Category: Statistics

Skeletal Radiol. 2026 Mar 22. doi: 10.1007/s00256-026-05199-y. Online ahead of print.

ABSTRACT

OBJECTIVES: The purpose of this study was to evaluate the effectiveness of collagen-sensitive dual-energy computed tomography (DECT) as a quantitative imaging tool for the assessment and monitoring of load-induced tendinopathy in the Achilles and patellar tendons, comparing it to magnetic resonance imaging (MRI).

METHODS: In a prospective study, 15 consecutive patients clinically diagnosed with Achilles or patellar tendinopathy underwent bilateral DECT and MRI at baseline and 6 months. Quantitative measurements included collagen density assessed via DECT and signal intensity via MRI. Clinical symptoms were evaluated using numerical pain ratings and VISA-A/P scores. The diagnostic accuracy of both imaging modalities was assessed using ROC analysis, and correlations between DECT and MRI findings were investigated.

RESULTS: DECT revealed significantly lower collagen densities on corresponding maps in affected tendons (n = 18, 23.7 ± 20.2) compared to unaffected tendons (n = 12, 60.2 ± 29.6 HU, p < 0.001), whereas MRI demonstrated increased signal intensities in pathological regions. ROC analysis indicated comparable diagnostic performance for DECT (AUC = 0.84) and MRI (AUC = 0.80). A strong inverse correlation (r = -0.83) was observed between DECT-measured collagen densities and MRI signal intensities. Clinical improvements at follow-up were reflected by normalization trends in both imaging modalities, though not statistically significant.

CONCLUSIONS: Collagen-sensitive DECT provides a reliable quantitative approach for detecting and assessing tendon pathologies in load-induced tendinopathy, demonstrating diagnostic capabilities comparable to MRI while offering the possibility for collagen density quantification.

PMID:41865099 | DOI:10.1007/s00256-026-05199-y

Sci Rep. 2026 Mar 21. doi: 10.1038/s41598-026-44603-4. Online ahead of print.

ABSTRACT

With the increasing availability of multimodal remote sensing (RS) data, semantic segmentation that leverages complementary information from true orthophotos (TOP) and digital surface models (DSM) has become essential for urban analysis. Diffusion-based segmentation provides an effective iterative refinement mechanism for modeling complex multimodal distributions; however, conventional pixel-wise supervision emphasizes local accuracy while overlooking global distribution alignment, often leading to inconsistent predictions and blurred object boundaries. Although maximum mean discrepancy (MMD) measures global statistical differences between predicted and ground-truth distributions, its effectiveness in high-dimensional class-probability spaces is limited by directional cancellation effects that reduce sensitivity to complex distribution shifts. To address this issue, we propose a projection-kernel regularized diffusion-based multimodal RS segmentation framework that enforces global statistical alignment through distribution-level regularization rather than modifying the intrinsic diffusion process. The proposed regularization performs multi-directional projections of high-dimensional class-probability vectors onto one-dimensional subspaces and derives a closed-form kernel integration to avoid numerical sampling across projection directions, enabling efficient and stable global distribution matching. In addition, a Cross-Attention Dual-Encoder Fusion (CADEF) module is introduced to alleviate geometry-texture misalignment, and a Hierarchical EMA-Gated Recursive Denoising (HERD) mechanism is designed to stabilize multiscale feature refinement. Experiments on the ISPRS Vaihingen and Potsdam benchmarks demonstrate that the proposed regularization consistently improves segmentation accuracy over state-of-the-art CNN-, Transformer-, and diffusion-based baselines, yielding enhanced global consistency and sharper boundary delineation. Code is available at: https://github.com/tonyy127/PKDiff.

PMID:41865080 | DOI:10.1038/s41598-026-44603-4

Commun Chem. 2026 Mar 21. doi: 10.1038/s42004-026-01974-z. Online ahead of print.

ABSTRACT

Intrinsically disordered protein regions (IDRs) play a key role in the formation of biomolecular condensates, a ubiquitous mode of cellular compartmentalization, but the underlying microscopic details remain unclear. Here, microsecond-level molecular dynamics simulations and fractal formalism are employed to study at atomistic resolution a model dense phase composed of 24 copies of a C-terminal 73-residue arginine- and glycine-rich IDR (RGG3) of fused in sarcoma (FUS) protein in the absence of RNA. RGG3 displays a highly dynamic behavior in the dense phase with only a small configurational entropy loss and a minor slowdown in diffusion as compared to the dilute phase. Despite rapid mixing, short contact residence times and structurally heterogenous binding interfaces in the dense phase, RGG3 exhibits a distinct dynamic binding mode, with statistically defined interaction motifs and a robust multi-scale topology of self-associated protein clusters. An analysis of bound water suggests that solvent entropy may significantly contribute to the thermodynamics of condensate formation. Our results demonstrate how a well-defined organization of the disordered protein dense phase across scales emerges from highly heterogenous, transient interactions at the molecular level.

PMID:41865079 | DOI:10.1038/s42004-026-01974-z

Sci Rep. 2026 Mar 21. doi: 10.1038/s41598-026-44888-5. Online ahead of print.

ABSTRACT

This study investigates the nonlinear fractional-order Pochhammer-Chree equation, featuring a power-law nonlinearity of order τ, a model that describes how nonlinear longitudinal waves travel in elastic materials with memory of prior deformations. Understanding nonlinear wave propagation in elastic materials with memory effects is important for accurately modeling complex physical phenomena in nonlinear elasticity, geophysics, and material science. To incorporate these memory effects, conformable fractional derivative is utilized that allowing us to examine the fractional-order spatial and temporal changes. Kumar-Malik method is used to extract analytical solutions like bright soliton, dark soliton, kink soliton and solitary wave forms, that demonstrates the dynamics of the model. To better understand these solutions behaviours, visual analysis is considered. In this analysis mathematica 14.2 is used to construct the two-dimensional, three-dimensional, and contour plots, which illustrate the influence of the fractional parameter χ on the waveforms. The shape, width and amplitude of the solitons also vary with the change in the value of the parameter, χ. These diagrams are able to make it clear how the system would respond to various physical situations. These findings indicate the efficiency of the Kumar-Malik method which guarantees accurate solutions of the fractional Pochhammer-Chree equation having power laws nonlinearity. The work enhances the theoretical knowledge on the nonlinear waves of the fractional-order systems and brings forth new uses in the field of mathematical physics and nonlinear elasticity.

PMID:41865072 | DOI:10.1038/s41598-026-44888-5

Sci Rep. 2026 Mar 21. doi: 10.1038/s41598-026-43362-6. Online ahead of print.

ABSTRACT

This study presents the optimization of nickel oxide nanoparticles (NiO NPs) synthesized through an environmentally benign route using Sida acuta (SA) leaf extract as a reducing and capping agent. Taguchi-Grey Relational Analysis (TGRA) was employed to optimize the hydrodynamic diameter (HDD) and polydispersity index (PDI) of the synthesized NiO NPs. Key synthesis parameters (extract concentration, reaction temperature, and reaction time) were varied within an L9 orthogonal array. Using Grey Relational Analysis (GRA), a regression-based model was developed to predict the grey relational grade (GRG) for multi-response optimization. The optimal synthesis conditions (60 mg/mL extract concentration, 70 °C reaction temperature, and 120 min reaction time) produced NiO NPs with an HDD of 62.72 nm and a PDI of 0.232. ANOVA identified temperature as the dominant factor governing the size and distribution of the NPs. UV-Vis spectroscopy showed a characteristic absorption peak at 284 nm, and XRD confirmed a face-centered cubic crystalline structure with an average crystallite size of 5.99 nm. SEM, EDS, and TEM analyses indicated well-dispersed polycrystalline NPs with 80% purity. The synthesized NiO NPs possess physicochemical characteristics that position them as promising candidates for catalytic, sensing, and energy-storage applications. This work demonstrates a statistical-experimental framework for tuning nanoparticle properties through sustainable synthesis routes, highlighting a scalable strategy for precision nanomaterial design.

PMID:41865066 | DOI:10.1038/s41598-026-43362-6

Sci Rep. 2026 Mar 21. doi: 10.1038/s41598-026-42552-6. Online ahead of print.

ABSTRACT

Cholemic nephropathy(CN) is an unrecognized cause of kidney dysfunction in patients with acute on chronic liver failure (ACLF). We aimed to evaluate whether urine microscopy(UM) could identify CN in ACLF patients and differentiate from hepatorenal syndrome (HRS) and acute tubular necrosis (ATN). Forty-five patients with ACLF with AKI stratified based on UM as HRS(bland sediment; n = 15), CN(bilirubin crystals; n = 15) and ATN (coarse granular casts; n = 15) were compared to no AKI (n = 15). ACLF patients with mean age of 44 ± 10 years, 93% males were enrolled. Patients with HRS and CN showed significantly elevated biomarkers of renal repair (EGF, Osteopontin, calbindin) and lower levels of renal injury (renin, lipocalin-2, cystatin c, alpha-1 macroglobulin, albumin, TIMP-1, IP-10 and KIM-1) compared to ATN. CN patients had significantly elevated bile acids, proinflammatory cytokines (20 out of 29) compared to other groups. Metabolomic analysis of plasma and renal tubule epithelial cells (RTEC)identified 190 (151 up- and 39 downregulated) and 196 (61 up and 135-down) differentially expressed metabolites in biopsy-proven CN compared to ATN(FC > 1.5, P < 0.05). Preservation of mitochondrial function was seen in the RTEC of CN compared to ATN. The top 5 biomarkers which predicted CN included GST-alpha, IL-15, bile acids, IL-3, and osteopontin. Clinical models including GST-alpha, IL-15, bilirubin (> 22 mg/dl) or AARC score identified CN with more than 95% accuracy. Taken together, our study shows higher bile acids, preserved renal repair and lesser tubular injury despite intense systemic inflammation with preserved metabolic adaptation of the host differentiated CN from ATN.

PMID:41865060 | DOI:10.1038/s41598-026-42552-6

Sci Rep. 2026 Mar 21. doi: 10.1038/s41598-026-41744-4. Online ahead of print.

ABSTRACT

In orthodontics, the increasing use of AI-generated smile images in patient communication raises ethical and practical concerns about user perception and misinterpretation of these visuals. This cross-sectional, non-probabilistic sample study evaluated the ability of dentists, dental students, and laypeople to distinguish between real and AI-generated orthodontic smile images, and their perceived attractiveness. The final sample consisted of 288 participants, (63.4% female; mean age = 32.4 years) including 76 dentists, 63 dental students, and 149 laypeople. Each participant was presented with three clinical scenarios, mild dental misalignment, midline diastema, and moderate anterior crowding, and viewed randomized sets of images depicting pre-treatment, real post-treatment, and AI-generated smiles. For each image, participants indicated whether they believed it was AI-generated or real and rated its aesthetic appeal using a visual analog scale ranging from 0 to 100. Data were analyzed using descriptive statistics and diagnostic performance metrics (accuracy, sensitivity, specificity, PPV, and NPV), with attractiveness ratings compared between AI-generated and real images. Sensitivity for identifying AI-generated images was low across all groups (< 50%), while specificity for recognizing real images was high (> 87%). Dental students achieved the highest overall accuracy (72.7%), followed by laypeople (66.3%) and dentists (62.6%). AI-generated smiles were consistently rated as significantly more attractive than real outcomes by all groups (mean VAS: 78.8 vs. 37.9; p < 0.001). AI-generated smile images were less accurately identified and more aesthetically pleasing than real clinical outcomes compared to real post-treatment outcomes, which were more consistently recognized across all participant groups, regardless of treatment type.

PMID:41865052 | DOI:10.1038/s41598-026-41744-4

J Orthop Surg Res. 2026 Mar 21. doi: 10.1186/s13018-026-06769-5. Online ahead of print.

ABSTRACT

INTRODUCTION: This study compared the clinical outcomes of the all-inside endoscopic and the minimally invasive modified Bunnell suture configurations for the management of acute midsubstance Achilles tendon ruptures (AMATR).

METHODS: A retrospective analysis was conducted on 63 AMATR patients (54 men and 9 women, with a mean age of 39.84 ± 10.40 years (range, 21-62 years). All patients underwent Achilles tendon repair using the modified Bunnell suture configuration using the all-inside endoscopic repair (n = 31) or a minimally invasive repair (n = 32). The primary endpoint was postoperative functional outcome, assessed using the American Orthopaedic Foot and Ankle Society (AOFAS) score and the Achilles Tendon Total Rupture Score (ATRS) at 6, 12, and 24 months. Secondary endpoints included perioperative and short-term recovery parameters, including operative time, incision length, postoperative pain assessed by the Visual Analog Scale (VAS) on postoperative days 1 and 3, wound complications, and time to return to work and sports activities.

RESULTS: There were no intraoperative complications, and all patients in the endoscopic group achieved primary wound healing. At the 6-, 12-, and 24-month follow-up, both groups demonstrated significant improvement in AOFAS and ATRS scores over time, with no significant differences between groups. Regarding secondary endpoints, the all-inside endoscopic group had a significantly longer operative time but a significantly shorter incision length compared with the minimally invasive group (p < 0.05). VAS pain scores on postoperative days 1 and 3 were significantly lower in the endoscopic group (p < 0.05). No wound infections occurred in the endoscopic group, whereas three superficial infections were observed in the minimally invasive group; however, the difference was not statistically significant. Patients in the endoscopic group returned to work one week earlier (p < 0.05), while the time to return to sports was comparable between groups.

CONCLUSION: Both the all-inside endoscopic and the minimally invasive modified Bunnell suture configurations provide reliable repair for AMATR and support a successful return to occupational and athletic activity. While the all-inside endoscopic procedure was associated with a longer operative time, it offered advantages in terms of reduced early postoperative pain, smaller incisions, and earlier return to work, without compromising functional recovery at the 2-year follow-up.

PMID:41865018 | DOI:10.1186/s13018-026-06769-5

Sci Rep. 2026 Mar 21. doi: 10.1038/s41598-026-39638-6. Online ahead of print.

NO ABSTRACT

PMID:41865014 | DOI:10.1038/s41598-026-39638-6

Sci Rep. 2026 Mar 21. doi: 10.1038/s41598-026-38952-3. Online ahead of print.

ABSTRACT

Environmentally benign and straightforward spectrophotometric methods were developed and validated for the simultaneous determination of saxagliptin (SAX), metformin (MET), and the pharmacopeial impurity of MET, melamine (MEL), in bulk powder and pharmaceutical formulations. These proposed approaches provide reliable, low-cost, and accessible alternatives to conventional chromatographic techniques, which often require complex instrumentation, extended analysis times, and significant solvent consumption. Two complementary spectrophotometric methods were established. Method A, the ratio-difference approach, utilized MEL as a divisor for the quantification of SAX, while SAX served as a divisor for determining MET and MEL. Method B, based on the first derivative of ratio spectra, applied MEL as a divisor under optimized conditions (scaling factor = 10, Δλ = 4 nm). However, MEL could not be quantified by Method B because its derivative ratio signals in the selected spectral region were too weak and overlapped extensively with those of SAX and MET, preventing the establishment of a reliable linear calibration curve for this impurity. The methods exhibited linearity over the ranges of 5-90 µg/mL for SAX, 1-40 µg/mL for MET, and 0.5-10 µg/mL for MEL. Validation in accordance with ICH Q2(R1) guidelines confirmed their accuracy, precision, selectivity, and specificity. The results obtained by the proposed methods were statistically compared with those of a reported RP‑HPLC method, confirming the reliability of the proposed procedures. The environmental impact was assessed using the principles of green analytical chemistry (GAC), which incorporates sustainability by promoting methods that limit hazardous reagents, reduce energy consumption, and minimize waste while maintaining suitable analytical performance. Holistic evaluation tools such as the analytical greenness metric (AGREE), the green analytical procedure index (GAPI), the national environmental methods index (NEMI), the blue applicability grade index (BAGI), and the RGB 12 model enable simultaneous assessment of analytical quality, environmental impact, and practical applicability. These tools foster the development of “white” analytical chemistry and complement emerging indices like the environmental and practical performance index (EPPI).Overall, these spectrophotometric approaches represent sustainable, efficient, and accessible analytical alternatives for the routine quality control of Saxagliptin and Metformin in combined pharmaceutical formulations.

PMID:41865005 | DOI:10.1038/s41598-026-38952-3