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Nevin Manimala Statistics

Childhood Maltreatment and Anxiety in Adulthood: Disentangling the Role of Personality Functioning

Psychol Rep. 2026 Apr 16:332941261441834. doi: 10.1177/00332941261441834. Online ahead of print.

ABSTRACT

Childhood maltreatment (CM), particularly emotional neglect and abuse, has been associated with an increased risk of anxiety and less favorable psychotherapy outcomes in adulthood. Impairments in personality functioning are a significant mechanism mediating this relation. This naturalistic cross-sectional study examined the mediating role of personality functioning in the relation between CM and anxiety symptoms in a clinical adult sample. A total of 335 adult patients starting individual psychotherapy completed intake self-report questionnaires about CM experiences, personality functioning, and anxiety symptoms. We assessed the two dimensions of personality functioning described in Section III of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), specifically, self-functioning and interpersonal functioning. Bootstrapped mediation analyses were conducted to evaluate the mediating role of personality functioning in the association between each CM type and anxiety symptoms. 64.2% of the sample reported at least one type of CM. Personality functioning explained 73% of the total effect of CM on anxiety symptoms. Only emotional abuse and emotional neglect showed significant total effects. Emotional abuse retained a direct effect, while emotional neglect was fully mediated by personality functioning. Both personality functioning dimensions were significant mediators, yet self-functioning had a larger impact. Psychotherapeutic interventions targeting impairments in personality functioning are essential for treating anxiety symptoms in adults with CM. Findings emphasize the importance of trauma-informed, personalized interventions, and CM prevention strategies.

PMID:41989126 | DOI:10.1177/00332941261441834

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Nevin Manimala Statistics

Thermal conductivities of monolayer graphene oxide from machine learning molecular dynamics simulations

J Chem Phys. 2026 Apr 21;164(15):154703. doi: 10.1063/5.0319735.

ABSTRACT

Graphene oxide (GO) exhibits rich chemical heterogeneity that strongly influences its structural, thermal, and mechanical properties, yet quantitatively linking reduction chemistry to heat transport remains challenging. In this study, we develop a machine-learned neuroevolution potential (NEP) trained on an existing density functional theory dataset [El-Machachi et al., Angew. Chem., Int. Ed. 63, e202410088 (2024)], achieving reasonable accuracy at a computational cost much lower than the existing machine-learned and empirical potentials. Leveraging this potential, we perform large-scale molecular dynamics (MD) simulations to model the thermal reduction of GO across realistic structural domains. Using the homogeneous nonequilibrium MD method with a proper quantum-statistical correction scheme, we find that reduced GO exhibits strongly suppressed thermal conductivities, ranging from a few to tens of Wm-1 K-1, substantially lower than pristine GO without defects and far below graphene. Moreover, the thermal conductivity of reduced GO increases moderately with increasing OH/O ratio, except at the highest oxidation level (O/C = 0.5), where this trend inverts, while decreasing significantly with increasing O/C ratio, a trend strongly correlated with the fraction of recovered graphene-like structures. Our study provides a computationally tractable and predictive atomistic machine learning framework for exploring how chemical structure governs heat transport in heterogeneous carbon materials.

PMID:41989114 | DOI:10.1063/5.0319735

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Nevin Manimala Statistics

Response to “Comment on ‘Unsupervised Machine Learning for Differential Analysis in Proteomics’ ”

Anal Chem. 2026 Apr 16. doi: 10.1021/acs.analchem.6c00512. Online ahead of print.

ABSTRACT

In this response, we address key points by commentators on our previous article, “Unsupervised Machine Learning for Differential Analysis in Proteomics” (DOI: 10.1021/acs.analchem.5c03117), concerning the choice and characteristics of statistical testing and machine learning (ML) in differential proteomics. We clarify that while certain ML methods are statistically grounded, many operate on distinct nonparametric principles, offering an alternative approach when data violate standard distributional assumptions or exhibit complex multivariate structures. We also want to clarify our position that ML is proposed not as a replacement for established statistical frameworks but as a valuable expansion of the analytical toolbox, particularly useful in exploratory analysis or with heterogeneous data. We emphasize methodological pluralism, advocating for the combined use of ML and statistical methods across different stages of research, from hypothesis generation to confirmatory testing, to better address the diverse challenges in precision proteomics and to enrich biological discovery.

PMID:41989104 | DOI:10.1021/acs.analchem.6c00512

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Nevin Manimala Statistics

Prognosis of Tricuspid Regurgitation after Mitral Transcatheter Edge-to-Edge Repair: The EXPANDed Studies

ESC Heart Fail. 2026 Apr 16:xvag108. doi: 10.1093/eschf/xvag108. Online ahead of print.

ABSTRACT

BACKGROUND: Transcatheter therapies offer new treatment options for patients with both mitral regurgitation (MR) and tricuspid regurgitation (TR). However, the optimal treatment pathway in patients with combined MR and TR is not completely understood.

AIMS: This analysis evaluated the natural TR progression after mitral transcatheter edge-to-edge repair (MTEER) with the MitraClip System in patients with MR and TR from the EXPANDed studies.

METHODS: EXPANDed is a pooled cohort from the EXPAND and EXPAND G4 studies. This study includes patients who had severe TR, achieved procedural success with MTEER, and received no direct TR intervention. Echocardiographic assessments were performed independently by echo core lab. Baseline characteristics, 1-year outcomes, and associations with TR improvement were reported based on 30-day TR severity following MTEER.

RESULTS: Of those with evaluable TR data at 30 days (N=160), 73% (N=116) improved to ≤moderate TR, while 28% (N=44) had ≥severe TR. The ≤moderate TR group had a lower prevalence of atrial fibrillation (68% vs 89%, p=0.009), numerically lower LV ejection fraction (49% vs 56%, p=0.07), and larger LV dimensions (LVEDV: 137.5±73.4 vs 107.9±44.8 ml, p=0.01). TR reduction was sustained in 86% of ≤moderate TR patients, while 45% of ≥severe TR patients improved to ≤moderate at 1 year. In the ≤moderate TR group, significant and larger improvements in NYHA functional class (p<0.0001) and KCCQ-OS score (Δ = +30.6±25.7, p<0.0001) were observed through 1 year. One-year mortality was numerically lower in the ≤moderate TR group (12.4% vs 22.3%) though not statistically significant (HR=1.92 [0.77, 4.79], p=0.16). Lower LVEF and larger baseline LV size were associated with TR improvement post-MTEER.

CONCLUSIONS: Early TR improvement to ≤moderate was observed in almost 3/4 of the population and was associated with significant symptomatic relief. Patients with both severe MR and TR, particularly those with LV dilation, may experience TR improvement following MTEER.

PMID:41989098 | DOI:10.1093/eschf/xvag108

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Nevin Manimala Statistics

Rehabilitation and dosing practice for individuals with cerebral palsy in Indonesia: a survey of physiotherapists and occupational therapists

Disabil Rehabil. 2026 Apr 16:1-16. doi: 10.1080/09638288.2026.2647439. Online ahead of print.

ABSTRACT

PURPOSE: Although rehabilitation is vital for cerebral palsy (CP), in Indonesia, where the prevalence is high, practices are understudied. This study aimed to describe rehabilitation practice, explore perceptions of service delivery, and examine how dosage correlated with perceptions to inform strategies.

METHODS: A total of 233 Indonesian therapists (83% physiotherapists; 17% occupational therapists) completed an anonymous online survey between February and April 2025. Survey developed from existing literature and validated through expert review. The survey captured dosage and perceptions of service-related factors (Likert scale). Data were analyzed using descriptive statistics and correlations.

RESULTS: Therapists reported using both recommended evidence-based practices (e.g., mobility training) and non‑recommended practices (e.g., neurodevelopmental therapy). Rehabilitation typically lasted 30-45 min, 1-2 times/week, with limited agreement on strong evidence-based practice (EBP) exposure, adequate workforce, and families’ financial readiness. Therapy time correlated with positive perceptions of EBP exposure (p < 0.001, r = 0.305), skill set (p = 0.001, r = 0.244), infrastructure (p = 0.001, r = 0.239), and workforce (p = 0.002, r = 0.231). Moreover, institutional support for training showed the strongest association with greater EBP exposure (p < 0.001, r = 0.700).

CONCLUSION: In Indonesia, rehabilitation practice stays below recommended dosages, mirroring trends elsewhere. Barriers include families’ financial constraints, limited workforce, and insufficient exposure to EBP. Institutional support for training is vital for improving therapy and EBP adoption. Increasing the therapist workforce through new programs could enhance the delivery of CP services.

PMID:41989062 | DOI:10.1080/09638288.2026.2647439

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Nevin Manimala Statistics

Performance Is Not All You Need! Comment on “Unsupervised Machine Learning for Differential Analysis in Proteomics”

Anal Chem. 2026 Apr 16. doi: 10.1021/acs.analchem.5c06848. Online ahead of print.

ABSTRACT

In their recently published article (DOI: 10.1021/acs.analchem.5c03117), Xu et al. argue that the detection of differentially abundant proteins in proteomic experiments should go beyond traditional statistical methods and should leverage unsupervised machine learning for anomaly detection. Shedding light on this category of methods is insightful, and the reported performances are promising. However, we believe the benchmarking angle of this article is restrictive. First, the reported performance increments are associated with overstated theoretical differences. Second, an excessive focus on the performances could lead proteomic investigators to undermine their usual elicitation of the biological question. As both reasons pertain to the researchers’ empowerment of machine learning tools and of computational workflows, we believe it is important to formulate complementary guidelines.

PMID:41989059 | DOI:10.1021/acs.analchem.5c06848

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Nevin Manimala Statistics

Brain tissue perfusion during pulmonary endarterectomy – The impact of controlled regional cooling

Perfusion. 2026 Apr 16:2676591261429813. doi: 10.1177/02676591261429813. Online ahead of print.

ABSTRACT

BackgroundOpen pulmonary endarterectomy (PEA) carries a high risk of neurological complications due to cerebral hypoperfusion and ischemia-reperfusion injury. Systemic cooling during extracorporeal circulation may not sufficiently reduce brain temperature. Combining systemic and targeted head-neck cooling may enhance neuroprotection.MethodsIn this single-center retrospective study, 22 PEA patients were analyzed. All underwent deep systemic hypothermia (22-24°C). Eleven received adjunctive external head cooling using the Aurora head-neck device, and eleven used ice packs (Control). Cerebral oxygenation was monitored with near-infrared spectroscopy (NIRS), and neuron-specific enolase (NSE) levels were measured preoperatively and postoperatively.ResultsCerebral desaturation events (rSO2 < 40%) occurred in 22.2% of Aurora patients versus 77.8% of Controls (p = 0.030). Postoperative NSE levels were lower in the Aurora group; however, the difference did not reach statistical significance (p = 0.087).ConclusionDual-modality cooling combining extracorporeal hypothermia and targeted head-neck cooling improved intraoperative cerebral oxygenation and were associated with lower postoperative NSE levels; however, due to the limited sample size, no definitive conclusions regarding neuronal injury can be drawn.

PMID:41989018 | DOI:10.1177/02676591261429813

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Nevin Manimala Statistics

Effects of elevation, season and bait type on assemblage of forensically relevant blow flies (Diptera: Calliphoridae) in contrasting habitats of northwestern Arizona

Med Vet Entomol. 2026 Apr 16. doi: 10.1111/mve.70073. Online ahead of print.

ABSTRACT

Blow flies represent one of the most forensically significant insects in legal investigations. Their habitat-specific abundance and temperature-dependent development rates can help estimate a post-mortem interval (PMI), cause of death and post-mortem movement of a deceased body. As the role of forensic entomology expands in human and wildlife criminal investigations, there is a need for updated regional surveys for blow fly species. All recent and previous blow fly surveys in Arizona have been limited to the southern and central ecoregions. The objective of this study was to identify blow fly species between two contrasting habitats in northwestern Arizona-the Black Mountains (Mojave Desert) and the Hualapai Mountains (Arizona/New Mexico Mountains). This research aimed to assess the impacts of food source (game meat (javelina; Tayassu tajacu) compared to chicken (Gallus domesticus) liver), seasonality and elevation on blow fly biodiversity. Each habitat had three site locations at different elevational gradients (low, middle, high) with four bait traps deployed at each site (two of each bait type). This study found a significant difference in the biodiversity of blow flies between and within each habitat seasonally, as well as elevational variation within each habitat. Bait-preference also was statistically significant for overall abundance, and two indicator species for each bait type were identified. Additionally, this research presents the northernmost recorded presence of Chrysomya rufifacies in Arizona, as well as the first records of Cynomya cadaverina and Calliphora alaskensis in the state. The data collected establishes an important baseline for these understudied regions of Arizona and facilitates a wider use of blow flies in forensic investigations for rural areas of Mohave County, AZ.

PMID:41989004 | DOI:10.1111/mve.70073

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Nevin Manimala Statistics

Identifying context-specific community understanding of COVID-19 and mental health in Haiti, Malawi, and Rwanda

Glob Health Action. 2026 Dec;19(1):2627679. doi: 10.1080/16549716.2026.2627679. Epub 2026 Apr 16.

ABSTRACT

BACKGROUND: Community health workers (CHWs) play a vital role in spreading health-related information in low-and middle-income countries. Assessing their knowledge is crucial to combat health misinformation.

OBJECTIVE: To identify locally relevant COVID-19 and mental health-related information commonly held by CHWs and the misconceptions most prevalent in their communities in Haiti, Malawi, and Rwanda.

METHODS: A card-sorting activity was conducted with 39 CHWs from rural communities in Haiti (n = 13), Malawi (n = 12), and Rwanda (n = 14), between February and April 2023. The activity involved free sorting, true/false sorting, and card ranking to assess CHWs’ knowledge, beliefs, and misconceptions surrounding COVID-19 and mental health.

RESULTS: CHWs primarily categorized cards based on perceived truths, reflecting knowledge from trainings, media, and community beliefs. Overall, CHWs correctly identified 59% of true COVID-19 statements and 73% of false statements, with no statistical differences in COVID-19 knowledge rates among countries [correctly sorted as true: p = 0.421; correctly sorted as false: p = 0.128]. However, specific COVID-19 misconceptions varied across countries, such as beliefs about vaccine effectiveness and side effects. Mental health knowledge varied substantially across countries, with Haitian CHWs demonstrating the highest expertise in correctly identifying false mental health information [Haiti: median 86.0%; Malawi: median 21.0%; Rwanda: median 79.0%; p < 0.001)]. Significant misunderstandings about mental health causes and treatments were influenced by religious and spiritual beliefs.

CONCLUSION: CHWs have substantial gaps in information about COVID-19 and mental health. Knowledge of areas of misinformation can differ between countries. Constructing country-specific educational messages to address these areas can better inform CHWs and improve health literacy.

PMID:41988959 | DOI:10.1080/16549716.2026.2627679

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Nevin Manimala Statistics

Health care discrimination and self-reported health in transgender, gender nonconforming, and nonbinary individuals with cancer

Cancer. 2026 Apr 15;132(8):e70409. doi: 10.1002/cncr.70409.

ABSTRACT

BACKGROUND: There is limited information about care experiences and health outcomes among transgender, gender-nonconforming, and nonbinary (TGNCNB) individuals with cancer. This study quantifies experienced health care discrimination among TGNCNB individuals living with cancer and its impact on their health.

METHODS: This cross-sectional analysis used data from the All of Us Research Program on individuals with cancer. The authors performed propensity score matching (1:5) to balance TGNCNB and cisgender individuals by sociodemographic factors and cancer site. Health care discrimination and health were assessed using the Discrimination in Medical Settings Scale and the Overall Health survey. They used multivariable logistic regression models to adjust for sociodemographic characteristics.

RESULTS: The cohort included 1476 participants, of which 246 (17%) identified as TGNCNB. TGNCNB participants had greater odds of reporting feeling unheard by providers (odds ratio [OR], 2.38; 95% confidence interval [CI], 1.79-3.17), treated with less respect (OR, 2.61; 95% CI, 1.91-3.57), receiving poorer service (OR, 2.39; 95% CI, 1.73-3.31), and providers acting afraid (OR, 2.32; 95% CI, 1.37-3.93) compared to their cisgender counterparts. In adjusted models, TGNCNB identity was associated with increased odds of experiencing any health care discrimination (OR, 2.42; 95% CI, 1.81-3.25), and discrimination was associated with self-reported poor health (OR, 3.24; 95% CI, 2.58-4.07).

DISCUSSION: The findings of this study suggest that in the TGNCNB population, increased rates of health care discrimination are associated with poorer health outcomes, which may perpetuate medical mistrust and decrease patient-centric quality of care overall. Future research and policy efforts should identify actionable interventions to advance equitable cancer care for TGNCNB individuals.

PMID:41988958 | DOI:10.1002/cncr.70409