Crimean-Congo Hemorrhagic Fever: Tick-Host-Virus Interactions

Papa, Anna; Tsergouli, Katerina; Tsioka, Katerina; Mirazimi, Alì

doi:10.3389/fcimb.2017.00213

Cited by 70 publications

(61 citation statements)

References 63 publications

(82 reference statements)

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“…In a review by Papa et al, it was reported that both the intrinsic and the extrinsic apoptosis pathways are induced in patients with CCHF. This result, which was specifically concluded based on in vitro studies, was supported by our study with patients with CCHF.…”

Section: Discussionmentioning

confidence: 99%

Apoptosis and its relation with clinical course in patients with Crimean‐Congo hemorrhagic fever

Engin

Aydın

Çınar

et al. 2019

Journal of Medical Virology

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Crimean-Congo hemorrhagic fever (CCHF) is a tick-mediated viral infection. Patients with CCHF may show various clinical presentations. The cause of this difference in the clinical course is not completely understood. Apoptosis is programmed cell death and plays an important role in regulating the immune system. Our knowledge of the role of apoptosis in CCHF disease is limited. We investigated the role of apoptosis and their relationship with the severity of the disease in CCHF.Thus, in 30 patients with CCHF and 30 healthy individuals, we analyzed the serum levels of cytochrome C, apoptotic protease activating factor-1 (Apaf 1), caspase 3, caspase 8, caspase 9, sFas, sFasL, perforin, granzyme B, and CK18 by enzyme-linked immunosorbent assay. This is the first study that research the serum levels of the mentioned apoptosis markers in adult patients with CCHF.

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Section: Discussionmentioning

confidence: 99%

Apoptosis and its relation with clinical course in patients with Crimean‐Congo hemorrhagic fever

Engin

Aydın

Çınar

et al. 2019

Journal of Medical Virology

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“…The vectors of CCHFV are better known, and are presumed to almost always be Hyalomma ticks, which are widespread throughout Africa and Eurasia; other tick vectors have been suspected, but evidence for their competence is limited. (Papa et al , 2017) In Africa, Hyalomma truncatum in particular is common throughout rangeland and is one of the strongest candidates for a primary vector. (Logan et al , 1989; Wilson et al , 1991)…”

Section: Example: Crimean-congo Haemorrhagic Fevermentioning

confidence: 99%

embarcadero: Species distribution modelling with Bayesian additive regression trees in R

Carlson

2019

Preprint

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8 1. Classification and regression tree methods, like random forests (RF) or 9 boosted regression trees (BRT), are one of the most popular methods of 10 mapping species distributions. 11 12 2. Bayesian additive regression trees (BARTs) are a relatively new alterna-13 tive to other popular regression tree approaches. Whereas BRT iteratively 14 fits an ensemble of trees each explaining smaller fractions of the total vari-15 ance, BART starts by fitting a sum-of-trees model and then uses Bayesian 16 backfitting with an MCMC algorithm to create a posterior draw. So far, 17BARTs have yet to be applied to species distribution modeling. 18 19 3. embarcadero is an R package of convenience tools for researchers in-20 terested in species distribution modeling with BARTs. It includes function-21 ality for spatial prediction, an automated variable selection and importance 22 procedure, and other functionality for rapid implementation and data visu-23 alization. 24 25 4. To show how embarcadero can be used by ecologists, we re-map the distri-26 bution of Crimean-Congo haemorrhagic fever and a likely vector, Hyalomma 27 truncatum, in Africa.28 29 Keywords: Bayesian additive regression trees, species distribution model-30 ing, ecological niche modeling, Crimean Congo haemorrhagic fever 31 1 Introduction 32 In the last two decades, over a dozen statistical and machine learning methods have 33 been proposed for species distribution modeling (SDM). Over time, a handful of 34 methods have risen to predominance due to ease of implementation, computational 35 speed, and strong predictive performance in rigorous cross-validation. Some meth-36 ods are especially popular for specific applications, mostly because of disciplinary 37 tradition. For example, maximum entropy (MaxEnt) models are widely popular 38 for studies of global ecological responses to climate change. (VanDerWal et al., 39 2013; Warren et al., 2013) In disease ecology, boosted regression trees (BRTs) have 40 become the dominant tool for mapping vectors, reservoirs, and transmission risk of 41 infectious zoonoses and vector-borne diseases (Carlson et al., 2019; Pigott et al., 42 2014; Messina et al., 2016), largely due to an influential 2013 paper on dengue 43 virus. (Bhatt et al., 2013) 44 Boosted regression trees are easily implemented as an out-of-the-box machine 45 learning method, are powerful for ecological inference, and consistently perform 46 well in rigorous tests of SDM performance. The classification tree approach is also 47 more intuitive than the complex fitting procedures "under the hood" of MaxEnt 48 or Maxlike methods. However, BRTs also have downsides: they can be prone 49 to overfitting, and fitting procedures are largely handed down as anecdotal best 50 practices, with most studies choosing learning rates and tree depth based on the de-51 fault settings recommended by early work (Elith et al., 2008), with very few studies 52 selecting parameters from formal cross-validation with packages like caret. Fur-53 thermore, uncertainty is usually measured by ...

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“…Crimean Congo hemorrhagic fever virus (CCHFV), a member of Orthonairovirus genus and Nairoviridae family, is a major tick-borne human pathogen, causing hemorrhagic fever disease with considerable mortality rates up to 40% in endemic areas [1,2]. The widespread distribution, significant mortality rates and the lack of specific treatment or control measures make CCHFV an urgent target for vaccine development [3].…”

Section: Introductionmentioning

confidence: 99%

Bovine Herpesvirus Type 4 (BoHV-4) Vector Delivering Nucleocapsid Protein of Crimean Congo Hemorrhagic Fever Virus Induces Comparable Protective Immunity against Lethal Challenge in IFNAR<sup>-/-</sup> Mice Model

Farzani¹,

Földes²,

Hanifehnezhad³

et al. 2019

Preprint

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Crimean-Congo hemorrhagic fever virus (CCHFV) is the causative agent of a tick-borne infection with significant mortality rate of up to 40% in the endemic areas, with evidence for geographical expansion. Lacking effective therapeutics and control measures, the development of protective CCHFV vaccine remains a crucial public health task. This manuscript describes, for the first time, a Bovine herpesvirus type 4 (BoHV-4) based viral vector (BoHV4-∆TK-CCHFV-N) and its immunogenicity and protection potential in BALB/c and IFNAR-/- mice models in comparison with Adenovirus type 5 (Ad5-N) and pCDNA3.1 myc/His A (pCD-N1), two widely used vaccine platforms. All constructs expressing viral nucleocapsid (N) protein successfully elicited cytokine and total/specific antibody responses in BALB/c mice. BoHV4-∆TK-CCHFV-N and Ad5-N constructs further produced 100% protection in IFNAR-/- mice during CCHFV Ank-2 strain lethal challenge. Despite elevated specific antibody responses in both animal models, the produced antibodies were unable to neutralize the virus in vitro. A comparison of delivery platforms was not possible, due to similar protection rates in IFNAR-/- mice. In conclusion, vector-based CCHFV N protein expression proved to constitute an effective approach for the vaccine development pipeline and BoHV-4 emerged as a strong alternative to previously-used virus vectors.

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Crimean-Congo Hemorrhagic Fever: Tick-Host-Virus Interactions

Cited by 70 publications

References 63 publications

Apoptosis and its relation with clinical course in patients with Crimean‐Congo hemorrhagic fever

Apoptosis and its relation with clinical course in patients with Crimean‐Congo hemorrhagic fever

embarcadero: Species distribution modelling with Bayesian additive regression trees in R

Bovine Herpesvirus Type 4 (BoHV-4) Vector Delivering Nucleocapsid Protein of Crimean Congo Hemorrhagic Fever Virus Induces Comparable Protective Immunity against Lethal Challenge in IFNAR<sup>-/-</sup> Mice Model

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