Репозиторий Университета

© 2020 Elsevier Inc. Arecoline is a naturally occurring psychoactive alkaloid with partial agonism at nicotinic and muscarinic acetylcholine receptors. Arecoline consumption is widespread, making it the fourth (after alcohol, nicotine and caffeine) most used substance by humans. However, the mechanisms of acute and chronic action of arecoline in-vivo remain poorly understood. Animal models are a valuable tool for CNS disease modeling and drug screening. Complementing rodent studies, the zebrafish (Danio rerio) emerges as a promising novel model organism for neuroscience research. Here, we assessed the effects of acute and chronic arecoline on adult zebrafish behavior and physiology. Overall, acute and chronic arecoline treatments produced overt anxiolytic-like behavior (without affecting general locomotor activity and whole-body cortisol levels), with similar effects also caused by areca nut water extracts. Acute arecoline at 10 mg/L disrupted shoaling, increased social preference, elevated brain norepinephrine and serotonin levels and reduced serotonin turnover. Acute arecoline also upregulated early protooncogenes c-fos and c-jun in the brain, whereas chronic treatment with 1 mg/L elevated brain expression of microglia-specific biomarker genes egr2 and ym1 (thus, implicating microglial mechanisms in potential effects of long-term arecoline use). Finally, acute 2-h discontinuation of chronic arecoline treatment evoked withdrawal-like anxiogenic behavior in zebrafish. In general, these findings support high sensitivity of zebrafish screens to arecoline and related compounds, and reinforce the growing utility of zebrafish for probing molecular mechanisms of CNS drugs. Our study also suggests that novel anxiolytic drugs can eventually be developed based on arecoline-like molecules, whose integrative mechanisms of CNS action may involve monoaminergic and neuro-immune modulation.

© 2020, The Author(s). In the original version of this Article, Ghulam Md Ashraf was incorrectly affiliated with ‘Enzymoics and Novel Global Community Educational Foundation, Hebersham, NSW, Australia’. The correct affiliation is listed below. King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia. Additionally, within the Supplementary Information file originally published with this Article, authors Vijaya Rao Pidugu, Mohammad A. Kamal, Ghulam Md Ashraf, Vadim V. Tarasov, Vladimir N. Chubarev, Sergey G. Klochkov, George E. Barreto and Sergey O. Bachurin were omitted. These errors have now been corrected in the PDF and HTML versions of the Article, and in the accompanying Supplementary material.

© 2020, The Author(s). Somatic mutation profiling in gastric cancer (GC) enables main driver mutations to be identified and their clinical and prognostic value to be evaluated. We investigated 77 tumour samples of GC by next-generation sequencing (NGS) with the Ion AmpliSeq Hotspot Panel v2 and a custom panel covering six hereditary gastric cancer predisposition genes (BMPR1A, SMAD4, CDH1, TP53, STK11 and PTEN). Overall, 47 somatic mutations in 14 genes were detected; 22 of these mutations were novel. Mutations were detected most frequently in the CDH1 (13/47) and TP53 (12/47) genes. As expected, somatic CDH1 mutations were positively correlated with distant metastases (p = 0.019) and tumours with signet ring cells (p = 0.043). These findings confirm the association of the CDH1 mutations with diffuse GC type. TP53 mutations were found to be significantly associated with a decrease in overall survival in patients with Lauren diffuse-type tumours (p = 0.0085), T3-T4 tumours (p = 0.037), and stage III-IV tumours (p = 0.013). Our results confirm that the detection of mutations in the main driver genes may have a significant prognostic value for GC patients and provide an independent GC-related set of clinical and molecular genetic data.

© 2020, The Author(s). Machine learning techniques have been previously applied for classification of tumors based largely on morphological features of tumor cells recognized in H&E images. Here, we tested the possibility of using numeric data acquired from software-based quantification of certain marker proteins, i.e. key autophagy proteins (ATGs), obtained from immunohistochemical (IHC) images of renal cell carcinomas (RCC). Using IHC staining and automated image quantification with a tissue microarray (TMA) of RCC, we found ATG1, ATG5 and microtubule-associated proteins 1A/1B light chain 3B (LC3B) were significantly reduced, suggesting a reduction in the basal level of autophagy with RCC. Notably, the levels of the ATG proteins expressed did not correspond to the mRNA levels expressed in these tissues. Applying a supervised machine learning algorithm, the K-Nearest Neighbor (KNN), to our quantified numeric data revealed that LC3B provided a strong measure for discriminating clear cell RCC (ccRCC). ATG5 and sequestosome-1 (SQSTM1/p62) could be used for classification of chromophobe RCC (crRCC). The quantitation of particular combinations of ATG1, ATG16L1, ATG5, LC3B and p62, all of which measure the basal level of autophagy, were able to discriminate among normal tissue, crRCC and ccRCC, suggesting that the basal level of autophagy would be a potentially useful parameter for RCC discrimination. In addition to our observation that the basal level of autophagy is reduced in RCC, our workflow from quantitative IHC analysis to machine learning could be considered as a potential complementary tool for the classification of RCC subtypes and also for other types of tumors for which precision medicine requires a characterization.

© 2020, The Author(s). Semiconductor quantum dots (QDs) embedded into polymer microbeads are known to be very attractive emitters for spectral multiplexing and colour encoding. Their luminescence lifetimes or decay kinetics have been, however, rarely exploited as encoding parameter, although they cover time ranges which are not easily accessible with other luminophores. We demonstrate here the potential of QDs made from II/VI semiconductors with luminescence lifetimes of several 10 ns to expand the lifetime range of organic encoding luminophores in multiplexing applications using time-resolved flow cytometry (LT-FCM). For this purpose, two different types of QD-loaded beads were prepared and characterized by photoluminescence measurements on the ensemble level and by single-particle confocal laser scanning microscopy. Subsequently, these lifetime-encoded microbeads were combined with dye-encoded microparticles in systematic studies to demonstrate the potential of these QDs to increase the number of lifetime codes for lifetime multiplexing and combined multiplexing in the time and colour domain (tempo-spectral multiplexing). These studies were done with a recently developed novel luminescence lifetime flow cytometer (LT-FCM setup) operating in the time-domain, that presents an alternative to reports on phase-sensitive lifetime detection in flow cytometry.

Middle East respiratory syndrome (MERS) coronavirus (MERS-CoV) causes a severe respiratory disease in humans. The MERS-CoV spike (S) glycoprotein mediates viral entry into target cells. For this, MERS-CoV S engages the host cell protein dipeptidyl peptidase 4 (DPP4, CD26) and the interface between MERS-CoV S and DPP4 has been resolved on the atomic level. Here, we asked whether naturally-occurring polymorphisms in DPP4, that alter amino acid residues required for MERS-CoV S binding, influence cellular entry of MERS-CoV. By screening of public databases, we identified fourteen such polymorphisms. Introduction of the respective mutations into DPP4 revealed that all except one (Δ346-348) were compatible with robust DPP4 expression. Four polymorphisms (K267E, K267N, A291P and Δ346-348) strongly reduced binding of MERS-CoV S to DPP4 and S protein-driven host cell entry, as determined using soluble S protein and S protein bearing rhabdoviral vectors, respectively. Two polymorphisms (K267E and A291P) were analyzed in the context of authentic MERS-CoV and were found to attenuate viral replication. Collectively, we identified naturally-occurring polymorphisms in DPP4 that negatively impact cellular entry of MERS-CoV and might thus modulate MERS development in infected patients.

© 2020, The Author(s). Machine learning techniques have been previously applied for classification of tumors based largely on morphological features of tumor cells recognized in H&E images. Here, we tested the possibility of using numeric data acquired from software-based quantification of certain marker proteins, i.e. key autophagy proteins (ATGs), obtained from immunohistochemical (IHC) images of renal cell carcinomas (RCC). Using IHC staining and automated image quantification with a tissue microarray (TMA) of RCC, we found ATG1, ATG5 and microtubule-associated proteins 1A/1B light chain 3B (LC3B) were significantly reduced, suggesting a reduction in the basal level of autophagy with RCC. Notably, the levels of the ATG proteins expressed did not correspond to the mRNA levels expressed in these tissues. Applying a supervised machine learning algorithm, the K-Nearest Neighbor (KNN), to our quantified numeric data revealed that LC3B provided a strong measure for discriminating clear cell RCC (ccRCC). ATG5 and sequestosome-1 (SQSTM1/p62) could be used for classification of chromophobe RCC (crRCC). The quantitation of particular combinations of ATG1, ATG16L1, ATG5, LC3B and p62, all of which measure the basal level of autophagy, were able to discriminate among normal tissue, crRCC and ccRCC, suggesting that the basal level of autophagy would be a potentially useful parameter for RCC discrimination. In addition to our observation that the basal level of autophagy is reduced in RCC, our workflow from quantitative IHC analysis to machine learning could be considered as a potential complementary tool for the classification of RCC subtypes and also for other types of tumors for which precision medicine requires a characterization.

© 2020, The Author(s). Semiconductor quantum dots (QDs) embedded into polymer microbeads are known to be very attractive emitters for spectral multiplexing and colour encoding. Their luminescence lifetimes or decay kinetics have been, however, rarely exploited as encoding parameter, although they cover time ranges which are not easily accessible with other luminophores. We demonstrate here the potential of QDs made from II/VI semiconductors with luminescence lifetimes of several 10 ns to expand the lifetime range of organic encoding luminophores in multiplexing applications using time-resolved flow cytometry (LT-FCM). For this purpose, two different types of QD-loaded beads were prepared and characterized by photoluminescence measurements on the ensemble level and by single-particle confocal laser scanning microscopy. Subsequently, these lifetime-encoded microbeads were combined with dye-encoded microparticles in systematic studies to demonstrate the potential of these QDs to increase the number of lifetime codes for lifetime multiplexing and combined multiplexing in the time and colour domain (tempo-spectral multiplexing). These studies were done with a recently developed novel luminescence lifetime flow cytometer (LT-FCM setup) operating in the time-domain, that presents an alternative to reports on phase-sensitive lifetime detection in flow cytometry.

Middle East respiratory syndrome (MERS) coronavirus (MERS-CoV) causes a severe respiratory disease in humans. The MERS-CoV spike (S) glycoprotein mediates viral entry into target cells. For this, MERS-CoV S engages the host cell protein dipeptidyl peptidase 4 (DPP4, CD26) and the interface between MERS-CoV S and DPP4 has been resolved on the atomic level. Here, we asked whether naturally-occurring polymorphisms in DPP4, that alter amino acid residues required for MERS-CoV S binding, influence cellular entry of MERS-CoV. By screening of public databases, we identified fourteen such polymorphisms. Introduction of the respective mutations into DPP4 revealed that all except one (Δ346-348) were compatible with robust DPP4 expression. Four polymorphisms (K267E, K267N, A291P and Δ346-348) strongly reduced binding of MERS-CoV S to DPP4 and S protein-driven host cell entry, as determined using soluble S protein and S protein bearing rhabdoviral vectors, respectively. Two polymorphisms (K267E and A291P) were analyzed in the context of authentic MERS-CoV and were found to attenuate viral replication. Collectively, we identified naturally-occurring polymorphisms in DPP4 that negatively impact cellular entry of MERS-CoV and might thus modulate MERS development in infected patients.

© 2020, The Author(s). Semiconductor quantum dots (QDs) embedded into polymer microbeads are known to be very attractive emitters for spectral multiplexing and colour encoding. Their luminescence lifetimes or decay kinetics have been, however, rarely exploited as encoding parameter, although they cover time ranges which are not easily accessible with other luminophores. We demonstrate here the potential of QDs made from II/VI semiconductors with luminescence lifetimes of several 10 ns to expand the lifetime range of organic encoding luminophores in multiplexing applications using time-resolved flow cytometry (LT-FCM). For this purpose, two different types of QD-loaded beads were prepared and characterized by photoluminescence measurements on the ensemble level and by single-particle confocal laser scanning microscopy. Subsequently, these lifetime-encoded microbeads were combined with dye-encoded microparticles in systematic studies to demonstrate the potential of these QDs to increase the number of lifetime codes for lifetime multiplexing and combined multiplexing in the time and colour domain (tempo-spectral multiplexing). These studies were done with a recently developed novel luminescence lifetime flow cytometer (LT-FCM setup) operating in the time-domain, that presents an alternative to reports on phase-sensitive lifetime detection in flow cytometry.

Middle East respiratory syndrome (MERS) coronavirus (MERS-CoV) causes a severe respiratory disease in humans. The MERS-CoV spike (S) glycoprotein mediates viral entry into target cells. For this, MERS-CoV S engages the host cell protein dipeptidyl peptidase 4 (DPP4, CD26) and the interface between MERS-CoV S and DPP4 has been resolved on the atomic level. Here, we asked whether naturally-occurring polymorphisms in DPP4, that alter amino acid residues required for MERS-CoV S binding, influence cellular entry of MERS-CoV. By screening of public databases, we identified fourteen such polymorphisms. Introduction of the respective mutations into DPP4 revealed that all except one (Δ346-348) were compatible with robust DPP4 expression. Four polymorphisms (K267E, K267N, A291P and Δ346-348) strongly reduced binding of MERS-CoV S to DPP4 and S protein-driven host cell entry, as determined using soluble S protein and S protein bearing rhabdoviral vectors, respectively. Two polymorphisms (K267E and A291P) were analyzed in the context of authentic MERS-CoV and were found to attenuate viral replication. Collectively, we identified naturally-occurring polymorphisms in DPP4 that negatively impact cellular entry of MERS-CoV and might thus modulate MERS development in infected patients.

© 2020, The Author(s). Despite recent advances in drug delivery, the targeted treatment of unhealthy cells or tissues continues to remain a priority. In cancer (much like other pathologies), delivery vectors are designed to exploit physical and biological features of unhealthy tissues that are not always homogenous across the disease. In some cases, shifting the target from unhealthy tissues to the whole organ can represent an advantage. Specifically, the natural organ-specific retention of nanotherapeutics following intravenous administration as seen in the lung, liver, and spleen can be strategically exploited to enhance drug delivery. Herein, we outline the development of a cell-based delivery system using macrophages as a delivery vehicle. When loaded with a chemotherapeutic payload (i.e., doxorubicin), these cellular vectors (CELVEC) were shown to provide continued release within the lung. This study provides proof-of-concept evidence of an alternative class of biomimetic delivery vectors that capitalize on cell size to provide therapeutic advantages for pulmonary treatments.

© 2020, The Author(s). Despite recent advances in drug delivery, the targeted treatment of unhealthy cells or tissues continues to remain a priority. In cancer (much like other pathologies), delivery vectors are designed to exploit physical and biological features of unhealthy tissues that are not always homogenous across the disease. In some cases, shifting the target from unhealthy tissues to the whole organ can represent an advantage. Specifically, the natural organ-specific retention of nanotherapeutics following intravenous administration as seen in the lung, liver, and spleen can be strategically exploited to enhance drug delivery. Herein, we outline the development of a cell-based delivery system using macrophages as a delivery vehicle. When loaded with a chemotherapeutic payload (i.e., doxorubicin), these cellular vectors (CELVEC) were shown to provide continued release within the lung. This study provides proof-of-concept evidence of an alternative class of biomimetic delivery vectors that capitalize on cell size to provide therapeutic advantages for pulmonary treatments.

© 2020, The Author(s). Background: Across the globe, diseases secondary to environmental exposures have been described, and it was also found that existing diseases have been modified by exposure to environmental chemicals or an environmental factor that has been found in their pathogenesis. The Institute of Medicine has shared a permanent concern related to the nations environmental health capacity since 1988. Main body: Contemporary imaging methods in the last 15 years started reporting alterations in different human systems such as the central nervous system, cardiovascular system and pulmonary system among others; evidence suggests the existence of a human environmental disease network. The primary anatomic regions, affected by environmental diseases, recently assessed with imaging methods include Brain (lead exposure, cerebral stroke, pesticide neurotoxicity), uses MRI, DTI, carotid ultrasonography and MRS; Lungs (smoke inhalation, organophosphates poisoning) are mainly assessed with radiography; Gastrointestinal system (chronic inflammatory bowel disease), recent studies have reported the use of aortic ultrasound; Heart (myocardial infarction), its link to environmental diseased has been proved with carotid ultrasound; and Arteries (artery hypertension), the impairment of aortic mechanical properties has been revealed with the use of aortic and brachial ultrasound. Conclusions: Environmental epidemiology has revealed that several organs and systems in the human body are targets of air pollutants. Current imaging methods that can assess the deleterious effects of pollutants includes a whole spectrum: radiography, US, CT and MRI. Future studies will help to reveal additional links among environmental disease networks.

© 2020, The Author(s). Background: Across the globe, diseases secondary to environmental exposures have been described, and it was also found that existing diseases have been modified by exposure to environmental chemicals or an environmental factor that has been found in their pathogenesis. The Institute of Medicine has shared a permanent concern related to the nations environmental health capacity since 1988. Main body: Contemporary imaging methods in the last 15 years started reporting alterations in different human systems such as the central nervous system, cardiovascular system and pulmonary system among others; evidence suggests the existence of a human environmental disease network. The primary anatomic regions, affected by environmental diseases, recently assessed with imaging methods include Brain (lead exposure, cerebral stroke, pesticide neurotoxicity), uses MRI, DTI, carotid ultrasonography and MRS; Lungs (smoke inhalation, organophosphates poisoning) are mainly assessed with radiography; Gastrointestinal system (chronic inflammatory bowel disease), recent studies have reported the use of aortic ultrasound; Heart (myocardial infarction), its link to environmental diseased has been proved with carotid ultrasound; and Arteries (artery hypertension), the impairment of aortic mechanical properties has been revealed with the use of aortic and brachial ultrasound. Conclusions: Environmental epidemiology has revealed that several organs and systems in the human body are targets of air pollutants. Current imaging methods that can assess the deleterious effects of pollutants includes a whole spectrum: radiography, US, CT and MRI. Future studies will help to reveal additional links among environmental disease networks.

© 2020, The Author(s). A three dimensional magnetic patterning of two cell types was realised in vitro inside an additive manufactured magnetic scaffold, as a conceptual precursor for the vascularised tissue. The realisation of separate arrangements of vascular and osteoprogenitor cells, labelled with biocompatible magnetic nanoparticles, was established on the opposite sides of the scaffold fibres under the effect of non-homogeneous magnetic gradients and loading magnetic configuration. The magnetisation of the scaffold amplified the guiding effects by an additional trapping of cells due to short range magnetic forces. The mathematical modelling confirmed the strong enhancement of the magnetic gradients and their particular geometrical distribution near the fibres, defining the preferential cell positioning on the micro-scale. The manipulation of cells inside suitably designed magnetic scaffolds represents a unique solution for the assembling of cellular constructs organised in biologically adequate arrangements.

© 2020, The Author(s). A three dimensional magnetic patterning of two cell types was realised in vitro inside an additive manufactured magnetic scaffold, as a conceptual precursor for the vascularised tissue. The realisation of separate arrangements of vascular and osteoprogenitor cells, labelled with biocompatible magnetic nanoparticles, was established on the opposite sides of the scaffold fibres under the effect of non-homogeneous magnetic gradients and loading magnetic configuration. The magnetisation of the scaffold amplified the guiding effects by an additional trapping of cells due to short range magnetic forces. The mathematical modelling confirmed the strong enhancement of the magnetic gradients and their particular geometrical distribution near the fibres, defining the preferential cell positioning on the micro-scale. The manipulation of cells inside suitably designed magnetic scaffolds represents a unique solution for the assembling of cellular constructs organised in biologically adequate arrangements.

© 2020, The Author(s). Job-related stress has been associated with poor health outcomes but little is known about the causal nature of these findings. We employed Mendelian randomisation (MR) approach to investigate the causal effect of neuroticism, education, and physical activity on job satisfaction. Trait-specific genetic risk score (GRS) based on recent genome wide association studies were used as instrumental variables (IV) using the UK Biobank cohort (N = 315,536). Both single variable and multivariable MR analyses were used to determine the effect of each trait on job satisfaction. We observed a clear evidence of a causal association between neuroticism and job satisfaction. In single variable MR, one standard deviation (1 SD) higher genetically determined neuroticism score (4.07 units) was associated with −0.31 units lower job satisfaction (95% confidence interval (CI): −0.38 to −0.24; P = 9.5 × 10−20). The causal associations remained significant after performing sensitivity analyses by excluding invalid genetic variants from GRSNeuroticism (β(95%CI): −0.28(−0.35 to −0.21); P = 3.4 x 10−15). Education (0.02; −0.08 to 0.12; 0.67) and physical activity (0.08; −0.34 to 0.50; 0.70) did not show any evidence for causal association with job satisfaction. When genetic instruments for neuroticism, education and physical activity were included together, the association of neuroticism score with job satisfaction was reduced by only −0.01 units, suggesting an independent inverse causal association between neuroticism score (P = 2.7 x 10−17) and job satisfaction. Our findings show an independent causal association between neuroticism score and job satisfaction. Physically active lifestyle may help to increase job satisfaction despite presence of high neuroticism scores. Our study highlights the importance of considering the confounding effect of negative personality traits for studies on job satisfaction.

© 2020, The Author(s). Memory decline can be a devastating disease and increases in aging Western populations. Memory enhancement technologies hold promise for this and other conditions. Approaches include stem cell transplantation, which improved memory in several animal studies as well as vaccination against Alzheimer´s disease (AD) by β-amyloid antibodies. For a positive clinical effect, the vaccine should probably be administered over a long period of time and before amyloid pathologies manifest in the brain. Different drugs, such as erythropoietin or antiplatelet therapy, improve memory in neuropsychiatric diseases or AD or at least in animal studies. Omega-3 polyunsaturated fatty acid-rich diets improve memory through the gut–brain axis by altering the gut flora through probiotics. Sports, dancing, and memory techniques (e.g., Method of Loci) utilize behavioral approaches for memory enhancement, and were effective in several studies. Augmented reality (AR) is an auspicious way for enhancing memory in real time. Future approaches may include memory prosthesis for head-injured patients and light therapy for restoring memory in AD. Memory enhancement in humans in health and disease holds big promises for the future. Memory training helps only in mild or no impairment. Clinical application requires further investigation.

© 2020, The Author(s). Autoantibodies, which are antibodies that target self-epitopes, have considerable diagnostic, prognostic and predictive value in specific autoimmune diseases. Various infectious agents have been linked via numerous mechanisms to the formation of different autoantibodies. Therefore, estimating the prevalence of autoantibodies and anti-infectious antibodies in different populations is of high importance. Different genetic and environmental pressures, such as these found in Ghana’s different geographical provinces, may affect the prevalence of autoantibodies. In this study, we assessed the seroprevalence of a diverse panel of autoantibodies and anti-infectious antibodies among the healthy Ghanaian population and investigated possible environmental and genetic predispositions for autoantibodies and autoimmunity. The sera of 406 healthy individuals were obtained from Greater Accra, Upper West, Eastern and Volta regions. Multiplexed assay and chemiluminescent immunoassay techniques were utilized to assess the presence of a panel of autoantibodies and anti-infectious antibodies. We found a high prevalence of anti-HSV-1 IgG (91–100%), anti-EBNA IgG (81–93%) and anti-EBV-VCA IgG (97–100%) antibodies. The prevalence of ANA (at least one of: anti-dsDNA; anti-chromatin; anti-ribosomal-P; anti-Ro/SSA; anti-La/SSB; anti-centromere B; anti-Sm; anti-Sm/RNP; anti-Scl-70; anti-Jo1; anti-DFS70) was estimated at 14%. An inverse association between anti-HSV-2 antibodies and ANA (p = 0.044; adjusted OR = 0.398; CI [0.162–0.975]) was found, after adjusting for differences in gender, age, and familial history of autoimmune diseases. A trend towards reduced seroprevalence of anti-dsDNA antibodies among subjects who were positive for anti-HSV-2 antibodies was also noted (p = 0.1). In conclusion, the inverse association between anti-HSV-2 antibodies and ANA positivity suggests a possible protective role of HSV-2 infection against autoimmunity.