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Missing value imputation (MVI) has been studied for several decades being the basic solution method for incomplete dataset problems, specifically those where some data samples contain one or more missing attribute values. This paper aims at reviewing and analyzing related studies carried out in recent decades, from the experimental design perspective. Altogether, 111 journal papers published from 2006 to 2017 are reviewed and analyzed. In addition, several technical issues encountered during the MVI process are addressed, such as the choice of datasets, missing rates and missingness mechanisms, and the MVI techniques and evaluation metrics employed, are discussed. The results of analysis of these issues allow limitations in the existing body of literature to be identified based upon which some directions for future research can be gleaned.

Magnetic fluid hyperthermia (MFH) is a novel reliable technique with excellent potential for thermal therapies and treating breast tumours. This method involves injecting a magnetic nanofluid into the tumour and applying an external AC magnetic field to induce heat in the magnetic nanoparticles (MNPs) and raise the tumour temperature to ablation temperature ranges. Because of the complexity of considering and coupling all different physics involves in this phenomenon and also due to the intricacy of a thorough FEM numerical study, few FEM-based studies address the entire MFH process as similar to reality as possible. The current study investigates a FEM-based three-dimensional numerical simulation of MFH of breast tumours as a multi-physics problem. An anatomically realistic breast phantom (ARBP) is considered, some magnetic nanofluid is injected inside the tumour, and the diffusion phenomenon is simulated. Then, the amount of heat generated in the MNP-saturated tumour area due to an external AC magnetic field is simulated. In the end, the fraction of tumour tissue necrotized by this temperature rise is evaluated. The study’s results demonstrate that by injecting nanofluid and utilizing seven circular copper windings with each coil carrying 400 A current with a frequency of 400 kHz for generating the external AC magnetic field, the temperature in tumour tissue can be raised to a maximum of about 51.4°C, which leads to necrosis of entire tumour tissue after 30 minutes of electromagnetic field (EMF) exposure. This numerical platform can depict all four various physics involved in the MFH of breast tumours by numerically solving all different equation sets coupled together with high precision. Thus, the proposed model can be utilized by clinicians as a reliable tool for predicting and identifying the approximate amount of temperature rise and the necrotic fraction of breast tumour, which can be very useful to opt for the best MFH therapeutic procedure and conditions based on various patients. In future works, this numerical platform’s results should be compared with experimental in-vivo results to improve and modify this platform in order to be ready for clinical applications.

Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats 1 – 4 . Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans 5 – 7 . Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor—angiotensin converting enzyme II (ACE2)—as SARS-CoV. Characterization of full-length genome sequences from patients infected with a new coronavirus (2019-nCoV) shows that the sequences are nearly identical and indicates that the virus is related to a bat coronavirus.

Idiopathic pulmonary fibrosis (IPF) is characterized by fibrotic change in alveolar epithelial cells and leads to the irreversible deterioration of pulmonary function. Transforming growth factor-beta 1 (TGF-β1)-induced epithelial-mesenchymal transition (EMT) in type 2 lung epithelial cells contributes to excessive collagen deposition and plays an important role in IPF. Atractylodin (ATL) is a kind of herbal medicine that has been proven to protect intestinal inflammation and attenuate acute lung injury. Our study aimed to determine whether EMT played a crucial role in the pathogenesis of pulmonary fibrosis and whether EMT can be utilized as a therapeutic target by ATL treatment to mitigate IPF. To address this topic, we took two steps to investigate: 1. Utilization of anin vitro EMT model by treating alveolar epithelial cells (A549 cells) with TGF-β1 followed by ATL treatment for elucidating the underlying pathways, including Smad2/3 hyperphosphorylation, mitogen-activated protein kinase (MAPK) pathway overexpression, Snail and Slug upregulation, and loss of E-cadherin. Utilization of an in vivo lung injury model by treating bleomycin on mice followed by ATL treatment to demonstrate the therapeutic effectiveness, such as, less collagen deposition and lower E-cadherin expression. In conclusion, ATL attenuates TGF-β1-induced EMT in A549 cells and bleomycin-induced pulmonary fibrosis in mice.

Human infections with zoonotic coronaviruses (CoVs), including severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV, have raised great public health concern globally. Here, we report a novel bat-origin CoV causing severe and fatal pneumonia in humans. We collected clinical data and bronchoalveolar lavage (BAL) specimens from five patients with severe pneumonia from Wuhan Jinyintan Hospital, Hubei province, China. Nucleic acids of the BAL were extracted and subjected to next-generation sequencing. Virus isolation was carried out, and maximum-likelihood phylogenetic trees were constructed. Five patients hospitalized from December 18 to December 29, 2019 presented with fever, cough, and dyspnea accompanied by complications of acute respiratory distress syndrome. Chest radiography revealed diffuse opacities and consolidation. One of these patients died. Sequence results revealed the presence of a previously unknown β-CoV strain in all five patients, with 99.8% to 99.9% nucleotide identities among the isolates. These isolates showed 79.0% nucleotide identity with the sequence of SARS-CoV (GenBank NC_004718) and 51.8% identity with the sequence of MERS-CoV (GenBank NC_019843). The virus is phylogenetically closest to a bat SARS-like CoV (SL-ZC45, GenBank MG772933) with 87.6% to 87.7% nucleotide identity, but is in a separate clade. Moreover, these viruses have a single intact open reading frame gene 8, as a further indicator of bat-origin CoVs. However, the amino acid sequence of the tentative receptor-binding domain resembles that of SARS-CoV, indicating that these viruses might use the same receptor. A novel bat-borne CoV was identified that is associated with severe and fatal respiratory disease in humans.

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

Ferroptosis is a specialized iron-dependent cell death that is associated with lethal lipid peroxidation. Modulation of ferroptosis may have therapeutic potential since it has been implicated in various human diseases as well as potential antitumor activities. However, much remains unknown about the underlying mechanisms and genetic determinants of ferroptosis. Given the critical role of kinases in most biological processes and the availability of various kinase inhibitors, we sought to systemically identify kinases essential for ferroptosis. We performed a forward genetic-based kinome screen against ferroptosis in MDA-MB-231 cells triggered by cystine deprivation. This screen identified 34 essential kinases involved in TNFα and NF-kB signaling. Unexpectedly, the DNA damage response serine/threonine kinase ATM (mutated in Ataxia-Telangiectasia) was found to be essential for ferroptosis. The pharmacological or genetic inhibition of ATM consistently rescued multiple cancer cells from ferroptosis triggered by cystine deprivation or erastin. Instead of the canonical DNA damage pathways, ATM inhibition rescued ferroptosis by increasing the expression of iron regulators involved in iron storage (ferritin heavy and light chain, FTH1 and FTL) and export (ferroportin, FPN1). The coordinated changes of these iron regulators during ATM inhibition resulted in a lowering of labile iron and prevented the iron-dependent ferroptosis. Furthermore, we found that ATM inhibition enhanced the nuclear translocation of metal-regulatory transcription factor 1 (MTF1), responsible for regulating expression of Ferritin/FPN1 and ferroptosis protection. Genetic depletion of MTF-1 abolished the regulation of iron-regulatory elements by ATM and resensitized the cells to ferroptosis. Together, we have identified an unexpected ATM-MTF1-Ferritin/FPN1 regulatory axis as novel determinants of ferroptosis through regulating labile iron levels.

Atherosclerosis-associated cardiovascular disease is one of the main causes of death and disability among patients with diabetes mellitus. However, little is known about the impact of S-nitrosylation in diabetes-accelerated atherosclerosis. Here, we show increased levels of S-nitrosylation of guanine nucleotide-binding protein G(i) subunit alpha-2 (SNO-GNAI2) at Cysteine 66 in coronary artery samples from diabetic patients with atherosclerosis, consistently with results from mice. Mechanistically, SNO-GNAI2 acted by coupling with CXCR5 to dephosphorylate the Hippo pathway kinase LATS1, thereby leading to nuclear translocation of YAP and promoting an inflammatory response in endothelial cells. Furthermore, Cys-mutant GNAI2 refractory to S-nitrosylation abrogated GNAI2-CXCR5 coupling, alleviated atherosclerosis in diabetic mice, restored Hippo activity, and reduced endothelial inflammation. In addition, we showed that melatonin treatment restored endothelial function and protected against diabetes-accelerated atherosclerosis by preventing GNAI2 S-nitrosylation. In conclusion, SNO-GNAI2 drives diabetes-accelerated atherosclerosis by coupling with CXCR5 and activating YAP-dependent endothelial inflammation, and reducing SNO-GNAI2 is an efficient strategy for alleviating diabetes-accelerated atherosclerosis. S-nitrosylation can influence many pathophysiological processes. Here the authors show that the coupling efficiency of GNAI2 with CXCR5 is enhanced by S-nitrosylation of GNAI2, leading to Hippo-YAP dysfunction in endothelium, and plays a role in diabetes-accelerated atherosclerosis.

PIEZO channels respond to piconewton-scale forces to mediate critical physiological and pathophysiological processes 1 – 5 . Detergent-solubilized PIEZO channels form bowl-shaped trimers comprising a central ion-conducting pore with an extracellular cap and three curved and non-planar blades with intracellular beams 6 – 10 , which may undergo force-induced deformation within lipid membranes 11 . However, the structures and mechanisms underlying the gating dynamics of PIEZO channels in lipid membranes remain unresolved. Here we determine the curved and flattened structures of PIEZO1 reconstituted in liposome vesicles, directly visualizing the substantial deformability of the PIEZO1–lipid bilayer system and an in-plane areal expansion of approximately 300 nm 2 in the flattened structure. The curved structure of PIEZO1 resembles the structure determined from detergent micelles, but has numerous bound phospholipids. By contrast, the flattened structure exhibits membrane tension-induced flattening of the blade, bending of the beam and detaching and rotating of the cap, which could collectively lead to gating of the ion-conducting pathway. On the basis of the measured in-plane membrane area expansion and stiffness constant of PIEZO1 (ref. 11 ), we calculate a half maximal activation tension of about 1.9 pN nm −1 , matching experimentally measured values. Thus, our studies provide a fundamental understanding of how the notable deformability and structural rearrangement of PIEZO1 achieve exquisite mechanosensitivity and unique curvature-based gating in lipid membranes. Cryo-electron microscopy structures of PIEZO1 in liposome vesicles in curved and flattened conformations demonstrate the high deformability underlying the high mechanosensitivity and ion selectivity of PIEZO channel gating.

Recurrent breast cancer presents significant challenges with aggressive phenotypes and treatment resistance. Therefore, novel therapeutics are urgently needed. Here, we report that murine recurrent breast tumor cells, when compared with primary tumor cells, are highly sensitive to ferroptosis. Discoidin Domain Receptor Tyrosine Kinase 2 (DDR2), the receptor for collagen I, is highly expressed in ferroptosis-sensitive recurrent tumor cells and human mesenchymal breast cancer cells. EMT regulators, TWIST and SNAIL, significantly induce DDR2 expression and sensitize ferroptosis in a DDR2-dependent manner. Erastin treatment induces DDR2 upregulation and phosphorylation, independent of collagen I. Furthermore, DDR2 knockdown in recurrent tumor cells reduces clonogenic proliferation. Importantly, both the ferroptosis protection and reduced clonogenic growth may be compatible with the compromised YAP/TAZ upon DDR2 inhibition. Collectively, these findings identify the important role of EMT-driven DDR2 upregulation in recurrent tumors in maintaining growth advantage but activating YAP/TAZ-mediated ferroptosis susceptibility, providing potential strategies to eradicate recurrent breast cancer cells with mesenchymal features.