Machine learning approaches to predict age from accelerometer records of physical activity at biobank scale.

Physical activity improves quality of life and protects against age-related diseases. With age, physical activity tends to decrease, increasing vulnerability to disease in the elderly. In the following, we trained a neural network to predict age from 115,456 one week-long 100Hz wrist accelerometer recordings from the UK Biobank (mean absolute error = 3.7±0.2 years), using a variety of data structures to capture the complexity of real-world activity. We achieved this performance by preprocessing the raw frequency data as 2,271 scalar features, 113 time series, and four images. We defined accelerated aging for a participant as being predicted older than one's actual age and identified both genetic and environmental exposure factors associated with the new phenotype. We performed a genome wide association on the accelerated aging phenotypes to estimate its heritability (h_g2 = 12.3±0.9%) and identified ten single nucleotide polymorphisms in close proximity to genes in a histone and olfactory cluster on chromosome six (e.g HIST1H1C, OR5V1). Similarly, we identified biomarkers (e.g blood pressure), clinical phenotypes (e.g chest pain), diseases (e.g hypertension), environmental (e.g smoking), and socioeconomic (e.g income and education) variables associated with accelerated aging. Physical activity-derived biological age is a complex phenotype associated with both genetic and non-genetic factors.

Accuracy of Bolton's Analysis among Different Malocclusion Patients Plaster Models and Digital Models Obtained by Ex Vivo Scanning with iTero Scanner in Chinese Han Population.

AIM: This investigation aimed to compare the accuracy of Bolton's analysis on plaster models of various malocclusion groups by utilizing digital calipers and iTero scanner. MATERIALS AND METHODS: The data consisted maxillary and mandibular plaster study casts of 61 patients (Class I-20, Class II-20, Class III-21) there were 31 males and 30 females. iTero®element scanner was utilized to scan the models and Bolton's analysis was performed on digital models. Also, the Digital caliper was utilized to perform the Manual measurements. Mesiodistal tooth widths, Anterior and Overall Bolton ratio was measured utilizing OrthoCAD™ software on digital models and plaster models with digital calipers. Statistical analysis was performed utilizing One-way ANOVA and independent T-test. RESULTS: Results revealed anterior and overall Bolton ratios showed significant differences (P < 0.05) for the measurements performed utilizing digital models. Anterior ratio for (Group 1) iTero measurements depicted the statistical significant value (P < 0.03) and overall ratio for (Group 2) digital caliper measurements depicted the statistical significant value (P < 0.02). CONCLUSION: With the introduction of intra-oral laser scanners it has become more convenient for the practitioner to perform the intra-oral digital scanning and carry out the model analysis digitally and iTero scanner can also be utilized extra-orally to perform the scanning and model analysis. Our study concludes that intra-oral laser scanner like iTero is more convenient for an orthodontist, and can be utilized for extra-oral scanning of orthodontic dental models as the measurements obtained on digital models was as accurate as the conventional method.

An overview on the veracity of intraoral digital scanning system and utilization of iTero scanner for analyzing orthodontic study models both In-Vivo and Ex-Vivo.

In the domain of orthodontics, plaster models are contemplated as one of the important tools for diagnosis and treatment planning. In Dentistry, technological advancement has developed in the section of diagnostic devices, for example, the utilization of a 3D intraoral scanner, which can convert plaster models into digital models. With in-office utilization of this system, orthodontists can more meticulously and precisely construct custom braces, clear aligners, and orthodontic appliances. The digital data can be stored as a stereolithography file; it eliminates the disadvantages encountered with the storage of plaster models like breakage, space required, and distortion of the plaster models. ITero®element is the intraoral laser scanner (ILS) which utilizes parallel confocal scanning technology which maximizes the accuracy of the scan. By utilizing the iTero scanner, the dental measurement can be performed in OrthoCADTM software which is highly accurate. The objective of the contemporary study is to review the literature of studies on in-vivo and ex-vivo scanning with the iTero system.

Mid-infrared spectrometry prediction of the cheese-making properties of raw Montbéliarde milks from herds and cheese dairy vats used for the production of Protected Designation of Origin and Protected Geographical Indication cheeses in Franche-Comté.

Franche-Comté is the primary producing region of Protected Designation of Origin cheeses in France. Normally, mid-infrared (MIR) prediction models for cheese-making property (CMP) traits are developed using individual bovine milks. However, considering the requests of all actors in the dairy sector, the present study aimed to assess the feasibility of MIR spectroscopy to develop CMP equations of Montbéliarde herd and dairy vat milks. For this purpose, 22 CMP traits were analyzed on samples collected in 2016 (half in February-March and half in May-June) from 100 commercial herds and 70 dairy vats (55 cheese dairies) located in Franche-Comté. These characteristics included 11 rennet coagulation traits and 8 lactic acidification traits measured in either soft cheese or pressed cooked cheese conditions and 3 laboratory curd yields. Models of MIR prediction for each of the 22 CMP traits were built using partial least squares regression with external validation by dividing the data set into calibration (70%) and validation (30%) sets. We confirmed that the variability of milk traits depends largely on the production scale and is higher for individual milk than for herd milk and even higher for vat milk. The best prediction models were obtained in herd milk samples for curd yields expressed in dry matter or fresh, with a coefficient of determination (R2) in external validation of 0.78 and 0.77, respectively. As with individual milk, these traits are closely related to the gross composition of the milk and therefore easier to predict by MIR spectroscopy. However, these curd yield traits were poorly predicted (R2 = 0.58) in vat milk samples due to their lower variability. In herd milk samples, prediction models of other CMP traits were poorly accurate except for the ratio of the time to obtain a standard firmness to the rennet coagulation time in soft cheese or pressed cooked cheese conditions, which showed R2 > 0.66 in external validation. Such trait is important in qualifying the behavior of milk during cheese production. Prediction models of other CMP traits for either herd or vat milk samples had poor accuracy, and further work is needed to improve their performance.

Comparison of Bayesian and partial least squares regression methods for mid-infrared prediction of cheese-making properties in Montbéliarde cows.

Assessing the cheese-making properties (CMP) of milks with a rapid and cost-effective method is of particular interest for the Protected Designation of Origin cheese sector. The aims of this study were to evaluate the potential of mid-infrared (MIR) spectra to estimate coagulation and acidification properties, as well as curd yield (CY) traits of Montbéliarde cow milk. Samples from 250 cows were collected in 216 commercial herds in Franche-Comté with the objectives to maximize the genetic diversity as well as the variation in milk composition. All coagulation and CY traits showed high variability (10 to 43%). Reference analyses performed for soft (SC) and pressed cooked (PCC) cheese technology were matched with MIR spectra. Prediction models were built on 446 informative wavelengths not tainted by the water absorbance, using different approaches such as partial least squares (PLS), uninformative variable elimination PLS, random forest PLS, Bayes A, Bayes B, Bayes C, and Bayes RR. We assessed equation performances for a set of 20 CMP traits (coagulation: 5 for SC and 4 for PCC; acidification: 5 for SC and 3 for PCC; laboratory CY: 3) by comparing prediction accuracies based on cross-validation. Overall, variable selection before PLS did not significantly improve the performances of the PLS regression, the prediction differences between Bayesian methods were negligible, and PLS models always outperformed Bayesian models. This was likely a result of the prior use of informative wavelengths of the MIR spectra. The best accuracies were obtained for curd yields expressed in dry matter (CYDM) or fresh (CYFRESH) and for coagulation traits (curd firmness for PCC and SC) using the PLS regression. Prediction models of other CMP traits were moderately to poorly accurate. Whatever the prediction methodology, the best results were always obtained for CY traits, probably because these traits are closely related to milk composition. The CYDM predictions showed coefficient of determination (R2) values up to 0.92 and 0.87, and RSy,x values of 3 and 4% for PLS and Bayes regressions, respectively. Finally, we divided the data set into calibration (2/3) and validation (1/3) sets and developed prediction models in external validation using PLS regression only. In conclusion, we confirmed, in the validation set, an excellent prediction for CYDM [R2 = 0.91, ratio of performance to deviation (RPD) = 3.39] and a very good prediction for CYFRESH (R2 = 0.84, RPD = 2.49), adequate for analytical purposes. We also obtained good results for both PCC and SC curd firmness traits (R2 ≥ 0.70, RPD ≥1.8), which enable quantitative prediction.

Short communication: Confirmation of candidate causative variants on milk composition and cheesemaking properties in Montbéliarde cows.

In a previous study, we identified candidate causative variants located in 24 functional candidate genes for milk protein and fatty acid composition in Montbéliarde, Normande, and Holstein cows. We designed these variants on the custom part of the EuroG10K BeadChip (Illumina Inc., San Diego, CA), which is routinely used for genomic selection analyses in French dairy cattle. To validate the effects of these candidate variants on milk composition and to estimate their effects on cheesemaking properties, a genome-wide association study was performed on milk protein, fatty acid and mineral composition, as well as on 9 cheesemaking traits (3 laboratory cheese yields, 5 coagulation traits, and milk pH). All the traits were predicted from midinfrared spectra in the Montbéliarde cow population of the Franche-Comté region. A total of 194 candidate variants located in 24 genes and 17 genomic regions were imputed on 19,862 cows with phenotypes and genotyped with either the BovineSNP50 (Illumina Inc.) or the EuroG10K BeadChip. We then tested the effect of each SNP in a mixed linear model including random polygenic effects estimated with a genomic relationship matrix. We confirm here the effects of candidate causative variants located in 17 functional candidate genes on both cheesemaking properties and milk composition traits. In each candidate gene, we identified the most plausible causative variant: 4 are missense in the ALPL, SLC26A4, CSN3, and SCD genes, 7 are located in 5'UTR (AGPAT6), 3' untranslated region (GPT), or upstream (CSN1S1, CSN1S2, PAEP, DGAT1, and PICALM) regions, and 6 are located in introns of the SLC37A1, MGST1, CSN2, BRI3BP, FASN, and ANKH genes.

Genetic parameters for cheese-making properties and milk composition predicted from mid-infrared spectra in a large data set of Montbéliarde cows.

Cheese-making properties of pressed cooked cheeses (PCC) and soft cheeses (SC) were predicted from mid-infrared (MIR) spectra. The traits that were best predicted by MIR spectra (as determined by comparison with reference measurements) were 3 measures of laboratory cheese yield, 5 coagulation traits, and 1 acidification trait for PCC (initial pH; pH0PPC). Coefficients of determination of these traits ranged between 0.54 and 0.89. These 9 traits as well as milk composition traits (fatty acid, protein, mineral, lactose, and citrate content) were then predicted from 1,100,238 MIR spectra from 126,873 primiparous Montbéliarde cows. Using this data set, we estimated the corresponding genetic parameters of these traits by REML procedures. A univariate or bivariate repeatability animal model was used that included the fixed effects of herd × test day × spectrometer, stage of lactation, and year × month of calving as well as the random additive genetic, permanent environmental, and residual effects. Heritability estimates varied between 0.37 and 0.48 for the 9 cheese-making property traits analyzed. Coagulation traits were the ones with the highest heritability (0.42 to 0.48), whereas cheese yields and pH0 PPC had the lowest heritability (0.37 to 0.39). Strong favorable genetic correlations, with absolute values between 0.64 and 0.97, were found between different measures of cheese yield, between coagulation traits, between cheese yields and coagulation traits, and between coagulation traits measured for PCC and SC. In contrast, the genetic correlations between milk pH0 PPC and CY or coagulation traits were weak (-0.08 to 0.09). The genetic relationships between cheese-making property traits and milk composition were moderate to high. In particular, high levels of proteins, fatty acids, Ca, P, and Mg in milk were associated with better cheese yields and improved coagulation. Proteins in milk were strongly genetically correlated with coagulation traits and, to a lesser extent, with cheese yields, whereas fatty acids in milk were more genetically correlated with cheese yields than with coagulation traits. This study, carried out on a large scale in Montbéliarde cows, shows that MIR predictions of cheese yields and milk coagulation properties are sufficiently accurate to be used for genetic analyses. Cheese-making traits, as predicted from MIR spectra, are moderately heritable and could be integrated into breeding objectives without additional phenotyping cost, thus creating an opportunity for efficient improvement via selection.

Anthelmintic activity of Tunisian chamomile (Matricaria recutita L.) against Haemonchus contortus.

The chemical treatment of gastrointestinal parasitic diseases has been undermined by increasing resistance and high toxicity. There is an urgent need to search for alternative natural sources for the treatment of such parasites. In this respect, the present study aims to quantify phenolic compounds of chamomile (Matricaria recutita L.) and to study their in vitro anti-oxidant and anthelmintic activities in solvents with increasing polarity. In vitro determination of anti-oxidant capacity was carried out using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2-azino-bis-(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS) radical cation methods. In vitro anthelmintic activity was investigated on egg-hatching inhibition and loss of motility of adult worms of Haemonchus contortus from sheep. The results showed that methanolic and aqueous extracts contain more total polyphenols, total flavonoids and condensed tannins than chloroformic and hexanic extracts. ABTS and DPPH assays showed that methanolic extracts had the highest anti-oxidant potency (IC50 = 1.19 µg/ml and 1.18 µg/ml, respectively). In vitro anthelmintic activity showed that both methanolic (IC50 = 1.559 mg/ml) and aqueous (IC50 = 2.559 mg/ml) extracts had the greatest effect on egg hatching and motility of worms (100% after 8 h post exposure at 8 mg/ml). A significant and positive correlation between DPPH and ABTS tests was observed for all tested extracts. Therefore, total phenolic, total flavonoid and condensed tannin values were correlated with IC50 from both ABTS and DPPH, and with inhibition of egg hatching. To our knowledge, this report is the first of its kind to deal with in vitro anthelmintic activities of chamomile extracts.

Treatment for metastatic nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC) is a specific entity different from head and neck carcinoma. Incidence is higher in South-East Asia and North Africa. Prognosis, especially for locally advanced stages (IIB - IVB) and metastasis, remains poor: more than third of cases will present local and/or metastatic recurrence. Overall 5-year survival for all NPC stages ranges from 50% to 70%. The role of chemotherapy in metastasis is well established, and remains an important palliative treatment, although no randomized trial has been reported comparing the different chemotherapy regimens. As 1(st)-line treatment, platin-based regimens seems optimal; in 2(nd) line and after progression under platins, there is no consensus: monotherapy with drugs such as gemcitabine, capecitabine or taxanes has been the most widely tested, with acceptable results. Future trials should integrate targeted therapy, in the light of overexpression of EGFR1 and C-kit in NPC. The present study presents a review of the literature concerning the various studies of metastatic NPC.

[Resistance to B-lactamines of bacteria responsible for endodontic root canal infections]. / Résistance aux beta-lactamines des bactéries responsables des infections canalaires endodontiques.

Samples were taken under strictly anaerobic conditions from the root canals of 22 patients having a tooth in which necrotic pulp was associated with an inflammatory peri-apical lesion an optical periodontitis. In the majority of cases (85%), these lesions were chronic and the pulp chamber was closed. One hundred and two strains were isolated, 71.7% of the bacteria being obligate anaerobes and 49.8% being Gram-negative bacilli. Their ability to produce beta-lactamases was tested and 8.8% gave a positive reaction in a cefinase test. These cefinase positive strains were nevertheless susceptible to 3rd-generation cephalosporins (cefoxitin) and to amoxicillin-clavulanate, with the exception of M. Morganii.

Les soins dentaires chez la femme enceinte

La grossesse est un état physiologique caracterisé par des modifications hormonales ayant des repercussions bucco-dentaires. La plupart des praticiens appréhendent le déroulement des soins dentaires au cours de ces neuf mois. Il nous parait utile de mettre le point sur les particularités physiologiques durant chacun des trois trimestres de gestation d'une part; et les possibilités et les limites thérapeutiques d'autre part; afin d'éliminer toute ambiguité sur la prise en charge de la femme enceinte

Traitement endodontique d'une premolaire maxillaire triacidulee

Les premolaires maxillaires sont generalement considerees comme des dents faciles a traiter endodontiquement. Cependant; les etudes anatomiques ont montre une grande variete anatomique ce qui doit imposer une prudence lors des traitements canalaires de celles-ci. Le cas clinique confirme les variations du reseau canalaire de ces dents

L'obturation canalaire au systeme thermafil

L'obturation est l'acte terminal du traitement endontique qui vise a isoler le reseau canalaire du milieu buccal et du parodonte profond. La gutta compactee represente la technique de choix pour realiser une obturation tridimensionnelle. Plusieurs techniques ont ete adoptees mais necessitent souvent des preparations difficiles et souvent longues. Le choix de l'omnipraticien doit se faire vers une technique pouvant concilier entre trois piliers : efficacite; rapidite et cout. Les annees 90 voient l'apparition d'une nouvelle generation de gutta percha prechauffee avant d'etre inseree. L'une des techniques repondant a ce principe est le systeme thermafil

Le collage au service des pertes de substances dentaires anterieures

L'atteinte carieuse et les traumatismes sont des causes de pertes de substances dentaires anterieures. Cette perte de substance altere inevitablement l'esthetique et entraine le mecontentement de nos patients. L'avenement du collage et l'introduction de nouveaux materiaux composites permettent actuellement de repondre favorablement aux cas de pertes de substances anterieures en evitant le recours aux techniques prothetiques. L'utilisation de techniques de stratification assure la reproduction fidele de l'aspect et de la teinte de la dent. Cet article passe en revue quelques cas de pertes de substances dentaires anterieures traites au C.C.T.D Ibn Rochd de Casablanca

Multiresolution forecasting for futures trading using wavelet decompositions.

We investigate the effectiveness of a financial time-series forecasting strategy which exploits the multiresolution property of the wavelet transform. A financial series is decomposed into an over complete, shift invariant scale-related representation. In transform space, each individual wavelet series is modeled by a separate multilayer perceptron (MLP). We apply the Bayesian method of automatic relevance determination to choose short past windows (short-term history) for the inputs to the MLPs at lower scales and long past windows (long-term history) at higher scales. To form the overall forecast, the individual forecasts are then recombined by the linear reconstruction property of the inverse transform with the chosen autocorrelation shell representation, or by another perceptron which learns the weight of each scale in the prediction of the original time series. The forecast results are then passed to a money management system to generate trades.

A low-complexity intracardiac electrogram compression algorithm.

Implantable cardioverter defibrillators (ICD's) detect, diagnose and treat the potentially fatal heart arrhythmias known as bradycardia, ventricular tachycardia (VT), and ventricular fibrillation (VF) in cases where these arrhythmias are resistant to surgical and drug-based treatments by direct sensing and electrical stimulation of the heart muscle. Since the ICD is implanted, power consumption, reliability, and size are severe design constraints. This paper targets the problems associated with increasing the signal recording capabilities of an ICD. A data-compression algorithm is described which has been optimized for low power consumption and high reliability implementation. Reliance on a patients morphology or that of a population of patients is avoided by adapting to the intracardiac electrogram (ICEG) amplitude and phase variations and by using adaptive scalar quantization. The algorithm is compared to alternative compression algorithms which are also patient independent using a subset of VT arrhythmias from a data base of 146 patients. At low distortion the algorithm is closest to the Shannon lower bound achieving an average of 3.5 b/sample at 5% root mean square distortion for a 250-Hz sample rate. At higher distortion vector quantization and Karhunen-Loeve Transform approaches are superior but at the cost of considerable additional computational complexity.

Handwritten digit recognition by adaptive-subspace self-organizing map (ASSOM).

The adaptive-subspace self-organizing map (ASSOM) proposed by Kohonen is a recent development in self-organizing map (SOM) computation. In this paper, we propose a method to realize ASSOM using a neural learning algorithm in nonlinear autoencoder networks. Our method has the advantage of numerical stability. We have applied our ASSOM model to build a modular classification system for handwritten digit recognition. Ten ASSOM modules are used to capture different features in the ten classes of digits. When a test digit is presented to all the modules, each module provides a reconstructed pattern and the system outputs a class label by comparing the ten reconstruction errors. Our experiments show promising results. For relatively small size modules, the classification accuracy reaches 99.3% on the training set and over 97% on the testing set.

Artificial neural network-based channel selection and loudness mapping.

We present in this paper artificial neural network techniques for implementing loudness mapping and "smart" channel selection for cochlear implant systems. For loudness mapping, a multilayer perceptron (MLP) is trained to perform the mapping for each channel according to threshold and comfort levels. It is shown that good accuracy mapping can be performed by a very simple MLP architecture. For channel selection, we propose a neural network-based method that can make "smart" selection. We describe and report results for the case in which 6 channels are to be selected from 18. The neural network-based selection system is trained on a multispeaker labeled speech database and tested on a database of different speakers and spoken sentences. Compared with methods used by leading cochlear implant systems, our approach produces significantly better results, and it is easy to implement in the speech processor of the cochlear implant system.

A low-power VLSI arrhythmia classifier.

The design, implementation, and operation of a low-power multilayer perceptron chip (Kakadu) in the framework of a cardiac arrhythmia classification system is presented in this paper. This classifier, called MATIC, makes timing decisions using a decision tree, and a neural network is used to identify heartbeats with abnormal morphologies. This classifier was designed to be suitable for use in implantable devices and a VLSI (very large scale integration) neural-network chip (Kakadu) was designed so that the computationally expensive neural-network algorithm can be implemented with low power consumption. Kakadu implements a (10,6,4) perceptron and has a typical power consumption of tens of microwatts. When used with the arrhythmia classification system, the chip can operate with an average power consumption of less than 25 nW.

Kakadu--a low power analogue neural network classifier.

An analogue neural network VLSI chip designed for low power operation is presented. This chip consists of 84 synapse elements arranged as arrays of size 10 x 6 and 6 x 4 and was fabricated using a standard 1.2 micron double metal single poly CMOS process. The synapses are digitally programmable and static weight storage is provided. The chip has a typical power consumption of tens of microwatts. It has been successfully trained and tested on a range of classification problems including 4-bit parity, character recognition and morphological-based classification of intracardiac electrogram signals.