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Protein Fold Recognition Algorithms-A General Survey

Protein Fold Recognition Algorithms-A General Survey

The paper comprises the survey results in the developing area of protein folding that proffers many computational and mathematical problems. Further, the analysis have been done regarding various methods and techniques such as evolutionary algorithms, genetic algorithms, Support Vector Machine (SVM), Neural networks, Bayesian Network, etc., It is obvious from the research that a vital element for a structure survey is a library of protein folds that aligns all the known or defined structures into fold-families. From the results, the authors claimed that the protein fold recognition for long pattern protein sequences is a great confrontation for many years. However, the computational complexity can be solved by effective parallelization of evolutionary methods, which can also afford better performance in protein folding. As a future work, protein folding using some extended genetic algorithms along with evolutionary conceits is of great and valuable interest.
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A Deeply Glimpse into Protein Fold Recognition

A Deeply Glimpse into Protein Fold Recognition

Thomas W. proposed protein fold class prediction using neural networks with tailored early-stopping [22]. This method consists of two stages: first the training patterns are used completely for gradient calculation and then they are split into a training and validation data set. This led to good generalizing neural networks. The experiments showed that standard feed-forward neural networks combined with an appropriate regularization scheme can classify the fold class of a protein given solely its primary and it outperformed the standard statistical approaches (like the nearest neighbor method etc and did not perform worse than Support Vector Machines (SVMs). Nan Jiang et al. proposed MESSM which is a protein fold recognition model with mixed environment- specific substitution mapping [21]. It has three key features: a structurally-derived substitution score generated using neural networks, a mixed environment specific substitution mapping developed by combing the structural-derived substitution score with sequence profile from well-developed sequence substitution matrices, and a support vector machine employed to measure the significance of the sequence-structure alignment. MESSM is tested on two benchmark problems; Wallner’s Benchmark and Fischer’s Benchmark, and MESSM was found to lead to a good performance on protein fold recognition.
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Fast Nonnegative Matrix Factorization and Its Application for Protein Fold Recognition

Fast Nonnegative Matrix Factorization and Its Application for Protein Fold Recognition

Linear and unsupervised dimensionality reduction via matrix factorization with nonnegativity constraints is studied. Because of these constraints, it stands apart from other linear dimensionality reduction methods. Here we explore nonnegative matrix fac- torization in combination with three nearest-neighbor classifiers for protein fold recognition. Since typically matrix factorization is iteratively done, convergence, can be slow. To speed up convergence, we perform feature scaling (normalization) prior to the beginning of iterations. This results in a significantly (more than 11 times) faster algorithm. Justification of why it happens is pro- vided. Another modification of the standard nonnegative matrix factorization algorithm is concerned with combining two known techniques for mapping unseen data. This operation is typically necessary before classifying the data in low-dimensional space. Combining two mapping techniques can yield better accuracy than using either technique alone. The gains, however, depend on the state of the random number generator used for initialization of iterations, a classifier, and its parameters. In particular, when employing the best out of three classifiers and reducing the original dimensionality by around 30%, these gains can reach more than 4%, compared to the classification in the original, high-dimensional space.
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A knowledge-based approach to protein structure prediction

A knowledge-based approach to protein structure prediction

Chapter 2 describes the details of our investigations performed to check the fold-discriminatory potentials of various sequence- and structure-based features and develop a new SVM-based method for protein fold recognition. Of the various features investigated structural information of amino acid residues and amino acid residue pairs viz., secondary structural state frequencies with solvent accessibility state frequencies of amino acids and amino acid pairs gave rise to the best fold-discrimination and therefore they were used as feature vectors for training SVMs. Twofold as well as fivefold cross- validation studies using a standard benchmark test datasets revealed that the new method so developed outperforms all other available methods.
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PFP RFSM: Protein fold prediction by using random forests and sequence motifs

PFP RFSM: Protein fold prediction by using random forests and sequence motifs

Protein tertiary structure is indispensible in revealing the biological functions of proteins. De novo perdition of protein tertiary structure is dependent on protein fold recognition. This study proposes a novel method for prediction of protein fold types which takes pri- mary sequence as input. The proposed method, PFP- RFSM, employs a random forest classifier and a com- prehensive feature representation, including both se- quence and predicted structure descriptors. Particu- larly, we propose a method for generation of features based on sequence motifs and those features are firstly employed in protein fold prediction. PFP- RFSM and ten representative protein fold predictors are validated in a benchmark dataset consisting of 27 fold types. Experiments demonstrate that PFP-RFSM outperforms all existing protein fold predictors and improves the success rates by 2% - 14%. The results suggest sequence motifs are effective in classification and analysis of protein sequences.
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Two-layer SVM classifier for remote protein homology detection and fold recognition

Two-layer SVM classifier for remote protein homology detection and fold recognition

Since using these procedures is unpractical for the amount of data available, researchers are increasingly relying on computational techniques to automate the process. Accurately detecting homologs at low levels of sequence similarity or known as remote homology detection still remains a challenging problem to biologists. Remote protein homology detection refers to detection of structural homology in proteins where there are small or no similarity in the sequence. The remote protein homology detection is a classic problem and it aims to identify for a given protein or protein family from a large database of sequences, all distantly protein sequences are related. The principal idea behind homology is based on evolution; proteins that belong to the same family have evolutionary pressure to retain common regions associated with their biochemical function and maintenance of 3D fold. Fold recognition on the other hand is a key step in the protein structure discovery process, especially when traditional protein sequence comparison methods fail to yield convincing structural homologies. Although many methods have been developed for protein fold recognition, their accuracies remain low. This can be attributed to insufficient exploitation of fold discriminatory features.
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Protein Remote Homology Detection and Fold Recognition based on Features Extracted from Frequency Profiles

Protein Remote Homology Detection and Fold Recognition based on Features Extracted from Frequency Profiles

A recently established fold benchmark [15] is used for protein fold recognition. The benchmark contains 3840 proteins from 374 superfamilies and 86 superfamilies are tested. These proteins extracted from SCOP version 1.67 are filtered with Astral database [21] and contain no pair with a sequence similarity more than 95%. The proteins with lengths less than 30 are also removed. For each tested superfamily, there are at least 10 proteins in its positive training and test set. The proteins within one superfamily are taken as positive test samples, while the others in the same fold are taken as positive training examples. The negative test samples are selected from one random superfamily from each of the other folds and the negative training samples are selected from the remaining proteins. Because most of the proteins within a fold have a very low degree of similarity, this fold benchmark is considerably harder than the superfamily benchmark.
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EBV miR-BART10-3p Promotes Cell Proliferation and Migration by Targeting DKK1

EBV miR-BART10-3p Promotes Cell Proliferation and Migration by Targeting DKK1

Figure 5. Effect of DKK1 knockdown using siDKK1 in AGS cells. AGS cells were transfected with 20 nM siDKK1 or control siRNA. (A) A real-time RT-PCR analysis of DKK1 mRNA expression was carried out using a SYBR green qPCR kit. (B) DKK1 and β-catenin protein levels were analyzed by Western blot analysis. Anti-β-actin antibody was used as a loading control. (C) Western blots were performed on two additional sets of independently transfected AGS cells. Results were normalized to β-actin and are expressed as ratios. (D) At the indicated times after transfection, 20 µl of MTT solution was added to each well to assess cell proliferation. (E) Widths between wound edges were evaluated using ImageJ software. The percentages of wound closure from three independent experiments are shown as bar graphs. Error bars indicate the SD (n=3).
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Suppression of nodulation gene expression in bacteroids of Rhizobium leguminosarum biovar viciae

Suppression of nodulation gene expression in bacteroids of Rhizobium leguminosarum biovar viciae

levels of NodA, NodI, NodE, and NodO proteins were reduced at least 14-fold in bacteroids compared with cultured cells, whereas NodD protein was reduced only 3-fold.. Northern (RNA) blot[r]

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The Rise and Fall of the Hydrophobic Effect in Protein Folding and Protein Protein Association, and Molecular Recognition

The Rise and Fall of the Hydrophobic Effect in Protein Folding and Protein Protein Association, and Molecular Recognition

In the beginning everything was explained in Biochemistry in terms of hydrogen-bonds (HB). Then, the de- vastating blow, known as the HB-inventory argument came; hydrogen bonding with water molecules com- pete with intramolecular hydrogen-bonds. As a result, the HBs paradigm fell from grace. The void that was created immediately filled by Kauzmann’s idea of hydrophobic ( H O  ) effect which reigned supreme in bio- chemical literature for over 50 years (1960-2010). Cracks in the HB-inventory argument on one hand, and doubts about the adequacy of Kauzmann’s model for the H O  effect, have led to a comeback of the HBs, along with a host of new hydrophilic ( H I  ) effects. The H O  effects lost much of its power—which it never really had-in explaining protein folding and protein-protein association. Instead, the more powerful and richer repertoire of H I  effects took over the reins. The H I  interactions also offered simple and straightforward answers to the problems of protein folding, and protein-protein association.
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p53 directly activates cystatin D/CST5 to mediate mesenchymal- epithelial transition: a possible link to tumor suppression by vitamin D3

p53 directly activates cystatin D/CST5 to mediate mesenchymal- epithelial transition: a possible link to tumor suppression by vitamin D3

Cystatin D/CST5 encodes an inhibitor of cysteine proteases of the cathepsin family and is directly induced by the vitamin D receptor (VDR). Interestingly, vitamin D3 exerts tumor suppressive effects in a variety of tumor types. In colorectal cancer (CRC) cells CST5 was shown to mediate mesenchymal-epithelial transition (MET). We recently performed an integrated genomic and proteomic screen to identify targets of the p53 tumor suppressor in CRC cells. Thereby, we identified CST5 as a putative p53 target gene. Here, we validated and characterized CST5 as a direct p53 target gene. After activation of a conditional p53 allele, CST5 was upregulated on mRNA and protein levels. Treatment with nutlin-3a or etoposide induced CST5 in a p53- dependent manner. These regulations were direct, since ectopic and endogenous p53 occupied a conserved binding site in the CST5 promoter region. In addition, treatment with calcitriol, the active vitamin D3 metabolite, and simultaneous activation of p53 resulted in enhanced CST5 induction and increased repression of SNAIL, an epithelial- mesenchymal transition (EMT) inducing transcription factor. Furthermore, CST5 inactivation decreased p53-induced mesenchymal-epithelial transition (MET) as evidenced by decreased inhibition of SNAIL and of migration by p53. Furthermore, CST5 expression was directly repressed by SNAIL. In summary, these results imply CST5 as an important mediator of tumor suppression by p53 in colorectal cancer. In addition, they suggest that a combined treatment activating p53 and the vitamin D3 pathway may function via induction of CST5.
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A proteomic analysis of serum-derived exosomes in rheumatoid arthritis

A proteomic analysis of serum-derived exosomes in rheumatoid arthritis

As mentioned above, exosomes have various immuno- logical functions and are thus expected to play roles in the pathophysiology of RA. For instance, fibroblast-like synoviocyte (FLS)-derived exosomes were reported to contain citrullinated proteins [15] and a membrane form of TNF- α [16]. IL-1 β -stimulated FLS-derived exosomes were reported to up-regulate the matrix metalloproteinase (MMP)-13 expression in chondrocytes [17]. We showed that IL-1 β and anti-rheumatic drugs of salazosulfapyridine (SASP) and methotrexate (MTX) considerably altered the protein profiles of exosomes derived from SW982 of syn- ovial sarcoma cell line [18]. Recently, it was reported that some serum exosomal proteins in patients with RA might be useful parameters of disease activity [19]. In terms of bone formation and resorption, osteoclast-derived exo- somes containing microRNA (miR-214) were reported to play an inhibitory role in osteoblast activity [20, 21]. However, at present, the roles of exosomes in RA are largely unclear.
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Impact of combined acidic and hyperosmotic shock conditions on the proteome of Listeria monocytogenes ATCC 19115 in a time course study

Impact of combined acidic and hyperosmotic shock conditions on the proteome of Listeria monocytogenes ATCC 19115 in a time course study

In the present study, we aimed to identify differentially expressed proteins over a range of different sampling times (5, 30, and 60 min), using iTRAQ techniques with the ob- jective of acquiring new and confirming existing insights into the cellular response strategy developed by L. mono- cytogenes to survive in nongrowth permissive low pH and high-salinity stress conditions. In the previous studies, we observed mRNA is stabilized in inactivated cells [18]. This suggests there may be a short window of time for protein synthesis to aid survival of cells. Prior experiments have revealed a subpopulation of cells that survive (0.01–1%) with the proportion increasing with temperature and showing longer survival time in a classic Weibull-type relationship [18]. However, the underlying physiological reasons for this survival remain unclear. Therefore, knowing how L. mon- ocytogenes mechanistically responds to multiple stresses might enable the development of innovative food safety strategies for controlling listerial contamination especially in high-risk foods, such as those with minimal thermal pro- cessing and which tend to be stored for prolonged times at chill temperatures.
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Structural Changes in Dengue Virus When Exposed to a Temperature of 37°C

Structural Changes in Dengue Virus When Exposed to a Temperature of 37°C

changes on the surface of DENV presented here is different from the virus structure as observed in the cryo-EM Fab 1A1D-2– DENV complex structure (12). Binding of antibody 1A1D-2 re- quires the structural changes of the virion in order to expose the partially hidden epitopes. Thus, Fab 1A1D-2 was thought to trap the DENV surface in a state of motion. Comparison between the class III structure and the Fab 1A1D-2–DENV complex structure showed vastly different E protein organization, especially near the 5-fold and 3-fold vertices (molecules A and C, respectively) (Fig. 6A). These two E proteins were bound by Fab molecules in the 1A1D-2–DENV complex, suggesting that the conformation changes of these two E proteins were induced by Fab binding. In addition, the fusion loops of these molecules in the Fab 1A1D-2– DENV complex were interacting with its viral membrane. The structure is therefore unlikely to represent part of the natural structural motion as the fusion loop will not be available for in- fection. For the E protein near the 2-fold vertices (B molecule), the two structures showed that the 1A1D-2 epitope on domain III gradually turned inwards, eventually facing the viral lipid mem- brane in the 1A1D-2–DENV structure (Fig. 6B). This is consistent with the observation that antibody 1A1D-2 is unable to bind to the B molecule.
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NF-κB activation in myeloid cells mediates ventilator-induced lung injury

NF-κB activation in myeloid cells mediates ventilator-induced lung injury

[15]. In contrast, it was reported that IL-6 beneficially limited the disruption of alveolar barrier and regulated neutrophils adhesion and migration [8]. However, ele- vated IL-6 levels have been observed in most experi- mental VILI models and IL-6 can be a biological maker of VALI [6,16]. In this study, the steady increase of IL-6 levels in the lung and BALF were observed after ventilation as demonstrated by mRNA or protein de- tection. To investigate the role of IL-6 in this VILI model, a specific IL-6-blocking antibody (0.25 mg/kg) was intraperitoneally injected to WT mice just before high-stretch ventilation, which had significant thera- peutic effects in the arthritis [28]. After 6 hr of ventila- tion procedure, mice pretreated with IL-6-blocking antibodies showed a decrease in proinflammatory cyto- kines and adhesion molecules when compared with high tidal volume group. Besides, blocking IL-6 pro- duction in VILI had positive effects as demonstrated by decreased lung damage. This suggests that IL-6
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Computational analysis of protein sequence and structure

Computational analysis of protein sequence and structure

In the previous sections, the discussion of the relative performance of various pre­ diction methods has been kept to a minimum. W hilst many secondary structure prediction methods have been tested on the same or similar sets of proteins, there is no substitute for predictions of structures not yet determined experimentally (blind predictions). A number of these have taken place over the years through collabora­ tion between experimentalists and predictors (Russell & Barton, 1993, this paper gives a summary of pre-1993 blind predictions). Recently, however, extensive blind trials of comparative modelling, fold recognition, ab initio prediction and docking have been undertaken at two international meetings under the title of Critical A s ­ sessment of Structure Prediction at Asilomar in California, USA. The organisers of the meetings requested sequences of proteins which were under study by X-ray crystallography or NMR spectroscopy. Blind predictions were then gathered until the expiry dates set for each target sequence (for example before structures were made public). The clear benefit of this coordinated approach is the evaluation of prediction results on the same targets using the same criteria. The meetings also provide a focus for predictors and delineate between those who are prepared to see their work tested in public and those who are not. Their main drawback is the relatively small and/or variable number of targets in some categories (docking and fold recognition in particular). The results and evaluation of the first meeting (CA SPl, December 1994) are available in a special edition of Proteins: Structure^ Function and Genetics (Lattm an, 1995). Summaries of CASP2 (December 1996) have already been published (Dunbrack et ai, 1997; Marchler-Bauer & Bryant, 1997), although a forthcoming edition of Proteins: Structure, Function and Ge­ netics will give the definitive analysis. Some conclusions from CASP 2 will also be
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OCR4all - An Open-Source Tool Providing a (Semi-)Automatic OCR Workflow for Historical Printings

OCR4all - An Open-Source Tool Providing a (Semi-)Automatic OCR Workflow for Historical Printings

Abstract: Optical Character Recognition (OCR) on historical printings is a challenging task mainly due to the complexity of the layout and the highly variant typography. Nevertheless, in the last few years great progress has been made in the area of historical OCR, resulting in several powerful open-source tools for preprocessing, layout recognition and segmentation, character recognition and post-processing. The drawback of these tools often is their limited applicability by non-technical users like humanist scholars and in particular the combined use of several tools in a workflow. In this paper we present an open-source OCR software called OCR4all, which combines state-of-the-art OCR components and continuous model training into a comprehensive workflow. A comfortable GUI allows error corrections not only in the final output, but already in early stages to minimize error propagations. Further on, extensive configuration capabilities are provided to set the degree of automation of the workflow and to make adaptations to the carefully selected default parameters for specific printings, if necessary. Experiments showed that users with minimal or no experience were able to capture the text of even the earliest printed books with manageable effort and great quality, achieving excellent character error rates (CERs) below 0.5%. The fully automated application on 19 th century novels showed that OCR4all can considerably outperform the commercial state-of-the-art tool ABBYY Finereader on moderate layouts if suitably pretrained mixed OCR models are available. The architecture of OCR4all allows the easy integration (or substitution) of newly developed tools for its main components by standardized interfaces like PageXML, thus aiming at continual higher automation for historical printings.
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Conservation and Divergence of the I-Domain Inserted into the Ubiquitous HK97 Coat Protein Fold in P22-Like Bacteriophages

Conservation and Divergence of the I-Domain Inserted into the Ubiquitous HK97 Coat Protein Fold in P22-Like Bacteriophages

In conclusion, this study highlights that the six-stranded anti-parallel ␤ -barrel pro- tein module that occurs in the HK97 folds of coat proteins from the P22-like phage cluster has important differences in structural properties. These differences emphasize the complex coevolution of structure and function of phage and virus capsid proteins. These include the following: (i) variations in elements of secondary structure and functionally important flexible loop regions that participate in capsid assembly, (ii) differences in charges at the interface used to dock the I-domain to the coat protein core, and (iii) differences in TUT sequence motifs displayed on the capsid surface that could comprise carbohydrate binding moieties. Thus, while the HK97 fold is one of the most ubiquitous structural motifs in nature, the many embellishments that have been added to the structure suggest that a significant degree of structural adaptability is required to fulfill its versatile range of specific functional requirements.
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Linear Classifier with Reject Option for the Detection of Vocal Fold Paralysis and Vocal Fold Edema

Linear Classifier with Reject Option for the Detection of Vocal Fold Paralysis and Vocal Fold Edema

nearest mean one for detecting vocal fold paralysis in male utterances and vocal fold edema in female utterances was assessed in [29]. The subjects were called to articulate the sustained vowel “ah” (/a/). From each recording, two central frames were selected among the ones that belong to the most stationary portion of the sustained speech signal as is proposed in [41, 42]. 14-order linear prediction coe ffi cients (LPCs) were extracted from each frame. The dimensionality of the raw feature vector was then reduced to 2 by PCA. Receiver operating characteristic (ROC) curves for the Fisher linear classifier were demonstrated. It was shown that a probability of detection close to 85% could be achieved for a probability of false alarm 10% in the case of vocal fold paralysis in male utterances, while the probability of detection for vocal fold edema in female utterances was found to be approximately 73% at the same probability of false alarm. The nearest mean classifier was found to outperform K -nearest neighbor classifiers for K = 1, 2, 3 in both experiments. Two linear classifiers were examined in [32]. The first one is based on a sample-based optimal linear classifier design [43], while the second one is based on the dual-space linear discriminant analysis [44]. Again 14 LPCs were extracted by processing utterances corresponding to the sustained vowel “ah.” Both the rectangular and the Hamming window are used to extract the speech frames [45]. The assessment of the classifiers studied in [32] was done by estimating the probability of false alarm and the probability of detection using the leave-one-out method. The parametric classifier was found to be more accurate than the dual space linear discriminant classifier. In particular, a slightly higher probability of detection for vocal fold paralysis in men was measured, that is approximately equal to 90% for probability of false alarm 10%. The gain in the probability of detection for vocal fold edema in women was 20% higher than that achieved by the Fisher linear discriminant in [29]. LPCs, LPC-derived cepstral coefficients, and mel frequency cepstal coefficients were extracted for vocal fold edema detection in [33]. A vector quantizer was trained based on the distance between the feature vectors. Experiments were conducted by using 53 normal speakers and another 67, who were diagnosed with voice pathologies including vocal fold edema. Only a single operating point was reported, which yields probability of detection approximately 73% for probability of false alarm 4% [33]. For the same probability of false alarm, a probability of detection, which falls between 80.95% for rectangular window and 90.47% for Hamming window, was reported in [32].
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BPI-fold (BPIF) containing/plunc protein expression in human fetal major and minor salivary glands.

BPI-fold (BPIF) containing/plunc protein expression in human fetal major and minor salivary glands.

Abstract: The aim of this study was to determine expression, not previously described, of PLUNC (palate, lung, and nasal epithelium clone) (BPI-fold containing) proteins in major and minor salivary glands from very early fetal tissue to the end of the second trimester and thus gain further insight into the function of these proteins. Early fetal heads, and major and minor salivary glands were collected retrospectively and glands were classified according to morphodifferentiation stage. Expression of BPI-fold containing proteins was localized through immunohistochemistry. BPIFA2, the major BPI-fold containing protein in adult salivary glands, was detected only in the laryngeal pharynx; the lack of staining in salivary glands suggested salivary expression is either very late in development or is only in adult tissues. Early expression of BPIFA1 was seen in the trachea and nasal cavity with salivary gland expression only seen in late morphodifferentiation stages. BPIFB1 was seen in early neural tissue and at later stages in submandibular and sublingual glands. BPIFA1 is significantly expressed in early fetal oral tissue but BPIFB1 has extremely limited expression and the major salivary BPIF protein (BPIFA2) is not produced in fetal development. Further studies, with more sensitive techniques, will confirm the expression pattern and enable a better understanding of embryonic BPIF protein function.
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