Bronchodilator reversibility testing in long-term cough and dyspnea after Covid-19 viral infection: a trigger for asthma?

Objective: This study aims to investigate the presence of underlying chronic airway disease in individuals with chronic cough and dyspnea lasting longer than eight weeks and who had previously Coronavirus disease 2019 (COVID-19) and had no known lung disease.Methods: A total of 151 patients admitted to the respiratory diseases outpatient room with the complaint of cough and/or dyspnea that persisted for at least eight weeks following COVID-19 infection were accrued to the study. Demographic characteristics, smoking history, the severity of lung involvement on chest computed tomography in the acute phase of Covid-19 infection, and bronchodilator reversibility test results were recorded. Smoking history and forced expiratory volume in the first second (FEV1) were compared.Results: FEV1 increase ≥ 200 ml was observed in 40 (26.5%) patients. In 24 (15.9%) patients, an increase in FEV1 was found to be 200 ml and above, and the percentage of FEV1 was 12% or more. While 14 (9.3%) patients were diagnosed with asthma, 13 (8.6%) patients were diagnosed with nonreversible airflow obstruction (NRAO), and 1 (0.7%) patient was diagnosed with chronic obstructive pulmonary disease (COPD).Conclusions: COVID-19 infection may play a vital role in initiating asthma pathogenesis. It should be kept in mind that viral infection-related asthma may be the underlying cause of prolonged cough and dyspnea after COVID-19 infection.

Can oscillometry be a substitute to spirometry in the indigent?

The practical difficulties of using spirometry in a 3-year-old girl are highlighted, especially during the COVID-19 era. Oscillometry, a tidal breath-based technique, has shown promising future to reliably assess lung functions in the vulnerable cohort. A simple algorithmic approach has been provided till reference values can be established with multicenter studies.

Efficient Security and Authentication for Edge-Based Internet of Medical Things.

Internet of Medical Things (IoMT)-driven smart health and emotional care is revolutionizing the healthcare industry by embracing several technologies related to multimodal physiological data collection, communication, intelligent automation, and efficient manufacturing. The authentication and secure exchange of electronic health records (EHRs), comprising of patient data collected using wearable sensors and laboratory investigations, is of paramount importance. In this article, we present a novel high payload and reversible EHR embedding framework to secure the patient information successfully and authenticate the received content. The proposed approach is based on novel left data mapping (LDM), pixel repetition method (PRM), RC4 encryption, and checksum computation. The input image of size [Formula: see text] is upscaled by using PRM that guarantees reversibility with lesser computational complexity. The binary secret data are encrypted using the RC4 encryption algorithm and then the encrypted data are grouped into 3-bit chunks and converted into decimal equivalents. Before embedding, these decimal digits are encoded by LDM. To embed the shifted data, the cover image is divided into [Formula: see text] blocks and then in each block, two digits are embedded into the counter diagonal pixels. For tamper detection and localization, a checksum digit computed from the block is embedded into one of the main diagonal pixels. A fragile logo is embedded into the cover images in addition to EHR to facilitate early tamper detection. The average peak signal to noise ratio (PSNR) of the stego-images obtained is 41.95 dB for a very high embedding capacity of 2.25 bits per pixel. Furthermore, the embedding time is less than 0.2 s. Experimental results reveal that our approach outperforms many state-of-the-art techniques in terms of payload, imperceptibility, computational complexity, and capability to detect and localize tamper. All the attributes affirm that the proposed scheme is a potential candidate for providing better security and authentication solutions for IoMT-based smart health.

Similarities and differences in the conformational stability and reversibility of ORF8, an accessory protein of SARS-CoV-2, and its L84S variant.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has the characteristic accessory protein ORF8. Although clinical reports indicate that ORF8 variant strains (Δ382 and L84S variants) are less likely to cause severe illness, functional differences between wild-type and variant ORF8 are unknown. Furthermore, the physicochemical properties of the ORF8 protein have not been analyzed. In this study, the physicochemical properties of the wild-type ORF8 and its L84S variant were analyzed and compared. Using the tobacco BY-2 cell production system, which has been successfully used to produce the wild-type ORF8 protein with a single conformation, was used to successfully produce the ORF8 L84S variant protein at the same level as wild-type ORF8. The produced proteins were purified, and their temperature and pH dependencies were examined using nuclear magnetic resonance spectra. Our data suggested that the wild-type and L84S variant ORF8 structures are highly stable over a wide temperature range. Both proteins displayed an aggregated conformation at higher temperature that reverted when the temperature was decreased to room temperature. Moreover, ORF8 precipitated at acidic pH and this precipitation was reversed when the solution pH was shifted to neutral. Interestingly, the L84S variant exhibited greater solubility than wild-type ORF8 under acidic conditions. Thus, the finding indicated that conformational stability and reversibility of ORF8 are key properties related to function in oppressive environments.