Abstract: Securing electronic health records (EHRs) is critical in the modern healthcare landscape, where digital transformation enhances connectivity and data-driven decision-making. This paper introduces a secure framework that integrates voice-based authentication, blockchain technology, and machine learning to protect EHRs, particularly in IoT-enabled, high-frequency wireless communication environments. The new distributed system utilizes blockchain technology to improve the security and integrity of medical records. User verification is achieved through voice authentication, which adds a biometric element as well. A working model was designed to show the system’s feasibility along with a case study on heart health monitoring. Simulated results demonstrated better block creation time, transaction latency, and validation accuracy.

Abstract: Objectives: The aim of our study was to investigate the in vitro activity and in vivo effica-cy of rezafungin, anidulafungin, caspofungin and micafungin against Candida auris iso-lates belonging to clade V. Methods: Five clinical isolates were evaluated (IFRC2087, IFRC4050, MRL40, TMML616 and TMML617). Echinocandin MICs and killing activities were determined in RPMI-1640. In the survival and fungal tissue burden experiments (heart, kidney and brain), neutro-penic mice were infected intravenously (107 CFU/mouse). Treatment was initiated 24 hours post-infection with intraperitoneal dosing of 20 mg/kg of rezafungin on days 1, 3 and 6 or once-daily dosing for 6 days with 3 mg/kg of caspofungin, 5 mg/kg of micafungin or 5 mg/kg of anidulafungin. Results: MIC ranges of rezafungin, anidulafungin, caspofungin, and micafungin were 0.06-0.25, ≤0.03-0.12, 0.12-0.5 and ≤0.03-0.12 mg/L, respectively. The four echinocandins at ≥1 mg/L were fungicidal only against isolate MRL40. All echinocandin regimens im-proved the survival in mice infected with isolates MRL40 and IFRC4050 (P-values were ≤0.0002 and 0.0006, respectively), but only rezafungin was effective against isolate TML617 (P=0.0049). All four echinocandins induced more than 3 logs mean CFU/gram decreases in the kidneys and hearts of mice infected with the three isolates compared to control mice, some of which were not statistically significant. Fungal growth, regardless of the isolate tested, was poorly inhibited by echinocandins in the brain. Histopathology showed large aggregates of pseudohyphae in the hearts, kidneys and brains in control mice. In echinocandin treated mice only blastoconidia were found. Conclusions: In vitro activity and in vivo efficacy of the four echinocandins against the fifth clade of C. auris was echinocandin- and isolate-specific. Pseudohyphal production was common in controls, but not in echinocandin treated mice. Rezafungin activity was comparable to or better than the three previously approved echinocandins. Keywords: Candida auris, fifth clade, time-kill, neutropenic mouse model, pseudohypha production, rezafungin, echinocandins,

Abstract: This study examines the retail food environment surrounding public schools in Michigan using a multiscale, multidimensional framework. A cross-sectional spatial analysis integrates relative healthfulness (modified Retail Food Environment Index, mRFEI), availability (outlet density), and accessibility (network-based walking time) across school districts, census tracts, block groups, and school-centered buffers. The analysis includes 3,530 public schools, 7,680 fast food restaurants, and 2,065 convenience stores. Results show pronounced spatial heterogeneity and clustering of unhealthful outlets (Nearest Neighbor Index = 0.284, p < 0.001), with many located near schools. Approximately 34% of schools are within a 10-minute walk of a fast food restaurant, increasing to 65% within 20 minutes. Urban schools face significantly higher exposure—2.27–2.80 times more fast food outlets and shorter walking times than rural schools (p ≤ 0.002)—with consistent gradients across city, suburban, town, and rural contexts. Overall, school neighborhood food environments are highly structured, obesogenic, and inequitable. By integrating multiple spatial scales and dimensions, this study advances food environment research and provides policy-relevant evidence for targeted, place-based interventions to improve access to healthier food around schools.

Abstract: In this study, the effect of incorporating maltodextrin into films composed of thermoplastic starch and chitosan was evaluated with the aim of improving their physicomechanical properties. X-ray diffraction revealed greater organization in sample TPS-CH-M3 compared with TPS-CH-M0 and TPS-CH-M5, indicating a balanced semicrystalline structure. Thermal analyses showed an increase in the glass transition temperature from 63.0 °C to 72.6 °C and a shift of the main degradation step from 308 °C to 311 °C, reflecting enhanced thermal stability. The contact angle decreased from 89.5° to 74.0°, confirming increased hydrophilicity. SEM micrographs revealed a homogeneous surface in TPS-CH-M0 and controlled roughness in TPS-CH-M3. Mechanical tests recorded the highest tensile strength (12.5 MPa) and elongation at break (18%) for TPS-CH-M3. FTIR spectra showed physical interactions without new chemical bands, and colorimetric analysis indicated an increase in yellow tonality, which is suitable for packaging and coatings of light-sensitive foods.

Abstract: We construct electromagnetic Kantowski–Sachs (KS) solutions in covariant teleparallel F(T) gravity using the coframe/spin–connection (CSC) formalism. In the restricted branch considered here, the Maxwell conservation laws (CLs) impose strong restrictions on the anisotropic scale factors and lead to the scaling ρ_{em} A_3^{−4}. We derive the corresponding symmetric and antisymmetric field equations (SFEs and AFEs) and formulate a reconstruction scheme in which F(T) is determined from the KS dynamics rather than imposed a priori. Power-law (PL) and exponential (EXP) coframe ansätze generate distinct invariant reconstruction branches, including scaling cosmologies, teleparallel de Sitter (TdS) regimes, and KS black-hole-interior-like reconstruction branches. The resulting models are organized using the Coley–Landry invariant classification and analyzed through leading-order stability conditions F_T>0 and F_{TT}>0.

Abstract: The cap-binding protein eIF4E is a key protein for mRNA metabolism. The eIF4E biological role is defined by the specific protein it interacts with. The best characterized role of eIF4E is in promoting mRNA translation through its interaction with eIF4G. To seek for new interactors in the ascomycete Saccharomyces cerevisiae, we performed a genomic yeast two-hybrid screen using eIF4E as bait. In addition to the already reported p20 and Eap1, we identified Med9, a component of the RNA polymerase II Mediator complex. A physical interaction between eIF4E and Med9 was confirmed using recombinant proteins prepared in E. coli and further isolating the eIF4E―Med9 complex both by size-exclusion chromatography and by m7GTP-Sepharose pull-down experiments. Surprisingly, the eIF4E W75A mutation, which impairs the interaction with eIF4G, p20, and Eap1 only slightly affected the interaction with Med9 in the two-hybrid system. We further performed random mutagenesis to identify the Med9 amino acids involved in eIF4E interaction. Mutants F65A/I66A and F65A/I66A/H68N did not interact with eIF4E. We also demonstrated that the interaction eIF4E―Med9 depended on the carbon source for cell growth and that it might happen within the nucleus. Finally, we found that the eIF4E―Med9 interaction is conserved in the yeast Saccharomyces kudriavzevii.

Abstract: The growing prevalence of gaming disorder (GD) in adolescents is a global concern. Although parents should play a critical role in preventing GD, how parenting styles help prevent adolescent GD remains understudied. This study assessed the association of parenting styles with adolescent GD in junior high school boys in Tokyo, Japan. Data were collected in 2024 via web-based, self-administered questionnaires from 300 parents. Suspected adolescent GD was assessed using a validated parent report measure (i.e., the Gaming Disorder Scale for Parents). Parenting styles were measured using the Parenting Scale, comprising two dimensions: Overreactivity and Laxness. The mean factor scores of Overreactivity and Laxness were compared between the suspected and non-suspected GD groups by t-test. Logistic regression analysis assessed the association of Overreactivity and Laxness with suspected GD, controlling for covariates. The mean factor score of Overreactivity was significantly higher in the suspected GD than in the non-suspected group, whereas Laxness was not. Logistic regression analysis identified parental Overreactivity as an independent predictor of suspected GD (adjusted odds ratio: 1.75, 95% CI: 1.24 to 2.49). This study showed that overreactive parenting is independently and significantly associated with an increased risk of adolescent GD, suggesting the importance of psychological support for parents.

Abstract: The Omicron variant of SARS CoV-2 is associated with milder symptoms and lower hospitalization and mortality rates than Delta variants, although the impact of Omicron on immunocompromised patients, especially Solid Organ Transplant (SOT) recipients, is still unclear. This study compares the hospitalization rate and outcomes between immunocompromised, immunocompetent, and SOT patients during the Delta and Omicron periods. We included adult patients who tested positive for SARS-CoV-2 on PCR or nasopharyngeal antigen test between June 26, 2021 to September 8, 2022, at our institution. 12,401 COVID-19 patients were included, of which 11,055 were immunocompetent, and 1,346 were immuno-compromised (375 SOT recipients). Throughout the Delta and Omicron outbreaks, immunocompromised patients exhibited higher comorbidities and 30-day hospitalizations, but rates of mechanical ventilation and ICU-level care were like immunocompetent patients. During the Omicron wave, immunocompromised patients had higher unadjusted relative risk estimates (RR=2.37, 95% CI 1.96-2.87, p< 0.05) than Delta (RR=1.58, 95% CI 1.24-2.01, p< 0.05) with higher adjusted relative risk for hospitalization in Omicron (RR=1.50, 95% CI 1.10-2.03, p=0.01). Analyses show increased hospitalization risk in immunocompromised during the Omicron wave compared to the Delta wave with no significant difference in hospitalization outcomes. The relative risk of hospitalization for SOT patients was higher in both waves.

Abstract: Breast cancer remains the most frequently diagnosed malignancy among women worldwide, while metabolic dysfunction–associated steatotic liver disease (MASLD) represents the leading cause of chronic liver disease, reflecting a global burden of metabolic dysfunction. Increasing evidence suggests that MASLD is not only a common comorbidity but also a potential independent risk factor for breast cancer development and progression. This review synthesizes current epidemiological, clinical, and mechanistic data linking hepatic metabolic dysfunction to breast carcinogenesis. Population-based studies consistently demonstrate an association between hepatic steatosis and increased breast cancer incidence, particularly in postmenopausal and metabolically vulnerable populations, as well as poorer oncological outcomes. Mechanistically, MASLD promotes a systemic pro-tumorigenic environment through interconnected pathways, including insulin resistance, hormonal dysregulation with increased estrogen bioavailability, chronic inflammation, oxidative stress, lipid metabolic reprogramming, and gut–liver axis disruption. Hepatokines, particularly fibroblast growth factor 21 (FGF21), emerge as key mediators of tumor progression and potential biomarkers of metabolic vulnerability, while Fetuin-A and ANGPTL8 further support the liver’s endocrine role in oncogenic signaling. Preclinical evidence highlights fatty acid oxidation as a metabolic dependency in aggressive breast cancer subtypes, suggesting novel therapeutic targets. Despite consistent associations, causality remains unproven. Future prospective studies are needed to determine whether targeting metabolic dysfunction can improve breast cancer prevention and outcomes.

Abstract: This study evaluated reproductive performance, metabolic and hormonal fluctuations in Sarda rams raised under semi-extensive management conditions during the breeding season. Fourteen rams were isolated from ewes, subjected to nutritional flushing, and treated with melatonin implants (3X18 mg) before joining the flock. From June to December, body condition score (BCS), NEFA, urea, triglycerides, cholesterol, testosterone, fecal thyroid hormone metabolites (FTMs), and fecal corticosteroid metabolites (FCMs) were measured every 45 days. Ewes’ pregnancy rates (PR) and conception dates were determined by reproductive ultrasound scanning to estimate rams' reproductive performance. BCS declined (p&lt;0.05) from June (3.11 ± 0.06) to November (2.80 ± 0.06). In November, NEFA, cholesterol and FCMs concentrations peaked (p&lt;0.05), whereas triglycerides and urea reached the lowest levels (p&lt;0.05). FTMs peaked in November and June (p&lt;0.05). Testosterone concentrations were three-fold higher in June than the rest of BS (p&lt;0.05), while overall PR was stable during the BS. Despite metabolic and endocrine changes, rams maintained reproductive efficiency, indicating an interaction between metabolic status, stress response, and reproduction, and supporting the need for targeted management strategies to sustain welfare and long-term performance.

Abstract: This paper presents an explainable defense framework against perception-layer and Man-in-the-Middle (MitM) attacks in Internet of Things (IoT)-based environmental hazard warning systems. These systems rely on heterogeneous sensors (gas, light, sound, temperature, and humidity) whose integrity is crucial for reliable environmental alerts. Perception-layer attacks such as spoofing, jamming, and data injection can compromise sensor readings, while MitM attacks threaten communication reliability. The proposed approach integrates Dynamic Time Warping (DTW) for time-series anomaly detection with Shapley Additive Explanations (SHAP) for interpretability. A comparative evaluation framework jointly considers detection performance and explanation quality through metrics including pre-registering a Casual Ground Truth based on network protocol specifications and measuring the Sperman’s rank correlation of SHAP outputs, which eliminates the need for manual expert evaluation. Experimental simulations using an authentic EdgeIIoT-2022 dataset demonstrate high detection accuracy and moderated explainability scores. The results prove the framework’s ability to detect and explain adversarial behaviors in sensor networks, strengthening trust, transparency, and resilience in safety-critical IoT infrastructures.

Abstract: We show that a single Hodgkin–Huxley (HH) neuron with Pyragas-type delayed feedback control (DFC) can store multiple symbols as stable periodic orbits, where the specific orbit is selected by tuning the DFC gain K and time delay τ. Sweeping the (K,τ) parameter plane at fixed bias current Ibias=10.0μA/cm2 reveals 207 orbit types across 12 topological categories, with inter-spike interval (ISI) means from 5.9 to 56.9 ms. We establish: (i) a write protocol that reliably locks orbits with 13.9 ms median settling time; (ii) a novel Pattern-Oriented Limit-cycle Decoder (POLD) that reads orbits at 100% accuracy from only 5 observed ISIs; (iii) a full write–read–erase (W–R–E) cycle with 100% read accuracy, 92% erase verification, and no decay over hold durations up to 50 s; and (iv) a fully validated 12-symbol memory capacity, with a read-discriminable upper bound of 67 symbols (11.2× over rate coding) pending write-viability confirmation for the extended set. Reliable orbit addressing needs delay precision of ±2%, which constitutes a write-precision specification and not a fundamental capacity limit. These findings show that parametric delayed feedback is a viable mechanism for limit-cycle-based information storage in conductance-based spiking neurons. The biological interpretation is analogical, not direct: the ±2% delay-precision requirement exceeds what has been demonstrated for biological autaptic variability, and the orbit-coded memory framing is best understood as a computational proof-of-principle aimed at neuromorphic engineering, not as a claim about biological working memory.

Abstract: A series of critical interactions within the viral core between the viral RNA (vRNA) and HIV-1 Integrase (IN) has previously been reported. In these studies, contact points between vRNA and IN were identified using RNA-seq and MS-based protein foot-printing approaches. Several IN amino acids located in its C-terminal domain (CTD) were found to be essential for vRNA binding and their alanine substitution severely impacted the correct morphogenesis of the matured viral core. Here, we have extended these studies by performing a comprehensive mapping of the IN-vRNA interaction by deploying RNA crosslinking and NMR methodologies. Together, these approaches were able to identify additional contacts points between the vRNA and IN. Our results reveal several new basic amino acids located in the IN CTD critical for the vRNA-IN interaction, viral replication and correct morphology of the matured viral core.

Abstract: Oleanolic acid (OA) is a pentacyclic triterpenoid with broad biological activity, but its primary molecular points of engagement remain incompletely resolved. Most available studies describe OA through selected pathway markers, particularly within PI3K/AKT/mTOR, AMPK/mTOR, MAPK, NF-κB, and Nrf2 signaling, without clearly distinguishing direct target engagement from downstream adaptive responses. This limits mechanistic interpretation and weakens translational prioritization. This review examines how phosphoproteomics and integrated multi-omics can support OA target deconvolution. We discuss why phosphoproteomics is particularly informative for capturing early signaling events, how it can be combined with proteomics, tran-scriptomics, metabolomics, and chemoproteomic approaches, and why orthogonal tar-get-engagement methods remain essential for stronger causal inference. We also organize the current signaling evidence for OA and its derivatives, highlighting the strongest support for AMPK/mTOR-linked regulation of autophagy and apoptosis while identi-fying major gaps in systems-level validation across other reported pathways. Finally, we propose a stepwise workflow for OA target deconvolution based on time-resolved phosphoproteomics, analysis of informative phosphosite subsets, mul-ti-omics integration, kinase/phosphatase activity inference, and experimental target validation. This framework may help move OA research from descriptive pathway pharmacology toward mechanism-based target prioritization and more rational deriva-tive development.

Abstract: Objective: To describe a rare case of subglottic foreign body (FB) impaction in an adult, leading to subglottic stenosis, and to evaluate the effectiveness of Suspension Microlaryn-goscopy (SML) as a minimally invasive technique for its management. Methods: A single case of subglottic FB in an adult was managed using endotracheal intubation and SML. This approach allowed for precise visualization and extraction of the FB. When granula-tion tissue or mucosal overgrowth was encountered, targeted resection and controlled cauterization were performed. Results: The SML technique provided excellent exposure to the subglottic region, enabling safe removal of the FB while minimizing trauma to the surrounding tissues. Postoperative follow-up demonstrated successful resolution of sub-glottic stenosis without complications, confirming the efficacy and safety of this approach. Conclusions: Subglottic FB impaction is an exceptionally rare occurrence in adults, posing diagnostic and therapeutic challenges. SML is a valuable tool for managing such cases, offering precise visualization, safe FB extraction, and effective management of complica-tions such as granulation tissue, ensuring optimal patient outcomes.

Abstract: Binary Waring decomposition seeks to express a homogeneous binary form as a minimal sum of powers of linear forms. In the binary setting, Sylvester’s theorem gives a classical algebraic route for rank determination and parameter recovery through structured Hankel/catalecticant matrices. Although this procedure is exact and interpretable in ideal arithmetic, practical rank identification may become unstable when the input coefficients are contaminated by noise or when the underlying roots are close to degenerate configurations. This paper develops a data-driven rank inference framework coupled with certified Sylvester reconstruction for robust binary Waring decomposition. The proposed method first converts the coefficient sequence into a Hankel-aware graph that captures recurrence-induced dependencies among polynomial coefficients. A graph neural network is then used to infer plausible rank candidates from this structured representation. Instead of accepting a single prediction directly, the framework performs explicit Sylvester reconstruction and algebraic residual verification for candidate ranks. To further improve decision reliability, a lightweight meta-verification module integrates reconstruction residuals, model confidence scores, and stability-related indicators to select the most credible rank. Experiments on large-scale synthetic binary forms demonstrate that the proposed approach improves rank identification accuracy and verified reconstruction success under low-to-moderate noise, while maintaining the transparency and auditability of classical symbolic–numeric computation. These results suggest that data-driven rank inference can serve as an effective front-end for algebraically certified reconstruction, especially in numerically ambiguous regimes where fixed threshold-based Sylvester implementations are fragile.

Abstract: The high energy consumption of conventional mixers equipped with active mixing elements necessitates the development of more efficient technologies for mixing bulk materials and feed mixtures. This study proposes a gravity-based mixing method based on the rotation of an inclined cylindrical chamber without the use of active mixing elements. During rotation, the mixture components move toward both end walls of the chamber and simultaneously perform circular motion along the inner cylindrical surface, which intensifies the mixing process and reduces energy consumption. A structural and technological design of the gravity mixer was developed, and an experimental prototype was manufactured. Analytical relationships were obtained to determine the critical rotational speed of the chamber, particle movement velocity, and the power required for the mixing process. Laboratory experiments showed that the average particle movement velocity was 1.21 m/s and the average friction coefficient was 0.40. Under optimal operating conditions, the mixture uniformity reached 95.7% after 4 min of mixing. The mixer productivity was 0.95 t/h, while the specific energy consumption was 0.5 kWh/t, which is 2.5 times lower than that of conventional mixers equipped with active mixing elements. The obtained results confirm the potential of the proposed gravity-based mixing method for preparing feed and organomineral mixtures in small-scale farming systems.

Abstract: Background Short-term exposure to PM2.5 has been associated with respiratory infections, yet evidence on the health effects of its chemical components remains limited. Moreover, as PM2.5 components coexist as complex mixtures, it is unclear whether differences in compositional profiles contribute additional influenza-like illness (ILI) risk beyond the independent effects of individual components. Methods We analyzed weekly ILI surveillance data from 111 sentinel hospitals in 17 cities of Hubei, China (2021-2024), together with weekly PM2.5 concentrations and chemical components (sulfate, nitrate, ammonium, organic matter, and black carbon) from the TAP dataset and meteorological variables from ERA5-Land. To evaluate the associations of individual PM2.5 components and overall compositional profiles with ILI, we applied K-means clustering to identify distinct PM2.5 profiles and fitted city-specific quasi-Poisson models, which were then pooled using DerSimonian-Laird method. Results Among 2,804,416 ILI cases, PM2.5 mass was positively associated with weekly ILI, with a pooled RR of 1.041 (95% CI: 1.028-1.054) per 10 µg/m3 increase. Positive associations were also observed for sulfate, nitrate, ammonium, OM, and BC. Three compositional profiles were identified (SID: secondary inorganic-dominated, MOD: mixed organic-dominated; ORM: Other-rich mixed). After adjustment for PM2.5 and its component concentrations, exposure to ORM was associated with an extra 19.6% higher ILI risk than SID (RR = 1.196, 95% CI: 1.096-1.305), while exposure to the MOD was associated with an 8.9% higher ILI risk (RR = 1.089, 95% CI: 1.008-1.176). Conclusions These findings suggest that PM2.5 related ILI risk may depends not only on overall mass concentration and individual components, but also on compositional profiles. Incorporating PM2.5 mixture heterogeneity may improve assessment of air pollution related respiratory health risks.

Abstract: Modular decision systems expose multiple operating points, but downstream utility can vary by regime. Portfolio construction is a useful setting because routing, aggregation, and allocation can help or hurt depending on market structure. We instantiate a hierarchy with three operating points: direct optimizer, routed consensus, and alpha-augmented optimizer. Across universes, these modes are not uniformly ranked. Routing helps when dispersion/decorrelation is high; direct optimization is safer in low-signal settings; alpha augmentation helps in concentrated signal-rich settings. We identify the market characteristics (cross-sectional dispersion, concentration, forecast signal density) that predict which mode dominates. A rolling adaptive meta-policy that selects among operating points based on recent performance achieves competitive or superior risk-return profiles without foreknowledge of the optimal mode. We validate against classical baselines demonstrate that the operating-point structure persists across time frequencies from 15-minute bars to daily rebalancing, and confirm robustness under realistic transaction costs (0--15 bps). More broadly, our results suggest for hierarchical decision systems: the key is not to find one universally best configuration, but to characterize when each operating mode is most effective. To support future research and ensure reproducibility, we make source code publicly available at https://github.com/kouzhizhuo/Regime-Adaptive-Portfolio-Agents.

Abstract: The effect of atom size on the shock wave structure in a binary monatomic gas mix with Rydberg atoms has been investigated. The problem was solved numerically using the system of hydrodynamic equations in Argon gas, for the atom size ratios between 2 and 100, T = 1500 K, and the density between 10¹⁷ and 10²⁰ m^-3. It was found that the presence of larger size atoms in the mix results in the shock front splitting that is on the order of mean free path for this component. The results can be of interest in supersonic plasma dynamics and in astrophysics studying shock waves in the environments where high-n Rydberg states are present.