Detection of tick-borne pathogens in wild birds and their ticks in Western Siberia and high level of their mismatch

Abstract: The Tomsk region located in the south of Western Siberia is one of the most high-risk areas for tick-borne diseases due to elevated incidence of tick-borne encephalitis and Lyme disease in humans. Wild birds may be considered as one of the reservoirs for tick-borne pathogens and hosts for infected ticks. A high mobility of wild birds leads to unpredictable possibilities for the dissemination of tick-borne pathogens into new geographical regions. The primary goal of this study was to evaluate the prevalence of tick-borne pathogens in wild birds and ticks that feed on them as well as to determine the role of different species of birds in maintaining the tickborne infectious foci. We analysed the samples of 443 wild birds (60 species) and 378 ticks belonging to the genus Ixodes Latraille, 1795 collected from the wild birds, for detecting occurrence of eight tick-borne pathogens, the namely tick-borne encephalitis virus (TBEV), West Nile virus (WNV), and species of Borrelia, Rickettsia, Ehrlichia, Anaplasma, Bartonella and Babesia Starcovici, 1893, using RT-PCR/or PCR and enzyme immunoassay. One or more tick-borne infection markers were detected in 43 species of birds. All markers were detected in samples collected from fieldfare Turdus pilaris Linnaeus, Blyth’s reed warbler Acrocephalus dumetorum Blyth, common redstart Phoenicurus phoenicurus (Linnaeus), and common chaffinch Fringilla coelebs Linnaeus. Although all pathogens have been identified in birds and ticks, we found that in the majority of cases (75.5%), there were mismatches of pathogens in birds and ticks collected from them. Wild birds and their ticks may play an extremely important role in the dissemination of tick-borne pathogens into different geographical regions

Two-Ply Composite Membranes with Separation Layers from Chitosan and Sulfoethylcellulose on a Microporous Support Based on Poly(diphenylsulfone-N-phenylphthalimide)

Two-ply composite membranes with separation layers from chitosan and sulfoethylcellulose were developed on a microporous support based on poly(diphenylsulfone-N-phenylphthalimide) and investigated by use of X-ray diffraction and scanning electron microscopy methods. The pervaporation properties of the membranes were studied for the separation of aqueous alcohol (ethanol, propan-2-ol) mixtures of different compositions. When the mixtures to be separated consist of less than 15 wt % water in propan-2-ol, the membranes composed of polyelectrolytes with the same molar fraction of ionogenic groups (-NH3+ for chitosan and -SO3− for sulfoethylcellulose) show high permselectivity (the water content in the permeate was 100%). Factors affecting the structure of a non-porous layer of the polyelectrolyte complex formed on the substrate surface and the contribution of that complex to changes in the transport properties of membranes are discussed. The results indicate significant prospects for the use of chitosan and sulfoethylcellulose for the formation of highly selective pervaporation membranes

Serial Llama Immunization with Various SARS-CoV-2 RBD Variants Induces Broad Spectrum Virus-Neutralizing Nanobodies

The emergence of SARS-CoV-2 mutant variants has posed a significant challenge to both the prevention and treatment of COVID-19 with anti-coronaviral neutralizing antibodies. The latest viral variants demonstrate pronounced resistance to the vast majority of human monoclonal antibodies raised against the ancestral Wuhan variant. Less is known about the susceptibility of the evolved virus to camelid nanobodies developed at the start of the pandemic. In this study, we compared nanobody repertoires raised in the same llama after immunization with Wuhan’s RBD variant and after subsequent serial immunization with a variety of RBD variants, including that of SARS-CoV-1. We show that initial immunization induced highly potent nanobodies, which efficiently protected Syrian hamsters from infection with the ancestral Wuhan virus. These nanobodies, however, mostly lacked the activity against SARS-CoV-2 omicron-pseudotyped viruses. In contrast, serial immunization with different RBD variants resulted in the generation of nanobodies demonstrating a higher degree of somatic mutagenesis and a broad range of neutralization. Four nanobodies recognizing distinct epitopes were shown to potently neutralize a spectrum of omicron variants, including those of the XBB sublineage. Our data show that nanobodies broadly neutralizing SARS-CoV-2 variants may be readily induced by a serial variant RBD immunization

Terahertz spectroscopy of diabetic and non-diabetic human blood plasma pellets

Significance: The creation of fundamentally new approaches to storing various biomaterial and estimation parameters, without irreversible loss of any biomaterial, is a pressing challenge in clinical practice. We present a technology for studying samples of diabetic and non-diabetic human blood plasma in the terahertz (THz) frequency range. Aim: The main idea of our study is to propose a method for diagnosis and storing the samples of diabetic and non-diabetic human blood plasma and to study these samples in the THz frequency range. Approach: Venous blood from patients with type 2 diabetes mellitus and conditionally healthy participants was collected. To limit the impact of water in the THz spectra, lyophilization of liquid samples and their pressing into a pellet were performed. These pellets were analyzed using THz time-domain spectroscopy. The differentiation between the THz spectral data was conducted using multivariate statistics to classify non-diabetic and diabetic groups’ spectra. Results:We present the density-normalized absorption and refractive index for diabetic and nondiabetic pellets in the range 0.2 to 1.4 THz. Over the entire THz frequency range, the normalized index of refraction of diabetes pellets exceeds this indicator of non-diabetic pellet on average by 9% to 12%. The non-diabetic and diabetic groups of the THz spectra are spatially separated in the principal component space. Conclusion: We illustrate the potential ability in clinical medicine to construct a predictive rule by supervised learning algorithms after collecting enough experimental data