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Nevin Manimala Statistics

Regional Differences in Postexcision Outcomes of Keloids: A Focus on Auricular Versus Nonauricular Sites

Ann Plast Surg. 2026 May 25. doi: 10.1097/SAP.0000000000004775. Online ahead of print.

ABSTRACT

BACKGROUND: The pathophysiology of keloid formation remains poorly understood, and treatment typically involves multimodal approaches. Previous studies suggest that keloids on the earlobes, head, and neck may be more responsive to radiation than those on other anatomic sites due to putative differences in skin tension and biomechanical properties. However, limited comparative data exist to substantiate these anatomic distinctions in clinical outcomes.

AIM: To compare recurrence rates, treatment outcomes, and radiation-related side effects between auricular and nonauricular keloids following surgical excision with adjuvant radiation therapy or surgical excision alone.

METHODS: This retrospective cohort study analysed 168 cases with keloids (60 auricular and 108 nonauricular) treated by a single surgeon between January 2020 and May 2024. Of these, 122 patients underwent surgical excision followed by adjuvant radiation therapy, while 46 patients received surgical excision only. Intralesional 5-Fluorouracil and Kenalog was injected across both groups during surgical excision. Demographic and clinical data, including age, sex, race, BMI, keloid site and size, and treatment modality, were collected. Patients were followed up post-treatment to assess recurrence, radiation-related side effects, and treatment response patterns.

RESULTS: Auricular keloids were more common in younger patients and significantly smaller in size (median 12 vs. 19.5 mm for nonauricular, P<0.001). The majority of patients received 2100 cGy of radiation. Among those receiving surgery plus radiation, 17.07% of auricular and 16.22% of nonauricular keloids recurred (P=0.91). In the surgery-only group, recurrence was 47.37% and 44.12%, respectively (P=0.82). Notably, radiation-related side effects were significantly more frequent in nonauricular sites (37%) compared with auricular (20%) (P=0.022). Age, sex, race, BMI, and radiation dose did not independently predict recurrence in the final model.

CONCLUSION: Anatomic site did not significantly influence keloid recurrence rates, challenging previous assumptions about site-specific treatment responses, while adjuvant radiotherapy significantly reduced recurrence irrespective of site. Radiation-related side effects were more common in nonauricular locations. Age, sex, race and BMI did not emerge as statistically significant demographic predictors of recurrence in this study. These findings support the routine inclusion of radiotherapy in keloid management and suggest that demographic and treatment factors may outweigh anatomic considerations in predicting outcomes.

PMID:42184131 | DOI:10.1097/SAP.0000000000004775

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Nevin Manimala Statistics

A preliminary examination of the psychometrics and cognitive correlates of an abbreviated version of the verbal naming test administered via telephone

Arch Clin Neuropsychol. 2026 May 6;41(4):acag039. doi: 10.1093/arclin/acag039.

ABSTRACT

OBJECTIVE: Confrontational naming is an important part of many neuropsychological evaluations. Yet, data on the feasibility and psychometric properties of telephone-based confrontational verbal naming tests (VNTs) are quite limited. The current study conducted a preliminary, exploratory examination of the psychometrics and correlates of an abbreviated version of the 50-item VNT administered via telephone.

METHOD: Participants were 220 healthy adults, including 110 younger adults (ages 18-35) and 110 middle-aged to older adults (ages 50-85). Participants completed a 15-item version of the VNT as part of a broader telephone-based cognitive battery.

RESULTS: Confirmatory factor analysis suggested support for a 12-item model of the VNT (VNT-T12) with acceptable fit. VNT-T12 scores were negatively skewed and demonstrated good internal consistency. A quantile regression predicting VNT-T12 from domain-level cognitive variables showed that executive functions (e.g., verbal fluency) and fund of verbal knowledge were significantly and positively associated with VNT-T12 scores at most percentile ranges. The VNT-T12 scores were also significantly associated with race/ethnicity and English as a second language at higher quantiles of performance. Demographically-adjusted coefficients and an associated calculator are provided as a normative resource.

CONCLUSIONS: Findings provide mixed and preliminary support for the feasibility, psychometrics, and validity of a 12-item VNT administered via telephone. Future research on the psychometrics and validity of the VNT-T12 is warranted in samples with lower levels of education and in clinical populations.

PMID:42184122 | DOI:10.1093/arclin/acag039

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Nevin Manimala Statistics

Out-of-distribution generalization enhances protein function annotation for low-homology sequences

Brief Bioinform. 2026 May 4;27(3):bbag243. doi: 10.1093/bib/bbag243.

ABSTRACT

Understanding protein functions in biological processes is pivotal for disease elucidation and drug discovery. Despite notable progress, existing approaches primarily focus on function transfer under in-distribution (ID) settings, where training and test proteins exhibit high sequence similarity. As a result, their performance often degrades when applied to novel, diverse, and low-homology protein sequences, posing a major challenge for out-of-distribution (OOD) generalization encountered in practice. Towards this end, we develop ProteinScore, a graph transformer approach tailored to improve protein function prediction in OOD settings. ProteinScore integrates a label-invariant variational subgraph generator with self-supervised contrastive learning, thereby identifying meaning substructures within proteins. By highlighting informative features while filtering out redundant ones, ProteinScore improves generalization to diverse and low-homology sequences. Experiments on datasets with both experimentally resolved and AlphaFold2-predicted structures demonstrate that ProteinScore consistently outperforms strong baselines and provides biologically meaningful interpretability through accurately identifying binding sites. In addition, ProteinScore generalizes effectively to two additional downstream tasks, drug-target interaction classification and subcellular localization prediction, achieving superior predictive performance and reliable interpretability.

PMID:42184116 | DOI:10.1093/bib/bbag243

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Nevin Manimala Statistics

Decoding causal m6A: a bioinformatics roadmap for psychiatric disorders

Brief Bioinform. 2026 May 4;27(3):bbag251. doi: 10.1093/bib/bbag251.

ABSTRACT

N 6-methyladenosine (m6A), the most prevalent internal RNA modification, is an emerging key regulator of gene expression in the central nervous system, and its dysregulation is connected to psychiatric disorders. However, disentangling the causal links between specific m6A sites and diseases phenotypes remain challenging. This review presents a comprehensive survey of practical bioinformatics strategies to address it. Our review outlines four analytical themes: (i) the reliable calibration of false-positive signals, (ii) causal inference via statistical genetics, (iii) the acquisition of cell-type-specific functional insights, and (iv) the application of machine learning to predict clinical biomarkers. We validate these analytical strategies through a case study in major depressive disorder, specifically by intersecting m6A effects with psychiatric genetic risk. By streamlining these workflows, we provide a roadmap for formulating testable hypotheses regarding epitranscriptome-targeted therapeutic interventions in psychiatric disorders.

PMID:42184108 | DOI:10.1093/bib/bbag251

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Nevin Manimala Statistics

Comparative review of artificial intelligence for transcriptomic biomarker discovery in coronavirus disease 2019 (COVID-19)

Brief Bioinform. 2026 May 4;27(3):bbag249. doi: 10.1093/bib/bbag249.

ABSTRACT

The Coronavirus Disease 2019 (COVID-19) pandemic has highlighted the significance of reliable molecular biomarkers in clinical use. Despite the popularity of traditional statistical approaches, the high dimensionality of transcriptomic data presents challenges for these conventional methods. While artificial intelligence (AI) algorithms have emerged as highly advantageous for handling these complex datasets, there is a lack of evaluation of these approaches in COVID-19 transcriptomic studies. This review aims to provide an evaluation of these studies employed for transcriptomic biomarker discovery in COVID-19 using AI, assessing their study designs, methodologies, and outcomes. Based on a comprehensive search for literature across five databases including Web of Science Core Collection, Scopus, PubMed/MEDLINE, IEEE Xplore Digital Library, and LitCovid from December 2019 to March 2025, this review selected 63 studies for a narrative synthesis of four key sections: (i) The Landscape of AI-Driven COVID-19 Transcriptomics, (ii) Limitations of Studies, (iii) A Proposed AI-Driven Transcriptomics Framework, and (iv) Clinical Translation Challenges, Opportunities, and Future Directions. Our analysis revealed limitations in data quality, sample size, and heterogeneity, as well as methodologies regarding validation and interpretability. Thus, we proposed an evidence-informed workflow that addresses these current limitations in study design, while acknowledging real-world constraints. We further discuss the emerging potential of agentic AI systems as a promising solution to current limitations. By bridging methodological gaps with translation considerations, this review can enhance pandemic response strategies for future emerging infectious diseases. Key Points Applications observed in reviewed studies mainly included applications in diagnosis and severity stratification of COVID-19 patients. The limitations of current studies included small sample sizes, the reliance on public datasets lacking detailed metadata, batch effects and data heterogeneity reducing model robustness, the lack of external validation, risks of data leakage and circular validation leading to inflated performance metrics, and challenges in model interpretability. An evidence-informed AI-driven framework is proposed, acknowledging real-world constraints including small pandemic cohort sizes, domain shift from viral evolution, and resource-limited settings, with emerging agentic AI systems offering potential solutions.

PMID:42184107 | DOI:10.1093/bib/bbag249

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Nevin Manimala Statistics

Cerebral Venous Sinus Thrombosis in Pediatric Critical Care

Crit Care Explor. 2026 May 25;8(6):e1418. doi: 10.1097/CCE.0000000000001418. eCollection 2026 Jun 1.

ABSTRACT

IMPORTANCE: Pediatric cerebral venous sinus thrombosis (CVST) is being increasingly recognized and can pose substantial risks of morbidity and mortality. Data on the epidemiology, management, and outcomes of CVST in the PICU remain limited.

OBJECTIVES: To describe the clinical characteristics, management, and outcomes of critically ill children with CVST during their admission to the PICU.

DESIGN, SETTING, AND PARTICIPANTS: We conducted a retrospective observational cohort study in a quaternary PICU in Toronto, Canada, between 2018 and 2023. Patients 18 years old and younger with acute primary CVST (CVST being the primary indication for ICU admission) and secondary CVST (diagnosis during an admission for an alternative diagnosis) were included in this study.

MAIN OUTCOMES AND MEASURES: The primary outcome was in-hospital mortality. Descriptive statistics were used to describe characteristics and outcomes.

RESULTS: Thirty patients were admitted with a diagnosis of CVST: 19 (63%) primary, 11 (37%) secondary. Fourteen (47%) had an associated cerebral infarct, and nine (30%) had an associated intracranial hemorrhage. The most common condition associated with secondary CVST was a brain disease requiring neurosurgical intervention (5/11). Five (17%) children with CVST died in this study, of which four had a primary CVST. Children residing in neighborhoods with increased marginalization were disproportionally represented in this cohort.

CONCLUSIONS AND RELEVANCE: Primary CVST is more common than secondary and is associated with significant mortality. The disproportionate impact on marginalized children emphasizes the need for heightened awareness and determination of factors associated with this finding.

PMID:42184099 | DOI:10.1097/CCE.0000000000001418

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Nevin Manimala Statistics

Trend of Adjuvant Radiation in Resected Pancreatic Ductal Adenocarcinoma: Evaluation of RTOG 0848 with a Large National Database

J Gastrointest Cancer. 2026 May 25;57(1):124. doi: 10.1007/s12029-026-01492-0.

ABSTRACT

PURPOSE: Adjuvant radiation (AR) remains a controversial treatment modality for pancreatic ductal adenocarcinoma (PDAC). This study aimed to evaluate the findings of the RTOG 0848 trial assessing the benefits of adjuvant radiation in node-negative disease utilizing a national database.

METHODS: Utilizing the National Cancer Database, all patients diagnosed with non-metastatic PDAC, who underwent pancreatectomy, were included (2004-2019). The trend of adjuvant radiation utilization was evaluated. Overall survival in a cohort of patients mimicking the RTOG 0848 protocol was examined as were clinicodemographic and pathologic predictors of adjuvant radiation.

RESULTS: Overall rates of adjuvant radiation decreased from 45 to 12%, while neoadjuvant radiation rates simultaneously increased from 4 to 12%. Positive margins and nodal disease were the strongest predictors of adjuvant radiation receipt (OR 1.7[ 95% CI: 1.6-1.7] p < 0.001 and OR: 1.1 [95% CI: 1.1-1.2] p < 0.001; respectively). Both high-risk pathologic groups experienced a decline in the use of adjuvant radiation over time, even after exclusion of patients who received neoadjuvant radiation. After application of the RTOG 0848 criteria, improved overall survival was observed in patients with node-negative and positive margins (adjuvant radiation: 28.6 [95% CI: 25.4-31.8] vs 23.0 [95% CI: 19.4-26.7] months; p = 0.005). In the margin positive cohort, adjuvant radiation was significantly associated with reduced mortality (HR: 0.791 [95% CI: 0.7-0.9]; p < 0.001).

CONCLUSION: Evaluation of RTOG 0848 in the setting of real-world data indicates a role for adjuvant radiation for patients with margin-positive, node-negative pancreatic cancer. This highlights the essential role of multidisciplinary discussions regarding patients with PDAC care.

PMID:42184090 | DOI:10.1007/s12029-026-01492-0

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Nevin Manimala Statistics

Identification of precursor origins of synthetic graphite anodes in lithium-ion batteries using LDI-MS and multivariate analysis

Nano Converg. 2026 May 25;13(1):21. doi: 10.1186/s40580-026-00551-3.

ABSTRACT

Synthetic graphites have been widely used in industrial applications, including as anodes in lithium-ion batteries. Because they are produced at temperatures above 3000 °C, which generate highly ordered graphitic domains, there is typically no discernible evidence of their precursor materials. In this study, three types of graphite, coal tar based anisotropic graphite, petroleum fluid oil based anisotropic graphite, and coal tar based isotropic graphite, were prepared. Conventional characterization techniques such as X-ray diffraction, Raman spectroscopy, transmission electron microscopy, and even electrochemical performance were unable to distinguish their precursors. Therefore, we introduced laser desorption/ionization time-of-flight mass spectrometry (LDI-MS) combined with multivariate statistical analysis to characterize three graphites prepared from different synthetic precursors as well as two commercial graphites. The resulting LDI-MS spectra were analyzed using principal component, hierarchical cluster, and heatmap analyses, which are widely used in clinical mass spectrometric diagnostics. Notably, LDI-MS coupled with multivariate statistics successfully classified the graphites depending on their precursor materials and processing parameters, such as heat-treatment temperature, whereas conventional analytical tools failed to reveal these differences. These results clearly demonstrate the strong potential of LDI-MS and statistical analysis for the precise characterization of carbon materials and for distinguishing their origins and processing routes.

PMID:42184059 | DOI:10.1186/s40580-026-00551-3

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Nevin Manimala Statistics

Epidemiological, Clinical, and Socioenvironmental Characteristics of Cutaneous Leishmaniasis Cases in the Xakriabá Indigenous Population, Brazil

Acta Parasitol. 2026 May 25;71(3):122. doi: 10.1007/s11686-026-01312-2.

ABSTRACT

BACKGROUND: Cutaneous leishmaniasis (CL) remains a neglected tropical disease that disproportionately affects indigenous populations, where transmission is shaped by complex socioenvironmental conditions. Our objective is to describe and analyze the sociodemographic, environmental, clinical, and therapeutic characteristics of CL cases in the Xakriabá indigenous population, and to explore associations between these characteristics and clinical outcomes.

METHODS: An observational analytical study based on a case series was conducted using secondary data from the Brazilian Notifiable Diseases Information System (SINAN), covering the period from 2013 to 2024. Analyses were restricted to internal associations among reported cases, without inference of population-level risk. Sociodemographic, environmental, clinical, and therapeutic variables were analyzed using descriptive statistics and logistic regression models.

RESULTS: A total of 259 CL cases were identified. Most cases occurred in males (63%) and individuals aged 20-39 years (38%), with nearly all cases residing in rural areas (99%). Associations were observed between clinical outcomes and variables such as occupational exposure (OR = 2.45; 95% CI 1.38-4.33) and proximity to vegetation (OR = 2.71; 95% CI 1.49-4.92). These findings represent associations within the case population and should not be interpreted as causal effects or population risk estimates. A high proportion of missing laboratory data was identified. Spatial distribution was described without inferential analysis.

CONCLUSION: CL in the Xakriabá population is characterized by heterogeneous distribution and associations with socioenvironmental factors within reported cases. Given the study design, results should be interpreted cautiously, without causal inference. Strengthening diagnostic capacity, improving data quality, and implementing territorially adapted public health strategies are essential to improve disease management in indigenous contexts.

PMID:42184053 | DOI:10.1007/s11686-026-01312-2

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Nevin Manimala Statistics

Mindfulness-based cognitive-behavioral therapy improves sexual quality of life and reduces sexual distress in pregnant women

Discov Ment Health. 2026 May 25. doi: 10.1007/s44192-026-00366-y. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Pregnancy is accompanied by numerous physical and psychological changes that can affect sexual quality of life and increase sexual distress in women. Identifying effective interventions to address these issues is essential. This study aimed to evaluate the effect of mindfulness-based cognitive-behavioral therapy on sexual distress and sexual quality of life in pregnant women.

METHODS: In this single-blind randomized clinical trial, 84 pregnant women (20-35 weeks of gestation) were randomly assigned to an intervention group (n = 40) or a control group (n = 41) using a block design. The intervention group participated in seven weekly sessions of mindfulness-based cognitive therapy. Data were collected using a demographic questionnaire, the Sexual Quality of Life-Female (SQOL-F) questionnaire, and the Female Sexual Distress Scale (FSDS).

RESULT: At baseline, there were no statistically significant differences between the two groups in demographic characteristics, sexual distress, or sexual quality of life. Repeated measures analysis showed significant improvements in the intervention group compared with the control group in overall sexual quality of life and its dimensions (psychosexual feelings, sexual and relationship satisfaction, self-worthlessness, and sexual repression). Sexual distress scores were also significantly reduced in the intervention group after the intervention and at follow-up.

DISCUSSION: Mindfulness-based cognitive-behavioral therapy appears to be an effective approach for enhancing sexual quality of life and reducing sexual distress in pregnant women. Integrating this intervention into prenatal care services may help promote the overall well-being of expectant mothers.

TRIAL REGISTRATION: This study was approved by the Ethics Committee of Ahvaz Jundishapur University of Medical Sciences (IR.AJUMS.REC.1399.135) and registered in the Iranian Registry of Clinical Trials (IRCT20200901048581N1) on September 21, 2020.

PMID:42184044 | DOI:10.1007/s44192-026-00366-y