Search Results (93)

COVID-19 and influenza A (FluA) cause severe respiratory infections in elderly patients, with cytokine dysregulation playing a central role. Direct comparative data in older adults remains limited. We aimed to characterize cytokine dynamics and their prognostic value in hospitalized elderly patients with COVID-19 vs. FluA. We performed a prospective cohort study including adults ≥ 60 years hospitalized with respiratory failure due to COVID-19 or FluA between March 2023 and March 2024. Serum IL-1β, IL-6, IL-10, IL-17A, IL-34, MCP-1, and CXCL10 were measured on Day 1 and Day 5 of hospitalization using Luminex^®. Cytokines and associations with non-invasive ventilation (NIV) were assessed by ROC analysis and multivariate logistic regression. 83 patients were included (39 COVID-19, median age 79 years; 44 FluA, median 77 years). At Day 1, COVID-19 exhibited significantly higher IL-6, IL-10, and CXCL10; FluA showed an attenuated cytokine response. At Day 5, cytokines declined in both groups. Baseline IL-6 independently predicted NIV (adjusted OR 3.02), whereas higher MCP-1 was associated with reduced NIV requirement. Early cytokine differences between COVID-19 and FluA are evident in elderly patients, but values converged by Day 5. IL-6 remains an informative early predictor of respiratory deterioration; MCP-1 may reflect a regulated innate response. Full article

Background: Neonatal mortality remains a significant public health challenge in Ethiopia. Despite efforts to implement key evidence-based interventions, their coverage and utilization remain low. The Saving Little Lives (SLL) program aims to scale-up a Minimum Care Package (MCP) of synergistic, life-saving interventions for all liveborn neonates, with a focus on preterm and low birth weight (LBW) infants, across 290 hospitals in Ethiopia (206 primary, 69 general, and 15 referral hospitals), representing 82% of all hospitals in the country at the time of the study, and evaluate the impact on neonatal mortality. Methods: A non-randomized stepped-wedge trial will be conducted to evaluate the impact of implementing the SLL MCP interventions. Quantitative evaluation data will be collected from 36 primary hospitals, selected from 206 primary hospitals across four regions, receiving the interventions. An independent evaluation research assistant will be deployed in each of the hospitals to collect data using Open Data Kit (ODK) through interviewing mothers before discharge, on the 29th day of life if discharged, and reviewing medical records. A mixed-method, cross-sectional formative assessment will be conducted prior to implementation, employing quantitative facility assessment and qualitative interviews with mothers, healthcare providers, and facility managers. This will be followed by continuous program learning assessment once implementation begins. Descriptive data will be presented using numbers, percentages, tables, and graphs. Regression modeling and generalized estimating equations (GEEs) will be used to estimate the impact of the SLL MCP interventions. Qualitative data will be gathered through in-depth interviews, digitally recorded, transcribed, and thematically analyzed using ATLAS.ti Version 7.5 software to assess facility readiness, barriers, and enablers of implementing the SLL MCP interventions. Expected Outcome: We hypothesize that achieving 80% coverage of the SLL MCP interventions among eligible neonates will result in a 35% reduction in neonatal mortality at implementation facilities. Full article

Background and Objectives: Hand joint deformity remains a main cause impairing quality of life in rheumatoid arthritis (RA). This study aimed to investigate the association between biologic and targeted-synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) treatment and the prevalence of hand joint deformity in RA patients. Materials and Methods: This cross-sectional analysis included RA patients recruited between 2019 and 2024. Hand joint deformity was defined as the presence of specific deformity in any of 28 hand joints, including the metacarpophalangeal (MCP) joints I-V, proximal interphalangeal (PIP) joints I-V, and distal interphalangeal (DIP) joints II-V. The key exposure was the use of b/tsDMARDs. Multivariable logistic regression was used to assess the association between b/tsDMARDs treatment and hand joint deformity. Results: A total of 1083 RA patients with a mean age of 52.6 ± 12.4 years and a median disease duration of 5 (2,11) years were included. Hand joint deformity was present in 25.4% (275/1083) of patients. The top three deformed joint locations were PIP V (12.9%, 140/1083), PIP III (11.6%, 126/1083), and PIP IV (10.9%, 118/1083). The top three deformity types were ulnar deviation of MCP II-V (8.0%, 87/1083), boutonniere deformity of II-V fingers (6.8%, 74/1083), and swan neck deformity of II-V fingers (6.7%, 73/1083). In total, 17.4% (188/1083) of patients had received b/tsDMARDs. After 1:1 propensity score matching for age, sex, and disease duration, the prevalence of deformity was significantly lower in patients treated with conventional medicine (csDMARDs and/or GCs) add-on b/tsDMARDs compared to those treated with conventional medicine (27.1% vs. 61.7%, p < 0.001). Multivariable logistic regression analysis showed that b/tsDMARDs use was independently associated with a lower prevalence of hand joint deformity after adjusting for confounding factors (OR = 0.211, 95%CI: 0.129–0.345, p < 0.001). Conclusions: The use of b/tsDMARDs was independently associated with a lower prevalence of hand joint deformity in RA. Full article

The consumption of ultra-processed foods (UPFs) in adolescence is high due to their widespread availability and accessibility and has been linked to increased cardiometabolic risk. In the Autonomous City of Melilla, an environment with particular cultural and religious characteristics, it is relevant to analyze the relationship of UPFs with metabolic markers of type 2 diabetes mellitus. This is a cross-sectional pilot study on 31 Muslim adolescents aged 15 to 17 years. The NOVA food classification was used to identify UPFs. The final sample comprised Muslim adolescents because written consent for venous blood sampling was obtained only from Muslim families/legal guardians. Separate multiple linear regression models adjusted for sex were fitted to examine the associations between UPF intake (%E/day) and each cardiometabolic and inflammatory marker. Higher UPF intake was positively associated with BMI, body fat percentage, waist circumference, waist-to-height indicator (ICA), and fasting glucose after controlling for the false discovery rate (q < 0.05). Regarding the inflammatory component, Muslim girls had elevated levels of IL-7, IL-10, and IL-13, and Muslim boys had higher levels of MIP-1β. In addition, IL-8 correlated positively with waist circumference, BMI, and the HDL/LDL ratio, while MCP-1 was negatively associated with Apo A1, total cholesterol, and HDL. In this exploratory pilot study, higher intake of UPF appears to be associated with greater central adiposity and higher fasting glucose; these hypothesis-generating findings warrant confirmation in larger, representative samples and may inform culturally adapted nutritional screening in Melilla. Full article

The representativeness of long-term wind data at a site remains a challenge, as it is essential for resource analysis, production adjustment in operating plants, and the simulation of hybridised plants. A representative one-year hourly time series, known as a Wind Reference Year (WRY), is required, yet the availability of long-term real data is rare, making the estimation of WRY from reanalysis data and shorter measurement campaigns a common approach. In this study, Gaussian Mixture Copula Models (GMCM) and five regression models were applied and compared. The GMCM was trained using 15 years of reanalysis data to generate simulations, and subsequently, regression-based Measure–Correlate–Predict (MCP) methods were applied to adapt the simulated reference year to site-specific conditions. Finally, the Hungarian algorithm was used to reorder the simulated data series, aligning it with a typical wind pattern and producing the WRY dataset. The results were validated against 15 years of real measurements and benchmarked against a heuristic method based on long-term similarity of main wind parameters and the commercial tool Windographer. The findings demonstrate the potential of the proposed method, showing improvements over existing techniques and providing a robust approach to constructing representative WRY datasets. Full article

HIV infection is accompanied by production of pro-inflammatory cytokines, which are regarded as critical in neuronal damage, leading to brain dysfunction. To develop diagnostic tools and therapeutic interventions, we need to measure CNS response to immune activation, hence the need to identify specific cytokine biomarkers that are associated with brain damage in HIV infection. This cross-sectional retrospective study applied Magnetic Resonance Imaging (MRI) for brain volumetric measurements and high-throughput Luminex-based immunoassays to quantify plasma cytokine and chemokine concentrations. We then used generalized linear models and Partial Least Square Regression models to evaluate the association between brain volume and plasma cytokines in predominantly treatment-naïve participants with HIV. After adjusting for clinical and demographic variables, we observed that higher MCP-1 (p = 0.013) and RANTES (p = 0.002) remained significantly associated with lower cortical white matter volume, whereas the anti-inflammatory cytokine IL-9 (p = 0.025) and the growth factors PDGFBB (p = 0.012) and VEGF (p = 0.001) were associated with higher cortical white matter volume. Only IL-6 (p = 0.010) was significantly associated with lower subcortical grey matter volume. Higher concentrations of five pro-inflammatory cytokines, IL-6 (p = 0.0001), IL-8 (p = 0.018), GCSF (p = 0.004), MCP-1 (p = 0.004), and RANTES (p = 0.015), were associated with lower total grey matter volume. Associations of pro-inflammatory cytokines with lower brain volume could imply a link to mechanisms of HIV-associated brain damage, which may lead to neurocognitive impairment. Therefore, the use of highly sensitive neuroimaging and high-throughput immunoassays in HIV-associated brain disorders has potential applications in clinical assessments and therapeutic monitoring. Full article

Vitamin D deficiency (VDD) is a widespread human condition closely associated with musculoskeletal disorders, involving alterations in body composition and systemic inflammation. In this cross-sectional study, 1075 adults were classified into a VDD (n = 304) group and a VD sufficient (VDS) group (n = 771). Body composition measurements, including the fat mass-to-weight ratio (FM/WT), were assessed using bioelectrical impedance analysis. Plasma levels of IL-9, IL-34, and MCP-1 were also measured. Data on osteoporosis (OP) and knee osteoarthritis (KOA) were collected. Regression analyses indicated that FM/WT was independently associated with VDD, which in turn was linked to elevated IL-34 levels. Individuals with VDD had a significantly higher prevalence of OP and KOA compared with those with VDS. Structural equation modeling confirmed and quantified these associations, suggesting that FM/WT is a significant predictor of VDD status (β = 0.305, 95% CI: 0.231–0.367). VDD is directly associated with elevated IL-34 levels (β = 0.353, 95% CI: 0.308–0.398), while IL-34 levels, in turn, are a possible cause of KOA (β = 0.573, 95% CI: 0.460–0.687) and OP (β = 0.433, 95% CI: 0.329–0.536). Our data clearly demonstrate existence of a physiological-pathological continuum: obesity-VDD-IL-34 and both OP and KOA. Full article

Poland, as a leading apple producer in the EU, must maintain high fruit quality during prolonged storage and distribution, which is crucial for exports to distant markets. Therefore, it is essential to clearly identify which factors most strongly affect quality and the magnitude of their effects in order to make informed choices about pre- and postharvest practices, storage technology, and logistics. The objective of this study was to assess the effect of selected factors on the quality of apples of the ‘Gala Schniga^® SchniCo Red(s)’ cultivar after long-term storage. The study analyzed the effects of harvest date (optimal and delayed), three variants of 1-methylcyclopropene application (control-0 µL·L⁻¹ 1-MCP, Harvista™, SmartFresh™, and Harvista™ + SmartFresh™), storage period (5, 7, and 9 months), simulated trading period (0 or 7 days at 20 °C) and storage technology (ULO: 1.2% CO₂: 1.2% O₂; DCA: 0.6% CO₂: 0.6% O₂) in two consecutive seasons (2022/2023 and 2023/2024). Five quality parameters were evaluated: flesh firmness (F), soluble solid content (SSC), titratable acidity (TA), SSC/TA ratio, and the concentration of 1-aminocyclopropane-1-carboxylic acid (ACC). Backward-elimination stepwise regression and partial eta squared (η²) calculations were used to analyze the data to determine the factors with the greatest impact. The post-harvest application of 1-MCP had the strongest effect in terms of maintaining firmness (η² = 70.4%) and acidity (η² = 38.0%) and reducing ACC content (η² = 21.3%). Harvista™ preparation had a weaker or negligible effect on ACC content, but reduced SSC (η² = 22.7%). Harvest date, storage duration, and shelf life significantly influenced all traits, with controlled-atmosphere regime further modulating outcomes. By integrating preharvest maturity with treatment timing and CA storage, we disentangled the relative contributions of harvest timing, treatment, and storage. The results provide actionable inputs for a decision-support tool to help producers maintain target quality—firmness, SSC, TA, SSC/TA, and ACC—through optimized practice, storage technology choice, and logistics. Full article

Objectives: This study proposes a systematic strategy for optimizing sustained-release formulations using mixture experiments. Methods: Model variables were identified and screened via LASSO regression, Smoothly Clipped Absolute Deviation (SCAD), and Minimax Concave Penalty (MCP), leading to the construction of a quadratic inference function-based objective model. Using this model, three multi-objective optimization algorithms—NSGA-III, MOGWO, and NSWOA—were employed to generate a Pareto-optimal solution set. Solutions were further evaluated through the entropy weight method combined with TOPSIS to reduce subjective bias. Results: The MCP-screened model demonstrated strong fit (AIC = 19.8028, BIC = 45.2951) and suitability for optimization. Among the Pareto-optimal formulations, formulation 45, comprising HPMC K4M (38.42%), HPMC K100LV (13.51%), MgO (6.28%), lactose (17.07%), and anhydrous CaHPO₄ (7.52%), exhibited superior performance, achieving cumulative release rates of 22.75%, 64.98%, and 100.23% at 2, 8, and 24 h, respectively. Compared with the original formulation, drug release was significantly improved across all time points. Conclusions: This integrated workflow effectively accounted for component interactions and repeated measurements, providing a robust and scientifically grounded approach for optimizing multi-component sustained-release formulations. Full article

In this study, we apply machine learning to model the spatiotemporal dynamics of gene expression during early Drosophila embryogenesis. By optimizing model architecture, feature selection, and spatial grid resolution, we developed a predictive pipeline capable of accurately classifying active nuclei and forecasting their future distribution in time. We evaluated the model on two reporter constructs for the short gastrulation (sog) gene, sogD and sogD_∆Su(H), allowing us to assess its performance across distinct genetic contexts. The model achieved high accuracy on the wild-type sogD dataset, particularly along the dorsal–ventral (DV) axis during nuclear cycle 14 (NC14), and accurately predicted expression in the central regions of both wild-type and Suppressor of Hairless (Su(H)) mutant enhancers, sogD_∆Su(H). Bootstrap analysis confirmed that the model performed better in the central region than at the edges, where prediction accuracy dropped. Our previous work showed that Su(H) can act both as a repressor at the borders and as a stabilizer of transcriptional bursts in the center of the sog expression domain. This dual function is not unique to Su(H); other broadly expressed transcription factors also exhibit context-dependent regulatory roles, functioning as activators in some regions and repressors in others. These results highlight the importance of spatial context in transcriptional regulation and demonstrate the ability of machine learning to capture such nuanced behavior. Looking ahead, incorporating mechanistic features such as transcriptional bursting parameters into predictive models could enable simulations that forecast not just where genes are expressed but also how their dynamics unfold over time. This form of in silico enhancer mutagenesis would make it possible to predict the effects of specific binding site changes on both spatial expression patterns and underlying transcriptional activity, offering a powerful framework for studying cis-regulatory logic and modeling early developmental processes across diverse genetic backgrounds. Full article

The associations between sialylated anti-cyclic citrullinated peptide (anti-CCP) antibodies bearing α-2,6-sialic acid (SIA), ST6Gal1 and Neu1 enzymes, and clinical disease activity measures such as disease activity score 28 (DAS28), the Simplified Disease Activity Index (SDAI), and Clinical Disease Activity Index (CDAI) are unknown in rheumatoid arthritis (RA). To address this gap, this study included 97 patients with RA evaluated at baseline (month 0) and at 6 and 12 months. At each visit, blood cells were analyzed for B-cell ST6Gal1 and Neu1 expressions, and plasma samples were assessed for ST6Gal1 and Neu1 levels. The erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), monocyte chemotactic protein-1 (MCP-1), and IgG anti-CCP with its α-2,6-SIA modification were measured. Disease activity measures, namely DAS28-ESR, DAS28-CRP, DAS28-MCP-1, SDAI, and CDAI, were calculated. Correlations and Receiver Operating Characteristics among ST6Gal, Neu1, SIA/anti-CCP ratios, and disease activity measures were assessed. Multivariate regression analyses were performed to reveal confounding factors in such correlations. The total SIA content of anti-CCP antibodies was inversely correlated with B-cell Neu1 levels (ρ = −0.317 with p = 0.013. Plasma (free-form) Neu1 levels were inversely correlated with SIA/IgG anti-CCP ratios (ρ = −0.361, p = 0.001) in the DAS28-MCP-1 < 2.2 (remission) subgroup. No such correlation was observed for the DAS28-ESR, DAS28-CRP, SDAI, or CDAI subgroups. B-cell ST6Gal1 levels correlated inversely with SDAI ≤ 11 and DAS28-MCP-1 ≤ 3.6 combined remission and low-disease-activity subgroups (ρ = −0.315 with p = 0.001 and ρ = −0.237 with p = 0.008, respectively). The same was observed for B-cell ST6Gal1/Neu1 ratios correlating with the SDAI ≤ 11 subgroup (ρ = −0.261, p = 0.009). Nevertheless, B-cell ST6Gal1/Neu1 ratios against SDAI ≤ 11 and DAS28-MCP-1 ≤ 3.6 subgroups produced significant area-under-curve (AUC) values of 0.616 and 0.600, respectively (asymptotic p-Values 0.004 and 0.018, respectively). Through multivariate regression analyses, we found that biologics (a confounding factor) interfered with p-Values related to the B-cell ST6Gal1 enzyme but did not interfere with p-Values related to the pure B-cell Neu1 enzyme. In addition, disease duration interfered with p-Values related to the pure Neu1 enzyme on B-cells or in plasma. Moreover, plasma ST6Gal1/Neu1 ratios against the DAS28-MCP-1 < 2.2 remission subgroup produced an AUC of 0.628 and asymptotic p = 0.003. Therefore, it is suggested that B-cell ST6Gal1/Neu1 ratios can be used as clinical indicators for the combined remission and low-disease-activity subgroup of SDAI and DAS28-MCP-1 formulae. Plasma ST6Gal1/Neu1 ratios are also good indicators of DAS28-MCP-1 remission. Full article

Background and Objectives: This study aimed to explore the risk factors of histopathological crescent formation in pediatric IgA vasculitis nephritis (IgAVN). Materials and Methods: Enrolled patients with biopsy-proven IgAVN from Zhejiang University’s hospital were split into two groups: 377 with no crescents on histopathology (Group 1) and 364 with crescentic nephritis (Group 2). Collected data included clinical features, lab indicators, histopathological grading, and factors causing glomerular sclerosis. Logistic regression was used to assess factors affecting crescent formation in IgAVN. Double-immunofluorescence assay was used to detect TGF-β1, MCP-1, α-SMA, Collagen I, and FN1 in kidney biopsy specimens. The relationship between kidney fibrosis factors and histopathological grade were analyzed using Chi-square and Pearson tests. Results: A total of 741 patients with IgAVN were included in the study. Univariate logistic regression identified potential factors related to crescent formation, including age, gender, clinical classification, hematuria grade, 24 h urine protein level, peripheral white blood cells (WBCs), serum albumin, Cystatin-C, APTT, and PT. Multivariate analysis revealed statistical significance for age, 24 h urine protein, and WBCs across pathological grades (p < 0.05). Mantel–Haenszel Chi-square tests indicated a linear relationship between IgAVN pathological grade and α-SMA, TGF-β1, MCP-1, and FN1. Pearson correlation analysis confirmed a positive correlation between pathological grade and these markers. Conclusions: Age, 24 h urinary protein, and blood WBCs are identified as risk factors for histopathological crescent formation in children with IgAVN. Additionally, a higher pathological grade is associated with more pronounced fibrosis indicators. Full article

Introduction: Chronic kidney disease (CKD) increases cardiovascular risk through mechanisms such as oxidative stress and the accumulation of advanced glycation end products (AGEs). Glycated albumin (GA) is associated with cardiovascular risk in CKD patients, but its relationship with AGEs and systemic inflammation remains unclear. This study investigated these associations in old patients with severe CKD, with and without diabetes. Methods: We conducted a cross-sectional analysis in 122 patients aged ≥ 65 years with CKD stages G3a–G5, including 67 diabetics and 55 non-diabetics. Patients with confounding comorbidities were excluded. We measured GA, AGEs, various AGEs receptors (RAGE) isoforms, and inflammatory cytokines (CRP, IL-6, TNFα, and MCP-1) using standardized assays. Statistical analyses included group comparisons, correlation coefficients, and multivariate regression. Results: Of 122 patients (mean age 77.7 ± 11.3 years), diabetics had higher GA percentages than non-diabetics (22.0 ± 7.1% vs. 17.5 ± 5.4%, p = 0.0001), while AGEs (2931 ± 763 vs. 3156 ± 809 AU; p = 0.118) and inflammatory markers (CRP 0.240[0.380] vs. 0.200[0.280] mg/dL; p = 0.142; IL-6 3.4[4.0] vs. 3.0[3.8] pg/mL; p = 0.238) were similar between groups. Overall, GA was inversely correlated with estimated glomerular filtration rate (eGFR) (ρ = −0.189, p = 0.037) and positively with glycated hemoglobin (HbA1c) (ρ = 0.525, p < 0.0001), but showed no significant correlation with AGEs, RAGE isoforms, or inflammatory cytokines. In multivariate analysis, only HbA1c remained independently associated with GA (β = 0.222, p = 0.005). Conclusions: In old patients with severe CKD, GA appears to be a more useful marker of glycemic control than glycation stress, the latter of which is the result of multiple factors, including impaired kidney function and systemic inflammation. Full article

The assessment of milk coagulation properties (MCPs) is crucial for enhancing goat cheese production and quality. In this study, 501 bulk goat milk samples were collected from various farms to evaluate the MCPs. Traditionally, cheesemaking aptitude is evaluated using lactodynamographic analysis, a reliable but time-consuming laboratory method. Mid-infrared spectroscopy (MIRS) offers a promising alternative for the large-scale prediction of goat milk’s technological traits. Reference MCP measurements were paired with mid-infrared spectra, and prediction models were developed using partial least squares regression, with accuracy evaluated through cross- and external validation. The ability of MIRS to classify milk samples by coagulation aptitude was evaluated using partial least squares discriminant analysis. Only the model for rennet coagulation time obtained sufficient accuracy to be applied for screening (R²_CrV = 0.68; R²_Ext = 0.66; RPD = 2.05). Lower performance was observed for curd-firming time (R²_CrV = 0.33; R²_Ext = 0.27; RPD = 1.42) and curd firmness (R²_CrV = 0.55; R²_Ext = 0.43; RPD = 1.35). Classification of high coagulation aptitude achieved balanced accuracy values of 0.81 (calibration) and 0.74 (validation). With further model refinement and larger calibration datasets, MIRS may become a resource for the dairy-goat sector to monitor and improve milk suitability for cheesemaking. Full article

Background: Cytokines are effector molecules of the host immune response that have been associated with chronic inflammatory processes related to risk and a poor prognosis in cancer patients. However, the impact of these molecules on the genesis and prognosis of Neuroblastoma (NB) is uncertain. Objective: The aim of the study was to analyze serum concentrations of pro-inflammatory and anti-inflammatory cytokines in a cohort of pediatric patients with NB. Methods: We evaluated the serum levels of several cytokines with a pro-inflammatory profile (IL-8, MCP-1, IL-6, IL-1β, IFN-γ, TNF-α, IL-12 p40 and IL-12p70), and anti-inflammatory profile (IL-10 and TGF-β), in pediatric patients with NB using the ELISA method, compared to a healthy control group (non-oncology). Results: Serum levels of pro-inflammatory cytokines IL-6, TNF-α, INF-γ, IL-12, IL-8 and MCP1 were significantly elevated in patients with NB compared to healthy pediatric controls. Only the anti-inflammatory cytokine IL-10 showed high levels in patients with NB in relation to the control group, unlike the synthesis of TGF-β, which had no differences between both groups. Likewise, significant positive correlations were found between the circulating levels of IL-6 with TNF-α (r = 0.667; p ≤ 0.01), IL-6 with IL-8 (r = 0.641; p ≤ 0.01), IL-8 with TNF-α (r = 0.637; p ≤ 0.01) and IL-10 with INF-γ (r = 0.542; p ≤ 0.01) in patients with NB. The simple logistic regression analysis revealed a significant association between low serum concentrations of IL-6 and a lower risk of presenting an unfavorable tumor histology (p = 0.048); in addition, low levels of IL-12p40 (p = 0.007), IFN-γ (p = 0.006) and MCP-1 (p = 0.029) were found to be associated with a lower risk of presenting NB in disseminated stages of the disease (INSS 3 and 4). Additionally, a higher risk of death was found in patients with high levels of IL-6 (p = 0.022) and IL-8 (p = 0.04). Conclusions: Taken together, the results demonstrate that the serum levels of pro-inflammatory cytokines such as IL-6, IL-8, IFN-γ, and TNF-α could be considered serum immunological indicators with a potential prognostic role in the pathogenesis of NB. Full article