Scientific Reports[JOURNAL]
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200 papers
Metabolic profiling and microbiological evaluation of Staphylococcus aureus in a poly-microbial system in soft white cheese.
El-Ssayad MF, Elaaser M, Abd-Elfatah SI … +1 more , Salem SH
Sci Rep · 2026 Jul · PMID 42401644 · Full text
There is a significant lack of data on microbial interactions in polymicrobial food systems. This study aimed to investigate the effects of Escherichia coli and Bacillus cereus on Staphylococcus aureus growth and metabol...
There is a significant lack of data on microbial interactions in polymicrobial food systems. This study aimed to investigate the effects of Escherichia coli and Bacillus cereus on Staphylococcus aureus growth and metabolite production in soft white cheese, a food model. The growth dynamics of single and mixed cultures of these pathogens in various microbial systems were examined, including single, binary, and tertiary combinations. Gas chromatography-mass spectrometry (GC-MS) was used to analyze the metabolic profiles of these poly-microbial systems. Additionally, we assessed the impact of nisin/EDTA on the tertiary microbial system in soft white cheese and evaluated its microbiological safety and quality. All microbiological experiments were performed in triplicates and data expressed as mean ± Std (P < 0.05). The results showed that B. cereus growth was significantly reduced in binary (Bc -Sa) and tertiary (Bc- Sa-Ec) systems, with reductions of 95.91% (1.42 Log cycle) and 94.77% (1.4 Log cycle), respectively. E. coli growth was also reduced in binary (Ec- Sa) and tertiary (Bc- Sa-Ec) systems, with reductions of 66.67% (0.48 Log cycle) and 96.67% (1.48 Log cycle), respectively. S. aureus growth was inhibited by 54.17% (0.33 Log cycle), 79.17% (0.67 Log cycle), and 91.67% (1.07 Log cycle) in (Bc -Sa), (Bc- Sa-Ec), and (Ec- Sa) systems, respectively. GC-MS analysis revealed the presence of various metabolites, including hydroxyurea, methane nitroso, and pyridinium derivatives, with different ratios depending on the poly-microbial system. The addition of nisin/EDTA effectively reduced growth in both single and poly-microbial systems, and its application in soft white cheese enhanced microbiological safety and quality. Our findings suggest that studying microbial interactions and metabolite production in poly-microbial systems can inform the development of effective preservation methods that improve food safety and quality while enhancing sensory characteristics.
Granular soil densification using expansive resins.
Lee A, Wehbi M, Szulca M
Sci Rep · 2026 Jul · PMID 42401643 · Full text
Specialist expansive resins have been developed over time for the purposes of ground improvement and soil stabilisation. They are injected into the soil in two phase liquid form (resin and hardener) and on reaction expan...
Specialist expansive resins have been developed over time for the purposes of ground improvement and soil stabilisation. They are injected into the soil in two phase liquid form (resin and hardener) and on reaction expand into a hardened material. The expansive forces generated cause granular soils to be compacted. This technology has been developing since the 1970's and it is installed mainly by employing the observational approach to grouting, which is based on the measurement of lift and the execution of pre and post in-situ testing to verify performance. This is an iterative process, which may require secondary or even tertiary injections to meet specified requirements. The objective of this paper is to propose an innovative design approach to the densification of coarse granular soils via the injection of expansive resins. This will enable designers to more accurately calculate the required amount of material to meet the engineering objectives of ground improvement and soil stabilisation projects. The design approach is based on a combination of the cavity expansion theory and a cubic compaction model which equates the volumetric expansion of the resin to an increase in the angle of friction of granular soils. This approach has been tested in the laboratory to quantify the cavity expansion and by finite element methods to confirm the strain generated is proportional to the expansion of the resin. Two ground improvement case studies are described, which were undertaken in loose to very loose coarse granular soils. Expansive resin treatments were designed using the new method described and predictive results compared to the current state of the art. Following the treatment an increase in soil densification of between 49.5% and 51.6% was measured on the two sites. The mean difference between the actual and predicted performance of the new design approach on these two cases was - 0.3% compared to a difference of -19.2% for the current state of the art. The surface boundary conditions, depth of injection and in-situ density are particularly important factors to define when undertaking expansive resins design. The case studies and PLAXIS modelling undertaken indicate that the new model will slightly underestimate actual compaction when the surface movement is constrained but overestimate it, if the soils are very loose, when not due to soil heave. The innovative design approach is the first to be verified by actual field case studies and provides a method to optimise the mass of expansive resin to be used for practical application cases, which should lead to a more sustainable and accurate approach to design.
Study on the evolution mechanism of permeability and displacement efficiency in CO-ECBM in low-permeability coal seam.
Zhang F, Lu X, Pan T … +1 more , Han Y
Sci Rep · 2026 Jul · PMID 42401642 · Full text
Unmineable coal seams and residual coal resources in closed mines provide ideal carriers for CO₂ sequestration. However, the evolution mechanisms of permeability and displacement efficiency during CO₂-ECBM in low-permeab...
Unmineable coal seams and residual coal resources in closed mines provide ideal carriers for CO₂ sequestration. However, the evolution mechanisms of permeability and displacement efficiency during CO₂-ECBM in low-permeability coal seams remain unclear, which restricts the engineering application efficiency of this technology. In this study, the No. 15 coal seam of the Lutaishan Coal Mine was taken as the research object. A fully coupled thermal-hydraulic-mechanical model of CO₂-ECBM was constructed and validated using COMSOL Multiphysics software, and a quantitative evaluation method for key influencing factors was proposed based on coal deformation effects. The results indicate that injection pressure is the dominant factor affecting permeability, and its influence range expands with increasing pressure and time. In the near-injection well region, coal matrix swelling induced by CO₂ adsorption is stronger than matrix shrinkage caused by CH₄ desorption, leading to a decrease in coal reservoir permeability; the higher the injection pressure, the more significant the permeability reduction. In the near-production well region, CH₄ desorption causes matrix shrinkage, resulting in increased permeability. The intermediate zone remains relatively stable. The influence of injection temperature is weak: in the near-injection well area, thermal expansion reduces permeability; in the adjacent zone, reduced gas adsorption capacity leads to a recovery in permeability; the peripheral zone is stable, and the near-production well area remains dominated by CH₄ desorption. Increasing injection pressure accelerates displacement, promoting CH₄ recovery and CO₂ storage, while increasing temperature slightly reduces recovery efficiency but has a minor impact. Under all scenarios, CO₂ storage exceeds CH₄ production. This study aims to provide guidance for injection strategies of CO₂-ECBM in low-permeability coal seams, and its findings help optimize displacement parameters, thereby improving engineering implementation efficiency.
A fog-aware lightweight vision transformer architecture for real-time coastal landscape recognition on edge devices.
He Y, Liu D, Hu Y … +1 more , Li Q
Sci Rep · 2026 Jul · PMID 42401641 · Full text
Intelligent landscape recognition sits at the heart of smart coastal tourism, yet pushing vision Transformers onto resource-constrained edge hardware remains awkward-the self-attention mechanism scales quadratically with...
Intelligent landscape recognition sits at the heart of smart coastal tourism, yet pushing vision Transformers onto resource-constrained edge hardware remains awkward-the self-attention mechanism scales quadratically with token count, and marine atmospheric haze quietly erodes recognition accuracy long before it is noticed in the laboratory. We propose a hybrid lightweight architecture that swaps standard self-attention in the early stages for depthwise separable convolution token mixers, switches to kernel-based linear attention in the deeper stages, and follows an adaptive channel reduction policy that trims feature dimensions where redundancy is empirically highest. A Fog-Aware Feature Calibration module, motivated by the Koschmieder atmospheric scattering model, is embedded between the convolutional and attention stages so that learned dehazing happens inside the network rather than as a separate preprocessing pass. Training proceeds through a three-phase pipeline that interleaves progressive structured pruning with temperature-scheduled knowledge distillation from a Swin-Base teacher; the composite objective shrinks the model to 4.8 M parameters and 0.91 GFLOPs without abrupt accuracy collapse. On a newly collected 17,565-image dataset spanning eight coastal scene categories across six shoreline regions of Zhejiang Province, our model reaches 92.6% ± 0.4% Top-1 accuracy (mean ± std over three independent runs), the best result among all baselines below 6 M parameters, including the recently released MobileViT-v2, FastViT, TinyViT, EfficientViT and RepViT. On an NVIDIA Jetson Orin Nano with TensorRT INT8 optimisation the system delivers 18.3 ms latency (54.6 FPS) within a 7.4 W average power envelope, and a 200 m visibility heavy-fog subset that mixes synthetic and real captures shows an 85.7% accuracy retention rate-6.8 percentage points above the strongest baseline. Cross-dataset zero-shot tests on Fujian, Hainan and the Places365 coastal subset, together with deployment benchmarks on Jetson Nano 4 GB and Coral Edge TPU, suggest the design transfers reasonably-though not effortlessly-beyond the original collection sites.
miRNA-mediated therapeutic effects of AST-001 through modulation of key marker genes in autism spectrum disorder.
Lee DH, Park EG, Kim WR … +8 more , Lee YJ, Jeong HS, Roh HY, Jeong GR, Hwang SK, Hong J, Kim MJ, Kim HS
Sci Rep · 2026 Jul · PMID 42401640 · Full text
Dysregulation of microRNAs (miRNAs) has emerged as a critical factor in the pathophysiology of Autism spectrum disorder (ASD), particularly in the disruption of gene networks involved in neurodevelopment. AST-001, an L-s...
Dysregulation of microRNAs (miRNAs) has emerged as a critical factor in the pathophysiology of Autism spectrum disorder (ASD), particularly in the disruption of gene networks involved in neurodevelopment. AST-001, an L-serine derivative, has shown potential to improve ASD-like behaviors by modulating dopaminergic signaling, but its underlying molecular mechanisms remain unclear. This study aimed to explore whether AST-001 exerts therapeutic effects by regulating ASD-related gene expression through miRNA modulation. Male offspring exposed to VPA were treated with AST-001 for two weeks. Midbrain samples were collected from control, VPA, and AST-001-treated VPA groups. qPCR and small RNA sequencing (small RNA-seq) were performed to profile gene and miRNA expression. The regulatory relationships between miRNAs and ASD-related genes were evaluated using dual-luciferase assays and qPCR. Among seven ASD-related genes examined, DLG4, PAX5, and SNAP23 were significantly upregulated in the VPA model and downregulated following AST-001 treatment. Small RNA-seq and qPCR identified four miRNAs (mmu-miR-378c, mmu-miR-483-5p, mmu-miR-3085-3p, and mmu-miR-128-3p) that were downregulated in the VPA group and restored toward Control levels after AST-001 treatment. Gene ontology analysis showed that these miRNAs are involved in synaptic signaling and neurodevelopmental processes associated with ASD. Their predicted binding to the 3' UTRs of the ASD-related genes was further analyzed and characterized. These findings suggest a potential mechanism by which AST-001 modulates miRNA-mediated regulation of genes involved in synaptic function and brain development, including DLG4, PAX5, and SNAP23. This post-transcriptional modulation highlights a plausible pathway to help rebalance disrupted dopaminergic and synaptic signaling networks, offering early mechanistic insights into the therapeutic potential of AST-001.
Assessing the validity of self-reported weight, height, and body mass index among hispanic breast cancer survivors.
Zeinomar N, Montague J, Qin B … +5 more , Perlstein M, Bjerklie S, Wang T, Pawlish KS, Bandera EV
Sci Rep · 2026 Jul · PMID 42401639 · Full text
Self-reported measurements of body size are commonly used in cancer epidemiological studies; however, inaccuracies may lead to misclassification of body mass index (BMI) and biased estimates of associations with health o...
Self-reported measurements of body size are commonly used in cancer epidemiological studies; however, inaccuracies may lead to misclassification of body mass index (BMI) and biased estimates of associations with health outcomes. Despite their widespread use, the validity of these self-reported measures has not been well established among Hispanic breast cancer survivors, a growing and understudied population. This is particularly important, as prior research suggests that the accuracy of self-reported anthropometric measures may vary across racial and ethnic groups, highlighting the need for population-specific validation. To address this gap, we compared self-reported and measured weight, height, and BMI among 192 Hispanic women participating in the New Jersey Breast Cancer Survivors Study using intraclass correlation coefficients (ICCs), Bland-Altman analyses, and Cohen's kappa, and examined predictors of reporting error using multivariable regression models. Data were collected during home visits, including body measurements taken by research staff and interviewer-administered questionnaires on body size and related factors. Self-reported and measured values were highly correlated (Intraclass correlation coefficients (95% Confidence Intervals (CI)): 0.99 (0.99, 0.99), 0.8 (0.64, 0.88), 0.95 (0.92, 0.97) for weight, height, and BMI, respectively). The agreement between self-reported and measured BMI categories (normal, overweight, and obese) was strong (kappa: 0.85; 95% CI: 0.79, 0.91). The mean difference observed between self-reported and measured BMI (-0.67 kg/m) was primarily explained by slight over-reporting of height (mean difference: 1.94 cm). These findings support the use of self-reported weight, height, and BMI measures in large epidemiologic studies of Hispanic/ Latina cancer survivors when direct measurements are not feasible.
Cinnamyl alcohol dehydrogenase (CAD) underlies the orange lemma trait and lignin reduction in barley.
Sato K, Morita M, Yamaji N … +3 more , Kako R, Ushijima T, Hisano H
Sci Rep · 2026 Jul · PMID 42401638 · Full text
Barley (Hordeum vulgare L.) is one of the world's major cereal crops and is widely used for feed, brewing, and food. Reducing lignin content in barley grain and straw is beneficial for improving forage digestibility and...
Barley (Hordeum vulgare L.) is one of the world's major cereal crops and is widely used for feed, brewing, and food. Reducing lignin content in barley grain and straw is beneficial for improving forage digestibility and enhancing the efficiency of bioethanol production. The orange lemma mutation-characterized by orange pigmentation of husks and nodes-has long been associated with altered lignin metabolism; however, its genetic basis has remained unclear. We show that Cinnamyl Alcohol Dehydrogenase (CAD) is the causal gene underlying the orange lemma phenotype in barley. Genetic mapping using a 'Haruna Nijo' × 'L053' F₂ population and the Barley 50 K SNP array defined a candidate region on chromosome 6H containing the CAD gene. Sequence analysis revealed that all orange lemma mutants, including both naturally occurring and EMS-induced lines, carried nucleotide changes in the CAD gene, resulting in amino acid substitutions or premature stop codons. Furthermore, CRISPR/Cas9-mediated knockout of CAD in the cultivar 'Golden Promise' reproduced the orange lemma phenotype, providing functional validation. The knockout plants also showed significantly lower lignin content than wild-type plants. These findings resolve a long-standing question regarding the genetic basis of the orange lemma trait and demonstrate that disruption of CAD alters lignin accumulation in barley. This work provides a valuable genetic resource for breeding barley cultivars with improved biomass utilization for feed and bioenergy applications.
Roadside trees along school routes enhance foliar particulate-matter retention but increase children's pedestrian-level exposure.
Hoppa A, Sikorski P, Przybysz A … +4 more , Łaszkiewicz E, Nawrocki A, Archiciński P, Sikorska D
Sci Rep · 2026 Jul · PMID 42401637 · Full text
Children's school commutes represent microenvironments where exposure to traffic-related particulate matter (PM) occurs at breathing height. Roadside trees are often promoted to reduce PM by capturing particles on their...
Children's school commutes represent microenvironments where exposure to traffic-related particulate matter (PM) occurs at breathing height. Roadside trees are often promoted to reduce PM by capturing particles on their leaves, but dense tree crowns can also limit ventilation, increasing concentrations at pedestrian level. We quantified these effects along frequently used access routes to primary schools in Łódź, Poland. In June 2022, we measured PM2.5 and PM10 at 1.4 m above ground during commuting periods (n = 242). We assessed tree crown structures using two indicators: horizontal crown density (leaf area index, LAI) and vertical crown density (the proportion of tree crowns obstructing visibility). Our mixed-effects models showed that greater vertical crown density was associated with higher airborne PM: each one percentage-point increase in vertical crown density corresponded to roughly 1.9% more PM at child height. Higher horizontal crown density (LAI), by contrast, improved foliar retention - a 1% increase in LAI was associated with 0.52% and 0.56% higher foliar PM₁₀ and PM₂.₅, respectively. Thus, while roadside trees offer particulate deposition benefits, they may also increase pedestrian exposure. Urban planning should consider the balance between horizontal crown density and vertical crown density to limit airflow obstruction, rather than assuming higher vegetation density always enhances air quality.
Sevoflurane does not restore alveolar fluid clearance in a murine model of endotoxin-induced acute lung injury.
Finotto T, Bezaud B, Theilliere C … +12 more , Roche C, Vivier L, Henrioux F, Triché LR, Saint-Béat C, Monturet L, Belville C, Bouvier D, Blanchon L, Sapin V, Garnier M, Jabaudon M
Sci Rep · 2026 Jul · PMID 42401636 · Full text
Volatile anesthetics have demonstrated anti-inflammatory and epithelial-protective effects in several sterile experimental models of acute lung injury (ALI). However, their effects in endotoxin-induced ALI remain unclear...
Volatile anesthetics have demonstrated anti-inflammatory and epithelial-protective effects in several sterile experimental models of acute lung injury (ALI). However, their effects in endotoxin-induced ALI remain unclear, and recent clinical data have raised concerns regarding their potential impact on patient outcomes. We investigated whether sevoflurane restores alveolar fluid clearance (AFC) and preserves epithelial integrity in a murine model of lipopolysaccharide (LPS)-induced ALI. Wild-type (WT) and receptor for advanced glycation end-products-deficient (RAGE-/-) mice received intratracheal lipopolysaccharide (LPS) and were exposed to sevoflurane (1 vol %) or control gas for 1 h. Our primary outcome, the net AFC rate was measured 48 h after injury. Secondary outcomes included lung histology, bronchoalveolar lavage (BAL) protein and cytokine levels, and lung expression of epithelial sodium channel (ENaC), water transporter aquaporin-5 (AQP5), and adherens junction protein E-cadherin. LPS induced significant weight loss and severe lung injury, with impaired AFC and downregulation of ENaC and AQP5. Sevoflurane did not restore AFC, reduce alveolar-capillary permeability, or preserve epithelial junctional integrity. RAGE-/- mice exhibited attenuated lung injury and partial preservation of epithelial marker expression, without a statistically significant interaction with sevoflurane exposure. BAL cytokine levels were largely unaffected by sevoflurane. These findings suggest context-dependent effects of a 1-h exposure to 1.0 vol% sevoflurane in experimental ALI, with absence of epithelial benefit in a mouse model of endotoxin-induced ALI, in contrast with previously reported effects in a sterile model. This work may provide mechanistic insight into the differential translational impact of inhaled sedation strategies.
Fabrication of hybrid PCL-Chitosan/PVA nanofibers by hybrid electrospinning for Local melanoma skin cancer therapy.
Jafari-Najaf-Abadi A, Pazoki-Toroudi H, Mirjafary Z … +2 more , Akbarzadeh A, Hadjianfar M
Sci Rep · 2026 Jul · PMID 42401635 · Full text
In this study, we have a type of functional nanofibers, hybrid nanofibers containing Polycaprolactone (PCL) / Chitosan (CS) and Polyvinyl alcohol (PVA) were successfully fabricated by hybrid electrospinning method. Piogl...
In this study, we have a type of functional nanofibers, hybrid nanofibers containing Polycaprolactone (PCL) / Chitosan (CS) and Polyvinyl alcohol (PVA) were successfully fabricated by hybrid electrospinning method. Pioglitazone Hydrochloride (PIO) was incorporated in PCL/CS solution due to its hydrophobic nature, and Gemcitabine Hydrochloride (GEM) was incorporated in PVA solution due to its hydrophilic nature. The prepared hybrid PCL-CS-PIO/PVA-GEM nanofibers exhibited a biphasic release profile in each case, indicating an initial burst followed by a sustained phase of GEM and PIO over 5 days. The maximum amount released from the hybrid nanofibers reached 75.88 ± 1.5% of the GEM and 64.54 ± 2.05% of the PIO in a medium of pH 7.4. Flow cytometry and MTT analyses demonstrated that the combination of PIO and GEM induced apoptosis and inhibited the growth of melanoma cancer cell lines by inhibiting proliferation with cell viability of 51.34 ± 2.2% and 46.04 ± 1.5% after 24 and 48 h compared to control group. Obtained nanofibers were assessed for their chemical composition and morphology followed by scanning electron microscopy (SEM), FTIR, contact angle measurements and drug release profile. Then, a cytotoxicity study was performed on human melanoma cancer cell line, followed by investigating its potential in treatment applications.
Green valorization of cotton-acrylic fabric blends into magnetic nanofiber adsorbents for PFAS and organic dye remediation in complex wastewater streams.
Mubarak MF, Metwally BS, Bendary HI … +5 more , Hosny R, Nassar MY, Alfurayj I, Taha A, Bakir EM
Sci Rep · 2026 Jul · PMID 42401634 · Full text
The increasing generation of mixed textile waste and the persistence of per- and polyfluoroalkyl substances (PFAS) and synthetic dyes in industrial effluents present significant challenges for sustainable wastewater trea...
The increasing generation of mixed textile waste and the persistence of per- and polyfluoroalkyl substances (PFAS) and synthetic dyes in industrial effluents present significant challenges for sustainable wastewater treatment. In this study, cotton-acrylic textile waste was valorized into multifunctional magnetic nanofiber adsorbents (CA-Fe₃O₄-NF) via a combined sol-gel-assisted in situ co-precipitation and electrospinning approach. The resulting nanofibers exhibited a hierarchically porous structure, a surface area of 112 m g⁻, and superparamagnetic properties enabling rapid magnetic separation. The developed material demonstrated effective adsorption performance toward PFOS, PFOA, methylene blue, and rhodamine B, with maximum adsorption capacities of 184, 165, 142, and 118 mg g⁻, respectively, along with relatively fast kinetics and spontaneous, endothermic adsorption behavior. The nanofibers retained more than 90% of their initial performance after multiple regeneration cycles, indicating good reusability. Unlike many previously reported magnetic nanofiber adsorbents that rely on virgin polymers and are evaluated under simplified conditions, this study employs waste-derived materials and includes assessment under varying pH, ionic strength, and real wastewater matrices, providing improved environmental relevance. Although the material exhibited potential for simultaneous removal of PFAS and dyes in simplified systems, the study primarily focuses on controlled experimental conditions, and further validation under more complex multi-component environments is required. In addition, the proposed adsorption mechanisms are based on indirect evidence derived from spectroscopic analysis and adsorption behavior, and should therefore be considered as plausible interpretations rather than definitive conclusions. Overall, this work presents a sustainable and cost-effective approach for converting textile waste into functional magnetic nanofiber adsorbents, highlighting their potential application in wastewater treatment while acknowledging the need for further validation under realistic conditions.
Development of a hybrid RSM-Fermatean fuzzy WASPAS framework for multi-objective drilling optimization of WAAM nickel-stainless steel bimetallics.
Sivam SPSS, Kesavan S, Sathishkumar P
Sci Rep · 2026 Jul · PMID 42401633 · Full text
This study develops an integrated RSM-Fermatean fuzzy WASPAS framework for multi-response drilling optimization of wire arc additively manufactured ERNiCrMo-3/316LSi nickel-stainless steel bimetallic structures. WAAM bim...
This study develops an integrated RSM-Fermatean fuzzy WASPAS framework for multi-response drilling optimization of wire arc additively manufactured ERNiCrMo-3/316LSi nickel-stainless steel bimetallic structures. WAAM bimetallics often contain bead waviness, geometric deviation, residual stress, thermal distortion, and microstructural heterogeneity, which make drilling performance difficult to optimize through a single response. The effects of cutting speed, feed rate, tool point angle, and coolant condition were evaluated through twelve drilling trials. Four responses were considered: surface roughness, material removal rate, hole dimensional accuracy, and energy consumption. The measured results showed clear variation across the tested conditions. Surface roughness ranged from 0.666 to 2.166 μm, material removal rate from 10 to 75 mm³/min, hole dimensional accuracy from 90 to 99%, and energy consumption from 120 to 300 W. Response Surface Methodology was used to model factor effects and interaction behavior, while Fermatean fuzzy logic was applied to reduce the influence of response uncertainty in ranking. WASPAS combined the weighted criteria into a single ranking index to identify the best compromise among the tested alternatives. The selected condition was 50 m/min cutting speed, 0.1 mm/rev feed rate, 135° tool point angle, and oil-based cooling, producing Ra = 1.1667 μm, MRR = 50 mm³/min, HDA = 96%, and EC = 220 W. This condition offered a balanced trade-off among surface quality, productivity, dimensional accuracy, and energy demand. The observed performance is associated with reduced chip load, stable tool engagement, improved chip evacuation, lower friction, and controlled heat generation at the tool-workpiece interface. Statistical validation and sensitivity analysis showed that the ranking remained stable within the tested experimental range. The proposed framework provides a reproducible decision-support method for drilling the investigated WAAM bimetallic system and requires validation before use in other WAAM material combinations.
Interpretable deep learning to predict one year glycemic control in type 1 diabetes using real world data.
Tapia-Galisteo J, Somolinos-Simón FJ, Hernando ME … +1 more , García-Sáez G
Sci Rep · 2026 Jul · PMID 42401631 · Full text
Type 1 diabetes (T1D) involves long-term health risks and challenges in individualizing therapeutic strategies. Meeting glycemic targets is a reliable indicator of effective diabetes management and positive prognosis. Th...
Type 1 diabetes (T1D) involves long-term health risks and challenges in individualizing therapeutic strategies. Meeting glycemic targets is a reliable indicator of effective diabetes management and positive prognosis. This study develops a clinically interpretable predictive model of 1-year glycemic control-defined as a binary outcome based on HbA1c values-using Real-World Data from 8999 T1D patients. A 1-year horizon is clinically meaningful, as annual reassessment aligns with standard care guidelines and supports timely treatment adjustments and complication screening. Deep Learning techniques are evaluated for discrimination and calibration. Various feature subsets, calibration methodologies, and sampling strategies for unbalanced outcomes are compared. The best-performing model includes 12 features, encompassing socio-demographics, clinical variables, associated complications, and pharmacological treatment. The scaling-binning calibration technique achieved the best calibration performance. The final model yielded an area under the receiver operating characteristic curve of 0.870, an F1-score of 0.789, and calibration errors between 0.014 and 0.038. Sampling techniques did not outperform unbalanced models followed by calibration. To enhance interpretability, a graphical representation quantifies the contribution of each variable to the patient's risk score. Combining strong predictive accuracy, calibration, and interpretability, the model may help clinicians make individualized decisions, intensify care for high-risk patients, and optimize healthcare resource allocation.
A novel dynamic risk assessment tool for evaluating cybersecurity risks in the digital industry.
Halawi Ghoson N, Benfriha K
Sci Rep · 2026 Jul · PMID 42401630 · Full text
The increasing integration of Operational Technology (OT) and Information Technology (IT) systems within industrial environments has introduced significant cybersecurity challenges. Traditional risk assessment approaches...
The increasing integration of Operational Technology (OT) and Information Technology (IT) systems within industrial environments has introduced significant cybersecurity challenges. Traditional risk assessment approaches often lack the adaptability and scalability needed to address evolving threat landscapes and complex asset interdependencies. This paper presents a semi-automated risk analysis tool designed to evaluate OT cybersecurity risks through a multi-layered approach that integrates asset inventories, governance-based questionnaires, and external threat intelligence databases such as MITRE ATT&CK and CVE. The tool applies fuzzy logic to map potential threats and vulnerabilities, and generates graphical outputs including risk level visualizations, threat distribution charts, and lifecycle-based exposure matrices. Through experimentation on an industrial platform and validation via intrusion testing, the tool demonstrated its capacity to identify high-risk assets and operational stages that require mitigation. The framework provides a practical foundation for structured, scalable, and governance-aligned OT risk assessments.
Antimicrobial activity of plasma-activated water against Paenibacillus larvae, the causative agent of American foulbrood.
Boonmee T, Sinpoo C, Nakpla S … +2 more , Disayathanoowat T, Chaimanee V
Sci Rep · 2026 Jul · PMID 42401629 · Full text
Paenibacillus larvae, the causative agent of American foulbrood, poses a major threat to global apiculture. This study evaluated the antibacterial efficacy of plasma-activated water generated using air (PAW-Air) or argon...
Paenibacillus larvae, the causative agent of American foulbrood, poses a major threat to global apiculture. This study evaluated the antibacterial efficacy of plasma-activated water generated using air (PAW-Air) or argon (PAW-Argon) against vegetative P. larvae. PAW-Air contained higher concentrations of nitrate (NO₃⁻; 100-1,000 mg/L) and nitrite (NO₂⁻; 50-600 mg/L), whereas PAW-Argon contained higher concentrations of hydrogen peroxide (H₂O₂; 30-150 mg/L). Despite these physicochemical differences, both PAW-Air and PAW-Argon significantly reduced viable cell counts. Viable counts ranged from 4.65 to 4.74 log CFU/mL following PAW-Air treatment and from 4.54 to 4.67 log CFU/mL following PAW-Argon treatment. PAW exposure increased membrane-compromised cells and reduced relative membrane integrity to 35.87-37.47%, accompanied by enhanced leakage of intracellular nucleic acids and proteins, and severe morphological damage. Among representative long-lived reactive species, H₂O₂ exhibited dose-dependent antibacterial effects, whereas NO₃⁻ and NO₂⁻ showed comparatively weaker effects. In a honeybee larval infection model, larvae fed PAW-treated bacteria showed significantly reduced bacterial loads, with no detectable colonies in the PAW-Air groups and only 1.11 ± 0.67 CFU/larva in the PAW-Argon group. Larval survival was also improved in PAW-treated groups (59.38-60.42%) compared with untreated infection controls (43.23%). These findings suggest that PAW can reduce the culturability and infectivity of vegetative P. larvae, likely through oxidative membrane-associated damage, and provide a basis for further investigation of plasma-based strategies for American foulbrood control.
Influence of diffractive surface geometry on optical quality and halo formation in sinusoidal trifocal intraocular lenses.
Martínez-Espert A, Vila-Andrés R, García-Delpech S … +3 more , Esteve-Taboada JJ, Micó V, Furlan WD
Sci Rep · 2026 Jul · PMID 42401628 · Full text
This study reports the optical characterization of three non-kinoform (sinusoidal-based) designs of trifocal multifocal intraocular lenses (MIOLs): Acriva Trinova Pro C (VSY Biotechnology GmbH, Germany), I-Stream Diffrax...
This study reports the optical characterization of three non-kinoform (sinusoidal-based) designs of trifocal multifocal intraocular lenses (MIOLs): Acriva Trinova Pro C (VSY Biotechnology GmbH, Germany), I-Stream Diffrax Trifocal Plus (MD-Tech Srl, Italy), and Intensity SL (Hanita Lenses Ltd, Israel). Diffractive surface profiles were quantitatively reconstructed using a compact lensless digital in-line holography (DIH) system, enabling high-resolution morphological assessment. In vitro optical performance was evaluated with a custom ISO 11979-2:2014-compliant optical bench incorporating automated axial point spread function (PSF) acquisition. All MIOLs exhibited well-defined trifocal behavior at 550 nm with comparable longitudinal chromatic aberration (LCA) at their principal focal planes. However, the distinct geometric characteristics of the sinusoidal diffractive structures resulted in measurable differences in both the modulation transfer function (MTF) and the halo patterns produced. These findings highlight the influence of diffractive surface geometry in shaping optical quality and photic phenomena, providing relevant insights for personalized MIOL selection.
Precise ECG diagnosis and validation of educational utility for acute myocardial infarction using deep learning and explainable artificial intelligence.
Kim J, Shon B, Kim Y … +7 more , Kim N, Jang Y, Lee J, Yoon SM, Yang DH, Kim N, Jeong S
Sci Rep · 2026 Jul · PMID 42401625 · Full text
Artificial intelligence (AI) holds significant promise for electrocardiogram (ECG) analysis, yet accurately detecting non-ST-segment elevation myocardial infarction (NSTEMI) and overcoming the "black box" nature of deep...
Artificial intelligence (AI) holds significant promise for electrocardiogram (ECG) analysis, yet accurately detecting non-ST-segment elevation myocardial infarction (NSTEMI) and overcoming the "black box" nature of deep learning models remain persistent challenges. Here, we present a comprehensive deep learning framework capable of classifying STEMI, NSTEMI, and non-acute coronary syndrome (non-ACS) from 12-lead ECG images, while also localizing infarction sites. Utilizing ,2070 validated ECGs, our pipeline integrates ResNet for acute myocardial infarction detection, Faster R-CNN for ST-segment elevation localization, and an ensemble approach for final classification. The model achieved a 98.3% AUROC for detection and an overall three-class accuracy of 93.6%, with high F1 scores for identifying infarction territories. To address interpretability, we developed an explainable AI (XAI) web viewer that visualizes detected regions. Furthermore, we evaluated the model's utility as an educational tool in a prospective pilot study with medical students. AI assistance significantly improved the students' overall diagnostic accuracy from 43% to 82% (p < 0.05), with notable gains in identifying NSTEMI and complex STEMI subtypes. These findings demonstrate that our interpretable AI model not only supports clinical decision-making with high diagnostic precision but also serves as an effective educational aid for enhancing novice clinicians' proficiency.
Study on the properties of TiC, Nano-CaCO, and steel fiber reinforced concrete based on RSM-BBD: optimization of mechanical properties.
Bai T, Yang X, Wang Z … +2 more , Wang P, Liu Z
Sci Rep · 2026 Jul · PMID 42401624 · Full text
As modern civil engineering demands increasingly higher strength, toughness, and long-term stability from concrete materials, the performance limitations of ordinary concrete in complex service environments have become i...
As modern civil engineering demands increasingly higher strength, toughness, and long-term stability from concrete materials, the performance limitations of ordinary concrete in complex service environments have become increasingly apparent. The dual-blending modification of nanomaterials and steel fibers (SF) has emerged as an effective technical approach to overcome these limitations. The ratio design of the TiC-NC-SF dual-blending system has largely relied on empirical methods, lacking systematic quantitative optimization. The synergistic mechanisms among multiple factors remain unclear, hindering the engineering application of modified concrete. This study employs Box-Behnken experimental design and response surface methodology to systematically investigate the influence patterns of three factors on concrete's 28-day compressive strength, splitting tensile strength, and flexural strength. Scanning electron microscopy (SEM) characterization reveals microstructural mechanisms, while model optimization validates optimal ratios. Results indicate the dominance order of the three factors on concrete mechanical properties is SF > NC > TiC (with NC and TiC having similar effects on compressive strength). A significant synergistic enhancement effect exists between TiC and NC (interaction term P < 0.05). Both TiC and NC enhance concrete strength by optimizing matrix density through "hydration regulation and multi-level filling," while SF dominates crack control via "bridging crack propagation and energy dissipation toughening." No significant interaction was observed between TiC-SF or NC-SF (P > 0.05). Concrete compressive strength exhibits a quadratic variation with increasing dosage of all three factors, with SF exerting greater influence on splitting tensile strength and flexural strength. The response surface model optimization yielded the optimal mix design of TiC 2.12%, NC 2.14%, and SF 1.19%. Its 28-day compressive strength, splitting strength, and flexural strength reached 69.83 MPa, 7.22 MPa, and 9.34 MPa, respectively (measured values). The response surface optimization values were 70.50 MPa, 7.52 MPa, and 9.60 MPa, respectively. According to the experimental results, these values increased by 22.66%, 26.44%, and 15.02%, respectively, compared with the control group (CG). The performance deviation from the optimal experimental group was less than 0.5%, and the deviation from the optimization target was within 10%. SEM characterization revealed that the cement matrix in the CN10 and CN18 groups exhibited significantly higher densification than the CG group, with SF tightly bonded to the matrix interface.
Deep learning-accelerated NEGF formalism for autonomous design of quantum transport in microscopic heterostructures.
Awol B
Sci Rep · 2026 Jul · PMID 42401620 · Full text
Two-dimensional (2D) materials exhibit a wide range of electronic properties that make them promising candidates for next-generation nanoelectronic devices. Accurate prediction of their quantum transport behavior is ther...
Two-dimensional (2D) materials exhibit a wide range of electronic properties that make them promising candidates for next-generation nanoelectronic devices. Accurate prediction of their quantum transport behavior is therefore of both fundamental and technological importance. While the Non-Equilibrium Green's Function (NEGF) formalism coupled with Density Functional Theory (DFT) provides reliable insights, its high computational cost limits applications to large-scale or high-throughput studies. Here we present DeePTB-NEGF, a framework that combines a deep learning-based tight-binding Hamiltonian derived directly from first-principles calculations (DeePTB) with efficient quantum transport simulations implemented in the DPNEGF package. We validate the method on five prototypical 2D materials (graphene, hexagonal boron nitride (h-BN), [Formula: see text], [Formula: see text], and black phosphorus) demonstrating excellent agreement with conventional DFT-NEGF for band structures and transmission spectra. Beyond single-material benchmarks, we showcase the framework's versatility by exploring strain engineering (uniaxial strain on graphene and biaxial strain on [Formula: see text]), substitution doping in [Formula: see text], and current-voltage characteristics of a graphene field-effect transistor (FET). A scaling analysis reveals that DeePTB-NEGF can simulate systems with hundreds of atoms in minutes, achieving speed-ups of over [Formula: see text] compared to DFT-NEGF for heterostructures such as graphene/h-BN/graphene. These results establish DeePTB-NEGF as a powerful tool for autonomous, high-throughput design of quantum transport in microscopic heterostructures, enabling rapid prototyping of next-generation 2D devices.
Programmed cell death ligand 1(PD-L1) association in metastatic and non-metastatic oral squamous cell carcinoma: clinicopathologic and immunohistochemical study.
Kamel EM, Esmaeil DAM, Abdelsalam RA … +1 more , El-Sisi AA
Sci Rep · 2026 Jul · PMID 42401619 · Full text
Oral Squamous Cell Carcinoma (OSCC) is considered a highly immunosuppressive malignancy largely mediated by the Programmed Cell Death 1/Programmed Cell Death Ligand 1(PD-1/PD-L1) axis. The interaction between PD-L1 expre...
Oral Squamous Cell Carcinoma (OSCC) is considered a highly immunosuppressive malignancy largely mediated by the Programmed Cell Death 1/Programmed Cell Death Ligand 1(PD-1/PD-L1) axis. The interaction between PD-L1 expressed on tumor cells and PD-1 receptors on T-cells results in T-cell dysfunction, exhaustion, and immune evasion within the tumor microenvironment. This study aimed to evaluate PD-L1 expression in primary non-metastatic OSCC, primary metastatic OSCC, and nodal metastatic OSCC, as well as to investigate its association with different available clinicopathological parameters. Immunohistochemical staining was performed to retrospectively evaluate PD-L1 expression in 30 archival paraffin-embedded OSCC specimens retrieved from the Department of Oral Pathology, Faculty of Dentistry, and the Oncology Center, Faculty of Medicine, Mansoura University. PD-L1 immunoreactivity was evaluated using a semi-quantitative scoring system based on both the staining intensity and the percentage of positively stained cells. The percentage of immunopositive cells was scored as stated: 0 (0%); 1 (< 25%); 2 (25-50%); 3 (50-75%); and 4 (> 75%). Staining intensity was graded as follows: (0 = negative); (1 = weak); (2 = moderate); and (3 = strong). A combined immunoreactivity score was calculated by adding the percentage and the intensity for each case (range 0-7). The final score was categorized as follows: 0 (negative); 1-3 (weak); 4-7 (strong). Statistical analysis was conducted to determine significant differences and correlations between PD-L1 expression and clinicopathological parameters using the Chi-square test, Monte Carlo test, one-way ANOVA, Student's t-test, and Fisher's exact test. The p-value < 0.05 was considered statistically significant. PD-L1 immunopositivity was detected in all OSCC cases (100%). A statistically significant difference was observed among the different studied groups (p < 0.001), with the strongest PD-L1 expression detected in both primary metastatic and nodal metastatic OSCC. Strong PD-L1 expression showed a significant association with patient age (p = 0.024). Additionally, a significant correlation was identified between PD-L1 expression and the depth of tumor invasion (p < 0.001). PD-L1 expression may have a potential role in tumor progression of OSCC.
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