Search

Osteoarthritis (OA), a progressive degenerative disease of cartilage in joints, is the most common cause of chronic disability in older adults. While OA is mostly considered an age-related pathology, women have a 1.5-fold higher risk of developing OA relative to men and experience more severe symptoms. Yet, they remain underrepresented in musculoskeletal research and clinical trials. Responsible for cartilage formation, articular chondrocytes experience physiological changes in OA, but the functional implications of such alterations remain largely unexplored due to difficulties in acquiring the data experimentally. Through reparameterization, we expand a mathematical chondrocyte model to investigate sex-specific OA pathogenesis. We performed sensitivity analysis to address the impact of ion channel activity in healthy and OA chondrocyte populations. Simulations show that in healthy female chondrocytes, the resting membrane potential is more depolarized than in healthy male chondrocytes, suggesting potential sex-specific emergent physiological differences in articular chondrocytes. In both sexes, the resting membrane potential of healthy chondrocytes is most sensitive to 𝐼𝐶𝑎−𝐴𝑇𝑃, 𝐼𝑁𝑎−𝑏, 𝐼𝑁𝑎𝐾 and 𝐼𝐾−𝑏, but in OA it depolarizes and becomes sensitive to 𝐼𝐾𝐷𝑅, 𝐼𝑁𝑎𝐾 and 𝐼𝐾−𝑏. Developed and evaluated against experimental data, our articular chondrocyte OA electrophysiological model can be used to further study OA pathology and sex-specific pathological OA changes.

Microprocessor (MP) is a complex involved in initiating the biogenesis of microRNAs (miRNAs) by cleaving primary microRNAs (pri-miRNAs). miRNAs are small single-stranded RNAs that play a key role in the post-transcriptional regulation of gene expression. Thus, understanding the molecular mechanism of MP is critical for interpreting the roles of miRNAs in normal cellular processes and during the onset of various diseases. MP comprises a ribonuclease enzyme, DROSHA, and a dimeric RNA-binding protein, which is called DGCR8 in humans and Pasha in Caenorhabditis elegans. DROSHA cleaves stem-loop structures located within pri-miRNAs to generate pre-miRNAs. Although the molecular mechanism of human MP (hMP; hDROSHA-DGCR8) is well understood, that of Caenorhabditis elegans MP (cMP; cDrosha-Pasha) is still largely unknown. Here, we reveal the molecular mechanism of cMP and show that it is distinct from that of hMP. We demonstrate that cDrosha and Pasha measure ∼16 and ∼25 bp along a pri-miRNA stem, respectively, and they work together to determine the site of cMP cleavage in pri-miRNAs. We also demonstrate the molecular basis for their substrate measurement. Thus, our findings reveal a previously unknown molecular mechanism of cMP; demonstrate the differences between the mechanisms of hMP and cMP; and provide a foundation for revealing the mechanisms regulating miRNA expression in different animal species.The Microprocessor complex that initiates miRNA biogenesis was discovered in animals in 2004. However, the molecular mechanism of C. elegans Microprocessor (cMP) has remained elusive since its discovery 18 years ago. In this study, we revealed the unique molecular mechanism of cMP by conducting high-throughput pri-miRNA cleavage assays. We demonstrated that cMP, consisting of cDrosha and Pasha, each can measure the stem lengths of pri-miRNAs. cDrosha measures ∼16 bp of the lower stem length, whereas Pasha measures ∼25 bp of the upper stem in pri-miRNAs. In addition, we identified the cleavage sites and cleavage efficiency of cMP in C. elegans pri-miRNAs. These results will be helpful for future studies of miRNA biogenesis in C. elegans.

The rational improvement of the enzyme catalytic activity is one of the most significant challenges in biotechnology. Most conventional strategies used to engineer enzymes involve selecting mutations to increase their thermostability. Determining good criteria for choosing these substitutions continues to be a challenge. In this work, we combine bioinformatics, electrostatic analysis, and molecular dynamics to predict beneficial mutations that may improve the thermostability of XynA from

International audience; Word alignments identify translational correspondences between words in a parallel sentence pair and are used, for instance, to learn bilingual dictionaries, to train statistical machine translation systems or to perform quality estimation. Variational autoencoders have been recently used in various of natural language processing to learn in an unsupervised way latent representations that are useful for language generation tasks. In this paper, we study these models for the task of word alignment and propose and assess several evolutions of a vanilla variational autoencoders. We demonstrate that these techniques can yield competitive results as compared to Giza++ and to a strong neural network alignment system for two language pairs.

Xanthine oxidase inhibitory activity of celery seed extract was predicted from UV–Vis spectrum using five different algorithms: multiple linear regression, artificial neural network, support vector regression, random forest and partial linear regression. The optimal parameters of each model established by these methods were examined carefully and the best model was selected. The results showed that the model obtained by partial linear regression had the best quality with coefficient of determination R2 = 0.9618, correlation coefficient of leave-one-out cross validation Q2 = 0.8746, average absolute deviation MAD = 0.0671, root mean square error RMSE = 0.0761 and the accuracy of the model with train and test were 99.29% and 96.69%, respectively. Our findings suggest that this model could be an effective method for rapidly determining xanthine oxidase inhibitory activity of herbal medicine, particularly celery seed extract from UV–Vis spectra. However, more investigations are required in order to improve the performance of the partial linear regression model.

This paper proposes and validates a new design for autogenous mobile systems based on the combination of vibration and impact of an oscillating mass with two-side elastic constraints. The proposed system is driven by a two-side impact oscillator which is excited by a periodic pulsed force. The system can move backward and forward as desired by simply reverse the excitation force. A mathematical model has been developed to form a basis of the design process and to choose proper operational parameters. An experimental rig has been implemented to validate the proposed design. The mathematical model of the system with non-dimensional parameters allows extending the results to both large- and micro-scale autogenous drifting applications.

Word alignments identify translational correspondences between words in a parallel sentence pair and is used, for instance, to learn bilingual dictionaries, to train statistical machine translation systems , or to perform quality estimation. In most areas of natural language processing, neural network models nowadays constitute the preferred approach, a situation that might also apply to word alignment models. In this work, we study and comprehensively evaluate neural models for unsupervised word alignment for four language pairs, contrasting several variants of neural models. We show that in most settings, neural versions of the IBM-1 and hidden Markov models vastly outperform their discrete counterparts. We also analyze typical alignment errors of the baselines that our models overcome to illustrate the benefits-and the limitations-of these new models for morphologically rich languages., Comment: The 16th International Workshop on Spoken Language Translation, Nov 2019, Hong Kong, Hong Kong SAR China

This paper presents a new approach to developing the torque model in deep hole drilling, both for conventional and ultrasonic assisted drilling processes. The model was proposed as a sum of three components: the cutting, the chip evacuation and the stick-slip torques. Parameters of the new model were carried out by applying the regression analysis technique, with the correlation values higher than 0.999. The data were collected from 36 experimental dry drilling tests, both in conventional and ultrasonic assisted cutting conditions, with the depth-to-diameter of the drilled holes of 7.5. The major advantage of the new model compared to previous models is that the new model of chip-evacuation torque has only one coefficient, thus making it easier to evaluate and compare different deep-drilling processes. The effectiveness of ultrasonic assistance in deep hole drilling was also highlighted using the proposed model. The new model is promising to predict critical depth and torque in deep hole drilling.