Tag: statistics

Bioinformatics. 2025 Mar 14:btaf111. doi: 10.1093/bioinformatics/btaf111. Online ahead of print.

ABSTRACT

MOTIVATION: Nanopore sequencing by Oxford Nanopore Technologies (ONT) enables direct analysis of DNA and RNA by capturing raw electrical signals. Different nanopore chemistries have varied k-mer lengths, current levels, and standard deviations, which are stored in ‘k-mer models’. In cases where official models are lacking or unsuitable for specific sequencing conditions, tailored k-mer models are crucial to ensure precise signal-to-sequence alignment, analysis and interpretation. The process of transforming raw signal data into nucleotide sequences, known as basecalling, is a fundamental step in nanopore sequencing.

RESULTS: In this study, we leverage the move table produced by ONT’s basecalling software to create a lightweight de novo k-mer model for RNA004 chemistry. We demonstrate the validity of our custom k-mer model by using it to guide signal-to-sequence alignment analysis, achieving high alignment rates (97.48%) compared to larger default models. Additionally, our 5-mer model exhibits similar performance as the default 9-mer models another analysis, such as detection of m6A RNA modifications. We provide our method, termed Poregen, as a generalisable approach for creation of custom, de novo k-mer models for nanopore signal data analysis.

AVAILABILITY AND IMPLEMENTATION: Poregen is an open source package under an MIT licence: https://github.com/hiruna72/poregen.

SUPPLEMENTARY INFORMATION: Supplementary Note 1.

PMID:40085000 | DOI:10.1093/bioinformatics/btaf111

Dentomaxillofac Radiol. 2025 Mar 14:twaf023. doi: 10.1093/dmfr/twaf023. Online ahead of print.

ABSTRACT

OBJECTIVES: This study aimed to evaluate the accuracy of airway volume measurements obtained from cone-beam computed tomography (CBCT) images using various software programs, with a focus on assessing the performance of NemoStudio compared to other tools. The estimated volumes were compared with the volume of the solid model’s cavity filled with water (gold standard).

METHODS: A single 3D-printed airway model was created based on CBCT data and scanned ten times under identical conditions. Volume measurements were performed using semi-automatic segmentation in four software programs (NemoStudio, NNT Viewer, ITK-SNAP, and 3D Slicer). The results were compared to the gold standard using repeated measures ANOVA, Bland-Altman plots, and post hoc comparisons.

RESULTS: Nemo Studio demonstrated a systematic bias and higher variability compared to the gold standard, resulting in lower accuracy than the other software programs. ITK-SNAP and 3D Slicer showed the highest agreement with the gold standard, while NNT Viewer also exhibited acceptable performance. Statistical analyses revealed significant differences in the accuracy of volume measurements among the software tools (P < 0.001). Bland-Altman plots highlighted Nemo Studio’s broader limits of agreement, emphasizing its deviation from the gold standard.

CONCLUSION: Variability in airway volume measurement accuracy underscores the need for careful software selection and methodological standardization. Further refinement of segmentation algorithms is essential for improved consistency and reliability in clinical applications.

ADVANCES IN KNOWLEDGE: This study provides the first evaluation of NemoStudio’s volumetric accuracy for CBCT-based airway measurements, offering novel insights into software reliability and the impact of algorithm selection in clinical and academic settings.

PMID:40084997 | DOI:10.1093/dmfr/twaf023

Ann Plast Surg. 2025 Mar 6. doi: 10.1097/SAP.0000000000004310. Online ahead of print.

ABSTRACT

BACKGROUND: Patient-directed discharge (PDD) poses a significant challenge in healthcare. Prior studies have shown associations of PDD with factors like race, housing, psychiatric illness, socioeconomic status, and intravenous drug use (IVDU). This study aims to identify factors contributing to PDD in hand infection patients at a public safety-net hospital and to investigate the long-term consequences through readmissions or returns to the emergency department (ED).

METHODS: A retrospective analysis was conducted on adult patients presenting with hand infections at San Francisco’s main public hospital over 1 year. Data collected included demographics, housing status, social support, psychiatric diagnoses, and IVDU. Statistical analysis involved Mann-Whitney U tests, Fisher’s exact tests, and logistic regression with odds ratios (ORs).

RESULTS: A total of 131 patients were included, comprising 95 (73%) conventionally discharged and 36 (27%) PDD patients. Positive correlations were found between PDD and several factors, including unemployment, unstable housing, living alone, lack of a phone number on file, alcohol use, and IVDU. However, in the multivariate analysis, IVDU emerged as the sole statistically significant predictor (OR, 4.22; CI, 1.18-15.05; P = 0.026). Further regression analysis identified unstable housing (OR, 4.39; CI, 1.17-16.44; P = 0.028) and living alone (OR, 4.45; CI, 1.25-15.89; P = 0.021) to be positively correlated with IVDU. PDD had higher ED revisits (P = 0.025) and readmission rates (P = 0.014).

CONCLUSIONS: This study underscores the critical role of socioeconomic factors, particularly IVDU, in influencing PDD among hand infection patients. The findings highlight the need for integrated healthcare strategies addressing medical and social determinants to reduce PDD and improve patient outcomes.

PMID:40084988 | DOI:10.1097/SAP.0000000000004310

Laryngoscope. 2025 Mar 14. doi: 10.1002/lary.32122. Online ahead of print.

ABSTRACT

OBJECTIVES: To investigate the association between the vestibular aqueduct (VA) and endolymphatic hydrops (EH) in patients with Meniere’s disease (MD) using three-dimensional real inversion recovery (3D-real IR) sequences.

METHODS: This retrospective study included patients diagnosed with unilateral MD who underwent computed tomography (CT) and 3D-real IR sequencing. The VA course was identified on CT, and its visibility was assessed using a 3D-real IR sequence. The presence and severity of the cochlear and vestibular EH were evaluated. VA visualization was classified as Grade 0, whereas nonvisualization was classified as Grade 1. Differences in VA visibility between the affected and unaffected ears were compared, and correlations between VA visibility and EH severity were analyzed. Finally, the diagnostic efficacy of various MD indicators was assessed.

RESULTS: A total of 56 patients with unilateral MD were analyzed. The incidence rates of cochlear or vestibular EH were higher in the affected ear group than in the unaffected ear group (p < 0.001). The rates of nonvisualization of the VA in the affected and unaffected ears were 91.1% and 41.1%, respectively, with a statistically significant difference (χ² = 31.226, p < 0.001). The VA visualization status was positively correlated with vestibular and cochlear EH (p < 0.001). The area under the curve for diagnosing MD using combined VA nonvisualization and EH was 0.876, which was significantly higher than that obtained using EH alone (Z = 3.414, p = 0.001).

CONCLUSION: VA visibility on 3D-real IR sequences may assist in the diagnosis of MD and associated EH.

PMID:40084987 | DOI:10.1002/lary.32122

Anal Chem. 2025 Mar 14. doi: 10.1021/acs.analchem.4c06520. Online ahead of print.

ABSTRACT

Mass spectrometry imaging (MSI) is a technique that uncovers the contextual distribution of biomolecules in tissue. This involves collecting large data sets with information-rich mass spectra in each pixel. To streamline image processing and interpretation, the MSI community has developed toolboxes for image preprocessing, segmentation, statistical analysis, and visualization. These generally require data to be input as imzML files, an Extensible Markup Language file with vocabulary for mass spectrometry and imaging-specific parameters. While commercial systems (e.g., MALDI) come with proprietary file converters, to our knowledge, no open-access user-friendly converters exist for continuously acquired imaging data (e.g., nano-DESI, DESI). Here, we present imzML Writer, an easy-to-use Python application with a graphical user interface to convert data from vendor format into pixel-aligned imzML files. We package this application with imzML Scout, allowing visualization of the resulting file(s) and batch export of ion images across a range of image and data formats (e.g., PNG, TIF, CSV). To demonstrate the utility of files generated by imzML Writer, we processed nano-DESI data with popular tools such as Cardinal MSI and METASPACE. Overall, this work provides a simple open-access tool for emerging MSI modality users to access advanced MSI processing tools reliant on imzML format. ImzML Writer is available as a distributable Python package via pip or as a standalone program for Mac and PC at https://github.com/VIU-Metabolomics/imzML_Writer.

PMID:40084954 | DOI:10.1021/acs.analchem.4c06520

Radiol Imaging Cancer. 2025 Mar;7(2):e240213. doi: 10.1148/rycan.240213.

ABSTRACT

Purpose To develop deep learning (DL) radiopathomics models based on contrast-enhanced MRI and pathologic imaging to predict vessels encapsulating tumor clusters (VETC) and survival in hepatocellular carcinoma (HCC). Materials and Methods In this retrospective, multicenter study, 578 patients with HCC (mean age [±SD], 59 years ± 10; 442 male, 136 female) were divided into the training (n = 317), internal (n = 137), and external (n = 124) test sets. DL radiomics and pathomics models were developed to predict VETC using gadoxetic acid-enhanced MR and pathologic images. Deep radiomics score (DRS) and handcrafted and deep pathomics scores were compared between the group with VETC pattern in HCC (VETC+) and group without VETC pattern in HCC (VETC-). Multivariable Cox regression analyses were performed to identify independent prognostic factors, and the radiopathomics nomogram models were developed for early recurrence and progression-free survival (PFS). The prognostic power was evaluated using the concordance index (C index) and time-dependent receiver operating characteristic (ROC) curves. Results In the external test set, the Swin Transformer showed good performance for predicting VETC in both DL radiomics (area under the ROC curve [AUC], 0.77-0.79) and pathomics (AUC, 0.79) models. Patients with VETC+ HCC had significantly higher DRS and handcrafted and deep pathomics scores compared with patients with VETC- HCC in all datasets (all P < .001). The radiopathomics nomogram model incorporating DRS in the arterial phase and the handcrafted and deep pathomics scores achieved C indexes of 0.69, 0.60, and 0.67 for early recurrence and time-dependent AUCs of 0.83 (95% CI: 0.76, 0.91), 0.81 (95% CI: 0.68, 0.94), and 0.78 (95% CI: 0.67, 0.88) for 3-year PFS in the training, internal, and external test sets, respectively. Early recurrence and PFS rates statistically significantly differed between the high- and low-risk patients stratified by the radiopathomics nomogram model (all P < .05). Conclusion DL radiopathomics models effectively helped to predict VETC in HCC and assess the risk for early recurrence and PFS. Keywords: Hepatocellular Carcinoma, Deep Learning, MRI, Radiopathomics, Survival Supplemental material is available for this article. © RSNA, 2025.

PMID:40084948 | DOI:10.1148/rycan.240213

Rev Sci Instrum. 2025 Mar 1;96(3):033510. doi: 10.1063/5.0242943.

ABSTRACT

An efficient and stable Abel inversion method is developed using Zernike polynomials to reconstruct the local emissivity profile from line integrated data. We reconstructed emissivity for parabolic, Gaussian, and non-monotonic profiles. By leveraging Cormack’s method, we skip evaluating the integrals numerically, reducing error in reconstruction. This method is derivative-free and singularity-free. The standard deviation of the reconstructed profiles is estimated and found to be small. For a parabolic profile with n = 3, the standard deviation is 0.0887, and the Kolmogorov-Smirnov test yields a KS statistic value of 0.002, with a reduced chi-square value of 0.857. A chi-square test and a Kolmogorov-Smirnov test are performed to reject the null hypothesis, adding another verification layer to the efficiency of our method along with a standard deviation test.

PMID:40084934 | DOI:10.1063/5.0242943

Ecol Lett. 2025 Mar;28(3):e70094. doi: 10.1111/ele.70094.

ABSTRACT

Online portals have facilitated collecting extensive biodiversity data by naturalists, offering unprecedented coverage and resolution in space and time. Despite being the most widely available class of biodiversity data, opportunistically collected records have remained largely inaccessible to community ecologists since the imperfect and highly heterogeneous detection process can severely bias inference. We present a novel statistical approach that leverages these datasets by embedding a spatiotemporal joint species distribution model within a flexible site-occupancy framework. Our model addresses variable detection probabilities across visits and species by modelling phenological patterns and by extending the use of latent variables to characterise observer-specific detection and reporting behaviour. We apply our model to an opportunistically collected dataset on lentic odonates, encompassing over 100,000 waterbody visits in Flanders (N-Belgium), to show that the model provides insights into biological communities at high resolution, including phenology, interannual trends, environmental associations and spatiotemporal co-distributional patterns in community composition.

PMID:40084931 | DOI:10.1111/ele.70094

Int J Med Educ. 2025 Mar 13;16:52-61. doi: 10.5116/ijme.679e.091b.

ABSTRACT

OBJECTIVES: To explore medical students’ self-assessed preparedness for clinical practice and attitudes towards learning communication skills, and attitudes towards patient-centeredness before and after introducing a new curriculum with a group mentorship program.

METHODS: A cross-sectional questionnaire-study (1-5 Likert scale) was conducted among the first class of medical students following the new curriculum (NC, n = 51) in their fifth year and the final class of students in the old curriculum (OC, n = 48) in their sixth year. The questionnaire contained questions regarding program evaluation, and statements that measured the students’ attitudes towards learning communication skills and patient-centeredness. Descriptive statistics and Mann-Whitney U-test were used.

RESULTS: NC-students (Mdn=4) scored significantly higher than the OC-students (Mdn=3), when asked how they thought the first four years of the medical curriculum had prepared them for clinical practice (U=828.5, p=.003, r=0.35). Similarly, NC-students felt more prepared for communication with patients (Mdn=4 for both groups, U=748.5, p<.001, r=0.35) and ethical reflections (Mdn=4 for both groups, U=951.5, p=0.043, r=0.20). NC-students reported significantly more positive attitudes towards learning communication skills than did OC-students. They had higher mean scores on all items regarding patient-centeredness, although these differences were not statistically significant.

CONCLUSIONS: A group-based mentorship program within the new curriculum significantly enhanced medical students’ self-assessed clinical preparedness and positively shifted their attitudes towards communication skills and patient-centeredness. More research is needed to compare medical schools with and without longitudinal group mentorship programs to assess students’ professional attitudes, and ideally, their performance in clinical practice.

PMID:40084905 | DOI:10.5116/ijme.679e.091b

J Acoust Soc Am. 2025 Mar 1;157(3):1772-1783. doi: 10.1121/10.0036129.

ABSTRACT

This study introduces the concept of activity-based acoustic situations in primary schools, which describe the everyday sound environment in classrooms. During a series of noise measurements in seven German primary schools, differences in noise parameters and subjective listening effort, as assessed by questionnaires, were investigated across the activity-based acoustic situations. Classroom noise was analyzed for sound pressure level (SPL), A-weighted SPL, loudness, and sharpness. The results showed statistically significant differences in average loudness and A-weighted SPL between the activity-based acoustic situations, with silent work yielding 55.48 dB(A), student-teacher interaction 65.13 dB(A), group work 67.44 dB(A), and breakfast break in the classroom 69.34 dB(A). All loudness parameters, SPL, A-weighted SPL, and loudness, showed higher values for first grade than for fourth grade supporting that noise levels decrease with increasing age. Subjective listening effort, as assessed by questionnaires, did not differ significantly between activity-based acoustic situations. This suggests that the questionnaire may not have been suited to evaluate subjective listening effort for the age group investigated. The present study highlights the importance of activity-based assessment of classroom noise to better represent the classroom sound environment.

PMID:40084904 | DOI:10.1121/10.0036129