Tag: statistics

Biodegradation. 2025 Dec 20;37(1):16. doi: 10.1007/s10532-025-10235-0.

ABSTRACT

Used engine oil is considered a major environmental concern due to difficulty in disposal or reuse. Using enrichment method, nine bacterial strains were isolated from the oil contaminated sites in Abbottabad. The NMD strain was considered the best biosurfactant producing strain, having the highest emulsification index and cell hydrophobicity up to 72% and 67% respectively. Based on morphology and 16S rRNA sequence analysis, the isolate was identified as Enterobacter hormaechei strain NMD. The effect of various factors which may influence the biodegradation rate including pH, incubation temperature and oil concentration were evaluated by response surface methodology with Box-Behnken design. The analysis of variance (ANOVA) indicated that regression coefficient (R²) is 0.99 with P-value 0.0325 with best fitted second-order quadratic regression model for used engine oil degradation. The F value of model is 338.13 with P-value < 0.0001 showed that the applied model is statistically significant and the optimal parameters i.e., temperature, pH and inoculum size, were observed to have significant effect on engine oil degradation efficiency. The optimum parameters temperature, pH and engine oil concentration were found to be 32.5℃, 6.5, and 4% (v/v) respectively. Under the optimized conditions, the degradation efficiency of used engine oil is observed 80%, which closely matched with the predicted values. The Monod kinetic equation is used to determine the growth rate of isolated strain utilizing used engine oil as sole carbon source with the highest rate of μmax (h-1) = 0.112, with Ks 9.5, and μmax/ Ks is 0.011 mg/L/h. The engine oil degradation was confirmed by GC/MS analysis, and its metabolites were also identified providing comprehensive insights into the breakdown products and degradation efficiency. This is the first report on the growth kinetics of these biosurfactants NMD on used engine oil, with these parameters helping to assess the isolated bacterial strain’s capability to degrade the pollutant effectively and guiding the development of more efficient bioremediation strategies. The future study should elucidate detail metabolomic study, optimization study at larger scale bioremediation process and enhancement of bacterial degradation efficiency through immobilization and use of consortium approaches.

PMID:41420715 | DOI:10.1007/s10532-025-10235-0

Eur Radiol. 2025 Dec 20. doi: 10.1007/s00330-025-12184-x. Online ahead of print.

ABSTRACT

OBJECTIVES: Transcatheter aortic valve implantation (TAVI) is crucial for treating calcified aortic stenosis (CAS), yet post-procedural outcomes remain variable. The CAPRI score previously showed promising results in predicting 1-year all-cause mortality, by combining manually measured thoracic aortic calcium (TAC) volume with clinical risk factors. This study introduces an enhanced CAPRI score (eCAPRI), which automates TAC volume measurement and incorporates additional automatically extracted biomarkers from pre-operative CT scans.

MATERIALS AND METHODS: TAC volume extraction was automated using a deep learning model trained on 66 patients and evaluated on 1111 CT scans. Additional automatically extracted imaging biomarkers were incorporated into the eCAPRI score, following the original methodology for biomarker selection. The eCAPRI score was trained on 765 pre-TAVI CT scans for one-year mortality prediction and then compared to CAPRI and EuroSCORE Logistic using AUC, bootstrap tests, and calibration curves on 192 CT scans.

RESULTS: Automated TAC segmentation achieved a mean Dice score of 0.777 ± 0.108. The eCAPRI score included body surface area (BSA)-indexed right ventricle volume, BSA-indexed pulmonary arteries max diameter, and abdominal muscles surface at L3 level in addition to automatically computed TAC volume and clinical biomarkers previously identified in the CAPRI score. On the evaluation dataset, eCAPRI showed an AUC of 0.731, outperforming CAPRI (AUC = 0.669) and EuroSCORE Logistic (AUC = 0.588) significantly (p = 0.034), with better calibration.

CONCLUSION: The eCAPRI score, combining fully automated TAC volume extraction and additional imaging biomarkers, improved one-year mortality prediction over CAPRI and EuroSCORE Logistic. It may support standardized risk stratification in TAVI patients.

KEY POINTS: Question Can an eCAPRI using imaging biomarkers from pre-operative CT scans improve the prediction of one-year mortality in patients undergoing transcatheter aortic valve replacement? Findings The eCAPRI score, integrating automated TAC volume and additional biomarkers, outperformed CAPRI and EuroSCORE Logistic in predicting one-year mortality (AUC = 0.731, p = 0.034). Clinical relevance The eCAPRI score provides a standardized approach to mortality risk assessment in transcatheter valve procedures. By improving prediction accuracy, it supports more informed clinical decisions and personalized care planning, ultimately contributing to better outcomes for patients undergoing TAVI.

PMID:41420708 | DOI:10.1007/s00330-025-12184-x

Eur Radiol. 2025 Dec 20. doi: 10.1007/s00330-025-12225-5. Online ahead of print.

ABSTRACT

OBJECTIVES: To evaluate the diagnostic utility of T1ρ mapping for assessing hepatic fibrosis in patients with chronic liver disease (CLD), including steatotic liver disease (SLD).

MATERIALS AND METHODS: In this prospective study (September 2024 to May 2025), consecutive patients with CLD underwent liver MRI, including MR-elastography, PDFF, T1, extracellular volume fraction (ECV), and T1ρ mapping. MRE-based liver stiffness was used as the reference to assess the diagnostic performance of the MRI-derived mapping parameters. MR-elastography-based liver stiffness thresholds for significant fibrosis (≥ F2) were set at > 3.66 kPa for participants without hepatic steatosis (PDFF ≤ 5%), and > 3.14 kPa for participants with hepatic steatosis (PDFF > 5%). The t-test, Spearman’s correlation, and the ROC analysis were applied.

RESULTS: One hundred twelve CLD participants were included (mean age, 48 ± 16 years; 53 participants with hepatic steatosis). All assessed quantitative mapping parameters were significantly increased in participants with significant fibrosis than in those without (e.g., T1ρ: 110 ± 15 vs 92 ± 6 ms, p < 0.001). T1ρ revealed a moderate to strong correlation with MR-elastography-based stiffness, superior to T1 and ECV (entire cohort: r = 0.75 [T1ρ] vs 0.49 [native T1] vs 0.68 [ECV]; participants with hepatic steatosis: r = 0.67 [T1ρ] vs 0.32 [native T1] vs 0.62 [ECV]; p < 0.05 in each case, respectively). T1ρ provided the highest diagnostic performance for diagnosing significant fibrosis (in the entire cohort: AUC 0.90 [T1ρ] vs 0.73, p < 0.001 [native T1], vs 0.81, p = 0.05 [ECV]; in participants with hepatic steatosis: AUC 0.87 [T1ρ] vs 0.67, p = 0.03 [native T1], vs 0.79, p = 0.047 [ECV], p values are given vs T1ρ).

CONCLUSION: Hepatic T1ρ might be a more accurate marker of hepatic fibrosis in CLD, including SLD, compared to hepatic native T1 and ECV mapping.

KEY POINTS: Question Accurate non-invasive assessment of hepatic fibrosis remains challenging, particularly in the presence of steatosis, where MRI biomarkers such as native T1 and ECV fraction are limited. Findings T1ρ mapping outperformed native T1 and ECV for identifying significant fibrosis and maintained robust accuracy in the presence of hepatic steatosis. Clinical relevance T1ρ mapping offers a robust, non-invasive MRI biomarker for assessing hepatic fibrosis across the full spectrum of CLD, including SLD, with superior accuracy to native T1 and ECV and reduced influence from hepatic fat infiltration.

PMID:41420707 | DOI:10.1007/s00330-025-12225-5

Eur Radiol. 2025 Dec 20. doi: 10.1007/s00330-025-12179-8. Online ahead of print.

ABSTRACT

OBJECTIVES: Accurate localization of deep brain stimulation (DBS) electrodes is critical for effective therapy. Conventional CT is widely used postoperatively but fails to delineate individual electrode contacts due to metallic artifacts. This study aimed to evaluate extended Hounsfield unit (EHU) CT – using an expanded scale up to 40,000 HU- for accurate localization of individual DBS electrode contacts.

MATERIALS AND METHODS: This retrospective study included 29 patients (58 DBS electrodes) who underwent DBS implantation. Postoperative imaging comprised both conventional CT and EHU-CT reconstructions. Two independent raters localized electrode contacts using a standardized protocol. Inter-method and inter-rater agreement were quantified using intraclass correlation coefficients (ICCs) and Euclidean distances. Qualitative assessments of contact visibility were also performed.

RESULTS: Quantitative analysis showed near-perfect agreement between EHU-CT and conventional CT (ICC ≈ 1), with high inter-rater consistency. However, qualitative evaluation revealed superior contact visualization with EHU-CT: all contacts were clearly identifiable in 100% of cases, while conventional CT consistently failed to distinguish individual contacts due to blooming artifacts. Conventional CT localizations were also sensitive to window-level adjustments, particularly along the z-axis.

CONCLUSION: EHU-CT enables consistent and direct visualization of individual DBS contacts and provides a robust alternative to conventional CT. Its reduced sensitivity to display settings and improved interpretability may enhance intra-operative decision-making and postoperative programming, supporting more reliable DBS workflows.

KEY POINTS: Question Accurate deep brain stimulation (DBS) electrode localization is crucial for optimal intra-operative adjustments and outcomes, yet conventional CT is hindered by metallic artifacts limiting individual contact visualization. Findings Extended Hounsfield unit (EHU)-CT and conventional CT showed near-perfect agreement in electrode localization, but EHU-CT provided clearly superior visualization of individual electrode contacts. Clinical relevance By enabling direct visualization of individual contacts through an extended Hounsfield scale, EHU-CT can improve intra-operative decision-making and postoperative programming, potentially enhancing DBS localization accuracy and patient outcomes.

PMID:41420706 | DOI:10.1007/s00330-025-12179-8

Eur Radiol. 2025 Dec 20. doi: 10.1007/s00330-025-12231-7. Online ahead of print.

ABSTRACT

Radiomics is increasingly explored as a tool for improving diagnosis, prognosis, and treatment planning. However, concerns exist about the reproducibility and methodological rigor of its studies. The integration of high-dimensional radiomic features and machine learning makes the field prone to unintentional errors that may warrant retraction. Despite a rising number of retractions in science overall, no dedicated study has examined retractions specifically within radiomics. Therefore, this study aimed to review retracted radiomics publications and identify the characteristics and reasons for their retraction. We systematically searched six databases (Crossref, Retraction Watch Database, OpenAlex, PubMed, Scopus, Web of Science) and identified 93 retracted radiomics publications, of which 20 were included. These articles were analyzed with respect to publisher, country of origin, dates, citation counts, and reasons for retraction. Retraction rates were then estimated and compared with those in general radiology. Our findings indicate that a disproportionate number of retractions are linked to specific publishers and countries (particularly China and India), with overall low citation counts (median 4.0 citations). Retractions peaked sharply in 2023, followed by a strong decline. Many retraction notes lack a clear explanation for the retraction. Estimated retraction rates in radiomics were lower than in general radiology (6.7 vs 7.4 per 10,000 publications). Notably, no major radiological or oncological journal appears to have retracted a radiomics publication. Given that radiomics demands higher, interdisciplinary expertise, this suggests a gap, implying that flawed research may yet have to be retracted. KEY POINTS: Question Considering the technical complexity of radiomics studies and their susceptibility to unintentional errors, how do their retraction rates compare to those in general radiology? Findings Retractions in radiomics were disproportionately linked to specific publishers and countries; however, no retractions appeared in major journals. Estimated retraction rates were lower than those for general radiology publications. Clinical relevance A potential gap in the number of retracted radiomics studies was identified, implying that flawed research in the field may not yet have been addressed.

PMID:41420705 | DOI:10.1007/s00330-025-12231-7

Acta Neurochir (Wien). 2025 Dec 20. doi: 10.1007/s00701-025-06737-8. Online ahead of print.

ABSTRACT

PURPOSE: to comprehensively and hierarchically assess risk factors for recurrence requiring reoperation (RrR) in chronic subdural hematoma (cSDH) in the era of middle meningeal artery embolization (MMAE).

METHODS: Patients treated for a cSDH from January 2019 to October 2024 at Fondazione Gemelli research hospital were considered for inclusion. Clinical, coagulation, radiological, and treatment factors were recorded. MMAE was performed systematically from October 2022, using polyvinyl alcohol (PVA) particles injected directly from the main trunk of MMA. The dataset comprised 45 quantitative and qualitative variables for each cSDH. Variables showing statistical significance (p-value < 0.05) were selected as covariates in two supervised learning frameworks to predict the RrR (outcome, Y): (i) Classification and Regression Tree (CART) and (ii) Random Forest (RF) classifier.

RESULTS: 500 patients were eligible and 233 were included, resulting in 283 treated cSDHs (mean follow-up: 119 days); 129 underwent adjuvant MMAE. 50 cSDH had a RrR (mean time to recurrence: 47 days), of which 41 (82%) in the non-embolized group and 9 (18%) in the embolized group (p-value < 0.001). Adjuvant embolization was the strongest factor associated with RrR, significantly reducing the risk for reintervention. Markwalder grading scale, preoperative cSDH volume, and platelet count (PLT) are strong predictors in non-embolized patients. A critical PLT cut-off of 229 × 10⁹/L strongly impacts RrR risk for substantial cSDH volumes.

CONCLUSIONS: The present results support the routine use of MMAE and the correction of PLT in relation to cSDH volume.

PMID:41420704 | DOI:10.1007/s00701-025-06737-8

Aging Clin Exp Res. 2025 Dec 20. doi: 10.1007/s40520-025-03294-z. Online ahead of print.

ABSTRACT

BACKGROUND: Life-space mobility (LSM) is a critical health indicator in older adults, the mechanisms underlying the relationship between subjective cognitive decline (SCD) and LSM remain unclear.

AIMS: This study examined depression as a mediator between SCD and LSM, and assessed whether perceived social support (PSS) moderates the relationship between SCD and depression among Chinese community-dwelling older adults.

METHODS: We seek to elucidate psychosocial mechanisms of the SCD-LSM link and inform targeted intervention strategies. Drawing on a face-to-face interview sample of 287 community-dwelling aged, this cross-sectional study utilised a moderated mediation analysis. Key constructs were evaluated by the Subjective Cognitive Decline Questionnaire-9, 15-item geriatric depression scale, Perceived Social Support Scale, the Life Space Assessment, respectively.

RESULTS: The results showed that SCD was negatively associated with LSM (β = -0.213, p < 0.001). Mediation analysis indicated an indirect association between SCD and LSM through depression (indirect effect = -1.868, 95% CI [-2.825, -1.029]), accounting for 41.6% of the total association. Furthermore, PSS was identified as a significant moderator in the relationship between SCD and depression (β = -0.088, p < 0.05), with a stronger association observed among older adults with lower PSS levels. The interaction term contributed a unique incremental variance of ΔR² = 0.0086 to the model.

DISCUSSION: Establishing a social support system holds promise for improving life-space mobility and alleviating depression among community-dwelling older adults with subjective cognitive decline, thereby enhancing their well-being.

CONCLUSION: A negative association between SCD and LSM was observed, with depression partially mediating this relationship. Importantly, PSS demonstrated a statistically significant moderating effect on the relationship between SCD and depression, although the effect size was small.

PMID:41420691 | DOI:10.1007/s40520-025-03294-z

J Racial Ethn Health Disparities. 2025 Dec 20. doi: 10.1007/s40615-025-02773-3. Online ahead of print.

ABSTRACT

The scientific literature continues to recognize the changing health status of migrants residing in geographic destinations outside their homeland. However, very little research has compared the health of Caribbean residents within their homeland with those across various diasporic destinations. This five-country study examined the physical and mental health of Caribbeans within the region and those in host countries, and whether the length of time in host countries is associated with declining health. We analyzed population-based data collected in Jamaica (2005), Guyana (2005), Canada (2000/2001, 2003, and 2005), the United States (2001-2003), and England (1998-2000). Parallel descriptive statistics and multivariate logistic regression were used to assess the health status of first-generation Caribbeans. The study revealed that Caribbean people within the region generally maintained a higher degree of health advantage compared to Caribbean migrants in North America and England. Length of time was associated with physical and mental health problems within certain host countries. Sociodemographic factors contribute to health. The findings suggest that first-generation Caribbeans might initially lose certain health benefits in host countries, although we find trends for improved cardiovascular health over time in Canada. Further exploration of other influences on health among Caribbeans across the diaspora is needed.

PMID:41420681 | DOI:10.1007/s40615-025-02773-3

Environ Monit Assess. 2025 Dec 20;198(1):59. doi: 10.1007/s10661-025-14927-1.

ABSTRACT

Research on the segmentation and analysis of forest canopy gaps (CGs) is important for understanding forest dynamics, biodiversity, and ecosystem resilience. In this study, seasonal changes in CGs over a five-year period were analyzed using unmanned aerial vehicle (UAV) RGB imagery, satellite multispectral imagery, Synthetic Aperture Radar (SAR), and Light Detection and Ranging (LiDAR) data. The aerial LiDAR achieved the highest segmentation accuracy (87%) for smaller gaps, followed by UAV RGB imagery (84%) and satellite-based observations (70%). Statistical models, including the Weibull Distribution and the Markov Chain, were used for spatial and temporal modeling of CGs. Gap size distribution over the five years showed that smaller CGs (< 100 m²) were more common in the early years, while larger gaps increased in later years, particularly in spring and autumn. This research supports CG segmentation and analysis by combining multi-source data and statistical modeling. Providing a flexible solution for monitoring forest ecosystems and promoting sustainable management practices.

PMID:41420677 | DOI:10.1007/s10661-025-14927-1

Biogerontology. 2025 Dec 20;27(1):25. doi: 10.1007/s10522-025-10372-2.

ABSTRACT

BACKGROUND: Epigenetic age acceleration (EAA) is a biomarker of biological aging associated with multiple diseases. Plasma metabolites are potential targets for disease prevention. Therefore, our study aims to investigate the association between plasma metabolites and EAA.

METHODS: Statistics of plasma metabolites and EAA were obtained from the GWAS database. After rigorously screening the instrumental variables, we applied five Mendelian randomization methods to evaluate the relationship between each metabolite and the EAA. The robustness of the results was verified by a series of sensitivity analyses, and metabolic pathway enrichment analysis was performed for significantly associated metabolites.

RESULTS: Our analysis identified 149 plasma metabolites associated with EAA (p < 0.05), including 46 metabolites associated with IEAA, 47 with HannumAge, 38 with GrimAge, and 41 with PhenoAge. Among these, palmitoylcarnitine levels remained correlated with EAA after multiple testing correction (P_FDR < 0.05). In the enrichment analysis, 13 metabolic pathways were associated with EAA. Among them, “cysteine and methionine metabolism” was identified as the most significantly enriched pathway (P_FDR < 0.1), and 3 metabolites in this pathway were correlated with EAA.

CONCLUSION: These results demonstrated that plasma metabolomics, particularly amino acid and lipid metabolism, were associated with EAA and aging. The “cysteine and methionine metabolism” pathway emerged as a potential mechanism of aging, and may underpin metabolic alterations during the aging process, and its metabolites, such as methionine, 5-methylthioadenosine, and α-ketobutyrate, may serve as intervention targets.

PMID:41420675 | DOI:10.1007/s10522-025-10372-2