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Enhanced experience in performing percutaneous tracheostomies during the COVID-19 pandemic resulted in changes to airway management protocol for patients undergoing major head and neck reconstructive surgery within our department. Most patients now receive a percutaneous tracheostomy over the previously favoured surgical tracheostomy. The aim of this study was to review our experience in performing percutaneous tracheostomies, whilst comparing complication rates with surgical tracheostomies performed in similar settings. All consecutive patients undergoing free flap reconstructive surgery for head and neck cancer between June 2020 and November 2021 were included, with 56 patients receiving a percutaneous tracheostomy. Data across a range of variables including age, BMI, comorbidities and complications was compared with 56 surgical tracheostomies performed for the same group of patients before the COVID-19 pandemic and resultant protocol changes. In the percutaneous group, a marginally lower complication rate was observed over the surgical tracheostomy group;28.57% and 30.35% respectively. Analysis of the 16 patients who experienced complications in the percutaneous group led to development of selection criteria to identify appropriate patients to receive a percutaneous tracheostomy in future, based on factors such as BMI, bleeding risk and positioning deformities. The COVID-19 pandemic has offered a multitude of learning experiences for healthcare professionals to change our practice. In our unit, this has involved modifying the routine tracheostomy procedure used for airway management intra- and post-operatively in major head and neck reconstruction surgery.Copyright © 2023 The Authors
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Introduction/Aims: Enhanced experience in performing percutaneous dilatational tracheostomies (PDT) during the COVID-19 pandemic resulted in changes to airway management for patients undergoing head and neck reconstructive surgery at Queen Elizabeth Hospital Birmingham. All patients now receive a percutaneous tracheostomy over the previously favoured surgical tracheostomy (ST), unless contraindicated. This ambispective case series aimed to review experiences in performing percutaneous tracheostomies, whilst comparing complication rates with surgical tracheostomies performed in similar settings. In addition, we propose a selection criteria for identifying patients suitable for PDT. Material(s) and Method(s): All patients undergoing free flap reconstruction for head and neck cancer treatment between June 2020-November 2021 were included, with 56 patients receiving PDT. This was compared with data of 56 ST performed before the COVID-19 pandemic. Results/Statistics: In the percutaneous group, a marginally lower complication rate was observed over the surgical tracheostomy group;28.57% and 30.35% respectively. Although not statistically significant, time to decannulation was slightly lower in PDT group (5.8 days) compared to ST group (7.3 days). An additional observed advantage included quicker tracheostomy wound healing with PDT. Analysis of the 16 patients who experienced complications with PDT aided development of the selection criteria for identifying patients for percutaneous tracheostomy. This selection criteria considers BMI, ASA, bleeding risk and positioning deformities. Conclusions/Clinical Relevance: This study has demonstrated PDT to be an equally safe and successful technique with a similar complication rate to ST in head and neck cancer reconstruction surgery. Moving forward, further studies with larger sample sizes would be recommended to draw conclusions. Copyright © 2022
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Current situation in our country is been suffering from a dangerous disease called corona virus which is seen both creatures and human beings. SARS (Severe Acute Respiratory Syndrome) -COV is an example for corona virus.Retrosepective observation by Chinese people have seen many number of cases with start of manifestation in the month of December 2019[1].The first case was seen in china with different types of symptoms and it is known that it was a transmittable disease.Many people who are suffering with this will have an illness which is related to respiration part and it will be cured after taking the period of quarantine for 14 days, with any different kinds of treatments at home or an advice of doctors. Some people who are been affected others health issues will develop serious illness. Around 90% of the people are recovered without undergoing any special treatments because they themselves taking quarantine at home by following home remedies. But some people are being suffering with trouble breathing [5].In the month of March 11 2020 (WHO) recognized and declared it as an pandemic which has spread in many parts of the country within less span of time. This virus was first seen in a city called Wuhan, state of China. In the month of December 2019 the reports of the first COVID-19 cases have started. Yet, it is undecided exactly the spread of this virus and it is spreading very faster in humans. This paper tells about control and safety measures regarding water, sanitation, wash in covid-19 pandemic [1] and following the prevention methods critically is very essential to avoid the spread of this virus.Maintaining cleanliness, following all the rules, and advising your loved ones to do likewise for averting the transmission of SARS-CoV-2. © 2022 Author(s).
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Depression has become a global concern, and COVID-19 also has caused a big surge in its incidence. Broadly, there are two primary methods of detecting depression: Task-based and Mobile Crowd Sensing (MCS) based methods. These two approaches, when integrated, can complement each other. This paper proposes a novel approach for depression detection that combines real-time MCS and task-based mechanisms. We aim to design an end-to-end machine learning pipeline, which involves multimodal data collection, feature extraction, feature selection, fusion, and classification to distinguish between depressed and non-depressed subjects. For this purpose, we created a real-world dataset of depressed and non-depressed subjects. We experimented with: various features from multi-modalities, feature selection techniques, fused features, and machine learning classifiers such as Logistic Regression, Support Vector Machines (SVM), etc. for classification. Our findings suggest that combining features from multiple modalities perform better than any single data modality, and the best classification accuracy is achieved when features from all three data modalities are fused. Feature selection method based on Pearson’s correlation coefficients improved the accuracy in comparison with other methods. Also, SVM yielded the best accuracy of 86%. Our proposed approach was also applied on benchmarking dataset, and results demonstrated that the multimodal approach is advantageous in performance with state-of-the-art depression recognition techniques.
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Agriculture is a fundamental human activity and has a lot of significance in India. The quality and quantity of production have reduced drastically due to diseases that occur and impact of bad weather. Though farmers are producing a good quantity of crops, middle men are stealing the benefits, and this leads to a curb in financial position to start the next crop. The utilization of blockchain technology in the agriculture sector can yield significant results by creation of direct markets to farmers as the blockchain tools are capable of tracing the origin of appetite as it facilitates the creation of reliable food supply chain and constructs faith among the consumer and farmer. It is the reliable process of storing data that smooth the progress of various aspects of the information motivated tools that makes smarter agriculture and this chapter examines the main areas of smart farming, insurance to farm, agricultural transactions and food supply chains. The blockchain technology is growing as an inclusive full-fledged technology which can be utilized in almost all smart applications established within future generation aspects of the Internet, and it is a flourishing technology where each and every node that is involved within the blockchain comprises a disseminated ledger that reinforces the protection and transparency aspects of data. Prohibited users will be restricted to perform any illegitimate transaction in the blockchain network as it has the potential to perform smart contract and consensus. Due to COVID-19 Indian government has taken decision to facilitate farmers to sell their crops anywhere in India and the Real time environment IoT can be combined with the block chain to get better the performance by eliminating the middleperson. © 2021, Springer Nature Switzerland AG.
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The current outbreak of severe acute respiratory distress syndrome (SARS) or nCOVID-19 pandemic, caused by the coronavirus-2 (CoV-2), continues to wreak havoc globally. As novel vaccines are being discovered and developed, small molecule drugs still constitute a viable treatment option for SARS-CoV-2 infections due to their advantages such as superior patient compliance for oral therapies, reduced manufacturing costs and ease of large scale distribution due to better stability and storage profiles. Discovering new drugs for SARS-CoV-2 infections is a time consuming and expensive proposition. In this regard, drug repurposing is an appealing approach which can provide rapid access to therapeutics with proven record of safety and efficacy. We investigated the drug repurposing potential of a library of dipeptidyl peptidase 4 (DPP4) inhibitors which are currently marketed for type-2 diabetes as treatment option for SARS-CoV-2 infections. These computational studies led to the identification of three marketed DPP4 inhibitors; gemigliptin, linagliptin and evogliptin as potential inhibitors of SARS-CoV-2 Mpro viral cysteine protease. In addition, our computational modeling shows that these drugs have the potential to inhibit other viral cysteine proteases from the beta coronavirus family, including the SAR-CoV Mpro and MERS-CoV CLpro suggesting their potential to be repurposed as broad-spectrum antiviral agents.
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The current outbreak of severe acute respiratory distress syndrome (SARS) or nCOVID-19 pandemic, caused by the coronavirus-2 (CoV-2), continues to wreak havoc globally. Unfortunately, there are no concrete treatment options available which has severely hampered the pharmacotherapy of this devastating infection. This calls for an urgent need to consider alternative strategies which can be employed quickly, as discovering new drugs for SARS-CoV-2 infections is a time consuming and expensive proposition. In this regard, drug repurposing is an appealing approach which can provide rapid access to therapeutics with proven record of safety and efficacy. Accordingly, we investigated the drug repurposing potential of a library of dipeptidyl peptidase 4 (DPP4) inhibitors which are currently marketed for type-2 diabetes, to treat SARS-CoV-2 infections. Computational studies were conducted in the crystal structure of the substrate binding site of viral protease, the SARS-CoV-2 Mpro dimer, which led to the identification of three marketed DPP4 inhibitors; gemigliptin, linagliptin and evogliptin exhibiting favorable binding, in the SARS-CoV-2 Mpro dimer, viral protease. These studies support the repurposing of DPP4 class of inhibitors in treating SARS-CoV-2 infections, especially in elderly patients with type-2 diabetes, who are at a greater risk of suffering from increased disease severity and mortality.
Subject(s)
Respiratory Distress Syndrome , Diabetes Mellitus, Type 2 , COVID-19ABSTRACT
The recent outbreak of novel coronavirus disease, COVID‐19 has created a threat to human population across the world. The unavailability of specific therapeutics and vaccines, demands the sincere efforts in this direction. Main Proteases of this novel Coronavirus (SARS‐CoV‐2) play critical role during the disease propagation, and hence represents a crucial target for the drug discovery. Reported phytoconstituents of T. grandis Linn were prepared for docking evaluation. The current objective of the study is to identify some naturally occurring product from Tectona grandis Linn. and evaluate its binding activity against COVID‐19 Major protease as novel Coronavirus (SARS‐CoV‐2) target through in silico docking studies. The study results showed that all the selected phytoconstituents showed binding energy ranging between -7.723 to -1.524 kcal/mol. Barleriaquinone-I exhibited highest binding affinity ‐7.723 Kcal/mol and strong, stable interactions with the amino acid residues present on the active site of COVID‐19 Main Protease. Our findings suggest that these phytoconstituents molecules can be used as potential inhibitors against COVID‐19 Main Protease. However, further investigation and validation of these inhibitors against SARS‐CoV‐2 are needed to claim their candidacy for clinical trials