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Journal of Immunology Research 2024Vaccination is one of the most effective prophylactic public health interventions for the prevention of infectious diseases such as coronavirus disease (COVID-19).... (Review)
Review
Vaccination is one of the most effective prophylactic public health interventions for the prevention of infectious diseases such as coronavirus disease (COVID-19). Considering the ongoing need for new COVID-19 vaccines, it is crucial to modify our approach and incorporate more conserved regions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to effectively address emerging viral variants. The nucleocapsid protein is a structural protein of SARS-CoV-2 that is involved in replication and immune responses. Furthermore, this protein offers significant advantages owing to the minimal accumulation of mutations over time and the inclusion of key T-cell epitopes critical for SARS-CoV-2 immunity. A novel strategy that may be suitable for the new generation of vaccines against COVID-19 is to use a combination of antigens, including the spike and nucleocapsid proteins, to elicit robust humoral and potent cellular immune responses, along with long-lasting immunity. The strategic use of multiple antigens aims to enhance vaccine efficacy and broaden protection against viruses, including their variants. The immune response against the nucleocapsid protein from other coronavirus is long-lasting, and it can persist up to 11 years post-infection. Thus, the incorporation of nucleocapsids (N) into vaccine design adds an important dimension to vaccination efforts and holds promise for bolstering the ability to combat COVID-19 effectively. In this review, we summarize the preclinical studies that evaluated the use of the nucleocapsid protein as antigen. This study discusses the use of nucleocapsid alone and its combination with spike protein or other proteins of SARS-CoV-2.
Topics: Humans; COVID-19 Vaccines; SARS-CoV-2; COVID-19; Coronavirus Nucleocapsid Proteins; Immunogenicity, Vaccine; Animals; Phosphoproteins; Spike Glycoprotein, Coronavirus; Epitopes, T-Lymphocyte; Antibodies, Viral; Nucleocapsid Proteins
PubMed: 38939745
DOI: 10.1155/2024/9313267 -
Frontiers in Public Health 2024Ticks and pathogens they carry seriously impact human and animal health, with some diseases like Lyme and Alpha-gal syndrome posing risks. Searching for health...
INTRODUCTION
Ticks and pathogens they carry seriously impact human and animal health, with some diseases like Lyme and Alpha-gal syndrome posing risks. Searching for health information online can change people's health and preventive behaviors, allowing them to face the tick risks. This study aimed to predict the potential risks of tickborne diseases by examining individuals' online search behavior.
METHODS
By scrutinizing the search trends across various geographical areas and timeframes within the United States, we determined outdoor activities associated with potential risks of tick-related diseases. Google Trends was used as the data collection and analysis tool due to its accessibility to big data on people's online searching behaviors. We interact with vast amounts of population search data and provide inferences between population behavior and health-related phenomena. Data were collected in the United States from April 2022 to March 2023, with some terms about outdoor activities and tick risks.
RESULTS AND DISCUSSION
Results highlighted the public's risk susceptibility and severity when participating in activities. Our results found that searches for terms related to tick risk were associated with the five-year average Lyme Disease incidence rates by state, reflecting the predictability of online health searching for tickborne disease risks. Geographically, the results revealed that the states with the highest relative search volumes for tick-related terms were predominantly located in the Eastern region. Periodically, terms can be found to have higher search records during summer. In addition, the results showed that terms related to outdoor activities, such as "corn maze," "hunting," "u-pick," and "park," have moderate associations with tick-related terms. This study provided recommendations for effective communication strategies to encourage the public's adoption of health-promoting behaviors. Displaying warnings in the online search results of individuals who are at high risk for tick exposure or collaborating with outdoor activity locations to disseminate physical preventive messages may help mitigate the risks associated with tickborne diseases.
Topics: Humans; Tick-Borne Diseases; United States; Animals; Search Engine; Internet; Lyme Disease; Ticks; Information Seeking Behavior
PubMed: 38939559
DOI: 10.3389/fpubh.2024.1410713 -
JACC. Advances Feb 2024With an increasing interest in using large claims databases in medical practice and research, it is a meaningful and essential step to efficiently identify patients with...
BACKGROUND
With an increasing interest in using large claims databases in medical practice and research, it is a meaningful and essential step to efficiently identify patients with the disease of interest.
OBJECTIVES
This study aims to establish a machine learning (ML) approach to identify patients with congenital heart disease (CHD) in large claims databases.
METHODS
We harnessed data from the Quebec claims and hospitalization databases from 1983 to 2000. The study included 19,187 patients. Of them, 3,784 were labeled as true CHD patients using a clinician developed algorithm with manual audits considered as the gold standards. To establish an accurate ML-empowered automated CHD classification system, we evaluated ML methods including Gradient Boosting Decision Tree, Support Vector Machine, Decision tree, and compared them to regularized logistic regression. The Area Under the Precision Recall Curve was used as the evaluation metric. External validation was conducted with an updated data set to 2010 with different subjects.
RESULTS
Among the ML methods we evaluated, Gradient Boosting Decision Tree led the performance in identifying true CHD patients with 99.3% Area Under the Precision Recall Curve, 98.0% for sensitivity, and 99.7% for specificity. External validation returned similar statistics on model performance.
CONCLUSIONS
This study shows that a tedious and time-consuming clinical inspection for CHD patient identification can be replaced by an extremely efficient ML algorithm in large claims database. Our findings demonstrate that ML methods can be used to automate complicated algorithms to identify patients with complex diseases.
PubMed: 38939385
DOI: 10.1016/j.jacadv.2023.100801 -
Cureus May 2024Non-small cell lung carcinoma (NSCLC) is a prevalent and aggressive form of lung cancer, with a poor prognosis for metastatic disease. Immunotherapy, particularly immune... (Review)
Review
Non-small cell lung carcinoma (NSCLC) is a prevalent and aggressive form of lung cancer, with a poor prognosis for metastatic disease. Immunotherapy, particularly immune checkpoint inhibitors (ICIs), has revolutionized the management of NSCLC, but response rates are highly variable. Identifying reliable predictive biomarkers is crucial to optimize patient selection and treatment outcomes. This systematic review aimed to evaluate the current state of artificial intelligence (AI) and machine learning (ML) applications in predicting the response to immunotherapy in NSCLC. A comprehensive literature search identified 19 studies that met the inclusion criteria. The studies employed diverse AI/ML techniques, including deep learning, artificial neural networks, support vector machines, and gradient boosting methods, applied to various data modalities such as medical imaging, genomic data, clinical variables, and immunohistochemical markers. Several studies demonstrated the ability of AI/ML models to accurately predict immunotherapy response, progression-free survival, and overall survival in NSCLC patients. However, challenges remain in data availability, quality, and interpretability of these models. Efforts have been made to develop interpretable AI/ML techniques, but further research is needed to improve transparency and explainability. Additionally, translating AI/ML models from research settings to clinical practice poses challenges related to regulatory approval, data privacy, and integration into existing healthcare systems. Nonetheless, the successful implementation of AI/ML models could enable personalized treatment strategies, improve treatment outcomes, and reduce unnecessary toxicities and healthcare costs associated with ineffective treatments.
PubMed: 38939246
DOI: 10.7759/cureus.61220 -
Frontiers in Microbiology 2024The expansion of betel palm cultivation is driven by rising demand for betel nut, yet this growth is accompanied by challenges such as decreased agricultural...
The expansion of betel palm cultivation is driven by rising demand for betel nut, yet this growth is accompanied by challenges such as decreased agricultural biodiversity and the spread of infectious pathogens. Among these, Yellow Leaf Disease (YLD) emerges as a prominent threat to betel palm plantation. (APV1) has been identified as a primary causative agent of YLD, precipitating leaf yellowing, stunted growth, and diminished yield. However, the precise mechanisms underlying APV1-induced damage remain elusive. Our study elucidates that APV1 infiltrates chloroplasts, instigating severe damage and consequential reductions in chlorophyll a/b and carotene levels, alongside notable declines in photosynthetic efficiency. Moreover, APV1 infection exerts broad regulatory effects on gene expression, particularly suppressing key genes implicated in chloroplast function and photosynthesis. These disruptions correlate with growth retardation, yield diminishment, and compromised nut quality. Intriguingly, the paradoxical destruction of the host's photosynthetic machinery by APV1 prompts inquiry into its evolutionary rationale, given the virus's dependence on host resources for replication and proliferation. Our findings reveal that APV1-induced leaf yellowing acts as a beacon for transmission vectors, hinting at a nuanced "host-pathogen-vector co-evolutionary" dynamic.
PubMed: 38939190
DOI: 10.3389/fmicb.2024.1424489 -
Frontiers in Cellular and Infection... 2024The Asian citrus psyllid (ACP) Kuwayama is the leading vector of Liberibacter asiaticus (Las), the causative agent of citrus Huanglongbing (HLB) disease. The...
The Asian citrus psyllid (ACP) Kuwayama is the leading vector of Liberibacter asiaticus (Las), the causative agent of citrus Huanglongbing (HLB) disease. The distribution and dynamics of Las within ACP are critical to understanding how the transmission, spread and infection of Las occurs within its host vector in nature. In this study, the distribution and titer changes of Las in various tissues of ACP 5 instar nymphs and adults were examined by (FISH) and real-time quantitative PCR (qPCR) techniques. Results demonstrated that 100% of ACP 5 instar nymphs and adults were infected with Las following feeding on infected plants, and that Las had widespread distribution in most of the tissues of ACP. The titers of Las within the midgut, salivary glands and hemolymph tissues were the highest in both 5 instar nymphs and adults. When compared with adults, the titers of Las in these three tissues of 5 instar nymphs were significantly higher, while in the mycetome, ovary and testes they were significantly lower than those of adults. FISH visualization further confirmed these findings. Dynamic analysis of Las demonstrated that it was present across all the developmental ages of ACP adults. There was a discernible upward trend in the presence of Las with advancing age in most tissues of ACP adults, including the midgut, hemolymph, salivary glands, foot, head, cuticula and muscle. Our findings have significant implications for the comprehensive understanding of the transmission, dissemination and infestation of Las, which is of much importance for developing novel strategies to halt the spread of Las, and therefore contribute to the efficient prevention and control of HLB.
Topics: Animals; Hemiptera; Insect Vectors; Plant Diseases; Nymph; Citrus; In Situ Hybridization, Fluorescence; Rhizobiaceae; Real-Time Polymerase Chain Reaction; Salivary Glands; Hemolymph
PubMed: 38938879
DOI: 10.3389/fcimb.2024.1408362 -
Molecular Therapy : the Journal of the... Jun 2024Alveolar bone loss in elderly populations is highly prevalent and increases the risk of tooth loss, gum disease susceptibility, and facial deformity. Unfortunately,...
Alveolar bone loss in elderly populations is highly prevalent and increases the risk of tooth loss, gum disease susceptibility, and facial deformity. Unfortunately, there are very limited treatment options available. Here, we developed a bone-targeted gene therapy that reverses alveolar bone loss in patients with osteoporosis by targeting the adaptor protein Schnurri-3 (SHN3). SHN3 is a promising therapeutic target for alveolar bone regeneration, because SHN3 expression is elevated in human and mouse mandible tissues with osteoporosis while deletion of SHN3 in mice greatly increases alveolar bone and tooth dentin mass. We used a bone-targeted recombinant adeno-associated virus (rAAV) carrying an artificial microRNA (miRNA) that silences SHN3 expression to restore alveolar bone loss in mouse models of both postmenopausal and senile osteoporosis by enhancing WNT signaling and osteoblast function. Additionally, rAAV-mediated silencing of SHN3 enhanced bone formation and collagen production of human skeletal organoids in xenograft mice. Finally, rAAV expression in the mandible was tightly controlled via liver- and heart-specific miRNA-mediated repression or via a vibration-inducible mechanism. Collectively, our results demonstrate that AAV-based bone anabolic gene therapy is a promising strategy to treat alveolar bone loss in osteoporosis.
PubMed: 38937970
DOI: 10.1016/j.ymthe.2024.06.036 -
Virulence Dec 2024causes globally prevalent infections that are highly related to chronic gastritis and even development of gastric carcinomas. With the increase of antibiotic...
causes globally prevalent infections that are highly related to chronic gastritis and even development of gastric carcinomas. With the increase of antibiotic resistance, scientists have begun to search for better vaccine design strategies to eradicate colonization. However, while current strategies prefer to formulate vaccines with a single antigen, their potential has not yet been fully realized. Outer membrane vesicles (OMVs) are a potential platform since they could deliver multiple antigens. In this study, we engineered three crucial antigen proteins (UreB, CagA, and VacA) onto the surface of OMVs derived from serovar Typhimurium (. Typhimurium) mutant strains using the hemoglobin protease (Hbp) autotransporter system. In various knockout strategies, we found that OMVs isolated from the Δ Δ Δ Δ mutants could cause distinct increases in immunoglobulin G (IgG) and A (IgA) levels and effectively trigger T helper 1- and 17-biased cellular immune responses, which perform a vital role in protecting against . Next, OMVs derived from Δ Δ Δ Δ mutants were used as a vector to deliver different combinations of antigens. The antibody and cytokine levels and challenge experiments in mice model indicated that co-delivering UreB and CagA could protect against and antigen-specific T cell responses. In summary, OMVs derived from the . Typhimurium Δ Δ Δ Δ mutant strain as the vector while importing UreB and CagA as antigenic proteins using the Hbp autotransporter system would greatly benefit controlling infection.
Topics: Animals; Helicobacter Infections; Bacterial Proteins; Helicobacter pylori; Mice; Salmonella typhimurium; Antigens, Bacterial; Bacterial Vaccines; Female; Antibodies, Bacterial; Immunoglobulin G; Genetic Engineering; Urease; Disease Models, Animal
PubMed: 38937901
DOI: 10.1080/21505594.2024.2367783 -
Parasites & Vectors Jun 2024Female Aedes aegypti mosquitoes can spread disease-causing pathogens when they bite humans to obtain blood nutrients required for egg production. Following a complete...
BACKGROUND
Female Aedes aegypti mosquitoes can spread disease-causing pathogens when they bite humans to obtain blood nutrients required for egg production. Following a complete blood meal, host-seeking is suppressed until eggs are laid. Neuropeptide Y-like receptor 7 (NPYLR7) plays a role in endogenous host-seeking suppression and previous work identified small-molecule NPYLR7 agonists that inhibit host-seeking and blood-feeding when fed to mosquitoes at high micromolar doses.
METHODS
Using structure-activity relationship analysis and structure-guided design we synthesized 128 compounds with similarity to known NPYLR7 agonists.
RESULTS
Although in vitro potency (EC) was not strictly predictive of in vivo effect, we identified three compounds that reduced blood-feeding from a live host when fed to mosquitoes at a dose of 1 μM-a 100-fold improvement over the original reference compound.
CONCLUSIONS
Exogenous activation of NPYLR7 represents an innovative vector control strategy to block mosquito biting behavior and prevent mosquito-human host interactions that lead to pathogen transmission.
Topics: Animals; Aedes; Female; Feeding Behavior; Receptors, Neuropeptide Y; Mosquito Vectors; Structure-Activity Relationship; Humans
PubMed: 38937807
DOI: 10.1186/s13071-024-06347-w -
Parasites & Vectors Jun 2024Along the southern shoreline of Lake Malawi, the incidence of schistosomiasis is increasing with snails of the genera Bulinus and Biomphalaria transmitting urogenital...
BACKGROUND
Along the southern shoreline of Lake Malawi, the incidence of schistosomiasis is increasing with snails of the genera Bulinus and Biomphalaria transmitting urogenital and intestinal schistosomiasis, respectively. Since the underlying distribution of snails is partially known, often being focal, developing pragmatic spatial models that interpolate snail information across under-sampled regions is required to understand and assess current and future risk of schistosomiasis.
METHODS
A secondary geospatial analysis of recently collected malacological and environmental survey data was undertaken. Using a Bayesian Poisson latent Gaussian process model, abundance data were fitted for Bulinus and Biomphalaria. Interpolating the abundance of snails along the shoreline (given their relative distance along the shoreline) was achieved by smoothing, using extracted environmental rainfall, land surface temperature (LST), evapotranspiration, normalised difference vegetation index (NDVI) and soil type covariate data for all predicted locations. Our adopted model used a combination of two-dimensional (2D) and one dimensional (1D) mapping.
RESULTS
A significant association between normalised difference vegetation index (NDVI) and abundance of Bulinus spp. was detected (log risk ratio - 0.83, 95% CrI - 1.57, - 0.09). A qualitatively similar association was found between NDVI and Biomphalaria sp. but was not statistically significant (log risk ratio - 1.42, 95% CrI - 3.09, 0.10). Analyses of all other environmental data were considered non-significant.
CONCLUSIONS
The spatial range in which interpolation of snail distributions is possible appears < 10km owing to fine-scale biotic and abiotic heterogeneities. The forthcoming challenge is to refine geospatial sampling frameworks with future opportunities to map schistosomiasis within actual or predicted snail distributions. In so doing, this would better reveal local environmental transmission possibilities.
Topics: Animals; Malawi; Lakes; Biomphalaria; Bulinus; Schistosomiasis; Spatial Analysis; Humans; Bayes Theorem; Snails; Disease Vectors
PubMed: 38937778
DOI: 10.1186/s13071-024-06353-y