Explore the vast range of titles available.

Despite pediatric populations representing a smaller proportion of COVID-19 cases and having a less severe prognosis, those belonging to racial and ethnic minority groups are at an increased risk of developing more severe COVID-19-related outcomes. Vaccine coverage is crucial to pandemic mitigation efforts, yet since the start of the COVID-19 pandemic, vaccine hesitancy has increased and routine pediatric immunizations have decreased. Limited research exists on how vaccine hesitancy may contribute to low pediatric COVID-19 vaccine uptake among racial and ethnic minority populations. This study aimed to characterize COVID-19 vaccine-related discussion and sentiment among Twitter users, particularly among racial and ethnic minority users. We used the Twitter application programming interface to collect tweets and replies. Tweets were selected by filtering for keywords associated with COVID-19 vaccines and pediatric-related terms. From this corpus of tweets, we used the Biterm Topic Model to output topics and examined the top 200 retweeted tweets that were coded for pediatric COVID-19 vaccine relevance. Relevant tweets were analyzed using an inductive coding approach to characterize pediatric COVID-19 vaccine-related themes. Replies to relevant tweets were collected and coded. User metadata were assessed for self-reporting of race or ethnic group affiliation and verified account status. A total of 863,007 tweets were collected from October 2020 to October 2021. After outputting Biterm Topic Model topics and reviewing the 200 most retweeted tweets, 208,666 tweets and 3905 replies were identified as being pediatric COVID-19 vaccine related. The majority (150,262/208,666, 72.01%) of tweets expressed vaccine-related concerns. Among tweets discussing vaccine confidence, user replies expressing agreement were significantly outweighed by those expressing disagreement (1016/3106, 32.71% vs 2090/3106, 67.29%; P<.001). The main themes identified in the Twitter interactions were conversations regarding vaccine-related concerns including adverse side effects, concerns that the vaccine is experimental or needs more testing and should not be tested on pediatric populations, the perception that the vaccine is unnecessary given the perceived low risk of pediatric infection, and conversations associated with vaccine-related confidence (ie, the vaccine is protective). Among signal tweets and replies, we identified 418 users who self-identified as a racial minority individual and 40 who self-identified as an ethnic minority individual. Among the subcodes identified in this study, the vaccine being protective was the most discussed topic by racial and ethnic minority groups (305/444, 68.7%). Vaccine-related concerns can have negative consequences on vaccine uptake and participation in vaccine-related clinical trials. This can impact the uptake and development of safe and effective vaccines, especially among racial and ethnic minority populations.

The definitive diagnosis of aseptic meningitis is made by analyzing the cerebrospinal fluid, which requires lumbar puncture (an invasive procedure) that is usually not performed if the patient has mild symptoms. [...]symptomatic management is the mainstay of therapy in aseptic meningitis. [...]it can be concluded that the incidence of mumps vaccine-related meningitis in Japan may be much higher than the frequency currently reported. The funding source had no role in study design, or in the collection, analysis, and interpretation of data, in the writing of the report, or in the decision to submit the article for publication.

The World Health Organization declared the coronavirus disease 2019 (COVID-19) pandemic on March 11, 2020. Two vaccine types were developed using two different technologies: viral vectors and mRNA. Thrombosis is one of the most severe and atypical adverse effects of vaccines. This study aimed to analyze published cases of thrombosis after COVID-19 vaccinations to identify patients' features, potential pathophysiological mechanisms, timing of appearance of the adverse events, and other critical issues. We performed a systematic electronic search of scientific articles regarding COVID-19 vaccine-related thrombosis and its complications on the PubMed (MEDLINE) database and through manual searches. We selected 10 out of 50 articles from February 1 to May 5, 2021 and performed a descriptive analysis of the adverse events caused by the mRNA-based Pfizer and Moderna vaccines and the adenovirus-based AstraZeneca vaccine. In the articles on the Pfizer and Moderna vaccines, the sample consisted of three male patients with age heterogeneity. The time from vaccination to admission was ≤3 days in all cases; all patients presented signs of petechiae/purpura at admission, with a low platelet count. In the studies on the AstraZeneca vaccine, the sample consisted of 58 individuals with a high age heterogeneity and a high female prevalence. Symptoms appeared around the ninth day, and headache was the most common symptom. The platelet count was below the lower limit of the normal range. All patients except one were positive for PF4 antibodies. The cerebral venous sinus was the most affected site. Death was the most prevalent outcome in all studies, except for one study in which most of the patients remained alive. Vaccine-induced thrombotic thrombocytopenia (VITT) is an unknown nosological phenomenon secondary to inoculation with the COVID-19 vaccine. Several hypotheses have been formulated regarding its physiopathological mechanism. Recent studies have assumed a mechanism that is assimilable to heparin-induced thrombocytopenia, with protagonist antibodies against the PF4-polyanion complex. Viral DNA has a negative charge and can bind to PF4, causing VITT. New experimental studies have assumed that thrombosis is related to a soluble adenoviral protein spike variant, originating from splicing events, which cause important endothelial inflammatory events, and binding to endothelial cells expressing ACE2. Further studies are needed to better identify VITT's pathophysiological mechanisms and genetic, demographic, or clinical predisposition of high-risk patients, to investigate the correlation of VITT with the different vaccine types, and to test the significance of the findings.

Encephalitis is a severe inflammatory disorder of the brain with many possible causes and a complex differential diagnosis. Advances in autoimmune encephalitis research in the past 10 years have led to the identification of new syndromes and biomarkers that have transformed the diagnostic approach to these disorders. However, existing criteria for autoimmune encephalitis are too reliant on antibody testing and response to immunotherapy, which might delay the diagnosis. We reviewed the literature and gathered the experience of a team of experts with the aims of developing a practical, syndrome-based diagnostic approach to autoimmune encephalitis and providing guidelines to navigate through the differential diagnosis. Because autoantibody test results and response to therapy are not available at disease onset, we based the initial diagnostic approach on neurological assessment and conventional tests that are accessible to most clinicians. Through logical differential diagnosis, levels of evidence for autoimmune encephalitis (possible, probable, or definite) are achieved, which can lead to prompt immunotherapy.

Infection with varicella zoster virus (VZV) causes varicella (chickenpox), which can be severe in immunocompromised individuals, infants and adults. Primary infection is followed by latency in ganglionic neurons. During this period, no virus particles are produced and no obvious neuronal damage occurs. Reactivation of the virus leads to virus replication, which causes zoster (shingles) in tissues innervated by the involved neurons, inflammation and cell death — a process that can lead to persistent radicular pain (postherpetic neuralgia). The pathogenesis of postherpetic neuralgia is unknown and it is difficult to treat. Furthermore, other zoster complications can develop, including myelitis, cranial nerve palsies, meningitis, stroke (vasculopathy), retinitis, and gastroenterological infections such as ulcers, pancreatitis and hepatitis. VZV is the only human herpesvirus for which highly effective vaccines are available. After varicella or vaccination, both wild-type and vaccine-type VZV establish latency, and long-term immunity to varicella develops. However, immunity does not protect against reactivation. Thus, two vaccines are used: one to prevent varicella and one to prevent zoster. In this Primer we discuss the pathogenesis, diagnosis, treatment, and prevention of VZV infections, with an emphasis on the molecular events that regulate these diseases. For an illustrated summary of this Primer, visit: http://go.nature.com/14xVI1 Varicella zoster virus (VZV) causes varicella (chickenpox) and, upon reactivation following latency, zoster (shingles). In this Primer, the authors discuss VZV pathogenesis, diagnosis, treatment and prevention of VZV infections, with an emphasis on the molecular events that regulate these diseases.

Viral-associated respiratory infectious diseases are one of the most prominent subsets of respiratory failures, known as viral respiratory infections (VRI). VRIs are proceeded by an infection caused by viruses infecting the respiratory system. For the past 100 years, viral associated respiratory epidemics have been the most common cause of infectious disease worldwide. Due to several drawbacks of the current anti-viral treatments, such as drug resistance generation and non-targeting of viral proteins, the development of novel nanotherapeutic or nano-vaccine strategies can be considered essential. Due to their specific physical and biological properties, nanoparticles hold promising opportunities for both anti-viral treatments and vaccines against viral infections. Besides the specific physiological properties of the respiratory system, there is a significant demand for utilizing nano-designs in the production of vaccines or antiviral agents for airway-localized administration. SARS-CoV-2, as an immediate example of respiratory viruses, is an enveloped, positive-sense, single-stranded RNA virus belonging to the coronaviridae family. COVID-19 can lead to acute respiratory distress syndrome, similarly to other members of the coronaviridae. Hence, reviewing the current and past emerging nanotechnology-based medications on similar respiratory viral diseases can identify pathways towards generating novel SARS-CoV-2 nanotherapeutics and/or nano-vaccines.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance 1 – 4 . This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies 5 – 8 , but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3′ untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5′ long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy. Retroelements located in antisense orientation within interferon-regulated genes are reactivated in a subset of cancer cells and initiate a STING- and MAVS-dependent feed-forward inflammatory loop, driving antitumor immunity and exhaustion.

The development of safe and effective vaccines against severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) was a major turning point in the fight against the Coronavirus 2019 (COVID-19) pandemic. However, pharmacovigilance has revealed a small but significant incidence of cardiac inflammation manifesting clinically as myocarditis or pericarditis, particularly in younger vaccine recipients. The incidence is the highest among men under age 40 within a week of receiving the second dose of the mRNA vaccine. In this review, we summarise the evidence for, and guidelines in relation to, SARS-CoV2 vaccine-related myocarditis.

Since 2013, the Centers for Disease Control and Prevention (CDC) has hosted an annual influenza season forecasting challenge. The 2015–2016 challenge consisted of weekly probabilistic forecasts of multiple targets, including fourteen models submitted by eleven teams. Forecast skill was evaluated using a modified logarithmic score. We averaged submitted forecasts into a mean ensemble model and compared them against predictions based on historical trends. Forecast skill was highest for seasonal peak intensity and short-term forecasts, while forecast skill for timing of season onset and peak week was generally low. Higher forecast skill was associated with team participation in previous influenza forecasting challenges and utilization of ensemble forecasting techniques. The mean ensemble consistently performed well and outperformed historical trend predictions. CDC and contributing teams will continue to advance influenza forecasting and work to improve the accuracy and reliability of forecasts to facilitate increased incorporation into public health response efforts.

In the digital age, social media has become a crucial platform for public discourse on diverse health-related topics, including vaccines. Efficient sentiment analysis and hesitancy detection are essential for understanding public opinions and concerns. Large language models (LLMs) offer advanced capabilities for processing complex linguistic patterns, potentially providing valuable insights into vaccine-related discourse. This study aims to evaluate the performance of various LLMs in sentiment analysis and hesitancy detection related to vaccine discussions on social media and identify the most efficient, accurate, and cost-effective model for detecting vaccine-related public sentiment and hesitancy trends. We used several LLMs-generative pretrained transformer (GPT-3.5), GPT-4, Claude-3 Sonnet, and Llama 2-to process and classify complex linguistic data related to human papillomavirus; measles, mumps, and rubella; and vaccines overall from X (formerly known as Twitter), Reddit, and YouTube. The models were tested across different learning paradigms: zero-shot, 1-shot, and few-shot to determine their adaptability and learning efficiency with varying amounts of training data. We evaluated the models' performance using accuracy, F1-score, precision, and recall. In addition, we conducted a cost analysis focused on token usage to assess the computational efficiency of each approach. GPT-4 (F1-score=0.85 and accuracy=0.83) outperformed GPT-3.5, Llama 2, and Claude-3 Sonnet across various metrics, regardless of the sentiment type or learning paradigm. Few-shot learning did not significantly enhance performance compared with the zero-shot paradigm. Moreover, the increased computational costs and token usage associated with few-shot learning did not justify its application, given the marginal improvement in model performance. The analysis highlighted challenges in classifying neutral sentiments and convenience, correctly interpreting sarcasm, and accurately identifying indirect expressions of vaccine hesitancy, emphasizing the need for model refinement. GPT-4 emerged as the most accurate model, excelling in sentiment and hesitancy analysis. Performance differences between learning paradigms were minimal, making zero-shot learning preferable for its balance of accuracy and computational efficiency. However, the zero-shot GPT-4 model is not the most cost-effective compared with traditional machine learning. A hybrid approach, using LLMs for initial annotation and traditional models for training, could optimize cost and performance. Despite reliance on specific LLM versions and a limited focus on certain vaccine types and platforms, our findings underscore the capabilities and limitations of LLMs in vaccine sentiment and hesitancy analysis, highlighting the need for ongoing evaluation and adaptation in public health communication strategies.