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Nevin Manimala Statistics

The effect of incorporating whole body vibration into exercise therapy on the corticomotor excitability of the quadriceps in athletes following anterior cruciate ligament reconstruction

Sci Rep. 2025 Apr 23;15(1):14063. doi: 10.1038/s41598-025-98134-5.

ABSTRACT

Previous studies have shown that athletes recovering from anterior cruciate ligament (ACL) reconstruction experience a decline in motor cortex excitability and injury-related cortical reorganization, potentially leading to ongoing complications and a higher risk of subsequent injuries. Therefore, incorporating an intervention that consistently delivers sensory inputs to the central nervous system and enhances excitability at both spinal and supra-spinal levels, in addition to exercise therapy, may offer greater benefits. The purpose of this study was to explore whether combining whole body vibration (WBV) with exercise therapy enhances motor cortical excitability in athletes undergoing ACL reconstruction more effectively than exercise therapy alone. Additionally, it aimed to assess whether this combination improves quadriceps strength and reduces functional limitations in daily activities. This study is a randomized, single-blinded, controlled trial. Twenty-six participants were assigned to either the WBV plus exercise therapy group (intervention group) or the exercise therapy-only group (control group). Outcome measures, assessed before and after treatment, included motor cortex excitability [active motor threshold (AMT) and motor-evoked potential amplitude of the quadriceps], isometric peak torque of the quadriceps, and daily functional disabilities using the knee outcome survey activities of daily living scale (KOS-ADL scale). The treatment period consisted of 12 sessions (4 weeks, with 3 sessions per week). A two-way mixed ANOVA was conducted to examine the main effects of group, time and their interactions. The results showed that in the intervention group (WBV plus exercise therapy), AMT significantly decreased (F(1, 12) = 11.35, P = 0.006, η2 = 0.486), while the control group (exercise therapy only) showed no significant change (F(1, 12) = 0.252, P = 0.625, η2 = 0.021). In the intervention group, AMT decreased by 19.47% post-treatment. Both groups showed significant improvements in isometric peak torque and KOS-ADL scores (P < 0.001), with large effect sizes for these parameters. The study concluded that adding WBV to exercise therapy is more effective in increasing motor cortex excitability compared to exercise therapy alone. However, since both groups showed significant improvements in quadriceps peak torque and KOS-ADL scores, it suggests that the addition of WBV did not provide substantial added benefits in enhancing quadriceps strength and improving daily functional abilities. The observed improvements may primarily be attributed to exercise therapy. Nonetheless, it is important to consider the small sample size and low statistical power when interpreting these results.RCT registration: On the Iranian Registry of Clinical Trials (IRCT20220220054078N1).

PMID:40269014 | DOI:10.1038/s41598-025-98134-5

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Nevin Manimala Statistics

Significance and classification of AI-driven techniques in telecommunication sectors based on interval-valued bipolar fuzzy soft aggregation operators

Sci Rep. 2025 Apr 23;15(1):14126. doi: 10.1038/s41598-025-97866-8.

ABSTRACT

In the context of telecommunications, AI enhances network efficiency by predicting and managing traffic. In many decision-making scenarios, decision-makers choose the more flexible structure that can handle all kinds of information. Bipolarity is the only case in which we can discuss the positive and negative aspects of certain scenarios. On one side, AI enhances network efficiency, proactive maintenance, and personalized customer experience but on the other hand, it has also some negative aspects (1) implementing AI infrastructure can be costly (2) Uses of AI in telecommunication may raise data security concerns and user privacy (3) AI can lead to potential issues if system fail or misused. To cover these issues, the idea of an interval-valued bipolar fuzzy soft set (IVBFSS) has been developed that can deal with both positive and negative aspects of AI. Some basic operational laws for IVBPFS numbers are developed. Several fundamental aggregation operators have been introduced like arithmetic average and geometric average aggregation operators, indicating our main contribution. An algorithm is developed to discuss the application perspective of the initiated approaches. We have utilized these developed notions to classify AI-driven techniques in the telecommunications sector to discuss the applicability of the initiated notions. A comparative analysis of the developed approaches shows the advantages and superiority of the introduced work.

PMID:40269011 | DOI:10.1038/s41598-025-97866-8

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Nevin Manimala Statistics

Multi-strategy improved gazelle optimization algorithm for numerical optimization and UAV path planning

Sci Rep. 2025 Apr 23;15(1):14137. doi: 10.1038/s41598-025-98112-x.

ABSTRACT

The Gazelle Optimization Algorithm (GOA) is a recently proposed and widely recognized metaheuristic algorithm. However, it suffers from slow convergence, low precision, and a tendency to fall into local optima when addressing practical problems. To address these limitations, we propose a Multi-Strategy Improved Gazelle Optimization Algorithm (MIGOA). Key enhancements include population initialization based on an optimal point set, a tangent flight search strategy, an adaptive step size factor, and novel exploration strategies. These improvements collectively enhance GOA’s exploration capability, convergence speed, and precision, effectively preventing it from becoming trapped in local optima. We evaluated MIGOA using the CEC2017 and CEC2020 benchmark test sets, comparing it with GOA and eight other algorithms. The results, validated by the Wilcoxon rank-sum test and the Friedman mean rank test, demonstrate that MIGOA achieves average rankings of 1.80, 2.03, 2.03, and 2.70 on CEC2017 (Dim = 30/50/100) and CEC2020 (Dim = 20), respectively, outperforming the standard GOA and other high-performance optimizers. Furthermore, the application of MIGOA to three-dimensional unmanned aerial vehicle (UAV) path planning problems and 2 engineering optimization design problems further validates its potential in solving constrained optimization problems. Experimental results consistently indicate that MIGOA exhibits strong scalability and practical applicability.

PMID:40268989 | DOI:10.1038/s41598-025-98112-x

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Nevin Manimala Statistics

Heterogeneous quantization regularizes spiking neural network activity

Sci Rep. 2025 Apr 23;15(1):14045. doi: 10.1038/s41598-025-96223-z.

ABSTRACT

The learning and recognition of object features from unregulated input has been a longstanding challenge for artificial intelligence systems. Brains, on the other hand, are adept at learning stable sensory representations given noisy observations, a capacity mediated by a cascade of signal conditioning steps informed by domain knowledge. The olfactory system, in particular, solves a source separation and denoising problem compounded by concentration variability, environmental interference, and unpredictably correlated sensor affinities using a plastic network that requires statistically well-behaved input. We present a data-blind neuromorphic signal conditioning strategy, based on the biological system architecture, that normalizes and quantizes analog data into spike-phase representations, thereby transforming uncontrolled sensory input into a regular form with minimal information loss. Normalized input is delivered to a column of spiking principal neurons via heterogeneous synaptic weights; this gain diversification strategy regularizes neuronal utilization, yoking total activity to the network’s operating range and rendering internal representations robust to uncontrolled open-set stimulus variance. To dynamically optimize resource utilization while balancing activity regularization and resolution, we supplement this mechanism with a data-aware calibration strategy in which the range and density of the quantization weights adapt to accumulated input statistics.

PMID:40268966 | DOI:10.1038/s41598-025-96223-z

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Nevin Manimala Statistics

HindwingLib: A library of leaf beetle hindwings generated by Stable Diffusion and ControlNet

Sci Data. 2025 Apr 23;12(1):680. doi: 10.1038/s41597-025-05010-y.

ABSTRACT

The utilization of datasets from beetle hindwings is prevalent in research of morphology and evolution of beetles, serving as a valuable tool for comprehending the evolutionary processes and functional adaptations under specific environmental conditions. However, the collection of hindwing images of beetles poses several challenges, including limited sample availability, complex sample preparation procedures, and restricted public accessibility. Recently, a machine learning technique called Stable Diffusion has been developed to statistically generate diverse images using a pretrained model with prompts. In this study, we introduce an approach utilizing Stable diffusion and ControlNet for the generation of beetle hindwing images, along with the corresponding results obtained from its application to a diverse set of 200 leaf beetle hindwings. To demonstrate the fidelity of the synthetic hindwing images, we conducted a comprarative analysis of three key metrics: Structural Similarity Index (SSIM), Inception Score (IS), and Fréchet Inception Distance (FID), which are crucial for evaluating image fidelity. The results demonstrated a strong alignment between the actual data and the synthetic images, confirming their high fidelity. This novel library of leaf beetle hindwings not only offers morphological image for utilization in machine learning, but also showcases the extensive applicability of the proposed methodology.

PMID:40268959 | DOI:10.1038/s41597-025-05010-y

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Nevin Manimala Statistics

JointPRS: A data-adaptive framework for multi-population genetic risk prediction incorporating genetic correlation

Nat Commun. 2025 Apr 24;16(1):3841. doi: 10.1038/s41467-025-59243-x.

ABSTRACT

Genetic risk prediction for non-European populations is hindered by limited Genome-Wide Association Study (GWAS) sample sizes and small tuning datasets. We propose JointPRS, a data-adaptive framework that leverages genetic correlations across multiple populations using GWAS summary statistics. It achieves accurate predictions without individual-level tuning data and remains effective in the presence of a small tuning set thanks to its data-adaptive approach. Through extensive simulations and real data applications to 22 quantitative and four binary traits in five continental populations evaluated using the UK Biobank (UKBB) and All of Us (AoU), JointPRS consistently outperforms six state-of-the-art methods across three data scenarios: no tuning data, same-cohort tuning and testing, and cross-cohort tuning and testing. Notably, in the Admixed American population, JointPRS improves lipid trait prediction in AoU by 6.46%-172.00% compared to the other existing methods.

PMID:40268942 | DOI:10.1038/s41467-025-59243-x

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Nevin Manimala Statistics

Stress-induced phase separation in plastics drives the release of amorphous polymer micropollutants into water

Nat Commun. 2025 Apr 23;16(1):3814. doi: 10.1038/s41467-025-58898-w.

ABSTRACT

Residual stress is an intrinsic property of semicrystalline plastics such as polypropylene and polyethylene. However, there is no fundamental understanding of the role intrinsic residual stress plays in the generation of plastic pollutants that threaten the environment and human health. Here, we show that the processing-induced compressive residual stress typically found in polypropylene and polyethylene plastics forces internal nano and microscale segregation of low molecular weight (MW) amorphous polymer droplets onto the plastic’s surface. Squeeze flow simulations reveal this stress-driven volumetric flow is consistent with that of a Bingham plastic material, with a temperature-dependent threshold yield stress. We confirm that flow is thermally activated and stress dependent, with a reduced energy barrier at higher compressive stresses. Transfer of surface segregated droplets into water generates amorphous polymer micropollutants (APMPs) that are denatured, with structure and composition different from that of traditional polycrystalline microplastics. Studies with water-containing plastic bottles show that the highly compressed bottle neck and mouth regions are predominantly responsible for the release of APMPs. Our findings reveal a stress-induced mechanism of plastic degradation and underscore the need to modify current plastic processing technologies to reduce residual stress levels and suppress phase separation of low MW APMPs in plastics.

PMID:40268905 | DOI:10.1038/s41467-025-58898-w

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Nevin Manimala Statistics

Nkx2.7 is a conserved regulator of craniofacial development

Nat Commun. 2025 Apr 23;16(1):3802. doi: 10.1038/s41467-025-58821-3.

ABSTRACT

Craniofacial malformations arise from developmental defects in the head, face, and neck with phenotypes such as 22q11.2 deletion syndrome illustrating a developmental link between cardiovascular and craniofacial morphogenesis. NKX2-5 is a key cardiac transcription factor associated with congenital heart disease and mouse models of Nkx2-5 deficiency highlight roles in cardiac development. In zebrafish, nkx2.5 and nkx2.7 are paralogues in the NK4 family expressed in cardiomyocytes and pharyngeal arches. Despite shared cellular origins of cardiac and craniofacial tissues, the function of NK4 factors in head and neck patterning has not been elucidated. Molecular evolutionary analysis of NK4 genes shows that nkx2.5 and nkx2.7 are ohnologs resulting from whole genome duplication events. Nkx2.7 serves as a previously unappreciated regulator of branchiomeric muscle and cartilage formation for which nkx2.5 cannot fully compensate. Mechanistically, our results highlight that Nkx2.7 patterns the cranial neural crest and functions upstream of Endothelin1 to inhibit Notch signals. Together, our studies shed light on an evolutionarily conserved Nkx transcription factor with unique functions in vertebrate craniofacial development, advancing our understanding of congenital head and neck deformities.

PMID:40268889 | DOI:10.1038/s41467-025-58821-3

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Nevin Manimala Statistics

Risk Classification of Oral Cancer Surgical Margins: Margin to Depth of Invasion Ratio Analysis

Ann Surg Oncol. 2025 Apr 23. doi: 10.1245/s10434-025-17286-w. Online ahead of print.

ABSTRACT

BACKGROUND: A high-risk margin is a recurrence risk factor in oral squamous cell carcinoma (OSCC), but its exact definition is debated. The effectiveness of the margin-to-depth-of-invasion ratio (MDR) in identifying high-risk margin remains to be determined.

METHODS: Patients who had a diagnosis of pT1-4N0 OSCC with negative margins (margin > 1 mm) recorded in the Taiwan Cancer Registry between January 2018 and December 2021 were reviewed. All patients were categorized into two groups: MDR < 0.5 and MDR ≥ 0.5.

RESULTS: The study analyzed 7420 OSCC patients without a positive margin. Of these 7420 patients, 4669 (62.92%) had an MDR ≥ 0.5, and 2751 (37.08%) had an MDR < 0.5. The group with an MDR < 0.5 exhibited significantly poorer 3-year disease-free survival (DFS, 74% vs 86%) and overall survival (OS, 79% vs 89%) than the group with an MDR ≥ 0.5. Despite a higher rate of postoperative radiotherapy (PORT) in the group with an MDR < 0.5, multivariate Cox analysis showed that patients with a margin < 5 mm and an MDR ≥ 0.5 had a significantly better DFS than those with a margin < 5 mm and an MDR < 0.5 (p = 0.001). Treatment with PORT improved DFS and OS for the patients with an MDR < 0.5, but worsened outcomes for the patients with an MDR ≥ 0.5.

CONCLUSION: For OSCC patients without positive margin, an MDR < 0.5 was associated with worse survival and higher locoregional recurrence risk. The patients with an MDR < 0.5 may benefit from PORT, whereas those with an MDR ≥ 0.5 could experience worse outcomes. An MDR < 0.5 could serve as a criterion for high-risk OSCC margin.

PMID:40268847 | DOI:10.1245/s10434-025-17286-w

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Nevin Manimala Statistics

Normal ranges of right atrial strain by contemporary echocardiography software: a prospective comparative cohort study

J Echocardiogr. 2025 Apr 23. doi: 10.1007/s12574-025-00689-9. Online ahead of print.

ABSTRACT

BACKGROUND: Right atrial (RA) strains (RASr, RAScd, and RASct) are increasingly used in clinical and research settings, such as heart failure and pulmonary hypertension, but their feasibility and reference ranges across different strain software vendors are not well established. We aim to evaluate and compare two-dimensional RA strain values, reference ranges, and related factors across four strain software vendors in healthy subjects.

METHODS: Healthy subjects (n = 100) undergoing echocardiography during January-April 2023 were prospectively studied, with equal numbers by age groups, gender, and GE versus Philips scans. RA strains were quantified using TomTec version 51.02 (Autostrain LA), EchoPAC version 206 (AFI-LA), Velocity-Vector Imaging (VVI) version 2.00, and Epsilon software (5.0.2.11295) for statistical analyses.

RESULTS: Overall means and lower limits of normal (LLNs) of each type of RA strain by strain vendor, age group, sex, and scanner vendor were reported. For example, RASr (%) means and LLNs (95% confidence intervals) were 41.2 (38.5, 43.0) and 29.6 (26.5, 32.7) for TomTec, 35.9 (34.4, 37.3) and 27.0 (24.5, 29.5) for EchoPAC, 44.8 (42.3, 47.3) and 27.6 (23.3, 31.9) for VVI, and 38.9 (36.7, 41.0) and 25.5 (21.7, 29.3) for Epsilon, respectively. Linear mixed model regression showed EchoPAC and VVI had significantly lower RASr and higher RAScd magnitude than TomTec, with older age linked to lower RASr and RAScd magnitudes.

CONCLUSION: TomTec and VVI were vendor-neutral for measuring RA strains, while EchoPAC worked only on GE scans. Normal values, lower limits of normal, and related factors for RA strain measurements by vendor were established for clinical use.

PMID:40268844 | DOI:10.1007/s12574-025-00689-9