Protein-protein interactions and metabolic pathways reconstruction of Caenorhabditis elegans

Metabolic networks are the collections of all cellular activities taking place in a living cell and all the relationships among biological elements of the cell including genes, proteins, enzymes, metabolites, and reactions. They provide a better understanding of cellular mechanisms and phenotypic characteristics of the studied organism. In order to reconstruct a metabolic network, interactions among genes and their molecular attributes along with their functions must be known. Using this information, proteins are distributed among pathways as sub-networks of a greater metabolic network. Proteins which carry out various steps of a biological process operate in same pathway.The metabolic network of Caenorhabditis elegans was reconstructed based on current genomic information obtained from the KEGG database, and commonly found in SWISS-PROT and WormBase. Assuming proteins operating in a pathway are interacting proteins, currently available protein-protein interaction map of the studied organism was assembled. This map contains all known protein-protein interactions collected from various sources up to the time. Topology of the reconstructed network was briefly studied and the role of key enzymes in the interconnectivity of the network was analysed. The analysis showed that the shortest metabolic paths represent the most probable routes taken by the organism where endogenous sources of nutrient are available to the organism. Nonetheless, there are alternate paths to allow the organism to survive under extraneous variations. Signature content information of proteins was utilized to reveal protein interactions upon a notion that when two proteins share signature(s) in their primary structures, the two proteins are more likely to interact. The signature content of proteins was used to measure the extent of similarity between pairs of proteins based on binary similarity score. Pairs of proteins with a binary similarity score greater than a threshold corresponding to confidence level 95% were predicted as interacting proteins. The reliability of predicted pairs was statistically analyzed. The sensitivity and specificity analysis showed that the proposed approach outperformed maximum likelihood estimation (MLE) approach with a 22% increase in area under curve of receiving operator characteristic (ROC) when they were applied to the same datasets. When proteins containing one and two known signatures were removed from the protein dataset, the area under curve (AUC) increased from 0.549 to 0.584 and 0.655, respectively. Increase in the AUC indicates that proteins with one or two known signatures do not provide sufficient information to predict robust protein-protein interactions. Moreover, it demonstrates that when proteins with more known signatures are used in signature profiling methods the overlap with experimental findings will increase resulting in higher true positive rate and eventually greater AUC. Despite the accuracy of protein-protein interaction methods proposed here and elsewhere, they often predict true positive interactions along with numerous false positive interactions. A global algorithm was also proposed to reduce the number of false positive predicted protein interacting pairs. This algorithm relies on gene ontology (GO) annotations of proteins involved in predicted interactions. A dataset of experimentally confirmed protein pair interactions and their GO annotations was used as a training set to train keywords which were able to recover both their source interactions (training set) and predicted interactions in other datasets (test sets). These keywords along with the cellular component annotation of proteins were employed to set a pair of rules that were to be satisfied by any predicted pair of interacting proteins. When this algorithm was applied to four predicted datasets obtained using phylogenetic profiles, gene expression patterns, chance co-occurrence distribution coefficient, and maximum likelihood estimation for S. cerevisiae and C. elegans, the improvement in true positive fractions of the datasets was observed in a magnitude of 2-fold to 10-fold depending on the computational method used to create the dataset and the available information on the organism of interest. The predicted protein-protein interactions were incorporated into the prior reconstructed metabolic network of C. elegans, resulting in 1024 new interactions among 94 metabolic pathways. In each of 1024 new interactions one unknown protein was interacting with a known partner found in the reconstructed metabolic network. Unknown proteins were characterized based on the involvement of their known partners. Based on the binary similarity scores, the function of an uncharacterized protein in an interacting pair was defined according to its known counterpart whose function was already specified. With the incorporation of new predicted interactions to the metabolic network, an expanded version of that network was resulted with 27% increase in the number of known proteins involved in metabolism. Connectivity of proteins in protein-protein interaction map changed from 42 to 34 due to the increase in the number of characterized proteins in the network

Microencapsulation optimization of natural anthocyanins with maltodextrin, gum Arabic and gelatin

The barberry (Berberis vulgaris) extract which is a rich source of anthocyanins was used for spray drying encapsulation with three different wall materials, i.e., combination of maltodextrin and gum Arabic (MD + GA), maltodextrin and gelatin (MD + GE), and maltodextrin (MD). Response Surface Methodology (RSM) was applied for optimization of microencapsulation efficiency and physical properties of encapsulated powders considering wall material type as well as different ratios of core to wall materials as independent variables. Physical characteristics of spray-dried powders were investigated by further analyses of moisture content, hygroscopicity, degree of caking, solubility, bulk and absolute density, porosity, flowability and microstructural evaluation of encapsulated powders. Our results indicated that samples produced with MD + GA as wall materials represented the highest process efficiency and best powder quality; the optimum conditions of microencapsulation process for barberry anthocyanins were found to be the wall material content and anthocyanin load of 24.54 and 13.82, respectively. Under such conditions, the microencapsulation efficiency (ME) of anthocyanins could be as high as 92.83. © 2016 Elsevier B.V

Storage stability of encapsulated barberry's anthocyanin and its application in jelly formulation

The barberry (Berberis vulgaris) extract which is a rich source of anthocyanin was used for encapsulation with three different wall materials i.e., combination of gum Arabic and maltodextrin (GA+MD), combination of maltodextrin and gelatin (MD+GE) and maltodextrin (MD) by spray drying process. In this context, the storage stability of encapsulated pigments was investigated under four storage temperatures (4, 25, 35 and 42 °C), four relative humidities (20, 30, 40 and 50%) and light illumination until 90 days. All wall materials largely increased the half-life of the encapsulated pigments during storage compared with non-encapsulated anthocyanins. MD+GA showed the highest encapsulation efficiency, lower degradation rate in all temperatures and was found as the most effective wall material in stabilizing the pigments. The encapsulated pigments were utilized in coloring jelly powder as an alternative of synthetic color. Sensory evaluation were run to identify best encapsulated natural color concentration in jelly powder formulation according to acceptability by consumers. A jelly with added 7% encapsulated color had higher scores than the commercial jelly containing synthetic color for all the sensory attributes evaluated. Physicochemical properties of produced jelly including moisture content, hygroscopicity, acidity, ash content and texture were not significantly different with control sample while, syneresis and solubility of the samples prepared with encapsulated color was significantly reduced. © 2016 Elsevier Ltd

Equality Operators for Constant-weight Codewords with Applications in (Keyword) PIR

Homomorphic encryption allows computation to be performed on data while in encrypted form. However, the computational overhead of a circuit that is run using homomorphic encryption depends on the number of multiplications and multiplicative depth. For example, equality checks which are a common step in many tasks, have a multiplicative depth that depends on the bit-length of the numbers. In this work, we propose constant-weight equality operators, which compare constant-weight codewords using a circuit that has a multiplicative depth that depends solely on the Hamming weight of the constant-weight code, not the size of the operands. Private Information Retrieval (PIR) is one task where equality operations are a solution. In a PIR protocol, a user wishes to query a database without revealing which element is queried to the server. In this thesis, we also detail an architecture for PIR which was previously assumed to be impractical. At the heart of this architecture is the constant-weight equality operator. Our experiments show how constant-weight equality operators outperform existing equality operators and can be used for practical purposes. We also conduct experiments to show the practicality of PIR using our approach and our results show how constant-weight PIR outperforms existing work in aspects of scale such as large domain sizes and large responses

The role of psychosocial factors affecting marital satisfaction in couples after marital infidelity

Background: Marital infidelity in our country is increasing and a few studies have been done on the factors influencing marital satisfaction afterwards. Therefore, in this study, we decided to determine the role of psychosocial factors affecting marital satisfaction in couples after marital infidelity.Method: This analytical-cross-sectional study was conducted on 235 couples who betrayed and did betrayal referred to relevant centers (counseling centers of Tehran and Mashhad’s university and court). Subjects completed marital satisfaction questionnaires (ENRICH)[1], attitudes toward infidelity scale (MARK WHATLY), adult attachment scale (RAAS), men’s and women’s sexual schema scale, and data were entered into SPSS 21 software after encoding and were analyzed by linear regression statistical method.Results: The results of data analysis showed that the most important factors affecting marital satisfaction were: attitude toward infidelity, scale of passionate – romantic scale, age and embarrassed - conservation schema (women) (p <0.05). Among these variables, age, attitude towards infidelity and embarrassed - conservation scale are inversely correlated with marital satisfaction, meaning that the higher the variance in terms of these variables, we will see less marital satisfaction after infidelity. But the passionate – romantic scale has a direct relationship with marital satisfaction, meaning that the more men are stronger in terms of this schema, the greater the marital satisfaction between the couples after the infidelity.Discussion and Conclusion: According to the findings of this research, it can be recommended to therapists to consider these variables in their therapeutic components to promote marital satisfaction after infidelity.

Level Up: Private Non-Interactive Decision Tree Evaluation using Levelled Homomorphic Encryption

As machine learning as a service continues gaining popularity, concerns about privacy and intellectual property arise. Users often hesitate to disclose their private information to obtain a service, while service providers aim to protect their proprietary models. Decision trees, a widely used machine learning model, are favoured for their simplicity, interpretability, and ease of training. In this context, Private Decision Tree Evaluation (PDTE) enables a server holding a private decision tree to provide predictions based on a client's private attributes. The protocol is such that the server learns nothing about the client's private attributes. Similarly, the client learns nothing about the server's model besides the prediction and some hyperparameters. In this paper, we propose two novel non-interactive PDTE protocols, XXCMP-PDTE and RCC-PDTE, based on two new non-interactive comparison protocols, XXCMP and RCC. Our evaluation of these comparison operators demonstrates that our proposed constructions can efficiently evaluate high-precision numbers. Specifically, RCC can compare 32-bit numbers in under 10 milliseconds. We assess our proposed PDTE protocols on decision trees trained over UCI datasets and compare our results with existing work in the field. Moreover, we evaluate synthetic decision trees to showcase scalability, revealing that RCC-PDTE can evaluate a decision tree with over 1000 nodes and 16 bits of precision in under 2 seconds. In contrast, the current state-of-the-art requires over 10 seconds to evaluate such a tree with only 11 bits of precision

Surface Electromyography Feature Extraction Based on Wavelet Transform

Considering the vast variety of EMG signal applications such as rehabilitation of people suffering from some mobility limitations, scientists have done much research on EMG control system. In this regard, feature extraction of EMG signal has been highly valued as a significant technique to extract the desired information of EMG signal and remove unnecessary parts. In this study, Wavelet Transform (WT) has been applied as the main technique to extract Surface EMG (SEMG) features because WT is consistent with the nature of EMG as a nonstationary signal. Furthermore, two evaluation criteria, namely, RES index (the ratio of a Euclidean distance to a standard deviation) and scatter plot are recruited to investigate the efficiency of wavelet feature extraction. The results illustrated an improvement in class separability of hand movements in feature space. Accordingly, it has been shown that only the SEMG features extracted from first and second level of WT decomposition by second order of Daubechies family (db2) yielded the best class separability

Optimization of lipid production in Chlorella vulgaris for biodiesel production using flux balance analysis

The final publication is available at Elsevier via https://dx.doi.org/10.1016/j.bej.2018.10.011 © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/Microalgae, the world’s largest group of photosynthetic organisms, convert atmospheric CO2 to polar and neutral lipids using sunlight, which after esterification can be utilized for biodiesel production. In the present study, a fully compartmentalized metabolic network was developed to describe the metabolism of Chlorella vulgaris based on known enzymatic reactions and typical metabolic pathways of green algae. Flux balance analysis was employed to optimize the specific growth rate and the lipid production rate using measured exchange fluxes of the metabolites. The experimental data for batch and fed batch algal fermentation systems acquired from the literature were used to validate the accuracy of the pseudo- steady state model. The physiological pathways of the microalgae for lipid biosynthesis were identified. The simulation revealed that the microalgae would be able to produce higher levels of lipid content (43.6%) during N-starvation cultivation under 100 μmol m−2 s−1 light intensity, 0.25 vvm aeration with 2% (v/v) CO2, 2 mg L−1 PO4-P, and 5 mg L−1 NO3-N. Sensitivity analysis showed that CO2, light energy, O2, and nitrate were the most important factors affecting the lipid production at N-deficient conditions. The findings consequential for manipulation of the metabolism of the microalgae with optimal activity.Ferdowsi university of Mashhad’s research center, Iran ["25902"]

The utility of wavelet transform in surface electromyography feature extraction - a comparative study of different mother wavelets

Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements

PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting

Two parties with private data sets can find shared elements using a Private Set Intersection (PSI) protocol without revealing any information beyond the intersection. Circuit PSI protocols privately compute an arbitrary function of the intersection - such as its cardinality, and are often employed in an unbalanced setting where one party has more data than the other. Existing protocols are either computationally inefficient or require extensive server-client communication on the order of the larger set. We introduce Practically Efficient PSI or PEPSI, a non-interactive solution where only the client sends its encrypted data. PEPSI can process an intersection of 1024 client items with a million server items in under a second, using less than 5 MB of communication. Our work is over 4 orders of magnitude faster than an existing non-interactive circuit PSI protocol and requires only 10% of the communication. It is also up to 20 times faster than the work of Ion et al., which computes a limited set of functions and has communication costs proportional to the larger set. Our work is the first to demonstrate that non-interactive circuit PSI can be practically applied in an unbalanced setting