Category: Statistics

Sci Rep. 2025 Feb 17;15(1):5769. doi: 10.1038/s41598-025-86648-x.

ABSTRACT

The presence of microorganisms in the bloodstream can result in severe, potentially life-threatening conditions, which are a significant cause of morbidity and mortality worldwide. The rise of antimicrobial-resistant strains further exacerbates these outcomes. However, the data concerning bacterial profiles and resistance to antimicrobials, particularly against extended-spectrum beta-lactams and carbapenems, are limited. Aimed to characterize pathogens isolated from positive blood cultures, including bacterial profiles and antibiotic susceptibility patterns, and to identify predictors of blood culture positivity in septicemia-suspected patients at the University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia. A hospital-based cross-sectional study was conducted from February 15 to May 30, 2023. The study involved 341 patients suspected of having septicaemia who were selected consecutively through a convenience sampling technique. Blood samples were collected aseptically from each patient (10 ml from adults, 5 ml from children, and 1 ml from neonates) and inoculated into bottles containing tryptic soy broth in volumes appropriate for the patient’s age. The samples were incubated at 35-37 °C for up to 7 days to detect bacterial growth. Positive blood cultures were subcultured onto various media, including chocolate agar, blood agar, modified Thayer-Martin agar, MacConkey agar, and mannitol salt agar, and incubated again at 35-37 °C for 24 h. The suspected bacteria were identified on the basis of colony morphology, Gram staining, and biochemical tests. Antimicrobial susceptibility testing was conducted via both the Kirby-Bauer and modified Kirby-Bauer disk diffusion methods. Resistance to methicillin, extended-spectrum beta-lactams, and carbapenems was determined via the cefoxitin disc test, combined-disk diffusion method, and modified carbapenem inactivation method, respectively. The data were entered into Epi-Data version 4.6 and analysed via SPSS version 25. Binary logistic regression analyses were employed to identify factors associated with bloodstream infections (BSI), with a P value of less than 0.05 considered statistically significant. Out of 341 patients suspected of septicemia, 196 (57.5%) were male and 145 (42.5%) were female, with a mean (± SD) age of 16.5 (± 7.5) years. Bloodstream infection was identified in 87 (25.5%) patients (95% CI: 21.1-30.4). Among these positive cases, 67 (77%) were from ward patients, while 20 (23%) were from those visiting outpatient departments. The primary gram-positive bacteria identified included S. aureus 27 (31.0%), CoNS 14 (16.1%), S. viridans 8 (9.2%), and S. agalactiae 4 (4.6%). The gram-negative isolates were predominantly K. pneumoniae 11 (12.6%), followed by E. coli 9 (10.3%), E. cloacae 6 (6.9%), Acinetobacter spp. 3 (3.5%), N. meningitidis 3 (3.5%), and P. aeruginosa 2 (2.3%). Methicillin resistance was detected in 17/27 (63.0%) S. aureus strains and 2/14 (14.3%) CoNS strains. Multidrug resistance was detected in 63/87 (72.4%, 95% CI: 67.2-84.7%) of the isolates. Extended-spectrum beta-lactamase and carbapenemase production were observed in 12/31 (38.7%) and 5/31 (16.1%) of isolates, respectively. The factors associated with BSI were the presence of wounds and burns (AOR = 2.103, 95% CI: 1.365-3.241, P = 0.041), length of hospital stay (≥ 5) (AOR = 2.209, 95% CI: 1.122-4.347, P = 0.022), and prior medical procedures (AOR = 1.982, 95% CI: 1.125-3.492, P = 0.018). Bloodstream infection was identified in 25.5% of suspected septicemia cases, with multidrug-resistant bacteria present in 72.4% of isolates. Gram-positive bacteria, particularly S. aureus, and gram-negative bacteria like K. pneumoniae and E. coli were predominant. High rates of methicillin, beta-lactam, and carbapenem resistance were observed, emphasizing the magnitude of antimicrobial resistance. Risk factors such as wounds, extended hospital stays, and prior medical procedures significantly increased the likelihood of culture positivity. This suggests the need for regular antimicrobial susceptibility testing to guide antibiotic selection and track resistance trends, proper wound care and medical device usage to reduce the risk of BSI in healthcare settings.

PMID:39962179 | DOI:10.1038/s41598-025-86648-x

Sci Rep. 2025 Feb 17;15(1):5805. doi: 10.1038/s41598-024-72539-0.

ABSTRACT

Cervical spinal cord injury is often catastrophic, frequently leading to irreversible impairment. MRI has become the gold standard for evaluating spinal cord injuries (SCI). Our study aimed to assess the accuracy of a radiomics approach, based on machine learning and utilizing conventional MRI, in predicting the prognosis of patients with SCI. In a retrospective analysis of 82 SCI patients from three hospitals, we categorized them into good (n = 49) and poor (n = 33) prognosis groups. Preoperative T2-weighted MRI images were segmented using 3D-Region of Interest (ROI) techniques, and both radiomic and deep transfer learning features were extracted. These features were normalized using Z-score and harmonized via ComBat. Feature selection was performed using a greedy algorithm and Least absolute shrinkage and selection operator (LASSO), and others, followed by the calculation of radiomics scores through linear regression. Machine learning was then used to identify the most predictive radiomic features. Model performance was evaluated by analyzing the area under the curve (AUC) and other indicators.Univariate analysis indicated that the demographic characteristics of cervical spinal cord injury were not statistically significant. In the test dataset, the random forest (RF) combined with radiomics and ResNet34 demonstrated better performance, with an accuracy of 0.800 and an AUC of 0.893.Using MRI, deep learning-based radiomics signals show promise in evaluating and predicting the postoperative prognosis of these patients.

PMID:39962172 | DOI:10.1038/s41598-024-72539-0

Sci Rep. 2025 Feb 17;15(1):5735. doi: 10.1038/s41598-025-89289-2.

ABSTRACT

Simulated by nature’s evolution, numerous evolutionary algorithms had been proposed. These algorithms perform better for a particular problem domain and extensive parameter fine tuning and adaptations are required in optimizing problems of varied domain. This paper aims to develop robust and self-adaptive memetic algorithm by combining Differential Evolution based algorithm, a popular population based global search method with the Controlled Local search procedure to solve multi-objective optimization problems. Memetic Algorithm is an enhanced evolutionary algorithm, it combines global search method with local search techniques for faster convergence. Memetic algorithm improves both exploration and exploitation, preventing premature convergence and also refines the current best solutions efficiently. Proposed algorithm is named as Fuzzy based Memetic Algorithm using Diversity control (F-MAD). In F-MAD, population diversity is controlled through the control parameters self-adaptation of Differential Evolution algorithm (DE) such as, crossover rate and scaling factor by using two fuzzy systems. A controlled local search procedure is adapted for guiding convergence process thus balancing explore-exploit cycle. The control parameter self-adaptation and enhanced selection method with controlled local search method aid population diversity control in decision space and attaining optimal solutions with uniform distribution in terms of diversity and convergence metrics in objective space. These characteristics help the proposed method suitable to be extended to different application domain without the need of trial-and-error fine tuning of the parameters. The performance is tested through standard benchmark test problems-CEC 2009 test problems and DTLZ test problem and further validated through performance metrics and statistical test. It is compared with popular optimization algorithms and experiment results indicate that F-MAD perform well than State of-The-Art (SOTA) algorithms taken for comparison. F-MAD algorithm attains better results for 8 out of 10 CEC 2009 test problems (UF1-UF10) when compared to 20 other algorithms taken for comparison. For DTLZ problems, F-MAD attains better results for ALL 7 problems (DTLZ 1-DTLZ7) when compared to 8 other SOTA algorithms. The performance is further evaluated using Friedman rank test and the proposed F-MAD significantly outperformed other algorithms.

PMID:39962162 | DOI:10.1038/s41598-025-89289-2

Sci Rep. 2025 Feb 17;15(1):5699. doi: 10.1038/s41598-025-89527-7.

ABSTRACT

The flexible job shop scheduling problem with parallel batch processing operation (FJSP_PBPO) in this study is motivated by real-world scenarios observed in electronic product testing workshops. This research aims to tackle the deficiency of effective methods, particularly global scheduling metaheuristics, for FJSP_PBPO. We establish an optimization model utilizing mixed-integer programming to minimize makespan and introduce an enhanced walrus optimization algorithm (WaOA) for efficiently solving the FJSP_PBPO. Key innovations of our approach include novel encoding, conversion, inverse conversion, and decoding schemes tailored to the constraints of FJSP_PBPO, a random optimal matching initialization (ROMI) strategy for generating diverse and high-quality initial solutions, as well as modifications to the original feeding, migration, and fleeing strategies of WaOA, along with the introduction of a novel gathering strategy. Our approach significantly improves solution quality and optimization efficiency for FJSP_PBPO, as demonstrated through comparative analysis with four enhanced WaOA variants, eleven state-of-the-art algorithms, and validation across 30 test instances and a real-world engineering case.

PMID:39962149 | DOI:10.1038/s41598-025-89527-7

Spinal Cord. 2025 Feb 17. doi: 10.1038/s41393-025-01066-0. Online ahead of print.

ABSTRACT

STUDY DESIGN: Systematic review and meta-analysis.

OBJECTIVES: Cervical spinal cord injury (SCI) and brachial plexus injury (BPI) can result in hand paralysis. Reconstruction of hand motion is associated with improved functionality and quality of life. We synthesized the outcomes of finger and thumb flexion after various nerve transfers to the anterior interosseous nerve (AIN).

METHODS: A systematic literature review and meta-analysis was performed according to the PRISMA guidelines. Successful finger and thumb flexion recovery was defined as Medical research council (MRC) grade ≥3.

RESULTS: In total, 23 studies with 99 patients and 120 nerve transfers to the AIN were performed. The mean interval from injury to surgery was 12.8 months and mean follow-up duration was 24 months. Overall, 81/120 (67.5%) and 68/102 (66.7%) hands achieved successful finger and thumb flexion recovery, respectively. Individual-patient-data were available for 94 nerve transfers. Type of injury (SCI vs BPI/peripheral) did not affect finger flexion outcomes (OR 1.92, 95%CI 0.74-5.0, p = 0.17). On multivariate analysis adjusted for mechanism of injury, timing of injury to surgery and duration of follow-up, utilization of the brachioradialis (BR) branch (25%, 1/4, OR 0.01, 95%CI 0.0006-0.44, p = 0.01) and brachialis (BA) branch (59%, 30/51, OR 0.06, 95%CI 0.006-0.68, p = 0.02) as donors, were associated with statistically significant lower odds of successful finger flexion recovery compared to extensor carpi radialis brevis (ECRB) use (95%, 19/20).

CONCLUSIONS: Similar outcomes were observed with SCI and BPI/peripheral type injuries. ECRB utilization as a donor was superior to BA or BR branch in terms of successful finger flexion recovery.

PMID:39962147 | DOI:10.1038/s41393-025-01066-0

Sci Rep. 2025 Feb 17;15(1):5783. doi: 10.1038/s41598-025-89773-9.

ABSTRACT

The “Life’s Essential 8” (LE8) score is an assessment of cardiovascular health recently introduced by the American Heart Association. This study aimed to explore the correlation of the total LE8 score and its individual metrics with all-cause and cardiovascular disease (CVD) mortality in patients with hypertension. Data from 10,556 hypertension adults were retrieved from National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. After a median follow-up of 6.75 years, patients with high LE8 scores (≥ 75 points) showed significantly lower mortality rates from all causes and CVD (P < 0.001). Cox regression analysis indicated that high LE8 scores were associated with a 40% lower risk of all-cause [0.60(0.50-0.73)] and CVD mortality [0.60(0.43-0.83)] compared to low scores. As the total LE8 score increased linearly, the likelihood of all-cause and CVD mortality decreased, with a potential threshold at 60 points. Subgroup analyses revealed that diet, sleep, nicotine exposure, physical activity, and blood glucose control affected both types of mortality. The LE8 score was negatively correlated with the risks of all-cause and CVD mortality in hypertensive patients. Life interventions and management of physical indicators based on the LE8 score may be an effective way to improve mortality in hypertensive patients.

PMID:39962139 | DOI:10.1038/s41598-025-89773-9

Sci Rep. 2025 Feb 17;15(1):5810. doi: 10.1038/s41598-025-89678-7.

ABSTRACT

The illegal ivory trade has led to a sharp decline in wild elephant populations in recent decades, while mammoth (Mammuthus primigenius) ivory products have increasingly flooded the marketplace, complicating identification efforts by frontline law enforcement. Existing ivory identification methods face several challenges, including inconsistent accuracy due to sample quality, high costs, slow turnaround times, and destructive sample requirements. Currently, there is a lack of a fast, convenient, and highly effective solution to address these issues. To tackle these challenges, this study developed a novel, efficient, and accurate method for identifying and characterizing ivory products using ultra-performance liquid chromatography with a fluorescence detector (UPLC-FLR). The technique focuses on various organic small-molecule compounds in ivory that have been largely overlooked. A chemical fingerprint library was created using 72 African elephant and 69 mammoth ivory samples. Comprehensive comparative analyses, including principal component analysis, compound distribution analysis, proportion analysis, chord diagrams, and statistical significance tests, revealed significant differences between the organic compounds in the two sample groups, confirming the method’s reliability. Six widely used machine learning classification models were then applied to construct a discriminant model based on 11 key feature compounds among the 85 identified, with each model achieving 100% classification accuracy. Compared to the conventional ‘gold standard’ molecular biology method, this UPLC-based approach shortened detection time from 24 h to just 1 h, reduced the sample requirement by 50%, and cut costs by 90%, making it a more efficient, user-friendly solution for frontline law enforcement. Widespread adoption of this method in law enforcement could become a powerful tool in the fight against the illegal ivory trade.

PMID:39962129 | DOI:10.1038/s41598-025-89678-7

Sci Rep. 2025 Feb 17;15(1):5790. doi: 10.1038/s41598-025-87154-w.

ABSTRACT

Fluorescence recovery after photobleaching (FRAP) allows to study actin-turnover in dendritic spines by providing recovery trajectories over time within a nested data structure (i.e. spine/neuron/culture). Statistical approaches to FRAP usually consider one-phase association models to estimate recovery-curve-specific parameters and test statistical hypotheses on curve parameters either at the spine or neuron level, ignoring the nested data structure. However, this approach leads to pseudoreplication concerns. We propose a nonlinear mixed-effects model to integrate the one-phase association model estimate with the nested data structure of FRAP experiments; this also allows us to model heteroscedasticity and time dependence in the data. We used this approach to evaluate the effect of the downregulation of the actin-binding protein CAP2 on actin dynamics. Our model allows the additional modelling of the variance function across experimental conditions, which may represent a novel parameter of interest in FRAP experiments. Indeed, the detected differential effect of the experimental condition on the variance component captures the increased instability of time-specific observations around the spine-specific trajectory for the CAP2-downregulated spines compared to the control spines. We hypothesise that this parameter reflects the increased instability of the actin cytoskeleton in dendritic spines upon CAP2 downregulation. We developed an R-based Shiny application, termed FRApp, to fit the statistical models introduced without requiring programming expertise.

PMID:39962126 | DOI:10.1038/s41598-025-87154-w

Transl Psychiatry. 2025 Feb 17;15(1):55. doi: 10.1038/s41398-025-03259-w.

ABSTRACT

Narcolepsy is a severe sleep disorder with characteristics of fatigue, fragmented sleep, cataplexy and hypnagogic hallucinations. Earlier clinical studies have reported the onset of schizophrenia after narcolepsy but the causality behind narcolepsy and schizophrenia is unknown. Our goal was to understand the causality between narcolepsy and schizophrenia. To estimate the comorbidity between narcolepsy and schizophrenia, we employed data from the FinRegistry that contains data for the total population of Finland in total 7.2 million individuals (N = 1664 individuals with narcolepsy and 55,372 with schizophrenia). We then used Mendelian randomization and previously published genome-wide association data to test the causality between narcolepsy and schizophrenia. We observed a robust causal association from narcolepsy to schizophrenia using the HLA-independent lead variants (P-value = 6.0 × 10^-4), which was accentuated when including the HLA locus (P-value = 4.48 × 10^-7). Furthermore, we observed a modest bidirectional causality from schizophrenia to narcolepsy (P-value = 0.015). There was no evidence of pleiotropy. Our findings indicate a causal relationship where narcolepsy may increase the risk for schizophrenia, and a bidirectional causality from schizophrenia to narcolepsy. Additionally, our results clarify the psychiatric burden in narcolepsy.

PMID:39962082 | DOI:10.1038/s41398-025-03259-w

Nat Commun. 2025 Feb 17;16(1):1711. doi: 10.1038/s41467-025-56986-5.

ABSTRACT

Epistasis – the interaction between alleles at different genetic loci – plays a fundamental role in biology. However, several recent approaches quantify epistasis using a chimeric formula that measures deviations from a multiplicative fitness model on an additive scale, thus mixing two scales. Here, we show that for pairwise interactions, the chimeric formula yields a different magnitude but the same sign of epistasis compared to the multiplicative formula that measures both fitness and deviations on a multiplicative scale. However, for higher-order interactions, we show that the chimeric formula can have both different magnitude and sign compared to the multiplicative formula. We resolve these inconsistencies by deriving mathematical relationships between the different epistasis formulae and different parametrizations of the multivariate Bernoulli distribution. We argue that the chimeric formula does not appropriately model interactions between the Bernoulli random variables. In simulations, we show that the chimeric formula is less accurate than the classical multiplicative/additive epistasis formulae and may falsely detect higher-order epistasis. Analyzing multi-gene knockouts in yeast, multi-way drug interactions in E. coli, and deep mutational scanning of several proteins, we find that approximately 10% to 60% of inferred higher-order interactions change sign using the multiplicative/additive formula compared to the chimeric formula.

PMID:39962081 | DOI:10.1038/s41467-025-56986-5