The history of data stored can be used to forecast potential patterns and help companies make competitive decisions to increase their success and benefits. Many analysts look at healthcare sector ...data to identify and forecast illnesses in order to benefit patients and physicians in a variety of ways. This study is concerned with the diagnosis and estimation of heart disease. Heart disease is one of the most dangerous illnesses for humans, leading to death all over the world. Many different groups of researchers have used knowledge exploration methods in diverse fields to forecast heart disease and have shown acceptable degrees of precision. There were no real-time methods for analyzing and forecasting heart disease in its early stages. For the prediction of heart disease, decision trees are used to analyze various training and evaluation datasets. Classification algorithms such as Naive Bayes, ID3, C4.5, and SVM are being investigated. The UCI machinery heart disease data set is used in experimental studies.
Endometriosis is a complex gynecological disease that affects more than 10% of women in their reproductive years. While surgery can provide temporary relief from women's pain, symptoms often return ...in as many as 75% of cases within two years. Previous literature has contributed to theories about the development of endometriosis; however, the exact pathogenesis and etiology remain elusive. We conducted a preliminary investigation into the influence of primary endometrial cells (ECs) on the development and progression of endometriosis. In vitro studies, they were involved in inducing Lipopolysaccharide (LPS) in rat-isolated primary endometrial cells, which resulted in increased nuclear factor-kappa B (NF-κB) and vascular endothelial growth factor (VEGF) mRNA gene expression (quantitative polymerase chain reaction analysis, qPCR) and protein expression (western blot analysis). Additionally, in vivo studies utilized autogenic and allogeneic transplantations (rat to rat) to investigate endometriosis-like lesion cyst size, body weight, protein levels (immunohistochemistry), and mRNA gene expression. These studies demonstrated that estrogen upregulates the gene and protein regulation of cytoskeletal (CK)-18, transforming growth factor-β (TGF-β), VEGF, and tumor necrosis factor (TNF)-α, particularly in the peritoneum. These findings may influence cell proliferation, angiogenesis, fibrosis, and inflammation markers. Consequently, this could exacerbate the occurrence and progression of endometriosis.
Sulfur-based denitrification process has attracted increasing attentions because it does not rely on the external addition of organics and avoids the risk of COD exceeding the limit. Traditionally, ...limestone is commonly employed to maintain a neutral condition (SLAD process), but it may reduce the efficiency as the occupied zone by limestone cannot directly contribute to the denitrification. In this study, we propose a novel sulfur-based denitrification process by coupling with iron(II) carbonate ore (SICAD system). The ore was demonstrated to play roles as the buffer agent and additional electron donor. Moreover, the acid produced through sulfur driven denitrification was found to promote the Fe(II) leaching from the ore and likely extend the reaction zone from the surface to the liquid. As a result, more biomass was accumulated in the SICAD system compared with the controls (sulfur, iron(II) carbonate ore and SLAD systems). Owing to these synergistic effects of sulfur and iron(II) carbonate on denitrification, SICAD system showed much higher denitrification rate (up to 720.35 g·N/m3·d) and less accumulation of intermediates (NO2 – and N2O) than the controls. Additionally, sulfate production in SICAD system was reduced. These findings offer great potential of SICAD system for practical use as a highly efficient postdenitrification process.
Epistasis detection is vital to determining disease susceptibility in the human genome. With rapid advances in technology, multifactor dimensionality reduction (MDR) has become an effective algorithm ...for epistasis detection. Classification of high-risk (H) and low-risk (L) groups in MDR operations is a key topic, but it has not been thoroughly investigated. In this paper, we propose an improved fuzzy c-means-based entropy (FCME) approach to address the limitations of binary classification. For this approach, the degree of membership in MDR, referred to as FCMEMDR, was used. The FCME approach and MDR measure were integrated to enable more precise differentiation between similar frequencies of multifactor genotypes in the cases of possible epistasis. We used the MDR measures of correct classification rate and likelihood ratio. Numerous simulated datasets were applied, and the experimental results revealed two measures of FCMEMDR with higher detection rates than those of other MDR-based algorithms. Our analysis of binary and fuzzy classifications in MDR operations may offer insights into the problem of uncertainty in H/L classification. Two measures of FCMEMDR detected significant instances of epistasis associated with coronary artery disease in the Wellcome Trust Case Control Consortium dataset. FCMEMDR is freely available at https://gitlab.com/yudalinemail/fcmemdr .
Human immunodeficiency virus (HIV) exploits the sequence variation and structural dynamics of the envelope glycoprotein gp120 to evade the immune attack of neutralization antibodies, contributing to ...various HIV neutralization phenotypes. Although the HIV neutralization phenotype has been experimentally characterized, the roles of rapid sequence variability and significant structural dynamics of gp120 are not well understood. Here, 45 prefusion gp120 from different HIV strains belong to three tiers of sensitive, moderate, and resistant neutralization phenotype are structurally modeled by homology modeling and then investigated by molecular dynamics (MD) simulations and graph machine learning (ML). Our results show that the structural deviations, population distribution, and conformational flexibility of gp120 are related to the HIV neutralization phenotype. Per‐residue dynamics indicate the local regions especially in the second structural elements with high‐flexibility, may be responsible for the HIV neutralization phenotype. Moreover, a graph ML model with the attention mechanism was trained to explore inherent representation related to the classification of the HIV neutralization phenotype, further distinguishing the strong related gp120 sequence variation together with structural dynamics in the HIV neutralization phenotype. Our study not only deciphers gp120 sequence variation and structural dynamics in the HIV neutralization phenotype but also explores complex relationships between the sequence, structure, and dynamics of protein by combining MD simulations and ML.
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•A novel UV-EFCM filtration system was developed.•Low-concentration antibiotic contaminant was efficiently degraded.•The antibacterial activity was thoroughly eliminated with UV light ...pretreatment.•Specific energy consumption of the integrated system was significantly reduced.•Integrated system has the potential to tackle the problem of antibiotic pollution.
Antibiotics, especially halogenated antibiotics, which account for nearly 40% of the total antibiotics in China, pose great environmental risks; however, the superior stability of C–F bond and low concentrations hinder their degradation, indicating the need for developing of highly efficient treatment technologies. There is an additional concern that some degradation products could be as active/toxic as or even more than their parent compound. The stable C–F bond can be relative easily cleaved by UV light irradiation, which could come from sunlight. Herein, a novel UV-driven electro-Fenton catalytic membrane (UV-EFCM) filtration system that favors resistance elimination and efficient degradation of low-concentration antibiotics is proposed for the first time. The photo-electrochemical/electro-Fenton (PEC/EF) coupling reaction is synchronously conducted in a sequential filtration system. Almost complete degradation and high mineralization (78.4 ± 9.1%) of florfenicol were achieved at a concentration of as low as 14 µM with the hydraulic retention time of 0.98 h during the UV-EFCM filtration system. Complete elimination of its antibacterial activity, and significant defluorination improvement (56 ± 3.6%) compared to electro-Fenton filtration process (11 ± 5.3%) were achieved due to the prior cleavage of the stable C–F bond with antibiotic potency under UV light pretreatment. This study thus proposes a novel UV-EFCM filtration system, which couples PEC and EF with a potential to tackle the environmental problems associated with antibiotic pollution.
Gemcitabine (GEM) drug resistance remains a difficult challenge in pancreatic ductal adenocarcinoma (PDAC) treatment. Therefore, identifying a safe and effective treatment strategy for PDAC is ...urgent. Lucidone is a natural compound extracted from the fruits of Lindera erythrocarpa Makino. However, the role of lucidone in PDAC inhibition remains unclear. In addition, high‐mobility group box 1 (HMGB1) and receptor for advanced glycation end products (RAGE) are involved in multidrug resistance protein 1 (MDR1) regulation and GEM resistance. Thus, this study aimed to explore the function of lucidone in tumor cytotoxicity and chemosensitivity through the suppression of RAGE‐initiated signaling in PDAC cells. The data showed that lucidone significantly promoted apoptotic cell death and inhibited the expression of autophagic proteins (Atg5, Beclin‐1, LC3‐II, and Vps34) and MDR1 by inhibiting the HMGB1/RAGE/PI3K/Akt axis in both MIA Paca‐2 cells and MIA Paca‐2GEMR cells (GEM‐resistant cells). Notably, convincing data were also obtained in experiments involving RAGE‐specific siRNA transfection. In addition, remarkable cell proliferation was observed after treatment with lucidone combined with GEM, particularly in MIA Paca‐2GEMR cells, indicating that lucidone treatment enhanced chemosensitivity. Collectively, this study provided the underlying mechanism by which lucidone treatment inhibited HMGB1/RAGE‐initiated PI3K/Akt/MDR1 signaling and consequently enhanced chemosensitivity in PDAC.
Physical therapists play a crucial role in guiding patients through effective and safe rehabilitation processes according to medical guidelines. However, due to the therapist-patient imbalance, it is ...neither economical nor feasible for therapists to provide guidance to every patient during recovery sessions. Automated assessment of physical rehabilitation can help with this problem, but accurately quantifying patients' training movements and providing meaningful feedback poses a challenge. In this paper, an Expert-knowledge-based Graph Convolutional approach is proposed to automate the assessment of the quality of physical rehabilitation exercises. This approach utilizes experts' knowledge to improve the spatial feature extraction ability of the Graph Convolutional module and a Gated pooling module for feature aggregation. Additionally, a Transformer module is employed to capture long-range temporal dependencies in the movements. The attention scores and weight matrix obtained through this approach can serve as interpretability tools to help therapists understand the assessment model and assist patients in improving their exercises. The effectiveness of the proposed method is verified on the KIMORE dataset, achieving state-of-the-art performance compared to existing models. Experimental results also illustrate the interpretability of the method in both spatial and temporal dimensions.
Abstract
Primers are critical for polymerase chain reaction (PCR) and influence PCR experimental outcomes. Designing numerous combinations of forward and reverse primers involves various primer ...constraints, posing a computational challenge. Most PCR primer design methods limit parameters because the available algorithms use general fitness functions. This study designed new fitness functions based on user-specified parameters and used the functions in a primer design approach based on the multiobjective particle swarm optimization (MOPSO) algorithm to address the challenge of primer design with user-specified parameters. Multicriteria evaluation was conducted simultaneously based on primer constraints. The fitness functions were evaluated using 7425 DNA sequences and compared with a predominant primer design approach based on optimization algorithms. Each DNA sequence was run 100 times to calculate the difference between the user-specified parameters and primer constraint values. The algorithms based on fitness functions with user-specified parameters outperformed the algorithms based on general fitness functions for 11 primer constraints. Moreover, MOPSO exhibited superior implementation in all experiments. Practical gel electrophoresis was conducted to verify the PCR experiments and established that MOPSO effectively designs primers based on user-specified parameters.
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