A study on sex estimation by using machine learning algorithms with parameters obtained from computerized tomography images of the cranium

The aim of this study is to test whether sex prediction can be made by using machine learning algorithms (ML) with parameters taken from computerized tomography (CT) images of cranium and mandible skeleton which are known to be dimorphic. CT images of the cranium skeletons of 150 men and 150 women were included in the study. 25 parameters determined were tested with different ML algorithms. Accuracy (Acc), Specificity (Spe), Sensitivity (Sen), F1 score (F1), Matthews correlation coefficient (Mcc) values were included as performance criteria and Minitab 17 package program was used in descriptive statistical analyses. p <= 0.05 value was considered as statistically significant. In ML algorithms, the highest prediction was found with 0.90 Acc, 0.80 Mcc, 0.90 Spe, 0.90 Sen, 0.90 F1 values as a result of LR algorithms. As a result of confusion matrix, it was found that 27 of 30 males and 27 of 30 females were predicted correctly. Acc ratios of other MLs were found to be between 0.81 and 0.88. It has been concluded that the LR algorithm to be applied to the parameters obtained from CT images of the cranium skeleton will predict sex with high accuracy

Single-cell immune profiling reveals markers of emergency myelopoiesis that distinguish severe from mild respiratory syncytial virus disease in infants

Whereas most infants infected with respiratory syncytial virus (RSV) show no or only mild symptoms, an estimated 3 million children under five are hospitalized annually due to RSV disease. This study aimed to investigate biological mechanisms and associated biomarkers underlying RSV disease heterogeneity in young infants, enabling the potential to objectively categorize RSV-infected infants according to their medical needs. Immunophenotypic and functional profiling demonstrated the emergence of immature and progenitor-like neutrophils, proliferative monocytes (HLA-DRLow, Ki67+), impaired antigen-presenting function, downregulation of T cell response and low abundance of HLA-DRLow B cells in severe RSV disease. HLA-DRLow monocytes were found as a hallmark of RSV-infected infants requiring hospitalization. Complementary transcriptomics identified genes associated with disease severity and pointed to the emergency myelopoiesis response. These results shed new light on mechanisms underlying the pathogenesis and development of severe RSV disease and identified potential new candidate biomarkers for patient stratification

T cells, more than antibodies, may prevent symptoms developing from respiratory syncytial virus infections in older adults

Introduction: The immune mechanisms supporting partial protection from reinfection and disease by the respiratory syncytial virus (RSV) have not been fully characterized. In older adults, symptoms are typically mild but can be serious in patients with comorbidities when the infection extends to the lower respiratory tract. Methods: This study formed part of the RESCEU older-adults prospective-cohort study in Northern Europe (2017–2019; NCT03621930) in which a thousand participants were followed over an RSV season. Peripheral-blood samples (taken pre-season, post-season, during illness and convalescence) were analyzed from participants who (i) had a symptomatic acute respiratory tract infection by RSV (RSV-ARTI; N=35) or (ii) asymptomatic RSV infection (RSV-Asymptomatic; N=16). These analyses included evaluations of antibody (Fc-mediated–) functional features and cell-mediated immunity, in which univariate and machine-learning (ML) models were used to explore differences between groups. Results: Pre–RSV-season peripheral-blood biomarkers were predictive of symptomatic RSV infection. T-cell data were more predictive than functional antibody data (area under receiver operating characteristic curve [AUROC] for the models were 99% and 76%, respectively). The pre-RSV season T-cell phenotypes which were selected by the ML modelling and which were more frequent in RSV-Asymptomatic group than in the RSV-ARTI group, coincided with prominent phenotypes identified during convalescence from RSV-ARTI (e.g., IFN-γ+, TNF-α+ and CD40L+ for CD4+, and IFN-γ+ and 4-1BB+ for CD8+). Conclusion: The evaluation and statistical modelling of numerous immunological parameters over the RSV season suggests a primary role of cellular immunity in preventing symptomatic RSV infections in older adults

T cells, more than antibodies, may prevent symptoms developing from respiratory syncytial virus infections in older adults

INTRODUCTION: The immune mechanisms supporting partial protection from reinfection and disease by the respiratory syncytial virus (RSV) have not been fully characterized. In older adults, symptoms are typically mild but can be serious in patients with comorbidities when the infection extends to the lower respiratory tract. METHODS: This study formed part of the RESCEU older-adults prospective-cohort study in Northern Europe (2017-2019; NCT03621930) in which a thousand participants were followed over an RSV season. Peripheral-blood samples (taken pre-season, post-season, during illness and convalescence) were analyzed from participants who (i) had a symptomatic acute respiratory tract infection by RSV (RSV-ARTI; N=35) or (ii) asymptomatic RSV infection (RSV-Asymptomatic; N=16). These analyses included evaluations of antibody (Fc-mediated-) functional features and cell-mediated immunity, in which univariate and machine-learning (ML) models were used to explore differences between groups. RESULTS: Pre-RSV-season peripheral-blood biomarkers were predictive of symptomatic RSV infection. T-cell data were more predictive than functional antibody data (area under receiver operating characteristic curve [AUROC] for the models were 99% and 76%, respectively). The pre-RSV season T-cell phenotypes which were selected by the ML modelling and which were more frequent in RSV-Asymptomatic group than in the RSV-ARTI group, coincided with prominent phenotypes identified during convalescence from RSV-ARTI (e.g., IFN-γ+, TNF-α+ and CD40L+ for CD4+, and IFN-γ+ and 4-1BB+ for CD8+). CONCLUSION: The evaluation and statistical modelling of numerous immunological parameters over the RSV season suggests a primary role of cellular immunity in preventing symptomatic RSV infections in older adults

Distinct patterns of within-host virus populations between two subgroups of human respiratory syncytial virus

Human respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infection in young children globally, but little is known about within-host RSV diversity. Here, we characterised within-host RSV populations using deep-sequencing data from 319 nasopharyngeal swabs collected during 2017–2020. RSV-B had lower consensus diversity than RSV-A at the population level, while exhibiting greater within-host diversity. Two RSV-B consensus sequences had an amino acid alteration (K68N) in the fusion (F) protein, which has been associated with reduced susceptibility to nirsevimab (MEDI8897), a novel RSV monoclonal antibody under development. In addition, several minor variants were identified in the antigenic sites of the F protein, one of which may confer resistance to palivizumab, the only licensed RSV monoclonal antibody. The differences in within-host virus populations emphasise the importance of monitoring for vaccine efficacy and may help to explain the different prevalences of monoclonal antibody-escape mutants between the two subgroups.</p

Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

Importance Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Objective Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin–stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists’ diagnoses in a diagnostic setting. Design, Setting, and Participants Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Exposures Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. Main Outcomes and Measures The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. Results The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). Conclusions and Relevance In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting

Vulnerability leading to mobility: Syrians' exodus from Turkey

WOS: 000435837700006Turkey has been a stage for human mobility for many years, yet it did not have a comprehensive migration and asylum regime until recently. Being the worst refugee crisis of the last decades, the Syrian crisis actually had an impact on developing such a regime of which the Law on Foreigners and International Protection (LFIP) is a crucial element. The LFIP provides temporary protection to the Syrians in Turkey. However, it is recently observed that more and more Syrians are leaving the country. Examining their exodus, the present article is seeking answers to the question of "Why are the Syrians desperately trying to leave Turkey?" Two arguments are put forth in the article. First, Turkey's new migration and asylum regime has not been able to decrease the refugees' vulnerability because of its "expectation of temporariness". Secondly, it is argued that Turkey's "new asylum regime" is in fact "not that new" due to the fact that asylum-seekers coming from non-European countries have been provided a de facto temporary protection. The article reveals that the Syrian refugees are vulnerable in many fields mainly because they are subject to a protection regime marked by temporariness. As the regime is putting them in limbo, they are leaving Turkey. Turkey's new asylum regime appears not that new after all

The assessment of asbestos and carbon nanotubes induced genotoxic effects

Carbon nanotubes (CNT) are one of the most promising engineered nanomaterials. CNT are tubular fiber shaped engineered graphites and produced in two common types: single wall carbon nanotube (SWCNT) and multi wall carbon nanotube (MWCNT). Unfortunately, their unique properties, making CNT valuable in a large number of applications, can be problematic for their potential toxicity. Moreover, CNT share some physic-chemical properties with asbestos, a known carcinogen fiber if inhaled. In the current presentation, the genotoxicity of CNT in vitro will be discussed along with specific consideration concerning the validity of the FpG comet assay in CNT exposure. We have exposed MWCNT and SWCNT in human bronchial epithelial cell line (16HBE) and in human monocytic cell line (THP-1). FpG comet assay and micronucleus assay were performed in order to determine oxidative DNA strand breaks and aberrant micronuclei formation induced by CNTs. CNT can induce strand breaks and oxidative DNA damage. Both types of CNT induced a significant increase in % Tail DNA and Tail Moment in both cell types, whether or not in the presence of FpG. The micronuclei formation in the presence of cytochalasin B was apparent in all exposed 16HBE cultures, but not in THP-1 cultures. Without cytochalasin B, only MWCNT exposed 16HBE cells and the highest dose of SWCNT in THP-1 showed a significant increase in micronuclei. In conclusion we have observed both DNA damage and aberrant micronuclei formation in 16HBE cells. In THP-1 cells, although oxidative DNA damage and strand breaks occurred, aberrant micronuclei formation occurred in less extent. In all instances, interaction between CNT and assay system was avoided by adjusted protocols, and will be discussed during the presentation

Epigenetic effects of low exposure to carbon nanotubes and asbestos

Asbestos is a group of naturally occurring minerals. Depending on the physical properties of the asbestos fibres, two main groups are distinguished, especially the amphiboles and serpentines. Amphiboles include amosite (brown asbestos) and crocidolite (blue asbestos). These fibres are straight and needle-like. Serpentines include chrysotile (white asbestos) these are curled fibres. These types of asbestos were used in large quantities in industry in the 20th century. All three of the above types of asbestos can induce cancer, more specific inhalation of asbestos fibres leads to lung cancer and malignant mesothelioma. Carbon nanotubes (CNT) a new class of nanomaterials made up of circular hollow graphene layers with physicochemical properties related to asbestos. Due to their fibrous structure and small diameter, they can also be inhaled and induce toxicity in the lung and one type has identified to be a ‘possible’ carcinogen by IARC (MWCNT-7). CNTs are classified according to the number of layers in their structure: single walled CNTs or SWCNTs and multi-walled (CNTs) or MWCNTS. Epigenetics is a relatively young research field in toxicology. Epigenetics is defined as "stable hereditary phenotype due to changes in a chromosome without changes in the DNA sequence" (Berger et al., 2009). The epigenetic mechanisms include mechanisms of DNA methylation, histone modifications and microRNA induction / inhibition. These epigenetic endpoints can also be used as biomarkers for exposure or disease.status: publishe

Melanogryllus Desertus (Pallas, 1771) (Orthoptera: Gryllidae) hemositleri üzerine 2,4-D (Disklorofenoksiasetik asit)’nin etkileri

Bu çalışmada, yabani otlarlarla mücadelede çok yaygın olarak kullanılan 2,4- D herbisitinin, laboratuvar koşullarında (sıcaklık: 28±2 °C; bağıl nem:%45-50; fotoperiyot: 16 saat aydınlık/ 8 saat karanlık) kültürü yapılan ergin Melanogryllus desertus örneklerinin kan hücreleri üzerine sayısal ve histolojik etkileri incelendi. Bu amaçla, M. desertus ile yapılan bütün deneylerde, 2,4-D üç farklı konsantrasyonda (1000, 2500, 5000 ppm) ergin bireylere besin içinde verildi. 2,4-D uygulamasını takiben 4, 8 ve 24 saat sonra hemolenf örnekleri alınıp hemositometre ile toplam hemosit sayıları belirlendi ve yayma preparat yapıldı. Yapılan çalışmada 2,4-D uygulaması toplam hemosit sayılarında konsantrasyonla doğru orantılı olarak artışa neden oldu. Toplam hemosit sayılarında görülen bu artışın 2,4-D uygulamasının 8. saatinde en fazla iken, 24. saatte, 4. saat seviyesine indiği saptandı. 2,4-D uygulanan çekirgelerin ışık mikroskobu ile incelenen preparatlarında, hemosit membranlarında tomurcuklanmalar meydana geldiği ve sitoplazmada büyük vakuollerin oluştuğu, hücre membranı bütünlüğünün kaybolduğu, sitoplazmik içeriğin hücre dışına dağıldığı ve lizise benzer hücre bozulmaları gözlendi. Hemositlerde meydana gelen bu değişiklikler konsantrasyon ve uygulama zamanına bağlı olarak arttı. Sonuç olarak, ışık mikroskobu ile yapılan histolojik incelemelerde 2,4-D’nin hemositlerde morfolojik hasara, toplam hemosit sayısında ve bozulmuş hemosit sayısında artışa neden olduğu gözlendi