Identification of hub genes and establishment of a diagnostic model in tuberculosis infection.

Tuberculosis (TB) poses significant challenges due to its high transmissibility within populations and intrinsic resistance to treatment, rendering it a formidable respiratory disease with a substantial susceptibility burden. This study was designed to identify new potential therapeutic targets for TB and establish a diagnostic model. mRNA expression data for TB were from GEO database, followed by conducting differential expression analysis. The top 50 genes with differential expression were subjected to GO and KEGG enrichment analyses. To establish a PPI network, the STRING database was utilized, and hub genes were identified utilizing five algorithms (EPC, MCC, MNC, Radiality, and Stress) within the cytoHubba plugin of Cytoscape software. Furthermore, a hub gene co-expression network was constructed using the GeneMANIA database. Consistency clustering was performed on hub genes, and ssGSEA was utilized to analyze the extent of immune infiltration in different subgroups. LASSO analysis was employed to construct a diagnostic model, and ROC curves were used for validation. Through the analysis of GEO data, a total of 159 genes were identified as differentially expressed. Further, GO and KEGG enrichment analyses revealed that these genes were mainly enriched in viral defense, symbiotic defense, and innate immune response-related pathways. Hub genes, including DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15, were identified using cytoHubba analysis of the PPI network. The GeneMANIA analysis unmasked that the co-expression rate of hub genes was 81.55%, and the physical interaction rate was 12.27%. Consistency clustering divided TB patients into two subgroups, and ssGSEA revealed different degrees of immune infiltration in different subgroups. LASSO analysis identified IFIT1, IFIT2, IFIT3, IFIH1, RSAD2, OAS1, OAS2, and STAT1 as eight immune-related key genes, and a diagnostic model was constructed. The ROC curve demonstrated that the model exhibited excellent diagnostic performance. DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15 were hub genes in TB, and the diagnostic model based on eight immune-related key genes exhibited good diagnostic performance.

Metabolomics of cerebrospinal fluid reveals candidate diagnostic biomarkers to distinguish between spinal muscular atrophy type II and type III.

AIMS: Classification of spinal muscular atrophy (SMA) is associated with the clinical prognosis; however, objective classification markers are scarce. This study aimed to identify metabolic markers in the cerebrospinal fluid (CSF) of children with SMA types II and III. METHODS: CSF samples were collected from 40 patients with SMA (27 with type II and 13 with type III) and analyzed for metabolites. RESULTS: We identified 135 metabolites associated with SMA types II and III. These were associated with lysine degradation and arginine, proline, and tyrosine metabolism. We identified seven metabolites associated with the Hammersmith Functional Motor Scale: 4-chlorophenylacetic acid, adb-chminaca,(+/-)-, dodecyl benzenesulfonic acid, norethindrone acetate, 4-(undecan-5-yl) benzene-1-sulfonic acid, dihydromaleimide beta-d-glucoside, and cinobufagin. Potential typing biomarkers, N-cyclohexylformamide, cinobufagin, cotinine glucuronide, N-myristoyl arginine, 4-chlorophenylacetic acid, geranic acid, 4-(undecan-5-yl) benzene, and 7,8-diamino pelargonate, showed good predictive performance. Among these, N-myristoyl arginine was unaffected by the gene phenotype. CONCLUSION: This study identified metabolic markers are promising candidate prognostic factors for SMA. We also identified the metabolic pathways associated with the severity of SMA. These assessments can help predict the outcomes of screening SMA classification biomarkers.

Myokines and Biomarkers of Frailty in Older Inpatients with Undernutrition: A Prospective Study.

BACKGROUND: Population aging might increase the prevalence of undernutrition in older people, which increases the risk of frailty. Numerous studies have indicated that myokines are released by skeletal myocytes in response to muscular contractions and might be associated with frailty. This study aimed to evaluate whether myokines are biomarkers of frailty in older inpatients with undernutrition. METHODS: The frailty biomarkers were extracted from the Gene Expression Omnibus and Genecards datasets. Relevant myokines and health-related variables were assessed in 55 inpatients aged ≥ 65 years from the Peking Union Medical College Hospital prospective longitudinal frailty study. Serum was prepared for enzyme-linked immunosorbent assay using the appropriate kits. Correlations between biomarkers and frailty status were calculated by Spearman's correlation analysis. Multiple linear regression was performed to investigate the association between factors and frailty scores. RESULTS: The prevalence of frailty was 13.21%. The bioinformatics analysis indicated that leptin, adenosine 5'-monophosphate-activated protein kinase (AMPK), irisin, decorin, and myostatin were potential biomarkers of frailty. The frailty group had significantly higher concentrations of leptin, AMPK, and MSTN than the robust group (p < 0.05). AMPK was significantly positively correlated with frailty (p < 0.05). The pre-frailty and frailty groups had significantly lower concentrations of irisin than the robust group (p < 0.05), whereas the DCN concentration did not differ among the groups. Multiple linear regression suggested that the 15 factors influencing the coefficients of association, the top 50% were the ADL score, MNA-SF score, serum albumin concentration, urination function, hearing function, leptin concentration, GDS-15 score, and MSTN concentration. CONCLUSIONS: Proinflammatory myokines, particularly leptin, myostatin, and AMPK, negatively affect muscle mass and strength in older adults. ADL and nutritional status play major roles in the development of frailty. Our results confirm that identification of frailty relies upon clinical variables, myokine concentrations, and functional parameters, which might enable the identification and monitoring of frailty.

Dose-Responsive Impacts of Social Frailty on Intrinsic Capacity and Healthy Aging among Community-Dwelling Middle-aged and Older Adults: Stronger Roles of Social Determinants over Biomarkers.

OBJECTIVE: The intricate relationship between social determinants, e.g., social frailty, biomarkers and healthy aging remains largely unexplored, despite the potential for social frailty to impact both intrinsic capacity (IC) and functional ability in the aging process. DESIGN: Retrospective longitudinal cohort study. SETTING AND PARTICIPANTS: Participants aged 50+ years from the Social Environment and Biomarkers of Aging Study (SEBAS) in Taiwan, stratified into three age groups: 50-64, 65-74 and 75+. MEASUREMENTS: Social frailty was defined based on a score derived from four domains: exclusion from general resources, social resources, social activity, and fulfillment of basic social needs. The scores were categorized as score=0 (no social frailty), 1 (social pre-frailty), and 2+ (social frailty). Multivariable logistic regression and Cox proportional hazard models were employed to examine the dose-responsive relationship between social frailty, low IC, functional and psychological health, and mortality. RESULTS: Of 1015 study participants, 24.9% and 7.9% were classified as social pre-frailty and social frailty, respectively. No significant differences were observed in most biomarkers between those with social frailty and those without. A dose-responsive relationship was found between social frailty and increased risk of low IC (social pre-frailty: aOR 2.20 [95% CI 1.59-3.04]; social frailty: 5.73 [3.39-9.69]). Similar results were found for functional and psychological health. However, no significant association between social frailty and all-cause mortality was found at the 4-year follow-up (social pre-frailty: aHR 1.52 [95% CI 0.94-2.43]; social frailty: 1.59 [0.81-3.09]). CONCLUSIONS: The significant association between social frailty and low IC, functional limitations, cognitive declines, and depressive symptoms underscores the pressing need for research on intervention strategies to enhance healthy aging in the lifespan course.

Comparison of Urinary Biomarkers in Diagnosis of Ureteropelvic Junction Obstruction and Differentiation from Nonobstructive Dilatation.

Background and Aims: Differentiation of nonobstructive dilatation (NOD) from ureteropelvic junction obstruction (UPJO) is a challenge in children with antenatally detected hydronephrosis. The aim of this study is to compare the utility of urinary biomarkers: carbohydrate antigen (CA 19-9), neutrophil gelatinase-associated lipocalin (NGAL), and kidney injury molecule (KIM) in diagnosing UPJO. Methods: A prospective study was conducted after obtaining ethical clearance between 2021 and 2022. Group 1 - control group (n = 30): children with normal antenatal ultrasound with no urinary symptoms. Group 2 - study group (n = 48): children with unilateral hydronephrosis: Group 2a - NOD (n = 24): children stable on ultrasound and diuretic renogram and Group 2b - UPJO (n = 24): children who worsened to Grade 4 hydronephrosis on ultrasound/worsening of differential renal function (10% drop) on renogram who underwent pyeloplasty. Urinary biomarkers NGAL, KIM-1, and CA 19-9 were measured using the enzyme-linked immune absorbent assay method. Results: The urine CA 19-9 level was 128.05 ± 4.08 U/mL in the UPJO group, and this was significantly higher (P = 0.001) than NOD, 70.29 ± 4.41, and controls, 1.91 ± 1.57. The urine NGAL level was 21.41 ± 4.44 pg/mL in UPJO, and this was significantly higher than controls, 2.669 ± 0.513, but not NOD, 24.55 ± 2.67. The urine KIM level was 817 ± 15.84 pg/mL in the UPJO group, and this was significantly higher than controls, 285 ± 8.10, but not NOD, 768.23 ± 15.12. Receiver operating characteristic analysis of CA 19-9 revealed a urine biomarker cutoff of 95 U/mL for diagnosing UPJO (sensitivity 95%; specificity 96%; and area under the curve 0.99). Conclusions: CA 19-9 is a superior marker compared to NGAL and KIM in differentiating UPJO from NOD. Further studies with larger numbers are warranted.

Exosomal long non-coding RNAs in cancer: Interplay, modulation, and therapeutic avenues.

In the intricate field of cancer biology, researchers are increasingly intrigued by the emerging role of exosomal long non-coding RNAs (lncRNAs) due to their multifaceted interactions, complex modulation mechanisms, and potential therapeutic applications. These exosomal lncRNAs, carried within extracellular vesicles, play a vital partin tumorigenesis and disease progression by facilitating communication networks between tumor cells and their local microenvironment, making them an ideal candidates for use in a liquid biopsy approach. However, exosomal lncRNAs remain an understudied area, especially in cancer biology. Therefore this review aims to comprehensively explore the dynamic interplay between exosomal lncRNAs and various cellular components, including interactions with tumor-stroma, immune modulation, and drug resistance mechanisms. Understanding the regulatory functions of exosomal lncRNAs in these processes can potentially unveil novel diagnostic markers and therapeutic targets for cancer. Additionally, the emergence of RNA-based therapeutics presents exciting opportunities for targeting exosomal lncRNAs, offering innovative strategies to combat cancer progression and improve treatment outcomes. Thus, this review provides insights into the current understanding of exosomal lncRNAs in cancer biology, highlighting their crucial roles, regulatory mechanisms, and the evolving landscape of therapeutic interventions. Furthermore, we have also discussed the advantage of exosomes as therapeutic carriers of lncRNAs for the development of personalized targeted therapy for cancer patients.

Tuberculosis Chest X-Ray Image Retrieval System Using Deep Learning Based Biomarker Predictions.

The world health organization's global tuberculosis (TB) report for 2022 identifies TB, with an estimated 1.6 million, as a leading cause of death. The number of new cases has risen since 2020, particularly the number of new drug-resistant cases, estimated at 450,000 in 2021. This is concerning, as treatment of patients with drug resistant TB is complex and may not always be successful. The NIAID TB Portals program is an international consortium with a primary focus on patient centric data collection and analysis for drug resistant TB. The data includes images, their associated radiological findings, clinical records, and socioeconomic information. This work describes a TB Portals' Chest X-ray based image retrieval system which enables precision medicine. An input image is used to retrieve similar images and the associated patient specific information, thus facilitating inspection of outcomes and treatment regimens from comparable patients. Image similarity is defined using clinically relevant biomarkers: gender, age, body mass index (BMI), and the percentage of lung affected per sextant. The biomarkers are predicted using variations of the DenseNet169 convolutional neural network. A multi-task approach is used to predict gender, age and BMI incorporating transfer learning from an initial training on the NIH Clinical Center CXR dataset to the TB portals dataset. The resulting gender AUC, age and BMI mean absolute errors were 0.9854, 4.03years and 1.67kgm2. For the percentage of sextant affected by lesions the mean absolute errors ranged between 7% to 12% with higher error values in the middle and upper sextants which exhibit more variability than the lower sextants. The retrieval system is currently available from https://rap.tbportals.niaid.nih.gov/find_similar_cxr.

Sex differences in Alzheimer's disease blood biomarkers in a Caribbean population of African ancestry: The Tobago Health Study.

INTRODUCTION: Alzheimer's disease (AD) is increasing in the Caribbean, especially for persons of African ancestry (PAA) and women. However, studies have mostly utilized surveys without AD biomarkers. METHODS: In the Tobago Health Study (n = 309; 109 women, mean age 70.3 ± 6.6), we assessed sex differences and risk factors for serum levels of phosphorylated tau-181 (p-tau181), amyloid-beta (Aß)42/40 ratio, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). Blood samples were from 2010 to 2013 for men and from 2019 to 2023 for women. RESULTS: Women were more obese, hypertensive, and sedentary but reported less smoking and alcohol use than men (age-adjusted p < 0.04). Compared to men, women had worse levels of AD biomarkers, with higher p-tau181 and lower Aß42/40, independent of covariates (p < 0.001). In sex-stratified analyses, higher p-tau181 was associated with older age in women and with hypertension in men. GFAP and NfL did not differ by sex. DISCUSSION: Women had worse AD biomarkers than men, unexplained by age, cardiometabolic diseases, or lifestyle. Studying risk factors for AD in PAA is warranted, especially for women earlier in life.

Alzheimer's disease cerebrospinal fluid biomarkers and kidney function in normal and cognitively impaired older adults.

INTRODUCTION: Recent Alzheimer's disease (AD) clinical trials have used cerebrospinal fluid (CSF) biomarker levels for screening and enrollment. Preliminary evidence suggests that AD risk is related to impaired renal function. The impact of kidney function on commonly used AD biomarkers remains unknown. METHODS: Participants in studies conducted at the Goizueta Alzheimer's Disease Research Center (N = 973) had measurements of serum creatinine and CSF AD biomarkers. General linear models and individual data were used to assess the relationships between biomarkers and eGFR. RESULTS: Lower estimated glomerular filtration rate (eGFR) was associated with lower amyloid beta (Aß)42/tau ratio (p < 0.0001) and Aß42 (p = 0.002) and higher tau (p < 0.0001) and p-tau (p = 0.0002). The impact of eGFR on AD biomarker levels was more robust in individuals with cognitive impairment (all p-values were < 0.005). DISCUSSION: The association between eGFR and CSF AD biomarkers has a significant impact that varies by cognitive status. Future studies exploring this impact on the pathogenesis of AD and related biomarkers are needed. Highlights: There is a significant association between Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers and both estimated glomerular filtration rate (eGFR) and mild cognitive impairment (MCI).Kidney function influences CSF biomarker levels in individuals with normal cognitive function and those with MCI.The impact of kidney function on AD biomarker levels is more pronounced in individuals with cognitive impairment.The variation in CSF tau levels is independent of cardiovascular factors and is likely directly related to kidney function.Tau may have a possible role in both kidney and cognitive function.

A novel PD-1/PD-L1 pathway-related seven-gene signature for the development and validation of the prognosis prediction model for breast cancer.

Background: Breast cancer (BC/BRCA) is the most common carcinoma in women. The average 5-year survival rate of BC patients with stage IV disease is 26%. A considerable proportion of patients still do not receive effective therapy. It is an unmet need to identify novel biomarkers for BC patients. Herein, we evaluated whether the programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) status is associated with the clinical outcomes of BC, based on data from The Cancer Genome Atlas (TCGA). Methods: Clinical and transcriptome data of BC patients were obtained from TCGA dataset, and prognostic genes in BC patients were identified, as well as the PD-1/PD-L1 pathway mainly associating with the BC patients. Following the execution of the consensus clustering algorithm, BC patients were segregated into two clusters, and subsequent investigation of the potential mechanisms between them was carried out. A comparison of ferroptosis and N6-methyladenosine (m6A) was conducted between the two groups with the greatest difference in prognosis. Based on least absolute shrinkage and selection operator (LASSO) analysis, a signature associated with the PD-1/PD-L1 pathway was developed, and the prognosis outcome and the predictive accuracy of the signature model were further assessed. Results: Prognostic genes in BC patients were studied using TCGA data and it was found that the PD-1/PD-L1 pathway was most associated with the BC patients. Then, a low-risk (C1) group and a high-risk (C2) group of BC patients were constructed based on a PD-1/PD-L1 pathway-related signature. The functional analyses suggested that the underlying mechanisms between these groups were mainly associated with immune-related pathways. We found that ferroptosis and m6A were significantly different between the two groups. A PD-1/PD-L1 pathway-related gene signature was further developed to predict survival of BC patients, including 7 genes [mitogen-activated protein kinase kinase 6 (MAP2K6), NF-kappa-B inhibitor alpha (NFKBIA), NFKB Inhibitor Epsilon (NFKBIE), Interferon gamma (IFNG), Toll/interleukin-1 receptor domain-containing adapter protein (TIRAP), IkappaB kinase (CHUK), and Casein kinase 2 alpha 3 gene (CSNK2A3)]. The receiver operating characteristic (ROC) curves were analyzed to further assess the prognostic values of these 7 genes. The 1-, 3-, and 5-year values of the areas under the curve (AUCs) for overall survival were 0.651, 0.658, and 0.653 in this seven gene signature model, respectively. Conclusions: PD-1/PD-L1 pathway-related subtypes of BC were identified, which were closely associated with the immune microenvironment, the ferroptosis status, and m6A in BC patients. The gene signature involved in the PD-1/PD-L1 pathway might help to make a distinction and predict prognosis in BC patients.

Evaluating serum CXCL12, sCD22, Lp-PLA2 levels and ratios as biomarkers for diagnosis of Alzheimer's disease.

BACKGROUND: Grasping the underlying mechanisms of Alzheimer's disease (AD) is still a work in progress, and existing diagnostic techniques encounter various obstacles. Therefore, the discovery of dependable biomarkers is essential for early detection, tracking the disease's advancement, and steering treatment strategies. AIM: To explore the diagnostic potential of serum CXCL12, sCD22, Lp-PLA2, and their ratios in AD, aiming to enhance early detection and inform targeted treatment strategies. METHODS: The study was conducted in Dongying people's Hospital from January 2021 to December 2022. Participants included 60 AD patients (AD group) and 60 healthy people (control group). Using a prospective case-control design, the levels of CXCL12, sCD22 and Lp-PLA2 and their ratios were detected by enzyme-linked immunosorbent assay kit in the diagnosis of AD. The differences between the two groups were analyzed by statistical methods, and the corresponding ratio was constructed to improve the specificity and sensitivity of diagnosis. RESULTS: Serum CXCL12 levels were higher in the AD group (47.2 ± 8.5 ng/mL) than the control group (32.8 ± 5.7 ng/mL, P < 0.001), while sCD22 levels were lower (14.3 ± 2.1 ng/mL vs 18.9 ± 3.4 ng/mL, P < 0.01). Lp-PLA2 levels were also higher in the AD group (112.5 ± 20.6 ng/mL vs 89.7 ± 15.2 ng/mL, P < 0.05). Significant differences were noted in CXCL12/sCD22 (3.3 vs 1.7, P < 0.001) and Lp-PLA2/sCD22 ratios (8.0 vs 5.2, P < 0.05) between the groups. Receiver operating characteristic analysis confirmed high sensitivity and specificity of these markers and their ratios in distinguishing AD, with area under the curves ranging from 0.568 to 0.787. CONCLUSION: Serum CXCL12 and Lp-PLA2 levels were significantly increased, while sCD22 were significantly decreased, as well as increases in the ratios of CXCL12/sCD22 and Lp-PLA2/sCD22, are closely related to the onset of AD. These biomarkers and their ratios can be used as potential diagnostic indicators for AD, providing an important clinical reference for early intervention and treatment.

Potential salivary and serum biomarkers for burning mouth syndrome and their relationship with anxiety/depression.

Background/purpose: The pathophysiology of burning mouth syndrome (BMS), although considered a multifactorial etiology including psychological factors, is still not well understood. Hence, this study aimed to investigate the potential usage of salivary and serum biomarkers, including brain-derived neurotrophic factor (BDNF), interferon-gamma (IFN-γ), interleukin-1beta (IL-1ß), interleukin-6 (IL-6), interleukin-8 (IL-8), and tumor necrosis factor-alpha (TNF-α), in diagnosing BMS and their correlations with anxiety/depression. Materials and methods: 45 BMS patients and 14 healthy volunteers were enrolled. The patients were divided into BMS with anxiety/depression group and BMS without anxiety/depression group according to the scores of the Zung Self-rating Anxiety Scale (SAS) and Zung Self-rating Depression Scale (SDS). Additionally, concentrations of BDNF, IFN-γ, IL-1ß, IL-6, IL-8, and TNF-α in saliva and those in serum among the patients and healthy volunteers were assessed by multiplex assay using Luminex 200TM system and Enzyme-linked immunosorbent assay (ELISA), respectively. Results: Among all the serum biomarkers, only BDNF showed a statistically significant decrease in the patients than the healthy volunteers (P < 0.05). Regarding saliva biomarkers, BDNF, IL-1ß, and IL-8 all exhibited a statistically significant increase in all the BMS patients versus the healthy volunteers (P < 0.05) but only BDNF was significantly different between patients with anxiety/depression and healthy individuals when considering anxiety/depression. Among BMS patients with anxiety/depression, saliva TNF-α had positive associations with other biomarkers including BDNF, IFN-γ, IL-1ß, IL-6, and IL-8 (P < 0.05). Conclusion: The increased concentration of saliva BDNF holds strong potential for diagnosing BMS and the elevated level of saliva TNF-α is crucial in identifying BMS patients with anxiety/depression.

The assessment of dietary carotenoid intake of the Cardio-Med FFQ using food records and biomarkers in an Australian cardiology cohort: a pilot validation.

Dietary carotenoids are associated with lower risk of CHD. Assessment of dietary carotenoid intake using questionnaires can be susceptible to measurement error. Consequently, there is a need to validate data collected from FFQs which measure carotenoid intake. This study aimed to assess the performance of the Cardio-Med Survey Tool (CMST)-FFQ-version 2 (v2) as a measure of dietary carotenoid intake over 12-months against plasma carotenoids biomarkers and 7-Day Food Records (7DFR) in an Australian cardiology cohort. Dietary carotenoid intakes (ß- and α-carotene, lycopene, ß-cryptoxanthin and lutein/zeaxanthin) were assessed using the 105-item CMST-FFQ-v2 and compared to intakes measured by 7DFR and plasma carotenoid concentrations. Correlation coefficients were calculated between each dietary method, and validity coefficients (VCs) were calculated between each dietary method and theoretical true intake using the 'methods of triads'. Thirty-nine participants aged 37-77 years with CHD participated in the cross-sectional study. The correlation between FFQ and plasma carotenoids were largest and significant for ß-carotene (0.39, p=0.01), total carotenoids (0.37, p=0.02) and ß-cryptoxanthin (0.33, p=0.04), with weakest correlations observed for α-carotene (0.21, p=0.21) and lycopene (0.21, p=0.21). The FFQ VCs were moderate (0.3-0.6) or larger for all measured carotenoids. The strongest were observed for total carotenoids (0.61) and ß-carotene (0.59), while the weakest were observed for α-carotene (0.33) and lycopene (0.37). In conclusion, the CMST-FFQ-v2 measured dietary carotenoids intakes with moderate confidence for most carotenoids, however, there was less confidence in ability to measure α-carotene and lycopene intake, thus further research is warranted using a larger sample.

Neutrophil-to-Lymphocyte Ratio and Blood Eosinophil Levels As Inflammatory Indicators in Smoker and Non-smoker Young Adult Patients With Chronic Obstructive Pulmonary Disease at a Tertiary Care Hospital.

Background Inflammatory markers are elevated in chronic obstructive pulmonary disease (COPD) and can be quantified to detect severity, prognosis, mortality risk, and response to treatment. However, the estimation costs are high. The blood neutrophil-to-lymphocyte ratio (NLR) and eosinophil levels are emerging as biomarkers in COPD, yet there is a paucity of data. Aim and objectives This study was designed to elucidate the roles of the NLR and eosinophil levels in smokers and non-smokers with stable COPD male subjects, correlating them with lung functions. Materials and methods A prospective observational clinical study was conducted from January to June 2023, after receiving approval from the Institutional Ethics Committee, on 73 COPD patients aged 30-60 years who gave voluntary informed consent. Complete blood counts and spirometry were performed. Patients with a forced expiratory volume in one second (FEV1) % predicted <70% and an FEV1/forced vital capacity (FVC) % <70% based on the pulmonary function test (MIR Spirolab) were included. They were further divided into mild (n=10), moderate (n=27), severe (n=26), and very severe (n=10) categories as per the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines. Subjects were also categorized into smoker (n=45) and non-smoker (n=28) groups. The complete blood count was analyzed using an automated analyzer (Beckman Coulter). Analysis was also carried out with an NLR of more or less than three. A P-value of less than 0.05 was considered significant. Results Smokers constituted 61.65% (n=45) of the subjects, and non-smokers 38.35% (n=28). Among smokers, 17.78% had very severe airflow obstruction. In all COPD subjects (n=73), lymphocytes, eosinophils, and lung functions were lower in the group where the NLR was greater than three. NLR in smokers (3.52±1.43) was higher than in non-smokers (3.39±0.94). In non-smokers (n=28), blood eosinophils and lymphocytes were elevated. In smokers (n=45), blood neutrophils, monocytes, and basophils were increased. Smokers showed a non-significant increase in RBC, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH). Neutrophils, monocytes, eosinophils, and NLR increased with disease severity. NLR negatively correlated with FEV1 (r=-0.350, p=0.034) and positively with pack-years (r=0.546, p<0.001) in smokers. NLR negatively correlated with eosinophils, FVC, FEV1/FVC, and FEV1 % predicted. In all COPD subjects (n=73), NLR negatively correlated with blood eosinophils (r=-0.184, p=0.12), BMI, and lung functions. Conclusion NLR is elevated in COPD subjects and can serve as a marker of inflammation and a predictor of the risk and severity of airflow limitation. NLR correlates both positively and negatively with pack-years and lung functions, respectively.

Factor VIII as a Novel Biomarker for Diagnosis, Prognosis, and Therapy Prediction in Human Cancer and Other Disorders.

Coagulation factor VIII (FVIII) is an essential cofactor in the coagulation cascade, encoded by the F8 gene on the long arm of chromosome X (Xq28). FVIII is normally circulated in complex with Von Willebrand factor (VWF) and has relevant emerging extracoagulative functions. Dysregulation of FVIII is associated with tumor progression, and could be used as a novel biomarker for tumor screening and monitoring. In breast cancer, bladder cancer, colorectal carcinoma, esophageal carcinoma, hepatocellular carcinoma and lung cancer, F8 is regarded as an oncogene. In coronary heart disease, hemophilia A and liver disease, F8 dysregulation has been recognized as a potential biomarker for disease diagnosis and prognosis. However, the basis of these differential expression levels remains to be understood. In this review, which is a mixture of literature review and bioinformatics analysis we described the biological functions and characteristics of FVIII, and also its expression level in non-malignant disorders and various cancers.

The potential molecular markers of inflammatory response in KOA with AD based on single-cell transcriptome sequencing analysis and identification of ligands by virtual screening.

Alzheimer's disease (AD) and osteoarthritis (OA) are both senile degenerative diseases. Clinical studies have found that OA patients have a significantly increased risk of AD in their later life. This study hypothesized that chronic aseptic inflammation might lead to AD in KOA patients. However, current research has not yet clarified the potential mechanism between AD and KOA. Therefore, this study intends to use KOA transcriptional profiling and single-cell sequencing analysis technology to explore the molecular mechanism of KOA affecting AD development, and screen potential molecular biomarkers and drugs for the prediction, diagnosis, and prognosis of AD in KOA patients. It was found that the higher the expression of TXNIP, MMP3, and MMP13, the higher the risk coefficient of AD was. In addition, the AUC of TXNIP, MMP3, and MMP13 were all greater than 0.70, which had good diagnostic significance for AD. Finally, through the virtual screening of core proteins in FDA drugs and molecular dynamics simulation, it was found that compound Cobicistat could be targeted to TXNIP, Itc could be targeted to MMP3, and Isavuconazonium could be targeted to MMP13. To sum up, TXNIP, MMP3, and MMP13 are prospective molecular markers in KOA with AD, which could be used to predict, diagnose, and prognosis.

Evaluation of inflammatory biomarkers and the ratio of hemoglobin-red cell distribution width in patients with rheumatoid arthritis treated with tumor necrosis factor-alpha inhibitors.

BACKGROUND: The aim of this study was to examine pre-treatment and post-treatment hemogram-derived inflammatory biomarkers in patients with rheumatoid arthritis (RA) who received anti-tumor necrosis factor (TNF)-α treatment. MATERIAL AND METHODS: The data of 1182 patients with RA were screened. Among them, 207 patients who met the eligibility criteria were included in the retrospective study. Demographic parameters, disease activity, and blood cell-derived indexes were evaluated. The neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and hemoglobin-red cell distribution width (Hb/RDW) rates were evaluated before treatment and at the third month of treatment in patients with RA who received anti-TNF-α treatment. RESULTS: According to the EULAR response criteria, 12.6% of the 207 patients responded to anti-TNF-α treatment as none, 21.3% as good, and 66.2% as moderate, respectively. Post-treatment NLR and PLR values were significantly lower than pre-treatment values (p < 0.001), whereas post-treatment LMR and Hb/RDW values were significantly higher than pre-treatment values (respectively, p = 0.001 and p = 0.012). The difference between pre-treatment and post-treatment values of LMR and Hb/RDW was significantly higher when compared to the moderate + good response groups than the none-response group (p = 0.002 and p = 0.014, respectively). However, in the receiver operating characteristic curve analysis, these parameters were not found to be significant in predicting treatment response. CONCLUSION: Significant changes were detected in hemogram-derived inflammatory markers of the groups responding to anti-TNF-α treatment. They can be used as a guide during treatment follow-up. Yet, they do not predict treatment response. Key Points • RA may manifest with periods of remission and activation, and regular follow-up is essential. • There is a demand for readily available, reproducible, and cost-effective parameters to assess treatment response. • Hemogram-derived inflammatory markers differ in relation to anti-TNF-α treatment response in RA. • None of those markers demonstrate an acceptable predictive performance in distinguishing patients based on their response to TNF-α inhibitors.

Deciphering the prognostic landscape of osteosarcoma: Integrating the roles of hippo pathway genes, programmed cell death, and the tumor immune microenvironment.

Osteosarcoma is a highly aggressive cancer prevalent among adolescents and young adults, notorious for its tendency to metastasize to the lungs. This research delves into the molecular foundations of osteosarcoma by examining the role of the Hippo signaling pathway and its interaction with the tumor immune microenvironment (TME). Through analysis of transcriptomic data from the TARGET-OS dataset and control samples from GTEx, we identified a set of 131 genes that link high expression profiles in osteosarcoma with the Hippo pathway. A focused examination through univariate Cox regression analysis revealed eight key genes (DLG5, WNT11, TGFB2, DLG4, WNT16, ID2, WNT10B, and WNT10A) with a significant correlation to patient outcomes. Hierarchical clustering of these genes delineated two distinct patient groups with significantly different survival rates, a finding supported by Kaplan-Meier survival analysis. Further investigation into immune cell infiltration and expression profiles of immunoregulatory factors uncovered a notable pattern of immune evasion in the group with poorer prognosis, marked by reduced effector immune cell activity and lower levels of immunostimulatory factors. Single-cell sequencing highlighted the cellular diversity within osteosarcoma samples and identified markers differentiating malignant from nonmalignant cells, correlating these markers with prognostic risk scores. Our results emphasize the critical prognostic value of Hippo pathway genes and the TME in osteosarcoma, shedding light on new avenues for therapeutic intervention and patient-specific treatment strategies.

Methods to predict heart failure in diabetes patients.

INTRODUCTION: Type 2 diabetes mellitus (T2DM) is one of the leading causes of cardiovascular disease and powerful predictor for new-onset heart failure (HF). AREAS COVERED: We focus on the relevant literature covering evidence of risk stratification based on imaging predictors and circulating biomarkers to optimize approaches to preventing HF in DM patients. EXPERT OPINION: Multiple diagnostic algorithms based on echocardiographic parameters of cardiac remodeling including global longitudinal strain/strain rate are likely to be promising approach to justify individuals at higher risk of incident HF. Signature of cardiometabolic status may justify HF risk among T2DM individuals with low levels of natriuretic peptides, which preserve their significance in HF with clinical presentation. However, diagnostic and predictive values of conventional guideline-directed biomarker HF strategy may be non-optimal in patients with obesity and T2DM. Alternative biomarkers affecting cardiac fibrosis, inflammation, myopathy, and adipose tissue dysfunction are plausible tools for improving accuracy natriuretic peptides among T2DM patients at higher HF risk. In summary, risk identification and management of the patients with T2DM with established HF require conventional biomarkers monitoring, while the role of alternative biomarker approach among patients with multiple CV and metabolic risk factors appears to be plausible tool for improving clinical outcomes.