Search Results (58)

Background/Objectives: Romania remains a tuberculosis (TB) hotspot in the European Union, yet host-derived factors of poor outcomes are poorly characterised. We quantified circulating pro-inflammatory cytokines and examined their interplay with behavioural risk factors, the nutritional status, and the clinical course in adults hospitalised with pulmonary TB. We analysed 80 adults with microbiologically confirmed pulmonary TB and 40 respiratory symptom controls; four TB patients (5%) died during hospitalisation, all within 10 days of admission. Methods: A retrospective analytical case–control study was conducted at the Constanța regional TB referral centre (October 2020—October 2023). Patients with smear- or culture-confirmed TB were frequency-matched by sex, 10-year age band, and BMI class to culture-negative respiratory controls at a 2:1 ratio. The patients’ serum interferon-γ (IFN-γ), interleukin-1α (IL-1α), interleukin-1β (IL-1β), and tumour-necrosis-factor-α (TNF-α) were quantified within 24 h of admission; the neutrophil/lymphocyte ratio (NLR) was extracted from full blood counts. Independent predictors of in-hospital mortality were identified by multivariable logistic regression; factors associated with the length of stay (LOS) were modelled with quasi-Poisson regression. Results: The median TNF-α (24.1 pg mL⁻¹ vs. 16.2 pg mL⁻¹; p = 0.009) and IL-1β (5.34 pg mL⁻¹ vs. 3.67 pg mL⁻¹; p = 0.008) were significantly higher in the TB cases than in controls. TNF-α was strongly correlated with IL-1β (ρ = 0.80; p < 0.001), while NLR showed weak concordance with multiplex cytokine patterns. Among the patients with TB, four early deaths (5%) exhibited a tripling of TNF-α (71.4 pg mL⁻¹) and a doubling of NLR (7.8) compared with the survivors. Each 10 pg mL⁻¹ rise in TNF-α independently increased the odds of in-hospital death by 1.8-fold (95% CI 1.1–3.0; p = 0.02). The LOS (median 29 days) was unrelated to the smoking, alcohol, or comorbidity load, but varied across BMI strata: underweight, 27 days; normal weight, 30 days; overweight, 23 days (Kruskal–Wallis p = 0.03). In a multivariable analysis, under-nutrition (BMI < 18.5 kg m⁻²) prolonged the LOS by 19% (IRR 1.19; 95% CI 1.05–1.34; p = 0.004) independently of the disease severity. Conclusions: A hyper-TNF-α/IL-1β systemic signature correlates with early mortality in Romanian pulmonary TB, while under-nutrition is the dominant modifiable determinant of prolonged hospitalisation. Admission algorithms that pair rapid TNF-α testing with systematic nutritional assessment could enable targeted host-directed therapy trials and optimise bed utilisation in high-burden settings. Full article

Through the energy conversion of building skins, building-integrated photovoltaic (BIPV) technology, the core carrier of the smart city energy system, encourages the conversion of buildings into energy-generating units. However, the decommissioning of the module faces the challenge of physical dismantling and financial environmental damage because of the close coupling with the building itself. As the first tranche of BIPV projects will enter the end of their life cycle, it is urgent to establish a multi-dimensional collaborative recycling mechanism that meets the characteristics of building pv systems. Based on the theory of reverse logistics network, the research focuses on optimizing the reverse logistics network during the decommissioning stage of BIPV modules, and proposes a dual-objective optimization model that considers both cost and carbon emissions for BIPV. Meanwhile, the multi-level recycling network which covers “building points-regional transfer stations-specialized distribution centers” is designed in the research, the Pareto solution set is solved by the improved NSGA-II algorithm, a “1 + 1” du-al-core construction model of distribution center and transfer station is developed, so as to minimize the total cost and life cycle carbon footprint of the logistics network. At the same time, the research also reveals the driving effect of government reward and punishment policies on the collaborative behavior of enterprise recycling, and provides methodological support for the construction of a closed-loop supply chain of “PV-building-environment” symbiosis. The study concludes that in the process of constructing smart city energy system, the systematic control of resource circulation and environmental risks through the optimization of reverse logistics network can provide technical support for the sustainable development of smart city. Full article

Background: Acute ischemic stroke (AIS) remains a leading cause of mortality and disability worldwide. Accurate evaluation of collateral circulation is essential for predicting outcomes following endovascular thrombectomy (EVT). However, conventional visual collateral scoring (vCS) based on multiphase CT angiography (mCTA) is limited by subjectivity and inter-observer variability. This preliminary study introduces the multiphase quantitative collateral score (mqCS), a novel imaging biomarker designed to provide an objective and reproducible assessment of both the morphological extent and temporal dynamics of collateral flow. Methods: In this exploratory study, 54 AIS patients treated with EVT were retrospectively analyzed. Collateral status was evaluated using both vCS (graded by two blinded neuroradiologists) and mqCS, derived from mCTA-based fractal dimension (FD) and delay indicator (DI) metrics. Logistic regression and receiver operating characteristic (ROC) analyses were performed to assess the predictive value of each scoring system for favorable 90-day functional outcomes (modified Rankin scale, mRS ≤ 2). Results: The mqCS was significantly associated with favorable outcomes. Patients with mqCS ≥ 0.8674 had significantly higher odds of achieving favorable outcomes (adjusted OR = 5.98, 95% CI: 1.38–25.93, p = 0.017; AUC = 0.80). In comparison, the visual collateral score (vCS) showed a lower adjusted predictive value (adjusted OR = 2.84, 95% CI: 1.17–6.89, p = 0.02; AUC = 0.79). Patients in the highest mqCS quartiles (Q3–Q4) exhibited significantly better recovery rates (69%, p < 0.01). Conclusions: This proof-of-concept study suggests that mqCS provides a potentially more objective and robust alternative to visual scoring for collateral assessment in AIS. By integrating structural and temporal characteristics, mqCS enhances outcome prediction and may inform EVT decision-making, particularly in borderline cases. These preliminary findings warrant validation in larger, prospective cohorts and support its potential integration into automated imaging platforms. Full article

Muscle-invasive bladder cancer (MIBC) is a biologically aggressive disease with high recurrence rates, despite advances in surgical and systemic therapies. Circulating tumor DNA (ctDNA), a tumor-specific fraction of cell-free DNA, has emerged as a promising non-invasive biomarker for the real-time assessment of tumor burden, treatment response, and minimal residual disease (MRD). This review explores the biological basis, detection technologies, and clinical utility of ctDNA in MIBC, highlighting its role in preoperative risk stratification, postoperative surveillance, and personalized decision-making for adjuvant and systemic therapies. We critically examine current evidence from pivotal trials and ongoing studies that support ctDNA’s prognostic and predictive value. Additionally, we discuss emerging applications, including ctDNA-guided immunotherapy, integration with imaging and molecular data, and potential to inform bladder-sparing strategies. While ctDNA presents technical and logistical challenges, its incorporation into prospective clinical workflows promises to enhance precision oncology and improve outcomes in patients with MIBC. Full article

Background: Reliable biomarkers are urgently needed to aid in the differential diagnosis, prognosis, disease progression monitoring, and prediction of therapeutic response in patients with systemic sclerosis (SSc). This study aimed to evaluate a panel of potentially pathogenic circulating cytokines and chemokines in a cohort of SSc patients. Methods: Serum samples were obtained from 35 SSc patients and 40 age- and sex-matched healthy controls. Twenty-three cytokines/chemokines were quantified using a Luminex^® multiplex immunoassay (BioRad-BioPlex 200 System-Lumine x-Map technology R&D Systems, USA) following the manufacturer’s instructions and customized procedures. Data were acquired using Bioplex manager v 6.1. Data analysis was performed using GraphPad Prism v.8 (GraphPad Software, Inc.), with significance defined as p ≤ 0.05. V.8 Results: Levels of TNFRII and MMP-8 were significantly higher in SSc patients compared to healthy controls, while IL-1RII levels were significantly elevated in healthy individuals (p < 0.001 for all comparisons). Patients with elevated ESR at baseline (>30 mm/h) showed higher IL-15 levels (p = 0.019). A strong positive correlation was found between MCP-1 and the modified Rodnan skin score (mRSS) (p = 0.009, r = 0.740), and a moderate correlation between TNFRII and diffusing capacity for carbon monoxide (p = 0.046, r = 0.339). PLS regression identified MMP-8, MCP-1, TNFRII, IL-15, and IL-1RII as key predictors of SSc, with MMP-8 having the strongest influence. The logistic regression model showed high performance (AUC = 0.93, accuracy = 87.5%). Conclusions: TNFRII, MMP-8, and IL-1RII may play a pathogenic role in SSc. TNFRII, in particular, may serve as a biomarker for pulmonary involvement, aligning with its known role in pro-fibrotic pathways. These findings support their utility in diagnosis and disease profiling. Full article

Background: Intracranial atherosclerotic stenosis (ICAS) is a leading cause of ischemic stroke, particularly in the anterior circulation. Understanding the underlying stroke mechanisms is essential for guiding personalized treatment strategies. This study proposes an integrated framework that combines CT perfusion imaging, vascular anatomical features, computational fluid dynamics (CFD), and machine learning to classify stroke mechanisms based on the Chinese Ischemic Stroke Subclassification (CISS) system. Methods: A retrospective analysis was conducted on 118 patients with intracranial atherosclerotic stenosis. Key indicators were selected using one-way ANOVA with nested cross-validation and visualized through correlation heatmaps. Optimal thresholds were identified using decision trees. The classification performance of six machine learning models was evaluated using ROC and PR curves. Results: Time to Maximum (Tmax) > 4.0 s, wall shear stress ratio (WSSR), pressure ratio, and percent area stenosis were identified as the most predictive indicators. Thresholds such as Tmax > 4.0 s = 134.0 mL and WSSR = 86.51 effectively distinguished stroke subtypes. The Logistic Regression model demonstrated the best performance (AUC = 0.91, AP = 0.85), followed by Naive Bayes models. Conclusions: This multimodal approach effectively differentiates stroke mechanisms in anterior circulation ICAS and holds promise for supporting more precise diagnosis and personalized treatment in clinical practice. Full article

Ports are the main arteries of global trade, handling goods circulation and serving as hubs for information, capital, and technology. Integrating digital technology has become the key for green port development to achieve resource efficiency and ecological balance. The current literature overlooks how digital technology can facilitate greener port operations. This study integrates sustainable supply chain management and system dynamics theories based on an in-depth analysis of existing research results and expert interviews. The analysis focuses on three key dimensions: integrating digital technologies with infrastructure, optimizing digital management and operations, and improving environmental and safety management in a digitally driven setting. Using the fuzzy Decision Making Trial and Evaluation Laboratory (Fuzzy Dematel) methodology, we collaborated with domain experts in port logistics to identify and confirm 12 pivotal factors that support the green digital transformation of ports. The research shows that the most critical success factors for using digital technology to drive ports’ green transformation are green supply chain information platforms, intelligent vessel scheduling, traffic optimization, and digital carbon emission monitoring. This study significantly contributes to the literature on green port transformation, offering indispensable practical insights for port operators, government entities, and shipping firms in identifying and deploying these key success factors. The findings will help maritime supply chain stakeholders develop actionable digital strategies, improving port efficiency and ecological resilience. Full article

Background: Stroke is one of the leading causes of death and disability worldwide. The diagnosis of stroke remains largely clinical, yet widely used stroke scoring systems and brain imaging do not satisfactorily allow the distinction of ischaemic stroke (IS) patients from stroke mimics (SMs). Blood biomarkers are promising tools that could facilitate clinical triage. Methods: This study recruited 66 patients with IS and 24 SMs. The levels of Glial fibrillary acidic protein (GFAP), Neuron-specific enolase (NSE), Neurofilament light chain (NfL) and blood-brain barrier (BBB) proteins [Occludin (OCLN), Zonula occludens 1 (ZO-1), Claudin-5] in blood serum were measured by enzyme-linked immunosorbent assay technique. Biomarker levels in IS patients and SMs were compared using the Mann–Whitney U test. Multivariable logistic regression analysis was used to evaluate the diagnostic performance of biomarkers in combination with the National Institutes of Health Stroke Scale (NIHSS) score. Results: More significant differences in circulating GFAP, NfL, OCLN, ZO-1, and Claudin-5 but not NSE were found in IS patients compared to SMs. A combination of circulating ZO-1, Claudin-5, and OCLN with NIHSS score gives the highest diagnostic accuracy, sensitivity, and specificity. Conclusions: A prediction model with circulating BBB proteins in combination with NIHSS score differentiates between IS patients and SMs. Full article

Healthcare is a huge business sector in many countries, focusing on the social function of delivering quality health when people develop illness. The system is essentially financed by public funds based on the solidarity principle. With a large financial outlay, the sector must use economic evaluation methods to achieve better efficiency. The objective of our study was to evaluate and to understand how health economics is used today, taking Belgium as an example of a high-income country. The evaluation started with a historical view of healthcare development and ended with potential projections for its future. A literature review focused on country-specific evaluation reports to identify the health economic methods used, with a search for potential gaps. The first results indicated that Belgium in 2021 devoted 11% of its GDP, 17% of its total tax revenue, and 30% of the national Social Security Fund to health-related activities, totalizing EUR 55.5 billion spending. The main health economic method used was a cost-effectiveness analysis linked to budget impact, assigning reimbursable monetary values to new products becoming available. However, these evaluation methods only impacted at most 20% of the money circulating in healthcare. The remaining 80% was subject to financial regulations (70%) and budgeting (10%), which could use many other techniques of an economic analysis. The evaluation indicated two potentially important changes in health economic use in Belgium. One was an increased focus on budgeting with plans, time frames, and quantified treatment objectives on specific disease problems. Economic models with simulations are very supportive in those settings. The other was the application of constrained optimization methods, which may become the new standard of practice when switching from fee-for-service to pay-per-performance as promoted by value-based healthcare and value-based health management. This economic refocusing to a more constrained approach may help to keep the healthcare system sustainable and affordable in the face of the many future challenges including ageing, climate change, migration, pandemics, logistical limitations, and financial instability. Full article

Depressive disorders are highly prevalent among subjects suffering from chronic kidney disease (CKD). The aim of the present study is to evaluate clinical and biochemical factors associated with depressive disorders in a sample of older CKD patients, with a focus on advanced glycation end products (AGEs) and their soluble receptors (sRAGEs). A total of 115 older subjects affected by CKD (stages 3 to 5, not in dialysis) were selected for this study. These patients were divided into two groups according to the presence of depressive disorders defined by a score ≥ 10 on the 30-item Geriatric Depression Scale (GDS). The two groups were compared by independent sample t tests for continuous variables and χ² tests for qualitative ones. Significant variables at univariate analyses were then inserted as predictors of a binary logistic regression model, with the presence or absence of depressive disorders as a dependent variable. The binary logistic regression model showed that patients with concomitant depressive disorders were more frequently of female gender (p < 0.01) and had lower MCP1 (p < 0.01) and AGE circulating levels (p < 0.01) than their counterparts. Depressive disorders in older CKD patients are more prevalent in women and seem to be inversely associated with systemic inflammation and circulating AGEs. Full article

The circulation industry, centered on the flow of commodities and supported by logistics, information, and capital flows, serves as a vital link between production and consumption, playing a pivotal role in enhancing production efficiency and facilitating economic transformation and upgrading. Through the spatial aggregation and interconnection of industries such as wholesale and retail, logistics, and catering, the circulation industry forms an economic system characterized by spatial cohesion and resource sharing, thereby significantly impacting carbon emissions through improved production efficiency. This study integrates both the “production side” and “consumption side” into an analytical framework examining the relationship between the circulation industry and carbon emissions. It looks into the mechanisms underlying the industry’s influence on carbon reduction and empirically tests these mechanisms using systematic estimation methods based on data from 30 Chinese provinces spanning 2011 to 2020. The results reveal a pronounced carbon reduction effect within the circulation industry, which intensifies across quantiles, exhibiting regional disparities with stronger effects in central regions compared to eastern regions and insignificant effects in western regions. On the production side, the circulation industry significantly reduces carbon emissions through scale, technology, and structural effects. Conversely, on the consumption side, while the upgrading of rural residents’ consumption structure exhibits a carbon emission suppression effect, the same upgrade among urban residents leads to an enhancement of carbon emissions. The primary contribution of this study lies in constructing an analytical framework that explores the nexus between the circulation industry and carbon emissions. It empirically validates the mechanisms through which the industry impacts carbon emissions at both the production and consumption ends, uncovering regional heterogeneities in carbon reduction efforts. This work provides novel theoretical insights and empirical evidence that can inform global carbon reduction strategies. Full article

Background: Risk factors for severe dengue manifestations have been attributed to various factors, including specific serotypes, sex, and age. Mexico has seen the re-emergence of DENV-3, which has not circulated in a decade. Objective: To describe dengue serotypes by age, sex, and their association with disease severity in dengue-positive serum samples from epidemiological surveillance system units. Materials and Methods: A descriptive analysis was conducted to evaluate the frequency of dengue severity by sex, age, disease quarter, geographical location, and dengue virus serotypes. The study was conducted using laboratory samples from confirmed dengue cases through RT-qPCR from the epidemiological surveillance laboratory network of the Mexican Social Security Institute, Mexico. Simple frequencies and proportions were calculated using the z-test for proportional differences between groups. Bivariate analysis with adjusted Chi2 was performed, and binary logistic regression models were constructed using the forward Wald method considering the model’s predictive capacity. The measure of association was the odds ratio, with 95% confidence intervals. Statistical significance was set to an alpha level of <0.05. Results: In 2023, 10,441 samples were processed for dengue RT-qPCR at the IMSS, with a predominance of serotype DENV-3 (64.4%). The samples were mostly from women (52.0%) and outpatient cases (63.3%). The distribution of dengue severity showed significant variations by age, with a lower proportion of severe cases in young children and a higher proportion in the 5- to 14-year-old group. Hospitalizations increased significantly with severity. Warm regions had more cases overall and severity. Cases were most frequent from July to September. While DENV-2 was associated with severity, DENV-4 was not. Binary regression identified higher risk in women, age extremes, and DENV-2, with an overall predictive model of 58.5%. Conclusions: Women, age groups at the extremes of life, and the DENV-2 serotype presented severe risk of dengue in a population with social security in Mexico during 2023. Full article

Background and Objectives: MicroRNAs are short noncoding RNAs that play an essential role in controlling gene expression at the posttranscriptional level. They can serve as biomarkers in the management of obesity. Circulating miRNAs levels change with exercise, impacting various physiological and biological systems, including structural and functional changes. Aim: The purpose of this study is to evaluate the levels of miRNAs 423-5p and 128-1 in young adolescents with obesity before and after an aerobic exercise programme. We also analyse the relationship between those microRNAs and obesity-related parameters in response to aerobic exercise training. Materials and Methods: A total of 64 adolescent individuals (32 individuals with obesity and 32 healthy individuals) were enrolled in the study to participate in a 6-month aerobic exercise programme. Anthropometric measurements, biochemical parameters and blood samples were collected from all the participants prior to exercise training and after the 6-month programme. Gene expression analysis of the study participants was performed using quantitative real-time PCR. Results: Expression levels of circulating microRNAs 423-5p (p < 0.01) and 128-1 (p < 0.01) differed significantly before and after exercise in the study population. Circulating miRNA 423-5p increased and correlated significantly with BMI while circulating miRNA 128-1 decreased and also significantly correlated with BMI after the 6-month aerobic exercise programme. Logistic regression analysis shows that the elevation in miRNAs expression levels has a strong significant association with the increased levels of the cytokines IL-6 and TNF-α (p < 0.05). Conclusions: Obesity leads to alterations in the expressions of miRNA 423-5p and miRNA 128-1. The significant changes observed after an aerobic exercise programme demonstrate the potential of these miRNAs as diagnostic and prognostic biomarkers for obesity. Full article

More than 13.5 billion COVID-19 vaccine doses were delivered between 2021 and 2023 through a mix of delivery platforms, with mass vaccination campaigns being the main approach. In 2022, with the continued circulation of SARS-CoV2 and the need for periodic boosters being most likely, countries were required to plan for more sustainable approaches to provide COVID-19 vaccinations. In this context of uncertainty, a global tool for integrating COVID-19 vaccines into immunization programs and as part of broader health systems was published jointly by the WHO and UNICEF to respond to country needs. This paper summarizes the approach to, and lessons learned during, the development of a global guidance document and describes some examples of its early use in low- and middle-income countries (LMICs). The guidance leveraged existing health system frameworks, proposed four steps for planning and implementing the COVID-19 vaccination integration journey, and identified investment areas. The development process maximized robust global stakeholder and country engagement, and the timeframe was aligned with donor funding windows to support countries with the integration of COVID-19 vaccination. The rapid dissemination of the guidance document allowed countries to ascertain their readiness for integrating COVID-19 vaccination and inform the development of national plans and funding applications. While progress has been made in specific areas (e.g., optimizing cold chain and logistics leveraging COVID-19 vaccination), in the context of decreasing demand for COVID-19 vaccines, reaching adult COVID-19 vaccine high-priority-use groups and engaging and coordinating with other health programs (beyond immunization) remain challenges, particularly in LMICs. We share the learning that despite the uncertainties of a pandemic, guidance documents can be developed and used within a short timeframe. Working in partnership with stakeholders within and beyond immunization towards a common objective is powerful and can allow progress to be made in terms of integrating health services and better preparing for future pandemics. Full article

Identifying the optimal cabin layout is an important way to improve the efficiency of ship systems and ensure the efficient circulation of personnel and materials. The ship task state refers to the state maintained by the joint actions of ship machinery and equipment, cargo, and personnel when facing different jobs and tasks during operation. A cabin layout that facilitates multitasking states can improve the efficiency of collaboration between systems and ensure the operation of the ship. The demand for human flow and logistics is different in multitasking states. To express the demand in mathematical form, there is a certain random uncertainty in the numerical quantification of the demand. Thus, to better meet the needs of different states, the coefficient values of each state can be integrated using special methods. Ensuring values’ initial preference to the greatest extent inevitably produces a degree of cognitive uncertainty. Therefore, uncertainty analysis is necessary for cabin layout design to be used for multitasking states. In this paper, a deterministic optimization platform of cabin layout in multitasking states is obtained. Adjacent and circulating strength coefficients are obtained through numerical quantization of the demand for human flow and logistics. The random uncertainty in the input values of two coefficients was represented by random variables, and the cognitive uncertainty was represented by interval variables. In order to solve the problem of two types of variables, a random-interval hybrid uncertainty model was established. Through random intervalization and interval randomization, three cases, of random variables, interval variables, and random variables and interval variables, were studied. The probability distribution of the model function was used to evaluate the influence of different compositions of uncertainty parameters on the robustness of the cabin layout scheme. The necessity and effectiveness of uncertainty analysis in multitasking cabin layout are discussed below. Full article