A Study of Disease Prognosis in Lung Adenocarcinoma Using Single-Cell Decomposition and Immune Signature Analysis.

Background: The development of tumors is a highly complex process that entails numerous interactions and intricate relationships between the host immune system and cancer cells. It has been demonstrated in studies that the treatment response of patients can be correlated with the tumor microenvironment (TME). Consequently, the examination of diverse immune profiles within the TME can facilitate the elucidation of tumor development and the development of advantageous models for diagnoses and prognoses. Methods: In this study, we utilized a single-cell decomposition method to analyze the relationships between cell proportions and immune signatures in lung adenocarcinoma (LUAD) patients. Results: Our findings indicate that specific immune cell populations and immune signatures are significantly associated with patient prognosis. By identifying poor prognosis signatures (PPS), we reveal the critical role of immune profiles and cellular composition in disease outcomes, emphasizing their diagnostic potential for predicting patient prognosis. Conclusions: This study highlights the importance of immune signatures and cellular composition, which may serve as valuable biomarkers for disease prognosis in LUAD patients.

T lymphocyte proportion in Alzheimer's disease prognosis.

Bai et al investigate the predictive value of T lymphocyte proportion in Alzheimer's disease (AD) prognosis. Through a retrospective study involving 62 AD patients, they found that a decrease in T lymphocyte proportion correlated with a poorer prognosis, as indicated by higher modified Rankin scale scores. While the study highlights the potential of T lymphocyte proportion as a prognostic marker, it suggests the need for larger, multicenter studies to enhance generalizability and validity. Additionally, future research could use cognitive exams when evaluating prognosis and delve into immune mechanisms underlying AD progression. Despite limitations inherent in retrospective designs, Bai et al's work contributes to understanding the immune system's role in AD prognosis, paving the way for further exploration in this under-researched area.

Prognostic value of Alzheimer's disease plasma biomarkers in the oldest-old: a prospective primary care-based study.

Background: Blood-based biomarkers offer a promising, less invasive, and more cost-effective alternative for Alzheimer's disease screening compared to cerebrospinal fluid or imaging biomarkers. However, they have been extensively studied only in memory clinic-based cohorts. We aimed to validate them in a more heterogeneous, older patient population from primary care. Methods: We measured plasma Aß42/Aß40, P-tau181, NfL, and GFAP in 1007 individuals without dementia, aged 79-94 years, from the longitudinal, primary care-based German AgeCoDe study. We assessed the association with cognitive decline, disease progression, and the capacity to predict future dementia of the Alzheimer's type (DAT). We also evaluated biomarker dynamics in 305 individuals with a follow-up sample (∼8 years later). Findings: Higher levels of P-tau181 (HR = 1.32 [95% CI: 1.17-1.51]), NfL (HR = 1.19 [95% CI: 1.03-1.36]), and GFAP (HR = 1.36 [95% CI: 1.22-1.52]), and a lower Aß42/Aß40 ratio (HR = 0.80 [95% CI: 0.68-0.95]) were associated with an increased risk of progressing to clinically-diagnosed DAT. Additionally, higher levels of P-tau181 (ß = -0.49 [95% CI: -0.71 to 0.26]), NfL (ß = -0.29 [95% CI: -0.52 to 0.06]), and GFAP (ß = -0.60 [95% CI: -0.83 to 0.38]) were linked to faster cognitive decline. A two-step DAT prediction strategy combining initial MMSE with biomarkers improved the identification of individuals in the prodromal stage for potential treatment eligibility. Biomarker levels changed over time, with increases in P-tau181 (ß = 0.19 [95% CI: 0.14-0.25]), NfL (ß = 2.88 [95% CI: 2.18-3.59]), and GFAP (ß = 8.23 [95% CI: 6.71-9.75]). NfL (ß = 2.47 [95% CI: 1.04-3.89]) and GFAP (ß = 4.45 [95% CI: 1.38-7.51]) exhibited a faster increase in individuals progressing to DAT. Interpretation: Evaluating plasma biomarkers, alongside brief cognitive assessments, might enhance the precision of risk assessment for DAT progression in primary care. Funding: Alzheimer Forschung Initiative, Bundesministerium für Bildung und Forschung.

Eighty-six cases of clinical characteristics and outcomes of systemic lupus erythematosus-associated macrophage activation syndrome: A meta-analysis study.

OBJECTIVE: To improve our understanding of systemic lupus erythematosus (SLE)-macrophage activation syndrome (MAS). METHODS: A systematic review was performed, to retrieve all those papers on patients with SLE-MAS, in individual or aggregated form. The data in each of these medical records were extracted and analyzed to identify the characteristics of SLE-MAS. RESULTS: A total of 86 SLE-MAS patients were included (25 males and 61 females. The mean (±standard error of the mean) age was 31.21 ± 1.694 years. MAS occurred as the initial presentation of SLE in 47 people (54.65%) and during the course of SLE in 39 (45.35%). A coinfection was reported in 23 (26.74%) patients. The mean Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) score was 16.54 ± 0.9462. Overall, 10 patients (11.63%) died. The SLEDAI-2K score was higher in patients with MAS as an initial manifestation of SLE than in those where MAS occurred during the course of SLE. The proportion of patients receiving steroid pulse therapy was lower in patients with coinfections. The deceased group demonstrated lower platelet and ferritin levels. Multiple regression analysis revealed that age and thrombocytopenia were independent factors associated with poor prognosis. In receiver operating characteristic analysis, a platelet count cutoff value of ≤47 × 109/L was a predictor of poor outcome. CONCLUSIONS: SLE-MAS patients demonstrated high lupus activity, and lupus activity was especially higher in patients with MAS as an initial manifestation. Lupus activity was the predominant trigger of lupus MAS. Thrombocytopenia was an independent factor for poor prognosis.

[Effect of Flow Cytometric MRD Detection at Different Time Points during AML Chemotherapy on Prognosis].

OBJECTIVE: To investigate the effect of flow cytometric minimal residual disease (MRD) detection at different time points during AML chemotherapy on prognosis. METHODS: 130 adult primary AML patients diagnosed and standardized with chemotherapy from March 2018 to March 2022 were retrospectively analyzed, MRD was detected by flow cytometry, Kaplan-Meier curves was used for survival analysis and log-rank test was used for variance analysis, and univariate and multifactor influencing patient survival with COX proportional risk regression model analysis. Cumulative incidence rate (CIR) analysis with competing risk model and variance analysis using Fine-Gray. RESULTS: There were 81 CR1, 26 CR2, 14 PR, and 9 NR patients in 130 patients. OS of the CR1 group was higher than that in the CR2, PR,and NR groups. OS of the CR2 group was higher than that in the PR group, but there was no statistically difference compared to the NR group. There was no statistically difference in OS between the PR and NR groups. 107 patients in CR1 and CR2 were grouped according to MRD detected by flow cytometry, and after the first induction chemotherapy, for patients in the MRD- and MRD+ groups, the 4-year expected RFS rates were 65.3% and 27.9% respectively, the 4-year expected OS rates were 58.7% and 41.4% respectively, and the 4-year expected CIR were 34.7% and 69.7% respectively, with statistically significant differences between 2 groups (χ2=6.639, P =0.010; χ2=6.131, P =0.013 and χ2=6.637， P =0.010). After the second chemotherapy, for patients in the MRD- and MRD+ groups, the 4-year expected RFS rates were 50.8% and 37.9% respectively, the 4-year expected OS rates were 49.2% and 44.5% respectively, and the 4-year expected CIR were 49.2% and 59.5% respectively, with no statistically significant differences between 2 groups (χ2=1.475, P =0.225; χ2=2.432, P =0.119 and χ2=1.416， P =0.234). During consolidation therapy, for patients in the MRD - and MRD+ groups, the 4-year expected RFS rates were 51.9% and 29.6% respectively, the 4-year expected OS rates were 67.5% and 24.6% respectively, and the 4-year expected CIR were 48.1% and 70.4% respectively, with statistically significant differences between 2 groups (χ2=20.982, P < 0.001; χ2=17.794, P < 0.001 and χ2=19.879， P < 0.001). For patients with MRD- at all three time points and positive at either time point, the 4-year expected RFS rates were 69.9% and 33.3% respectively, the 4-year expected OS rates were 59.1% and 44.7% respectively, and the 4-year expected CIR were 30.1% and 65.1% respectively, with statistically significant differences between 2 groups (χ2=7.367, P =0.007; χ2=6.042, P =0.014 and χ2=7.662， P =0.006). Univariate analysis showed that karyotype at high risk of chromosome was an unfavorable factor affecting patients' RFS and OS, while 2 cycles of induction chemotherapy achieved CR, MRD- after the first induction chemotherapy and MRD- after the second induction chemotherapy was a protective factor affecting patients' RFS and OS. MRD- during consolidation therapy and MRD- at all three time points were all protective factors affecting patients' RFS, OS and CIR. Multivariate analysis showed that induction chemotherapy for 2 cycles achieved CR was a protective factor affecting patients' RFS and CIR, and MRD- during consolidation therapy was a protective factor affecting patients' RFS, OS and CIR. CONCLUSION: Early achievement of CR and MRD- in adult AML patients, especially MRD- during consolidation therapy, is a marker of good prognosis, and flow cytometry is the most commonly used method for MRD detection in AML patients.

Assessment of Endoscopy-Based Scoring Systems for Prognostication in Ulcerative Colitis: A Comparative Analysis.

BACKGROUND AND OBJECTIVE: Endoscopy-based scoring systems, including Mayo Endoscopic Score (MES), Modified Mayo Endoscopic Score (MMES), and Degree of Ulcerative Colitis Burden of Luminal Inflammation (DUBLIN) Score, have been introduced to evaluate UC prognosis. This study aims to compare their predictive capacity for clinical outcomes in UC patients. METHODS: Consecutive UC patients from a tertiary hospital were included. The primary outcome was acute severe ulcerative colitis (ASUC), and secondary outcomes were UC-related admission, medication treatment escalation, disease extension and surgery. Predictive performance was assessed using receiver operating characteristic (ROC) curves. RESULTS: Among 300 patients, 15.3% developed ASUC. Robust correlations were observed among the three scoring systems and were with elevated serum inflammatory markers. The DUBLIN score exhibited superior predictive ability for UC-related admission (AUC 0.751; 95%CI 0.698-0.799) and medication treatment escalation (AUC 0.735; 95% CI 0.681-0.784). No statistical differences were found among three scoring systems for predicting ASUC, disease extension, and surgery. Employing respective cut-offs of 2, 11.25, and 3, higher MES (HR = 3.859, 95% CI 1.636-9.107, p = 0.002), MMES (HR = 3.352, 95% CI 1.879-5.980, p < 0.001), and DUBLIN score (HR = 5.619, 95% CI 2.378-13.277, p < 0.001) were associated with an increased risk of developing ASUC. CONCLUSION: The DUBLIN score, assessing the overall inflammatory burden of the intestinal tract, outperforms the MMES in predicting admission and medication treatment escalation related to UC. Its integration into clinical practice has the potential to enhance risk stratification for patients with UC.

Corrigendum: Epigenetic immune monitoring for COVID-19 disease course prognosis.

[This corrects the article DOI: 10.3389/fimmu.2023.1107900.].

Different types of tumor microvessels in stage I-IIIA squamous cell lung cancer and their clinical significance.

BACKGROUND: Lung cancer (LC) is the leading cause of morbidity and mortality among malignant neoplasms. Improving the diagnosis and treatment of LC remains an urgent task of modern oncology. Previously, we established that in gastric, breast and cervical cancer, tumor microvessels (MVs) differ in morphology and have different prognostic significance. The connection between different types of tumor MVs and the progression of LC is not well understood. AIM: To evaluate the morphological features and clinical significance of tumor MVs in lung squamous cell carcinoma (LUSC). METHODS: A single-center retrospective cohort study examined medical records and archival paraffin blocks of 62 and 180 patients with stage I-IIIA LUSC in the training and main cohorts, respectively. All patients underwent radical surgery (R0) at the Orenburg Regional Cancer Clinic from May/20/2009 to December/14/2021. Tumor sections were routinely processed, and routine Mayer's hematoxylin and eosin staining and immunohistochemical staining for cluster of differentiation 34 (CD34), podoplanin, Snail and hypoxia-inducible factor-1 alpha were performed. The morphological features of different types of tumor MVs, tumor parenchyma and stroma were studied according to clinicopathological characteristics and LUSC prognosis. Statistical analysis was performed using Statistica 10.0 software. Univariate and multivariate logistic regression analyses were performed to identify potential risk factors for LUSC metastasis to regional lymph nodes (RLNs) and disease recurrence. Receiver operating characteristic curves were constructed to discriminate between patients with and without metastases in RLNs and those with and without disease recurrence. The effectiveness of the predictive models was assessed by the area under the curve. Survival was analyzed using the Kaplan-Meier method. The log-rank test was used to compare survival curves between patient subgroups. A value of P < 0.05 was considered to indicate statistical significance. RESULTS: Depending on the morphology, we classified tumor vessels into the following types: normal MVs, dilated capillaries (DCs), atypical DCs, DCs with weak expression of CD34, "contact-type" DCs, structures with partial endothelial linings, capillaries in the tumor solid component and lymphatic vessels in lymphoid and polymorphocellular infiltrates. We also evaluated the presence of loose, fine fibrous connective tissue (LFFCT) and retraction clefts in the tumor stroma, tumor spread into the alveolar air spaces (AASs) and fragmentation of the tumor solid component. According to multivariate analysis, the independent predictors of LUSC metastasis in RLNs were central tumor location (P < 0.00001), the presence of retraction clefts (P = 0.003), capillaries in the tumor solid component (P = 0.023) and fragmentation in the tumor solid component (P = 0.009), whereas the independent predictors of LUSC recurrence were tumor grade 3 (G3) (P = 0.001), stage N2 (P = 0.016), the presence of LFFCT in the tumor stroma (P < 0.00001), fragmentation of the tumor solid component (P = 0.0001), and the absence of tumor spread through the AASs (P = 0.0083). CONCLUSION: The results obtained confirm the correctness of our previously proposed classification of different types of tumor vessels and may contribute to improving the diagnosis and treatment of LUSC.

Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models.

INTRODUCTION: Identification of individuals with mild cognitive impairment (MCI) who are at risk of developing Alzheimer's disease (AD) is crucial for early intervention and selection of clinical trials. METHODS: We applied natural language processing techniques along with machine learning methods to develop a method for automated prediction of progression to AD within 6 years using speech. The study design was evaluated on the neuropsychological test interviews of n = 166 participants from the Framingham Heart Study, comprising 90 progressive MCI and 76 stable MCI cases. RESULTS: Our best models, which used features generated from speech data, as well as age, sex, and education level, achieved an accuracy of 78.5% and a sensitivity of 81.1% to predict MCI-to-AD progression within 6 years. DISCUSSION: The proposed method offers a fully automated procedure, providing an opportunity to develop an inexpensive, broadly accessible, and easy-to-administer screening tool for MCI-to-AD progression prediction, facilitating development of remote assessment. HIGHLIGHTS: Voice recordings from neuropsychological exams coupled with basic demographics can lead to strong predictive models of progression to dementia from mild cognitive impairment. The study leveraged AI methods for speech recognition and processed the resulting text using language models. The developed AI-powered pipeline can lead to fully automated assessment that could enable remote and cost-effective screening and prognosis for Alzehimer's disease.

Revolutionizing Pulmonary Diagnostics: A Narrative Review of Artificial Intelligence Applications in Lung Imaging.

Artificial intelligence (AI) has emerged as a transformative force in healthcare, particularly in pulmonary diagnostics. This comprehensive review explores the impact of AI on revolutionizing lung imaging, focusing on its applications in detecting abnormalities, diagnosing pulmonary conditions, and predicting disease prognosis. We provide an overview of traditional pulmonary diagnostic methods and highlight the importance of accurate and efficient lung imaging for early intervention and improved patient outcomes. Through the lens of AI, we examine machine learning algorithms, deep learning techniques, and natural language processing for analyzing radiology reports. Case studies and examples showcase the successful implementation of AI in pulmonary diagnostics, alongside challenges faced and lessons learned. Finally, we discuss future directions, including integrating AI into clinical workflows, ethical considerations, and the need for further research and collaboration in this rapidly evolving field. This review underscores the transformative potential of AI in enhancing the accuracy, efficiency, and accessibility of pulmonary healthcare.

Identification of a new genetic variant (G231N, E232T, N235D) of peptidylarginine deiminase from P. gingivalis in advanced periodontitis.

Chronic periodontitis (CP), an inflammatory disease of periodontal tissues driven by a dysbiotic subgingival bacterial biofilm, is also associated with several systemic diseases, including rheumatoid arthritis (RA). Porphyromonas gingivalis, one of the bacterial species implicated in CP as a keystone pathogen produces peptidyl arginine deiminase (PPAD) that citrullinates C-terminal arginine residues in proteins and peptides. Autoimmunity to citrullinated epitopes is crucial in RA, hence PPAD activity is considered a possible mechanistic link between CP and RA. Here we determined the PPAD enzymatic activity produced by clinical isolates of P. gingivalis, sequenced the ppad gene, and correlated the results with clinical determinants of CP in patients from whom the bacteria were isolated. The analysis revealed variations in PPAD activity and genetic diversity of the ppad gene in clinical P. gingivalis isolates. Interestingly, the severity of CP was correlated with a higher level of PPAD activity that was associated with the presence of a triple mutation (G231N, E232T, N235D) in PPAD in comparison to W83 and ATCC 33277 type strains. The relation between mutations and enhanced activity was verified by directed mutagenesis which showed that all three amino acid residue substitutions must be introduced into PPAD expressed by the type strains to obtain the super-active enzyme. Cumulatively, these results may lead to the development of novel prognostic tools to assess the progress of CP in the context of associated RA by analyzing the ppad genotype in CP patients infected with P. gingivalis.

Clinical characteristics of autoimmune encephalitis with co-existence of multiple anti-neuronal antibodies.

BACKGROUND: An increasing number of cases of autoimmune encephalitis (AE) with co-existing multiple anti-neuronal antibodies have been reported in recent years. However, the clinical significance of the concurrent presence of multiple anti-neuronal antibodies in patients with AE remains unclear. METHODS: We retrospectively enrolled AE patients with multiple anti-neuronal antibodies treated at our center between August 2019 and February 2022. We also reviewed cases reported in multiple literature databases. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed on selection process. And then the clinical and laboratory data of these cases were collected for review and summary. RESULTS: A total of 83 AE cases with multiple antibodies (9 cases from our center and 74 cases from the literatures reviewed) were identified. In our center, nine patients presented with encephalitis symptoms, clinically characterized as disturbed consciousness, seizures, cognitive impairment, and psychiatric disorders. Of the 83 cases, 73 cases had co-existence of 2 types of antibodies, 8 cases had 3 types, and 2 cases had 4 types. Thirty-nine cases (39/83, 46.9%) were confirmed or suspected of also having a tumor, of which the most common was lung cancer (28/83, 33.7%). Partial or complete recovery was achieved in 57 cases (57/83, 68.6%), while 26 cases (26/83, 31.3%) died during treatment or follow-up. CONCLUSIONS: AE with co-existing multiple anti-neuronal antibodies is a specific subgroup, that is increasingly recognized in clinical practice. The co-existence of multiple anti-neuronal antibodies has a major impact on clinical features, disease progression, and prognosis.

Cohort studies in public health practice and their significance / 上海预防医学

Cohort studies play an important role in elucidating the association between risk factors and diseases， and are widely used in etiology research， the assessment of disease prognosis， understanding the natural history of diseases， and the surveillance following the market release of new drugs. The data produced by cohort studies possess great scientific value and can provide essential evidence for public health practice. A well-conceived scientific design is a prerequisite to conducting a cohort study， and the design should focus on aspects such as sample size， selection of exposed and non-exposed populations， follow-up procedures， outcome assessments， research duration， and the choice of analytical indicators and methods. Cohort studies have become an important way to obtain scientific evidence. Internationally renowned population-based cohorts， such as China Kadoorie biobank and the Framingham heart study cohort， have provided a wealth of scientifically valuable evidence for promoting human health. The quality of data produced by a cohort study is extremely important， and a cohort study should continuously incorporate new technologies and methods to provide objective， accurate， and reliable means to determine exposure and outcomes， as well as control for bias. Cohort studies have great potential for application and will continue to provide abundant high-quality scientific evidence for the development of strategies and measures to enhance human health.

p16 Overexpression in Sinonasal Squamous Cell Carcinoma: Association with Human Papillomavirus and Prediction of Survival Outcomes.

p16 overexpression is often used as a surrogate marker for human papillomavirus (HPV) infection in oropharyngeal squamous cell carcinoma but remains an uncertain diagnostic tool for HPV-related sinonasal squamous cell carcinoma (SNSCC). Our study involved 79 consecutive SNSCC patients who were treated at a tertiary referral university hospital during 2006-2021. We retrospectively examined their clinical characteristics and conducted p16 immunohistochemistry and HPV detection. We found that 12.7% of the patients exhibited p16 overexpression, which was significantly more common in the nasal cavity and increased from 2015 onward. The HPV was a high-risk type and viral loads ranged from 4.2 to 1.6 × 106 copies/ng DNA with genome integration. Five-year overall survival (OS) and five-year relapse-free survival (RFS) rates were 74.6% and 69.9%, respectively. Our multivariate analysis showed that T category (T1-4a) and hemoglobin levels (≥13.7) were significant favorable prognostic factors for OS, while T category, performance status, and p16 overexpression were significantly associated with RFS. In patients with p16 overexpression, OS was 100% and RFS was 90%. Our findings suggest that p16 overexpression is a reliable surrogate marker for transcriptionally active HPV infection and predicts a favorable prognosis.

Prognostic prediction of idiopathic membranous nephropathy using interpretable machine learning.

BACKGROUND: Established prognostic models of idiopathic membranous nephropathy (IMN) were limited to traditional modeling methods and did not comprehensively consider clinical and pathological patient data. Based on the electronic medical record (EMR) system, machine learning (ML) was used to construct a risk prediction model for the prognosis of IMN. METHODS: Data from 418 patients with IMN were diagnosed by renal biopsy at the Fifth Clinical Medical College of Shanxi Medical University. Fifty-nine medical features of the patients could be obtained from EMR, and prediction models were established based on five ML algorithms. The area under the curve, recall rate, accuracy, and F1 were used to evaluate and compare the performances of the models. Shapley additive explanation (SHAP) was used to explain the results of the best-performing model. RESULTS: One hundred and seventeen patients (28.0%) with IMN experienced adverse events, 28 of them had compound outcomes (ESRD or double serum creatinine (SCr)), and 89 had relapsed. The gradient boosting machine (LightGBM) model had the best performance, with the highest AUC (0.892 ± 0.052, 95% CI 0.840-0.945), accuracy (0.909 ± 0.016), recall (0.741 ± 0.092), precision (0.906 ± 0.027), and F1 (0.905 ± 0.020). Recursive feature elimination with random forest and SHAP plots based on LightGBM showed that anti-phospholipase A2 receptor (anti-PLA2R), immunohistochemical immunoglobulin G4 (IHC IgG4), D-dimer (D-DIMER), triglyceride (TG), serum albumin (ALB), aspartate transaminase (AST), ß2-microglobulin (BMG), SCr, and fasting plasma glucose (FPG) were important risk factors for the prognosis of IMN. Increased risk of adverse events in IMN patients was correlated with high anti-PLA2R and low IHC IgG4. CONCLUSIONS: This study established a risk prediction model for the prognosis of IMN using ML based on clinical and pathological patient data. The LightGBM model may become a tool for personalized management of IMN patients.

Severe Acute Bronchial Asthma with Sepsis: Determining the Status of Biomarkers in the Diagnosis of the Disease.

Bronchial asthma is a widely prevalent illness that substantially impacts an individual's health standard worldwide and has a significant financial impact on society. Global guidelines for managing asthma do not recommend the routine use of antimicrobial agents because most episodes of the condition are linked to viral respiratory tract infections (RTI), and bacterial infection appears to have an insignificant impact. However, antibiotics are recommended when there is a high-grade fever, a consolidation on the chest radiograph, and purulent sputum that contains polymorphs rather than eosinophils. Managing acute bronchial asthma with sepsis, specifically the choice of whether or not to initiate antimicrobial treatment, remains difficult since there are currently no practical clinical or radiological markers that allow for a simple distinction between viral and bacterial infections. Researchers found that serum procalcitonin (PCT) values can efficiently and safely minimize antibiotic usage in individuals with severe acute asthma. Again, the clinical manifestations of acute asthma and bacterial RTI are similar, as are frequently used test values, like C-reactive protein (CRP) and white blood cell (WBC) count, making it harder for doctors to differentiate between viral and bacterial infections in asthma patients. The role and scope of each biomarker have not been precisely defined yet, although they have all been established to aid healthcare professionals in their diagnostics and treatment strategies.