Respiratory Infectious Diseases Research Articles

Advanced nanomedicines and immunotherapeutics to treat respiratory diseases especially COVID-19 induced thrombosis

Immunotherapy and associated immune regulation strategies gained huge attraction in order to be utilized for treatment and prevention of respiratory diseases. Engineering specifically nanomedicines can be used to regulate host immunity in lungs in the case of respiratory diseases including coronavirus disease 2019 (COVID-19) infection. COVID-19 causes pulmonary embolisms, thus new therapeutic options are required to target thrombosis, as conventional treatment options are either not effective due to the complexity of the immune-thrombosis pathophysiology. In this review, we discuss regulation of immune response in respiratory diseases especially COVID-19. We further discuss thrombosis and provide an overview of some antithrombotic nanoparticles, which can be used to develop nanomedicine against thrombo-inflammation induced by COVID-19 and other respiratory infectious diseases. We also elaborate the importance of immunomodulatory nanomedicines that can block pro-inflammatory signalling pathways, and thus can be recommended to treat respiratory infectious diseases.

An Infection Model for SARS-CoV-2 Using Rat Transplanted with hiPSC-Airway Epithelial Cells.

Investigating the infection mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the airway epithelium and developing effective defense strategies against infection are important. To achieve this, establishing appropriate infection models is crucial. Therefore, various in vitro models, such as cell lines and primary cultures, and invivo models involving animals that exhibit SARS-CoV-2 infection and genetically humanized animals have been used as animal models. However, no animal model has been established that allows infection experiments with human cells under the physiological environment of airway epithelia. Therefore, we aimed to establish a novel animal model that enables infection experiments using human cells. Human induced pluripotent stem cell-derived airway epithelial cell-transplanted nude rats (hiPSC-AEC rats) were used, and infection studies were performed by spraying lentiviral pseudoviruses containing SARS-CoV-2 spike protein and the GFP gene on the tracheae. After infection, immunohistochemical analyses revealed the existence of GFP-positive-infected transplanted cells in the epithelial and submucosal layers. In this study, a SARS-CoV-2 infection animal model including human cells was established mimicking infection through respiration, and we demonstrated that the hiPSC-AEC rat could be used as an animal model for basic research and the development of therapeutic methods for human-specific respiratory infectious diseases.

One-hit kill: On the inactivation of RNA viruses by ultraviolet (UV)-C-induced genomic damage

Large scale outbreaks of infectious respiratory disease have repeatedly plagued the globe over the last 100 years. The scope and strength of the outbreaks are getting worse as pathogenic RNA viruses are rapidly evolving and highly evasive to vaccines and anti-viral drugs. Germicidal UV-C is considered as a robust agent to disinfect RNA viruses regardless of their evolution. While genomic damage by UV-C has been known to be associated with viral inactivation, the precise relationship between the damage and inactivation remains unsettled as genomic damage has been analyzed in small areas, typically under 0.5 kb. In this study, we assessed genomic damage by the reduced efficiency of reverse transcription of regions of up to 7.2 kb. Our data seem to indicate that genomic damage was directly proportional to the size of the genome, and a single hit of damage was sufficient for inactivation of RNA viruses. The high efficacy of UV-C is already effectively adopted to inactivate airborne RNA viruses.

Trends in Nationally Notifiable Infectious Diseases in Humans and Animals during COVID-19 Pandemic, South Korea.

We investigated trends in notifiable infectious diseases in both humans and animals during the COVID-19 pandemic in South Korea and compared those data against expected trends had nonpharmaceutical interventions (NPIs) not been implemented. We found that human respiratory infectious diseases other than COVID-19 decreased by an average of 54.7% after NPIs were introduced. On the basis of that trend, we estimated that annual medical expenses associated with respiratory infections other than COVID-19 also decreased by 3.8% in 2020 and 18.9% in 2021. However, human gastrointestinal infectious diseases and livestock diseases exhibited similar or even higher incidence rates after NPIs were instituted. Our investigation revealed that the preventive effect of NPIs varied among diseases and that NPIs might have had limited effectiveness in reducing the spread of certain types of infectious diseases. These findings suggest the need for future, novel public health interventions to compensate for such limitations.

Rapid diagnosis of canine respiratory coronavirus, canine influenza virus, canine distemper virus and canine parainfluenza virus with a Taqman probe-based multiplex real-time PCR

Canine Infectious Respiratory Disease Complex (CIRDC) is a highly infectious diseases. Canine respiratory coronavirus (CRCoV), Canine influenza virus (CIV), Canine distemper virus (CDV), and Canine parainfluenza virus (CPiV) are crucial pathogens causing CIRDC. Due to the similar clinical symptoms induced by these viruses, differential diagnosis based solely on symptoms can be challenging. In this study, a multiplex real-time PCR assay was developed for detecting the four RNA viruses of CIRDC. Specific primers and probes were designed to target M gene of CRCoV, M gene of CIV, N gene of CDV and NP gene of CPiV. The detection limit is 10 copies/μL for CIV or CRCoV, while the detection limit of CDV or CPiV is 100 copies/μL. Intra-group and inter-group repeatability coefficient of variation (CV) were both less than 2 %. A total of 341 clinical canine samples were analyzed, and the results indicated that the method developed in our study owns a good consistency and better specificity compared with the conventional reverse transcription PCR. This study provides a new method to enable the simultaneous detection of all four pathogens in a single reaction, improving the efficiency for monitoring the prevalence of four viruses in CIRDC, which benefits the control of CIRDC.

Characteristics of COVID-19 patients with coronary artery disease comorbidity

Coronavirus disease 2019 (COVID-19) is an infectious respiratory disease which is caused by the SARS-CoV-2 virus. Coronary heart disease is a disease caused by plaque build-up in artery walls which supply blood to the heart and other body parts. Coronary heart disease is amongst the most severe COVID-19 comorbidities. Objective: To determine the patient profile of COVID-19 patients with coronary heart disease comorbidity Methods: Literature study with a systematic review that uses previous research as a reference to generate conclusions. Results: Based on the 24 journals used in this literature review, 11 journals discuss the topic of age, 9 journals discuss the topic of gender, and 8 journals discuss the topic of the prognosis of COVID-19 patients with coronary heart disease comorbidity. Conclusion: The mean age of COVID-19 patients with coronary heart disease comorbidity is 63,4 years old. The gender in this case is 64,7% males dan 34,3% females. The rates for prognosis are 47,6% of patients need to go to the ICU, 32,8% of patients died, 51,75% of patients recovered and 36,5% of patients need further treatment.

Community-acquired pneumonia associated with immunosuppression due to follicular thyroid cancer: a case report

BackgroundWe present the case of a woman with cancer, which weakened the immune system and increased the risk of infection. Thus, infections are a frequent complication of cancer. The development of community-acquired pneumonia, an acute respiratory infectious disease that damages the lung parenchyma, caused by the invasion of pathogenic microorganisms, can lead to respiratory failure with multiorgan failure due to respiratory sepsis.Case presentationCase report of a 38-year-old mixed-race woman with diabetes mellitus and irregular treatment, who was admitted with community-acquired pneumonia complicated by type I respiratory failure requiring mechanical ventilation. During her hospital stay, she developed ventilator-associated pneumonia, recurrent empyema, bronchopleural fistula, refractory septic shock and multiorgan dysfunction despite multiple interventions. The patient required prolonged mechanical ventilation, vasopressor support and antibiotic therapy. After 62 days, metastatic papillary thyroid carcinoma was diagnosed. She presented with hypoparathyroidism and permanent hypocalcemia. She died after multiple complications and a refractory critical condition.ConclusionThe case exemplifies the potential severity of community-acquired pneumonia in a patient with risk factors such as diabetes and immunosuppression. It highlights the complexity of treating multiple comorbidities and the importance of multidisciplinary management with close surveillance for timely interventions for complications.

Telemedical management of symptomatic Covid-19 outpatients

BackgroundCovid-19 remains a challenge to individual health and health care resources worldwide. Telemedical surveillance might minimize hospitalization and direct patient-physician-contacts. Yet, randomized clinical trials evaluating telemedical management of Covid-19 patients are lacking.MethodsCOVID SMART is a randomized, open label, controlled clinical trial investigating whether telemedicine reduces the primary endpoint of hospitalization or any unscheduled utilization of an emergency medical service within 30 days of follow-up. Key secondary endpoints included mortality and primary endpoint components. We enrolled acutely infected SARS-CoV2 patients suitable for outpatient care. All presented with ≥1 risk factor for an adverse Covid-19 course. Patients were randomized 1:1 into a control group receiving standard of care and an intervention group receiving smartphone-based assessment of oxygen saturation, heart rate and electrocardiogram, and telemedical counsellingviaa 24/7 emergency hotline.ResultsOf 607 enrolled patients (mean age 46.7±13.5 years), 304 were randomized into the intervention and 303 into the control group. The primary endpoint occurred in 6.9% (n=21) of the intervention and in 9.6% (n=29) of the control group (hazard ratio 0.72, 95% confidence interval 0.41–1.26; p=0.24). No deaths occurred during follow-up. Fewer intervention group participants utilized outpatient-based emergency medical services (hazard ratio 0.43, 95% confidence interval 0.20–0.90; p=0.03).ConclusionsCOVID SMART is the first randomized clinical trial assessing the benefit of telemedicine in an acute respiratory infectious disease. Whereas telemedical management did not reduce the primary endpoint of hospitalization, fewer intervention group patients used outpatient-based emergency services, suggesting a potential benefit for less-acutely infected individuals.Trial registrationclinicaltrials.gov (NCT04471636)

Infection prevention practice in home healthcare: a mixed-method study in two Swiss home healthcare organisations.

Infection prevention and control (IPC) research has long neglected the home healthcare sector with its unique challenges. This study aimed to gain an understanding of the barriers to the implementation of infection prevention practices relevant to this setting, the related attitudes, perceived relevance and priorities from the home healthcare worker perspective in Switzerland. The mixed-method study involved semi-structured interviews (n = 18) and an anonymous web-based survey (n = 144) among nursing assistants and nurses from two home healthcare organizations in northwest Switzerland. Questions in both sub-studies focused on perceived challenges to infection prevention practices, perceived relevance, and related attitudes and mitigation strategies. Using an exploratory-sequential design, survey questions were designed to quantify and complement the findings from the interview study. Healthcare workers in these two organisations felt adequately protected, trained and supported by their organisations regarding IPC (survey agreement rates > 90%). General challenges to IPC in the home environment most agreed on were lack of cleanliness, lack of space, and the priorities of the patient to be respected (survey agreement rates 85.4%, 77.1%, and 70.8%, respectively). Practices and perceived challenges in the case of colonisation with multi-drug resistant organisms (MDRO) and potentially infectious diarrheal or respiratory illnesses varied highly regarding information transfer, use of protective equipment, and use and disinfection practices of multi-use equipment. Challenges to hand hygiene, sharps safety, waste management and decontamination of equipment did not feature as a prominent concern. This study is the first to characterise the implementation of infection prevention practices and the related challenges in home healthcare in Switzerland. Home healthcare workers describe various challenges related to infection prevention practices as largely manageable in their work routine, and generally show satisfaction with the support provided by their organisations regarding IPC precautions. Key findings regarding challenges amenable to interventions include uncertainty and inconsistency regarding the management of MDRO colonisation and acute illnesses, and gaps in information transfer. Those challenges may benefit from both organisational interventions and further research into the level of precautions that are appropriate to the home healthcare setting.

Gypsum alleviates pneumonia via the gut–lung axis by mediating ILC2 compartmental migration

IntroductionBacterial pneumonia is a common lower respiratory tract infectious disease. Gypsum, a type of calcium sulfate mineral, primarily consists of calcium sulfate and contains trace amounts of other metallic elements. In traditional Chinese medicine, gypsum has been widely applied, possessing effects such as heat-clearing, detoxification, cooling blood, arresting bleeding, reducing swelling, and alleviating pain. The purpose of this study was to investigate the mechanism of gypsum inhibition of Streptococcus pneumoniae -induced pneumonia by mediating interregional migration of ILC2 through the gut-lung axis. MethodsNormal pneumonia model was induced by Streptococcus pneumoniae, and pseudo-sterile mouse model was established using broad-spectrum antibiotics. The influence of gypsum on the intestinal flora was analyzed using 16S rDNA. Flow cytometry was used to analyze the typing and content of ILC2 in mouse mesenteric lymph nodes and lung tissues. The expression levels of inflammatory cytokines and specific targets associated with immune migration were assessed using ELISA, RT-qPCR, and western blotting methods. And the effects of gypsum on mucosal barrier using IHC. ResultsGypsum effectively alleviates pulmonary inflammation in mice with pneumonia. Gypsum restores the gut microbiota in mice with Streptococcus pneumoniae and gypsum can regulate the expression of miR-155, miR-146a, IL-25, and S1P, promoting the migration of intestinal ILC2s to the lungs. Finally promotes type 2 immunity, alleviating pneumonia and restore lung mucosal barrier. DiscussionOur study contributes to the understanding of gypsum's function in treating infectious pulmonary conditions. Its mechanism involves remedying gut dysbiosis and initiating ILC2 migration, culminating in decreased lung inflammation and enhanced mucosal immunity in the lungs.

Sentiment Analysis of COVID-19 Tweets using Neural Network in Pakistan

Covid-19 is a respiratory infectious disease that spreads from person to person. World Health Organization declared it a pandemic in March 2020. Social distancing and lockdowns during the pandemic affected the lives, sentiments, and mental health of people. They are mentally, physically, and emotionally disturbed. It was observed that the verification of the very first Covid case increased the precariousness and fear in Pakistan because people had no information about the state policies. In this paper, Covid-related tweets from Pakistan for the year 2021 are collected. Pakistan faced two Covid waves in 2021. Dataset is preprocessed and a neural network-based model is applied to analyze the sentiment of the tweet. Sentiments of people are analyzed separately for each Covid wave, moreover, a comparative analysis is presented to discuss the change in people's sentiments with the passage of time. Results show a reduction in the number of tweets from third to fourth wave. Moreover, the %decrease in negative and positive sentiments are 6 and 1 respectively which show that by the passage of time, people started living with the environment and time healed the wounds of fears and uncertainty in their lives.

Dynamic contact networks of residents of an urban jail in the era of SARS-CoV-2

BackgroundIn custodial settings such as jails and prisons, infectious disease transmission is heightened by factors such as overcrowding and limited healthcare access. Specific features of social contact networks within these settings have not been sufficiently characterized, especially in the context of a large-scale respiratory infectious disease outbreak. The study aims to quantify contact network dynamics within the Fulton County Jail in Atlanta, Georgia. MethodsJail roster data were utilized to construct social contact networks. Rosters included resident details, cell locations, and demographic information. This analysis involved 6702 male residents over 140,901 person days. Network statistics, including degree, mixing, and dissolution (movement within and out of the jail) rates, were assessed. We compared outcomes for two distinct periods (January 2022 and April 2022) to understand potential responses in network structures during and after the SARS-CoV-2 Omicron variant peak. ResultsWe found high cross-sectional network degree at both cell and block levels. While mean degree increased with age, older residents exhibited lower degree during the Omicron peak. Block-level networks demonstrated higher mean degrees than cell-level networks. Cumulative degree distributions increased from January to April, indicating heightened contacts after the outbreak. Assortative age mixing was strong, especially for younger residents. Dynamic network statistics illustrated increased degrees over time, emphasizing the potential for disease spread. ConclusionsDespite some reduction in network characteristics during the Omicron peak, the contact networks within the Fulton County Jail presented ideal conditions for infectious disease transmission. Age-specific mixing patterns suggested unintentional age segregation, potentially limiting disease spread to older residents. This study underscores the necessity for ongoing monitoring of contact networks in carceral settings and provides valuable insights for epidemic modeling and intervention strategies, including quarantine, depopulation, and vaccination, laying a foundation for understanding disease dynamics in such environments.Top of Form

HOW TO REDUCE TRANSMISSION OF RESPIRATORY INFECTIOUS DISEASE IN INTERIOR SPACES: AN EMPIRICAL STUDY WITH INTERIOR DESIGN PROFESSIONALS

ABSTRACT This study was motivated by the need for empirical evidence to inform design guidelines for interior workspaces during the COVID-19 pandemic. This research had two goals: to identify the features of interior spaces and behaviors in Korea where many confirmed cases of COVID-19 were found; and to examine design professionals’ opinions on workplace management and operation to reduce transmission of respiratory infectious disease. A content analysis of newspaper articles on confirmed cases was conducted and a survey was administered to design professionals. The analysis identified common features of the interior spaces with confirmed cases of COVID-19. Based on the analysis of the article contents, a questionnaire was constructed. The questionnaire asked design professionals to suggest interior design considerations that could prevent the spread of the virus in interior spaces. They emphasized the separation of individual spaces from shared spaces; installing partitions in rooms that could not be divided; ending two-way traffic in narrow hallways; reducing room density and avoiding crowding; adopting touchless technologies and no-touch access to interior spaces; automating interior equipment and facilities; and encouraging office users to work from home if possible. These findings should be factored into interior space planning and management to reduce the risk of exposing future users of these spaces to infectious respiratory diseases.

Predominance of A2063G mutant strains in the Mycoplasma pneumoniae epidemic in children: A clinical and epidemiological study in 2023 in Wuhan, China

ObjectivesThe prevalence of respiratory infectious diseases has changed in the post-COVID-19 epidemic era, and mycoplasma pneumoniae (MP) infection in children has attracted wide attention. MethodsChildren hospitalized for pneumonia in Wuhan, China, in 2023 were enrolled. Respiratory secretions were obtained for the targeted next-generation sequencing (tNGS) including mutation of MP. Pulmonary inflammation was divided into bronchopneumonia and pulmonary consolidation/atelectasis according to lung computed tomography imaging. ResultsOf the 667 pediatric pneumonia, 478 were MP positive (72%). The positive rate of MP detected by tNGS increased from April, and MP had become the primary pathogen of pneumonia in children in 2023. The 23S rRNA mutations were all A2063G, accounting for 85% of detected MP. The clinical symptoms of the mutant and wild-type strains were similar, with half of them experiencing atelectasis and lung consolidation. Early bronchoscopic lavage combined with azithromycin in pediatric pulmonary consolidation was an effective therapy strategy, which could be an alternative selection to MP pneumonia treatment. ConclusionsA2063G mutant strain MP was the primary pathogen of mycoplasma pneumoniae in children recently, which was often complicated by extra-pulmonary symptoms and complications.

Association between ambient temperature and risk of notifiable infectious diseases in China from 2011 to 2019

ABSTRACT Previous studies on temperature and infectious diseases primarily focused on individual disease types, yielding inconsistent conclusions. This study collected monthly data on notifiable infectious disease cases and meteorological variables across 7 provinces in China from 2011 to 2019. A distributed lag nonlinear model was used to evaluate the association between ambient temperature and infectious diseases within each province, and random meta-analysis was applied to evaluate the pooled effect. Extreme hot temperature (the 97.5th percentile) was positively associated with the risk of respiratory infectious diseases with the relative risk (RR) of 1.45 (95%CI: 1.01–2.08). Conversely, extreme cold temperature (the 2.5th percentile) was negatively associated with intestinal infectious diseases and zoonotic diseases and vector-borne diseases, reporting RRs of 0.43 (95%CI: 0.30–0.60) and 0.46 (95%CI: 0.38–0.57), respectively. This study described the nonlinear association between ambient temperature and infectious diseases with different transmission routes, informing comprehensive prevention and control strategies for temperature-related infectious diseases.

Development and Evaluation of Monoclonal Antibodies against CBPP Antigen with the End Goal of Developing an ELISA Kit.

Contagious bovine pleuropneumonia (CBPP) is an infectious and contagious bacterial respiratory disease that affects cattle with significant economic losses to the African animal industry. The use of ELISA kits based on monoclonal antibodies (mAbs) will aid in quick and precise diagnosis of CBPP, contributing to disease control and prevention in cattle. Thus, this research aims to develop and evaluate monoclonal antibodies against CBPP (T1/44) antigen for use in ELISA kits for CBPP diagnosis. Hybridoma technology was used to develop monoclonal antibodies that recognize and bind to the CBPP (T1/44) antigen. The antibody-secreting hybridomas were produced after immunizing mice with purified CBPP antigens. The hybridomas were screened for high sensitivity, specificity, and liking to the antigen. The selected mAbs were assessed for sensitivity and specificity against CBPP antigen using different immunoassays, dot-blot, ELISA, and mouse mAb isotyping. The monoclonal antibodies were profoundly specific, with a higher hindrance to CBPP antigen (<0.50 OD) while lacking cross-reactivity to other antigens. The monoclonal antibodies could distinguish CBPP antigen at low concentrations, showing their high sensitivity (>80% PI). The isotyped mAbs of intrigued appeared to have a place in the IgG class. These identified monoclonal antibodies can be utilized to develop an ELISA kit for CBPP diagnosis, which would give a fast, precise, and cost-effective strategy for screening and checking CBPP in cattle herds.

Respiratory viral infections before the COVID-19 in Portugal: A single center study

ObjectivesWe aimed to describe the respiratory viruses (RV) found in respiratory samples from patients admitted to Hospital de São Bernardo, Setúbal, Portugal, between October 2019 and March 2020, and to correlate these with clinical features. DesignThis retrospective study explored 948 fresh frozen naso/oropharyngeal swabs, tested by reverse transcription-polymerase chain reaction. ResultsRhinovirus/enterovirus, influenza, and respiratory syncytial virus (hRSV) were the most prevalent RV. Half of the patients fulfilled the acute respiratory infection (ARI) and/or influenza-like illness (ILI) criteria, with increasing age significantly reducing the risk of ARI and/or ILI. Hospital admission was more frequently observed in symptomatic patients, but the length of stay and mortality were significantly lower. Most (96.5 %) patients had a main respiratory diagnosis. In adults, the most prevalent was pneumonia, which particularly affected older patients, while in children, the most common was bronchiolitis. The number of hospital admissions was high. Sudden onset, shortness of breath, older age, and hRSV detection significantly increased the risk of hospital admission overall. In bronchiolitis, female gender significantly increased the risk of hospital admission, while older age significantly reduced this risk. Twenty patients died within the first month of sampling, and all were older adults. Older age and male gender significantly increased the risk of death. ConclusionsRespiratory viral infections can have a significant clinical impact, particularly in young infants with bronchiolitis and older adults with pneumonia. This study provides the first snapshot of the respiratory viral infections just before the outbreak of SARS-CoV-2 in Portugal, providing relevant clinical insights.

Evaluating Seasonal Variations in Human Contact Patterns and Their Impact on the Transmission of Respiratory Infectious Diseases.

Human contact patterns are a key determinant driving the spread of respiratory infectious diseases. However, the relationship between contact patterns and seasonality as well as their possible association with the seasonality of respiratory diseases is yet to be clarified. We investigated the association between temperature and human contact patterns using data collected through a cross-sectional diary-based contact survey in Shanghai, China, between December 24, 2017, and May 30, 2018. We then developed a compartmental model of influenza transmission informed by the derived seasonal trends in the number of contacts and validated it against A(H1N1)pdm09 influenza data collected in Shanghai during the same period. We identified a significant inverse relationship between the number of contacts and the seasonal temperature trend defined as a spline interpolation of temperature data (p = 0.003). We estimated an average of 16.4 (95% PrI: 15.1-17.5) contacts per day in December 2017 that increased to an average of 17.6 contacts (95% PrI: 16.5-19.3) in January 2018 and then declined to an average of 10.3 (95% PrI: 9.4-10.8) in May 2018. Estimates of influenza incidence obtained by the compartmental model comply with the observed epidemiological data. The reproduction number was estimated to increase from 1.24 (95% CI: 1.21-1.27) in December to a peak of 1.34 (95% CI: 1.31-1.37) in January. The estimated median infection attack rate at the end of the season was 27.4% (95% CI: 23.7-30.5%). Our findings support a relationship between temperature and contact patterns, which can contribute to deepen the understanding of the relationship between social interactions and the epidemiology of respiratory infectious diseases.

Bioinformation Analysis of Differential Expression Proteins in Different Processes of COVID-19.

COVID-19 is a highly infectious respiratory disease whose progression has been associated with multiple factors. From SARS-CoV-2 infection to death, biomarkers capable of predicting different disease processes are needed to help us further understand the molecular progression of COVID-19 disease. The aim is to find differentially expressed proteins that are associated with the progression of COVID-19 disease or can be potential biomarkers, and to provide a reference for further understanding of the molecular mechanisms of COVID-19 occurrence, progression, and treatment. Data-independent Acquisition (DIA) proteomics to obtain sample protein expression data, using R language screening differentially expressed proteins. Gene Ontology and Kyoto Encyclopedia for Genes and Genomes analysis was performed on differential proteins and protein-protein interaction (PPI) network was constructed to screen key proteins. A total of 47 differentially expressed proteins were obtained from COVID-19 incubation patients and healthy population (L/H), mainly enriched in platelet-related functions, and complement and coagulation cascade reaction pathways, such as platelet degranulation and platelet aggregation. A total of 42 differential proteins were obtained in clinical and latent phase patients (C/L), also mainly enriched in platelet-related functions and in complement and coagulation cascade reactions, platelet activation pathways. A total of 10 differential proteins were screened in recovery and clinical phase patients (R/C), mostly immune-related proteins. The differentially expressed proteins in different stages of COVID-19 are mostly closely associated with coagulation, and key differential proteins, such as FGA, FGB, FGG, ACTB, PFN1, VCL, SERPZNCL, APOC3, LTF, and DEFA1, have the potential to be used as early diagnostic markers.

Exploring post-COVID-19 health effects and features with advanced machine learning techniques

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effects, particularly influenced by demographic factors such as gender and age, as well as physiological and neurological factors like sleep patterns, emotional states, anxiety, and memory. This research aims to explore various health factors affecting different demographic profiles and establish significant correlations among physiological and neurological factors in the post-COVID-19 state. To achieve these objectives, we have identified the post-COVID-19 health factors and based on these factors survey data were collected from COVID-recovered patients in Bangladesh. Employing diverse machine learning algorithms, we utilised the best prediction model for post-COVID-19 factors. Initial findings from statistical analysis were further validated using Chi-square to demonstrate significant relationships among these elements. Additionally, Pearson’s coefficient was utilized to indicate positive or negative associations among various physiological and neurological factors in the post-COVID-19 state. Finally, we determined the most effective machine learning model and identified key features using analytical methods such as the Gini Index, Feature Coefficients, Information Gain, and SHAP Value Assessment. And found that the Decision Tree model excelled in identifying crucial features while predicting the extent of post-COVID-19 impact.