Advancing Open Science

Diabetes is known to affect metabolic, vascular, and nervous systems, although its influence on auditory function in children remains poorly defined. Understanding this association is essential due to its implications for cognitive, language, and social development. Numerous studies have found that children with Type 1 Diabetes Mellitus (T1DM) exhibit higher hearing thresholds at high frequencies (4000–8000 Hz) and lower speech understanding scores compared to healthy controls. Poor glycemic control and longer disease duration are consistently associated with worse auditory outcomes. The proposed mechanisms include microangiopathy and diabetic neuropathy affecting the auditory pathway. Many affected children do not report noticeable auditory symptoms, indicating a risk of underdiagnosis. Early identification is crucial, as hearing difficulties in children may be related to underlying diabetic conditions and are likely associated with poor glycemic control. Regular audiometric screening should be incorporated into the routine care of pediatric diabetes patients to identify hearing deficits before they affect communication and cognitive development.

Physical activity (PA) and quality sleep are essential for cognitive health, providing synergistic protection against age-related cognitive decline. However, the shared molecular pathways that explain their combined and interactive benefits remain poorly understood. This review suggests that lactate, long dismissed as a metabolic waste product, is a unifying mechanism. We introduce the “Lactate Nexus”, a conceptual framework that proposes lactate functions as a key signalling molecule, mechanistically linking the pro-cognitive effects of both daytime exercise and nighttime sleep. We begin by outlining lactate’s evolving role—from an energy substrate shuttled from astrocytes to neurons (the Astrocyte–Neuron Lactate Shuttle) to a pleiotropic signal. As a signal, lactate influences neuroplasticity via NMDA receptors, neuroinflammation via the HCAR1 receptor, and gene expression through the epigenetic modification of histone lactylation. We then compile evidence demonstrating how PA provides a substantial lactate signal that activates these pathways and primes the brain’s metabolic infrastructure. Crucially, we integrate this with proof that lactate levels naturally increase during slow-wave sleep to support memory consolidation and glymphatic clearance. The “Lactate Nexus” framework offers a comprehensive molecular explanation for the synergy between PA and sleep, positioning lactate as a key signalling mediator and a promising biomarker and therapeutic target for fostering lifelong cognitive resilience.

In the domain of marine remote sensing, the real-time monitoring of ocean waves is a research hotspot, which employs acquired X-band radar images to retrieve wave information. To enhance the accuracy of the classical spectrum method using the extracted signal-to-noise ratio (SNR) from an image sequence, data from the preferred analysis area around the upwind is required. Additionally, the accuracy requires further improvement in cases of low wind speed and swell. For shore-based radar, access to the preferred analysis area cannot be guaranteed in practice, which limits the measurement accuracy of the spectrum method. In this paper, a method using extracted SNRs and an optimized genetic algorithm back-propagation (GABP) neural network model is proposed to enhance the inversion accuracy of significant wave height. The extracted SNRs from multiple selected analysis regions, included angles, and wind speed are employed to construct a feature vector as the input parameter of the GABP neural network. Considering the not-completely linear relationship of wave height to the SNR derived from radar images, the GABP network model is used to fit the relationship. Compared with the classical SNR-based method, the correlation coefficient using the GABP neural network is improved by 0.14, and the root mean square error is reduced by 0.20 m.

Elderspeak is a form of communication overaccommodation directed toward older adults, characterized by simplified language and an elevated pitch. While typically well-intentioned, it is rooted in ageist stereotypes and linked to negative health outcomes. A literature search was conducted in PubMed, CINAHL, and PsycINFO (2018–2025), yielding 24 key articles focusing on acute and surgical settings. The purpose of this narrative review is to synthesize current evidence on Elderspeak within acute care hospitals and propose a research framework and intervention strategies. Elderspeak is a key determinant of resistiveness to care (RTC), particularly in acute settings where it is triggered by functional impairment. Exposure increases patient distress and negatively impacts vital signs and cooperation with medical interventions. Inconsistent measurement is being addressed through standardized schemes like the Iowa Coding Scheme for Elderspeak (ICodE). This paper proposes that future research must employ mixed-methods, longitudinal designs to capture the impact of Elderspeak on long-term outcomes. Drawing on the ICodE, we propose a qualitative self-reflection tool for clinicians to enhance awareness in high-stakes acute settings. Eliminating Elderspeak is a foundational necessity for patient safety and dignity-affirming care in advanced nursing.

Lithium thermal batteries are primary reserve batteries utilizing solid molten salt electrolytes. They are regarded as ideal power sources for high-reliability applications due to their high power density, rapid activation, long shelf life, wide operating temperature range, and excellent environmental adaptability. However, existing electrode systems are limited by insufficient conductivity and the use of high-impedance MgO binders. This results in sluggish electrode reaction kinetics and incomplete material conversion during high-temperature discharge, causing actual discharge capacities to fall far below theoretical values. To address this, FeS₂-CoS₂ multi-component composite cathode materials were synthesized via a high-temperature solid-phase method. Furthermore, two distinct MgO binders were systematically investigated: flake-like MgO (MgO-F) with a sheet-stacking structure and spherical MgO (MgO-S) with a low-tortuosity granular structure. Results indicate that while MgO-F offers superior electrolyte retention via physical confinement, its high tortuosity limits ionic conduction. In contrast, MgO-S facilitates the construction of a wettability-enhanced continuous ionic network, which effectively reduces interfacial impedance and enhances system conductivity. This regulation promoted Li⁺ migration and accelerated interfacial reaction kinetics. This study provides a feasible pathway for improving the electrochemical performance of lithium thermal batteries through morphology-oriented MgO binder regulation.

Agricultural production residues are an easily accessible raw material for energy recovery in a circular economy. Therefore, the possibility of biogas production from herb processing waste, namely common thyme (Thymus vulgaris L.), peppermint (Mentha × piperita L.), curled mint (Mentha crispa L.), and currants (woody stems and leaves), was investigated. In this study, the evaluation of the natural biodegradability of plant waste under conditions typical for an agricultural biogas plant was consciously carried out without the application of pre-treatment processes (shredding, steam hydrolysis, chemical treatment) to facilitate the methane fermentation process. The average values of biogas production efficiency ranged from 75 to 320 m³/mg DM for herb species and from 152 to 209 m³/mg DM for currant varieties under normal conditions. As part of laboratory tests, the elemental composition, i.e., C, H, N, S, O, was determined. Moreover, the analysis showed the energy potential of the tested waste in thermochemical processes (combustion). Garden thyme residues have particularly high energy potential, as indicated by the high calorific value, low nitrogen and sulfur content, and low ash content.

Growing evidence suggests that persistent oral infectious diseases (OIDs) contribute to systemic disease, highlighting the importance of understanding their pathogenic mechanisms. Conventional dental treatments, primarily mechanical debridement, surgical intervention, or antimicrobial therapy, often struggle to fully control inflammation or prevent progressive tissue destruction. The nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain-containing 3 (NLRP3) inflammasome is a key regulator of innate immunity, mediating the maturation of proinflammatory cytokines (IL-1β and IL-18) and the pyroptosis-inducing protein gasdermin D. Dysregulated or excessive activation of NLRP3 contributes to the initiation and progression of major oral diseases, including periodontitis, peri-implantitis, pulpitis, and oral mucosal inflammation. Despite growing interest in NLRP3, comprehensive and up-to-date reviews integrating its pathogenic mechanisms and therapeutic potential remain limited. This review summarizes current and past evidence on the role of the NLRP3 inflammasome in oral disease development, highlights emerging pharmacological strategies, and outlines future research directions. Existing studies demonstrate that microbial components and danger signals from injured tissues activate NLRP3, thereby amplifying inflammation, tissue degradation, and bone resorption. Preclinical studies indicate that inflammasome inhibitors and several natural compounds reduce tissue damage; however, their clinical translation remains limited. These findings emphasize the need for deeper understanding of NLRP3-mediated pathways, with translational and clinical research offering promising therapeutic opportunities for oral diseases.

The objective of this study was to compare the proportion of explained genetic variance (EXGV) and the reliability of genomic breeding values (GBVs) predictions for milk yield (MY), fat yield (FY), protein yield (PY) fat percentage (FP), protein percentage (PP), and somatic cell score (SCS) in Holstein cattle. Three types of genomic information were evaluated. (a) SNP-ALL: this analysis included 88,911 single nucleotide polymorphisms (SNP) from 8290 animals. (b) HAP-PSEUDOSNP: haplotypes, defined based on high linkage disequilibrium (LD, r² ≥ 0.80) between SNPs, which were encoded as pseudo-SNPs, with a total of 35,552 pseudo-SNPs and 8331 animals included. (c) SNP-HAP: analysis using only individual SNPs included in the haplotypes (without recoding); for this analysis, 33,010 SNPs and 8192 individuals were retained. All analyses were conducted using the single-step genome-wide association study method implemented in the BLUPF90 software package. The results showed that the inclusion of SNPs with high LD (SNP-HAP) increases the reliability of GBVs’ predictions compared to the SNP-ALL analysis; average reliability increased between 0.05 and 0.11. Moreover, the SNP-HAP analysis resulted in a twofold increase in the EXGV for all traits, likely due to increased estimates of individual marker effects compared to the SNP-ALL analysis.