Metagenomic next-generation sequencing (mNGS) has emerged as an indispensable diagnostic tool for infectious diseases. The disparity in virulence and antimicrobial resistance among strains of the same species requires mNGS to reach strain-level resolution.

To compare the subtyping performance between mNGS and culture, thirty bronchoalveolar lavage fluid (BALF) or blood specimens positive by culture were sequenced using the Illumina NextSeq platform, while whole genome sequencing (WGS) was conducted on the corresponding cultured colonies. Additionally, thirty BALF specimens underwent both mNGS and Oxford nanopore technology (ONT)-based metagenomic third-generation sequencing (mTGS) to compare the subtyping efficacy of the two platforms. To characterize the strain-level composition of pneumonia pathogen Acinetobacter baumannii and Klebsiella pneumoniae, 185 BALF specimens from three hospitals were analyzed by mNGS.

WGS of the cultured colonies yielded identical subtyping results to mNGS at the level of clonal complex (CC). Although mNGS and mTGS predicted largely consistent primary CCs, mTGS demonstrated less accuracy and precision in CC identification. Co-infections at the CC level were detected in 5.40% of A. baumannii-positive and 19.55% of K. pneumoniae-positive BALF specimens. CC composition differed markedly according to bacterial load and between primary and secondary CCs in co-infection specimens. Antimicrobial resistance profiles remained constant for patients with single-infection but varied for those with co-infection. Spatial and temporal consistency of CC composition was observed within individual patients.

The heterogeneity in virulence and antimicrobial resistance among CCs, together with the prevalence of strain-level co-infections, highlights the need to extend pathogen identification to the strain level. Under current technical conditions, mNGS is a more suitable subtyping tool compared to culture and mTGS.

Respiratory ailments constitute various pathological conditions affecting the respiratory system, including the airways, pulmonary tissues, and associated structures. When these conditions are left untreated or inadequately managed, they can result in long-term complications, diminished life quality, and higher death rates. To alleviate the strain of respiratory illnesses and promote a more robust population, it is crucial to focus on raising public awareness, facilitating early detection, implementing preventive strategies like immunization, and furthering medical advancements in treatment options. The study presents a comprehensive Machine Learning (ML) method to improve the investigation and classification of respiratory datasets. The technique applies data preprocessing, augmentation, feature selection, genetic algorithms, and ensemble learning techniques on a "Respiratory dataset" and achieves high predicted accuracy while maintaining interpretability. The Synthetic Minority Oversampling Technique (SMOTE) is used to address data imbalance and ensure proper representation of minority class samples. The feature selection module uses various strategies to find relevant characteristics and reduce dimensionality. Machine learning algorithms that are apt for the dataset are employed for predicting the target variable; their performance is measured and analyzed thoroughly. By using Genetic algorithms, Random Forest, XGBoost, and Gradient Boosting are selected as optimal models. The ensemble learning framework combines the 3 optimal models and creates a strong classification system to predict "target variable : Clinical Progression" output. The performance measures of the proposed model achieved an overall accuracy of 95.02% when compared with the existing works and can be applied in healthcare analytics.

SARS-CoV-2 (severe acute respiratory syndrome causing coronavirus 2) caused an epidemic that swept the globe and resulted in large number of casualties. It is still sporadically causing cases and has a long-term impact on the health of once infected individuals. Molnupiravir binds RNA dependent RNA polymerase (RdRp) of SARS-CoV-2 as well as spike protein. In this study, we assessed the mutated spike protein of BA.5 variant and BQ.1.1 subvariant of COVID-19 and tested their binding with it. Multiple sequence and structural alignment of homologous structures revealed highly conserved amino acid residues at the active site of the domain. The molecular docking of Molnupiravir with the active site of the domain, comprised conserved motifs (motif A-G), and exhibited considerable binding affinity against variant and subvariant protein targets. Molnupiravir exhibited stability in its interactions with the Omicron and BQ.1.1 spike proteins, preserving constant engagement within the active site. The protein and Ligand reached An equilibrium with An RMSD of 10.46 Å after 100 nanoseconds, whereas the Ligand measured 8.0 Å. Fluctuations were noted between 40 And 75 nanoseconds, stabilizing from 80 to 100 ns. In simulations including the BQ.1.1 subvariant, the RMSD values demonstrated considerable stability, exhibiting Little variations. The ligand demonstrated flexibility, altering its binding orientation over time, resulting in An average RMSD of 18.72 Å. Herein, investigation of molecular dynamics trajectories elucidated the conformational stability of Molnupiravir, emphasizing its interactions with active residues and the hydrogen bond acceptor and donor environments. The results highlighted the crucial function of protein loops in offering flexibility and enabling ligand binding within the active site. It is concluded that Molnupiravir has the potential to function as an inhibitor of both omicron and its subvariant BQ.1.1.

Chronic Obstructive Pulmonary Disease (COPD) exacerbations pose significant challenges to healthcare systems due to their unpredictable nature and severe impact on patients. Current COPD prediction models often lack real-time capabilities and fail to leverage multi-source data for accurate forecasts. This research proposes a Cyber-Physical System-enabled framework that integrates both primary (clinical) and secondary (online) data sources to predict COPD exacerbations in real-time. The framework employs advanced machine learning techniques, specifically Random Forest and Artificial Neural Networks, for feature selection and prediction accuracy. Statistical validation through ANOVA ensures the harmonization of diverse data sources, enhancing the robustness of the prediction models. Experimental results demonstrate the framework's effectiveness, with key metrics such as accuracy, precision, recall, F1-score, and AUC showcasing its potential for early COPD detection. The proposed system offers proactive healthcare solutions by delivering timely alerts, forecasting exacerbations, and supporting clinical decision-making, ultimately improving patient outcomes and reducing healthcare costs.

High blood or sputum eosinophil counts are linked to poor clinical outcomes in chronic obstructive pulmonary disease (COPD), yet the value of combining both for the assessment of clinical prognosis remains unclear. In this study, we explore the value of combined blood and sputum eosinophil counts for assessing COPD outcomes.

Patients were divided into four groups by blood (≥300 cells/µL) and sputum (≥3%) eosinophil counts (low blood and low sputum, low blood and high sputum, high blood and low sputum, high blood and high sputum). Spirometry, questionnaires, CT scans, impulse oscillometry, blood laboratory tests and induced sputum tests were performed at baseline. Spirometry and follow-up questionnaires were performed annually. Poisson regression was used to compute the relative risk (RR) for acute exacerbation. The mixed-effects model was used to assess annual lung function decline.

Compared with the low blood and low sputum eosinophils group, the high blood and high sputum eosinophils group had poorer lung function, more severe airway resistance and worse emphysema and air trapping at baseline. The high blood and high sputum eosinophils group had higher risks of cough (adjusted OR=1.87, 95% CI 1.20 to 2.92, p=0.006) and wheezing (adjusted OR=2.19, 95% CI 1.32 to 3.64, p=0.002). The low blood and high sputum eosinophils group had higher risks of phlegm (adjusted OR=1.53, 95% CI 1.04 to 2.24, p=0.029) and dyspnoea (adjusted OR=1.68, 95% CI 1.13 to 2.50, p=0.010). The high blood and high sputum eosinophils group demonstrated higher total (adjusted RR=1.36, 95% CI 1.15 to 1.60, p<0.001) and moderate-to-severe (adjusted RR=1.42, 95% CI 1.14 to 1.76, p=0.001) exacerbation risks. There was no significant difference in annual lung function decline among the groups.

Elevated blood and sputum eosinophil counts are linked to worse lung function and a higher exacerbation risk in patients with COPD.

Mycoplasma pneumoniae (MP) is the most common cause of community-acquired bacterial pneumonia in children. Macrolides are used as the first-line treatment for MP infection, but resistance has increased significantly over the past few decades, making treatment difficult. This study examines the prevalence of M. pneumoniae infections and macrolide-resistant M. pneumoniae (MRMP) rates in Korean children across three recent epidemics in Korea between 2014 and 2024.

Data from Green Cross Laboratories on M. pneumoniae polymerase chain reaction (PCR) and macrolide-resistance tests were analyzed from January 2014 to March 2024, including 425,079 MP PCR tests and 11,206 resistance tests (macrolide-resistance testing began in 2019). We examined M. pneumoniae-positive rates by age and compared age composition to the epidemic and non-epidemic periods using Cochran-Armitage trend tests and also examined differences in MRMP positive rates by year, epidemic status, sex, age group, and region using the χ² test.

Three epidemics of M. pneumoniae infection were identified in 2015/16, 2019/20, and 2023/24, with seasonal peaks between the third and fourth quarter of each starting epidemic year and the highest M. pneumoniae-positive rates in children aged 7 to 9 years. There were significant differences in the proportion of children aged 12 years or younger between epidemic and non-epidemic periods (P < 0.001 for two epidemics and 0.027 for one). MRMP PCR positive rates for A2063G and A2064G mutations were 76.6% and 0.7%, respectively, with a notable increase in A2063G rates from 2019/20 to 2023/24, along with a significant decrease as age increased.

The findings indicate a significant rise in M. pneumoniae infections among Korean children, especially those aged 12 years or younger, suggesting a nationwide epidemic. The increase in A2063G mutation rates underscores the need for monitoring antibiotic resistance and further research into resistance factors for future epidemic responses.

Pulmonary arterial hypertension (PAH) is a chronic disease characterized by increased pulmonary vascular resistance, right ventricular overload and systemic repercussions, including disorders in non-target organs. This study aimed to investigate the effects of PAH on the ventral prostate of adult Wistar rats, as well as the role of resistance training (RT) in modulating potential changes caused by the disease. Male rats (n = 32, 60 days old) were divided into four groups: sedentary control, sedentary PAH, RT control and PAH + RT. PAH was induced using two injections of monocrotaline, while rats were submitted to the RT protocol for a month. Afterward, the ventral prostate was collected and analysed for biometric, histopathological and oxidative parameters (CEUA 38/2021). The results showed that PAH significantly reduced the body and prostate weights and increased glandular epithelium and stroma proportions, besides causing epithelium atrophy and inflammatory infiltrates (p < .05). The activity of superoxide dismutase and catalase was lower, culminating in high levels of malondialdehyde and carbonyl proteins (p < .05). The exercise mainly influenced biometric and stereological parameters. The RT protocol minimized the negative effect of PAH regarding catalase activity, epithelium/lumen proportion and inflammatory infiltrate incidence. However, it was ineffective in restoring prostate weight and completely normalizing markers of oxidative stress. In conclusion, PAH induces significant morphofunctional changes in the ventral prostate, including oxidative damage and tissue remodelling. Although RT exerts protective effects, its benefits are limited, highlighting the need for complementary therapies to counteract PAH-induced prostate alterations fully.

Immunoglobulin (Ig) A acts as a first line of defense against respiratory pathogens. Mucosal IgA in salivary and nasal passages has a rapid response to antigens and can play a protective role against reinfection. The mainstay for analyzing SARS-CoV-2 infection and vaccine efficacy has been assessment of serum IgG levels; however, validated assays for assessment of mucosal IgA in clinical samples are necessary as new and adapted measures are generated to combat immune-evasive viral variants. A mucosal IgA assay was developed and tested through assessment of IgA levels in salivary samples from participants of the 2019nCoV-314/NCT05973006 study. These participants had previously received ≥ 2 mRNA-based COVID-19 vaccinations prior to enrollment and received a single intramuscular study dose of NVX-CoV2601 (XBB.1.5) or bivalent vaccine (NVX-CoV2601 + NVX-CoV2373 [Wuhan]). Salivary samples were collected prior to vaccination on Day 0 and on Day 28 to assess response postvaccination. Both vaccine groups elicited a significant increase in anti-SARS-CoV-2 spike IgA against XBB.1.5. Furthermore, cross-reactivity by identification of anti-JN.1 and anti-Wuhan IgA was also observed. The detection of IgA in clinical mucosal samples using this assay will be a valuable tool in supporting vaccine development.

Influenza surveillance and drug resistance testing have always been central to clinical efforts. Therefore, researching the virus characteristics and antiviral drugs is essential.

The HA and NA activities were assessed in influenza strains, and mutations were identified through gene sequencing. The effects of oseltamivir, molnupiravir, and baloxavir treatments were evaluated in vitro. The effectiveness of molnupiravir monotherapy and its combination with baloxavir was also evaluated in a mouse model. Changes in body weight and lung tissue were examined, including pathological changes, virus replication, and inflammation levels.

Forty-one seasonal influenza H1N1 strains from 2023 were used. The EC₅₀ of oseltamivir was significantly increased compared to the 2009 reference strain. Correlation analysis showed that the increase in EC₅₀ was related to the HA and NA activities. The antiviral effects of molnupiravir and baloxavir significantly inhibited virus replication; the combination treatment of molnupiravir/baloxavir showed more potent and synergistic inhibitory effects in vitro. In the mouse model, molnupiravir treatment effectively inhibited virus replication and lung inflammation, but the treatment did not improve weight loss or reduce mortality. With the molnupiravir/baloxavir treatment, viral replication was significantly inhibited and proved to be more effective than either monotherapy. The combination therapy also showed the lowest inflammatory response along with a higher survival rate.

The increase in HA and NA activities of seasonal influenza reduced the efficacy of oseltamivir treatment, but the effectiveness of molnupiravir and baloxavir was retained. Combination therapy showed a significant antiviral effect, which provides a reference for the clinical treatment.

Human metapneumovirus (hMPV) has been increasingly recognized as a major contributor to respiratory infections in all age groups. Owing to its recent discovery, available data on the burden of hMPV in adults are still scant and heterogeneous. Here, we aimed to explore the epidemiology, symptomatic profile, and mortality related to hMPV among Italian adults.

We performed an integrated analysis of several community-based and hospital-based studies conducted in Genoa (Italy) between 2014 and 2025. Adults aged ≥ 18 years prescribed with ≥ 1 molecular test for hMPV were eligible.

Of 21,580 and 2671 adults included in the hospital-based and community-based studies, 376 and 117, respectively, tested positive for hMPV. Seasonal (November to April) hMPV detection rate was 4.4% (95% CI: 3.6%-5.2%) in the community-based and 2.4% (95% CI: 2.1%-2.6%) in the hospital-based studies. Most detections occurred during the spring months. Each 1-year increase in age was associated with a 1.1% increase in the odds of hMPV positivity (adjusted odds ratio [aOR] 1.011; 95% CI: 1.005-1.016). Clinical presentation of hMPV resembled that of the phylogenetically related respiratory syncytial virus. Among hMPV-positive inpatients, 7.3% (95% CI: 4.3%-11.5%) died during their hospital encounter. In-hospital mortality was associated with residency in long-term care facilities (aOR 8.73; 95% CI: 2.63-29.15) and cancer (aOR 4.51; 95% CI: 1.50-14.35).

hMPV is a common virological finding in outpatient and inpatient adults and is responsible for a measurable burden, especially among the most frail older adults.