Search Results (26,387)

Background/Objectives: The development of small-molecule agents that selectively target DNA replication remains a central strategy in anticancer drug discovery. In this study, we report the biological characterization of a novel 6-nitro-benzodioxin-naphthalimide (NI) derivative (compound 5a), evaluated as a potential DNA-targeted anticancer lead. Methods/Results: The antiproliferative activity of 5a was assessed in a small panel of human lung carcinoma cell models (A549, H1299) and a non-malignant control (MRC-5), revealing pronounced cytotoxic effects in tumor cells, accompanied by favorable selectivity indices. Mechanistic investigations demonstrated that treatment with 5a results in strong inhibition of DNA synthesis, as evidenced by a marked reduction in EdU incorporation and a robust induction of the DNA damage marker γH2AX. These effects were associated with cell-cycle perturbations characterized by accumulation in G₁ and G₂/M phases, followed by activation of apoptotic pathways. Importantly, clonogenic survival assays confirmed that even transient exposure to 5a leads to a sustained loss of proliferative capacity, indicating irreversible long-term cellular damage. These results support a replication stress-driven mechanism of action for compound 5a, consistent with interference in DNA-associated processes during S phase. Conclusions: While the precise molecular initiating event remains to be elucidated, the observed biological profile positions 5a as a promising DNA-targeted lead structure with potential for further pharmaceutical optimization. These findings provide a solid foundation for the continued development of naphthalimide-based compounds as anticancer agents within a pharmaceutically relevant framework. Full article

Background: Breast cancer survivors often experience long-term endocrine- and chemotherapy-related side effects, including sleep disorders, anxiety, and depression. Sleep disorders are particularly prevalent and affect patient adherence and quality of life. This study examined the prevalence and risk factors for sleep disorders in patients with breast cancer based on treatment exposure. Methods: Patients with breast cancer (2009–2015) were identified from the Health Insurance Review and Assessment database. They were categorized by chemotherapy exposure and further by endocrine or taxane use. Sleep disorders, anxiety, and depression were assessed using diagnostic and prescription codes. Propensity score matching and Cox proportional hazard models were applied to adjust confounders and evaluate risk factors. Results: Among the 62,714 patients, those receiving endocrine therapy had a higher risk of sleep disorders (hazard ratio [HR], 1.276; 95% confidence interval [CI], 1.087–1.497; p = 0.003), irrespective of tamoxifen or aromatase inhibitor use. In chemotherapy-treated patients, taxane exposure significantly increased sleep disorder risk (HR, 1.268; 95% CI, 1.159–1.389; p < 0.001). The cumulative incidence of sleep disorders peaked within two years post treatment and remained elevated over time. Anxiety and depression rates did not differ significantly between the treatment groups. Conclusions: Endocrine therapy and taxane chemotherapy are independent risk factors for sleep disorders in patients with breast cancer. Screening and interventions are essential for improving long-term well-being. Future studies should explore personalized approaches for managing treatment-related sleep disturbance. Full article

In recent decades, the burden of TB has been gradually declining; however, with the emergence of COVID-19 and ongoing political conflicts, including the war in Ukraine, the proper functioning of healthcare services and TB control programs has been jeopardized. Recently, research has emphasized the importance of hematological parameters associated with inflammation, which can be easily analyzed through routine blood tests. Combining these parameters may have predictive value for various diseases, including pulmonary tuberculosis and even help monitor the effectiveness of treatment. Since there is no single hematological or inflammatory biomarker that provides precise and dynamic information about the success or failure of treatment, identifying individual markers or sets of biomarkers with higher sensitivity and specificity is essential. This is particularly important since sputum culture conversion at two months remains insufficiently sensitive and microscopy conversion has limited sensitivity and specificity in detecting treatment failure. Also, the analysis of the impact of the standard directly observed treatment, short-course regimen on pathogenic mechanisms also focuses on how it influences the interaction between inflammation and oxidative tissue degradation, by measuring plasma levels of glutathione. Utilizing a combination of hematological, inflammatory, and antioxidant biomarkers offers significant insights into systemic inflammatory responses in pulmonary tuberculosis patients, both before commencing treatment and during the entire duration of antituberculosis therapy. Combining different inflammatory parameters into a multiple biomarker can significantly enhance the accuracy of predicting prognosis and response to antibiotic chemotherapy. Identifying an optimal combination of biomarkers with predictive value is crucial for assessing treatment response and evaluating the effectiveness of anti-TB medication. Rather than developing or testing a composite prediction model, this review summarizes reported performance metrics from individual studies and highlights priorities for future prospective validation of integrated biomarker panels. Full article

Citrus reticulata Blanco peel is a dominant industrial waste that was recently revalued as a source of bioactive molecules. This study explored its phytochemical and antileukemic potentials. The bioassay-guided fractionation of the dichloromethane extract yielded nobiletin, scoparone, and tangeretin, which were identified spectroscopically. The extract, fractions, and compounds showed antiproliferative effects in both THP-1 and U937 cells, which were employed as in vitro models of acute myeloid leukemia (AML). According to cytofluorimetric analysis, the extract and fractions inhibited cell growth by both apoptosis and necrosis, whereas the single molecules induced apoptosis. This mechanism was mediated by the modulation of BAX and BCL-2 genes in both AML cell lines. Notably, each treatment drove THP-1 and U937 cells into the sub-G0 phase, together with an increase in the cell population in the G1 phase of the cell cycle, both of which were detected cytofluorimetrically. In line with these findings, the extract, fractions, and single molecules counteracted the overexpression of CYCLIN A1 in THP-1 cells while reducing the expression of CYCLIN D2 in U937 cells. Moreover, cell treatments attenuated the invasiveness of AML cells through the upregulation of TIMP-2 at the transcriptional level. Therefore, this study supports pharmaceutical interest in citrus waste for cancer management, providing evidence on its antileukemic potential in vitro. Full article

This study presents a sustainable valorization strategy for wastewater treatment plant (WWTP) residual sands through their hydrothermal conversion into a dual-phase FAU/LTA zeolite and evaluates its adsorption performance toward methylene blue (MB) as a model cationic contaminant. The synthesized material (ZEO-RS) exhibited a low Si/Al ratio (~1.7), well-developed FAU supercages with minor LTA domains, and high structural integrity, as confirmed by XRD, FTIR, XRF, SEM and PZC analyses. ZEO-RS demonstrated rapid adsorption kinetics, reaching approximately 92% of equilibrium uptake within 30 min and following a pseudo-second-order kinetic model (k₂= 2.73 g·mg⁻¹·h⁻¹). Equilibrium data were best described by the Langmuir isotherm, yielding a maximum adsorption capacity of 34.2 mg·g⁻¹ at 20 °C, with favorable separation factors (0 < r_L < 1), while Freundlich fitting indicated moderate surface heterogeneity. Thermodynamic analysis revealed that MB adsorption is spontaneous (ΔG° = −11.98 to −12.56 kJ·mol⁻¹), mildly endothermic (ΔH° = +5.26 kJ·mol⁻¹), and entropy-driven (ΔS° = +0.059 kJ·mol⁻¹·K⁻¹). FTIR evidence, combined with pH-dependent behavior, indicates that adsorption proceeds via synergistic electrostatic attraction, pore confinement within FAU domains, and partial ion-exchange interactions. Desorption efficiencies conducted under mild acidic, neutral, and alkaline conditions resulted in low MB release (1–8%), indicating strong dye retention and high framework stability. Overall, the results demonstrate that WWTP residual sands are an effective and scalable low-cost precursor for producing zeolitic adsorbents, supporting their potential application in sustainable water purification and circular-economy-based wastewater treatment strategies. Full article

The radiosensitivity of cancer patients determines the efficacy of radiotherapy, and patients with low radiosensitivity cannot benefit from radiotherapy. Therefore, accurately predicting radiosensitivity before treatment is essential for personalized and precise radiotherapy. However, most existing studies rely solely on genomic and clinical features, neglecting the tumor microenvironmental information embedded in histopathological images, which limits prediction accuracy. To address this issue, we propose Resfusion, a deep multimodal fusion framework that integrates patient-level gene expression profiles, clinical records, and histopathological images for tumor radiosensitivity prediction. Specifically, the pre-trained large-scale pathology model is used as an image encoder to extract global representations from whole-slide pathological image. Radiosensitivity-related genes are selected using an autoencoder combined with univariate Cox regression, while clinically relevant variables are manually curated. The three modalities are first concatenated and then refined through a self-attention-based module, which captures inter-feature dependencies within the fused representation and highlights complementary information across modalities. The model was evaluated using five-fold cross-validation on two common tumor datasets suitable for radiotherapy: the Breast Invasive Carcinoma (BRCA) dataset (282 patients in total, with each fold partitioned into 226 training samples and 56 validation samples) and the Head and Neck Squamous Cell Carcinoma (HNSC) dataset (200 patients in total, with each fold partitioned into 161 training samples and 39 validation samples). The average AUC values obtained from the five-fold cross-validation reached 76.83% and 79.49%, respectively. Experimental results demonstrate that the Resfusion model significantly outperforms unimodal methods and existing multimodal fusion methods, verifying its effectiveness in predicting the radiosensitivity of tumor patients. Full article

Neuromuscular junctions (NMJs) are highly specialized synapses that enable efficient communication between motor neurons and skeletal muscle fibers. Impaired formation or maintenance of NMJs is implicated in the pathogenesis of multiple neuromuscular disorders and contributes to age-related declines in skeletal muscle mass and strength. NMJ functionality is governed by complex regulatory crosstalk among different cells and is mediated by a diverse network of proteins. Moreover, immune cells often reside at NMJs and exhibit phenotypically different characteristics depending on the regenerative state of the muscle. These complex interfaces have posed a significant challenge for elucidating pathogenic mechanisms and developing biomarkers or effective targeted treatments. Many animal models have been developed to address this challenge by characterizing the fundamental structural features of neuromuscular junctions (NMJs) and their transmission capacity under both healthy and disease conditions. In contrast, studies of human NMJs remain limited, although emerging evidence is increasingly revealing substantial morphological and functional differences from animal NMJs. This review provides an overview of animal research on NMJs over the past decades, highlighting interspecies differences and key advances in our understanding of human NMJs. Full article

Knee osteoarthritis (KOA) is a leading cause of disability in older adults, characterized by persistent pain and reduced physical function. Beyond localized joint pathology, many individuals with knee osteoarthritis experience multisite pain and live with multiple comorbidities, reflecting a heterogeneous and multifactorial pain condition. Prognostic models based primarily on biomedical variables have shown limited ability to explain long-term outcomes, partly due to insufficient integration of pain chronicity, comorbidity count and psychosocial determinants such as treatment expectations and pain self-efficacy. While exercise and education are commonly recommended as primary non-surgical treatments, people often respond to them very differently. This study protocol describes a secondary longitudinal observational analysis of data from the EPIPHA-KNEE two-arm, multicentre randomized controlled trial. The primary outcomes will be knee OA pain intensity and physical function, assessed using the Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire at baseline, 3, 6 and 12 months. Baseline prognostic factors will include pain duration, pain distribution, comorbidity count and patient expectations, including treatment expectations and pain self-efficacy. Linear mixed-effects models will be used to examine longitudinal associations between these predictors and pain and function trajectories, with particular emphasis on predictor-by-time interactions to characterize differential patterns of change over time. The planned analyses aim to improve understanding of how clinical characteristics and expectancy-related factors jointly shape 12-month pain and physical function trajectories in older adults with knee osteoarthritis receiving education and exercise-based care, thereby informing prognostic stratification within non-surgical management. Full article

Bone conduction hearing implant systems (BCHIs) are established treatments for patients with conductive or mixed hearing loss or single-sided deafness when conventional hearing aids are unsuitable. This study evaluated the cost-effectiveness of the active transcutaneous system Sentio versus a similar system, i.e., Osia in an Australian setting. Scenario analyses also compared Sentio to other systems, i.e., Ponto and Baha Attract. A Markov cohort model was adapted from a previously published source to reflect Australian practice, incorporating device acquisition, surgery, maintenance, battery replacement and adverse event management over a 15-year horizon from a healthcare perspective. Effectiveness inputs were derived from published evidence using a naïve indirect comparison. Extensive sensitivity analyses and external validation tested robustness. In the base case, Sentio was associated with lower costs and a small modelled incremental quality-adjusted life years (QALYs) gain versus Osia. Scenario analyses confirmed cost-effectiveness relative to Ponto and Baha Attract, with outcomes below the Australian willingness-to-pay threshold. Health state utility, device price and reimplantation assumptions were the most influential drivers, yet Sentio remained cost-effective in over 95% of simulations. These findings support Sentio as a clinically and economically efficient BCHI in Australia and highlight the need for direct utility and long-term durability data. Full article

As an important industrial organizational form in the era of the digital economy, digital industry agglomeration exerts a profound impact on urban ecological resilience. Using panel data of 281 prefecture-level cities in China from 2011 to 2021, this study measures the level of digital industry agglomeration by means of the location entropy method, and constructs an urban ecological resilience evaluation system based on the “Pressure-State-Response (PSR)” model. It systematically examines the impact effects and action mechanisms of digital industry agglomeration on urban ecological resilience. The results show that: (1) The spatio-temporal evolution of the two presents a gradient pattern of “eastern leadership and central-western catch-up”, and their spatial correlation deepens over time, with the synergy maturity in the eastern region being significantly higher than that in the central and western regions. (2) Digital industry agglomeration significantly promotes the improvement in urban ecological resilience, and this conclusion remains valid after endogeneity treatment and robustness tests. (3) The promotional effect is more prominent in central cities, coastal cities, and key environmental protection cities, whose advantages stem from digital infrastructure and innovation endowments, industrial synergy and an open environment, and the adaptability of green technologies under strict environmental regulations, respectively. (4) Digital industry agglomeration empowers ecological resilience by driving green innovation and improving the efficiency of land resource allocation, while the construction of digital infrastructure plays a positive regulatory role. Full article

Background: Emotion processing is critical in the neuropathology of major depressive disorder (MDD), while its relationship with clinical treatment remains unclear. This study aims to indicate the associations between emotion processing and treatment effects following a sequential dual-site accelerated repetitive transcranial magnetic stimulation (rTMS) protocol. Methods: MDD patients were recruited to receive rTMS treatment with four sessions per day for four consecutive days, with stimulation sequentially delivered to the left dorsolateral prefrontal cortex (dlPFC) and the dorsomedial prefrontal cortex (dmPFC). Symptoms were assessed at baseline, end of treatment, and week 4 using the Montgomery–Åsberg Depression Rating Scale (MADRS), Snaith-Hamilton Pleasure Scale (SHAPS), and Fatigue Severity Scale (FSS). Emotional valence and arousal were evaluated with the Affect Rating Task (ART). Results: A total of 51 participants completed the clinical assessments and ART, with two excluded due to missing baseline data in the SHAPS and FSS. The linear mixed-effects models revealed significant improvement in depressive (p < 0.001, d = −0.343) and fatigue symptoms (p = 0.010, d = −0.572) following rTMS treatment. Neutral valence was correlated with MADRS scores at baseline (R² = 0.096, p = 0.027). In addition, changes in arousal for positive images (p = 0.047, adjusted R² = 0.097) and neutral images (p = 0.019, adjusted R² = 0.160) at treatment end were significantly correlated with MADRS improvement at week 4. Conclusions: Our study highlights the association between changes in emotional arousal and improvement in MDD following accelerated dlPFC-dmPFC dual-site rTMS treatment. Full article

Depression represents a leading cause of global disability, yet its pathogenesis remains incompletely understood. This review synthesizes emerging evidence highlighting the multifaceted role of Aquaporin-4 (AQP4), the central nervous system’s predominant water channel, in the pathophysiology of depression. Preclinical studies frequently report AQP4 dysregulation in depression models, characterized by reduced perivascular expression and impaired polarization in mood-relevant brain circuits. We delineate how AQP4 impairment is implicated in depression through several interconnected mechanistic pathways: (1) exacerbating glutamate excitotoxicity by disrupting astrocytic glutamate clearance; (2) impairing monoaminergic neurotransmission and synaptic plasticity; (3) potentiating neuroinflammatory cascades; (4) inducing mitochondrial functional impairment and oxidative stress; and (5) participating in hypothalamic–pituitary–adrenal (HPA) axis dysregulation by disrupting perineuronal osmotic and ionic homeostasis in response to arginine vasopressin (AVP) signaling. Furthermore, we explore the therapeutic relevance of AQP4, noting that diverse antidepressant treatments appear to partly exert their effects by modulating AQP4 expression and function. Collectively, the evidence positions AQP4 not as a solitary causative factor, but as a critical contributing component within the broader astrocyte–neuron–immune network. We therefore propose AQP4 as a promising node for therapeutic intervention, whose modulation may help counteract core pathophysiological processes in depression, offering a potential avenue for novel treatment development. Full article

Drinking-water treatment systems must effectively control natural organic matter (NOM), a major precursor of regulated disinfection by-products (DBPs). Specific ultraviolet absorbance (SUVA) is widely used as an operational surrogate for NOM aromaticity and hydrophobicity; however, ozonation and subsequent filtration can disrupt the linear relationship between SUVA and trihalomethane formation potential (THMFP). This study evaluates whether SUVA can reliably predict THMFP under two ozonation configurations frequently applied in drinking-water treatment: pre-ozonation prior to coagulation–filtration and final ozonation following filtration. Experimental data were analyzed using conventional linear regression and artificial neural network (ANN) models, with SUVA employed as the sole predictor variable. Across all treatment configurations, reductions in SUVA were consistently more pronounced than corresponding decreases in THMFP, indicating a decoupling between chromophoric loss and chlorine-reactive precursor dynamics under ozonation-dominated conditions. Linear regression models exhibited only moderate predictive performance (R² = 0.63–0.76), reflecting the limitations of proportional surrogate-based approaches when NOM undergoes oxidative and adsorptive transformation. In contrast, single-parameter ANN models captured the nonlinear SUVA–THMFP relationship with substantially higher accuracy across both pre- and final-ozonation regimes (R² = 0.88–0.99), successfully resolving process-dependent patterns embedded within optically compressed SUVA signals. These findings demonstrate that, although SUVA alone cannot linearly represent the multistep transformation of NOM during ozonation and adsorption, it retains process-relevant structure information on DBP precursor reactivity that can be effectively extracted using nonlinear modelling. The results highlight the potential of integrating ANN-driven tools into advanced monitoring and DBP-control strategies in modern drinking-water treatment systems. Full article

Background: Human papillomavirus (HPV) infection is the necessary cause of almost all cervical cancers. HPV vaccination programs have been implemented worldwide, yet real-world evidence on vaccine effectiveness against invasive cervical cancer remains limited. Methods: We conducted a retrospective cohort study using synthetically generated data from a large health provider in Israel, including women who underwent a first Papanicolaou (Pap) test during 2014–2015. Their HPV-vaccination status before an index Pap test was obtained from computerized records. Incident cervical cancer and high-grade cervical pathology (cervical cancer, cervical intraepithelial neoplasia [CIN] 1–3, and carcinoma in situ) occurrence were examined through 2022. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models and fitted with propensity score weighting. Results: The cohort included 98,102 women, of whom 9198 (9.4%) were vaccinated against HPV before an index Pap test. While HPV-vaccinated women had a higher risk of cervical pathology compared with unvaccinated women, among women vaccinated before age 18, HPV vaccination was associated with a substantially lower, though not statistically significant, risk of cervical cancer (HR 0.28, 95% CI: 0.07–1.20, p = 0.087). Conclusions: In this large cohort, HPV vaccination was correlated with a higher risk of cervical pathology, likely reflecting residual confounding factors from sexual behavior and differential baseline risks of HPV infection. In contrast, vaccination during adolescence showed a marked trend toward a reduced risk of cervical cancer, consistent with international evidence that early vaccination, prior to HPV exposure, is the most effective preventative treatment. Full article

Background/Objectives: Self-care is a cornerstone of healthy aging and chronic disease management; however, evidence on the most effective intervention models for improving quality of life in older adults with chronic non-communicable diseases (NCDs) remains fragmented. This review aimed to evaluate the effectiveness of self-care interventions in promoting quality of life and health outcomes in older adults with NCDs. Methods: A systematic review was conducted in accordance with PRISMA 2020 guidelines and registered in PROSPERO (CRD420251040613). Randomized and non-randomized clinical trials published between 2019 and 2024 were retrieved from Scopus, Web of Science, and EBSCOhost. Eligible studies included adults aged ≥60 years with NCDs receiving self-care interventions. Data extraction and risk of bias assessment were independently performed using Joanna Briggs Institute tools. Results: Twenty-nine studies involving 7241 older adults were included. Self-care interventions comprised nurse-led educational programs, digital health strategies, community- and peer-based approaches, and person-centered care models. Multicomponent and continuous interventions demonstrated consistent improvements in physical and psychological domains of quality of life, self-efficacy, autonomy, symptom management, and treatment adherence. Digital interventions enhanced monitoring and engagement, although their effectiveness varied according to sensory and health literacy limitations. Conclusions: Structured, person-centered, and nurse-led self-care interventions are effective in improving quality of life and autonomy among older adults with NCDs. These findings support their integration into primary and community-based care, reinforcing their relevance for clinical practice, care planning, and the development of assistive and educational strategies in aging care. Full article