In recent years, there has been growing interest in understanding the potential role of microbiota dysbiosis or alterations in the composition and function of human microbiota in the development of chronic rhinosinusitis with nasal polyposis (CRSwNP). This systematic review evaluated the literature on CRSwNP and host microbiota for the last ten years, including mainly nasal bacteria, viruses, and fungi, following the PRISMA guidelines and using the major scientific publication databases. Seventy original papers, mainly from Asia and Europe, met the inclusion criteria, providing a comprehensive overview of the microbiota composition in CRSwNP patients and its implications for inflammatory processes in nasal polyps. This review also explores the potential impact of microbiota-modulating therapies for the CRSwNP treatment. Despite variability in study populations and methodologies, findings suggest that fluctuations in specific taxa abundance and reduced bacterial diversity can be accepted as critical factors influencing the onset or severity of CRSwNP. These microbiota alterations appear to be implicated in triggering cell-mediated immune responses, cytokine cascade changes, and defects in the epithelial barrier. Although further human studies are required, microbiota-modulating strategies could become integral to future combined CRSwNP treatments, complementing current therapies that mainly target inflammatory mediators and potentially improving patient outcomes.

Porcine pleuropneumonia (PPP) is one of the main causes leading to massive losses in the pig industry, with high economic impacts. Among different etiological agents, Actinobacillus pleuropneumoniae (APP) is responsible for severe fibrinous-necrotizing pleuropneumonia. A total of 19 different APP serotypes are currently recognized. This study aimed to identify APP serotypes isolated from pneumonic lesions in naturally infected and dead pigs in the Piedmont Region and to describe lesions. A total of 107 dead pigs with a suspected PPP diagnosis were included in this study. Lungs were evaluated using gross-pathology scoring systems, histopathology, and APP isolation and serotypes identification by multiplex PCR were conducted. Gross lung lesions were mainly represented by fibrinous pneumonia and pleuropneumonia. APP was isolated in 20/107 (18.7%) samples. PCR indicated APP DNA presence in 53/107 (49.5%) of lung samples. The most observed serotypes were serotype 2 in 24/53 (45.3%) and serotype 6 in 13/53 (24.5%) samples. Moreover, multiplex PCR results suggested a coinfection of different serotypes in five samples. This study emphasizes the importance of an integrated approach, utilizing various techniques, such as gross- and histopathology, and bacteriological culture and PCR, to enhance the diagnosis of APP infections.

Mycoplasma pneumoniae (M. pneumoniae) continues to pose a significant disease burden on global public health as a respiratory pathogen. The antimicrobial resistance among M. pneumoniae strains has complicated the outbreak control efforts, emphasizing the need for robust surveillance systems and effective antimicrobial stewardship programs. This review comprehensively investigates studies stemming from previous outbreaks to emphasize the multifaceted nature of M. pneumoniae infections, encompassing epidemiological dynamics, diagnostic innovations, antibiotic resistance, and therapeutic challenges. We explored the spectrum of clinical manifestations associated with M. pneumoniae infections, emphasizing the continuum of disease severity and the challenges in gradating it accurately. Artificial Intelligence and Machine Learning have emerged as promising tools in M. pneumoniae diagnostics, offering enhanced accuracy and efficiency in identifying infections. However, their integration into clinical practice presents hurdles that need to be addressed. Further, we elucidate the pivotal role of pharmacological interventions in controlling and treating M. pneumoniae infections as the efficacy of existing therapies is jeopardized by evolving resistance mechanisms. Lessons learned from previous outbreaks underscore the importance of adaptive treatment strategies and proactive management approaches. Addressing these complexities demands a holistic approach integrating advanced technologies, genomic surveillance, and adaptive clinical strategies to effectively combat this pathogen.

BACKGROUND: Biomass burning (BB) is a major source of air pollution and particulate matter (PM) in Southeast Asia. However, the health effects of PM smaller than 10 µm (PM10) originating from BB may differ from those of other sources. This study aimed to estimate the short-term association of PM10 from BB with respiratory and cardiovascular hospital admissions in Peninsular Malaysia, a region often exposed to BB events.
METHODS: We obtained and analyzed daily data on hospital admissions, PM10 levels and BB days from five districts from 2005 to 2015. We identified BB days by evaluating the BB hotspots and backward wind trajectories. We estimated PM10 attributable to BB from the excess of the moving average of PM10 during days without BB hotspots. We fitted time-series quasi-Poisson regression models for each district and pooled them using meta-analyses. We adjusted for potential confounders and examined the lagged effects up to 3 days, and potential effect modification by age and sex.
RESULTS: We analyzed 210 960 respiratory and 178 952 cardiovascular admissions. Almost 50% of days were identified as BB days, with a mean PM10 level of 53.1 µg/m3 during BB days and 40.1 µg/m3 during normal days. A 10 µg/m3 increment in PM10 from BB was associated with a 0.44% (95% CI: 0.06, 0.82%) increase in respiratory admissions at lag 0-1, with a stronger association in adults aged 15-64 years and females. We did not see any significant associations for cardiovascular admissions.
CONCLUSIONS: Our findings suggest that short-term exposure to PM10 from BB increased the risk of respiratory hospitalizations in Peninsular Malaysia.

UNASSIGNED: Many respiratory viruses and their associated diseases are sensitive to meteorological factors. For SARS-CoV-2 and COVID-19, evidence on this sensitivity is inconsistent. Understanding the influence of meteorological factors on SARS-CoV-2 transmission and COVID-19 epidemiology can help to improve pandemic preparedness.
UNASSIGNED: This review aimed to examine the recent evidence about the relation between meteorological factors and SARS-CoV-2/COVID-19.
UNASSIGNED: We conducted a global scoping review of peer-reviewed studies published from January 2020 up to January 2023 about the associations between temperature, solar radiation, precipitation, humidity, wind speed, and atmospheric pressure and SARS-CoV-2/COVID-19.
UNASSIGNED: From 9,156 initial records, we included 474 relevant studies. Experimental studies on SARS-CoV-2 provided consistent evidence that higher temperatures and solar radiation negatively affect virus viability. Studies on COVID-19 (epidemiology) were mostly observational and provided less consistent evidence. Several studies considered interactions between meteorological factors or other variables such as demographics or air pollution. None of the publications included all determinants holistically.
UNASSIGNED: The association between short-term meteorological factors and SARS-CoV-2/COVID-19 dynamics is complex. Interactions between environmental and social components need further consideration. A more integrated research approach can provide valuable insights to predict the dynamics of respiratory viruses with pandemic potential.

APOE ε4 and BIN1 are the two main genetic risk factors for sporadic Alzheimer\'s Disease (AD). Among several BIN1 variants, the rs744373 is frequently associated with AD risk by contributing to tau pathology and poor cognitive performance. This study addressed the association of APOE and BIN1 rs744373 to specific characteristics in a Portuguese primary care-based study group, denoted pcb-Cohort. The study included 590 participants from five primary care health centers in the Aveiro district of Portugal. Individuals were evaluated and scored for cognitive and clinical characteristics, and blood samples were collected from the volunteers meeting the inclusion and exclusion criteria (N = 505). APOE and BIN1 genotypes were determined, and their association with cognitive characteristics and other diseases that might contribute to cognitive deficits, namely depression, hypertension, type 2 diabetes, dyslipidemia, osteoarticular diseases, gastrointestinal diseases, cardiovascular and respiratory diseases, was assessed. The diseases attributed to the study group were those previously diagnosed and confirmed by specialists. The results generated through multivariate analysis show that APOE ε4 carriers significantly associated with poorer cognitive performance (OR = 2.527; p = 0.031). Additionally, there was a significant risk of dyslipidemia for APOE ε4 carriers (OR = 1.804; p = 0.036), whereas BIN1 rs744373 risk-allele carriers were at a significantly lower risk of having dyslipidemia (OR = 0.558; p = 0.006). Correlations were evident for respiratory diseases in which APOE ε4 showed a protective tendency (OR = 0.515; p = 0.088), and BIN1 had a significative protective profile (OR = 0.556; p = 0.026). Not of statistical significance, APOE ε2 showed a trend to protect against type 2 diabetes (OR = 0.342; p = 0.093), in contrast BIN1 rs744373 risk-allele carriers were more likely to exhibit the disease (OR = 1.491; p = 0.099). The data here presented clearly show, for the first time, that the two top genetic risk factors for sporadic AD impact a similar group of common diseases, namely dyslipidemia, respiratory diseases, and type 2 diabetes.

Allergic asthma is a complex inflammatory disorder predominantly orchestrated by T helper 2 (Th2) lymphocytes. The anti-inflammatory protein Clara Cell 10-kDa (CC10), also known as secretoglobin family 1A member 1 (SCGB1A1), shows promise in modulating respiratory diseases. However, its precise role in asthma remains unclear. This study examines the potential of CC10 to suppress allergic asthma inflammation, specifically assessing its regulatory effects on Th2 cell responses and dendritic cells (DCs). Lower CC10 levels in asthma were observed and correlated with increased IgE and lymphocytes. Cc10-/- mice exhibited exacerbated allergic airway inflammation marked by increased inflammatory cell infiltration, Th2 cytokines, serum antigen-specific IgE levels, and airway hyperresponsiveness (AHR) in house dust mite (HDM)-induced models. Conversely, recombinant CC10 significantly attenuated these inflammatory responses. Intriguingly, CC10 did not directly inhibit Th cell activation but significantly downregulated the population of CD11b+CD103- DCs subsets in lungs of asthmatic mice and modulated the immune activation functions of DCs through NF-κB signaling pathway. The mixed lymphocyte response assay revealed that DCs mediated the suppressive effect of CC10 on Th2 cell responses. Collectively, CC10 profoundly mitigates Th2-type allergic inflammation in asthma by modulating lung DC phenotype and functions, highlighting its therapeutic potential for inflammatory airway conditions and other related immunological disorders.

Asthma is a significant public health concern. This study identified the provinces with the highest morbidity and mortality rates due to asthma among the working-age population (15-69 years) in the Republic of Ecuador. The secondary objective was to explain the possible differences attributable to occupational exposure. This nationwide ecological study was conducted in 24 provinces between 2016 and 2019. Government databases were used as sources of information. Age-standardized rates were calculated for codes J45 and J46. The hospitalization morbidity rate for asthma decreased from 6.51 to 5.76 cases per 100,000 working-age population, and the mortality rate has consistently been low and stable from 0.14 to 0.15 deaths per 100,000 working-age population. Geographic differences between the provinces were evident. The risk of hospitalization and death due to asthma was higher in the Pacific coast (Manabí with 7.26 and 0.38, Esmeraldas with 6.24 and 0.43, Los Ríos with 4.16 and 0.40, El Oro with 7.98 and 0.21, Guayas with 4.42 and 0.17 and the Andean region (Azuay with 6.33 and 0.45, Cotopaxi (5.84 and 0.48)). The high rates observed in provinces with greater agricultural and industrial development could be national heterogeneity\'s main determinants and act as occupational risk factors. The contribution of occupational hazards in each province should be examined in depth through ad hoc studies. The findings presented here provide valuable information that should prompt further detailed studies, which will assist in designing public policies aimed at promoting and safeguarding the respiratory health of the population, particularly that of workers. We believe that this study will inspire the creation of regional networks for the research and surveillance of occupational health.

BACKGROUND: Several studies suggest that environmental and climatic factors are linked to the risk of mortality due to cardiovascular and respiratory diseases; however, it is still unclear which are the most influential ones. This study sheds light on the potentiality of a data-driven statistical approach by providing a case study analysis.
METHODS: Daily admissions to the emergency room for cardiovascular and respiratory diseases are jointly analyzed with daily environmental and climatic parameter values (temperature, atmospheric pressure, relative humidity, carbon monoxide, ozone, particulate matter, and nitrogen dioxide). The Random Forest (RF) model and feature importance measure (FMI) techniques (permutation feature importance (PFI), Shapley Additive exPlanations (SHAP) feature importance, and the derivative-based importance measure (κALE)) are applied for discriminating the role of each environmental and climatic parameter. Data are pre-processed to remove trend and seasonal behavior using the Seasonal Trend Decomposition (STL) method and preliminary analyzed to avoid redundancy of information.
RESULTS: The RF performance is encouraging, being able to predict cardiovascular and respiratory disease admissions with a mean absolute relative error of 0.04 and 0.05 cases per day, respectively. Feature importance measures discriminate parameter behaviors providing importance rankings. Indeed, only three parameters (temperature, atmospheric pressure, and carbon monoxide) were responsible for most of the total prediction accuracy.
CONCLUSIONS: Data-driven and statistical tools, like the feature importance measure, are promising for discriminating the role of environmental and climatic factors in predicting the risk related to cardiovascular and respiratory diseases. Our results reveal the potential of employing these tools in public health policy applications for the development of early warning systems that address health risks associated with climate change, and improving disease prevention strategies.

UNASSIGNED: Kawasaki disease is an uncommon vasculitis affecting young children. Its etiology is not completely understood, although infections have been frequently postulated as the triggers. Respiratory viruses, specifically, have often been implicated as causative agents for Kawasaki disease presentations.
UNASSIGNED: We aimed to conduct an ecological spatiotemporal analysis to determine whether Kawasaki disease incidence was related to community respiratory virus circulation in a shared region and population, and to describe viral associations before and during the COVID-19 pandemic.
UNASSIGNED: We obtained independent statewide data sets of hospital admissions of Kawasaki disease and respiratory multiplex polymerase chain reaction tests performed at two large hospital networks in Victoria, Australia, from July 2011 to November 2021. We studied spatiotemporal relationships by negative binomial regression analysis of the monthly incidence of Kawasaki disease and the rate of positive respiratory polymerase chain reaction tests in different regions of Victoria. Peak viral seasons (95th percentile incidence) were compared to median viral circulation (50th percentile incidence) to calculate peak season increased rate ratios.
UNASSIGNED: While no seasonal trend in Kawasaki disease incidence was identified throughout the study period, we found a 1.52 (99% CI 1.27-1.82) and a 1.43 (99% CI 1.17-1.73) increased rate ratio of Kawasaki disease presentations in association with human metapneumovirus and respiratory syncytial virus circulation, respectively, before the COVID-19 pandemic. No respiratory viral associations with Kawasaki disease were observed during the COVID-19 pandemic.
UNASSIGNED: Our large ecological analysis demonstrates novel spatiotemporal relationships between human metapneumovirus and respiratory syncytial virus circulation with Kawasaki disease. The disappearance of these associations in the COVID-19 pandemic may reflect the reduced circulation of non-SARS-CoV-2 viruses during this period, supporting the prepandemic associations identified in this study. The roles of human metapneumovirus and respiratory syncytial virus in Kawasaki disease etiology warrant further investigation.