Effective Vaccine Research Articles

Recombinant characterization and pathogenicity of a novel L1C RFLP-1-4-4 variant of porcine reproductive and respiratory syndrome virus in China.

Porcine reproductive and respiratory syndrome (PRRS) is one of the most significant diseases affecting the pig industry worldwide and is caused by the PRRS virus (PRRSV), which has complex genetic variation due to frequent mutations, indels, and recombination. The emergence of PRRSV L1C.5 in 2020 in the United States has raised worldwide concerns about PRRSV with the RFLP 1-4-4 pattern and lineage 1C. However, studies on the pathogenic characteristics, epidemiological distribution, and effectiveness of vaccines against PRRSV with L1C and RFLP1-4-4 pattern in China are still insufficient. In this study, a novel recombinant variant of PRRSV with RFLP 1-4-4 and lineage 1C features, different from L1C.5 in the United States, was isolated in China in 2021. In pathogenicity experiments in specific pathogen-free piglets or farm piglets, 60-100% of artificially infected experimental piglets died with high fever and respiratory symptoms. Inflammatory cytokine and chemokine levels were upregulated in infected piglets. A commercially modified live vaccine against highly pathogenic PRRSV did not provide effective protection when the vaccinated piglets were challenged with the novel L1C-1-4-4 variant. Therefore, this strain merits special attention when devising control and vaccine strategies. These findings suggest that extensive joint surveillance is urgently needed and that vaccine strategies should be updated to prevent the disease from spreading further.

Canine Brucellosis: A Comprehensive Review

Canine brucellosis, caused by Brucella canis, is a global infectious and zoonotic disease that poses a significant public health risk due to the close interactions between dogs and humans. In dogs, the disease can lead to abortion outbreaks, reproductive failures, lymphadenopathy, and occasionally osteoarticular issues. Asymptomatic infections are also relatively common. In humans, brucellosis typically presents with a febrile illness and non-specific symptoms such as splenomegaly, fatigue, and weakness. The disease is notably problematic in breeding programs due to reproductive failures, including infertility and abortion, leading to substantial economic losses. Transmission occurs through direct contact with infected bodily fluids, particularly during mating, or via contaminated environments. Diagnosing canine brucellosis accurately is critical and can be achieved using various methods, including bacterial cultures, serological tests like the Rose Bengal Plate Test (RBPT) and Enzyme-Linked Immunosorbent Assay (ELISA), and molecular techniques such as polymerase chain reaction (PCR). Treatment is limited, with neutering and antibiotic therapy being the main approaches, though these do not always ensure complete recovery. Preventive measures are essential and include regular screening of breeding dogs, isolation of infected animals, and strict biosecurity protocols. Given its zoonotic potential, it is crucial for veterinary professionals and pet owners to be aware of the disease. Increased awareness and future research on new diagnostic methods and effective vaccines are vital for improving control strategies and reducing the impact of canine brucellosis on both canine and human health.

Benchmark Investigation of SARS-CoV-2 Mutants’ Immune Escape with 2B04 Murine Antibody: A Step Towards Unraveling a Larger Picture

Even though COVID-19 is no longer the primary focus of the global scientific community, its high mutation rate (nearly 30 substitutions per year) poses a threat of a potential comeback. Effective vaccines have been developed and administered to the population, ending the pandemic. Nonetheless, reinfection by newly emerging subvariants, particularly the latest JN.1 strain, remains common. The rapid mutation of this virus demands a fast response from the scientific community in case of an emergency. While the immune escape of earlier variants was extensively investigated, one still needs a comprehensive understanding of how specific mutations, especially in the newest subvariants, influence the antigenic escape of the pathogen. Here, we tested comprehensive in silico approaches to identify methods for fast and accurate prediction of antibody neutralization by various mutants. As a benchmark, we modeled the complexes of the murine antibody 2B04, which neutralizes infection by preventing the SARS-CoV-2 spike glycoprotein’s association with angiotensin-converting enzyme (ACE2). Complexes with the wild-type, B.1.1.7 Alpha, and B.1.427/429 Epsilon SARS-CoV-2 variants were used as positive controls, while complexes with the B.1.351 Beta, P.1 Gamma, B.1.617.2 Delta, B.1.617.1 Kappa, BA.1 Omicron, and the newest JN.1 Omicron variants were used as decoys. Three essentially different algorithms were employed: forced placement based on a template, followed by two steps of extended molecular dynamics simulations; protein–protein docking utilizing PIPER (an FFT-based method extended for use with pairwise interaction potentials); and the AlphaFold 3.0 model for complex structure prediction. Homology modeling was used to assess the 3D structure of the newly emerged JN.1 Omicron subvariant, whose crystallographic structure is not yet available in the Protein Database. After a careful comparison of these three approaches, we were able to identify the pros and cons of each method. Protein–protein docking yielded two false-positive results, while manual placement reinforced by molecular dynamics produced one false positive and one false negative. In contrast, AlphaFold resulted in only one doubtful result and a higher overall accuracy-to-time ratio. The reasons for inaccuracies and potential pitfalls of various approaches are carefully explained. In addition to a comparative analysis of methods, some mechanisms of immune escape are elucidated herein. This provides a critical foundation for improving the predictive accuracy of vaccine efficacy against new viral subvariants, introducing accurate methodologies, and pinpointing potential challenges.

FGL2172-220 peptides improve the antitumor effect of HCMV-IE1mut vaccine against glioblastoma by modulating immunosuppressive cells in the tumor microenvironment

ABSTRACT Glioblastoma multiforme (GBM) is a highly aggressive primary brain tumor characterized by poor prognosis and lack of effective treatments. In recent years, peptide vaccines that use sequences based on tumor-specific or tumor-associated antigens to activate immune responses against tumor cells have emerged as a new therapeutic strategy. In this study, we developed a novel therapeutic polypeptide vaccine targeting the tumor-associated antigen Fibrinogen-Like Protein 2 (FGL2), whose dominant epitope peptide was tandemly linked to the C-terminus of HCMV-IE1mut via a linker. We used this vaccine to compare the therapeutic efficacy of HCMV-IE1mut alone versus HCMV-IE1mut-FGL2172-220 and investigate the potential mechanism of action of HCMV-IE1mut-FGL2172-220 in glioma treatment. An in situ GBM model (GL261-IE1-luc cells) was used to determine the efficacy of the vaccine. Treatment with HCMV-IE1mut-FGL2172-220 exerted antitumor effects and extended the survival of the GL261 animal model. We observed reduced proportions of microglia, regulatory T cells (Treg), and myeloid-derived suppressor cells (MDSC) in the tumor microenvironment (TME) by immunofluorescence. Flow cytometry showed that compared to HCMV-IE1mut alone, treatment with HCMV-IE1mut-FGL2172-220 increased the proportion of CD8+ T cells and tissue-resident memory T cells (TRM). ELISA analysis showed that it improved the secretion of tumor-specific IFN-γ and TNF-α by these cells and downregulated the expression of IL-6 and IL-10. Our study demonstrates that the long-peptide FGL2172-220 improves the antitumor efficacy of HCMV-IE1mut, possibly by reshaping immune cells in the glioma microenvironment. These findings lay the groundwork for the development of therapeutic antigenic peptide vaccines to improve antitumor effects for cancer.

Beneficial Impact of Vaccination Against SARS-CoV-2 on the Mental Health of IPF Patients

Background: Depression and anxiety represent significant comorbidities in idiopathic pulmonary fibrosis (IPF) patients, affecting their quality of life. The COVID-19 pandemic has had an uneven impact on global mental health. The Hospital Anxiety and Depression Scale (HADS) constitutes a validated tool to identify anxiety disorders and depression. The aim of this multicentre study was to evaluate the effect of COVID-19 vaccination on depression and anxiety in IPF patients. Methods: Consecutive IPF patients (median 73.5 years) who are regularly followed-up with were included in the study. Demographics, functional, and clinical were recorded. The HADS score was calculated before and one month after vaccination against COVID-19 in all participants. A Wilcoxon signed ranks test was conducted. Results: A total of 180 IPF patients (median 73.5 years) were included in the study. Among them, 145 patients (81%) received antifibrotic treatment. A significant reduction in HADS, both in anxiety and depression scales, was observed one month after vaccination against SARS-COV-2), independent of age, smoking, lung function impairment, and prior history of depression (p < 0.01). Conclusions: A higher Hospital Anxiety and Depression Scale score was detected before vaccination against COVID-19. It seems that vaccination also offered a beneficial effect on depression and anxiety in IPF patients, independent of age, smoking, lung function impairment, and prior history of depression.

Mathematical analysis of a three-strain model for dengue with vaccination

Abstract Dengue has emerged as the most widespread mosquito-borne ailment in humans, causing an estimated 390 million infections within the endemic regions of the world annually. In this paper, a novel mathematical model is proposed for three strains of dengue virus with vaccination measures. Some of the important qualitative analysis carried out are as follows: The dengue serotypes 1, 2 and 3 sub-models are qualitatively analyzed, using well constructed candidates of Lyapunov function. The sub-models' infection-free equilibria are proven to be locally asymptotically stable.The infection-free and endemic equilibria of the sub-models are established to be globally asymptotically stable. The complete model's infection-free equilibrium is proven to be locally and globally asymptotically stable. Also, simulations are also presented to validate the theoretical analysis in the paper. The solution profiles of all epidemiological compartments when the reproduction numbers are both below one and greater than one are graphically presented. It was observed that, for the scenarios when the dengue reproduction number $\mathcal{R}_{0}$ is below and above one, the solution trajectories converge to the infection-free and dengue-endemic steady states, respectively. Sensitivity analyses using the Latin Hypercube Sampling (LHS), and also using contour plots and surface plots are performed on the dengue serotypes associated reproduction numbers. The impact of influential parameters are graphically presented. Worthy of mention, is the significant impact of dengue transmission rates (positively correlated) and dengue vaccination rates and vaccine effectiveness levels (negatively correlated). Different scenario analyses to investigate the impact of dengue vaccination measures are presented. It was observed that enhanced dengue vaccination programme under the administration of safe and highly effective vaccine could curtail the spread and co-circulation of different dengue serotypes within the population.

The Impact of the U.S. Maternal Tdap Vaccination Program on Preventing Pertussis in Infants 2-<6 Months of Age: A Case-control Evaluation

Abstract Background To protect infants aged <2 months against pertussis, the United States recommends Tdap (tetanus toxoid, reduced diphtheria toxoid, and acellular pertussis) vaccination during each pregnancy. Data are limited on the strategy’s effectiveness against pertussis in infants aged ≥2 months. Methods Pertussis cases aged 2-<6 months with cough onset between 1/1/2011-12/31/2014 were identified in six U.S. states. Controls were 2-<6 months of age, hospital-matched, and selected by birth certificate. Mothers were interviewed to collect demographic and healthcare information. Provider-verified vaccination history was obtained for infants and mothers. Adjusted odds ratios (aORs) were calculated using conditional logistic regression; overall vaccine effectiveness (VE) was estimated as (1 - aOR) x 100. To describe maternal Tdap VE modified by infant DTaP (diphtheria and tetanus toxoids, and acellular pertussis) doses, case-control sets were unmatched and a time-to-event analysis conducted through a Generalized Linear Mixed Model. Results A total of 335 cases and 927 controls were enrolled. The overall adjusted VE estimate for Tdap during pregnancy was 45.6% (95% confidence interval [CI], 5.8% – 68.5%) and increased slightly, but not significantly against infant hospitalization (55.7% (-116.8% – 90.9%)). Although point estimates were not significant, VE was modified by infant DTaP doses (58.8% (-6.0% – 84.0%) for zero DTaP doses, 30.5% (-21.4% – 60.2%) for one DTaP dose, and 3.2% (-170.8% – 65.4%) for two DTaP doses). Conclusions Our study suggests that there is some benefit of maternal Tdap vaccination beyond the first two months of life, however, on-time vaccination of infants remains critical to maintain protection from pertussis.

Prospective clinical surveillance for severe acute respiratory illness and COVID-19 vaccine effectiveness in Kenyan hospitals during the COVID-19 pandemic.

There are limited data from sub-Saharan Africa describing the demographic characteristics, clinical features and outcome of patients admitted to public hospitals with severe acute respiratory infections during the COVID-19 pandemic. We conducted a prospective longitudinal hospital-based sentinel surveillance between May 2020 and December 2022 at 16 public hospitals in Kenya. All patients aged above 18 years admitted to adult medical wards in the participating hospitals were included. We collected data on demographic and clinical characteristics, SARS-CoV-2 infection and COVID-19 vaccination status and, admission episode outcomes. We determined COVID-19 vaccine effectiveness (VE) against admission with SARS-CoV-2 positive severe acute respiratory illness (SARI) (i.e., COVID-19) andprogression to inpatient mortality among patients admitted with SARI, using a test-negative case control design. Of the 52,636 patients included in the study, 17,950 (34.1%) were admitted with SARI. The median age was 50 years. Patients were equally distributed across sexes. Pneumonia was the most common diagnosis at discharge. Hypertension, Human Immunodeficiency Virus (HIV) infection and Diabetes Mellitus were the most common chronic comorbidities. SARS-CoV-2 test results were positive in 2,364 (27.9%) of the 8,471 patients that underwent testing. After adjusting for age, sex and presence of a chronic comorbidity, SARI patients were more likely to progress to inpatient mortality compared to non-SARI patients regardless of their SARS-CoV-2 infection status (adjusted odds ratio (aOR) for SARI and SARS-CoV-2 negative patients 1.22, 95% CI 1.10-1.37; and aOR for SARI and SARS-CoV-2 positive patients 1.32, 95% CI 1.24-1.40). After adjusting for age, sex and presence of a chronic comorbidity, COVID-19 VE against progression to inpatient mortality following admission with SARI for those with a confirmed vaccination status was 0.59 (95% CI 0.27-0.77). We have provided a comprehensive description of the demographic and clinical pattern of admissions with SARI in Kenyan hospitals during the COVID-19 pandemic period as well as the COVID-19 VE for these patients. These data were useful in providing situational awareness during the first three years of the pandemic in Kenya and informing national response measures.

Adapting COVID-19 research infrastructure to capture influenza and respiratory syncytial virus alongside SARS-CoV-2 in UK healthcare workers winter 2022/23 and beyond: protocol for a pragmatic sub-study

Introduction During the COVID-19 pandemic, extensive research was conducted on SARS-CoV-2; however, important questions about other respiratory pathogens remain unanswered. A severe influenza season in 2022–2023 with simultaneous circulation of SARS-CoV2 and respiratory syncytial virus is anticipated. This sub-study aims to determine the incidence and impact of these respiratory viruses on healthcare workers, the symptoms they experienced, the effectiveness of both COVID-19 and influenza vaccination and the burden of these infections on the National Health Service (NHS) workforce. Methods and analysis This is a longitudinal prospective cohort sub-study, utilising the population and infrastructure of the SARS-CoV-2 Immunity & Reinfection Evaluation (SIREN) study, which focuses on hospital staff in the UK. Participants undergo fortnightly nucleic acid amplification testing on a multiplex assay including SARS-CoV-2, influenza A and B and RSV, regardless of symptoms. Questionnaires are completed every two weeks, capturing symptoms, sick days, exposures, and vaccination records. Serum samples are collected monthly or quarterly from participants associated with a SIREN site. This sub-study commenced on 28/11/22 to align with the predicted influenza season and participants’ influenza vaccine status. The SIREN Participant Involvement Panel shaped the aims and methods for the study, highlighting its acceptability. UK devolved administrations were supported to develop local protocols. Analysis plans include incidence of asymptomatic and symptomatic infection, comparisons of vaccination coverage, assessment of sick day burden, and effectiveness of seasonal influenza against infection and time off work. Data are also integrated into UKHSA nosocomial modelling. Ethics and dissemination The protocol was approved by the Berkshire Research Ethics Committee (IRAS ID 284460, REC Reference 20SC0230) on 14/11/2022. Participants were informed in advance. As the frequency and method of sampling remained the same, implied consent processes were approved by the committee. Participants returning to the study give informed consent. Regular reports to advisory groups and peer-reviewed publications are planned to disseminate findings and inform decision making. Clinical trial registration number: ISRCTN11041050; registration date: 12 January 2021. Sub study included in protocol version: v8.0, and amended in v9.0

VP8 Mosaic Nanoparticles Elicit Cross-Neutralizing Immune Responses and Provide Protection Against Heterotypic Rotavirus Challenge in Mice.

Group A rotaviruses (RVA) remain one of the dominant pathogens causing diarrhea in children under 5 years of age worldwide, despite a sharp decrease of RVA-associated diarrhea and mortality since the introduction of rotavirus vaccines. The decreased effectiveness of live attenuated rotavirus vaccines, coupled with the emergence of new rotavirus genotypes and the risk of cross-species virus transmission, underscores the necessity to develop more effective and broad-spectrum rotavirus vaccines. In this study, we utilized nanoparticles coupled with the SpyCatcher-SpyTag system to effectively display the truncated VP8-1 protein. The modular display of the monovalent VP8-1 proteins markedly increased the immunogenicity of VP8-1. Furthermore, the bivalent display of VP8-1 proteins from simian rotavirus SA11 and lamb rotavirus LLR on the same particle not only increased immunogenicity against homotypic antigens but also elicited robust heterotypic immune responses and conferred effective protection against a distant heterotypic rotavirus with sequence identities of only 62%-66% in an adult mouse model. Therefore, mosaic VP8 nanoparticles could be considered as a viable strategy for the development of the next-generation broad-spectrum rotavirus vaccine.

An Immunoinformatic Approach for Identifying and Designing Conserved Multi-Epitope Vaccines for Coronaviruses

Background/Objectives: The COVID-19 pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has exposed the vulnerabilities and unpreparedness of the global healthcare system in dealing with emerging zoonoses. In the past two decades, coronaviruses (CoV) have been responsible for three major viral outbreaks, and the likelihood of future outbreaks caused by these viruses is high and nearly inevitable. Therefore, effective prophylactic universal vaccines targeting multiple circulating and emerging coronavirus strains are warranted. Methods: This study utilized an immunoinformatic approach to identify evolutionarily conserved CD4+ (HTL) and CD8+ (CTL) T cells, and B-cell epitopes in the coronaviral spike (S) glycoprotein. Results: A total of 132 epitopes were identified, with the majority of them found to be conserved across the bat CoVs, pangolin CoVs, endemic coronaviruses, SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV). Their peptide sequences were then aligned and assembled to identify the overlapping regions. Eventually, two major peptide assemblies were derived based on their promising immune-stimulating properties. Conclusions: In this light, they can serve as lead candidates for universal coronavirus vaccine development, particularly in the search for pan-coronavirus multi-epitope universal vaccines that can confer protection against current and novel coronaviruses.

Age-Specific Seroprevalence of Hepatitis A Virus in Turkey Between 2000 and 2023: Systematic Review and Meta-Analysis

Background: Hepatitis A virus (HAV) is a leading cause of acute viral hepatitis and is primarily transmitted by the fecal–oral route. The clinical presentation and progression of the disease varies according to the age of the patient. Turkey is classified as a moderately endemic country, and HAV infection continues to be an important public health problem worldwide. Methods: In this study, a systematic meta-analysis was conducted to evaluate age-specific HAV seroprevalence rates in Turkey between 2000 and 2023. A comprehensive literature review identified 57 articles that met the inclusion criteria. The studies were assessed for quality, and seroprevalence rates were evaluated across four different age groups. Statistical analyses were performed using Comprehensive Meta-Analysis (CMA) software (CMAVersion 3.0) and SPSS (SPSS Statistics 25.0). Results: HAV seroprevalence rates were found to be 73.18% in the 0 < 5 age group and 90.90% in the >35 age group. The overall seroprevalence estimated using a random effects model was 64.5% (95% CI: 58.3–70). High heterogeneity was observed among the studies, and the prevalence estimates changed when low-quality studies were excluded. Conclusions: This meta-analysis suggests that the increasing trend in HAV IgG seroprevalence in Turkey, especially among young populations, is likely due to the vaccination program initiated in 2012. Furthermore, the heterogeneity observed among regions highlights the importance of regional public health strategies. Future studies should focus on providing more detailed data to evaluate the long-term effects of vaccination and to explain regional differences in HAV seroprevalence.

Epidemiology, clinical and biological characteristics, and prognosis of critically ill COVID 19 patients: a single-center experience through 4 successive waves

ObjectiveThe aim of this study was to describe the characteristics of patients admitted to the intensive care unit with severe pneumonia due to SARS-CoV-2, comparing them according to successive waves, and to identify prognostic factors for morbidity and mortality.Materials and methodsThis single-center retrospective observational descriptive study was conducted from March 10, 2020, to October 17, 2021. All adult patients admitted with SARS-CoV-2 pneumonia presenting acute respiratory failure were included. COVID 19 diagnosis was confirmed by RT-PCR testing of respiratory specimens. The primary endpoint was ICU mortality. Secondary endpoints were the occurrence of ventilator-associated pneumonia (VAP) or bronchopulmonary aspergillosis.ResultsOver the study period, 437 patients were included of whom 282 (65%) patients were ventilated for 9 [5;20] days. Among the studied population, 38% were treated for one or more episodes of VAP, and 22 (5%) for bronchopulmonary aspergillosis. ICU mortality was 26% in the first wave, then fell and stabilized at around 10% in subsequent waves (p = 0.02). Increased age, Charlson index, SOFA score and lactatemia on admission were predictive of mortality. Survival at 90 days was 85% (95% CI 82–88) and was unaffected by the presence of VAP. However, the occurrence of bronchopulmonary aspergillosis increased mortality to 36%.ConclusionIn this study, we observed mortality in the lower range of those previously reported. Risk factors for mortality mainly included age and previous comorbidities. The prognosis of these critically ill Covid 19 patients improved over the four waves, underlining the likely beneficial effect of vaccination and dexamethasone.

Investigating the Effect of COVID-19 Vaccination on the Course of Disease and Recurrence of Attacks in Patients with Multiple Sclerosis

Background: The COVID-19 pandemic, with its high mortality rate, has underscored the urgent need for the rapid production of vaccines. This has prompted research into the effects of vaccines on specific populations, including patients with immune diseases such as multiple sclerosis (MS). Objectives: This study aimed to examine the impacts of COVID vaccination on individuals with MS. Methods: A retrospective cohort study was conducted involving 302 patients with relapsing-remitting MS who had received the coronavirus vaccine. These patients were referred to the MS clinic of two referral hospitals affiliated with Tehran University of Medical Sciences. The data collection instrument used was a checklist that included demographic information and disease-related details, such as the duration of the disease, underlying conditions, type and timing of vaccine administration, and the occurrence of attacks before and after the vaccination rounds. Results: During the first and second rounds of vaccination, the majority of patients (90.7% and 87.1%, respectively) received the Sinopharm vaccine. In the third round, approximately one-third (32.8%) did not receive the vaccine, and in the fourth round, the majority of individuals (85.8%) also did not receive it. However, most vaccinated individuals had received the Sinopharm vaccine. Among the sample, 34 individuals (11.3%) were newly diagnosed with MS after receiving the vaccine. Additionally, 41.7% of individuals experienced an attack within three months after receiving one of the vaccine doses. Conclusions: Vaccinations during the COVID era have significantly contributed to saving lives and preventing death. However, they have also had consequences that need careful examination and consideration in future vaccine production and epidemic management. The results obtained from this study can be associated with the vaccine, but given the retrospective nature of the study, further research on the long-term effects of the vaccine is needed to generalize the findings.

Minicircle-based vaccine induces potent T-cell and antibody responses against hepatitis C virus

An effective vaccine against hepatitis C virus (HCV) should elicit both humoral and cellular immune responses. Previously, we characterized a bivalent vaccine candidate against hepatitis B (HBV) and HCV using chimeric HBV-HCV virus-like particles (VLP), in which the highly conserved epitope of HCV E2 glycoprotein (residues 412–425) was inserted into the hydrophilic loop of HBV small surface antigen (sHBsAg). While sHBsAg_412–425 elicited cross-neutralizing antibodies, it did not trigger a T-cell response against HCV. Thus, this study aimed to develop a vaccine candidate engaging both arms of adaptive immune response, potentially offering stronger protection against HCV. We evaluated the immunogenicity of minicircle (MC) DNA vaccines encoding sHBsAg_412–425 and HCV nonstructural (NS) proteins in BALB/c mice. Co-administration of sHBsAg_412–425 and NS induced a potent T-cell response, especially against NS3 and high titers of antibodies specific to HCV E2. Additionally, these antibodies recognized native HCV envelope glycoprotein heterodimers (E1E2) across multiple HCV genotypes and showed binding profiles to E1E2 alanine mutants comparable to the broadly neutralizing AP33 antibody. Overall, the findings demonstrate that MC DNA vaccine incorporating both sHBsAg_412–425 and HCV NS protein sequences induces robust, T-cell and AP33-like antibody responses, highlighting its potential as pan-genotypic prophylactic vaccine against HCV.

How well do different COVID-19 vaccines protect against different viral variants? A systematic review and meta-analysis.

While the efficacy of coronavirus disease 2019 (COVID-19) vaccines has been evaluated in numerous trials, comprehensive evidence on how protection by different vaccines has varied over time remains limited. We aimed to compare protective effects of different vaccines against different viral variants. To achieve this, we searched Medline, Cochrane Library and Embase for randomized controlled trials assessing the efficacy of COVID-19 vaccines. Forest plots using Mantel-Haenszel and random-effects models were generated showing risk ratios (RRs) and 95% CIs by vaccines and variants. We included 36 studies with 90 variant-specific primary outcomes. We found a RR of 0.26 (95% CI 0.21 to 0.31) against all variants overall, with the highest protective effects against the wild-type (RR 0.13; 95% CI 0.10 to 0.18), followed by Alpha (RR 0.26; 95% CI 0.18 to 0.36), Gamma (RR 0.34; 95% CI 0.21 to 0.55), Delta (RR 0.39; 95% CI 0.28 to 0.56) and Beta (RR 0.49; 95% CI 0.40 to 0.62) variants. Nucleic acid vaccines showed the highest protection levels against all variants (RR 0.11; 95% CI 0.08 to 0.15), followed by protein subunit, inactivated virus and viral vector. In conclusion, we found high but heterogenous levels of protection for most COVID-19 vaccines, with decreasing protective effects for vaccines based on traditional technologies as SARS-CoV-2 variants emerged over time. Novel nucleic acid-based vaccines offered substantially higher and more consistent protection.

Resveratrol Potentiates BCG-induced Trained Immunity in Human Monocytes.

Resveratrol is a natural polyphenol derived from plants such as grapes and berries. In addition to its role in plants during injury and infection, various cardioprotective, neuroprotective, and longevity-promoting effects were reported in diverse model organisms. The primary target of resveratrol is the deacetylase Sirtuin 1 (SIRT1), which regulates many immunological processes, including BCG-induced trained immunity response in humans. We, therefore, investigated the effect of resveratrol on trained immunity induced by BCG, β-glucan, C. albicans, or oxidized low-density lipoprotein (oxLDL). Using an in-vitro model of trained immunity with monocytes obtained from healthy donors, we demonstrate that resveratrol amplifies BCG-induced trained immunity regarding IL-6 and TNFα production after a secondary challenge. Although resveratrol did not improve and even limited glycolysis, oxidative phosphorylation, and reactive oxygen species production, it enhanced the permissive epigenetic mark H3K27Ac on IL-6 and TNFα promoters. In contrast to BCG-induced trained immunity, resveratrol potently inhibited training induced by β-glucan, C. albicans, oxLDL, and muramyl dipeptide (MDP), a peptidoglycan component of BCG. Resveratrol's unique boosting effect on BCG training depended on BCG being alive and metabolically active. These results suggest that resveratrol might amplify the effects of BCG vaccination, which should be mechanistically characterized further. In addition, resveratrol could alleviate oxLDL-induced training of innate immune cells in atherosclerosis, and in-vivo studies of trained immunity combined with resveratrol are warranted to explore these therapeutic possibilities.

Lipid nanoparticles as adjuvant of norovirus VLP vaccine augment cellular and humoral immune responses in a TLR9- and type I IFN-dependent pathway.

Norovirus (NoV) virus-like particles (VLPs) adjuvanted with aluminum hydroxide (Alum) are common vaccine candidates in clinical studies. Alum adjuvants usually inefficiently assist recombinant proteins to induce cellular immune responses. Thus, novel adjuvants are required to develop NoV vaccines that could induce both efficient humoral and robust cellular immune responses. Lipid nanoparticles (LNPs) are well-known mRNA delivery vehicles. Increasing evidence suggests that LNPs may have intrinsic adjuvant activity and can be used as adjuvants for recombinant protein vaccines; however, the underlying mechanism remains poorly understood. In this study, we compared the adjuvant effect of LNPs and Alum for a bivalent GI.1/GII.4 NoV VLP vaccine. Compared with Alum, LNP-adjuvanted vaccines induced earlier production of binding, blocking, and neutralizing antibodies and promoted a more balanced IgG2a/IgG1 ratio. It is crucial that LNP-adjuvanted vaccines induced stronger Th1-type cytokine-producing CD4+ T cell and CD8+ T cell responses than Alum. The adjuvant activity of LNPs depended on the ionizable lipid components. Mechanistically, LNPs activated innate immune responses in a type I IFN-dependent manner and were partially dependent on Toll-like receptor (TLR) 9, thus affecting the adaptive immune responses of the vaccine. This conclusion was supported by RNA-seq analysis and in vitro cell experiments and by the deeply blunted T cell responses in IFNαR1-/- mice immunized with LNP-adjuvanted vaccines. This study not only identified LNPs as a high quality adjuvant for NoV VLP vaccines, but also clarified the underlying mechanism of LNPs as a potent immunostimulatory component for improving protein subunit vaccines.IMPORTANCEWith the rapid development of mRNA vaccines, recurrent studies show that lipid nanoparticles (LNPs) have adjuvant activity. However, the mechanism of its adjuvant effect in protein vaccines remains unknown. In this study, we found that the LNP-adjuvanted norovirus bivalent virus-like particle vaccines led to durable antibody responses as well as Th1-type cytokine-producing CD4+ T cell and CD8+ T cell responses, which exceeded the efficiency of the conventional adjuvant aluminum hydroxide. Mechanistically, LNPs activated innate immune responses in a type I IFN-dependent manner and were partially dependent on Toll-like receptor 9, thus affecting the adaptive immune responses of the vaccine. This work unveils that LNPs as a potent immunostimulatory component may be ideal for generating CD8+ T cell and B cell responses for recombinant protein vaccines.

COVID-19 vaccine uptake and associated factors among individuals living in a peri-urban area in Uganda: A cross-sectional study.

The Corona virus disease (COVID-19) is a respiratory illness that is caused by SARS-CoV-2 virus. This virus was first reported in China in December 2019. It then spread to all countries and from March 11, 2020, the World Health Organization declared the COVID-19 outbreak a pandemic. In Uganda, the disease was first reported in March 2020 and COVID-19 vaccines became available by January 2021. Although COVID-19 vaccines were available in Uganda, uptake remained low. The aim of this study was to establish COVID-19 vaccine uptake awareness in a peri-urban setting in Entebbe City, Uganda. This was a cross-sectional study conducted among 127 men and 263 women who reside in Entebbe City, Uganda. Data was collected on socio-behavioral characteristics, knowledge, attitude, and practice (KAP) about COVID-19 vaccine using interviewer administered questionnaires. Uptake of COVID-19 vaccine was defined as the proportion of participants who had received at least one dose of the COVID-19 vaccine. We used descriptive statistics to estimate awareness of COVID-19 vaccines. The 'chi-square test' and 'modified Poisson regression' were used to assess variations in uptake of COVID-19 vaccines among respondents and their socio-demographics as well as other characteristics. Ninety-nine percent (388 out of 390) of the study population were aware of at least one brand of COVID-19 vaccines in the country. Thirty-five percent (138 out of 390) knew that the vaccine immunity was achieved 14 days after the 2nd dose and 98.7% (385 out of 390) admitted that observing the standard operating procedure for COVID-19 infection prevention was necessary after vaccination. There was a gap in knowledge on vaccine safety reported by 74.6% (291 out of 390) participants. Some participants 37.2% (145 out of 390) had concerns about the vaccine. Of these, 57.9% (84 out of 145) believed that the vaccines were not helpful; and 30.3% (44 out of 145) feared serious side effects. Sixty-six percent (257 out of 390) believed that vaccines were not working and 79.0% (308 out of 390) admitted that vaccines were promoted for financial gain. At the time of performing the study, 36.2% and 22.3% had received the 1st and 2nd dose respectively. The main sources of information on COVID-19 vaccine were television (TV) and social media (p-value 0.001). In a multivariate model, COVID-19 vaccine acceptability was associated with salaried and self-employment (p-value 0.046). The other predicative factors were awareness of the COVID-19 vaccine (p-value <0.001) and having vaccine concerns (p-value 0.013). Uptake of COVID-19 vaccination in Entebbe community was low, partly attributed to knowledge gaps and concerns about vaccine safety and effectiveness. This highlights the need to enhance dissemination of information about COVID-19 vaccine. The lessons learnt in this study would be relevant for other emerging infections by informing vaccination implementation programs in similar settings.

AI based predictive acceptability model for effective vaccine delivery in healthcare systems

Vaccine acceptance is a crucial component of a viable immunization program in healthcare system, yet the disparities in new and existing vaccination adoption rates prevail across regions. Disparities in the rate of vaccine acceptance result in low immunization coverage and slow uptake of newly introduced vaccines. This research presents an innovative AI-driven predictive model, designed to accurately forecast vaccine acceptance within immunization programs, while providing high interpretability. Primarily, the contribution of this study is to classify vaccine acceptability into Low, Medium, Partial High, and High categories. Secondly, this study implements the Feature Importance method to make the model highly interpretable for healthcare providers. Thirdly, our findings highlight the impact of demographic and socio-demographic factors on vaccine acceptance, providing valuable insights for policymakers to improve immunization rates. A sample dataset containing 7150 data records with 31 demographic and socioeconomic attributes from PDHS (2017–2018) is used in this paper. Using the LightGBM algorithm, the proposed model constructed on the basis of different machine-learning procedures achieved 98% accuracy to accurately predict the acceptability of vaccines included in the immunization program. The association rules suggest that higher SES, region, parents’ occupation, and mother’s education have an association with vaccine acceptability.