Tag: nevin manimala

Horm Behav. 2025 Sep 25;176:105821. doi: 10.1016/j.yhbeh.2025.105821. Online ahead of print.

ABSTRACT

The care that a mother rat provides is essential for the ability of her pups to survive and thrive. Maternal care naturally varies between litters, including among animals with close genetic relatedness. There are also significant differences in behavior even among offspring reared together. Our lab and others have documented stable, naturally occurring individual differences in maternal care received by individual pups within the litter that persist throughout at least the first ten days of postnatal life. In this study, we hypothesized that within-litter variation in maternal care received constitutes a significant source of variation in offspring behavior and neurochemistry in Long-Evans rats. We analyzed measures related to maternal care behavior, offspring anxiety-like and social behaviors, and neurotransmitter levels in specific brain regions after the offspring became mothers themselves. For statistical modeling, we used the coefficient of variation (CV) to standardize and directly compare between- and within-litter variation across a range of behavioral and neurophysiological outcomes. Several variables analyzed showed greater within-litter CVs than between-litter CVs, especially for offspring behavior and levels of the monoamines dopamine, serotonin, and their primary metabolites DOPAC (3,4-dihydroxyphenylacetic acid) and 5-HIAA (5-hydroxyindoleacetic acid) in the nucleus accumbens, ventral tegmental area, medial preoptic area, hippocampus, and prefrontal cortex. Our findings suggest that within-litter variation in maternal care plays a prominent role in behavioral and physiological outcomes. This study provides a methodological advance by demonstrating that within-litter variability often exceeds between-litter variability across maternal, behavioral, and neurochemical domains, challenging a key assumption in experimental designs using littermate controls.

PMID:41004891 | DOI:10.1016/j.yhbeh.2025.105821

Appl Radiat Isot. 2025 Sep 23;226:112204. doi: 10.1016/j.apradiso.2025.112204. Online ahead of print.

ABSTRACT

There are very few radioactive environmental reference materials (RM) traceable to the International System of Units. Existing radioactive RMs for environmental samples that can be measured by mass spectrometry are even more limited and their characterisation does not always include relevant parameters such as isotopic ratios. This paper focuses on the development of two environmentally relevant candidate RMs, one liquid and one solid, which could be used for routine quality control measurements. The liquid RM was prepared by spiking seawater sampled from the North Sea, and therefore the matrix is representative of a real environmental sample, while the solid RM was prepared using a synthetic approach by spiking a mixture of silica precursors before a sol-gel reaction. The homogeneity, between-bottles and within-bottles, of both RMs was assessed using gamma-ray spectrometry and mass spectrometry. For the liquid RM, the variation among sub-samples was due mainly to the within-bottle variance, and was lower than 1 %, for all the radionuclides tested. For the solid RM, the ²⁴¹Am content measured with gamma-ray spectrometry revealed a statistically significant variation between-bottles, but was lower than 1 %. The ²³⁸U and ²³⁹Pu contents, measured by mass spectrometry, showed higher measurement variability (∼5 %), with the main contribution coming from within the bottles.

PMID:41004888 | DOI:10.1016/j.apradiso.2025.112204

Curr Res Transl Med. 2025 Sep 19;73(4):103544. doi: 10.1016/j.retram.2025.103544. Online ahead of print.

ABSTRACT

BACKGROUND: Ensuring accurate statistical reporting is critical in oncology research, where data-driven conclusions impact clinical decision-making. Despite standardized guidelines such as the Statistical Analyses and Methods in the Published Literature (SAMPL), adherence remains inconsistent. This study evaluates the performance of Gemini Advanced 2.0 Flash, an AI model, in assessing compliance with SAMPL guidelines in oncology research articles.

METHODS: A total of 100 original research articles published in four peer-reviewed oncology journals (October 2024-February 2025) were analyzed. Gemini Advanced 2.0 Flash assessed adherence to ten key SAMPL guidelines, categorizing each as “not met,” “partially met,” or “fully met.” AI evaluations were compared with independent assessments by a statistical editor, with agreement quantified using Cohen’s Kappa coefficient.

RESULTS: The overall weighted Kappa coefficient was 0.77 (95 % CI: 0.6-0.94), indicating substantial agreement between AI and manual assessment. Full agreement (Kappa = 1) was found for four guidelines, including naming statistical packages and reporting confidence intervals. High agreement was observed for specifying statistical methods (Kappa = 0.85) and confirming test assumptions (Kappa = 0.75). Moderate agreement was noted for summarizing non-normally distributed data (Kappa = 0.42) and specifying test directionality (Kappa = 0.43). The lowest agreement (Kappa = 0.37) was observed in multiple comparison adjustments due to missing justifications for post hoc tests.

CONCLUSION: AI-assisted evaluation showed substantial agreement with expert assessment, demonstrating its potential in statistical review. However, discrepancies in specific guidelines suggest human oversight remains essential for ensuring statistical rigor in oncology research. Further refinement of AI models may enhance their reliability in scientific publishing.

PMID:41004884 | DOI:10.1016/j.retram.2025.103544

Eur J Oncol Nurs. 2025 Jul 24;78:102944. doi: 10.1016/j.ejon.2025.102944. Online ahead of print.

ABSTRACT

PURPOSE: To statistically characterise both contemporaneous and temporal symptom networks to identify robust, stage-specific intervention targets.

METHODS: We conducted a prospective cohort study of patients with stage I-III breast cancer who completed the MD Anderson Symptom Inventory across each of four chemotherapy cycles (T1-T4, April 2024 to June 2025). Exploratory factor analysis (EFA) first identified co-occurring symptom clusters, which informed the construction of cycle-specific cross-sectional networks via Gaussian graphical models and bridge centrality metrics. We then built cross-lagged panel networks to estimate directed symptom effects across successive cycles and applied non-parametric bootstrapping to derive confidence intervals and assess network stability.

RESULTS: A total of 153 patients completed data collection across four chemotherapy cycles. Parallel analysis showed three relatively stable symptom clusters across the first three chemotherapy cycles (T1-T3), but consolidation into two clusters occurred at the final cycle (T4). Cross-sectional hubs influencing contemporaneous symptom interplay were identified via bridge symptoms in cycle-specific cross-sectional networks: loss of appetite (T1), sadness (T2, T3), and numbness (T4). The core temporal drivers predicting future symptom cascades were identified via cross-lagged panel networks (CLPNs): shortness of breath (T1→T2), sadness (T2→T3), and somnolence (T3→T4). The precision of edge-weight yielded narrow to moderate 95 % confidence intervals (CI) for both cross-sectional and longitudinal networks. Case-drop bootstrapping (1000 iterations) demonstrated moderate to strong stability in the rank order of centrality indices.

CONCLUSIONS: Our integrative network approach reveals a dynamic, dual-mechanistic symptom framework (cross-sectional and temporal key symptom drivers): early intervention should target somatic symptoms, mid-treatment efforts should disrupt psychological amplifiers, and late cycles require attention to neurotoxic perpetuators. This phase-specific roadmap offers precision in symptom management for patients undergoing chemotherapy.

PMID:41004877 | DOI:10.1016/j.ejon.2025.102944

Top Magn Reson Imaging. 2025 Sep 29;34(3):e0319. doi: 10.1097/RMR.0000000000000319. eCollection 2025 Oct 1.

ABSTRACT

BACKGROUND AND AIM: Magnetic resonance imaging (MRI) is essential for diagnosis but often induces anxiety, especially in claustrophobic patients, potentially affecting image quality. This study compared oxygen saturation, heart rate, and anxiety levels between claustrophobic and non-claustrophobic patients undergoing closed and open MRI in Erbil, Iraq.

MATERIAL AND METHODS: The comparative study was conducted from October 2024 to April 2025 in the Radiology Departments of Consultant Medical City and Top Med Medical Complex Centers in Erbil using purposive sampling. The questionnaire contained 3 sections: sociodemographic variables, the Claustrophobia Questionnaire, and the State-Trait Anxiety Inventory-State Subscale. Physiological measures (oxygen saturation and heart rate) were recorded at 3 timepoints: pre-, mid-, and post-MRI. Statistical analyses included one-way ANOVA, repeated measures ANOVA, post hoc tests, and both univariate and multiple linear regression, using SPSS version 26.

RESULTS: A total of 125 participants were involved in the study. The mean anxiety score was moderate, with higher levels in claustrophobic patients. Claustrophobia scores also fell within the moderate range, indicating psychological discomfort during the MRI procedure. Physiological measurements showed that claustrophobic patients, particularly those undergoing closed MRI, experienced elevated heart rates and reduced oxygen saturation compared to non-claustrophobic individuals. Statistical analysis indicated a strong positive association between anxiety and claustrophobia, with scan entry direction, age, and sex also being significant predictors of claustrophobic responses.

CONCLUSIONS: Claustrophobic patients undergoing closed MRI experience increased anxiety and physiological distress. Open MRI systems and pre-scan anxiety screening are recommended to enhance patient comfort and diagnostic outcomes.

PMID:41004856 | DOI:10.1097/RMR.0000000000000319

J Neurosurg Pediatr. 2025 Sep 26:1-9. doi: 10.3171/2025.5.PEDS24631. Online ahead of print.

ABSTRACT

OBJECTIVE: The authors’ objective was to assess the impact of telehealth on pediatric neurosurgical care access for underserved and rural populations in West Virginia. The authors explored how telehealth utilization varied over time, the socioeconomic benefits it provided to families, and its effect on visit completion rates compared with in-person appointments.

METHODS: Clinic visits from January 1, 2017, to May 31, 2023, at the sole pediatric neurosurgery clinic in West Virginia were retrospectively reviewed. The data included three types of outpatient visits: in-person, telemedicine satellite clinic, and MyChart video appointments. Initial statistical analysis focused on visit completion rates, distance traveled, and time and cost savings for families. Additional geospatial analysis used heat density mapping to recognize regional utilization patterns, and community-level socioeconomic variables were analyzed for correlation with visit type utilization.

RESULTS: Telehealth usage (telemedicine and MyChart) increased significantly during and after the COVID-19 pandemic. MyChart visits demonstrated the highest completion rates postpandemic. Telehealth visits saved families substantial travel time and cost, especially for those living more than 100 miles from the clinic. Geospatial analysis revealed that telemedicine usage was clustered in specific Appalachian regions, and in-person visits were more common among patients from economically distressed communities. Correlation analysis showed that higher poverty and unemployment rates were associated with in-person visit reliance, while telehealth adoption was lower in these populations.

CONCLUSIONS: Telehealth significantly enhances access to pediatric neurosurgical care for rural and economically disadvantaged families, reducing travel-related burdens and increasing visit adherence. However, economically distressed communities in Appalachia are less likely to use telehealth, possibly due to digital access issues or skepticism about remote care. Addressing these barriers is crucial to ensure equitable healthcare access. Further research should investigate structural and personal obstacles to telehealth uptake to improve service delivery for at-risk populations, ultimately fostering more inclusive and accessible healthcare options in remote areas.

PMID:41004850 | DOI:10.3171/2025.5.PEDS24631

J Neurosurg. 2025 Sep 26:1-7. doi: 10.3171/2025.5.JNS243160. Online ahead of print.

ABSTRACT

OBJECTIVE: Digital enhancement and visualization technologies, such as augmented reality (AR), are increasingly used in surgery. Rapid and accurate patient registration with minimal device confinements enables AR systems to increase efficiency, safety, and effectiveness, especially in urgent/emergency and/or bedside scenarios. The aim of this study was to quantitatively compare an AR headset-based neuronavigation system with a standard-of-care reference array-based neurosurgical stereotactic navigation system in a real-world setting.

METHODS: This clinical validation trial included adult patients undergoing cranial neurosurgery with stereotactic navigation at a single center from February 2024 to July 2024. Preoperative CT and MR images were acquired and used for construction of a 3D hologram model that included surface-based target fiducial markers for comparison. Preoperative images were stereotactically registered to the patient’s head using standard techniques. The registration coordinates for the fiducial markers (control) and registration time were recorded. The AR system was then deployed to create a separate stereotactic registration to the same preoperative images. A second set of registration coordinates for the fiducial markers (experimental) were acquired using the AR system, and the time for this process was also recorded. The Wilcoxon signed-rank test was used to assess differences in registration time, and a linear mixed-effects model (LMM) was used to conduct equivalence testing of coordinates between the control and experimental data.

RESULTS: Twenty patients (mean age ± SD 50.05 ± 14.38 years) were included in the trial. The mean baseline validation error of the control system was 0.73 ± 0.29 mm (range 0-1.0 mm). Using the control system as ground truth, the mean registration accuracy of the AR system was 2.16 ± 0.12 mm. LMM equivalence testing, conducted with margins of 3 mm and 2.5 mm, demonstrated statistical equivalence between the ground truth and AR system coordinates (p < 0.001 and p < 0.003, respectively). The time required for patient model registration using the AR system was a mean of 45.98 ± 15.00 seconds, which was significantly shorter compared with the control system (228.86 ± 100.06 seconds, p < 0.001).

CONCLUSIONS: The AR navigation system provided statistically similar registration accuracy and significantly faster patient model registration compared with the standard-of-care stereotactic neuronavigation system. AR navigation was accurate, fast, and had a minimal footprint, offering new opportunities to incorporate stereotaxis in low-resource, bedside, and urgent/emergency settings.

PMID:41004845 | DOI:10.3171/2025.5.JNS243160

J Comput Assist Tomogr. 2025 Sep 23. doi: 10.1097/RCT.0000000000001802. Online ahead of print.

ABSTRACT

OBJECTIVE: To assess whether few-shot prompting improves the performance of 2 popular large language models (LLMs) (ChatGPT o1 and DeepSeek-R1) in assigning Coronary Artery Disease Reporting and Data System (CAD-RADS™ 2.0) categories.

METHODS: A detailed few-shot prompt based on CAD-RADS™ 2.0 framework was developed using 20 reports from the MIMIC-IV database. Subsequently, 100 modified reports from the same database were categorized using zero-shot and few-shot prompts through the models’ user interface. Model accuracy was evaluated by comparing assignments to a reference radiologist’s classifications, including stenosis categories and modifiers. To assess reproducibility, 50 reports were reclassified using the same few-shot prompt. McNemar tests and Cohen kappa were used for statistical analysis.

RESULTS: Using zero-shot prompting, accuracy was low for both models (ChatGPT: 14%, DeepSeek: 8%), with correct assignments occurring almost exclusively in CAD-RADS 0 cases. Hallucinations occurred frequently (ChatGPT: 19%, DeepSeek: 54%). Few-shot prompting significantly improved accuracy to 98% for ChatGPT and 93% for DeepSeek (both P<0.001) and eliminated hallucinations. Kappa values for agreement between model-generated and radiologist-assigned classifications were 0.979 (0.950, 1.000) (P<0.001) for ChatGPT and 0.916 (0.859, 0.973) (P<0.001) for DeepSeek, indicating almost perfect agreement for both models without a significant difference between the models (P=0.180). Reproducibility analysis yielded kappa values of 0.957 (0.900, 1.000) (P<0.001) for ChatGPT and 0.873 [0.779, 0.967] (P<0.001) for DeepSeek, indicating almost perfect and strong agreement between repeated assignments, respectively, with no significant difference between the models (P=0.125).

CONCLUSION: Few-shot prompting substantially enhances LLMs’ accuracy in assigning CAD-RADS™ 2.0 categories, suggesting potential for clinical application and facilitating system adoption.

PMID:41004838 | DOI:10.1097/RCT.0000000000001802

J Gastrointestin Liver Dis. 2025 Sep 26;34(3):309-316. doi: 10.15403/jgld-6433.

ABSTRACT

BACKGROUND AND AIMS: Small bowel neuroendocrine neoplasms (SB-NENs) are a rare type of tumor that is clinically challenging and is often diagnosed in advanced stages. This retrospective study aimed to characterize the clinical presentation, diagnostic workup, and therapeutic strategies, as well as to evaluate the prognosis of patients managed in a tertiary care center in Bucharest, Romania, over five years.

METHODS: We conducted an observational, retrospective cohort study on 42 cases of SB-NEN evaluated at our center between January 1, 2020, and March 31, 2025. Data regarding clinicopathological characteristics, treatments, and disease evolution were summarized. Overall survival was estimated at 1, 3, and 5 years.

RESULTS: Computed tomography was the most frequently used imaging method for diagnosis (52.4%). Surgery was the most adopted method for obtaining the pathological specimen, used in 70.7% of cases. The majority of tumors were well-differentiated (85.6%). The overall survival distribution showed a median survival time of 94 months. The cumulative proportion of patients surviving at 1 year was 97.6%, at 3 years was 89.3% and at 5 years was 75.7%. There was a significant difference in overall survival stratified by tumor grading (p=0.006), indicating that this was a significant prognostic factor; the metastatic status and large tumors showed a trend toward statistical significance, but they did not meet the conventional threshold (p=0.068 and 0.103, respectively).

CONCLUSIONS: SB-NEN showed favorable outcomes, with surgery improving survival even in some metastatic cases. Lower tumor grade was associated with a better prognosis, while somatostatin analogues (SSA) therapy showed no survival benefit. Patients with large tumors and metastatic disease also showed a trend towards reduced survival.

PMID:41004806 | DOI:10.15403/jgld-6433

J Glob Health. 2025 Sep 26;15:04122. doi: 10.7189/jogh.15.04122.

ABSTRACT

BACKGROUND: Sleep problems are common among children and mothers. However, little is understood about sleep behaviours in low- and middle-income countries. Here we examine sleep behaviours and predictors among black, low-income, South African mothers and their eight-year-old children over time.

METHODS: We administered standardised measures of sleep behaviours at eight years post-birth to a population cohort of mothers and children in 24 neighbourhoods of Cape Town, South Africa, in 2009-10. We assessed mothers and children six times over eight years with 84% retention since pregnancy. While 71% remained in Cape Town, about 29% of households moved to the profoundly rural Eastern Cape of South Africa. Mothers completed the Pittsburgh Sleep Quality Index and rated their children on the Children’s Sleep Habits Questionnaire.

RESULTS: Among mothers, 29.5% reported sleep difficulties based on their global sleep score, with a mean sleep quality score of 3.72 (standard deviation (SD) = 2.6). Children’s sleep scores were 64.4 (SD = 4.0), with subscale scores on sleep difficulties higher than documented in high-income countries (HICS). There was a relatively low inverse relationship between the quality of maternal and child sleep (r = -0.201; 95% confidence interval (CI) = -0.264, -0.136), which resulted in an R² value of 0.041 in the simple linear regression model. Problematic maternal sleep was associated with living in the rural Eastern Cape (P = 0.034), experiencing intimate partner violence (P = 0.052), and a higher score on the Edinburgh Postnatal Depression Scale (P < 0.001), but not alcohol use. Children’s sleep difficulties decreased by 0.191 points (95% CI = -0.229, -0.152) with a one-unit increase in aggressive behaviour and, similarly, cognitive scores decreased by 0.035 points (95% CI = -0.063, -0.006). Household resources, such as formal vs. informal housing, income, and having water on the premises, were unrelated to sleep difficulties.

CONCLUSIONS: Counter to hypotheses, a small, inverse relationship existed between mothers’ and children’s sleep behaviours. Alcohol use, HIV status, and socioeconomic markers were unrelated to sleep, but intimate partner violence and depressive symptoms affect sleep negatively, similar to HICS.

PMID:41004805 | DOI:10.7189/jogh.15.04122