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In recent years, due to the increase in the incidence of traffic accidents, the number of people with limb injuries has also increased. At the same time, among the aging population, neurological diseases or cardiovascular and cerebrovascular diseases have caused many people to have limb hemiplegia. It has been clinically proven that the use of rehabilitation equipment can help patients with limb injuries to restore limb motor function. This paper takes wearable lower limb rehabilitation exoskeleton as the research object, and its main contents are mechanical structure design, kinematics analysis, gait planning, virtual prototype simulation, and experimental verification and analysis. Based on the physiological characteristics of human body and the principle of comfortable and reliable wearing, this paper designs wearable exoskeleton for lower limb rehabilitation. Firstly, the physiological structure characteristics and movement mechanism of human lower limbs were studied and analyzed. By referring to the rotation range and height and size of each joint of human lower limbs, the overall scheme of wearable lower limb rehabilitation exoskeleton was designed and the degree of freedom was allocated. At the same time, Solidworks was used to establish a three-dimensional model. On the basis of a 3D model, a kinematics model was established, and the forward kinematics solution was obtained by using homogeneous coordinate transformation. Since the inverse kinematics solution was relatively complicated, the inverse kinematics solution was conducted in this paper according to the geometric relations of the joints of the lower limbs. Kinematics analysis of the exoskeleton structure of wearable lower limb rehabilitation was carried out to lay a theoretical foundation for gait planning. The off-line gait planning was carried out by using the method based on ZMP stability criterion, and the gait planning was divided into five stages: squat, start, middle step, stop and rise, and the motion trajectory of the center of mass and ankle joint was planned. Based on the inverse kinematics formula, the function of the change of joint angle with time in walking process is derived. The virtual prototype is established in ADAMS, and the simulation of virtual prototype is carried out by using the function of gait planning's joint angle and time. The correctness of structural design and gait planning was verified by measuring the trajectories of the centroid and ankle joints in each gait stage and the functional relationship between the rotation angle of each joint and time. Then, using a 3D dynamic capture system to capture the human lower limb motion trajectory of each joint, each joint trajectory data output, using the MATLAB software to output data, gets the joint trajectory change over time function curve and is used to verify feasibility and applicability of human gait planning. Through the research and analysis of the joints of the lower limbs of the human body, it can be concluded that the hip joint and the knee joint have 3 degrees of freedom, respectively, and the knee joint has 1 degree of freedom. [ABSTRACT FROM AUTHOR]

This work delivers a novel technique to detect brain tumor with the help of enhanced watershed modeling integrated with a modified ResNet50 architecture. It also involves stochastic approaches to help in developing enhanced watershed modeling. Cancer diseases, primarily the brain tumor, have been exponentially raised which has alarmed researchers from academia and industry. Nowadays, researchers need to attain a more effective, accurate, and trustworthy brain tumor tissue detection and classification approach. Different from traditional machine learning methods that are just targeting to enhance classification efficiency, this work highlights the process to extract several deep features to diagnose brain tumor effectively. This paper explains the modeling of a novel technique by integrating the modified ResNet50 with the Enhanced Watershed Segmentation (EWS) algorithm for brain tumor classification and deep feature extraction. The proposed model uses the ResNet50 model with a modified layer architecture including five convolutional layers and three fully connected layers. The proposed method can retain the optimal computational efficiency with high-dimensional deep features. This work obtains a comprised feature set by retrieving the diverse deep features from the ResNet50 deep learning model and feeds them as input to the classifier. The good performing capability of the proposed model is achieved by using hybrid features of ResNet50. The brain tumor tissue images were extracted by the suggested hybrid deep feature-based modified ResNet50 model and the EWS-based modified ResNet50 model with a high classification accuracy of 92% and 90%, respectively. [ABSTRACT FROM AUTHOR]

The applications of 3D printing technology in health care, particularly orthopedics, continue to broaden as the technology becomes more advanced, accessible, and affordable worldwide. 3D printed models of computed tomography (CT) and magnetic resonance image (MRI) scans can reproduce a replica of anatomical parts that enable surgeons to get a detailed understanding of the underlying anatomy that he/she experiences intraoperatively. The 3D printed anatomic models are particularly useful for preoperative planning, simulation of complex orthopedic procedures, development of patient-specific instruments, and implants that can be used intraoperatively. This paper reviews the role of 3D printing technology in orthopedic surgery, specifically focusing on the role it plays in assisting surgeons to have a better preoperative evaluation and surgical planning. [ABSTRACT FROM AUTHOR]

Angiogenesis is a crucial area in scientific research because it involves many important physiological and pathological processes. Indeed, angiogenesis is critical for normal physiological processes, including wound healing and embryonic development, as well as being a component of many disorders, such as rheumatoid arthritis, obesity, and diabetic retinopathies. Investigations of angiogenic mechanisms require assays that can activate the critical steps of angiogenesis as well as provide a tool for assessing the efficacy of therapeutic agents. Thus, angiogenesis assays are key tools for studying the mechanisms of angiogenesis and identifying the potential therapeutic strategies to modulate neovascularization. However, the regulation of angiogenesis is highly complex and not fully understood. Difficulties in assessing the regulators of angiogenic response have necessitated the development of an alternative approach. In this paper, we review the standard models for the study of tumor angiogenesis on the macroscopic scale that include in vitro, in vivo, and computational models. We also highlight the differences in several modeling approaches and describe key advances in understanding the computational models that contributed to the knowledge base of the field. [ABSTRACT FROM AUTHOR]

Obtaining the computational models for the functioning of the brain gives us a chance to understand the brain functionality thoroughly. This would help the development of better treatments for neurological illnesses and disorders. We created a cortical model using Python language using the Brian simulator. The Brian simulator is specialized in simulating the neuronal connections and synaptic interconnections. The dynamic connection model has multiple parameters in order to ensure an accurate simulation (Bowman, 2016). We concentrated on the connection weights and studied their effect on the interactivity and connectivity of the cortical neurons in the same cortical layer and across multiple layers. As synchronization helps us to measure the degree of correlation between two or more neuronal groups, the synchronization between the neuronal groups, which are connected across layers, is considered. Despite its obvious importance, there are no sufficient studies concerned about the synchronization in the simulated cortical models. Such studies can help in examining the hypothesis and the dynamical behavior of the simulated model. In this paper, we simulated a cortical model and dynamical behavior and then studied the effect of input noise on its internal neuronal networks and their synchronization. [ABSTRACT FROM AUTHOR]

The objective of this paper is to determine the best optical probe configuration that would help to detect neoplastic lesions in oral tongue epithelial tissue. Three geometrical configurations are investigated. The first one is a single-fibre probe with different fibre diameters. The second one is a multitilted fibre probe that employs different tilting angles for emission and collection fibres. While the third one is a multidiameter probe that employs different fibre diameters and distances between the emission and the collection fibres. All probes were evaluated for their depth-limited sensitivity in the epithelium layer of the tongue. Probes that showed efficient sensitivities were then compared for their fluorescence intensities acquired from both tissue types. The sensitivity for the first two types of probes was found to be roughly comparable. However, the differentiation capability of the multitilted fibre probe between dysplastic and healthy tissue was found to be noticeably larger by 30% of that of the single-fibre probe. The third type showed more sensitivity to fluorescence emerging from deeper layers. Finally, the proposed configuration is presented and proved to achieve higher sensitivity for both superficial and deep layers. [ABSTRACT FROM AUTHOR]

Introduction. Applying computerized simulation education tool for learning in medical domains is widely used in many countries. This review is aimed at systematically investigating the computerized simulation tools developed to educate physiotherapy students and determine the effectiveness of these interventions. Methods. A comprehensive search was conducted in Medline (through PubMed) and Scopus databases from inception to Sept. 10, 2022. The studies that examined the effectiveness of computerized simulation-based interventions were included. Results. Sixteen studies were included in this systematic review. All included examinations were ranked "good" or "low risk of bias" based on the criteria utilized in the Joanna Briggs Institute (JBI) scale and the Effective Public Health Practice Project (EPHPP) tool. Most of the articles (43%) were conducted in the USA and 25% in Australia. In 43% of the total studies, the study population was only physiotherapy students, and in 12.5% of them, the scope of education was related to practical skills training. Three of the 16 reviewed articles presented positive qualitative results; thirteen quantitative investigations also declared statistically positive effects. Positive effects have been seen in areas such as improving professional and behavioral abilities, improving knowledge and self-confidence, and reducing stress. The sample size of the studies ranged from eight to 162 participants. The limited sample sizes in groups, lack of interaction, and short follow-up duration were the most consistent limitations evident within the included studies. Conclusion. Computerized simulation education approaches can help to improve physiotherapy students' skills and knowledge. They also have great potential to reduce learning costs and increase the quality of education. [ABSTRACT FROM AUTHOR]

To determine the relationship between the ultrasonic backscatter parameters and trabecular microstructural variations in cancellous bone, three erosion procedures were performed to simulate various changes in the cancellous bone microstructure. The finite difference time domain (FDTD) method was used to simulate the backscatter signal in cancellous bone. Ultrasonic backscatter properties were derived as functions of the porosity when the ultrasound incident directions were perpendicular and parallel to the major trabeculae direction (MTD), respectively. The variability in the apparent backscatter coefficient (ABC) and apparent integrated backscatter (AIB) due to the trabecular microstructure was revealed. Significant negative correlations between the backscatter parameters (ABC and AIB) and the porosity of the cancellous bone were observed. The simulations showed that the ABC and AIB were influenced by the direction of the trabecular microstructural variations. The linear regressions between the ultrasonic backscatter parameters (ABC and AIB) and the porosity showed significantly different slopes for three erosion procedures when they are ultrasonically perpendicular (for ABC, −1.22 dB, −0.98 dB, and −0.46 dB; for AIB, −0.74 dB, −0.69 dB, and −0.25 dB) and parallel (for ABC, −1.87 dB, −0.69 dB, and −0.51 dB; for AIB, −0.9 dB, −0.5 dB, and −0.34 dB) to the MTD. This paper investigated the relationship between ultrasonic backscatter and cancellous bone microstructure deterioration and indicated that the ultrasonic backscatter could be affected by cancellous bone microstructure deterioration direction. [ABSTRACT FROM AUTHOR]

Phosphatidylinositol 3,4,5-trisphosphate- (PIP3-) dependent Rac exchanger 1 (P-Rex1) functions as Rho guanine nucleotide exchange factor and is activated by synergistic activity of Gβγ and PIP3 of the heterotrimeric G protein. P-Rex1 activates Rac GTPases for regulating cell invasion and migration and promotes metastasis in several human cancers including breast, prostate, and skin cancer. The protein is a promising therapeutic target because of its multifunction roles in human cancers. Herein, the present study attempts to identify selective P-Rex1 natural inhibitors by targeting PIP3-binding pocket using large-size multiple natural molecule libraries. Each library was filtered subsequently in FAF-Drugs4 based on Lipinski's rule of five (RO5), toxicity, and filter pan assay interference compounds (PAINS). The output hits were virtually screened at the PIP3-binding pocket through PyRx AutoDock Vina and cross-checked by GOLD. The best binders at the PIP3-binding pocket were prioritized using a comparative analysis of the docking scores. Top-ranked two compounds with high GOLD fitness score (>80) and lowest AutoDock binding energy (< -12.7 kcal/mol) were complexed and deciphered for molecular dynamics along with control-P-Rex1 complex to validate compound binding conformation and disclosed binding interaction pattern. Both the systems were seen in good equilibrium, and along the simulation time, the compounds are in strong contact with the P-Rex1 PIP3-binding site. Hydrogen bonding analysis towards simulation end identified the formation of 16 and 22 short- and long-distance hydrogen bonds with different percent of occupancy to the PIP3 residues for compound I and compound 2, respectively. Radial distribution function (RDF) analysis of the key hydrogen bonds between the compound and the PIP3 residues demonstrated a strong affinity of the compounds to the mentioned PIP3 pocket. Additionally, MMGB/PBSA energies were performed that confirmed the dominance of Van der Waals energy in complex formation along with favorable contribution from hydrogen bonding. These findings were also cross-validated by a more robust WaterSwap binding energy predictor, and the results are in good agreement with a strong binding affinity of the compounds for the protein. Lastly, the key contribution of residues in interaction with the compounds was understood by binding free energy decomposition and alanine scanning methods. In short, the results of this study suggest that P-Rex1 is a good druggable target to suppress cancer metastasis; therefore, the screened druglike molecules of this study need in vitro and in vivo anti-P-Rex1 validation and may serve as potent leads to fight cancer. [ABSTRACT FROM AUTHOR]

The evolution of the next generation sequencing technology increases the demand for efficient solutions, in terms of space and time, for several bioinformatics problems. This paper presents a practical and easy-to-implement solution for one of these problems, namely, the all-pairs suffix-prefix problem, using a compact prefix tree. The paper demonstrates an efficient construction of this time-efficient and space-economical tree data structure. The paper presents techniques for parallel implementations of the proposed solution. Experimental evaluation indicates superior results in terms of space and time over existing solutions. Results also show that the proposed technique is highly scalable in a parallel execution environment. [ABSTRACT FROM AUTHOR]

Ultrasound elastography is an imaging modality to evaluate elastic properties of soft tissue. Recently, 1D quasi-static elastography method has been commercialized by some companies. However, its performance is still limited on high strain level. In order to improve the precision of estimation during high compression, some algorithms have been proposed to expand the 1D window to a 2D window for avoiding the side-slipping. But they are usually more computationally expensive. In this paper, we proposed a modified 2D multiresolution hybrid method for displacement estimation, which can offer an efficient strain imaging with stable and accurate results. A FEM phantom with a stiffer circular inclusion is simulated for testing the algorithm. The elastographic contrast-to-noise rate (CNRe) is calculated for quantitatively comparing the performance of the proposed algorithm with conventional 1D elastography using phase zero estimation and the 1D elastography using downsampled (d-s) baseband signals. Results show that the proposed method is robust and performs similarly as other algorithms in low strain but is superior when high level strain is applied. Particularly, the CNRe of our algorithm is 15 times higher than original method under 4% strain level. Furthermore, the execution time of our algorithm is five times faster than other algorithms. [ABSTRACT FROM AUTHOR]

The naïve Bayes classifier (NBC) is one of the most popular classifiers for class prediction or pattern recognition from microarray gene expression data (MGED). However, it is very much sensitive to outliers with the classical estimates of the location and scale parameters. It is one of the most important drawbacks for gene expression data analysis by the classical NBC. The gene expression dataset is often contaminated by outliers due to several steps involved in the data generating process from hybridization of DNA samples to image analysis. Therefore, in this paper, an attempt is made to robustify the Gaussian NBC by the minimum β-divergence method. The role of minimum β-divergence method in this article is to produce the robust estimators for the location and scale parameters based on the training dataset and outlier detection and modification in test dataset. The performance of the proposed method depends on the tuning parameter β. It reduces to the traditional naïve Bayes classifier when β → 0. We investigated the performance of the proposed beta naïve Bayes classifier (β-NBC) in a comparison with some popular existing classifiers (NBC, KNN, SVM, and AdaBoost) using both simulated and real gene expression datasets. We observed that the proposed method improved the performance over the others in presence of outliers. Otherwise, it keeps almost equal performance. [ABSTRACT FROM AUTHOR]

Noncoding RNAs (ncRNAs) play important roles in various cellular activities and diseases. In this paper, we presented a comprehensive review on computational methods for ncRNA prediction, which are generally grouped into four categories: (1) homology-based methods, that is, comparative methods involving evolutionarily conserved RNA sequences and structures, (2) de novo methods using RNA sequence and structure features, (3) transcriptional sequencing and assembling based methods, that is, methods designed for single and pair-ended reads generated from next-generation RNA sequencing, and (4) RNA family specific methods, for example, methods specific for microRNAs and long noncoding RNAs. In the end, we summarized the advantages and limitations of these methods and pointed out a few possible future directions for ncRNA prediction. In conclusion, many computational methods have been demonstrated to be effective in predicting ncRNAs for further experimental validation. They are critical in reducing the huge number of potential ncRNAs and pointing the community to high confidence candidates. In the future, high efficient mapping technology and more intrinsic sequence features (e.g., motif and k-mer frequencies) and structure features (e.g., minimum free energy, conserved stem-loop, or graph structures) are suggested to be combined with the next- and third-generation sequencing platforms to improve ncRNA prediction. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel method for solving the single-trial evoked potential (EP) estimation problem. In this method, the single-trial EP is considered as a complex containing many components, which may originate from different functional brain sites; these components can be distinguished according to their respective latencies and amplitudes and are extracted simultaneously by multiple-input single-output autoregressive modeling with exogenous input (MISO-ARX). The extraction process is performed in three stages: first, we use a reference EP as a template and decompose it into a set of components, which serve as subtemplates for the remaining steps. Then, a dictionary is constructed with these subtemplates, and EPs are preliminarily extracted by sparse coding in order to roughly estimate the latency of each component. Finally, the single-trial measurement is parametrically modeled by MISO-ARX while characterizing spontaneous electroencephalographic activity as an autoregression model driven by white noise and with each component of the EP modeled by autoregressive-moving-average filtering of the subtemplates. Once optimized, all components of the EP can be extracted. Compared with ARX, our method has greater tracking capabilities of specific components of the EP complex as each component is modeled individually in MISO-ARX. We provide exhaustive experimental results to show the effectiveness and feasibility of our method. [ABSTRACT FROM AUTHOR]

Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect. [ABSTRACT FROM AUTHOR]

The adult heart is composed of a dense network of cardiomyocytes surrounded by nonmyocytes, the most abundant of which are cardiac fibroblasts. Several cardiac diseases, such as myocardial infarction or dilated cardiomyopathy, are associated with an increased density of fibroblasts, that is, fibrosis. Fibroblasts play a significant role in the development of electrical and mechanical dysfunction of the heart; however the underlying mechanisms are only partially understood. One widely studied mechanism suggests that fibroblasts produce excess extracellular matrix, resulting in collagenous septa. These collagenous septa slow propagation, cause zig-zag conduction paths, and decouple cardiomyocytes resulting in a substrate for arrhythmia. Another emerging mechanism suggests that fibroblasts promote arrhythmogenesis through direct electrical interactions with cardiomyocytes via gap junctions. Due to the challenges of investigating fibroblast-myocyte coupling in native cardiac tissue, computational modeling and in vitro experiments have facilitated the investigation into the mechanisms underlying fibroblast-mediated changes in cardiomyocyte action potential morphology, conduction velocity, spontaneous excitability, and vulnerability to reentry. In this paper, we summarize the major findings of the existing computational studies investigating the implications of fibroblast-myocyte interactions in the normal and diseased heart. We then present investigations fromour group into the potential role of voltage-dependent gap junctions in fibroblast-myocyte interactions. [ABSTRACT FROM AUTHOR]

Most hosts harbor multiple pathogens at the same time in disease epidemiology. Multiple pathogens have the potential for interaction resulting in negative impacts on host fitness or alterations in pathogen transmission dynamics. In this paper we develop a mathematical model describing the dynamics of HIV-malaria coinfection. Additionally, we extended our model to examine the role treatment (of malaria and HIV) plays in altering populations' dynamics. Our model consists of 13 interlinked equations which allow us to explore multiple aspects of HIV-malaria transmission and treatment. We perform qualitative analysis of the model that includes positivity and boundedness of solutions. Furthermore, we evaluate the reproductive numbers corresponding to the submodels and investigate the long term behavior of the submodels. We also consider the qualitative dynamics of the full model. Sensitivity analysis is done to determine the impact of some chosen parameters on the dynamics of malaria. Finally, numerical simulations illustrate the potential impact of the treatment scenarios and confirm our analytical results. [ABSTRACT FROM AUTHOR]

Background. The bacterial membrane plays a critical role in the survival of bacteria and the effectiveness of antimicrobial peptides in protecting the host. The lipid constituents of the bacterial membrane are not evenly distributed, and they could be affected by clustering anionic lipids with cationic peptides with multiple positive charges. That could be harmful to bacteria because it prevents lipids from interacting with other molecular components of the cell membrane, disrupts existing natural domains, or creates phase boundary defects between the clustered lipids and the bulk of the membrane. This preliminary quantitative study is aimed at assembling a correlation between antibiotic resistance and bacterial lipid composition in E. coli, based on the function and arrangement of the bilipid coating of the bacterial cell, intimately associated with the path of antimicrobials through membranes. Methods. Fifteen multiresistant E. coli samples are collected from swine with enterocolitis tested for resistance levels using the disc diffusimetric method (Kirby-Bauer disc diffusion). Pathogen identification completed using the API 20E multitest system revealed the E. coli presence in 11 samples. In these samples, bacterial membrane detection of fatty acid methyl esters (FAME) operating a 240 MS Ion Trap (Varian) GC/MS (Agilent Technologies, Santa Clara, CA, USA) was performed, using the MIDI Sherlock recognition software model. Results. Interpreting the descriptive statistical method, the correlation matrix, and regression curves and after ANOVA analysis, we ascertained that the studied E. coli population statistically confirmed different degrees of resistance in most of the samples analyzed in this test. Conclusions. In one case, the methyl-(Z)-11-tetradecenoate acid was observed to have a relationship with the susceptibility evaluation by using the disc diffusimetric method, which has revealed the lowest rate of antimicrobial resistance, so it has importance in further resistance evaluation studies. [ABSTRACT FROM AUTHOR]

More and more studies have shown that many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional biological pathway or network and are highly correlated. Differential coexpression analysis, as a more comprehensive technique to the differential expression analysis, was raised to research gene regulatory networks and biological pathways of phenotypic changes through measuring gene correlation changes between disease and normal conditions. In this paper, we propose a gene differential coexpression analysis algorithm in the level of gene sets and apply the algorithm to a publicly available type 2 diabetes (T2D) expression dataset. Firstly, we calculate coexpression biweight midcorrelation coefficients between all gene pairs. Then, we select informative correlation pairs using the “differential coexpression threshold” strategy. Finally, we identify the differential coexpression gene modules using maximum clique concept and k-clique algorithm. We apply the proposed differential coexpression analysis method on simulated data and T2D data. Two differential coexpression gene modules about T2D were detected, which should be useful for exploring the biological function of the related genes. [ABSTRACT FROM AUTHOR]

It is challenging and inspiring for us to achieve high spatiotemporal resolutions in dynamic cardiac magnetic resonance imaging (MRI). In this paper, we introduce two novel models and algorithms to reconstruct dynamic cardiac MRI data from under-sampled k-t space data. In contrast to classical low-rank and sparse model, we use rank-one and transformed sparse model to exploit the correlations in the dataset. In addition, we propose projected alternative direction method (PADM) and alternative hard thresholding method (AHTM) to solve our proposed models. Numerical experiments of cardiac perfusion and cardiac cine MRI data demonstrate improvement in performance. [ABSTRACT FROM AUTHOR]

Nature often brings several domains together to form multidomain and multifunctional proteins with a vast number of possibilities. In our previous study, we disclosed that the protein function prediction problem is naturally and inherently Multi-Instance Multilabel (MIML) learning tasks. Automated protein function prediction is typically implemented under the assumption that the functions of labeled proteins are complete; that is, there are no missing labels. In contrast, in practice just a subset of the functions of a protein are known, and whether this protein has other functions is unknown. It is evident that protein function prediction tasks suffer from weak-label problem; thus protein function prediction with incomplete annotation matches well with the MIML with weak-label learning framework. In this paper, we have applied the state-of-the-art MIML with weak-label learning algorithm MIMLwel for predicting protein functions in two typical real-world electricigens organisms which have been widely used in microbial fuel cells (MFCs) researches. Our experimental results validate the effectiveness of MIMLwel algorithm in predicting protein functions with incomplete annotation. [ABSTRACT FROM AUTHOR]

Type IV pili (T4P) and T2SS (Type II Secretion System) pseudopili are filaments extending beyond microbial surfaces, comprising homologous subunits called “pilins.” In this paper, we presented a new approach to predict pseudo atomic models of pili combining ambiguous symmetric constraints with sparse distance information obtained from experiments and based neither on electronic microscope (EM) maps nor on accurate a priori symmetric details. The approach was validated by the reconstruction of the gonococcal (GC) pilus from Neisseria gonorrhoeae, the type IVb toxin-coregulated pilus (TCP) from Vibrio cholerae, and pseudopilus of the pullulanase T2SS (the PulG pilus) from Klebsiella oxytoca. In addition, analyses of computational errors showed that subunits should be treated cautiously, as they are slightly flexible and not strictly rigid bodies. A global sampling in a wider range was also implemented and implied that a pilus might have more than one but fewer than many possible intact conformations. [ABSTRACT FROM AUTHOR]

Pseudogene, disabled copy of functional gene, plays a subtle role in gene expression and genome evolution. The first step in deciphering RNA-level regulation of pseudogenes is to understand their transcriptional activity. So far, there has been no report on possible roles of nucleosome organization in pseudogene transcription. In this paper, we investigated the effect of nucleosome positioning on pseudogene transcription. For transcribed pseudogenes, the experimental nucleosome occupancy shows a prominent depletion at the regions both upstream of pseudogene start positions and downstream of pseudogene end positions. Intriguingly, the same depletion is also observed for nontranscribed pseudogenes, which is unexpected since nucleosome depletion in those regions is thought to be unnecessary in light of the nontranscriptional property of those pseudogenes. The sequence-dependent prediction of nucleosome occupancy shows a consistent pattern with the experimental data-based analysis. Our results indicate that nucleosome positioning may play important roles in both the transcription initiation and termination of pseudogenes. [ABSTRACT FROM AUTHOR]

Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods. [ABSTRACT FROM AUTHOR]

Most surgical simulators leverage virtual or bench models to simulate reality. This study proposes and validates a method for workspace configuration of a surgical simulator which utilizes a haptic device for interaction with a virtual model and a bench model to provide additional tactile feedback based on planned surgical manoeuvers. Numerical analyses were completed to determine the workspace and position of a haptic device, relative to the bench model, used in the surgical simulator, and the determined configuration was validated using device limitations and user data from surgical and nonsurgical users. For the validation, surgeons performed an identical surgery on a cadaver prior to using the simulator, and their trajectories were then compared to the determined workspace for the haptic device. The configuration of the simulator was determined appropriate through workspace analysis and the collected user trajectories. Statistical analyses suggest differences in trajectories between the participating surgeons which were not affected by the imposed haptic workspace. This study, therefore, demonstrates a method to optimally position a haptic device with respect to a bench model while meeting the manoeuverability needs of a surgical procedure. The validation method identified workspace position and user trajectory towards ideal configuration of a mixed reality simulator. [ABSTRACT FROM AUTHOR]

Background and Purpose. Ruptured tiny volume intracranial aneurysms (TVIAs) are associated with high risk of intraprocedural perforation. Aneurysm volume measuring is important for treatment planning and packing density calculation. We aim to assess the ability of the AngioSuite software in calculating TVIAs and guiding the selection of suitable coil. Methods. Thirty-three consecutive patients with 34 TVIAs were prospectively recruited and treated with endovascular techniques. The volume of TVIAs and the required length of coils were calculated by the AngioSuite software before embolization. The treatment efficacy of TVIAs was assessed using the Raymond scale (Rs) and the modified Rankin scale (mRs). Results. Of the 34 aneurysms with an average volume of 7.16 mm3, 13 aneurysms were treated with sole coil embolization, 19 by stent-assisted embolization, and 2 by balloon-assisted embolization. The average coil length was 5.32 cm, and the average packing density was 41.21%. The immediate DSA showed that total occlusion (Rs = 1) was achieved in 15 aneurysms, subtotal (Rs = 2) in 9, and partial (Rs = 3) in 11. Total occlusion was achieved in 30 aneurysms and subtotal in the other 4 aneurysms at 6-month follow-up. Baseline volume and diameter of aneurysms were significantly correlated with the coil length (r = 0.801 , P < 0.001 ; r = 0.711 , P < 0.001). Conclusions. Coil embolization of TVIAs was easy to achieve high packing density. According to the data from AngioSuite, relative few coils can increase the safety in procedure and stenting may reduce risk of aneurysmal recurrence. [ABSTRACT FROM AUTHOR]

The last decade (2010-2021) has witnessed the evolution of robotic applications in orthodontics. This review scopes and analyzes published orthodontic literature in eight different domains: (1) robotic dental assistants; (2) robotics in diagnosis and simulation of orthodontic problems; (3) robotics in orthodontic patient education, teaching, and training; (4) wire bending and customized appliance robotics; (5) nanorobots/microrobots for acceleration of tooth movement and for remote monitoring; (6) robotics in maxillofacial surgeries and implant placement; (7) automated aligner production robotics; and (8) TMD rehabilitative robotics. A total of 1,150 records were searched, of which 124 potentially relevant articles were retrieved in full. 87 studies met the selection criteria following screening and were included in the scoping review. The review found that studies pertaining to arch wire bending and customized appliance robots, simulative robots for diagnosis, and surgical robots have been important areas of research in the last decade (32%, 22%, and 16%). Rehabilitative robots and nanorobots are quite promising and have been considerably reported in the orthodontic literature (13%, 9%). On the other hand, assistive robots, automated aligner production robots, and patient robots need more scientific data to be gathered in the future (1%, 1%, and 6%). Technological readiness of different robotic applications in orthodontics was further assessed. The presented eight domains of robotic technologies were assigned to an estimated technological readiness level according to the information given in the publications. Wire bending robots, TMD robots, nanorobots, and aligner production robots have reached the highest levels of technological readiness: 9; diagnostic robots and patient robots reached level 7, whereas surgical robots and assistive robots reached lower levels of readiness: 4 and 3, respectively. [ABSTRACT FROM AUTHOR]

Drug-target interactions provide useful information for biomedical drug discovery as well as drug development. However, it is costly and time consuming to find drug-target interactions by experimental methods. As a result, developing computational approaches for this task is necessary and has practical significance. In this study, we establish a novel dual Laplacian graph regularized logistic matrix factorization model for drug-target interaction prediction, referred to as DLGrLMF briefly. Specifically, DLGrLMF regards the task of drug-target interaction prediction as a weighted logistic matrix factorization problem, in which the experimentally validated interactions are allocated with larger weights. Meanwhile, by considering that drugs with similar chemical structure should have interactions with similar targets and targets with similar genomic sequence similarity should in turn have interactions with similar drugs, the drug pairwise chemical structure similarities as well as the target pairwise genomic sequence similarities are fully exploited to serve the matrix factorization problem by using a dual Laplacian graph regularization term. In addition, we design a gradient descent algorithm to solve the resultant optimization problem. Finally, the efficacy of DLGrLMF is validated on various benchmark datasets and the experimental results demonstrate that DLGrLMF performs better than other state-of-the-art methods. Case studies are also conducted to validate that DLGrLMF can successfully predict most of the experimental validated drug-target interactions. [ABSTRACT FROM AUTHOR]

Background. Child mortality is a global health problem. The United Nations' 2018 report on levels and trends on child mortality indicated that under-five mortality is one of the major public health problems in Ghana with a rate of 60 deaths per 1000 live births. To further mitigate this problem, it is important to identify the drivers of under-five mortality in order to achieve the United Nations SDG Goal 3 target 2. Methods. In this study, we investigated the effects of some selected risk factors on child mortality using data from the 2014 Ghana Demographic Health Survey. We modelled the relationship between child mortality and the risk factors using a logistic regression model under the frequentist and Bayesian frameworks. We used the Metropolis-Hastings Algorithm to simulate parameter estimates from the posterior distributions, and statistical analyses were carried out using STATA version 14.1. Results. Results from the frequentist framework are in line with those from the Bayesian framework. The results showed an increased risk of death among children who were delivered through caesarean and reduced relative odds of death among children whose sizes are average or large at birth and whose mothers have formal education. Conclusions. There is a need for improved health facilities for better health-care for mothers and children. Education should, among other things, emphasise on the need for mothers to go for regular check-ups during antinatal and postnatal periods for improved mother and child health. [ABSTRACT FROM AUTHOR]

In silico T-cell epitope prediction plays an important role in immunization experimental design and vaccine preparation. Currently, most epitope prediction research focuses on peptide processing and presentation, e.g., proteasomal cleavage, transporter associated with antigen processing (TAP), and major histocompatibility complex (MHC) combination. To date, however, the mechanism for the immunogenicity of epitopes remains unclear. It is generally agreed upon that T-cell immunogenicity may be influenced by the foreignness, accessibility, molecular weight, molecular structure, molecular conformation, chemical properties, and physical properties of target peptides to different degrees. In this work, we tried to combine these factors. Firstly, we collected significant experimental HLA-I T-cell immunogenic peptide data, as well as the potential immunogenic amino acid properties. Several characteristics were extracted, including the amino acid physicochemical property of the epitope sequence, peptide entropy, eluted ligand likelihood percentile rank (EL rank(%)) score, and frequency score for an immunogenic peptide. Subsequently, a random forest classifier for T-cell immunogenic HLA-I presenting antigen epitopes and neoantigens was constructed. The classification results for the antigen epitopes outperformed the previous research (the optimal AUC = 0.81 , external validation data set AUC = 0.77). As mutational epitopes generated by the coding region contain only the alterations of one or two amino acids, we assume that these characteristics might also be applied to the classification of the endogenic mutational neoepitopes also called "neoantigens." Based on mutation information and sequence-related amino acid characteristics, a prediction model of a neoantigen was established as well (the optimal AUC = 0.78). Further, an easy-to-use web-based tool "INeo-Epp" was developed for the prediction of human immunogenic antigen epitopes and neoantigen epitopes. [ABSTRACT FROM AUTHOR]

Pancreaticoduodenal artery (PDA) aneurysm and celiac artery (CA) stenosis are rare diseases in themselves. Interestingly, however, there are more cases documented in the literature in which these two disease entities occurred together than could be coincidental, and CA stenosis has been suggested as the provocative condition in developing PDA aneurysm. This study is aimed at examining the causal relationship between CA stenosis and PDA aneurysm by simulating the splanchnic circulation with an electric circuit. A patient with multiple PDA aneurysms and collaterals with CA stenosis was treated in our institution using hybrid techniques. The patient's pre- and postoperative status was simulated using an electric circuit, and the two possible scenarios were tested for compatibility: the stenosis-first scenario vs. the aneurysm-first scenario. The simulation was performed in two ways: using Simulink® software (MATLAB® Release 2018b) and actual circuit construction on a breadboard. The stenosis-first scenario showed that as the CA stenosis progresses, the blood flow through PDA increases, favoring the development of an aneurysm and/or collaterals if the artery was already compromised by a weakening condition. On the other hand, the aneurysm-first scenario also showed that if the aneurysm or collaterals developed first, the aneurysm will steal the blood flow through the CA, causing it to collapse if the artery was already compromised by increased wall tension. Contrary to the common belief, this study showed that in patients suffering from concurrent CA stenosis and PDA aneurysm, either condition could develop first and predispose the development of the other. The simulation of splanchnic blood flow with an electric circuit provides a useful tool for analyzing rare vascular diseases that are difficult to provoke in clinical and animal studies. [ABSTRACT FROM AUTHOR]

In this study, we propose a simple and computationally efficient method based on the multifactor dimensional reduction algorithm to identify gene-gene interactions associated with the survival phenotype. The proposed method, referred to as KM-MDR, uses the Kaplan-Meier median survival time as a classifier. The KM-MDR method classifies multilocus genotypes into a binary attribute for high- or low-risk groups using median survival time and replaces balanced accuracy with log-rank test statistics as a score to determine the best model. Through intensive simulation studies, we compared the power of KM-MDR with that of Surv-MDR, Cox-MDR, and AFT-MDR. It was found that KM-MDR has a similar power to that of Surv-MDR, with less computing time, and has comparable power to that of Cox-MDR and AFT-MDR, even when there is a covariate effect. Furthermore, we apply KM-MDR to a real dataset of ovarian cancer patients from The Cancer Genome Atlas (TCGA). [ABSTRACT FROM AUTHOR]

Coronary heart disease (CHD) is one of the severe health issues and is one of the most common types of heart diseases. It is the most frequent cause of mortality across the globe due to the lack of a healthy lifestyle. Owing to the fact that a heart attack occurs without any apparent symptoms, an intelligent detection method is inescapable. In this article, a new CHD detection method based on a machine learning technique, e.g., classifier ensembles, is dealt with. A two-tier ensemble is built, where some ensemble classifiers are exploited as base classifiers of another ensemble. A stacked architecture is designed to blend the class label prediction of three ensemble learners, i.e., random forest, gradient boosting machine, and extreme gradient boosting. The detection model is evaluated on multiple heart disease datasets, i.e., Z-Alizadeh Sani, Statlog, Cleveland, and Hungarian, corroborating the generalisability of the proposed model. A particle swarm optimization-based feature selection is carried out to choose the most significant feature set for each dataset. Finally, a two-fold statistical test is adopted to justify the hypothesis, demonstrating that the performance differences of classifiers do not rely upon an assumption. Our proposed method outperforms any base classifiers in the ensemble with respect to 10-fold cross validation. Our detection model has performed better than current existing models based on traditional classifier ensembles and individual classifiers in terms of accuracy, F 1 , and AUC. This study demonstrates that our proposed model adds a considerable contribution compared to the prior published studies in the current literature. [ABSTRACT FROM AUTHOR]

A series of sulfonamide-bearing azaheterocyclic Schiff base derivatives 3(a-j) were synthesized as carbonic anhydrase inhibitors. The substituted benzene sulfonyl chlorides 1(a-d) were reacted with N2H4 to get aromatic sulfonyl hydrazides 2(a-d). The intermediate hydrazides 2(a-d) were treated with substituted aldehydes to afford azaheterocyclic sulfonamide Schiff bases 3(a-j). The spectral data of synthesized compounds confirmed the formation of the final products. The inhibitory effects of 3(a-j) on carbonic anhydrase activity were determined, and it was found that derivative 3c exhibited the most potent activity with IC50 0.84 ± 0.12 μ M among all other derivatives and is also more active than standard acetazolamide (IC50 0.91 ± 0.12). The enzyme inhibitory kinetics results determined by Lineweaver-Burk plots revealed that compound 3c inhibits the enzyme by noncompetitive mode of inhibition with K i value 8.6 μM. The molecular docking investigations of the synthesized analogues 3(a-j) were evaluated which assured that synthesized compounds bind well inside the active binding site of the target enzyme. Cytotoxicity on human keratinocyte (HaCaT) and MCF-7 cell lines was performed, and it was found that most of the synthesized analogues were nontoxic on these cell lines and the toxic effects follow the dose-dependent manner. Based on our investigations, it was suggested that analogue 3c may serve as core structure to project carbonic anhydrase inhibitors with greater potency. [ABSTRACT FROM AUTHOR]

Introduction. Airway management plays an essential role in anaesthesia practice, during both elective and urgent surgery procedures and emergency medicine. Aim. The aim of the study was to compare Macintosh laryngoscope (MAC), McGrath, and TruView PCD in 5 separate airway management scenarios. Methods. This prospective cross-over simulation study involved 93 paramedics. All paramedics performed intubation using direct laryngoscope (MAC), McGrath, and TruView PCD video laryngoscopes. The study was performed in 5 different scenarios: (A) normal airway, (B) tongue oedema, (C) pharyngeal obstruction, (D) cervical collar stabilization with tongue oedema, and (E) cervical collar stabilization with pharyngeal obstruction. Results. In scenario A, the success rate was 99% with MAC, 100% with McGrath, and 94% with PCD. Intubation time was 17 s (IQR: 16–21) for MAC, 18 s (IQR: 16–21) for McGrath, and 27 s (IQR: 23–34) for PCD. In scenario B, the success rate was 61% with MAC, 97% with McGrath, and 97% with PCD (p < 0.001). Intubation time was 44 s (IQR: 24–46) for MAC, 22 s (IQR: 20–27) for McGrath, and 39 s (IQR: 30–57) for PCD. In scenario C, the success rate with MAC was 74%, 97% with McGrath, and 72% with PCD (p < 0.001). Intubation time was 21 s (IQR: 19–29) for MAC, 18 s (IQR: 18–24.5) for McGrath, and 30 s (IQR: 23–39) for PCD. In scenario D, the success rate with MAC was 32%, 69% with McGrath, and 58% with PCD (p < 0.001). Intubation time was 26 s (IQR: 20–29) for MAC, 26 s (IQR: 20–29) for McGrath, and 45 s (IQR: 33–56) for PCD. In scenario E, the success rate with MAC was 32%, but 64% with McGrath and 62% with PCD (p < 0.001). Intubation time was 28 s (IQR: 25–39) for MAC, 19 s (IQR: 18–26) for McGrath, and 34 s (IQR: 27–45) for PCD. Conclusions. The McGrath video laryngoscope proved better than Truview PCD and direct intubation with Macintosh laryngoscope in terms of success rate, duration of first intubation attempt, number of intubation attempts, Cormack-Lehane grade, percentage of glottis opening (POGO score), number of optimization manoeuvres, severity of dental compression, and ease of use. [ABSTRACT FROM AUTHOR]

The present study aimed to evaluate the antioxidant and antiproliferative potential of ursolic acid and thujone isolated from leaves of Elaeagnus indica and Memecylon edule and their inhibitory effect on topoisomerase II using molecular docking study. The isolated ursolic acid and thujone were examined for different types of free radicals scavenging activity, the antiproliferative potential on U-937 and HT-60 cell lines by adopting standard methods. Further, these compounds were docked with the active site of the ATPase region of topoisomerase II. The findings of the research revealed that ursolic acid harbor strong antioxidant and antiproliferative capacity with low IC50 values than the thujone in all tested methods. Moreover, ursolic acid shows significant inhibition effect on topoisomerase II with a considerable docking score (−8.0312) and GLIDE energy (−51.86 kca/mol). The present outcome concludes that ursolic acid possesses significant antioxidant and antiproliferative potential, which can be used in the development of novel antioxidant and antiproliferative agents in the future. [ABSTRACT FROM AUTHOR]

Salbutamol (SBAL), a kind of short-acting beta 2-adrenergic agonist, has been mainly used to treat bronchial asthma and other allergic airway diseases clinically. In this study, the interaction mechanism between salbutamol and human serum albumin was researched by the multispectral method and molecular docking. The fluorescence intensity of HSA could be regularly enhanced with the increase of SBAL concentration. Both the results of the multispectral method and molecular docking showed that SBAL could bind HSA with van der Waals force and hydrogen bonds. The binding mechanism was further analysed by UV-Vis and synchronous fluorescence spectra. The contents of the secondary structure of free HSA and SBAL-HSA complex were evaluated using CD spectra. [ABSTRACT FROM AUTHOR]

The simultaneous effect of flexible wall and multiple stenoses on the flow and mass transfer of blood is investigated through numerical computation and simulations. The solution is obtained using the Marker and Cell technique on an axisymmetric model of Newtonian blood flow. The results compare favorably with physical observations where the pulsatile boundary condition and double stenoses result in a higher pressure drop across the stenoses. The streamlines, the iso-concentration lines, the Sherwood number, and the mass concentration variations along the entire wall segment provide a comprehensive analysis of the mass transport characteristics. The double stenoses and pulsatile inlet conditions increase the number of recirculation regions and effect a higher mass transfer rate at the throat, whereby more mass is expected to accumulate and cause further stenosis. [ABSTRACT FROM AUTHOR]

Mutant p53 (R248Q) induces doxorubicin (ADM) resistance in hepatocellular carcinoma (HCC). Dihydroartemisinin (DHA) can synergistically enhance anticancer effect of many chemotherapeutic agents. However, whether DHA could increase therapeutic efficacy of ADM in p53 (R248Q)-expressing HCC cells remains unknown. In the present study, we established mutant p53 (R248Q)-expressing Hep3B cells to study the effect and mechanism of DHA on ADM resistance and the synergistic effect of DHA with ADM. We found that P-gp was highly expressed in p53 (R248Q)-expressing Hep3B cells. As a result, cells expressing p53 (R248Q) displayed higher cell viability and lower cell apoptosis level upon ADM treatment. Meanwhile, phosphorylation levels of ERK1/2 and p65 were elevated in p53 (R248Q)-expressing Hep3B cells. However, combination of DHA and ADM treatment decreased cell viability and elevated cell apoptosis level in p53 (R248Q)-expressing Hep3B cells. Molecular dynamics simulations showed that DHA had the potential to bind with mutant p53 (R248Q) protein. Furthermore, DHA treatment decreased P-gp expression and inhibited phosphorylation levels of ERK1/2 and p65 in p53 (R248Q)-expressing Hep3B cells. Finally, DHA treatment could significantly reduce ADM efflux in p53 (R248Q)-expressing cells. Our results indicate that DHA could decrease P-gp expression via inhibiting the p53 (R248Q)-ERK1/2-NF-κB signaling pathway, which eventually confers sensitization of p53 (R248Q)-expressing HCC cells to ADM. Our study provides evidence for the potential application of DHA and ADM combination in treatment of mutant p53 (R248Q)-harbored HCC. [ABSTRACT FROM AUTHOR]

Objective. The use of a biofabrication nerve scaffold, which mimics the nerve microstructure, as an alternative for autologous nerve transplantation is a promising strategy for treating peripheral nerve defects. This study aimed to design a customized biofabrication scaffold model with the characteristics of human peripheral nerve fascicles. Methods. We used Micro-MRI technique to obtain different nerve fascicles. A full-length 28 cm tibial nerve specimen was obtained and was divided into 14 two-centimetre nerve segments. 3D models of the nerve fascicles were obtained by three-dimensional reconstruction after image segmentation. The central line of the nerve fascicles was fitted, and the aggregation of nerve fascicles was analysed quantitatively. The nerve scaffold was designed by simulating the clinical nerve defect and extracting information from the acquired nerve fascicle data; the scaffold design was displayed by 3D printing to verify the accuracy of the model. Result. The microstructure of the sciatic nerve, tibial nerve, and common peroneal nerve in the nerve fascicles could be obtained by three-dimensional reconstruction. The number of cross fusions of tibial nerve fascicles from proximal end to distal end decreased gradually. By designing the nerve graft in accordance with the microstructure of the nerve fascicles, the 3D printed model demonstrated that the two ends of the nerve defect can be well matched. Conclusion. The microstructure of the nerve fascicles is complicated and changeable, and the spatial position of each nerve fascicle and the long segment of the nerve fascicle aggregation show great changes at different levels. Under the premise of the stability of the existing imaging techniques, a large number of scanning nerve samples can be used to set up a three-dimensional database of the peripheral nerve fascicle microstructure, integrating the gross imaging information, and provide a template for the design of the downstream nerve graft model. [ABSTRACT FROM AUTHOR]

This study aims to delineate the effects of Manilkara zapota Linn. (Sapodilla) fruit chloroform (Mz.CHCl3) and aqueous (Mz.Aq) extracts tested through different techniques. Antidiarrheal activity and intestinal fluid accumulation were examined by using castor oil-induced diarrhea and castor oil fluid accumulation models. Isolated rabbit jejunum tissues were employed for in vitro experiments. Antimotility and antiulcer were performed through charcoal meal transient time and ethanol-induced ulcer assay, molecular studies were conducted through proteomic analysis, and virtual screening was performed by using a discovery studio visualizer (DSV). Mz.CHCl3 and Mz.Aq extracts attributed dose-dependent (50–300 mg/kg) protection (20–100%) against castor oil-induced diarrhea and dose-dependently (50–300 mg/kg) inhibited intestinal fluid secretions in mice. Mz.CHCl3 and Mz.Aq extracts produce relaxation of spontaneous and K+ (80 Mm) induced contractions in isolated tissue preparations and decreased the distance moved by charcoal in the gastrointestinal transit model in rats. It showed gastroprotective effect in ulcerative stomach of rats and decreased levels of IL-18 quantified by proteomic analysis. Histopathological results showed ethanol-induced significant gastric injury, leading to cloudy swelling, hydropic degeneration, apoptosis, and focal necrosis in all gastric zones using hematoxylin and eosin (H&E) staining. Moreover, ethanol increased the activation and the expression of tumor necrotic factor (TNF-α), cyclooxygenase (COX-2), and nuclear factor kappa-light-chain-enhancer of activated B cells (p-NFκB). In silico results were comparative to in vitro results evaluated through virtual screening. Moreover, ethanol increased the activation and expression of tumor necrotic factor, cyclooxygenase, and nuclear factor kappa-light-chain-enhancer of activated B cells. This study exhibits the gastroprotective effect of Manilkara zapota extracts in the peritoneal cavity using a proteomic and in silico approach which reveals different energy values against target proteins, which mediate the gastrointestinal functions. [ABSTRACT FROM AUTHOR]

The brain has the most complex structures and functions in living organisms, and brain networks can provide us an effective way for brain function analysis and brain disease detection. In brain networks, there exist some important neural unit modules, which contain many meaningful biological insights. It is appealing to find the neural unit modules and obtain their affiliations. In this study, we present a novel method by integrating the uniform design into the particle swarm optimization to find community modules of brain networks, abbreviated as UPSO. The difference between UPSO and the existing ones lies in that UPSO is presented first for detecting community modules. Several brain networks generated from functional MRI for studying autism are used to verify the proposed algorithm. Experimental results obtained on these brain networks demonstrate that UPSO can find community modules efficiently and outperforms the other competing methods in terms of modularity and conductance. Additionally, the comparison of UPSO and PSO also shows that the uniform design plays an important role in improving the performance of UPSO. [ABSTRACT FROM AUTHOR]

Pupil blocking force (PBF) can indicate the potential risk of pupil block (PB), which is considered as a main pathogenic factor of primary angle-closure glaucoma (PACG). However, the effect of PB on the PBF under different pupil diameters and iris-lens channel (ILC) distance was unknown. Besides, a simple and practical method to assess PBF has not been reported yet. In this study, 21 finite element models of eyes with various pupil diameters (2.4 mm–2.6 mm) and ILC (2 μm–20 μm) were constructed and were conducted to simulate aqueous humor flow by fluid-solid coupling numerical simulation. PBF in each model was calculated based on the numerical simulation results and was fitted using response surface methodology. The results demonstrated that ILC distance had a more significant effect than pupil diameter on PBF. With the decrease of ILC distance, the PBF increased exponentially. When the reduced distance was lower than 5 μm, the PBF exploded quickly, resulting in a high risk of iris bomb. The PBF also varied with pupil diameter, especially under the condition of narrow ILC. Both ILC distance and pupil diameter could explain more than 97% variation in PBF, and a second-order empirical model has been developed to be a good predictor of PBF. Based on the linear relationship between anterior chamber deformation and PBF, a threshold value of PBF was given to guide clinical decisions. This study could be used to investigate PACG pathological correlation and its pathogenesis, so as to provide a reference value for clinical diagnosis of PACG. [ABSTRACT FROM AUTHOR]

Background and Purpose. Hip dislocation combined with acetabular fracture remains a challenging condition for orthopedic surgeons. In this study, we utilized a computer-assisted simulation and three-dimensional (3D) printing technology to treat patients with hip dislocation combined with acetabular fracture. We hypothesized that the 3D printing-assisted method would shorten the internal fixation time and surgical time. Methods. We retrospectively reviewed 16 patients diagnosed with traumatic posterior dislocation of hip combined with acetabular fractures and treated with plate fixation from September 2013 to August 2017. Patients were divided into two groups: (1) traditional method and (2) 3D printing groups. In the traditional method group, the plates were contoured during the surgery, whereas in the 3D printing group, the patient's pelvic computed tomography image was transformed to the 3D medical image software for processing preoperatively. The fracture reduction was simulated by the computer. Thereafter, the 1:1 scale 3D printing model was used to design the surgical plan and contour patient-specific plates preoperatively. Results. The internal fixation time was significantly shorter in the 3D printing group than in the traditional method group (-33 min, P<0.05). The mean operative time was shorter than that in the traditional method group (-43 min). However, blood loss and postoperative radiograph results were similar between the groups. The complication rate was lower in the 3D printing group (2/7) than in the traditional method group (5/9). Interpretation. Computer-assisted simulation with 3D printing technology is a more efficient method for treating hip dislocation combined with acetabular fractures. [ABSTRACT FROM AUTHOR]

Although thyroid dyshormonogenesis (TDH) accounts for 10-20% of congenital hypothyroidism (CH), the molecular etiology of TDH is unknown in Bangladesh. Thyroid peroxidase (TPO) is most frequently associated with TDH and the present study investigated the spectrum of TPO mutations in Bangladeshi patients and analyzed the effects of mutations on TPO protein structure through in silico approach. Sequencing-based analysis of TPO gene revealed four mutations in 36 diagnosed patients with TDH including three nonsynonymous mutations, namely, p.Ala373Ser, p.Ser398Thr, and p.Thr725Pro, and one synonymous mutation p.Pro715Pro. Homology modelling-based analysis of predicted structures of MPO-like domain (TPO142-738) and the full-length TPO protein (TPO1-933) revealed differences between mutant and wild type structures. Molecular docking studies were performed between predicted structures and heme. TPO1-933 predicted structure showed more reliable results in terms of interactions with the heme prosthetic group as the binding energies were -11.5 kcal/mol, -3.2 kcal/mol, -11.5 kcal/mol, and -7.9 kcal/mol for WT, p.Ala373Ser, p.Ser398Thr, and p.Thr725Pro, respectively, implying that p.Ala373Ser and p.Thr725Pro mutations were more damaging than p.Ser398Thr. However, for the TPO142-738 predicted structures, the binding energies were -11.9 kcal/mol, -10.8 kcal/mol, -2.5 kcal/mol, and -5.3 kcal/mol for the wild type protein, mutant proteins with p.Ala373Ser, p.Ser398Thr, and p.Thr725Pro substitutions, respectively. However, when the interactions between the crucial residues including residues His239, Arg396, Glu399, and His494 of TPO protein and heme were taken into consideration using both TPO1-933 and TPO142-738 predicted structures, it appeared that p.Ala373Ser and p.Thr725Pro could affect the interactions more severely than the p.Ser398Thr. Validation of the molecular docking results was performed by computer simulation in terms of quantum mechanics/molecular mechanics (QM/MM) and molecular dynamics (MD) simulation. In conclusion, the substitutions mutations, namely, p.Ala373Ser, p.Ser398Thr, and p.Thr725Pro, had been involved in Bangladeshi patients with TDH and molecular docking-based study revealed that these mutations had damaging effect on the TPO protein activity. [ABSTRACT FROM AUTHOR]

ATP-binding cassette (ABC) transporters constitute one of the largest gene families in all living organisms, most of which mediate transport across biological membranes by hydrolyzing ATP. However, detailed studies of ABC transporter genes in the important oil crop, soybean, are still lacking. In the present study, we carried out genome-wide identification and phylogenetic and transcriptional analyses of the ABC gene family in G. max. A total of 261 G. max ABC (GmABCs) genes were identified and unevenly localized onto 20 chromosomes. Referring to protein-domain orientation and phylogeny, the GmABC family could be classified into eight (ABCA-ABCG and ABCI) subfamilies and ABCG were the most abundantly present. Further, investigation of whole genome duplication (WGD) signifies the role of segmental duplication in the expansion of the ABC transporter gene family in soybean. The Ka/Ks ratio indicates that several duplicated genes are governed by intense purifying selection during evolution. In addition, in silico expression analysis based on RNA-sequence using publicly available database revealed that ABC transporters are differentially expressed in tissues and developmental stages and in dehydration. Overall, we provide an extensive overview of the GmABC transporter gene family and it promises the primary basis for the study in development and response to dehydration tolerance. [ABSTRACT FROM AUTHOR]

Protein tyrosine phosphatase 1B (PTP1B) is considered a potential target for the treatment of type II diabetes and obesity due to its critical negative role in the insulin signaling pathway. However, improving the selectivity of PTP1B inhibitors over the most closely related T-cell protein tyrosine phosphatase (TCPTP) remains a major challenge for inhibitor development. Lys120 at the active site and Ser27 at the second pTyr binding site are distinct in PTP1B and TCPTP, which may bring differences in binding affinity. To explore the determinant of selective binding of inhibitor, molecular dynamics simulations with binding free energy calculations were performed on K120A and A27S mutated PTP1B, and the internal changes induced by mutations were investigated. Results reveal that the presence of Lys120 induces a conformational change in the WPD-loop and YRD-motif and has a certain effect on the selective binding at the active site. Ser27 weakens the stability of the inhibitor at the second pTyr binding site by altering the orientation of the Arg24 and Arg254 side chains via hydrogen bonds. Further comparison of alanine scanning demonstrates that the reduction in the energy contribution of Arg254 caused by A27S mutation leads to a different inhibitory activity. These observations provide novel insights into the selective binding mechanism of PTP1B inhibitors to TCPTP. [ABSTRACT FROM AUTHOR]