Although COVID-19 vaccination decreases the risk of severe illness, it is unclear whether vaccine administration may impact the prevalence of long-COVID. The aim of this systematic review is to investigate the association between COVID-19 vaccination and long-COVID symptomatology. MEDLINE, CINAHL, PubMed, EMBASE, and Web of Science databases, as well as medRxiv and bioRxiv preprint servers were searched up to June 20, 2022. Peer-reviewed studies or preprints monitoring multiple symptoms appearing after acute SARS-CoV-2 infection either before or after COVID-19 vaccination collected by personal, telephone or electronic interviews were included. The methodological quality of the studies was assessed using the Newcastle-Ottawa Scale. From 2584 studies identified, 11 peer-reviewed studies and six preprints were included. The methodological quality of 82% (n=14/17) studies was high. Six studies (n=17,256,654 individuals) investigated the impact of vaccines before acute SARS-CoV-2 infection (vaccine-infection-long-COVID design). Overall, vaccination was associated with reduced risks or odds of long-COVID, with preliminary evidence suggesting that two doses are more effective than one dose. Eleven studies (n=36,736 COVID-19 survivors) investigated changes in long-COVID symptoms after vaccination (infection-long-COVID-vaccine design). Seven articles showed an improvement in long-COVID symptoms at least one dose post-vaccination, while four studies reported no change or worsening in long-COVID symptoms after vaccination. Low level of evidence (grade III, case-controls, cohort studies) suggests that vaccination before SARS-CoV-2 infection could reduce the risk of subsequent long-COVID. The impact of vaccination in people with existing long-COVID symptoms is still controversial, with some data showing changes in symptoms and others did not. These assumptions are limited to those vaccines used in the studies. The LONG-COVID-EXP-CM study supported by a grant of Comunidad de Madrid.

Identification of predictors of long COVID-19 is essential for managing healthcare plans of patients. This systematic literature review and meta-analysis aimed to identify risk factors not associated with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, but rather potentially predictive of the development of long COVID-19. MEDLINE, CINAHL, PubMed, EMBASE, and Web of Science databases, as well as medRxiv and bioRxiv preprint servers were screened through 15 September 2022. Peer-reviewed studies or preprints evaluating potential pre-SARS-CoV-2 infection risk factors for the development of long-lasting symptoms were included. The methodological quality was assessed using the Quality in Prognosis Studies (QUIPSs) tool. Random-effects meta-analyses with calculation of odds ratio (OR) were performed in those risk factors where a homogenous long COVID-19 definition was used. From 1978 studies identified, 37 peer-reviewed studies and one preprint were included. Eighteen articles evaluated age, sixteen articles evaluated sex, and twelve evaluated medical comorbidities as risk factors of long COVID-19. Overall, single studies reported that old age seems to be associated with long COVID-19 symptoms (n = 18); however, the meta-analysis did not reveal an association between old age and long COVID-19 (n = 3; OR 0.86, 95% CI 0.73 to 1.03, p = 0.17). Similarly, single studies revealed that female sex was associated with long COVID-19 symptoms (n = 16); which was confirmed in the meta-analysis (n = 7; OR 1.48, 95% CI 1.17 to 1.86, p = 0.01). Finally, medical comorbidities such as pulmonary disease (n = 4), diabetes (n = 1), obesity (n = 6), and organ transplantation (n = 1) were also identified as potential risk factors for long COVID-19. The risk of bias of most studies (71%, n = 27/38) was moderate or high. In conclusion, pooled evidence did not support an association between advancing age and long COVID-19 but supported that female sex is a risk factor for long COVID-19. Long COVID-19 was also associated with some previous medical comorbidities.

This meta-analysis investigated the prevalence of post-COVID symptoms two-years after SARS-CoV-2 infection. Electronic literature searches on PubMed, MEDLINE, CINAHL, EMBASE, Web of Science databases, and on medRxiv/bioRxiv preprint servers were conducted up to October 1^st, 2023. Studies reporting data on post-COVID symptoms at two-years after infection were included. Methodological quality was assessed using the Newcastle-Ottawa Scale. Random-effects models were used for meta-analytical pooled prevalence of each symptom. From 742 studies identified, twelve met inclusion criteria. The sample included 7,912 COVID-19 survivors (50.7% female; age:59.5, SD:16.3). Post-COVID symptoms were assessed at a follow-up of 722.9 (SD:51.5) days after. The overall methodological quality of studies was moderate (mean: 6/10, SD:1.2 points). The most prevalent post-COVID symptoms two-years after SARS-CoV-2 infection were fatigue (28.0%, 95%CI 12.0-47.0), cognitive impairments (27.6%, 95%CI 12.6-45.8), and pain (8.4%, 95%CI 4.9-12.8). Psychological disturbances such as anxiety (13.4%, 95%CI 6.3-22.5) and depressive (18.0%, 95%CI 4.8-36.7) levels as well as sleep problems (20.9%, 95%CI 5.25-43.25) were also prevalent. Pooled data showed high heterogeneity (I²≥75%). This meta-analysis shows the presence of post-COVID symptoms in 30% of patients two-years after COVID-19. Fatigue, cognitive disorders, and pain were the most prevalent post-COVID symptoms. Psychological disturbances as well as sleep problems were still present two-years after COVID-19.

The association of SARS-CoV-2 variants with long-COVID symptoms is still scarce, but new data are appearing at a fast pace. This systematic review compares the prevalence of long-COVID symptoms according to relevant SARS-CoV-2 variants in COVID-19 survivors. The MEDLINE, CINAHL, PubMed, EMBASE and Web of Science databases, as well as the medRxiv and bioRxiv preprint servers, were searched up to 25 October 2022. Case-control and cohort studies analyzing the presence of post-COVID symptoms appearing after an acute SARS-CoV-2 infection by the Alpha (B.1.1.7), Delta (B.1.617.2) or Omicron (B.1.1.529/BA.1) variants were included. Methodological quality was assessed using the Newcastle–Ottawa Scale. From 430 studies identified, 5 peer-reviewed studies and 1 preprint met the inclusion criteria. The sample included 355 patients infected with the historical variant, 512 infected with the Alpha variant, 41,563 infected with the Delta variant, and 57,616 infected with the Omicron variant. The methodological quality of all studies was high. The prevalence of long-COVID was higher in individuals infected with the historical variant (50%) compared to those infected with the Alpha, Delta or Omicron variants. It seems that the prevalence of long-COVID in individuals infected with the Omicron variant is the smallest, but current data are heterogeneous, and long-term data have, at this stage, an obviously shorter follow-up compared with the earlier variants. Fatigue is the most prevalent long-COVID symptom in all SARS-CoV-2 variants, but pain is likewise prevalent. The available data suggest that the infection with the Omicron variant results in fewer long-COVID symptoms compared to previous variants; however, the small number of studies and the lack of the control of cofounders, e.g., reinfections or vaccine status, in some studies limit the generality of the results. It appears that individuals infected with the historical variant are more likely to develop long-COVID symptomatology.

The novel coronavirus SARS-CoV2, the causative agent of the pandemic disease COVID-19, emerged in December 2019 forcing lockdown of communities in many countries. The absence of specific drugs and vaccines, the rapid transmission of the virus, and the increasing number of deaths worldwide necessitated the discovery of new substances for anti-COVID-19 drug development. With the aid of bioinformatics and computational modelling, ninety seven antiviral secondary metabolites from fungi were docked onto five SARS-CoV2 enzymes involved in viral attachment, replication, post-translational modification, and host immunity evasion infection mechanisms followed by molecular dynamics simulation and in silico ADMET prediction (absorption, distribution, metabolism, excretion and toxicity) of the hit compounds. Thus, three fumiquinazoline alkaloids scedapin C (15), quinadoline B (19) and norquinadoline A (20), the polyketide isochaetochromin D1 (8), and the terpenoid 11a-dehydroxyisoterreulactone A (11) exhibited high binding affinities on the target proteins, papain-like protease (PLpro), chymotrypsin-like protease (3CLpro), RNA-directed RNA polymerase (RdRp), non-structural protein 15 (nsp15), and the spike binding domain to GRP78. Molecular dynamics simulation was performed to optimize the interaction and investigate the stability of the top-scoring ligands in complex with the five target proteins. All tested complexes were found to have dynamic stability. Of the five top-scoring metabolites, quinadoline B (19) was predicted to confer favorable ADMET values, high gastrointestinal absorptive probability and poor blood-brain barrier crossing capacities.

Pathologic hyperreactive inflammatory responses occur when there is excessive activation of a proinflammatory NF-κB pathway and a reduced cytoprotective NRF2 cascade. The noncytotoxic, highly selective COX-2 inhibitory flavonol-enriched butanol fraction (UaB) from Uvaria alba (U. alba) was investigated for its inflammatory modulating potential by targeting NF-κB activation and NRF2 activity. Enzyme-linked immunosorbent assay was initially performed to measure levels of proinflammatory mediators [nitric oxide (NO), prostaglandin E₂, and reactive oxygen species (ROS)] and cytokines [tumor necrosis factor-alpha (TNF-α), IL-1β, and IL-6], followed by reverse transcription-polymerase chain reaction and western blotting to determine mRNA and protein expression, respectively. Using immunofluorescence staining combined with western blot analysis, the activation of NF-κB was further investigated. NRF2 activity was also measured using a luciferase reporter assay. UaB abrogated protein and mRNA expressions of inducible nitric oxide synthase (iNOS), COX-2, TNF-α, IL-1β, and IL-6 in RAW 264.7 macrophages, thereby suppressing the production of proinflammatory mediators and cytokines. This was further validated when a concentration-dependent decrease in NO and ROS production was observed in zebrafish (Danio rerio) larvae. UaB also increased NRF2 activity in HaCaT/ARE cell line and attenuated NF-κB activation by inhibiting the nuclear translocation of transcription factor p65 in RAW 264.7 macrophages. Nontargeted LC-MS analysis of UaB revealed the presence of the flavonols quercitrin (1), quercetin (2), rutin (3), kaempferol (4), and kaempferol 3-O-rutinoside (5). Molecular docking indicates that major flavonol aglycones have high affinity toward COX-2 NSAID-binding sites, TNF-α, and TNF-α converting enzyme, while the glycosylated flavonoids showed strong binding toward iNOS and IKK-all possessing dynamic stability when performing molecular dynamics simulations at 140 ns. This is the first report to have elucidated the mechanistic anti-inflammatory potential of the Philippine endemic plant U. alba.