Coronaviruses - Volume 6, Issue 2, 2025

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been shown to trigger autoimmunity, and the phenomenon leads to several chronic human diseases such as Type-1 diabetes, Crohn’s disease, vasculitis, Guillian-Barrė syndrome, etc. The mechanism underlying SARS-CoV-2-induced autoimmune response is unknown and is an active area of interest for the researchers.

The primary objective of this study is to identify the autoantigen markers for the classification of SARS-CoV-2 (COVID-19 positive and negative samples) that trigger an immune response leading to autoimmunity using a machine learning approach that provides information to obtain a more accurate diagnosis for COVID-induced diseases.

Our study reports the transcriptomic profile of the long COVID patient's whole blood samples that are collected from 0 to 35^th day of acute infection as described in the GSE215865 dataset (1391 Samples after preprocessing: 1233-COVID positive and 158-COVID negative). The binary classification algorithm from the sci-kit learn python library, namely logistic regression and random forest with 10-fold cross-validation, was applied to the processed data, followed by a selection of the 20 best gene features with recursive feature elimination from a set of 10,719 gene features to obtain the classification accuracy of 87%.

The fidgetin, microtubule severing factor (FIGN), SH3 and cysteine-rich domain (STAC), Cadherin-6 (CDH6), docking protein 6 (DOK6), nuclear RNA export factor 3 (NXF3) and maternally expressed 3 (MEG3) are the autoantigens markers identified for classification of COVID-positive and negative samples.

The identified autoantigen markers from transcriptomic datasets using machine learning techniques provide a deeper understanding of COVID-induced diseases and may play an important role as potential diagnostic and drug targets for COVID-19.

‘Long COVID’ describes a wide range of symptoms lasting for at least four weeks after infection. Still, there are no therapies available right now that are intended to treat long-term COVID-19.

Here, we reported a 36-year-old woman with 2 main issues: persistent symptoms for nine months after SARS-CoV-2 infection and selected symptoms after Sinopharm COVID-19 vaccination. In this case, after the third infection, severe fatigue, panic attacks and dermatological problems were permanent for approximately nine months. As there was no alternative diagnosis, she was diagnosed with ’long COVID’, and it is the longest duration recorded, as per our knowledge. Besides, 60 days after the second vaccination, pain in the calcaneus region of her left foot, mild chest pain, joint pain, severe shoulder pain, extreme fatigue, and numbness were among the reported symptoms.

Although these uncommon complications can be related to vaccination, the advantages of obtaining the vaccine exceed the risks.

To determine the association between changes in haematological parameters and mortality in patients hospitalized due to severe COVID-19 at a Peruvian reference hospital from April to December 2020.

Observational, analytical, historical cohort study based on the review of clinical records of patients hospitalized due to severe COVID-19 from April to December 2020. We evaluated changes in common haematological parameters, including white blood cells (WBCs), lymphocytes, neutrophils, and platelet counts, as well as the neutrophil-to-lymphocyte ratio (NLR) on the third and seventh days of hospitalization compared with admission values in the deceased and non-deceased groups. Changes in haematological parameters were expressed as median and interquartile ranges (IQR). Multivariate Poisson regression analysis was further done to evaluate the effect of haematological changes in mortality, adjusting for gender, age, and comorbidities.

We included 1033 cases, of which 68.05% were male. Deceased patients had a significant increase in total WBC on the third day (1.0 *10³/µL; IQR -1.7 to 5.4) and the seventh day (1.6*10³/µL; IQR -1.9 to 4.9) compared to their admission values. The neutrophil count in the deceased patients also increased on the third day (1.2; IQR -1.7 to 4.9) and seventh day (1.9; IQR-1.5 to 5.8), as did the NLR ratio on the third day (0.2; IQR -0.4 to 1.6) and seventh day (0.7; IQR -0.2 to 2.2). Surviving patients showed an opposite trend in these parameters. In contrast, platelet counts increased on the third day (49*10⁵/µL; IQR -0.3 to 1.3) and the seventh day (90*10⁵; IQR 0.0 to 2.0) in surviving patients, whereas deceased patients did not show significant changes. All these differences remained statistically significant in the adjusted analysis.

An increase in total WBC, neutrophils, and NLR at the third and seventh days compared to admission values was associated with higher mortality in patients hospitalized due to COVID-19, while an increase in platelet count was associated with decreased mortality. Monitoring these changes can help in identifying those patients with higher mortality risk.

Even after more than three years of emergence of coronavirus disease 2019 (COVID-19), it remains incurable, despite the use of emergency-approved vaccines. The impact of the emergency-approved vaccines against it is not highly certain. The entire world may face surge of new wave of the infection, and therefore, its reoccurrence cannot be denied. Causalities and economic losses may happen in the future. In this situation, it is need of the hour to explore some suitable therapeutic agents against this highly infectious and challenging disease. Organic molecules, inactivated virus etc were largely focused to derive the vaccines, however, nanomaterials still remain untested for it. Interaction of nanomaterials like graphene against proteins of the coronavirus to inhibit its activity is yet to be tested computationally.

In this computational research work, graphene is tested for interaction with the viral proteins, as the dimension of the novel coronavirus also belongs to nano-scale (diameter 65-125 nm). A detailed study on docking structures and molecular dynamics between viral proteins and graphene, is undertaken. Autodock and Discovery Studio packages were used for docking calculations and interaction analysis, respectively. Molecular dynamics simulation was performed using NAMD software and obtained results were visualized using VMD software.

Range of proteins of the coronavirus including spike proteins (both open and closed form), Main Protease (MPRO), Receptor-Binding Domain (RBD), RNA-dependent RNA polymerase (RdRp), and Angiotensin Converting Enzyme 2 (ACE2) have been individually evaluated for their docking and dynamics with graphene, so as to inactivate the virus. Details of interacting amino acid residues of coronavirus with graphene are found in the study.

Computationally, it is observed that most of these proteins were found interactive through their amino acid residues with graphene. Number of interacting amino acid residues is considerable enough to collectively acquire high binding energy. It can be envisaged that cumulative perturbations of all the interactions of each protein caused by graphene can lower down or inactivate the virus.

This study aimed to determine the differences in laboratory and clinical characteristics of pregnant and non-pregnant women with COVID-19 in Hamadan, the West of Iran.

This cross-sectional study compared 135 pregnant with 135 non-pregnant women without underlying diseases and matched by age with COVID-19 from March 2020 to June 2021 in Hamadan, a western city in Iran. Their demographic characteristics, clinical symptoms, vital signs, and laboratory findings were evaluated using a preset checklist and contrasted between the two groups. The adjusted odds ratios (ORs) for the outcomes of illness were presented. A considerable amount of analysis was performed on all data using the SPSS version 26 software.

In general, there was a significant association between most clinical symptoms and status of pregnancy. Although the Peripheral oxygen saturation with a pulse oximeter (SPO2) mean was significantly lower among non-pregnant compared to the pregnant women (89.19±4.52 versus 94.91±3.12; p < 0.001), the mean of heart rate was significantly lower among pregnant women compared to non-pregnant women (90.59±11.80 versus 96.50±15.02; p = 0.001). The percentage of low hemoglobin (Hb), abnormal Blood Urea Nitrogen, high Creatinine (CR), high Erythrocyte Sedimentation Rate and high Lactate Dehydrogenase was significantly higher in non-pregnant women compared to the pregnant women. Women with pregnancy compared to non-pregnant women and women with low Hb compared to normal Hb had a considerably increased chance of intensive care unit /death. Each unit increase in SPO2 and pulse rate resulted in a considerable reduction in this risk. In addition, women with high CR, shortness of breath and per unit rise in temperature had a considerably higher chance of staying in the hospital for a longer period of time.

The clinical and para-clinical manifestations of pregnant women with COVID-19 are different from non-pregnant women. Although there was a significant difference between the two groups due to mortality, the percentage of admission to the intensive care unit in pregnant women with COVID-19 is higher than in non-pregnant women. To avoid these adverse outcomes, pregnant women should take precautions to avoid COVID-19 infection.

India undertakes the largest COVID-19 vaccination drive in the world, which has undergone multiple changes since the beginning. We examined how these changes in strategy affect public perception, which is connected to the campaign’s success.

A cross-sectional approach was undertaken, where non-health worker vaccine recipients at a COVID-19 vaccination centre in Kolkata, India, willing to participate, in Kolkata, India, willing to participate, were approached with a pre-tested questionnaire to understand their perception.

The majority of the participants (61.1% of 753 samples) felt that the under-18 population should have been vaccinated earlier; 32.7% and 13.5% stated effectiveness and safety issues resulted in changes in the vaccination strategy, respectively. A majority (50.7%) opined that vaccine shortage necessitated postponement in the second dose of Covishield. Changes in vaccination schedules caused confusion and chances of a longer-running COVID-19 crisis, according to 65.2% and 40.2% of participants, respectively. Moreover, many (56.3%) were unaware of raised efficacy due to inter-dosage delay. The elderly, females, salaried, and participants without any health worker in the family had a significant chance of having an unfavourable perception towards this changing vaccination strategy.

Vaccines often undergo changes in administration strategy due to evolving evidence. Moreover, it has been observed that a delay in the second dose increases vaccine efficacy. However, inadequate awareness regarding such changes causes confusion and creates a misconception in the public mind. Timely dissemination of accurate scientific information and stopping the propagation of misinformation are necessary to address the dilemma and ensure maximum public support for the vaccination programme.

Unintentional behavioral changes brought on by the COVID-19 outbreak may have contributed to the increase in reported suicidal attempts. The coronavirus pandemic era has contributed to modifying existing domestic violence, mental health, conflict, and anxiety. Moreover, quarantine and self-isolation may have resulted in melancholy, suicidal thoughts, drug and alcohol misuse, and loneliness. Therefore, it is crucial and significant to gather data on the global prevalence of suicide and suicidal attempts throughout the pandemic.

This study's objective was to evaluate the tone of tweets regarding suicide and whether or not those tweets are connected to COVID-19.

Twitter is one of the most widely used channels for sharing people's thoughts in various situations. A total of 9750 tweets have been found with respect to COVID-19-related suicidal ideation and other suicides. Gathered data were pre-processed, and feature vectors were constructed in order to establish a forecast paradigm by using artificial neural networks (ANN), long short-term memory (LSTM), and support vector machine (SVM).

The results demonstrated that ANN outperformed SVM and LSTM in terms of classification, achieving 91.33% accuracy while also having greater recall, precision, F-measure, and minimum error values.

The findings of this study may help to categorize peoples' suicidal thoughts successfully. The results will help to identify future suicidal incidents with the help of the proposed approach and avoid such kinds of situations from occurring.

Critically ill patients with COVID-19 have important risk factors for drug–drug interactions.

This study aimed to characterize and describe the profile and management of drug–drug interactions in critically ill patients affected by COVID-19 in a tertiary care hospital in Colombia.

A descriptive retrospective cohort with an exploratory analytical component was used. The medical records of 191 patients were reviewed from August 2020 to February 2021. An initial descriptive analysis was performed, and a bivariate analysis was developed to include variables of significance in a multivariate analysis.

In our cohort of critically ill patients, the following factors were associated with a higher risk of major outcome development: a higher age (p = 0.037), Charlson comorbidity index (CCI) (p = 0.001), Sequential Organ Failure Assessment (SOFA) score (p = 0.001), a greater number of prescribed drugs, number of interactions, and the presence of type-D interactions.

Identifying clinical predictors and types of drug interactions may alter the development of major outcomes such as mortality.

The Royal Thai College of Obstetricians and Gynaecologists (RTCOG) clinical practice guideline (CPG) does not recommend against elective Cesarean Section (CS) in case of prenatal maternal COVID-19 infections without obstetric indication. In Thailand, little is known about the mode of deliveries and perinatal outcomes in the mentioned group of patients. Therefore, this study aims to fill the gap in knowledge.

The objective of this study was to compare the mode of deliveries and perinatal outcomes between pregnant women, who were infected with COVID-19 and those who were without COVID-19 infection.

The retrospective cohort study was based on data retrieved between February 1^st and March 31^st, 2023. The primary data was collected between July 1^st, 2021, and October 31^st, 2022. Women with COVID-19 infection were matched with the non-COVID-19 group in a 1:1 ratio by date at antenatal care (± 7 days) and their gestational age (± 1 week). Comparison of maternal and perinatal outcomes was made by using chi-squared, Fisher’s exact, relative risk, and t-test as appropriate in STATA software version 10.0.

A total of 252 participants were recruited in this study, with 126 patients in each group. Demographic data between the two groups were comparable except for previous CS. The CS rates in the COVID-19 and non-COVID-19 groups were 46.03% and 30.95%, respectively, with p = 0.009. The significantly increased relative risk of CS in COVID-19 was 1.49 (95%CI, 1.07 to 2.05, p = 0.02). Eight women out of 126 had undergone CS with a “COVID-19 infection” indication (p = 0.007). The length of the maternal hospital stay was comparable. No serious maternal complications were observed. Perinatal outcomes were similar among the two groups, except for neonatal jaundice (p = 0.029), with no reports of COVID-19 infections in delivery-related personnel.

Prenatal COVID-19 infections lead to an increase in CS rate, while perinatal morbidities were comparable in both groups, with COVID-19 and non-COVID-19. The RTCOG’s CPG should be modified.

To shed light on the potential trajectories in the global mortality rate, the central question posed is the trajectory of global death rates in the years to come. This study was an effort to predict the trend of the global mortality rate following the COVID-19 pandemic until 2032 and, based on it, an attempt to contemplate potential solutions available for decision-making and planning.

We employed a time series model to predict future mortality rates based on global mortality rate data. Although several forecasting methods exist for time series data, this study utilized the Autoregressive method. This approach facilitated regression and prediction based on past mortality numbers. To predict mortality rates from 2023 to 2032, we applied an autoregressive model on mortality rate data spanning 1980 to 2022.

The predicted global mortality rate in the next 10 years (post-pandemic era) appeared to be higher than the 10 years before COVID-19 (pre-pandemic era). This projection indicates that despite a declining trend in mortality rates since 2023, the mortality rate from 2023 to 2032 exceeds that of the pre-COVID-19 years. We predict that the ongoing COVID-19 outbreak, although transitioning out of a crisis state, will result in an approximate increase in the global mortality rate over the next 10 years.

Our results indicate a noteworthy increase in the global mortality rate following the emergence of COVID-19. Furthermore, our findings suggest that the mortality rates will remain high in the future. Further research is necessary to attain more accurate insights into this matter.

The novel coronavirus disease also known as COVID-19 was first detected in December 2019 in Wuhan, China and was caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its effect can still be seen in some parts of the world due to the lack of effective antiviral drugs and vaccines for treatment and controlling the pandemic. Chymotrypsin-like protease (3CLpro), also known as the main protease (Mpro) of SARS-CoV-2 plays a vital role during its replication process of the pathogen’s lifecycle and is therefore considered a potential drug target for COVID-19. Hence, targeting the Mpro is an appealing approach for drug development because of its significant role in viral replication and transcription and therefore can act as an attractive drug target to combat COVID-19 as confirmed by researchers through numerous studies so far. Although small molecules dominate the field of drug market so far, peptide inhibitors still represent a class of promising candidates because of their similarity to endogenous ligands, high affinity, and low toxicity. It has been validated that therapeutic peptides can effectively and selectively inhibit the protein-protein interactions in viruses. Hence, it is necessary to design potential peptide inhibitors in order to inhibit the impact of the disease.

To design peptide inhibitors against the SARS-CoV-2 Main Protease using computational methods.

This study involves the development of potential target peptides that can act against the Mpro in a competitive mode against histone deacetylase (HDAC2) which had a high-confidence interaction with Mpro. Based on the interaction between Mpro and HDAC2, 13 peptides were designed out of which based on toxicity, binding affinity and binding site prediction, two peptides (peptide2 and peptide4) were screened and subjected to MD simulation.

Our study shows that the two peptides bind to the active site of the Mpro and it attains a higher stability upon binding to the peptides. We also found out that the Mpro has a strong binding affinity with both the peptides (GBTOT = -72.85 kcal/mol for Mpro-peptide2 complex and GBTOT = -46.36 kcal/mol for the Mpro-peptide4 complex).

Even though declaring those peptides as future potent drug candidates would require more analysis and trials, our analysis will surely add value to the future findings and these findings could aid in the development of novel SARS-CoV-2 Mpro peptide inhibitors. These findings could aid in the development of novel SARS-CoV-2 Mpro peptide inhibitors.

The overcrowding conditions provide a favorable environment for viral transmission and increase the risk of respiratory infections among pilgrims. Hence, acute respiratory infections (ARIs) that can be transmitted through aerosols, droplets, and close contacts are a major public health concern during mass gathering (MG) events like Hajj.

In this study, we reported the prevalence of different respiratory viruses in returning pilgrims at Tehran airport in August 2022 during the COVID-19 pandemic.

In this cross-sectional study, throat and nasal swab samples from pilgrims with respiratory signs and symptoms were taken. The samples were sent to the National Influenza Center for influenza detection. We tested the samples for detection of influenza (IFV), SARS-CoV-2, HCoV-229E, NL63, HKU1, OC43, human respiratory syncytial virus (HRSV), adenovirus (AdV), and human rhinovirus (HRV). Real-time RT-PCR was performed to detect all RNA viruses except HRV, and nested PCR was performed to detect AdV and HRV.

Of returning pilgrims on arrival at Tehran airport, 10 (38.5%) were positive for at least one respiratory virus as follows: 2(7.7%) AdV, 3(11.5%) IFVA, which included 1 A/H1N1, 1 A/H3N2, and 1 A/H3N2 and A/H1N1 coinfection, 2 (7.7%) HCoV-229E, 2(7.7%) SARS-CoV-2, 1(3.9%) HCoV-OC43, and 1(3.9%) HRV. No HRSV was detected. It is worth noting that the SARS-CoV-2-positive sample was co-infected with IFVA/H3N2.

This report showed that respiratory viruses remain a possible public health concern for pilgrims during Hajj seasons. We showed the circulation of some respiratory viruses among a small number of pilgrims during the COVID-19 pandemic.

Two independent sets of medical records, comprising 441 and 100 patients (50 smokers and 50 non-smokers), respectively, clinically diagnosed with COVID-19, suggested reduced death among smokers.

Medical records from patients were examined to record the biochemical parameters available and to perform comparisons between smokers and non-smokers. Bioinformatics was used to predict epitopes of tobacco mosaic virus coat protein (TMV-CP) to produce antibodies to SARS-CoV-2.

Data recorded in 441 medical records indicated no deaths among smoking patients. Death was three times higher in non-smokers than smokers in the second group, comprising 50 smokers and 50 non-smokers. However, biochemical parameters were similar among the groups. Bioinformatics analysis predicted the presence of B-cell epitopes in TMV-CP, suggesting that the production of anti-TMV-CP antibodies in smokers could occur, who, although developing severe forms of COVID-19, had greater survival in the evaluated groups than did non-smokers.

This prospective study suggested that smokers suffer severe effects of SARS-Cov-2 infection, associated with inadequate inflammatory reaction. On the other hand, the deaths of patients in the two groups examined correlated negatively with smokers. Bioinformatics analysis permitted the exploit an exciting hypothesis that anti-TMV-CP antibodies, potentially present in smokers, might act as an immune agent against SARS-CoV-2 at earlier stages of infection. Although these data are sketchy and should be taken carefully, due to the limited set of data, they are helpful for future studies to assess COVID-19 in smokers.

Studies suggest that cancer is a main complication regarding life expectancy and a foremost reason for death worldwide. For the treatment of COVID-19 infected 703,525,337 cases with 6,984,801 deaths worldwide up to February 21, 2024, well-designed pharmacotherapy management in different diseases, such as cancer, is respected. This investigation aims to review the current accessible medical treatment for patients with different diseases, cancer, and COVID-19.

The appropriate documents for this review were achieved by searching databases such as Web of Science, Scopus, and PubMed. Relevant studies included in review articles, clinical trials, and case reports that were evaluated and used (n=109 articles).

In those with cancer and COVID-19, publications reported worsened clinical conditions with a considerably higher risk of death. The result of existing regular antitumor management could be a basis of debate. In the general population, asymptomatic patients with positive nasopharyngeal swabs are recommended to receive antibiotic prophylaxis, and in those with symptomatic signs, adjustment of angiotensin-converting enzyme based on anti-hypertensive therapy should be considered. In patients with liver disease, nitazoxanide plus sofosbuvir, ivermectin, tocilizumab, convalescent plasma, and low molecular weight heparin in certain situations is recommended. Furthermore, favipiravir, chloroquine, and hydroxychloroquine could also be recommended, but with caution regarding to polypharmacy interactions. For those with moderate disease, hydroxychloroquine or chloroquine/azithromycin was recommended. In the patients with respiratory failure, convalescent plasma was suggested. In the populations where those symptoms progress to the sign of a cytokine storm, the antagonists of interleukin-6 (IL-6) were suggested. To reduce fever, however, ibuprofen showed more potent efficacy compared to acetaminophen, but it may delay the benefits of a fever response.

Owing to the immune suppression that could be caused by anti-cancer drugs and deterioration of lung functions due to COVID-19, for proposed management regarding pharmacotherapy strategies, further evidence-based studies seem to be advantageous.