Nevin Manimala

Soc Cogn Affect Neurosci. 2025 Mar 14:nsaf028. doi: 10.1093/scan/nsaf028. Online ahead of print.

ABSTRACT

Social interaction plays a crucial role in human societies, encompassing complex dynamics among individuals. To understand social interaction at the neural level, researchers have utilized hyperscanning in several social settings. These studies have mainly focused on inter-brain synchrony and the efficiency of paired functional brain networks, examining group interactions in dyads. However, this approach may not fully capture the complexity of multiple interactions, potentially leading to gaps in understanding inter-network differences. To overcome this limitation, the present study aims to bridge this gap by introducing methodological enhancements using the multilayer network approach, which is tailored to extract features from multiple networks. We applied this strategy to analyze the triad condition during social behavior processes to identify group interaction indices. Additionally, to validate our methodology, we compared the multilayer networks of triad conditions with group synchrony to paired conditions without group synchrony, focusing on statistical differences between alpha and beta waves. Correlation analysis between inter-brain and group networks revealed that this methodology accurately reflects the characteristics of actual behavioral synchrony. The findings of our study suggest that measures of paired brain synchrony and group interaction may exhibit distinct trends, offering valuable insights into interpreting group synchrony.

PMID:40085071 | DOI:10.1093/scan/nsaf028

Fa Yi Xue Za Zhi. 2024 Dec 25;40(6):582-588. doi: 10.12116/j.issn.1004-5619.2023.431005.

ABSTRACT

OBJECTIVES: To analyze the independent influencing factors of intimate partner homicide (IPH) cases, construct an IPH prediction model, and provide a basis for criminal profiling.

METHODS: A total of 476 convicted homicide cases in Guangdong Province from January 1, 2014, to December 31, 2020, were collected as modeling dataset. They were divided into the IPH group (n=180) and the non-intimate partner homicide (N-IPH) group (n=296) based on whether the offender and victim were intimate partners. Logistic regression was used to build the model, the model was evaluated through the receiver operating characteristic (ROC) curve analysis and a nomogram was drawn. Internal validation was conducted using ten-fold cross-validation method. A total of 126 court judgments from outside Guangdong Province from January 1, 2011, to December 31, 2020, were randomly collected for external validation.

RESULTS: Through multi-factor Logistic regression analysis, 7 variables were ultimately selected for inclusion in the model. The Hosmer-Lemeshow goodness of fit test result of the model was χ²=13.158, P=0.068. The ROC area under the curve (AUC) of the model was 0.939 (95% CI: 0.919-0.959), the cut-off value was 0.292, the sensitivity was 0.900, and the specificity was 0.865. The calibration curve was close to the ideal curve. The ten-fold cross-validation showed the accuracy of 0.863 and a Kappa value of 0.708. The external validation results showed an AUC of 0.922 (95% CI: 0.872-0.971), a cut-off value of 0.292, a sensitivity of 0.890, and a specificity of 0.886. The calibration curve tended to the ideal curve.

CONCLUSIONS: The IPH prediction model based on forensic field indicators has good predictive ability, reliable accuracy and stability, and can provide a scientific method for criminal profiling.

PMID:40085040 | DOI:10.12116/j.issn.1004-5619.2023.431005

Int Endod J. 2025 Mar 14. doi: 10.1111/iej.14221. Online ahead of print.

ABSTRACT

AIM: To characterize the deep dentinal caries microbiota in teeth diagnosed with normal pulp with deep caries (NP), reversible pulpitis (RP), symptomatic irreversible pulpitis (SIP), and asymptomatic irreversible pulpitis (AIP), and to identify potential key pathogens associated with pulpitis progression, exploring their roles in disease advancement.

METHODOLOGY: In this cross-sectional study, we collected 108 dentinal caries samples, categorized into NP (n = 27), RP (n = 27), SIP (n = 27), and AIP (n = 27), according to the American Association of Endodontists’ diagnostic criteria. 2 NP samples and 2 RP samples were excluded due to contamination. Samples were processed using Illumina MiSeq high-throughput sequencing. Alpha and beta diversity, taxa abundance differences, co-occurrence network analysis, and functional prediction were evaluated. Correlation analysis between the abundance of bacteria associated with clinical diagnosis, clinical signs, and pulp exposure status was performed with Spearman analysis and the Mantel test.

RESULTS: The bacteriome of deep dentinal caries exhibited statistically significant differences among NP, RP, SIP, and AIP groups. NP and RP showed similar microbial community structures, with comparable alpha diversity, beta diversity, bacterial phenotypes, functions, and network structures. In contrast, AIP and SIP displayed distinct microbial community profiles. AIP was characterized by higher alpha diversity and a greater abundance of gram-negative bacteria, with Propionibacterium and Prevotella_7 identified as bacteria associated with AIP pathogenesis. On the other hand, SIP showed lower alpha diversity and a higher abundance of facultative anaerobes, with Lactobacillus and Limosilactobacillus identified as bacteria associated with SIP pathogenesis. Fusobacterium, Prevotella, Treponema, and Selenomonas were identified as bacteria associated with both AIP and SIP. Compared to NP and RP, the microbial networks in AIP and SIP are more complex and contain more gram-negative endodontic pathogens. These pathogens form complex positive correlations with each other and numerous negative correlations with lactic acid bacteria.

CONCLUSIONS: The bacteriome of deep dentinal caries differs significantly across teeth diagnosed with NP, RP, AIP, and SIP. NP and RP exhibit similar microbial communities, whereas SIP and AIP display distinct microbial profiles.

PMID:40085030 | DOI:10.1111/iej.14221

Pain. 2025 Mar 13. doi: 10.1097/j.pain.0000000000003583. Online ahead of print.

ABSTRACT

Pain is the hallmark symptom of sickle cell disease (SCD). By adolescence, 20% of youth with SCD develop chronic SCD pain. Our randomized controlled trial found significant reductions in pain in youth receiving digital cognitive-behavioral therapy (CBT) vs education control. However, little is known about factors that moderate the effects of CBT in adolescents with SCD. This secondary data analysis aims to identify adolescent and family characteristics that moderate treatment effects on pain outcomes in 111 adolescents aged 12 to 18 with SCD (M = 14.9, SD = 1.9, girls = 59%) and their caregivers. Adolescents were randomly assigned to digital CBT (N = 57) or education control (N = 54). Digital CBT included separate content for parents/caregivers (ie, a website to learn problem-solving skills and behavioral and communication strategies) and youths (ie, a smartphone app and website to learn pain management skills). Outcomes were assessed at pretreatment, posttreatment (2 months), and follow-up (6 months). Potential moderators included pretreatment variables (ie, adolescent variables: age, executive functioning, anxiety, depression; parent variables: psychological distress, protective behaviors, family functioning). There was a significant overall effect modification on pain intensity outcomes from pretreatment parent psychological distress (P = 0.012), where CBT appeared more effective among those with elevated parental distress. Differential intervention effects were observed across multiple potential moderator groups, though most of these differences did not reach statistical significance. Our study underscores the importance of family factors in understanding the efficacy of digital CBT for adolescent SCD pain, pointing to the need for future research to optimize CBT through targeted family-focused strategies.

PMID:40085012 | DOI:10.1097/j.pain.0000000000003583

Eur J Cardiothorac Surg. 2025 Mar 14:ezaf071. doi: 10.1093/ejcts/ezaf071. Online ahead of print.

ABSTRACT

OBJECTIVES: The Ross procedure has been associated with better long-term outcomes in selected patients. Nevertheless, its complexity has limited its adoption. The aim of this study was to assess the learning curve of the Ross procedure and to evaluate the impact of new surgeons joining an experienced Ross program.

METHODS: From 2011 to 2023, 673 consecutive Ross procedures were performed in adults (<69 years) at the Montreal Heart Institute. The cohort was divided into 3 groups depending on the previous experience of the operating surgeon. Safety (including mortality and major complications), efficiency (cardiopulmonary bypass and aortic cross-clamp times), and efficacy end-points (aortic regurgitation >1/4) were compared. Cumulative sum analyses (CUSUM) were performed to evaluate mortality and major complications.

RESULTS: There were 3 (0.45%) peri-operative mortalities. All analyzed outcomes exhibited temporal trends towards improvement. Major complications decreased from 9.5% in the Early period to 1.8% in the Late (p = 0.019). Similarly, there was a statistically significant improvement in median cardiopulmonary bypass (from 203.5 min in the Early period to 163.5 in the Late, p < 0.001) and aortic cross-clamp times (from 180 min in the Early period to 148 in the Late, p < 0.001).

CONCLUSIONS: Improvement in safety, efficiency and resource utilization were observed after an initial learning period. Addition of new surgeons to an established Ross program did not negatively impact surgical outcomes. Mortality and morbidity remained low and compared favorably with predicted risks for conventional AVR. The Ross procedure is reproducible with adequate mentorship and support to help minimize individual learning curves.

PMID:40085010 | DOI:10.1093/ejcts/ezaf071

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