Tracheomalacia and bronchomalacia are becoming increasingly well recognized. Although pathologically benign conditions, they are responsible for considerable morbidity, occasional mortality and significant difficulties in the operating theatre and intensive care unit. We performed an extensive literature search to identify causal associations, methods of clinical and investigative assessment, treatment modalities and anaesthetic experience with these conditions.

Background: TSG-6 (TNF-stimulated gene-6)-dependent transfer of heavy chains from inter-α-inhibitor onto hyaluronan is critical for ovulation.Results: A calcium ion and chelating glutamate within TSG-6 mediate formation of the covalent heavy chain-TSG-6 intermediate.Conclusion: TSG-6 transferase activity rather than hyaluronan binding drives cumulus expansion.Significance: The role of metal ions in hyaluronan-heavy chain formation has been determined.

Brown–Vialetto–Van Laere syndrome (BVVLS) is a genetic condition caused by a mutation in the C20orf54 gene, which also codes for an intestinal riboflavin transporter. We report the case of a female who presented at 22 months with acute‐onset stridor and generalized muscle weakness, in whom a genetic diagnosis of BVVLS was made, and whose symptoms improved on therapy with high‐dose riboflavin. She had previously been developing normally and was able to walk at 11 months, then developed progressive muscle weakness at 22 months, and within 2 weeks was unable to sit without support. She also demonstrated stridor and paradoxical breathing indicating diaphragmatic weakness, and required continuous non‐invasive ventilation (NIV) through a tracheostomy. After treatment with riboflavin she was able to walk unaided, and her Gross Motor Functional Classification level improved from level IV to level I, having fully regained the motor function she showed before symptom onset. There were no longer signs of diaphragmatic paralysis while on NIV, and she was able to tolerate 10‐minute periods off NIV before paradoxical breathing again became apparent. We therefore recommend that in all cases suspected to be in the BVVLS or Fazio–Londe spectrum, early treatment with high‐dose riboflavin must be considered.

COVID-19 syndrome has extensively escalated worldwide with the induction of the year 2020 and has resulted in the illness of millions of people. COVID-19 patients bear an elevated risk once the symptoms deteriorate. Hence, early recognition of diseased patients can facilitate early intervention and avoid disease succession. This article intends to develop a hybrid deep neural networks (HDNNs), using computed tomography (CT) and X-ray imaging, to predict the risk of the onset of disease in patients suffering from COVID-19. To be precise, the subjects were classified into 3 categories namely normal, Pneumonia, and COVID-19. Initially, the CT and chest X-ray images, denoted as ‘hybrid images’ (with resolution 1080 × 1080) were collected from different sources, including GitHub, COVID-19 radiography database, Kaggle, COVID-19 image data collection, and Actual Med COVID-19 Chest X-ray Dataset, which are open source and publicly available data repositories. The 80% hybrid images were used to train the hybrid deep neural network model and the remaining 20% were used for the testing purpose. The capability and prediction accuracy of the HDNNs were calculated using the confusion matrix. The hybrid deep neural network showed a 99% classification accuracy on the test set data.

No abstract

No abstract

No abstract

No abstract