Browse Articles

Sodium hexachloroplatinate (IV) induces concentration- and time-dependent depolarization and cytotoxicity in HEI-OC1 auditory cells

Over the past decades, cochlear implants (CIs) have been widely acknowledged for their efficacy and reliability in restoring auditory function in patients with severe to profound sensorineural hearing loss. Nonetheless, electrode corrosion involving platinum (Pt) components in CI systems can lead to increased electrode impedance and the release of Pt corrosion products, which possibly have toxic effects on cochlear sensorineural structures. Despite advances in CI technology, the biological responses, mediating cell damage, induced by platinum corrosion products following cochlear implantation remain incompletely characterized. To address this gap, we employed the H ouse E ar I nstitute– O rgan of C orti 1 (HEI-OC1) cell line as an in vitro auditory model to characterize the cytotoxic effects of sodium hexachloroplatinate (IV) (Na 2 [PtCl 6 ]) through electrophysiological analyses and relative quantification of mitochondrial oxidative activity. Using whole-cell patch-clamp recordings in current-clamp mode, we observed that Na 2 [PtCl 6 ] caused a significant, concentration- and time-dependent depolarization of resting membrane potentials, potentially facilitating activation of voltage-gated ion channels and disrupting ionic homeostasis. Consistent with the intracellular accumulation of Pt and the electrophysiological findings, significant concentration-dependent changes in oxidative activity were observed in HEI-OC1 cells following Na 2 [PtCl 6 ] exposure. No time-dependent differences in metabolic activity were detected after 24 h and 48 h of exposure, suggesting that cellular repair mechanisms may be activated in parallel during cultivation. Overall, these findings suggest that this Pt(IV) compound directly alters auditory cell electrophysiology, thereby promoting cytotoxicity. Understanding these mechanisms will improve the development of better implant materials, optimized stimulation pulse protocols, and protective therapies to enhance CI longevity and safety.

Energy-efficient CNN acceleration using approximate multipliers with error-aware weight precomputation

Enhancing the long-term abstinence rate of smoking through telemedicine: A multicenter, retrospective cohort study in Japan

The aim of this study is to analyze the differences between telemedicine and face-to-face examinations for smoking cessation in terms of long-term abstinence and completion rates in a large Japanese population. Although the effectiveness of various smoking cessation methods has been confirmed, the treatment outcomes of face-to-face interviews for tobacco cessation are still insufficient, because it is bother to go to a clinic regularly for most patients. In line with current trends of developing digital healthcare services, we assessed the role of telemedicine as a potential tool in smoking cessation clinics. A total of 5005 current smokers who applied for the telemedicine smoking cessation program between April 2021 and December 2022 and a total of 1308 current smokers who visited some smoking cessation clinics between April 2016 and March 2017 were included. Clinical data, such as age, sex, Brinkman index, were collected from all the participants, in addition to a preliminary questionnaire including smoking habits, reason for applying and self-efficacy for smoking cessation. This online program consists of four sessions in the first 8 weeks, with a 1-year follow-up period (final follow-up at 52 weeks). The success rates of long-term smoking abstinence at week 52 and the completion rates of scheduled treatment with varenicline or nicotine patches were compared between the telemedicine and face-to-face examinations. Data on face-to-face examinations were obtained from the database of the Ministry of Health, Labor and Welfare in Japan for comparison. A total of 3708 patients (3364 men and 352 women) were analyzed. The completion rate of this program (68.2%) was significantly greater than that of face-to-face examinations (29.8%). The long-term abstinence rate was significantly greater with telemedicine than with conventional examination (P < 0.005). In conclusion, the findings revealed that telemedicine is helpful for long-term abstinence from smoking on the basis of improved availability and accessibility.

Retraction Note: Study on novel neutron irradiation without beam shaping assembly in Boron Neutron Capture Therapy

Spatiotemporally Asynchronous Dual-Modality Probe: Real-Time and Accurate Monitoring of Neutrophil Recruitment in Phototherapy Prognosis

Binary image acquisition and texture parameter calculation of asphalt pavement based on a U-Net model

Current methods for detecting and evaluating pavement skid resistance vary widely, yet each has its own scope of applicability and inherent limitations. Therefore, this paper proposes a method based on U-Net model segmentation to obtain binary images of asphalt pavement surfaces, enabling precise calculation of pavement texture distribution parameters. A dataset required for model training and testing was constructed, and preprocessing was performed on forward-collected asphalt pavement images to eliminate noise interference. Based on the established three-dimensional asphalt pavement model, reverse engineering is employed to obtain binary images of the pavement surface as target images for model training. A U-Net semantic segmentation model is constructed to train the segmentation of asphalt pavement images, distinguishing between the aggregate and void components of the pavement. The feature parameters of the binary images generated by U-Net segmentation are calculated and correlated with the average texture depth measured using the sand patch method. Results indicate that the U-Net model achieved an F1-score of 0.7214 on the validation set, demonstrating satisfactory segmentation performance for subsequent texture parameter extraction. The correlation coefficient R² between the mean texture depth (MTD) calculated from the binary image and the sand patch method reached 0.85, while the correlation coefficient between the fractal dimension and MTD-1 was 0.86. Both correlations were statistically significant at the 95% confidence level. The proposed method can provide effective technical support for texture-based skid resistance evaluation of asphalt pavements.

In silico insights into the adsorption and detection of dimethyltryptamine on metal doped C20 fullerene

Abstract Given the psychoactive effects of dimethyltryptamine (DMT), classified as a Schedule I drug, developing diagnostic methods is essential. In this computational study, we investigate the adsorption and sensing behavior of DMT on pristine C 20 fullerene and its beryllium (Be), magnesium (Mg), and calcium (Ca) doped derivatives using density functional theory (DFT), time-dependent DFT (TD-DFT), and quantum theory of atoms in molecules (QTAIM) to provide suitable candidates that reduce trial-and-error in subsequent experimental work. Three computational methods (B97D/lanl2dz, B97D/6-311 + G(d), and ωB97XD/lanl2dz) were employed to ensure the accuracy of qualitative results. Our results reveal that pristine C 20 and BeC 19 exhibit strong adsorption characterized by donor-acceptor interactions, electrostatic attraction, polarization/charge transfer, and dispersion forces. Electronic structure analysis indicates that BeC 19 exhibits the largest reduction in Egap upon DMT adsorption, accompanied by pronounced charge transfer and substantial modulation of conductivity. UV-Vis spectra show that C 20 and BeC 19 exhibit a significant redshift from the UV to the visible region after DMT absorption, making them candidates for further experimental evaluation as colorimetric sensors. NCI, ELF, LOL, and QTAIM analyses confirm that interactions are predominantly non-covalent, with Be doping introducing localized attractive regions that enhance sensitivity. In contrast, MgC 19 and CaC 19 show minimal electronic perturbation and weak adsorption dominated by van der Waals forces. Statistical validation using MAD, RMSD, and Pearson correlation coefficients ( R  > 0.93) confirms good qualitative agreement across all computational methods. These theoretical findings suggest pure C 20 as a potential adsorbent and BeC 19 as a dual-purpose material for adsorption and electrochemical/colorimetric detection of DMT for further experimental work in the future, and provide a theoretical basis for the development of future experimental sensors.

Detergent-like Toxicity Mechanism of Amyloid Cylindrins Revealed by Cross-Link Spin Labeling Electron Spin Resonance

Retraction: Application of IRSA-BP neural network in diagnosing diabetes

DRFAS-enhanced personalized federated learning for secure and robust cardiovascular disease detection

Intermolecular Reductive Coupling of Ketones and Alkenes under Ferrioxalate Photocatalysis

A two-step iterative framework for signal and image deblurring using G-I-Nonexpansive Mappings

This study introduces G-I- nonexpansive mapping by combining I- nonexpansive mapping with a directed graph. It also establishes convergence results for a two-step Ishikawa-type iteration. Numerical experiments were conducted on benchmark image deblurring problems, in which images were degraded by motion blur and additive Gaussian noise. The proposed method achieves competitive restoration performance, with peak signal-to-noise ratio values of up to 24.51 dB. It outperforms classical approaches such as Wiener filtering, Lucy-Richardson and the Fast Iterative Shrinkage-Thresholding Algorithm while remaining comparable to Total variation (TV)-based methods. The method reliably enhances signals in 1D, achieving a peak signal-to-noise ratio of 29.73 dB and high structural similarity index measure values. These results suggest that the framework is an effective tool for restoring signals and images degraded by blur and noise.

Experimental study on improving the performance of fluid solidified soil based on optimization of solidifying agent ratio and vibration mixing

Distinct, Phase-Dependent Orientations of GPI and GPI-Anchored Proteins in Lipid Bilayers Revealed Using Spin Labeling and Power Saturation Electron Paramagnetic Resonance Depth Profiling

Low-latency stage-adaptive cascade architecture for real time non-stationary noise filtering

In many real-time measurement and monitoring systems, the quality of acquired signals is often severely degraded by complex environmental noise sources with non-stationary properties, rendering analysis, important feature extraction, and decision-making unreliable. This study proposes a multi-stage adaptive denoising architecture based on the least mean square (LMS) algorithm, in which the number of filter stages and the step size are automatically adjusted according to error statistics, the remaining correlation between the residual and the reference signal, and the real-time signal-to-noise ratio (SNR) of the signal. The stopping mechanism is determined by a two-tailed Fisher-z correlation test, with effective sample size correction in the presence of autocorrelation and modulation based on SNR, to ensure the stability of the adaptive system against non-stationary noise. The filter is evaluated on simulated signal datasets and real-world measured data. Compared with the conventional LMS filter configuration under the tested simulated conditions, the proposed architecture reduces mean squared error (MSE) by 38–82% and mean absolute error (MAE) by 15–45%, while improving both SNR and peak signal-to-noise ratio (PSNR). The execution time of the proposed method is approximately 3.5–4 times lower than that of the fixed-threshold method under the tested settings. These results indicate that the proposed method can improve the trade-off between denoising performance and computational efficiency, showing potential for low-latency implementation on resource-constrained devices.

Genomic population structure and adaptation of eastern Mediterranean loggerhead (Caretta caretta) nesting areas

Age at first marriage among women in Lesotho: Multilevel survival analysis- insight from 2023-24 demographic and health survey data

Background Early marriage remains a significant public health and social issue in Lesotho, with profound implications for women's health, education, and economic empowerment. Despite legal frameworks aimed at curbing the practice, a substantial proportion of women continue to marry before the age of 18, driven by sociocultural norms, economic constraints, and limited access to opportunities. This study investigates the timing and factors associated with first marriage among women in Lesotho using advanced multilevel survival analysis to inform targeted interventions. Methods We analyzed retrospective time-to-event data from the nationally representative, cross-sectional 2023−24 Lesotho Demographic and Health Survey (LDHS), employing a log-logistic accelerated failure time (AFT) model within a multilevel framework to account for individual, household, and community-level factors. The analysis included 6,413 women aged 15–49, with 48.76% having experienced first marriage (events) and 51.24% right-censored. Statistical computations were performed using R statistical software (version 4.4.3), incorporating survey weights to ensure representativeness. Results The median age at first marriage was 24 years (95% CI: 24–25), with significant variation across socioeconomic and contextual factors. Employment (TR = 1.072, 95% CI: 1.043–1.103), middle wealth quintile (TR = 1.060, 95% CI: 1.012–1.110), low community poverty (TR = 1.094, 95% CI: 1.045–1.145), and urban residence (TR = 1.079, 95% CI: 1.033–1.126) were statistically associated with later age at first marriage (p < 0.05). In contrast, primary education (TR = 0.856, 95% CI: 0.749–0.979), younger birth cohorts (1979–2003: TR range 0.774–0.907), richest wealth quintile (TR = 0.927, 95% CI: 0.875–0.981), and rural residence (TR = 0.927, 95% CI: 0.888–0.967) were associated with earlier age at first marriage. The intraclass correlation coefficient (ICC = 0.0029) indicated that only 0.3% of the variation in age at first marriage was attributable to community-level differences. Although statistically significant, the magnitude of these associations is modest. Conclusions The findings show that employment, middle wealth status, low community poverty, and urban residence are associated with a later age at first marriage, while primary education, younger birth cohorts, richest wealth quintile, and rural residence are associated with earlier marriage. The minimal community-level variation suggests that individual and household-level factors are more important determinants of marriage timing. Policymakers could consider prioritizing multisectoral interventions, including expanded educational access, economic empowerment programs, and poverty reduction strategies, with particular attention to rural-urban disparities. Addressing these structural factors may be relevant to achieving sustainable development goals related to gender equality and women's empowerment in Lesotho.

Behavioral and molecular characterization of fatigue-like manifestations triggered by acute restraint stress and LPS or saline

Minority Sites on Cu Surfaces Drive C–C Coupling in the Electrochemical Reduction of CO ₂

Faster turnover of taxonomic over functional bacterial composition during vermicomposting indicates increasing functional redundancy

Microbial taxonomy underpins microbial functionality; consequently, changes in taxonomic composition are expected to influence community functional profiles. However, functional redundancy—the ability of different microorganisms to perform similar functions—can sometimes decouple taxonomic and functional variation in microbial communities. In this study, we estimated the turnover rates of bacterial taxonomic and functional composition, as well as functional redundancy, across different substrates during vermicomposting. Our results showed that, during the early stages of vermicomposting, bacterial functional composition largely mirrored taxonomic composition across substrates. However, by the final stage, samples converged toward similar functional profiles despite remaining taxonomically distinct, indicating an increase in functional redundancy over time. Consistent with this pattern, the taxonomic turnover rate was approximately twelve times higher than the functional turnover rate. Functional redundancy increased throughout the process, with values ranging from 0.27 to 0.58 (on a scale from 0 to 1). The high turnover rates observed demonstrate that vermicomposting is an accelerated decomposition system with respect to both bacterial taxonomic and functional dynamics, exhibiting turnover rates more than 200 times higher than those reported for soil ecosystems. However, because this study did not include a non-earthworm control treatment, the accelerated turnover rates cannot be attributed exclusively to earthworm activity and should instead be interpreted as the result of the combined effects of earthworms and microorganisms. Future studies should incorporate non-worm controls to disentangle the specific contribution of earthworms and to evaluate how varying earthworm densities influence microbial turnover dynamics.