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Objective: This study addresses the significant challenges posed by emerging SARS-CoV-2 variants, particularly in developing diagnostics and therapeutics. Drug repurposing is investigated by identifying critical regulatory proteins impacted by the virus, providing rapid and effective therapeutic solutions for better disease management., Materials and Methods: We employed a comprehensive approach combining mathematical modeling and efficient parameter estimation to study the transient responses of regulatory proteins in both normal and virus-infected cells. Proportional-integral-derivative (PID) controllers were used to pinpoint specific protein targets for therapeutic intervention. Additionally, advanced deep learning models and molecular docking techniques were applied to analyze drug-target and drug-drug interactions, ensuring both efficacy and safety of the proposed treatments. This approach was applied to a case study focused on the cytokine storm in COVID-19, centering on Angiotensin-converting enzyme 2 (ACE2), which plays a key role in SARS-CoV-2 infection., Results: Our findings suggest that activating ACE2 presents a promising therapeutic strategy, whereas inhibiting AT1R seems less effective. Deep learning models, combined with molecular docking, identified Lomefloxacin and Fostamatinib as stable drugs with no significant thermodynamic interactions, suggesting their safe concurrent use in managing COVID-19-induced cytokine storms., Discussion: The results highlight the potential of ACE2 activation in mitigating lung injury and severe inflammation caused by SARS-CoV-2. This integrated approach accelerates the identification of safe and effective treatment options for emerging viral variants., Conclusion: This framework provides an efficient method for identifying critical regulatory proteins and advancing drug repurposing, contributing to the rapid development of therapeutic strategies for COVID-19 and future global pandemics., (© The Author(s) 2025. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

To measure the life quality, clinical-functional outcomes of a patient who had undergone acute reconstruction of radio scapho capitate (RSC), radio lunate (RLL) ligaments, using brachiorradialis tendon in treatment of radiocarpal fracture dislocation. 21-years-old, man with radiocarpal fracture dislocation in his left wrist, after motorcycle accident. Percutaneous screw fixation of the distal radius and acute reconstruction of the RSC and RLL was performed, assisted by arthroscopy. One year later, the patient experienced good evaluation. ROM was full, grip strength was 96% compared with the unaffected side were obtained. Wrist radiographic aspects showed fracture healed and radiocarpal joint congruency. Good stability and joint congruency of the radiocarpal joint were obtained and improving the life quality of that patient. Radiocarpal fracture dislocation management is difficult and complicated. There is no consensus. As there is still a lack of long-term results, the indications for surgery, and options, type of the intervention have been a matter of controversy in the literature. Would radiocarpal (RC) joint be stable when reconstruction of the radiocarpal ligaments, using brachiorradialis tendon was obtained? Is it possible to reduce and to maintain stable radiocarpal joint with this technique? The clinical relevance of this work is our suggestion of reconstruction of the RC ligament to improve this treatment. We believe that this will maintain a stable and functional wrist. We agree that the best time to perform corrections is as soon as possible and we prefer to reconstruct the RC ligament with suture or temporary or permanent radioscapholunate arthrodesis., Competing Interests: Conflito de Interesses Os autores não têm conflitos de interesses a declarar., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution 4.0 International License, permitting copying and reproduction so long as the original work is given appropriate credit ( https://creativecommons.org/licenses/by/4.0/ ).)

Wrist and hand arthroscopy, despite being an old tool, has gained popularity and advanced in assisting in the treatment of various injuries and conditions in the region in recent years. Dorsal, volar, ulnar, and radial accessory portals are used to reach all points of the carpal and hand joints. The minimal tissue damage, lesser injury to the capsule and its mechanoreceptors, the assessment of injuries associated with the reason for surgery, and aesthetically more favorable scars have attracted many doctors and their patients. As a result, there has been an increase in publications and diversifications of arthroscopic techniques. The aim of this update article is to present the advances and the evidence available in the literature to assist readers in their decision on which technique to use in the treatment of wrist and hand conditions., Competing Interests: Conflito de Interesses Os autores declaram não haver conflito de interesses., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution 4.0 International License, permitting copying and reproduction so long as the original work is given appropriate credit ( https://creativecommons.org/licenses/by/4.0/ ).)

A turning point in cancer research is the introduction of massively parallel sequencing technology which greatly reduced the cost and time for genome sequencing. This enhanced the scope for detecting and analyzing the role of structural alterations in cancer. However, certain bias exists in NGS-based approaches, which badly affects the CNV identification process. Moreover, DNA repeats existing in CNV regions need special attention as they will degrade the performance of majority of the existing CNV detection tools, even after applying generalized bias correction method. This motivated this work, where a novel method has been designed to address the issue of DNA repeats and thereby mappability bias existing in regions of CNV. The method consists of three phases, where the first phase computes the alignment information of uniquely mapped DNA reads, considering the base quality and base mismatch parameters at nucleotide level precision. The second and the third phase use a novel approach to allocate the non-uniquely mapped reads to an optimal region of the DNA repeats based on a probabilistic membership model. The proposed method is capable of identifying CNVs present in coding, as well as non-coding region of the DNA, and is also capable of detecting CNVs existing in DNA repeat regions. The methodology achieves a sensitivity greater than [Formula: see text] during the performed simulations, and on real data, the detected variants are validated with the database of genomic variants, where the percentage overlap is also greater than 95%, and has achieved much better breakpoint prediction, as compared with other popular bias correction CNV detection methods.

The revolution in sequencing technologies has enabled human genomes to be sequenced at a very low cost and time leading to exponential growth in the availability of whole-genome sequences. However, the complete understanding of our genome and its association with cancer is a far way to go. Researchers are striving hard to detect new variants and find their association with diseases, which further gives rise to the need for aggregation of this Big Data into a common standard scalable platform. In this work, a database named Enlightenment has been implemented which makes the availability of genomic data integrated from eight public databases, and DNA sequencing profiles of H. sapiens in a single platform. Annotated results with respect to cancer specific biomarkers, pharmacogenetic biomarkers and its association with variability in drug response, and DNA profiles along with novel copy number variants are computed and stored, which are accessible through a web interface. In order to overcome the challenge of storage and processing of NGS technology-based whole-genome DNA sequences, Enlightenment has been extended and deployed to a flexible and horizontally scalable database HBase, which is distributed over a hadoop cluster, which would enable the integration of other omics data into the database for enlightening the path towards eradication of cancer.

Objective  The endoscopic release of the ulnar nerve reproduces a simple ( in situ ) procedure with smaller incisions, less soft tissue damage, and higher preservation of nerve vascularization. Endoscopy allows the clear visualization of the entire path of the nerve and surrounding noble structures. Moreover, it reveals any signs of compression and allows a safe release of 10 cm distally or proximally to the medial epicondyle. Methods  A retrospective survey revealed that 15 subjects (1 with a bilateral injury) underwent an ulnar nerve compression release at the elbow using the endoscopic technique with Agee (Micro-Aire Sugical Instruments, Charlottesville, VA, EUA) equipment from January 2016 to January 2020. Results  Symptoms of ulnar nerve compression improved in all patients; on average, they resumed their work activities in 26.5 days. There was no recurrence or need for another procedure. In addition, there were no severe procedure-related complications, such as infection and nerve or vascular injury. One patient had transient paresthesia of the sensory branches to the forearm, with complete functional recovery in 8 weeks. Conclusion  Our study shows that the endoscopic release of the ulnar nerve at the elbow with the Agee equipment is a safe, reliable technique with good outcomes., Competing Interests: Conflito de Interesses Os autores declaram não haver conflito de interesses., (Sociedade Brasileira de Ortopedia e Traumatologia. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

Background  Ulnarly sided wrist pain is a common and challenging symptom. Arthroscopy has become a safe and effective tool for the correct diagnosis and treatment, proving to be better than all other clinical and imaging diagnostic methods. Some tests have been described for the diagnosis of triangular fibrocartilage (TFC) lesions, such as the trampoline test for peripheral lesions and the hook, ghost, and suction tests for foveal detachments. In tears at the disc level, when they affect all layers of the TFC (complete lesion) at the same point, testing with the probe will usually suffice for the diagnosis. However, in some apparently partial lesions, the probe cannot pass through all layers because the proximal and distal sites of the lesion are not aligned. There has been no arthroscopic test described for such cases. Case Description  We describe a simple and practical test that we have called the "bubble test" in a typical case to diagnose TFC central injuries, aiming to discriminate partial from complete lesions, which are eventually hard to differentiate through direct vision and arthroscopic probing, leading to a direct influence onto the treatment. The bubble test is performed with external compression of the distal radioulnar joint (DRUJ) aspect, with the thumb on the back of the DRUJ and the index and middle fingers onto the volar aspect. The abrupt compression of this region causes the passage of air mixed with synovial fluid from the DRUJ to the radiocarpal joint, generating bubble formation. Clinical Relevance  The bubble test should correlate to physical examination and imaging (magnetic resonance imaging [MRI]) findings and is particularly useful in central and degenerative (Type II) TFC lesions in patients complaining of chronic pain on the ulnar region of the wrist, with no history of trauma and with inconclusive MRI findings. Once the diagnosis is confirmed, arthroscopic treatment consists of wide debridement of the lesion with resection of the injured tissue and the local inflammatory reaction. Thus, it is essential for the correct treatment to define the exact location of the lesion and to know whether the disc injury is complete., Competing Interests: Conflict of Interest None declared., (Thieme. All rights reserved.)

Multi-omics studies have enabled us to understand the mechanistic drivers behind complex disease states and progressions, thereby providing novel and actionable biological insights into health status. However, integrating data from multiple modalities is challenging due to high dimensionality and diverse nature of data, and noise associated with each platform. Sparsity in data, non-overlapping features and technical batch effects make the task of learning more complicated. Conventional machine learning (ML) tools are not quite effective against such data integration hazards due to their simplistic nature with less capacity. In addition, existing methods for single cell multi-omics integration are computationally expensive. Therefore, in this work, we have introduced a novel Unsupervised neural network for single cell Multi-omics INTegration (UMINT). UMINT serves as a promising model for integrating variable number of single cell omics layers with high dimensions. It has a light-weight architecture with substantially reduced number of parameters. The proposed model is capable of learning a latent low-dimensional embedding that can extract useful features from the data facilitating further downstream analyses. UMINT has been applied to integrate healthy and disease CITE-seq (paired RNA and surface proteins) datasets including a rare disease Mucosa-Associated Lymphoid Tissue (MALT) tumor. It has been benchmarked against existing state-of-the-art methods for single cell multi-omics integration. Furthermore, UMINT is capable of integrating paired single cell gene expression and ATAC-seq (Transposase-Accessible Chromatin) assays as well., Competing Interests: VD works as a Senior Research Scientist at Novo Nordisk A/S, Måløv. DS works as an Associate Data Scientist at Tatras Data Services Pvt. Ltd. None of them has received any funds for this work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Maitra, Seal, Das and De.)

Raphidascarid nematodes have been the focus of several studies, mainly due to the zoonotic potential of some species, even though the cases are underreported. Due to the difficulty in identifying their larvae, the use of diagnostic techniques involving morphological and molecular analyses has grown in the last 20 years. The present study had as objective the morphological and molecular characterization of the L3 larval types of Hysterothylacium collected in Pomatomus saltatrix and Pagrus pagrus from the Brazilian coast, close to the municipality of Santos, State of São Paulo. Twenty specimens of P. saltatrix were necropsied and Hysterothylacium type V (n = 257) and Hysterothylacium type X (n = 5) larvae were found. Five specimens of P. pagrus were necropsied and all were parasitized by Hysterothylacium type V larvae. The analyses showed a genetic proximity relationship between Hysterothylacium types V with other Hysterothylacium V and with H. deardorffoverstreetorum, although this is a species inquirenda. Haplotypes for Hysterothylacium type X found in the present study formed a monophyletic group with other Hysterothylacium X, H. amoyense, and H. zhoushanense. Through this study, new hosts and localities were registered for Hysterothylacium type V and Hysterothylacium type X.

Dimension reduction is one of the most sought-after strategies to cope with high-dimensional ever-expanding datasets. To address this, a novel deep-learning architecture has been designed with multiple deconstruction and single reconstruction layers for non-negative matrix factorization aimed at low-rank approximation. This design ensures that the reconstructed input matrix has a unique pair of factor matrices. The two-stage approach, namely, pretraining and stacking, aids in the robustness of the architecture. The sigmoid function has been adjusted in such a way that fulfils the non-negativity criteria and also helps to alleviate the data-loss problem. Xavier initialization technique aids in the solution of the exploding or vanishing gradient problem. The objective function involves regularizer that ensures the best possible approximation of the input matrix. The superior performance of MDSR-NMF, over six well-known dimension reduction methods, has been demonstrated extensively using five datasets for classification and clustering. Computational complexity and convergence analysis have also been presented to establish the model.

World is now experiencing a major health calamity due to the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus clade 2. The foremost challenge facing the scientific community is to explore the growth and transmission capability of the virus. Use of artificial intelligence (AI), such as deep learning, in (i) rapid disease detection from x-ray or computed tomography (CT) or high-resolution CT (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) forecasting the disease and psychological impact on the population from social networking data, and (iv) prediction of drug-protein interactions for repurposing the drugs, has attracted much attention. In the present study, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real-time polymerase chain reaction and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, prevent the spread of disease, and face mask detection are also discussed. We inspect how the virus transmits depending on different factors. We investigate the deep learning technique to assess the affinity of the most probable drugs to treat COVID-19. This article is categorized under:Application Areas > Health CareAlgorithmic Development > Biological Data MiningTechnologies > Machine Learning., Competing Interests: The authors have declared no conflicts of interest for this article., (© 2022 Wiley Periodicals LLC.)

Stochastic simulation algorithms are extensively used for exploring stochastic behavior of biochemical pathways/networks. Computational cost of these algorithms is high in simulating real biochemical systems due to their large size, complex structure and stiffness. In order to reduce the computational cost, several algorithms have been developed. It is observed that these algorithms are basically fast in simulating weakly coupled networks. In case of strongly coupled networks, they become slow as their computational cost become high in maintaining complex data structures. Here, we develop Block Search Stochastic Simulation Algorithm (BlSSSA). BlSSSA is not only fast in simulating weakly coupled networks but also fast in simulating strongly coupled and stiff networks. We compare its performance with other existing algorithms using two hypothetical networks, viz., linear chain and colloidal aggregation network, and three real biochemical networks, viz., B cell receptor signaling network, FceRI signaling network and a stiff 1,3-Butadiene Oxidation network. It has been shown that BlSSSA is faster than other algorithms considered in this study.

Identifying intragenic as well as intergenic sequences of the DNA, having structural alterations, is a significantly important research area, since this may be the root cause of many neurological and autoimmune diseases, including cancer. Working with whole genome NGS data has provided a new insight in this regard, but has lead to huge explosion of data that is growing exponentially. Hence, the challenges lie in efficient means of storage and processing this big data. In this study, we have developed a novel segmentation algorithm, called GenSeg, and its parallel MapReduce based algorithm, called MR-GenSeg, for detecting copy number variations. In order to annotate CNVs (variants), segments formed by GenSeg/MR-GenSeg have been represented in a novel way using a binary tree, where each node is a CNV event. GenSeg considers each position specific data of whole genome DNA sequence, so that precise identification of breakpoints is possible. GenSeg/MR-GenSeg has been compared with twelve popular CNV detection algorithms, where it has outperformed the others in terms of sensitivity, and has achieved a good F-score value. MR-GenSeg has excelled in terms of SpeedUp, when compared with these algorithms. The effect of CNVs on immunoglobulin (IG) genes has also been analysed in this study. Availability: The source codes are available at https://github.com/rituparna-sinha/MapReduce-GENSEG.

Objeticve  To compare the range of motion (ROM), return-to-work time, visual analogue score (VAS), disability of the arm, shoulder, and hand (QuickDASH), and radiographic outcomes of two methods of definitive internal fixation in active patients with boxer's fractures, operated in the first week. Methods  This was a prospective, randomized trial, in which 50 patients, with a mean age range of 18 to 40 years old, were randomized and treated to definitive intramedullary fixation using 2 headless screws ( n  = 20) or bouquet (2 or 3 Kirschner wires) ( n  = 20). The patients were assessed on return-to-work time, ROM, patient reported QuickDASH outcome, VAS, and radiographic evaluation at 6 months. Results  At 6 months, there were no differences between the two groups in terms of ROM, postoperative pain (VAS), or QuickDASH score. The overall complication rate was 4.76% in the screw group, compared with 5% in the bouquet-fixation group. Conclusions  In the treatment of the active patients with unstable boxer's fractures, headless screws and bouquet fixation proved to be a safe and reliable treatment. The outcomes were similar in both groups., Competing Interests: Conflito de Interesses Os autores não têm conflitos de interesses para declarar., (Sociedade Brasileira de Ortopedia e Traumatologia. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

In the freshwater ecosystems of Brazil can be found high biodiversity of fish, about 5160 species. However, the Jacaré-Pepira River, located in the state of São Paulo, Brazil, presents a diversity of fish still to be explored in ichthyological studies. Metazoan parasites of Pimelodus maculatus and Rhamdia quelen were qualitatively and quantitatively diagnosed. Ten species of parasites (Demidospermus sp., D. majusculus, D. bidiverticulatum, D. paravalenciennesi, Ameloblastella paranaensis, Scleroductus sp., Riggia sp., Austrodiplostomum compactum, Helobdella sp. and Neochinorhynchus pimelodi) were collected in P. maculatus and eight species of parasites (Aphanoblastella robustus, A. mastigatus, Phyllodistomum rhamdiae, Crocodilicola pseudostoma, Henneguya jundiai, Contracaecum sp., Rhabdochona sp. and Capillariidae gen. sp.) were collected in R. quelen. All parasites presented aggregate distribution. A significant correlation was observed in P. maculatus concerning the weight with the prevalence of ectoparasite D. majusculus; however, R. quelen showed a relation to the length and weight with the abundance of ectoparasite A. mastigatus and endoparasites. The parasitic community of P. maculatus and R. quelen was characterized by high diversity, high richness, and low uniformity.

Interaction among different pathways, such as metabolic, signaling and gene regulatory networks, of cellular system is responsible to maintain homeostasis in a mammalian cell. Malfunctioning of this cooperation may lead to many complex diseases, such as cancer and type 2 diabetes. Timescale differences among these pathways make their integration a daunting task. Metabolic, signaling and gene regulatory networks have three different timescales, such as, ultrafast, fast and slow respectively. The article deals with this problem by developing a support vector regression (SVR) based three timescale model with the application of genetic algorithm based nonlinear controller. The proposed model can successfully capture the nonlinear transient dynamics and regulations of such integrated biochemical pathway under consideration. Besides, the model is quite capable of predicting the effects of certain drug targets for many types of complex diseases. Here, energy and cell proliferation management of mammalian cancer cells have been explored and analyzed with the help of the proposed novel approach. Previous investigations including in silico / in vivo / in vitro experiments have validated the results (the regulations of glucose transporter 1 (glut1), hexokinase (HK), and hypoxia-inducible factor-1 α (HIF-1 α ) among others, and the switching of pyruvate kinase (M2 isoform) between dimer and tetramer) generated by this model proving its effectiveness. Subsequently, the model predicts the effects of six selected drug targets, such as, the deactivation of transketolase and glucose-6-phosphate isomerase among others, in the case of mammalian malignant cells in terms of growth, proliferation, fermentation, and energy supply in the form of adenosine triphosphate (ATP)., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 The Authors.)

Synostosis is a generic term to indicate the union of two originally separated bones. At the elbow, humeroradial or longitudinal synostosis causes significant disability, which varies depending on hand function, elbow positioning, adjacent joints mobility and contralateral limb function. It is estimated that, to date, a little more than 150 patients have been described with this deformity, which is more common in subjects with deficient ulnar formation or affected by conditions such as Antley-Bixler and Hermann syndromes. The lack of the elbow joint, with the formation of a longer bone due to humerus-radius fusion, results in stiffness. As such, it is assumed that fractures in this topography are not uncommon. However, since synostosis is rare, this lesion was only described twice in the literature. We report two patients with a fracture of the single bone formed by a humeroradial synostosis and Bayne type-IV ulnar formation failure. Both patients were treated surgically with success. We emphasize the need for adequate treatment to not compromise the daily activities of patients who are adapted to their deformity, thus avoiding worsening the function of a previously affected limb., Competing Interests: Conflito de Interesses Os autores declaram não haver nenhum conflito de interesses., (Sociedade Brasileira de Ortopedia e Traumatologia. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

The scope of this study is to analyze the relationship between self-perception of eating habits and observance of the Ten Steps to Adequate and Healthy Eating among university students in Porto Alegre/RS. An online questionnaire was applied to students at a private university in Porto Alegre. Personal information, anthropometric data and eating behavior of the participants were collected. Data were analyzed by frequency and proportion, and statistical associations using Pearson's Chi-square and the linear trend test, adopting a significance level of 5%, using version 23.0 of the SPSS statistical program. The sample consisted of 357 students, 61.3% of which were female, between 20 and 29 years of age (56%). A total of 34.2% of the students were overweight and 55.5% did not consider they had healthy eating habits. Low observance was observed in eight of the Ten Steps to Adequate and Healthy Eating A review of healthy eating revealed an inverse relationship with observance of the guideline steps, since only 3 steps were followed by more than 60% of the students who evaluated their own eating habits positively. This result suggests that this population may have a distorted view of their own eating habits and need to be enlightened regarding adequate and healthy eating.

Methamidophos (MET) is a pesticide that has toxic properties, including effects on fertility. This study aimed to assess the joint action of treatment time and exposure to methamidophos on the male reproductive system. MET was orally administered to adult male Swiss mice at a dose of 0.004 mg.kg -1 for 15 and 50 consecutive days. The following parameters were evaluated: weight of reproductive organs, spermatogenesis, sperm and Sertoli cell count, daily sperm production and sperm transit time. Short-term exposure to methamidophos induced a decrease in epididymal weight. The frequency of stages V-VI of spermatogenesis increased and the frequency of stage IX decreased. In the epididymis, sperm transit time (caput/corpus) was reduced and the relative sperm number (cauda) increased. Long-term exposure induced an increase in the frequencies of stages I-IV and V-VI and decreased the stages VII-VIII and IX. The number of Sertoli cells with evident nucleoli was reduced in both exposures. These results confirm the reproductive toxicity of MET., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish Academy of Sciences in Olsztyn. Published by Elsevier B.V. All rights reserved.)

Background: Metabolic engineering aims at contriving microbes as biocatalysts for enhanced and cost-effective production of countless secondary metabolites. These secondary metabolites can be treated as the resources of industrial chemicals, pharmaceuticals and fuels. Plants are also crucial targets for metabolic engineers to produce necessary secondary metabolites. Metabolic engineering of both microorganism and plants also contributes towards drug discovery. In order to implement advanced metabolic engineering techniques efficiently, metabolic engineers should have detailed knowledge about cell physiology and metabolism. Principle behind methodologies: Genome-scale mathematical models of integrated metabolic, signal transduction, gene regulatory and protein-protein interaction networks along with experimental validation can provide such knowledge in this context. Incorporation of omics data into these models is crucial in the case of drug discovery. Inverse metabolic engineering and metabolic control analysis (MCA) can help in developing such models. Artificial intelligence methodology can also be applied for efficient and accurate metabolic engineering., Conclusion: In this review, we discuss, at the beginning, the perspectives of metabolic engineering and its application on microorganism and plant leading to drug discovery. At the end, we elaborate why inverse metabolic engineering and MCA are closely related to modern metabolic engineering. In addition, some crucial steps ensuring efficient and optimal metabolic engineering strategies have been discussed. Moreover, we explore the use of genomics data for the activation of silent metabolic clusters and how it can be integrated with metabolic engineering. Finally, we exhibit a few applications of artificial intelligence to metabolic engineering., Competing Interests: Declaration of Competing Interest The authors declare that they do not have any financial or nonfinancial conflict of interests., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Gene expression analysis plays a significant role for providing molecular insights in cancer. Various genetic and epigenetic factors (being dealt under multi-omics) affect gene expression giving rise to cancer phenotypes. A recent growth in understanding of multi-omics seems to provide a resource for integration in interdisciplinary biology since they altogether can draw the comprehensive picture of an organism's developmental and disease biology in cancers. Such large scale multi-omics data can be obtained from public consortium like The Cancer Genome Atlas (TCGA) and several other platforms. Integrating these multi-omics data from varied platforms is still challenging due to high noise and sensitivity of the platforms used. Currently, a robust integrative predictive model to estimate gene expression from these genetic and epigenetic data is lacking. In this study, we have developed a deep learning-based predictive model using Deep Denoising Auto-encoder (DDAE) and Multi-layer Perceptron (MLP) that can quantitatively capture how genetic and epigenetic alterations correlate with directionality of gene expression for liver hepatocellular carcinoma (LIHC). The DDAE used in the study has been trained to extract significant features from the input omics data to estimate the gene expression. These features have then been used for back-propagation learning by the multilayer perceptron for the task of regression and classification. We have benchmarked the proposed model against state-of-the-art regression models. Finally, the deep learning-based integration model has been evaluated for its disease classification capability, where an accuracy of 95.1% has been obtained., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Eighty-one Hoplias malabaricus specimens were collected between February 2014 and June 2016. A total of 29 species of metazoan parasites were found, 13 of which were identified as monogeneans, seven were digenean species, seven of which were nematodes, and two of which were from the subclass Hirudinea. The highest prevalence values ​​were presented by Contracaecum sp. and Tylodelphys sp. The highest mean abundance and mean intensity was recorded by Tylodelphys sp.; the values were ​​36.7 ± 61.8 and 55.65 ± 69.1, respectively. The abundance of the monogenean Urocleidoides cuiabai was found to be positively correlated with host weight. The abundance of Bucephalidae gen. sp. exhibited significant positive correlations with host weight and length. For Contracaecum sp., a significant negative correlation was found between its abundance and host length and weight. No significant differences between the diversity indexes (Margalef, Pielou and Shannon) of the parasites collected in the two points were found. The Sorensen similarity index, with a value of 0.82 between the two sampling points revealed that the parasitic diversity between them is similar. The findings from this study represent new records of occurrence of H. malabaricus, as well as of Urocleidoides margolisi, Scleroductus sp. and Helobdella sp.

Background: Intracranial arteriovenous malformations (AVMs) have been considered congenital. We present and discuss a case of a child who had no evidence of an AVM at 6 years of age when presenting with parenchymatous hemorrhage due to cavernous angioma and who developed the lesion during 10 years of follow-up., Case Description: A 6-year-old female presented with parenchymatous hemorrhage and was diagnosed with cavernous angioma of the right occipital lobe. She was treated with lesion removal and remained asymptomatic during the initial follow-up. At age 16, she presented to the emergency department with a new-onset headache. A new magnetic resonance imaging scan was performed and revealed an AVM in the right temporal lobe, which was confirmed with digital subtraction angiography. The AVM had not been present 10 years earlier, as seen on the previous digital subtraction angiography and magnetic resonance imaging examinations., Conclusions: On the basis of recent findings of de novo AVMs and on the current theory of a postnatal origin of AVMs, we propose that AVMs cannot always be considered congenital and that several factors can contribute to their pathogenesis., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The significance of metabolic pathway prediction is to envision the viable unknown transformations that can occur provided the appropriate enzymes are present. It can facilitate the prediction of the consequences of host-pathogen interactions. In this article, we have proposed a new algorithm Architectural Similarity-based Automated Pathway Prediction (ASAPP) to predict metabolic pathways based on the structural similarity among the metabolites. ASAPP takes two-dimensional structure and molecular weight of metabolites as input, and generates a list of probable transformations without the knowledge of any externally established reactions, with an accuracy of 85.09 percent. ASAPP has also been applied to predict the outcome of pathogen liberated toxins on the carbohydrate and lipid pathways of the hosts. We have analyzed the disruption of host pathways in the presence of toxins, and have found that some metabolites in Glycolysis and the TCA cycle have a high chance of being the breakpoints in the pathway. The tool is available at http://asapp.droppages.com/.

Obesity is characterized by a state of chronic, unresolved inflammation in insulin-targeted tissues. Obesity-induced inflammation causes accumulation of proinflammatory macrophages in adipose tissue and liver. Proinflammatory cytokines released from tissue macrophages inhibits insulin sensitivity. Obesity also leads to inflammation-induced endoplasmic reticulum (ER) stress and insulin resistance. In this scenario, based on the data (specifically patterns) generated by our in vivo experiments on both diet-induced obese (DIO) and normal chow diet (NCD) mice, we developed an in silico state space model to integrate ER stress and insulin signaling pathways. Computational results successfully followed the experimental results for both DIO and NCD conditions. Chromogranin A (CgA) peptide catestatin (CST: hCgA 352 - 372 ) improves obesity-induced hepatic insulin resistance by reducing inflammation and inhibiting proinflammatory macrophage infiltration. We reasoned that the anti-inflammatory effects of CST would alleviate ER stress. CST decreased obesity-induced ER dilation in hepatocytes and macrophages. On application of Proportional-Integral-Derivative (PID) controllers on the in silico model, we checked whether the reduction of phosphorylated PERK resulting in attenuation of ER stress, resembling CST effect, could enhance insulin sensitivity. The simulation results clearly pointed out that CST not only decreased ER stress but also enhanced insulin sensitivity in mammalian cells. In vivo experiment validated the simulation results by depicting that CST caused decrease in phosphorylation of UPR signaling molecules and increased phosphorylation of insulin signaling molecules. Besides simulation results predicted that enhancement of AKT phosphorylation helps in both overcoming ER stress and achieving insulin sensitivity. These effects of CST were verified in hepatocyte culture model., (© 2020 The Authors.)

A new species of Tereancistrum Kritsky, Thatcher & Kayton, 1980 collected of Prochilodus lineatus gills from the Batalha River, Tietê-Batalha basin, São Paulo State, Brazil is described. The new species can be distinguished from its congeners mainly by the configuration of the ventral bar, which has an anvil-shaped characteristic with corrugated anterior projection. Tereancistrum takemotoi n. sp. is morphologically similar to T. toksonum Lizama, Takemoto & Pavanelli, 2004 in terms of their dorsal bars (Y-shaped), their dorsal anchors with divergent roots (superficial and deep) wherein their deep root rather elongated, and by the fact that they both have the male copulatory organ counterclockwise. However, only T. takemotoi n. sp. presents the male copulatory organ with 2¼ rings and shows undulations in the anterior margin of the dorsal bar. These undulations are absent in T. toksonum (which only has 1¼ rings). This is the fourth Tereancistrum species described for P. lineatus and the first described for the region from the Tietê-Batalha basin.

Objectives  To describe the technique and results of the arthroscopic surgical treatment of volar ganglion cyst of the wrist. Materials and Methods  The present study comprised 21 patients submitted to the arthroscopic treatment of volar ganglion cysts of the wrist from January 2015 to May 2017, with a full evaluation for at least 6 months. The technique was indicated for patients presenting pain and functional impairment for more than four months, with no improvement with the conservative treatment, or for those with cosmetic complaints and cyst present for more than three months. Results  The mean age of the patients was 43.6 years; 16 (76%) patients were female, and 5 (24%) were male. The mean follow-up time from surgery to the final assessment was of 10.9 months. A total of 2 (9.6%) patients complained of mild pain after the procedure, and another patient presented slight motion restrictions. The 18 (90.4%) remaining patients reported cosmetic improvement, complete functional recovery, and pain improvement. There were no recurrences or infections. No patient required further surgery. Conclusions  The arthroscopic resection of volar ganglion cysts is a useful and safe technique. It is a minimally-invasive procedure, with low morbidity and very few complications, representing a good alternative to the open technique., Competing Interests: Conflito de Interesses Os autores declaram não haver conflito de interesses .

Background: Effector proteins of bacteria infect their hosts by specific dedicated machinery identified as secretion systems. Currently, no mechanism to identify the effector proteins based on their 3D structure has been reported in the literature. In order to identify effector proteins, extraction of features from their 3D structure is crucial. However, effector protein datasets are highly imbalanced. State-of-the-art oversampling algorithms are incapable of dealing with such datasets. They usually eliminate samples as noise. They do not ensure generation of synthetic samples strictly in the vicinity of the minority class samples. In effector protein datasets, deletion of any samples as noise would lead to loss of crucial information. Furthermore, generation of synthetic samples of the minority class in the vicinity of majority class samples would lead to an inept classifier., Method: In this paper, we introduce an algorithm called Cluster Quality based Non-Reductional (CQNR) oversampling technique. Its novelty lies in generating new samples proportional to the distribution of samples of the minority classes, without eliminating any sample as noise. Utilizing CQNR, we develop a novel Effector Protein Predictor based on the 3D (EPP3D) structure of proteins. EPP3D is trained on a feature set, balanced by CQNR, comprising 3D structure-based features, namely, convex hull layer count, surface atom composition, radius of gyration, packing density and compactness, derived from the 3D structure of the experimentally verified effector proteins., Result: Fscore and Gmean demonstrate that CQNR has outperformed some well-established oversampling methods by approximately 3-5%, with respect to classification accuracy, on five benchmark datasets and three other highly imbalanced synthetically generated datasets. Likewise, for classification of pathogenic effector proteins, a significant improvement of 7-9% in accuracy has been noticed, on the application of CQNR followed by EPP3D. Moreover, EPP3D has exhibited an improvement of 2-4% in classifying effector proteins based on their 3D structure compared to the classification of effector proteins based on their amino acid sequences. The software for CQNR and EPP3D are available at http://projectphd.droppages.com/CQNR.html., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Prediction of effector proteins is of paramount importance due to their crucial role as first-line invaders while establishing a pathogen-host interaction, often leading to infection of the host. Prediction of T6 effector proteins is a new challenge since the discovery of T6 Secretion System and the unique nature of the particular secretion system. In this paper, we have first designed a Python-based standalone tool, called PyPredT6, to predict T6 effector proteins. A total of 873 unique features has been extracted from the peptide and nucleotide sequences of the experimentally verified effector proteins. Based on these features and using machine learning algorithms, we have performed in silico prediction of T6 effector proteins in Vibrio cholerae and Yersinia pestis to establish the applicability of PyPredT6. PyPredT6 is available at http://projectphd.droppages.com/PyPredT6.html .

Cichla ocellaris is native to the Amazon region. It is popularly known as tucunaré and is widely used for human consumption. It is difficult to breed in captivity due to its highly predatory habits, it is considered symbolic of sport fishing in Brazil. This study aimed to make a qualitative and quantitative survey of helminth parasites of C. ocellaris. Thirty specimens from the Jacaré-Pepira River, located in the municipality of Ibitinga, in the interior of the state of São Paulo, were studied. The river is located 13 km from the urban area and at an altitude of approximately 600 m. A total of four taxa of metazoan parasites were collected and identified in Cestoda, Digenea, Monogenea and Nematoda. The cestoid Proteocephalus macrophallus presented the highest prevalence (63.3%) and had the greatest abundance and intensity, being found only in the intestine and stomach. The parasites found showed a significant positive correlation between the total body length of the hosts and the prevalence, as did the weight. This is the first study of helminth parasites of this host conducted in the Jacaré-Pepira River and the first record of a new location for P. macrophallus.

The human brain and its temporal behavior correlated with development, structure, and function is a complex natural system even for its own kind. Coding and automation are necessary for modeling, analyzing and understanding the 86.1 +/- 8.1 +/- billion neurons, an almost equal number of non-neuronal glial cells, and the neuronal networks of the human brain comprising about 100 trillion connections. 'Computational neuroscience' which is heavily dependent on biology, physics, mathematics and computation addresses such problems while the archival, retrieval and merging of the huge amount of generated data in the form of clinical records, scientific literature, and specialized databases are carried out by 'neuroinformatics' approaches. Neuroinformatics is thus an interface between computer science and experimental neuroscience. This article provides an introduction to computational neuroscience and neuroinformatics fields along with their state-ofthe- art tools, software, and resources. Furthermore, it describes a few innovative applications of these fields in predicting and detecting brain network organization, complex brain disorder diagnosis, large-scale 3D simulation of the brain, brain- computer, and brain-to-brain interfaces. It provides an integrated overview of the fields in a non-technical way, appropriate for broad general readership. Moreover, the article is an updated unified resource of the existing knowledge and sources for researchers stepping into these fields.

Objective: To describe the results of the surgical treatment of patients with congenital arthrogryposis with wrist deformity through biplanar carpal wedge osteotomy., Method: This study analyzed nine patients through a retrospective evaluation with severe deformity in flexion and ulnar deviation of the wrist in the period between January 2004 and December 2009. They were submitted to carpal osteotomy with a biplanar dorsal resection wedge, with a minimum evaluation of 48 months of postoperative evolution. In three patients the osteotomy was bilateral, totalling 12 cuffs analyzed. The indication for the technique described was deformity and stiffness for over six months, without improvement with the conservative treatment., Results: The mean age of the patients on the day of surgery was five years and eight months. The initial mean wrist mobility was 35°, and the joints presented a mean flexion of 72.5° in a resting position. Osteotomy union occurred in all patients at an average period of 5.7 weeks. The final position of the resting wrist was 12° of flexion and the mean mobility was 26.6°, slightly lower than preoperatively but in a much better position. No serious complications arising from surgery or in the immediate postoperative period were observed., Conclusions: Carpal osteotomy with biplanar dorsal resection wedge was useful and effective in helping to correct the deformities in flexion and ulnar deviation of the wrist, maintaining a reasonable mobility. It is a preservation surgery, which has low morbidity and avoids the progression of deformity and future degenerative changes.

The incidence and prevalence of nonalcoholic fatty liver disease (NAFLD) have been increasing to epidemic proportions around the world. NAFLD, a chronic liver disease that affects the nondrinkers, is mainly associated with steatohepatitis and cirrhosis. The progression of NAFLD associated with obesity increases the risk of liver cancer, a disease with poor outcomes and limited therapeutic options. In order to investigate the underlying cellular dynamics leading to NAFLD progression towards cancer on the onset of obesity, we have integrated human hepatocyte pathway with hypoxia-inducible factor1- α (HIF1- α ) signaling pathway using state space model based on classical control theory. Modified Michaelis-Menten equation and mass action law have been used to define flux vectors of the proposed model. We have incorporated feedback inhibition/activation and allosteric effects into the simulink-based model. The values of kinetic constants have been taken from the literature. It is found that on the onset of obesity, HIF1- α -induced proteins stabilize approximately 62 times that in the case of a normal cell. Consequently, the HIF1- α -induced proteins enhance the enzymatic activities of hexokinase (HK), phosphofructo kinase (PFK), lactate dehydrogenase (LDH), and pyruvate dehydrogenase (PDH), which induce Warburg effect promoting an environment suitable for cancer cells.

Massively parallel sequencing technique, introduced by NGS technology, has resulted in an exponential growth of sequencing data, with greatly reduced cost and increased throughput. This huge explosion of data has introduced new challenges in regard to its storage, integration, processing and analyses. In this paper, we have proposed a novel distributed model under Map-Reduce paradigm to address the NGS big data problem. The architecture of the model involves Map-Reduce based modularized approach involving 3 different phases that support various analytical pipelines. The first phase will generate detailed base level information of various individual genomes, by granulating the alignment data. The other 2 phases independently process this base level information in parallel. One of these 2 phases will provide an integrated DNA profile of multiple individuals, whereas the other phase will generate contigs with similar features in an individual. Each of these 2 phases will generate a repository of genomic information that will facilitate other analytical pipelines. A simulated and real experimental prototypes has been provided as results to show the effectiveness of the model and its superiority over a few existing popular models and tools. A detailed description of the scope of applications of this model is also included in this article.

The stochastic simulation algorithm (SSA) based modeling is a well recognized approach to predict the stochastic behavior of biological networks. The stochastic simulation of large complex biochemical networks is a challenge as it takes a large amount of time for simulation due to high update cost. In order to reduce the propensity update cost, we proposed two algorithms: slow update exact stochastic simulation algorithm (SUESSA) and slow update exact sorting stochastic simulation algorithm (SUESSSA). We applied cache-based linear search (CBLS) in these two algorithms for improving the search operation for finding reactions to be executed. Data structure used for incorporating CBLS is very simple and the cost of maintaining this during propensity update operation is very low. Hence, time taken during propensity updates, for simulating strongly coupled networks, is very fast; which leads to reduction of total simulation time. SUESSA and SUESSSA are not only restricted to elementary reactions, they support higher order reactions too. We used linear chain model and colloidal aggregation model to perform a comparative analysis of the performances of our methods with the existing algorithms. We also compared the performances of our methods with the existing ones, for large biochemical networks including B cell receptor and FcϵRI signaling networks., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background: Obesity is a medical condition that is known for increased body mass index (BMI). It is also associated with chronic low level inflammation. Obesity disrupts the immune-metabolic homeostasis by changing the secretion of adipocytes. This affects the end-organs, and gives rise to several diseases including type 2 diabetes, asthma, non-alcoholic fatty liver diseases and cancers. These diseases are known as co-morbid diseases. Several studies have explored the underlying molecular mechanisms of developing obesity associated comorbid diseases. To understand the development and progression of diseases associated with obesity, we need a detailed scenario of gene interactions and the distribution of the responsible genes in human system., Results: Obesity and Co-morbid Disease Database (OCDD) is designed for relating obesity and its co-morbid diseases using literature mining, and computational and systems biology approaches. OCDD is aimed to investigate the genes associated with comorbidity. Several existing databases have been used to extract molecular interactions and functional annotations of each gene. The degree of co-morbid associations has been measured and made available to the users. The database is available at http://www.isical.ac.in/~systemsbiology/OCDD/home.php., Conclusions: The main objective of the database is to derive the relations among the genes that are involved in both obesity and its co-morbid diseases. Functional annotation of common genes, gene interaction networks and key driver analyses have made the database a valuable and comprehensive resource for investigating the causal links between obesity and co-morbid diseases.

Why the intrinsically disordered regions evolve within human proteome has became an interesting question for a decade. Till date, it remains an unsolved yet an intriguing issue to investigate why some of the disordered regions evolve rapidly while the rest are highly conserved across mammalian species. Identifying the key biological factors, responsible for the variation in the conservation rate of different disordered regions within the human proteome, may revisit the above issue. We emphasized that among the other biological features (multifunctionality, gene essentiality, protein connectivity, number of unique domains, gene expression level and expression breadth) considered in our study, the number of unique protein domains acts as a strong determinant that negatively influences the conservation of disordered regions. In this context, we justified that proteins having a fewer types of domains preferably need to conserve their disordered regions to enhance their structural flexibility which in turn will facilitate their molecular interactions. In contrast, the selection pressure acting on the stretches of disordered regions is not so strong in the case of multi-domains proteins. Therefore, we reasoned that the presence of conserved disordered stretches may compensate the functions of multiple domains within a single domain protein. Interestingly, we noticed that the influence of the unique domain number and expression level acts differently on the evolution of disordered regions from that of well-structured ones.

The parasites are indicative of several biological aspects of their hosts, including their diet, migration, recruitment and phylogeny, but they can also be direct indicators of the environmental quality. Hoplosternum littorale is a fish that has a high commercial value in some South American countries. The fishes were collected from January to July 2012, in two locations of the Peixe River in the municipality of Anhembi, State of São Paulo, Brazil, which had different environmental and limnological characteristics (river mouth and Lagoa Cabeça de Boi). An amount of 30 fish specimens were captured in each location for the analysis of their parasitic fauna. Nine species of metazoan parasites were collected. Both Brillouin`s diversity index and Margalef`s richness index were greater in the Lagoa Cabeça de Boi. The ratio of heteroxenous and monoxenous parasite species richness (SH/SM) was higher in the Lagoa Cabeça de Boi. The results of the physicochemical analysis of the water showed that the mouth of the Peixe River can be considered an area that suffers more from anthropogenic actions than the Lagoa da Cabeça de Boi. Proteocephalus sp., Gyrodactylus sp., Scleroductus sp. and Capillaria (Neocapillaria) pterophylli are being registered for the first time in this host.

Background and Objective: Glycolytic activity during Crabtree effect is similar to that in tumor cells. Research regarding Crabtree effect is very much crucial., Methods: The mechanism of metabolic activities in glycolysis pathway and oxidative phosphorylation pathway in regards to Crabtree effect in Saccharomyces cerevisiae was studied in this paper. We also explored the effects of hexose phosphates in the activities of respiratory chain complexes (III and IV) in inhibition of respiration. Besides, the enhancement of fermentation in response to excess glucose concentration was studied. We discussed the significance of Crabtree effect in mammalian cancer in terms of Crabtree effect in a Crabtree positive organism, as it is similar to cancer metabolism in mammalian cells. We developed an in silico model of Crabtree effect., Results: A comparative study was performed with laboratory experiments regarding inhibitory role of fructose 1,6-bisphosphate on metabolic respiration. The model was simulated for different concentration levels of glucose and hexose phosphates using COPASI and SNOOPY tools., Conclusion: We have shown that a hike in glucose concentration increases ethanol concentration and leads glycolytic activity towards fermentation. This phenomenon occurs during Crabtree effect., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

Pollution in aquatic ecosystems due to negative human activities remains a problem in both freshwater and marine environments and is an ongoing subject of research. Several studies have shown that some fish parasites can be used as a tool for biomonitoring because they demonstrate higher metal accumulation capacity compared to their host tissues. However, compared to acanthocephalans, information regarding the absorption mechanisms and accumulation rates in nematodes is relatively limited. Here, we evaluated the potential of larvae Contracaecum sp. (L3) as indicators of contamination by metals by analyzing thirteen element concentrations: magnesium (Mg), aluminum (Al), titanium (Ti), chromium (Cr), manganese (Mn), iron (Fe), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), barium (Ba), and lead (Pb) in the parasites and host Acestrorhynchus lacustris, using inductively coupled plasma mass spectrometry. Twelve of the thirteen analyzed elements were detected in at least 2-fold higher concentrations (e.g. Ni) and were up to approximately 50-fold higher (e.g. Pb) in parasites than in host tissues, including elements known for their high toxicity (As, Cd, Pb) and those considered to be essential (Cu and Zn). Our results suggest that Contracaecum sp. larvae can be used as bioindicators of metal contamination because even in early stages of development, numerous essential and non-essential elements were accumulated, making this system a useful tool for monitoring polluted environments., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Obesity, characterized by chronic activation of inflammatory pathways, is a critical factor contributing to insulin resistance (IR) and type 2 diabetes (T2D). Free fatty acids (FFAs) are increased in obesity and are implicated as proximate causes of IR and induction of inflammatory signaling in adipose, liver, muscle, and pancreas. Cells of the innate immune system produce cytokines, and other factors that affect insulin signaling and result in the development of IR. In the lean state, adipose tissue is populated by adipose tissue macrophage of the anti-inflammatory M2 type (ATM2) and natural killer (NK) cells; this maintains the insulin-sensitive phenotype because ATM2 cells secrete IL10. In contrast, obesity induces lipolysis and release of pro-inflammatory FFAs and factors, such as chemokine (C-C motif) ligand 2 (CCL2) and tumor necrosis factor alpha (TNF-α), which recruit blood monocytes in adipose tissue, where they are converted to macrophages of the highly pro-inflammatory M1-type (ATM1). Activated ATM1 produce large amounts of pro-inflammatory mediators such as TNF-α, interleukin-1β, IL-6, leukotriene B4, nitric oxide (NO), and resistin that work in a paracrine fashion and cause IR in adipose tissue. In the liver, both pro-inflammatory Kupffer cells (M1-KCs) and recruited hepatic macrophages (Ly6C high ) contribute to decreased hepatic insulin sensitivity. The present mini-review will update the bidirectional interaction between the immune system and obesity-induced changes in metabolism in adipose tissue and liver and the metabolic consequences thereof.

The use of medications for the treatment of dyslipidemia is relevant in the control of cardiovascular disease. This article aims to analyze the prevalence, the use and the participation of the public sector in the supply of medication for adults aged 40 years and above using pharmacotherapy for dyslipidemia control living in a city in the southern region of Brazil. A cross-sectional, population-based study was conducted. Household interviews were staged with 1180 individuals aged over 40 living in Cambé, State of Paraná, of which 967 took laboratory examinations. The prevalence of dyslipidemia was 69.2%, of which 16.1% were taking medication. Among individuals undergoing treatment for dyslipidemia, 22.2% had adequate test results. Lipid-lowering medication used were simvastatin (81.5%) and bezafibrate (6.5%), mainly obtained by direct payment to private pharmacies and drug stores (52.2%) and NHS services (33.6%). A high prevalence of dyslipidemias was observed in population terms, together with a low level of dyslipidemia control and low participation of the public sector regarding the supply of medication compared to acquisition through direct payment for medication in private pharmacies. These results suggest a limited range of public policy for control of dyslipidemia.

Competing Interests: The authors have no conflicts of interest to declare.

The research on host-pathogen interactions is an ever-emerging and evolving field. Every other day a new pathogen gets discovered, along with comes the challenge of its prevention and cure. As the intelligent human always vies for prevention, which is better than cure, understanding the mechanisms of host-pathogen interactions gets prior importance. There are many mechanisms involved from the pathogen as well as the host sides while an interaction happens. It is a vis-a-vis fight of the counter genes and proteins from both sides. Who wins depends on whether a host gets an infection or not. Moreover, a higher level of complexity arises when the pathogens evolve and become resistant to a host's defense mechanisms. Such pathogens pose serious challenges for treatment. The entire human population is in danger of such long-lasting persistent infections. Some of these infections even increase the rate of mortality. Hence there is an immediate emergency to understand how the pathogens interact with their host for successful invasion. It may lead to discovery of appropriate preventive measures, and the development of rational therapeutic measures and medication against such infections and diseases. This review, a state-of-the-art updated scenario of host-pathogen interaction research, has been done by keeping in mind this urgency. It covers the biological and computational aspects of host-pathogen interactions, classification of the methods by which the pathogens interact with their hosts, different machine learning techniques for prediction of host-pathogen interactions, and future scopes of this research field.

An interaction between a pair of proteins unique for a particular tissue is denoted as a tissue-specific interaction (TSI). Tissue-specific (TS) proteins always perform TSIs with a limited number of interacting partners. However, it has been claimed that housekeeping (HK) proteins frequently take part in TSIs. This is actually an unusual phenomenon. How a single HK protein mediates TSIs - remains an interesting yet an unsolved question. We have hypothesized that HK proteins have attained a high degree of structural flexibility to modulate TSIs efficiently. We have observed that HK proteins are selected to be intrinsically disordered compared to TS proteins. Therefore, the purposeful adaptation of structural disorder brings out special advantages for HK proteins compared to TS proteins. We have demonstrated that TSIs may play vital roles in shaping the molecular adaptation of disordered regions within HK proteins. We also have noticed that HK proteins, mediating a huge number of TSIs, have a greater portion of their interacting interfaces overlapped with the adjacent disordered segment. Moreover, these HK proteins, mediating TSIs, preferably adapt single domain (SD). We have concluded that HK proteins adapt a high degree of structural flexibility to mediate TSIs. Besides, having a SD along with structural flexibility is more economic than maintaining multiple domains with a rigid structure. This assists them in attaining various structural conformations upon binding to their partners, thereby designing an economically optimum molecular system.

Background: Wnt signal transduction pathway (Wnt STP) is a crucial intracellular pathway mainly due to its participation in important biological processes, functions, and diseases, i.e., embryonic development, stem-cell management, and human cancers among others. This is why Wnt STP is one of the highest researched signal transduction pathways. Study and analysis of its origin, expansion and gradual development to the present state as found in humans is one aspect of Wnt research. The pattern of development and evolution of the Wnt STP among various species is not clear till date. A phylogenetic tree created from Wnt STPs of multiple species may address this issue., Results: In this respect, we construct a phylogenetic tree from modules of Wnt STPs of diverse species. We term it as the 'Module Tree'. A module is nothing but a self-sufficient minimally-dependent subset of the original Wnt STP. Authenticity of the module tree is tested by comparing it with the two reference trees., Conclusions: The module tree performs better than an alternative phylogenetic tree constructed from pathway topology of Wnt STPs. Moreover, an evolutionary emergence pattern of the Wnt gene family is created and the module tree is tallied with it to showcase the significant resemblances.

Dynamics of large nonlinear complex systems, like metabolic networks, depend on several parameters. A metabolic pathway may switch to another pathway in accordance with the current state of parameters in both normal and cancer cells. Here, most of the parameter values are unknown to us. A fuzzy logic controller (FLC) has been developed here for the purpose of modeling metabolic networks by approximating the reasons for the behaviour of a system and applying expert knowledge to track switching between metabolic pathways. The simulation results can track the switching between glycolysis and gluconeogenesis, as well as glycolysis and pentose phosphate pathways (PPP) in normal cells. Unlike normal cells, pyruvate kinase (M2 isoform) (PKM2) switches alternatively between its two oligomeric forms, i.e. an active tetramer and a relatively low activity dimer, in cancer cells. Besides, there is a coordination among PKM2 switching and enzymes catalyzing PPP. These phenomena help cancer cells to maintain their high energy demand and macromolecular synthesis. However, the reduction of initial adenosine triphosphate (ATP) to a very low concentration, decreasing initial glucose uptake, destroying coordination between glycolysis and PPP, and replacement of PKM2 by its relatively inactive oligomeric form (dimer) or inhibition of the translation of PKM2 may destabilize the mutated control mechanism of the mammalian central carbon metabolic (CCM) pathway in cancer cells. The performance of the model is compared appropriately with some existing ones.

Purified Shilajit, an Ayurvedic rasayana, was evaluated in healthy volunteers of age between 45 and 55 years for its effect on male androgenic hormone viz. testosterone in a randomised, double-blind, placebo-controlled clinical study at a dose of 250 mg twice a day. Treatment with Shilajit for consecutive 90 days revealed that it has significantly (P < 0.05) increased total testosterone, free testosterone and dehydroepiandrosterone (DHEAS) compared with placebo. Gonadotropic hormones (LH and FSH) levels were well maintained., (© 2015 The Authors. Andrologia Published by Blackwell Verlag GmbH.)