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Nevin Manimala Statistics

Machine learning-driven evaluation of mechanical and microstructural properties of agro-waste-derived geopolymer concrete

Sci Rep. 2026 May 26. doi: 10.1038/s41598-026-50251-5. Online ahead of print.

ABSTRACT

The growing demand for sustainable construction materials has accelerated research into eco-friendly alternatives to traditional Portland cement. This research explores the potential of geopolymer concrete formulated from agricultural-waste ashes as a sustainable replacement for conventional Portland cement. Banana peel ash (BPA) and sugarcane bagasse ash (SCBA) were employed as aluminosilicate precursors, and their combined effects were systematically examined through controlled variations in blend proportion, alkaline activator molarity, sodium silicate-to-sodium hydroxide (SS/SH) ratio, and aggregate-to-binder ratio. The influence of these parameters on fresh and hardened properties-including workability, compressive strength, and flexural strength-was rigorously evaluated. Within the defined experimental domain, an optimal formulation comprising 52.5% SCBA and 47.5% BPA activated with 10 M NaOH achieved compressive and flexural strengths of 33.17 MPa and 9.95 MPa, respectively, demonstrating structural-grade performance suitable for practical applications. Detailed microstructural investigations employing SEM-EDS, XRD, FTIR and TGA techniques confirmed that both ashes exhibit high silica content, significant pozzolanic behaviour, and that increased activator concentration enhanced the dissolution of aluminosilicate phases leading to a denser geopolymeric matrix with improved durability. To further strengthen the analytical framework and enable predictive mix optimization, artificial intelligence-based models-Gene Expression Programming (GEP) and Artificial Neural Networks (ANN)-were developed. Both models achieved excellent predictive performance (R2 > 0.98) with respect to slump Flexural and compressive strength; however, the GEP model consistently exhibited superior accuracy, lower error indices and better alignment with measured results than the ANN. Performance was validated through statistical metrics including Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and coefficient of determination (R2), confirming the robustness of the machine-learning framework in capturing the complex, non-linear interactions among mix variables. The novelty of this study lies in demonstrating that low-value agricultural waste ashes can be engineered into reliable, structural-grade geopolymer binders, producing a high-performance BPA-SCBA concrete that repurposes agricultural residues and reduces the carbon footprint of cement production. Additionally, the integration of AI-based optimization provides a robust decision-support tool for mix design, enabling data-driven, sustainable construction practices.

PMID:42192170 | DOI:10.1038/s41598-026-50251-5

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Nevin Manimala Statistics

Effect of common children’s beverages on surface properties of single-shade and restorative material: an in vitro study

Sci Rep. 2026 May 26. doi: 10.1038/s41598-026-55540-7. Online ahead of print.

ABSTRACT

Single-shade composite restorations can adapt to the tooth structure, improve esthetics, and reduce reliance on shade selection. The objective of this study was to assess the effect of four different children’s beverages on the color changes, gloss, and surface microhardness of single-shade resin composites compared to universal composite. Forty-eight specimens were prepared from each Shade A2 universal (Filtek Z250) and single-shade resin composite material (Vittra APS Unique). Then, the specimens were divided into four subgroups: Distilled Water (control group), Pepsi Cola Drink, Orange Juice, and Chocolate Milk, all at 24 °C. These specimens were immersed in their respective beverages for 30 min daily. Color changes, gloss, and microhardness values were evaluated at baseline before immersion and at the 1st, 7th, and 30th days of immersion. Data were collected and statistically analyzed using two-way variance analysis (ANOVA) and Tukey’s post-hoc test (p < 0.05). The results showed color change was significantly greater in Vittra APS than in Filtek Z250 across all time intervals, especially in Pepsi Cola after 30th days. For gloss, Vittra APS and Filtek Z250 at all time periods for four storage media showed statistically significant differences. Microhardness of Vittra APS was significantly affected by all time periods and all media except water. Filtek Z250 showed significant differences across all storage media at baseline and after 1st day. Overall, the single-shade composite showed more color change, gloss loss, and hardness reduction-especially in storage media like Pepsi Cola and Orange Juice-compared to the universal composite.

PMID:42192168 | DOI:10.1038/s41598-026-55540-7

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Nevin Manimala Statistics

Language access in the neonatal intensive care unit: inequities, legality, practice, and call to action

J Perinatol. 2026 May 26. doi: 10.1038/s41372-026-02731-9. Online ahead of print.

ABSTRACT

OBJECTIVE: Evaluate Neonatal Intensive Care Unit (NICU) interpreter access and utilization, unit-based interpreter policies and initiatives, staff awareness and confidence in understanding language-access laws, and perceptions of language-based inequities.

STUDY DESIGN: An exploratory national survey of NICU staff was distributed via the National Association of Neonatal Nurses and the American Academy of Pediatrics (AAP) (10/2024-4/2025). Descriptive statistics and qualitative analysis were used for survey results.

RESULT: The 189 respondents represented all ten AAP districts. Most were aware of NICU-based interpreter policies (76%). 81% were not aware of additional state laws/provisions and many lacked confidence understanding federal (43%) or state (63%) language-access laws. Many respondents disagreed that language-discordance resulted in worse quality of care (40%) and outcomes (59%) in their NICU.

CONCLUSION: Results highlight the need for additional education on federal and state laws and provisions as well as the broad and systemic nature of language-based healthcare inequities across institutions.

PMID:42192163 | DOI:10.1038/s41372-026-02731-9

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Nevin Manimala Statistics

Development of soil surface wetness models using machine learning techniques in the selected sites in Punjab, North-Western India

Sci Rep. 2026 May 26. doi: 10.1038/s41598-026-50687-9. Online ahead of print.

ABSTRACT

Accurate prediction of soil surface wetness (SSW) is vital for effective land management and resource optimization, particularly in sensitive ecosystems like the Western Himalayas. The main objective of the present study is to improve the accuracy of SSW prediction using hybrid and bagging models in the selected sites in Punjab, north-western India. The study utilizes ten machine-learning models comprising five base learners-random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), logistic model tree (LMT), and classification and regression tree (CART) and their corresponding AdaBoost-based hybrid variants: AdaBoost-RF, AdaBoost-XGBoost, AdaBoost-LightGBM, AdaBoost-LMT, and AdaBoost-CART. The SSW data set was collected from NASA POWER platform and Goddard Earth Observing System (GEOS) derived data which covers the period from 1986 to 2021. For model development, we applied a monthly data-lagging technique to generate different model scenarios. For feature selection, we applied greedy stepwise and best-first algorithms to identify the most effective predictors and improve model efficiency. Evaluations of the models were based on a variety of statistical indices. The results show that the RF model achieved the highest correlation coefficients (CC) across the study areas, ranging from 0.64 to 0.76 in Moga, 0.61 to 0.82 (XGBoost) in Hoshiarpur, and 0.41 to 0.64 (LMT) in Firozpur during the testing period. Accordingly, the hybrid AdaBoost-LightGBM model was the best, with CC values of 0.61-0.76, 0.63-0.82, and 0.49-0.60 for Moga, Hoshiarpur, and Firozpur, respectively. Overall model performance was limited to moderate and varied across locations and scenarios; although AdaBoost-LMT showed the best relative performance, the results primarily support its use for reproducing temporal variability in GEOS-derived SSW rather than precise wetness estimation. The findings contribute to improving SSW estimation and support data-driven decision-making for sustainable land and water management in the selected sites in Punjab, north-western India.

PMID:42192144 | DOI:10.1038/s41598-026-50687-9

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Nevin Manimala Statistics

Individualized cortico-basal ganglia-thalamo-cortical circuit dysfunction links striatal dopaminergic loss to motor symptom severity in Parkinson’s disease

NPJ Parkinsons Dis. 2026 May 26. doi: 10.1038/s41531-026-01409-5. Online ahead of print.

ABSTRACT

Motor impairment in Parkinson’s disease (PD) is classically attributed to striatal dopaminergic degeneration, yet dopamine loss alone does not fully explain symptom severity, suggesting a key role for circuit-level mechanisms. The cortico-basal ganglia-thalamo-cortical (CBGTC) system is central to dopaminergic motor modulation, but whether dysfunction within individualized CBGTC circuits mediates motor severity across disease stages remains unclear. Here, we studied 76 PD patients (40 mild, 36 moderate-to-severe) who underwent 18F-FP-CIT PET and multimodal MRI. Individualized long and short CBGTC loops were reconstructed using connectivity profile-based segmentation and probabilistic tractography, with functional connectivity (FC) quantified alongside striatal dopaminergic integrity. Compared with mild PD, moderate-to-severe PD showed a global reduction in striatal dopamine binding, most pronounced in the bilateral caudate. Critically, FC between the caudate and premotor cortex in the more-affected hemisphere was selectively reduced with increasing disease severity in both CBGTC loops (p-FDR = 0.027). The cross-sectional mediation models demonstrated that caudate-premotor FC statistically accounted for the association between caudate dopaminergic loss and motor symptom severity. These findings position individualized cortico-basal ganglia circuit connectivity as a potential mechanistically grounded biomarker linking molecular pathology to motor impairment in PD, with potential relevance for future circuit-guided therapeutic strategies.

PMID:42192116 | DOI:10.1038/s41531-026-01409-5

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Nevin Manimala Statistics

Absolute quantification of enantiomeric purity of sorted carbon nanotubes by correlating hyperspectral fluorescence microscopy with ensemble chiroptical spectroscopy

Nat Commun. 2026 May 26. doi: 10.1038/s41467-026-73397-2. Online ahead of print.

ABSTRACT

Accurate determination of enantiomeric purity is essential for advancing chiral materials in nanotechnology, optoelectronics, and quantum information science. Chiroptical spectroscopic techniques provide rapid, non-destructive measurements of enantiomeric excess (ee), but their use for complex systems like single-walled carbon nanotubes (SWCNTs) is limited by the lack of enantiopure references for calibration. Here we demonstrate an absolute approach combining hyperspectral imaging (HSI) with single-nanotube counting statistics and ensemble chiroptical spectroscopy such as electronic circular dichroism (ECD) and Raman optical activity (ROA) to quantify ee without requiring such standards. Analysis of thousands of individual nanotubes reveals sensitivity of HSI and chiroptical responses to synthesis, purification, and SWCNT concentration, highlighting pronounced source-dependent inhomogeneity. Nevertheless, universal calibration curves for ECD and ROA intensities are established from the purest, most uniform enantiomer-sorted samples. This methodology is extendable to other SWCNT chiralities and chiroptical techniques, enabling quantitative enantiomer sorting and systematic investigations of chirality-dependent properties and applications.

PMID:42192104 | DOI:10.1038/s41467-026-73397-2

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Nevin Manimala Statistics

Optimal time for aspirin withdrawal after PCI in ACS: a pairwise and network meta-analysis with time to event data of randomized trials

Cardiovasc Interv Ther. 2026 May 26. doi: 10.1007/s12928-026-01304-z. Online ahead of print.

ABSTRACT

In patients with ACS undergoing PCI, de-escalation to P2Y12-inhibitor monotherapy reduces bleeding, but the optimal timing of aspirin withdrawal is uncertain. We conducted pairwise and network meta-analyses of randomized trials comparing P2Y12-inhibitor monotherapy after aspirin discontinuation versus dual antiplatelet therapy (DAPT) in ACS post-PCI. Random-effects models were used. The network meta-analysis (NMA) compared four strategies (12-month DAPT [central comparator]; aspirin stop < 1 month, 1-2 months, or 3 months) and ranked treatments using SUCRA. (PROSPERO ID: CRD420251151605). A total of 33,292 participants from 10 RCTs were included. In the pairwise meta-analysis, monotherapy reduced net adverse clinical events (NACE) (5.1% vs. 6.7%; RR: 0.75; 95% CI: 0.65-0.86) and bleeding, including clinically relevant bleeding (RR: 0.45; 95% CI: 0.39-0.53) and major bleeding (RR: 0.47; 95% CI: 0.37-0.60). In the NMA, aspirin discontinuation at 3 months showed a trend toward lower NACE versus 12-month DAPT (RR 0.66; 95% CI 0.42-1.04) and ranked most favorable for net and ischemic outcomes (NACE, MI, MACCE, and all-cause mortality), although estimates for individual ischemic endpoints were imprecise and not statistically different from 12-month DAPT. Aspirin discontinuation at < 1 month showed an unfavorable mortality ranking, with a concordant meta-regression signal suggesting higher mortality with earlier aspirin withdrawal. De-escalation to P2Y₁₂ inhibitor monotherapy after PCI in ACS reduced NACE, mainly by lowering bleeding. In network analyses, aspirin discontinuation at 3 months ranked most favorable for net and ischemic outcomes, whereas discontinuation at < 1 month showed an unfavorable mortality signal.

PMID:42192090 | DOI:10.1007/s12928-026-01304-z

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Nevin Manimala Statistics

Discovering Age- and Sex-Specific Genetic Risk Factors in Sensorineural Hearing Loss: Genome-Wide Evidence from Large-Scale Biobanks

J Assoc Res Otolaryngol. 2026 May 26. doi: 10.1007/s10162-026-01054-y. Online ahead of print.

ABSTRACT

PURPOSE: Investigate the genetic components of sensorineural hearing loss (SNHL) by performing genome-wide meta-analyses using the data from FinnGen and Estonian Biobank.

METHODS: We studied genome-wide associations of SNHL in FinnGen and the Estonian Biobank in the general population and in sex- and age-of-onset stratified subgroups. The study-specific GWASs were combined through inverse variance-weighted genome-wide meta-analyses, encompassing a total of 531,059 individuals (Ncases = 35,960). Age-stratified meta-analyses included 28,198 individuals diagnosed at the age of 55 years or after and 7762 individuals diagnosed before the age of 55 years, with 495,099 controls. Sex-stratified meta-analyses included 313,501 females (Ncases = 17,761) and 217,558 males (Ncases = 18,199).

RESULTS: In the meta-analysis focusing on the general population, 22 SNHL-associated loci (±1 Mb window) were observed, three of which were previously unreported. In the sex-stratified analysis, two previously unreported SNHL loci were observed in the female subgroup and one locus in the male subgroup. Additionally, in the age-stratified analysis, two previously unreported SNHL loci were observed in the subgroup of those that were diagnosed at the age of 55 years or after. In those diagnosed before the age of 55 years, one previously unreported locus was observed. Overall, 32 loci were associated with SNHL at p < 5 × 10-8 in at least one of the study groups. Of these, nine have not been previously reported in association with SNHL. We also estimated if there were significant differences in the effect sizes of the lead variants at each locus between the analytical subgroups and observed differences for 14 variants.

CONCLUSIONS: Previously unreported SNHL risk loci and differences in effect sizes found in this study provide additional insight into the genetic underpinnings of SNHL. Our results validate the role of mechano-transduction and genetic components affecting the structure of the inner ear in the background of SNHL. Our study contributes to our understanding of the genetic causes of SNHL and may open the door for further translational research.

PMID:42192083 | DOI:10.1007/s10162-026-01054-y

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Nevin Manimala Statistics

Latent Profile Analysis of Acculturation and Associated Health Among Asian American Subgroups

J Racial Ethn Health Disparities. 2026 May 26. doi: 10.1007/s40615-026-03024-9. Online ahead of print.

ABSTRACT

Acculturation has been shown to be relevant to health outcomes. However, methodological limitations remain in the existing literature, particularly the lack of psychometric validation of acculturation measures for Asian American population. As a result, little is known about distinct acculturation profiles within this population and how these profiles relate to perceived stress and health. This study employs latent profile analysis (LPA) to identify distinct acculturation profiles among 337 Asian Americans and to examine their associations with perceived health and perceived stress. LPA were used based on acculturated-related variables, including perceived acculturation, immigration generation, associated ethnic group, heritage language competency pressure, English competency pressure, pressure to acculturation, pressure against acculturation. We detected a 3-class solution: acculturated, bicultural, and enculturated. Compared to bicultural group, the acculturated group has statistically significant lower perceived stress (p < .001), higher perceived mental health (p < .001) and physical health (p < .001); the enculturated group reported significantly lower perceived mental health than the bicultural group (p <.001). These findings highlight nuanced differences in health perceptions across acculturation profiles. Notably, the enculturated group may be at elevated risk for poorer mental health outcomes, underscoring the need for culturally tailored mental health interventions. By elucidating how acculturation experiences impact perceived health and stress, this study offers practical insights for mental health professionals and healthcare providers, encouraging the development of tailored, culturally sensitive interventions for Asian American subgroups based on their acculturation experiences.

PMID:42192078 | DOI:10.1007/s40615-026-03024-9

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Nevin Manimala Statistics

The Impact of the Number of Implantation-Window uNK Cells on Pregnancy Outcomes and Decidualization

Reprod Sci. 2026 May 26. doi: 10.1007/s43032-026-02125-4. Online ahead of print.

ABSTRACT

This study aims to further clarify the correlation between the quantity of natural killer (NK) cells in the endometrium and the successful implantation of embryos during the specific implantation window. Patients were stratified into four distinct groups according to the quantity of natural killer (NK) cells detected during the implantation window. The groups were defined as follows: Group A (NK cell percentage ≥ 10%, n = 62), Group B (NK cell percentage: 5%-9.99%, n = 128), Group C (NK cell percentage: 1%-4.99%, n = 106), and Group D (NK cell percentage ≤ 0.5%, n = 30). Among Group A, 32 patients received intrauterine infusion of dexamethasone (designated as Subgroup A1), while the remaining 30 patients did not undergo this treatment (designated as Subgroup A2). For Groups B and D, immunohistochemistry was performed to detect the expression of IGFBP1 (an endometrial decidualization marker) and HBP1 (a decidualization-related transcription factor). The live birth rate in Group D was statistically significantly lower than that in the other three study groups. For Group A, after dexamethasone administration, a notable reduction in NK cell quantity was observed in Subgroup A1 (patients who received intrauterine dexamethasone infusion) during the implantation window; however, the pregnancy rates of Subgroup A1 and Subgroup A2 (patients without dexamethasone treatment) were comparable. Furthermore, in Group D patients, the expression levels of the decidualization markers IGFBP1 and HBP1 were significantly lower than those in the reference group (Group B, as specified in Methods). Insufficient natural killer (NK) cells during the embryo implantation window significantly impede the embryo implantation process. This shortage of NK cells may be attributed to inadequate endometrial decidualization. Notably, although intrauterine infusion of dexamethasone effectively reduces NK cell counts, it does not exert a significant impact on clinical outcomes.

PMID:42192073 | DOI:10.1007/s43032-026-02125-4