Репозиторий Университета

© 2020 Elsevier B.V. Introduction: Vaginal birth after caesarean delivery is associated with better outcomes compared to repeat caesarean section. Accurate antenatal risk stratification of women undergoing a trial of labor after caesarean section is crucial in order to maximize perinatal and maternal outcomes. The primary aim of this study was to explore the role of antepartum ultrasound in predicting the probability of vaginal birth in women attempting trial of labor; the secondary aim was to build a multiparametric prediction model including pregnancy and ultrasound characteristics able to predict vaginal birth and compare its diagnostic performance with previously developed models based exclusively upon clinical and pregnancy characteristics. Methods: Prospective study of consecutive singleton pregnancies scheduled for trial of labor undergoing a dedicated antepartum ultrasound assessment at 36–38 weeks of gestation. Head circumference, estimated fetal weight cervical length, sub-pubic angle were recorded before the onset of labour. The obstetricians and midwives attending the delivery suite were blinded to the ultrasound findings. Multivariate logistic regression and area under the curve analyses were used to explore the strength of association and test the diagnostic accuracy of different maternal and ultrasound characteristics in predicting vaginal birth. Comparison with previously reported clinical models developed by the Maternal-Fetal Medicine Unit Network (Grobman's models) was performed using De Long analysis. Results: A total of 161women who underwent trial of labor were included in the study. Among them 114 (70.8 %) women had successful vaginal birth. At multivariable logistic regression analysis maternal height (adjusted odds ratio (aOR):1.24;9 5% Confidence Interval (CI)1.17−1.33), previous C-section for arrest labor (aOR:0.77; 95 %CI0.66−0.93), cervical dilation at admission (aOR:1.35; 95 %CI1.12−1.74), fetal head circumference (aOR:0.77; 5%CI0.43−0.89), subpubic angle (aOR:1.39 95 %CI1.11−1.99) and cervical length (aOR:0.82 95 % CI0.54−0.98) were independently associated with VBAC. A model integrating these variables had an area under curve of 0.839(95 % CI 0.710−0.727) for the prediction of vaginal birth, significantly higher than those achieved with intake (0.694; 95 %CI0.549−0.815; p = 0.01) and admission (0.732: 95 % CI 0.590−0.84; p = 0.04) models reported by Grobman. Conclusion: Antepartum prediction of vaginal birth after a caesarean section is feasible. Fetal head circumference, subpubic angle and cervical length are independently associated and predictive of vaginal birth. Adding these variables to a multiparametric model including maternal parameters improves the diagnostic accuracy of vaginal birth compared to those based only on maternal characteristic.

© 2020 The Authors The assessment of behavioral outcomes is a central component of neuroscientific research, which has required continuous technological innovations to produce more detailed and reliable findings. In this article, we provide an in-depth review on the progress and future implications for three model organisms (mouse, rat, and Drosophila) essential to our current understanding of behavior. By compiling a comprehensive catalog of popular assays, we are able to compare the diversity of tasks and usage of these animal models in behavioral research. This compilation also allows for the evaluation of existing state-of-the-art methods and experimental applications, including optogenetics, machine learning, and high-throughput behavioral assays. We go on to discuss novel apparatuses and inter-species analyses for centrophobism, feeding behavior, aggression and mating paradigms, with the goal of providing a unique view on comparative behavioral research. The challenges and recent advances are evaluated in terms of their translational value, ethical procedures, and trustworthiness for behavioral research.

© 2020 Elsevier Inc. Aim: Noninvasive ventilation (NIV) is known to reduce intubation in patients with acute hypoxemic respiratory failure (AHRF). We aimed to assess the outcomes of NIV application in COVID-19 patients with AHRF. Materials & methods: In this retrospective cohort study, patients with confirmed diagnosis of COVID-19 and AHRF receiving NIV in general wards were recruited from two university-affiliated hospitals. Demographic, clinical, and laboratory data were recorded at admission. The failure of NIV was defined as intubation or death during the hospital stay. Results: Between April 8 and June 10, 2020, 61 patients were enrolled into the final cohort. NIV was successful in 44 out of 61 patients (72.1%), 17 patients who failed NIV therapy were intubated, and among them 15 died. Overall mortality rate was 24.6%. Patients who failed NIV were older, and had higher respiratory rate, PaCO2, D-dimer levels before NIV and higher minute ventilation and ventilatory ratio on the 1-st day of NIV. No healthcare workers were infected with SARS-CoV-2 during the study period. Conclusions: NIV is feasible in patients with COVID-19 and AHRF outside the intensive care unit, and it can be considered as a valuable option for the management of AHRF in these patients.

© 2020 Elsevier Inc. Aim: Noninvasive ventilation (NIV) is known to reduce intubation in patients with acute hypoxemic respiratory failure (AHRF). We aimed to assess the outcomes of NIV application in COVID-19 patients with AHRF. Materials & methods: In this retrospective cohort study, patients with confirmed diagnosis of COVID-19 and AHRF receiving NIV in general wards were recruited from two university-affiliated hospitals. Demographic, clinical, and laboratory data were recorded at admission. The failure of NIV was defined as intubation or death during the hospital stay. Results: Between April 8 and June 10, 2020, 61 patients were enrolled into the final cohort. NIV was successful in 44 out of 61 patients (72.1%), 17 patients who failed NIV therapy were intubated, and among them 15 died. Overall mortality rate was 24.6%. Patients who failed NIV were older, and had higher respiratory rate, PaCO2, D-dimer levels before NIV and higher minute ventilation and ventilatory ratio on the 1-st day of NIV. No healthcare workers were infected with SARS-CoV-2 during the study period. Conclusions: NIV is feasible in patients with COVID-19 and AHRF outside the intensive care unit, and it can be considered as a valuable option for the management of AHRF in these patients.

© 2020 The Authors Regulated cell death (RCD) has a fundamental role in development, pathology, and tissue homeostasis. In order to understand the RCD mechanisms, it is essential to follow these processes in real time. Here, atomic force microscopy (AFM) is applied to morphologically and mechanically characterize four RCD modalities (intrinsic and extrinsic apoptosis, necroptosis, and ferroptosis) in murine tumor cell lines. The nano-topographical analysis revealed a distinct surface morphology in case of necroptosis, ∼ 200 nm membrane disruptions are observed. Using mechanical measurements, it is possible to detect the early onset of RCD. Combined elasticity and microrheology analysis allowed for a clear distinction between apoptotic and regulated necrotic cell death. Finally, immunofluorescence analysis of the cytoskeleton structure during the RCD processes confirm the measured mechanical changes. The results of this study not only demonstrate the possibility of early real-time cell death detection but also reveal important differences in the cytoskeletal dynamics between multiple RCD modalities.

© 2020 Arnold et al. The depletion of eosinophils represents an efficient strategy to alleviate allergic asthma, but the consequences of prolonged eosinophil deficiency for human health remain poorly understood. We show here that the ablation of eosinophils severely compromises antitumor immunity in syngeneic and genetic models of colorectal cancer (CRC), which can be attributed to defective Th1 and CD8+ T cell responses. The specific loss of GM-CSF signaling or IRF5 expression in the eosinophil compartment phenocopies the loss of the entire lineage. GM-CSF activates IRF5 in vitro and in vivo and can be administered recombinantly to improve tumor immunity. IL-10 counterregulates IRF5 activation by GM-CSF. CRC patients whose tumors are infiltrated by large numbers of eosinophils also exhibit robust CD8 T cell infiltrates and have a better prognosis than patients with eosinophillow tumors. The combined results demonstrate a critical role of eosinophils in tumor control in CRC and introduce the GM-CSF-IRF5 axis as a critical driver of the antitumor activities of this versatile cell type.

© 2020 Arnold et al. The depletion of eosinophils represents an efficient strategy to alleviate allergic asthma, but the consequences of prolonged eosinophil deficiency for human health remain poorly understood. We show here that the ablation of eosinophils severely compromises antitumor immunity in syngeneic and genetic models of colorectal cancer (CRC), which can be attributed to defective Th1 and CD8+ T cell responses. The specific loss of GM-CSF signaling or IRF5 expression in the eosinophil compartment phenocopies the loss of the entire lineage. GM-CSF activates IRF5 in vitro and in vivo and can be administered recombinantly to improve tumor immunity. IL-10 counterregulates IRF5 activation by GM-CSF. CRC patients whose tumors are infiltrated by large numbers of eosinophils also exhibit robust CD8 T cell infiltrates and have a better prognosis than patients with eosinophillow tumors. The combined results demonstrate a critical role of eosinophils in tumor control in CRC and introduce the GM-CSF-IRF5 axis as a critical driver of the antitumor activities of this versatile cell type.

© 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.