Enhancing deep learning techniques for the diagnosis of the novel coronavirus (COVID-19) using X-ray images

AbstractDeep learning techniques combined with radiological imaging provide precision in the diagnosis of diseases that can be utilised for the classification and diagnosis of several diseases in the medical sector. Several research studies have focused on binary classification of COVID-19, and there is limited research focusing on multiclass classification of COVID-19. The purpose of this study is to develop a model that can enhance the multiclass classification of COVID-19 using raw chest X-ray images. The study involved using convolutional neural networks as the classifier. Five pre-trained deep learning models including VGG16, MobileNet, EfficientNetB0, NasNetMobile and ResNet50V2 are used to distinguish between COVID-19 infection and other lung diseases. Data Augmentation and Normalization techniques have been used to improve the models’ performance and avoid training problems. The study findings revealed that it is possible to distinguish between COVID-19 infection and other lung diseases using pre-trained deep learning models. The proposed technique successfully classifies five classes (normal, COVID-19, lung opacity, viral pneumonia, and bacterial pneumonia). It is found that NasNetMobile model outperformed the rest of the models and achieved the highest results. It achieved an overall accuracy, sensitivity, specificity and precision of 91%, 91%, 97.7% and 91%, respectively. The VGG16 model produced better results in detecting COVID-19 infection, resulting in an accuracy of 95.8%. The suggested technique is more accurate in comparison to the other newly developed techniques presented in the literature. This provides healthcare staff with a powerful tool for the diagnosis of COVID-19 based on deep learning

Hypoxia inducible factor-1α (HIF-1α) as an early predictor of acute hydrogen cyanamide (Dormex) poisoning

Hydrogen cyanamide (Dormex) is a plant growth regulator that is classified as a highly toxic poison. There are no definite investigations to help in its diagnosis and follow-up. This study aimed to investigate the role of hypoxia-inducible factor-1α (HIF-1α) in the diagnosis, prediction, and follow-up of Dormex-intoxicated patients. Sixty subjects were equally divided into two groups: group A, the control group, and group B, the Dormex group. Clinical and laboratory evaluations, including arterial blood gases (ABG), prothrombin concentration (PC), the international normalized ratio (INR), a complete blood count (CBC), and HIF-1α, were done on admission. CBC and HIF-1α were repeated for group B 24 and 48 h after admission to track abnormalities. Group B also had brain computed tomography (CT). Patients with abnormal CT scans were referred for brain magnetic resonance imaging (MRI). Significant differences in levels of HB, WBCs, and platelets were also detected in group B up to 48 h after admission, as white blood cells (WBCs) rose with time and hemoglobin (HB) and platelets diminished. The results described a highly significant difference in HIF-1α between the groups, and it depended on the clinical condition; therefore, it can be used in the prediction and follow-up of patients up to 24 h after admission

B2R protein expression upon 3h STS treatment of PC12 cells.

<p><b>(a)</b> Western Blot of protein extracts from PC12 cells. <b>(b)</b> Histogram representing densitometry analysis of B2R expression using Image J software (n = 3). Error bars represent standard errors of the mean. Symbols indicate statistical difference: B2R vs. B2R-Ctrl, (***) p<0.001 (one-way ANOVA with Bonferroni correction for multiple comparisons).</p

Pathways study of STS-induced altered proteins.

<p>Global Interaction Proteome of <b>(a)</b> STS treated cells and <b>(b)</b> B2I+STS treated cells. The green rectangles, violet rectangles and blue hexagons are reflective of biological processes, disease processes and functional classes, respectively. The different colors of proteins reflect their alteration: upregulated (red), downregulated (orange), downregulated and unique to the treated group (yellow). The green highlights represent the detrimental effects observed following STS or B2I+STS treatment and the pink highlight represents the protective effect observed following B2I+STS treatment. STS: Staurosporine, B2I: Bradykinin 2 receptor inhibited. Creatine kinase B-type [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0128601#pone.0128601.ref015" target="_blank">15</a>], designated by blue highlight is shown to be upregulated in the STS+ B2I treatment where cell survival pathway was detected.</p

Immunofluorescent analysis of Bradykinin 1 and 2 receptors expression in PC12 cells.

<p>Immunofluorescent images of <b>(a)</b> B1R and <b>(b)</b> B2R in PC12 cells in response to 3h, 12h and 24h of STS treatment. Scale bar = 10μm. B1R: Bradykinin 1 receptor; B2R: Bradykinin 2 receptor; STS: Staurosporine. Blue: DAPI (4´,6-diamidino-2-phenylindole), Red: B1R pAb (upper panel) or B2R pAb (lower panel) with Alexa-Fluor 488-conjugated goat anti-mouse IgG.</p

Characterization of the Kallikrein-Kinin System Post Chemical Neuronal Injury: An <i>In Vitro</i> Biochemical and Neuroproteomics Assessment

<div><p>Traumatic Brain Injury (TBI) is the result of a mechanical impact on the brain provoking mild, moderate or severe symptoms. It is acknowledged that TBI leads to apoptotic and necrotic cell death; however, the exact mechanism by which brain trauma leads to neural injury is not fully elucidated. Some studies have highlighted the pivotal role of the Kallikrein-Kinin System (KKS) in brain trauma but the results are still controversial and inconclusive. In this study, we investigated both the expression and the role of Bradykinin 1 and 2 receptors (B1R and B2R), in mediating neuronal injury under chemical neurotoxicity paradigm in PC12 cell lines. The neuronal cell line PC12 was treated with the apoptotic drug Staurosporine (STS) to induce cell death. Intracellular calcium release was evaluated by Fluo 4-AM staining and showed that inhibition of the B2R prevented calcium release following STS treatment. Differential analyses utilizing immunofluorescence, Western blot and Real-time Polymerase Chain Reaction revealed an upregulation of both bradykinin receptors occurring at 3h and 12h post-STS treatment, but with a higher induction of B2R compared to B1R. This implies that STS-mediated apoptosis in PC12 cells is mainly conducted through B2R and partly via B1R. Finally, a neuroproteomics approach was conducted to find relevant proteins associated to STS and KKS in PC12 cells. Neuroproteomics results confirmed the presence of an inflammatory response leading to cell death during apoptosis-mediated STS treatment; however, a “survival” capacity was shown following inhibition of B2R coupled with STS treatment. Our data suggest that B2R is a key player in the inflammatory pathway following STS-mediated apoptosis in PC12 cells and its inhibition may represent a potential therapeutic tool in TBI.</p></div

Fluo-4 AM staining of PC12 cells 3h post-STS treatment depicting intracellular calcium release.

<p>Immunofluorescent images of <b>(a)</b> PC12 cells control, <b>(b)</b> STS treated, <b>(c)</b> B2A pre-treated, <b>(d)</b> B2A pre-treated and STS treated, <b>(e)</b> B2I pre-treated, and <b>(f)</b> B2I pre-treated and STS treated. Scale bar = 10 000nm. STS: Staurosporine; B2A: Bradykinin 2 Receptor activated; B2I: Bradykinin 2 Receptor inhibited.</p

Expression of the B1R and B2R genes in PC12 cells (a) 3h and (b) 12h post-STS treatment, using RT-PCR assay.

<p>(n = 3, triplicate). Each gene was normalized to the housekeeping gene GAPDH, and the control was used as a reference for comparative analysis. Error bars represent standard errors of the mean. Symbols indicate statistical difference: B1R vs B1R-Ctrl, (###) p<0.001, (##) p<0.01, (#) p<0.05; B2R vs B2R-Ctrl, (***) p<0.001 (one-way ANOVA with Bonferroni correction for multiple comparisons). B1R vs. B2R, (++) p<0.1, (+) p<0.05 (Paired t test).</p

Global economic burden of unmet surgical need for appendicitis

Background There is a substantial gap in provision of adequate surgical care in many low- and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially