acetylcholinesterase (AChE) enzyme was downregulated in HFD both in the frontal cortex and hippocampus. In the brain regions analyzed, it was reported a modulation of certain cholinergic receptors expressed pre- and post-synaptically (alpha7 nicotinic receptor and muscarinic receptor subtype 1). Collectively, these findings point out precise changes of cholinergic markers that can be targeted to prevent cerebral injuries related to obesity.

Brain and retinal organoids are functional and dynamic in vitro three-dimensional (3D) structures derived from pluripotent stem cells that spontaneously organize themselves to their in vivo counterparts. Here, we review the main literature data of how these organoids have been developed through different protocols and how they have been technically analyzed. Moreover, this paper reviews recent advances in using organoids to model neurological and retinal diseases, considering their potential for translational applications but also pointing out their limitations. Since the blood–brain barrier (BBB) and blood–retinal barrier (BRB) are understood to play a fundamental role respectively in brain and eye functions, both in health and in disease, we provide an overview of the progress in the development techniques of in vitro models as reliable and predictive screening tools for BBB and BRB-penetrating compounds. Furthermore, we propose potential future directions for brain and retinal organoids, in which dedicated biobanks will represent a novel tool for neuroscience and ophthalmology research.

We describe the implementation of a simple method for finding k approximate nearest neighbors (ANNs) on the GPU. While the performance of most ANN algorithms depends heavily on the distributions of the data and query points, our approach has a very regular data access pattern. It performs as well as state of the art methods on easy distributions with small values of k, and much more quickly on more difficult problem instances. Irrespective of the distribution and also roughly of the size of the set of input data points, we can find 50 ANNs for 1M queries at a rate of about 1200 queries/ms.

INTRODUCTION: There is a great percentage of failures in clinical trials of early detection of breast cancer. To do this, machine learning (ML) algorithms are useful to do diagnosis and prediction of cancer tumors with better accuracy. OBJECTIVE: In this study, we develop an ML model coupled with limited features to produce high classification accuracy in tumor classification. METHODS: We considered a dataset of 569 females diagnosed as 212 malignant and 357 benign types. For model development, three supervised ML algorithms namely support vector machines (SVM), logistic regression (LR), and K-nearest neighbors (KNN) were employed. Each model was further validated by 10-fold cross-validation and performance measures were defined to evaluate the model outcomes. RESULTS: Both SVM and LR models generated 97.66% accuracy with total feature evaluation. With selective features,the SVM accuracy was improved by 98.25%. Whereas the LR model including limited features produced 100% of true positive predictions. CONCLUSION: The proposed models involved by selective features could improve the prediction accuracy of a breast cancer diagnosis.

INTRODUCTION: Having justice for easy access to health services may probably be a standard feature and indisputable right of all health policies. The health policy of Iran enunciates this right. Unfortunately, as may happen in many countries, the execution of this policy depends on different factors. Among these parameters should be quoted as the suitable distribution of professionals, hospitals, and medical facilities. On the other hand, in Iran, there are many other problems linked to accessing areas with natural hindrances. OBJECTIVE: In this study, we analyzed the primary studies that report specialty and subspecialty challenges that had been faced by Iran to improve pediatric assistance. METHODS: Conduction of literature search in PubMed and CINAHL libraries was done, especially studies from 2010 to 2019. A Boolean operated ‘MeSH’ term was used for search. Newcastle–Ottawa Scale (NOS) scoring was adopted to assess the quality of each study. RESULTS: A total of 118 studies were displayed, and among them, 102 were excluded due to duplication and study relevance. Study selection was madebased on its content were classified into two groups (1) shortage and unsuitable distribution of specialist and sub-specialist physicians in Iran, and (2) studies that explain the status of degradation in different areas of Iran. Outcomes demonstrated that Iran is generally suffering the shortage and unsuitable distribution of specialists and sub-specialists. This lack is particularly crucial in deprived and far-away areas from the cities. CONCLUSION: The present study analyzed in detail the current data regarding pediatric health services (specialist and subspecialty) and health-specific facilities distribution in the country.

Background Internet represents a relevant source of information, but reliability of data that can be obtained by the web is still an unsolved issue. Non-reliable online information may have a relevance, especially in taking decisions related to health problems. Uncertainties on the quality of online health data may have a negative impact on health-related choices of citizens. Objective This work consisted in a cross-sectional literature review of published papers on online health information. The two main research objectives consisted in the analysis of trends in the use of health web sites and in the quality assessment and reliability levels of web medical sites. Methods Literature research was made using four digital reference databases, namely PubMed, British Medical Journal, Biomed, and CINAHL. Entries used were “trustworthy of medical information online,” “survey to evaluate medical information online,” “medical information online,” and “habits of web-based health information users”. Analysis included only papers published in English. The Newcastle Ottawa Scale was used to conduct quality checks of selected works. Results Literature analysis using the above entries resulted in 212 studies. Twenty-four articles in line with study objectives, and user characteristics were selected. People more prone to use the internet for obtaining health information were females, younger people, scholars, and employees. Reliability of different online health sites is an issue taken into account by the majority of people using the internet for obtaining health information and physician assistance could help people to surf more safe health web sites. Conclusions Limited health information and/or web literacy can cause misunderstandings in evaluating medical data found in the web. An appropriate education plan and evaluation tools could enhance user skills and bring to a more cautious analysis of health information found in the web.

The article aims at investigating the gynocentric reinvention of Slavic paganism in Polish fantasy fiction by women authors. Such a phenomenon derives from the intersection of two trends that have taken place in Poland during the last decades: the femininization of fantasy fiction and the revival of Slavic myths as a source of literary inspiration. The historical fantasy subgenre, in which fictitious versions of the Middle Ages are combined with folkloric elements, is particularly productive. Writers such as Małgorzata Saramonowicz, Joanna Żamejć and Elżbieta Cherezińska describe the clash between the advent of Christianity and an imagined Slavic paganism, in which women are able to control nature and magic. The analysis of their works shows how women authors rewrite national history to incorporate new visions of femininity into commercial and genre fiction.

Background. Health observatory (HO) models are helpful in gathering, analyzing, interpreting, and circulating reliable and quality information on population health and health service delivery. In this study, we proposed an HO conceptual model to enhance seafarer’s health, which subjects to disease trends. Methods. Three methods were followed during the study: a systematic collection of seafarer’s health data from the Centro Internazionale Radio Medico (C.I.R.M.) repository, an integrative review of existing seafarer’s policy, and both open and closed questionnaires were distributed to stakeholders to develop clinical knowledge. C.I.R.M. is the Italian Telemedical Maritime Assistance Service (TMAS). Results and Discussion. A three-layer HO framework was developed, and each layer had its components and functionalities. The proposed HO model integrated with the outcomes of the mentioned methods was working as the origin of the framework. In this way, we can design a standard infrastructure in ships and risk assessment conduction.

ITALIANO OLTRE I CONFINI: UNO SGUARDO SULLE VARIETÀ DEL REPERTORIO DEGLI EMIGRATI DI OGGI A cura di Luisa Amenta e Roberta Ferroni. Contributi di Luisa Amenta e Roberta Ferroni, Mariagrazia Palumbo, Barbara Bertoni, Elena Ballarin e Paolo Nitti, Luisa Revelli, Linda Badan e Emilie Lamote.

L’obiettivo di questa indagine è di documentare le varietà linguistiche in uso in un contesto intrafamiliare di tipo informale. Lo studio di caso che presentiamo ha come protagonisti i membri di una famiglia veneta con un livello di qualificazione medio-alta che in seguito all’ultima grande crisi economica mondiale del 2008 si sono trasferiti in Brasile. Questa indagine si inserisce all’interno degli studi sull’ecologia linguistica in contesti familiari e si è basata sull’analisi di una videoregistrazione avvenuta nel corso della consumazione del pranzo e di un questionario. L’analisi mostra che anche se l’italiano rimane il codice prevalente per tutti i membri della famiglia si nota una disinvoltura da un codice ad un altro (italiano, veneto e portoghese) che apre spazi a riflessioni metalinguistiche a livello lessicale. I codici del repertorio acquistano uno spazio di sovrapposizione ma al tempo stesso di demarcazione dei confini identitari laddove si voglia sottolineare la propria distanza dalla cultura ospite, ma anche in questo caso la commutazione avviene a seguito di una precisa volontà comunicativa. Il caso studio osservato permette di far emergere come nel caso di un plurilinguismo vissuto in termini di arricchimento tra le varietà del repertorio italiano/dialetto di cui dispongono i parlanti, l’inserimento della lingua del paese ospite si inserisce come ulteriore elemento di ricchezza accanto alla lingua di origine. Language varieties in an informal context: a case study of an italian family in Brazil The aim of this survey is to document the language varieties used in an informal intra-family context. The case study focuses on a family with a medium-high level of education from the Veneto Region who, following the last major world economic crisis of 2008, moved to Brazil. This survey falls within studies on linguistic ecology in family contexts and is based on the analysis of a video recording made during a lunch and a questionnaire. The analysis shows that even if Italian remains the prevailing code for all family members, there is a casualness from one code to another (Italian, Venetian dialect and Portuguese) that creates space for metalinguistic reflections at the lexical level. The codes of the repertory overlap but at the same time there are clear boundaries that emphasize the distance from the host culture, although the switching takes place following a precise communicative will. The case study observed highlights how in the case of multilingualism experienced in terms of enrichment among the varieties of the Italian repertoire / dialect available to the speakers, the inclusion of the language of the host country becomes a further element of wealth in addition to the language of origin.

Abstract Background The problem of determining the physical conformation of a protein dimer, given the structures of the two interacting proteins in their unbound state, is a difficult one. The location of the docking interface is determined largely by geometric complementarity, but finding complementary geometry is complicated by the flexibility of the backbone and side-chains of both proteins. We seek to generate candidates for docking that approximate the bound state well, even in cases where there is backbone and/or side-chain difference from unbound to bound states. Results We divide the surfaces of each protein into local patches and describe the effect of side-chain flexibility on each patch by sampling the space of conformations of its side-chains. Likely positions of individual side-chains are given by a rotamer library; this library is used to derive a sample of possible mutual conformations within the patch. We enforce broad coverage of torsion space. We control the size of the sample by using energy criteria to eliminate unlikely configurations, and by clustering similar configurations, resulting in 50 candidates for a patch, a manageable number for docking. Conclusions Using a database of protein dimers for which the bound and unbound structures of the monomers are known, we show that from the unbound patch we are able to generate candidates for docking that approximate the bound structure. In patches where backbone change is small (within 1 Å RMSD of bound), we are able to account for flexibility and generate candidates that are good approximations of the bound state (82% are within 1 Å and 98% are within 1.4 Å RMSD of the bound conformation). We also find that even in cases of moderate backbone flexibility our candidates are able to capture some of the overall shape change. Overall, in 650 of 700 test patches we produce a candidate that is either within 1 Å RMSD of the bound conformation or is closer to the bound state than the unbound is.

Peripheral neuropathies are chronic painful syndromes characterized by allodynia, hyperalgesia and altered nerve functionality. Nerve tissue degeneration represents the microanatomical correlate of peripheral neuropathies. Aimed to improve the therapeutic possibilities, this study investigated the hypersensitivity and the neuromorphological alterations related to the loose ligation of the sciatic nerve in rats. Effects elicited by treatment with acetyl-L-carnitine (ALCAR) in comparison to gabapentin were assessed. Axonal injury, reduction of myelin deposition and accumulation of inflammatory cells were detected in damaged nerve. A decrease of phosphorylated 200-kDa neurofilament (NFP) immunoreactivity and a redistribution in small clusters of myelin basic like-protein (MBP) were observed in ipsilateral nerves. Treatment with ALCAR (100 mg/kg intraperitoneally - i.p.) and gabapentin (70 mg/kg i.p.) administered bis in die for 14 days induced a significant pain relieving effect. ALCAR, but not gabapentin, significantly countered neuromorphological changes and increased axonal NFP immunoreactivity. These findings indicate that both ALCAR and gabapentin significantly decreased the hypersensitivity related to neuropathic lesions. The observation of the positive ALCAR effect on axonal and myelin sheath alterations in damaged nerve supports its use as neurorestorative agent against neuropathies through mechanism(s) consistent to those focused in this study.

In this study, two polymeric materials were tested in a dry rotating “pin-on-disc” configuration against differently coated surfaces, to evaluate their tribological response under conditions, such as those of rotary lip seals, and to identify the wear mechanism of each coupling. A PTFE based material, reinforced with glass fibers and a solid lubricant, and unreinforced polyketone were tested against a chromium oxide coating deposited by plasma thermal spraying, a CrN/NbN superlattice coating deposited by Physical Vapor Deposition (PVD), and a Diamond-Like Carbon (DLC) coating obtained through a hybrid PVD/PECVD (Plasma-Enhanced Chemical Vapor Deposition) process. The PTFE matrix composite offers better overall performance, in terms of specific wear rates and friction coefficients than polyketone. Although the tribological behavior of this material is generally worse than that of the PTFE matrix composite, it can be used without reinforcing fillers. Our analysis demonstrates the importance of transfer-film formation on the counter-surfaces, which can prevent further wear of the polymer if it adheres well to the counterpart. However, the tribofilm has opposing effects on the friction coefficient for the two materials: its formation leads to lower friction for PTFE and higher friction for polyketone.

Localized Components Analysis (LoCA) is a new method for describing surface shape variation in an ensemble of objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for localized components and allows a flexible trade-off between localized and concise representations, and the formulation of locality is flexible enough to incorporate properties such as symmetry. This paper demonstrates that LoCA can provide intuitive presentations of shape differences associated with sex, disease state, and species in a broad range of biomedical specimens, including human brain regions and monkey crania.

Establishing reliable correspondences between object surfaces is a fundamental operation, required in many contexts such as cleaning up and completing imperfect captured data, texture and deformation transfer, shapespace analysis and exploration, and the automatic generation of realistic distributions of objects. We present a method for matching a template to a collection of possibly target meshes. Our method uses a very small number of user-placed landmarks, which we augment with automatically detected feature correspondences, found using spin images. We deform the template onto the data using an ICP-like framework, smoothing the noisy correspondences at each step so as to produce an averaged motion. The deformation uses a differential representation of the mesh, with which the deformation can be computed at each iteration by solving a sparse linear system. We have applied our algorithm to a variety of data sets. Using only 11 landmarks between a template and one of the scans from the CEASAR data set, we are able to deform the template, and correctly identify and transfer distinctive features, which are not identified by user-supplied landmarks. We have also successfully established correspondences between several scans of monkey skulls, which have dangling triangles, non- manifold vertices, and self intersections. Our algorithm does not require a clean target mesh, and can even generate correspondence without trimming our extraneous pieces from the target mesh, such as scans of teeth.

Optical triangulation laser scanners produce errors at surface discontinuities and sharp features. These systematic errors are anisotropic. We examine the causes of these errors theoretically, and we study the correlation of systematic error with edge size and orientation experimentally. We then present a novel processing method for removing systematic errors, by combining scans taken at several different orientations. We apply an anisotropic filter to the separate scans, and use it to weight the data in a final combination step. Unlike previous approaches, our method does not require access to the scanner's internal data or firmware. We demonstrate the technique on data from laser range scanners by two different manufacturers.

We demonstrate an efficient data-parallel algorithm for building large hash tables of millions of elements in real-time. We consider two parallel algorithms for the construction: a classical sparse perfect hashing approach, and cuckoo hashing, which packs elements densely by allowing an element to be stored in one of multiple possible locations. Our construction is a hybrid approach that uses both algorithms. We measure the construction time, access time, and memory usage of our implementations and demonstrate real-time performance on large datasets: for 5 million key-value pairs, we construct a hash table in 35.7 ms using 1.42 times as much memory as the input data itself, and we can access all the elements in that hash table in 15.3 ms. For comparison, sorting the same data requires 36.6 ms, but accessing all the elements via binary search requires 79.5 ms. Furthermore, we show how our hashing methods can be applied to two graphics applications: 3D surface intersection for moving data and geometric hashing for image matching.

Hypertension is highly prevalent in elderly individuals and may be associated with cognitive decline, but the mechanisms by which hypertension may impact brain structure, and thereby modulate the time course of late-life cognitive performance, are not well understood. Therefore we used Localized Components Analysis, a novel computational method, to measure spatially-localized patterns of corpus callosum (CC) atrophy in 28 right-handed female subjects aged 75-79 years in the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik), a large-scale epidemiological study of aging. Localized callosal atrophy in the posterior midbody and splenium was significantly associated with systolic blood pressure in linear statistical models that controlled for age, while associations between blood pressure and anterior CC atrophy measures were not statistically significant. Additionally, overall measures of global CC atrophy were not significantly associated with blood pressure. The posterior CC may be differentially vulnerable to hypertension-associated atrophy, possibly due to its relatively tenuous vascularization.

Summary: We describe a general multiplatform exploratory tool called TreeQ-Vista, designed for presenting functional annotations in a phylogenetic context. Traits, such as phenotypic and genomic properties, are interactively queried from a relational database with a user-friendly interface which provides a set of tools for users with or without SQL knowledge. The query results are projected onto a phylogenetic tree and can be displayed in multiple color groups. A rich set of browsing, grouping and query tools are provided to facilitate trait exploration, comparison and analysis.Availability: The program, detailed tutorial and examples are available online at http://genome-test.lbl.gov/vista/TreeQVista.

Adult-onset dementia disorders represent a challenge for modern medicine. Alzheimer’s disease (AD) represents the most diffused form of adult-onset dementias. For half a century, the diagnosis of AD was based on clinical and exclusion criteria, with an accuracy of 85%, which did not allow for a definitive diagnosis, which could only be confirmed by post-mortem evaluation. Machine learning research applied to Magnetic Resonance Imaging (MRI) techniques can contribute to a faster diagnosis of AD and may contribute to predicting the evolution of the disease. It was also possible to predict individual dementia of older adults with AD screening data and ML classifiers. To predict the AD subject status, the MRI demographic information and pre-existing conditions of the patient can help to enhance the classifier performance. In this work, we proposed a framework based on supervised learning classifiers in the dementia subject categorization as either AD or non-AD based on longitudinal brain MRI features. Six different supervised classifiers are incorporated for the classification of AD subjects and results mentioned that the gradient boosting algorithm outperforms other models with 97.58% of accuracy.

Neural precursors (NPs) present in the hippocampus can be modulated by several neurogenic stimuli, including environmental enrichment (EE) acting through BDNF-TrkB signaling. We have recently identified NPs in meninges; however, the meningeal niche response to pro-neurogenic stimuli has never been investigated. To this aim, we analyzed the effects of EE exposure on NP distribution in mouse brain meninges. Following neurogenic stimuli, although we did not detect modification of the meningeal cell number and proliferation, we observed an increased number of neural precursors in the meninges. A lineage tracing experiment suggested that EE-induced β3-Tubulin+ immature neuronal cells present in the meninges originated, at least in part, from GLAST+ radial glia cells. To investigate the molecular mechanism responsible for meningeal reaction to EE exposure, we studied the BDNF-TrkB interaction. Treatment with ANA-12, a TrkB non-competitive inhibitor, abolished the EE-induced meningeal niche changes. Overall, these data showed, for the first time, that EE exposure induced meningeal niche remodeling through TrkB-mediated signaling. Fluoxetine treatment further confirmed the meningeal niche response, suggesting it may also respond to other pharmacological neurogenic stimuli. A better understanding of the neurogenic stimuli modulation for meninges may be useful to improve the effectiveness of neurodegenerative and neuropsychiatric treatments.

The association between obesity and loss of cognitive performance has been recognized. Although there are data regarding the metabolic alterations in obese conditions and the development of neuroinflammation, no clear evidence concerning obesity-related cholinergic and synaptic impairments in the frontal cortex and hippocampus has been reported yet. Here, we investigate different cholinergic and synaptic markers in 12-, 16-, and 20-week-old obese Zucker rats (OZRs) compared with lean littermate rats (LZRs), using immunochemical and immunohistochemical analysis. Consequently, OZRs showed body weight gain, hypertension, and dysmetabolism. In 20-week-old OZRs, the reduction of vesicular acetylcholine transporter (VAChT) and alpha7 nicotinic acetylcholine receptors (α7nAChR) occurred both in the frontal cortex and in the hippocampus, suggesting a cognitive dysfunction due to obesity and aging. Among the muscarinic receptors analyzed, the level of expression of type 1 (mAChR1) was lower in the hippocampus of the older OZRs. Finally, we showed synaptic dysfunctions in OZRs, with a reduction of synaptophysin (SYP) and synaptic vesicle glycoprotein 2B (SV2B) in 20-week-old OZRs, both in the frontal cortex and in the hippocampus. Taken together, our data suggest specific alterations of cholinergic and synaptic markers that can be targeted to prevent cognitive deficits related to obesity and aging.

Objective: This prospective in vivo study aimed to compare the clinical behavior of a flowable composite resin (Genial Universal Flo, GC) and a nanohybrid universal composite resin (Tetric Evo Ceram, Ivoclar Vivadent) used in Class I and II direct esthetic restorations in posterior teeth. Methods: A total of 108 Class I and II direct restorations were performed in patients aged between 20 and 60 years. The originality of this study lies in the fact that both materials were placed in pairs, in the same clinical environment (i.e., the same patient and the same type of tooth). The evaluations were performed now of restoration and after 2-weeks, 6-, 12-, and 24-months intervals using clinical examination, clinical photographs, and radiological examination, according to modified USPHS criteria. Statistical analysis was performed using the Fisher exact test and chi-square analysis. Results: At baseline, the universal composite resin showed better esthetic properties such as surface luster, surface staining marginal staining. Both materials regressed significantly over time with no significant difference between groups. Conclusions: Both flowable and nanohybrid composite resins exhibit acceptable clinical performance. The present 24 months of evaluation of different composites showed that the G-ænial Universal Flo could be an effective esthetic material for posterior restoration. No significant difference between both materials over time concerning surface luster, surface staining, and marginal staining.

We present a method that maps a complex surface geometry to an equally complicated, similar surface. One main objective of our effort is to develop technology for automatically transferring surface annotations from an atlas brain to a subject brain. While macroscopic regions of brain surfaces often correspond, the detailed surface geometry of corresponding areas can vary greatly. We have developed a method that simplifies a subject brain's surface forming an abstract yet spatially descriptive point cloud representation, which we can match to the abstract point cloud representation of the atlas brain using an approach that iteratively improves the correspondence of points. The generation of the point cloud from the original surface is based on surface smoothing, surface simplification, surface classification with respect to curvature estimates, and clustering of uniformly classified regions. Segment mapping is based on spatial partitioning, principal component analysis, rigid affine transformation, and warping based on the thin-plate spline (TPS) method. The result is a mapping between topological components of the input surfaces allowing for transfer of annotations.

We give a method for improving the resolution of surfaces captured with a laser range scanner by combining many very similar scans. This idea is an application of the 2D image processing technique known as super-resolution. The input lower-resolution scans are each randomly shifted, so that each one contributes slightly different information to the final model. Noise is reduced by averaging the input scans.

We introduce a technique to visualize the gradual evolutionary change of the shapes of living things as a morph between known three-dimensional shapes. Given geometric computer models of anatomical shapes for some collection of specimens - here the skulls of the some of the extant members of a family of monkeys - an evolutionary tree for the group implies a hypothesis about the way in which the shape changed through time. We use a statistical method which expresses the value of some variable - in this case the shape - at an internal point in the tree as a weighted average of the values at the leaves. The framework of geometric morphometrics can then be used to define a shape-space, based on the correspondences of landmark points on the surfaces, within which these weighted averages can be realized as actual surfaces. Our software provides tools for performing and visualizing such an analysis in three dimensions. Beginning with laser range surfaces scans of skulls, we use our landmark editor to interactively place landmark points on the surface. We use these to compute a treemorph which smoothly interpolates the shapes across the tree. Each intermediate shape in the morph is a linear combination of all of the input surfaces. We create a surface model for an intermediate shape by warping all the input meshes towards the correct shape and then merging them together. Our merging procedure is novel. Given several similar surface meshes, we compute a weighted average between them by averaging their associated trivariate squared distance functions, and then extract the extremal surface which traces out the ''valleys'' along which the averaged function is nearly zero.

It is useful to be able to define a two-dimensional point-set surface determined by a point cloud. One popular definition is Levin's MLS surface. This surface is defined on a domain which is a three-dimensional, a narrow region around the input point cloud. If we were to extend the definition outside the domain, we would produce components of the surface which are far from the point cloud. This is important in practice, since when moving points onto the MLS surface, we need to begin with an initial guess which is within the domain. We visualize the domain in two dimensions, and explain why it is so narrow. We also consider two MLS variants which can be defined on a wider domain without producing spurious surface components. One is efficient and works well except near sharp corners. The other is computationally expensive but seems to work well everywhere.