MPTherm: database for membrane protein thermodynamics for understanding folding and stability.

The functions of membrane proteins (MPs) are attributed to their structure and stability. Factors influencing the stability of MPs differ from globular proteins due to the presence of membrane spanning regions. Thermodynamic data of MPs aid to understand the relationship among their structure, stability and function. Although a wealth of experimental data on thermodynamics of MPs are reported in the literature, there is no database available explicitly for MPs. In this work, we have developed a database for MP thermodynamics, MPTherm, which contains more than 7000 thermodynamic data from about 320 MPs. Each entry contains protein sequence and structural information, membrane topology, experimental conditions, thermodynamic parameters such as melting temperature, free energy, enthalpy etc. and literature information. MPTherm assists users to retrieve the data by using different search and display options. We have also provided the sequence and structure visualization as well as cross-links to UniProt and PDB databases. MPTherm database is freely available at http://www.iitm.ac.in/bioinfo/mptherm/. It is implemented in HTML, PHP, MySQL and JavaScript, and supports the latest versions of major browsers, such as Firefox, Chrome and Opera. MPTherm would serve as an effective resource for understanding the stability of MPs, development of prediction tools and identifying drug targets for diseases associated with MPs.

Atrial fibrillation and preexcitation - A licence to kill.

Atrial fibrillation becomes a potentially lethal arrhythmia in the presence of preexcitation because the rapid ventricular activation can result in ventricular fibrillation. Fortunately, radiofrequency ablation is an effective treatment for these patients. Specific points of interest regarding this association are the mechanism of increased incidence of atrial fibrillation and the current management of patients presenting in atrial fibrillation. These are discussed in this editorial.

Statistical analysis of disease-causing and neutral mutations in human membrane proteins.

Mutations in transmembrane proteins (TMPs) have diverse effects on their structure and functions, which may lead to various diseases. In this present study, we have investigated variations in human membrane proteins and found that negatively charged to positively charged/polar and nonpolar to nonpolar changes are dominant in disease-causing and neutral mutations, respectively. Further, we analyzed the top 10 preferred mutations in 14 different disease classes and found that each class has at least two Arg mutations. Moreover, in cardiovascular diseases and congenital disorders of metabolism, Cys mutations occur more frequently in single-pass proteins, whereas Arg and nonpolar residues are more frequently substituted in multi-pass membrane proteins. The immune system diseases are enriched in C → R and C → Y mutations in inside and outside regions. On the other hand, in the membrane region, E → K and R → Q mutations are prevalent. The comparison of mutations in topologically similar regions of globular and membrane proteins showed that Ser and Thr mutations cause deleterious effects in membrane regions, whereas Cys and charged residues, Asp and Arg are prevalent in the buried regions of globular proteins. Our comprehensive analysis of disease-associated mutations in transmembrane proteins will be useful for developing prediction tools.

MutHTP: mutations in human transmembrane proteins.

Motivation: Existing sources of experimental mutation data do not consider the structural environment of amino acid substitutions and distinguish between soluble and membrane proteins. They also suffer from a number of further limitations, including data redundancy, lack of disease classification, incompatible information content, and ambiguous annotations (e.g. the same mutation being annotated as disease and benign). Results: We have developed a novel database, MutHTP, which contains information on 183 395 disease-associated and 17 827 neutral mutations in human transmembrane proteins. For each mutation site MutHTP provides a description of its location with respect to the membrane protein topology, structural environment (if available) and functional features. Comprehensive visualization, search, display and download options are available. Availability and implementation: The database is publicly available at http://www.iitm.ac.in/bioinfo/MutHTP/. The website is implemented using HTML, PHP and javascript and supports recent versions of all major browsers, such as Firefox, Chrome and Opera. Supplementary information: Supplementary data are available at Bioinformatics online.

Exploring preferred amino acid mutations in cancer genes: Applications to identify potential drug targets.

Somatic mutations developed with missense, silent, insertions and deletions have varying effects on the resulting protein and are one of the important reasons for cancer development. In this study, we have systematically analysed the effect of these mutations at protein level in 41 different cancer types from COSMIC database on different perspectives: (i) Preference of residues at the mutant positions, (ii) probability of substitutions, (iii) influence of neighbouring residues in driver and passenger mutations, (iv) distribution of driver and passenger mutations around hotspot site in five typical genes and (v) distribution of silent and missense substitutions. We observed that R→H substitution is dominant in drivers followed by R→Q and R→C whereas E→K has the highest preference in passenger mutations. A set of 17 mutations including R→Y, W→A and V→R are specific to driver mutations and 31 preferred substitutions are observed only in passenger mutations. These frequencies of driver mutations vary across different cancer types and are selective to specific tissues. Further, driver missense mutations are mainly surrounded with silent driver mutations whereas the passenger missense mutations are surrounded with silent passenger mutations. This study reveals the variation of mutations at protein level in different cancer types and their preferences in cancer genes and provides new insights for understanding cancer mutations and drug development.

Prediction of protein disorder on amino acid substitutions.

Intrinsically disordered regions of proteins are known to have many functional roles in cell signaling and regulatory pathways. The altered expression of these proteins due to mutations is associated with various diseases. Currently, most of the available methods focus on predicting the disordered proteins or the disordered regions in a protein. On the other hand, methods developed for predicting protein disorder on mutation showed a poor performance with a maximum accuracy of 70%. Hence, in this work, we have developed a novel method to classify the disorder-related amino acid substitutions using amino acid properties, substitution matrices, and the effect of neighboring residues that showed an accuracy of 90.0% with a sensitivity and specificity of 94.9 and 80.6%, respectively, in 10-fold cross-validation. The method was evaluated with a test set of 20% data using 10 iterations, which showed an average accuracy of 88.9%. Furthermore, we systematically analyzed the features responsible for the better performance of our method and observed that neighboring residues play an important role in defining the disorder of a given residue in a protein sequence. We have developed a prediction server to identify disorder-related mutations, and it is available at http://www.iitm.ac.in/bioinfo/DIM_Pred/.

Ligamentous Augmentation to Prevent Proximal Junctional Kyphosis and Failure: A Biomechanical Cadaveric Study.

STUDY DESIGN: Biomechanical cadaveric study (level V). OBJECTIVE: To evaluate the effectiveness of polyethylene bands looped around the supra-adjacent spinous process (SP) or spinal lamina (SL) in providing strength to the cephalad unfused segment and reducing junctional stress. BACKGROUND: Proximal junctional kyphosis (PJK) is a pathologic kyphotic deformity adjacent to posterior spinal instrumentation after fusion constructs. Recent studies demonstrate a mismatch in stiffness between the instrumented construct and nonfused adjacent levels to be a causative factor in the development of PJK and proximal junction failure. To our knowledge, no biomechanical studies have addressed the effect of different methods of polyethylene band placement at the proximal junction. MATERIALS AND METHODS: Twelve fresh frozen cadavers were divided into 3 groups of 4: pedicle screw-based instrumentation from T10 to L5 ("control"), T10-L5 instrumentation with a polyethylene band to the T9 "SP," T10-L5 instrumentation with 2 polyethylene bands to the T9 "SL." Specimens were tested with an eccentric (10 mm anterior) load at 5 mm/min for 15 mm or until failure occurred. Failure was defined by the inflection point on the load versus deformation curves. Linear regression was utilized to evaluate the effect of augmentation on the load-to-failure. Significance was set at 0.05. RESULTS: Fractures occurred in all specimens tested. The mean peak load to failure was 2148 N (974-3322) for the SP group, and 1248 N (742-1754) for the control group (P > 0.05) and 1390 N (1080-2004) for the SL group. No difference existed between the control group and the SP group in terms of fracture level (P > 0.05). Net kyphotic angulation shows no differences among these 3 groups (P > 0.05). CONCLUSION: Although statistical significance was not achieved, ligament augmentation to the SP increased mean peak load-to-failure in a cadaveric PJK model.

Early, reliable, utilitarian predictive factors for fat embolism syndrome in polytrauma patients.

BACKGROUND: Fat embolism is one of the apocalyptic pulmonary complications following high energy trauma situations. Since delay in diagnosis may have devastating consequences, early, easily accessible and relatively inexpensive investigations for risk stratification may prove useful, especially in developing nations. MATERIALS AND METHODS: This prospective trial included a total of 67 young polytrauma patients, in whom the role of nine easily available, rapidly performable clinical or laboratory investigations (or observations noted at admission) in predicting the later occurrence of fat embolism syndrome were assessed. All the patients also underwent continuous monitoring of oxygen saturation with pulsoximetry. RESULTS: The correlation between initial serum lactate (within 12 hours of injury) and hypoxia was statistically significant. There was a trend towards correlation with FES(by Gurd's criteria) (P=0.07), Sensitivity of 24-hour monitoring of oxygen saturation in predicting later pulmonary deterioration approached 100%. CONCLUSIONS: The combination of three factors including polytrauma (with NISS >17), serum lactate >22 mmol/l at admission (within 12 hours of injury) fall in oxygen saturation (SaO2 below 90% in the initial 24 hours) predict the development of post-traumatic pulmonary complications, especially the fat embolism syndrome.

Disturbance rejection for multi-weighted complex dynamical networks with actuator saturation and deception attacks via hybrid-triggered mechanism.

In this work, we address hybrid-driven-based robust synchronization problem for multi-weighted complex dynamical networks with actuator saturation and deception attacks. The hybrid-triggered mechanism, which combines a switch between the event-triggered scheme and the time-triggered scheme, is often used to reduce the data transmission and the alleviate network burden. Further, the equivalent-input-disturbance technique is applied to eliminate the unknown disturbance effect of the addressed system. Moreover, a memory controller is designed under actuator saturation to ensure that the resultant augmented system is asymptotically synchronized even in the presence of deception attacks. Finally, three numerical examples are given to show the validity of the obtained theoretical results.

Composite fault reconstruction and fault-tolerant control design for cyber-physical systems: An interval type-2 fuzzy approach.

This article scrutinizes the stabilization and fault reconstruction issues for interval type-2 fuzzy-based cyber-physical systems with actuator faults, deception attacks and external disturbances. The primary objective of this research is to formulate the learning observer system with the interval type-2 fuzzy technique that reconstructs the actuator faults as well as the immeasurable states of the addressed fuzzy based model. Further, the information of reconstructed actuator faults is incorporated in the developed controller with the imperfect premise variables for ensuring the stabilization of the system under consideration. At the same time, the H∞ technique is employed to reduce the impact of external disturbances in the considered model. In addition to that, the deception attacks are represented as a stochastic variable that satisfies the Bernoulli distributions. On the ground of this, a set of sufficient criteria is deduced in the context of linear matrix inequalities to affirm the stability of the addressed systems. Furthermore, the requisite gain matrices are computed by resolving the obtained linear matrix inequality based stability criteria. At last, two simulation examples, including the mass-spring-damper system are exhibited to demonstrate the usefulness of analytical findings of the developed strategy.

Prediction of COVID-19 growth and trend using machine learning approach.

The Covid-19 Corona Virus, also known as SARS-CoV-2, has wreaked havoc around the world, and the condition is only getting worse. It is a pandemic disease spreading from person-to-person every day. Therefore, it is important to keep track the number of patients being affected. The current system gives the computerized data in a collective way which is very difficult to analyze and predict the growth of disease in a particular area and in the world. Machine learning algorithms can be used to successfully map the disease and its progression to solve this problem. Machine Learning, a branch of computer science, is critical in correctly distinguishing patients with the condition by analyzing their chest X-ray photographs. Supervised Machine learning models with associated algorithms (like LR, SVR and Time series algorithms) to analyze data for regression and classification helps in training the model to predict the number of total number of global confirmed cases who will be prone to the disease in the upcoming days. In this proposed work, the overall dataset of the world is being collected, preprocessed and the number of confirmed cases up to a particular date are extracted which is given as the training set to the model. The model is being trained by supervised machine learning algorithms to predict the growth of cases in the upcoming days. The experimental setup with the above mentioned algorithms shows that Time series Holt's model outperforms Linear Regression and Support Vector Regression algorithms.

Nanotechnology- A ray of hope for heavy metals removal.

Environmental effects of heavy metal pollution are considered as a widespread problem throughout the world, as it jeopardizes human health and also reduces the sustainability of a cleaner environment. Removal of such noxious pollutants from wastewater is pivotal because it provides a propitious solution for a cleaner environment and water scarcity. Adsorption treatment plays a significant role in water remediation due to its potent treatment and low cost of adsorbents. In the last two decades, researchers have been highly focused on the modification of adsorption treatment by functionalized and surface-modified nanomaterials which has spurred intense research. The characteristics of nano adsorbents attract global scientists as it is also economically viable. This review shines its light on the functionalized nanomaterials application for heavy metals removal from wastewater and also highlights the importance of regeneration of nanomaterials in the view of visualizing the economic aspects along with a cleaner environment. The review also focused on the proper disposal of nanomaterials with crucial issues that persist in the adsorption process and also emphasize future research modification at a large-scale application in industries.

Design of robust tracking and disturbance attenuation control for stochastic control systems.

The focus of current research is to address the problem of robust output tracking, input delay compensation and disturbance attenuation performance for a family of stochastic systems by implementing the improved-equivalent-input-disturbance (IEID) estimator and the extended Smith predictor (ESP) technique. By integrating the observer and IEID-estimator together with ESP, a new closed-loop configuration is presented. Then, Lyapunov based mean-square asymptotic stability criterion is obtained. According to attained stability criterion, an IEID and ESP based-controller is designed, which ultimately guarantees the exact output tracking. Simulation studies of numerical examples are offered to expose the authenticity of IEID and ESP-based controller. Further, the proposed outcomes in comparison with existing results are presented to demonstrate the efficaciousness of the established control procedure.

Influence of metal oxide catalyst on co-pyrolysis of biomass and COVID-19 waste.

The disposal of waste generated by the COVID-19 pandemic is still a challenge to the government in most countries. The present study shines its light on the catalytic effect of metal oxide on converting COVID-19 waste i.e. used face masks into valuable products through co-pyrolysis. The co-pyrolysis trial was carried out for a mixture of waste face mask (WFM) and Moringa oleifera (MO) biomass at a constant temperature of 450°C for 15 min of resident time. This investigation focuses on studying the catalytic effect of calcium oxide (CaO) on the by-products of the pyrolysis process. From the FT-IR studies, it is observed that the CaO catalyst assisted to reduce oxygen as well as sulphur and carboxylic acids in the bio-oil due to its strong basic nature. The FE-SEM images suggest the increase in porous structure with catalytic pyrolysis (CP) char compared to non-catalytic pyrolysis (NCP) char. The catalytic activity of CaO increased the alcoholic content with a reduction in aldehydes and ketones in the bio-oil. The addition of WFM to the biomass with CaO catalyst pyrolysis (CP) delivered a higher oil yield of 52% compared to non-catalytic pyrolysis (NCP).

Composite fault-tolerant and anti-disturbance control for switched fuzzy stochastic systems.

This paper investigates the issue of fault-tolerant and anti-disturbance attenuation for a two-dimensional modified repetitive control system (2D MRCS) which is described by switched fuzzy systems with multiple disturbances. In particular, the multiple disturbances contain an exogenous disturbance and standard Wiener noise. Specifically, a generalized extended state observer (GESO) is incorporated with the 2D MRCS to estimate both fault and exogenous multiple disturbances so that the disturbances and faults can be attenuated in the control input. Further, the improved 2D MRCS relaxes the stability condition and provides an enhanced tracking performance. Based on the Lyapunov function approach, pole placement technique and average dwell time approach, the stability criteria for the considered system is developed in terms of linear matrix inequality (LMI). Then an algorithm for designing a GESO-based 2D MRC design is developed based on the obtained LMIs. Further, the results developed are validated in the simulation section through three numerical examples.

Liquid hot water as sustainable biomass pretreatment technique for bioenergy production: A review.

In recent years, lignocellulosic biomass has emerged as one of the most versatile energy sources among the research community for the production of biofuels and value-added chemicals. However, biomass pretreatment plays an important role in reducing the recalcitrant properties of lignocellulose, leading to superior quality of target products in bioenergy production. Among existing pretreatment techniques, liquid hot water (LHW) pretreatment has several outstanding advantages compared to others including minimum formation of monomeric sugars, significant removal of hemicellulose, and positive environmental impacts; however, several constraints of LHW pretreatment should be clarified. This contribution aims to provide a comprehensive analysis of reaction mechanism, reactor characteristics, influencing factors, techno-economic aspects, challenges, and prospects for LHW-based biomass pretreatment. Generally, LHW pretreatment could be widely employed in bioenergy processing from biomass, but circular economy-based advanced pretreatment techniques should be further studied in the future to achieve maximum efficiency, and minimum cost and drawbacks.

Risk of postoperative venous thromboembolism in Indian patients sustaining pelvi-acetabular injury.

Most surgeons believe that Asians have a low risk of developing venous thromboembolism (VTE) and routine thromboprophylaxis therapy is not required after major orthopaedic trauma. This study evaluates the postoperative risk of VTE in Indian patients sustaining pelvi-acetabular injury. Fifty-six patients with pelvi-acetabular injury, who underwent open reduction and internal fixation, were prospectively evaluated for VTE in the postoperative period. They were evaluated, both clinically and radiologically (pulmonary CT angiography and indirect venography of lower limb and pelvis veins), until six weeks after surgery. A total of 16 patients developed VTE, of which 12 had proximal deep vein thrombosis (DVT), ten had pulmonary embolism (PE) and only two had distal DVT. Six patients with proximal DVT had associated PE. The risk of development of VTE among Indian patients after pelvi-acetabular injury is high (28.6%) with increasing chances of proximal DVT and PE; hence, administration of routine thromboprophylaxis is fully justified in them.

Equivalent-input-disturbance estimator-based event-triggered control design for master-slave neural networks.

This paper investigates the robust synchronization problem for a class of master-slave neural networks (MSNNs) subject to network-induced delays, unknown time-varying uncertainty, and exogenous disturbances. An equivalent-input-disturbance (EID) estimation technique is applied to compensate for the effects of unknown uncertainty and disturbances in the system output. In addition, to reduce the burden of the communication channel in the addressed MSNNs and improve the utilization of bandwidth an event-triggered control protocol is developed to obtain the synchronization of MSNNs. In particular, event-triggering conditions are verified periodically at every sampling instant in both sensors and actuators to avoid the Zeno behavior in the networks. By designing an appropriate low-pass filter in the EID estimator block, the accuracy of disturbance estimation performance is improved. Moreover, by concatenating the synchronization error, observer, and filter states as a single state vector, an augmented system is formulated. Then the tangible delay-dependent stability condition for that augmented system is established by employing the Lyapunov stability theory and reciprocally convex approach. Based on the feasible solutions of the derived stability conditions, the event-triggering parameters, controller, and observer gains are co-designed. Finally, two toy examples are given to illustrate the established theoretical findings.

Nutritional supplementation in HIV-infected individuals in South India: a prospective interventional study.

BACKGROUND: Malnutrition in human immunodeficiency virus (HIV)-infected individuals is associated with faster disease progression, higher mortality rates, and suboptimal response to antiretroviral therapy (ART). METHODS: We conducted a prospective interventional study to evaluate the effects of an oral macronutrient supplement among HIV-infected adults in South India. Patients attending Tuberculosis Research Centre clinics from June 2005 through December 2007 had baseline nutritional assessment and laboratory investigations performed. Patients at 1 center received nutritional counseling and standard care, whereas patients at 2 centers additionally received a macronutrient providing 400 cal and 15 g of protein daily. Study outcomes were changes in anthropometry, body composition, blood chemistry, and immune status at 6 months. RESULTS: In total, 636 ART-naive patients were enrolled in the study; 361 completed 6 months of follow-up (282 received supplements and 79 received standard care). Mean age +/- standard deviation (SD) was 31 +/- 7 years, mean weight +/- SD was 50 +/- 10 kg, and 42% were male. Significant increases in body weight, body mass index, midarm circumference, fat-free mass, and body cell mass were observed in the supplement group but not in the control group at 6 months; gains were greater in patients with CD4 cell counts <200 cells/microL. No changes were observed in lipid levels, whereas the CD4 cell count decreased in the control group. However, after adjusting for baseline differences, these changes were not statistically significantly different between the groups. CONCLUSIONS: Macronutrient supplementation did not result in significantly increased weight gain compared with standard care (including nutritional counseling) among patients with moderately advanced HIV disease. The effect of supplementation on specific subsets of patients and on preserving immune function needs further research.

Disturbance rejection in fuzzy systems based on two dimensional modified repetitive-control.

This paper concerns with the issues of designing an improved-equivalent-input-disturbance (IEID) based robust two dimensional modified repetitive control (2D MRC) for a class of fuzzy systems in the presence of aperiodic disturbances. Specifically, IEID-estimator is implemented to the 2D MRC systems that estimates all types of disturbances and compensates them for assuring robust stability. In particular, the proposed 2D MRC system has two different type of behaviours such as continuous control and discrete learning independently. To obtain gains of the observer and the controller, an adequate set of robust stability conditions is derived in the form of a linear-matrix-inequalities. Finally, simulation results for three numerical examples are provided to depict the efficacy of the proposed control technique.