Frontiers and hotspots in comorbid epilepsy and depression: a bibliometric analysis from 2003 to 2023.

Background: Epilepsy ranks among the most common neurological disorders worldwide, frequently accompanied by depression as a prominent comorbidity. This study employs bibliometric analysis to reveal the research of comorbid epilepsy and depression over the past two decades, aiming to explore trends and contribute insights to ongoing investigations. Methods: We conducted a comprehensive search on the Web of Science Core Collection database and downloaded relevant publications on comorbid epilepsy and depression published from 2003 to 2023. VOSviewer and CiteSpace were mainly used to analyze the authors, institutions, countries, publishing journals, reference co-citation patterns, keyword co-occurrence, keyword clustering, and other aspects to construct a knowledge atlas. Results: A total of 5,586 publications related to comorbid epilepsy and depression were retrieved, with a general upward trend despite slight fluctuations in annual publications. Publications originated from 121 countries and 636 institutions, with a predominant focus on clinical research. The United States led in productivity (1,529 articles), while Melbourne University emerged as the most productive institution (135 articles). EPILEPSY & BEHAVIOR was the journal with the highest publication output (1,189 articles) and citation count. Keyword analysis highlighted emerging trends, including "recognitive impairment" and "mental health," indicating potential future research hotspots and trends. Conclusion: This study is one of the first to perform a bibliometric analysis of the 20-year scientific output of comorbid epilepsy and depression. While research has trended upwards, ambiguity in pathogenesis and the absence of standardized diagnostic guidelines remain concerning. Our analysis offers valuable guidance for researchers, informing that this might be a strong area for future collaborations.

Donor-acceptor bulk-heterojunction sensitizer for efficient solid-state infrared-to-visible photon up-conversion.

Solid-state infrared-to-visible photon up-conversion is important for spectral-tailoring applications. However, existing up-conversion systems not only suffer from low efficiencies and a need for high excitation intensity, but also exhibit a limited selection of materials and complex fabrication processes. Herein, we propose a sensitizer with a bulk-heterojunction structure, comprising both an energy donor and an energy acceptor, for triplet-triplet annihilation up-conversion devices. The up-conversion occurs through charge separation at the donor-acceptor interface, followed by the formation of charge transfer state between the energy donor and annihilator following the spin statistics. The bulk-heterojunction sensitizer ensures efficient charge generation and low charge recombination. Hence, we achieve a highly efficient solid-state up-conversion device with 2.20% efficiency and low excitation intensity (10 mW cm-2) through a one-step solution method. We also demonstrate bright up-conversion devices on highly-flexible large-area substrates. This study introduces a simple and scalable platform strategy for fabricating efficient up-conversion devices.

A bioactive xyloglucan polysaccharide hydrogel mechanically enhanced by Pluronic F127 micelles for promoting chronic wound healing.

Chronic wounds represent a formidable global healthcare challenge due to the bacteria infections and uncontrollable inflammation responses, while developing wound healing materials capable of resolving these issues remains a challenge. In this study, we integrated xyloglucan (XG) with Pluronic F127 diacrylate (F127DA)to develop a composite hydrogel for wound healing, where the XG introduced anti-inflammation and anti-bacterial properties to the construct, and F127DA provides the photocurable properties essential for hydrogel formation and robust mechanical characteristics to achieve physical strength that matches tissue regeneration. The material characterizations suggested that XG/F127DA hydrogels had great biostability, blood compatibility and antibacterial effects, which was suitable to be used as a wound healing material. The in vitro analysis by culturing L929 fibroblasts on the hydrogel surface demonstrated that the inclusion of XG could promote the cellular proliferation rate, migration rate, and re-epithelialization-related marker expression, while downregulate the inflammation process. The XG/F127DA hydrogel was further used for the full-thickness skin wound healing test on mice, where the inclusion of XG significantly increased the wound closure rate through reducing the inflammation responses, and promote re-epithelialization and angiogenesis. These results indicated that XG/F127DA hydrogel has great potential to be used for wound healing in future clinical translation.

Co-Creating a Synchronous Tele-Education Program With Community-Dwelling Older Adults Using a Participatory Approach: A Mixed-Methods Study.

There is a pressing need to include older individuals in health education and uncover their specific needs. Leveraging the advantages of digitized health education, this study employed a participatory approach to engage community-dwelling older adults in co-creating a synchronous tele-education program, with dementia as the focus due to its rising prevalence and associated stigma in Singapore. Our findings demonstrate the preliminary effectiveness and feasibility of tele-education. Participants' feedback and recommendations provided valuable insights and could guide the future development of a comprehensive tele-education program. Participants' satisfaction with the co-design workshops also indicates the potential of involving older generations in the design process of user-centered digital health interventions in online environments. Moving forward, the study advocates collaboration among health institutes, government and social agencies, and community organizations, alongside systematic evaluation of the long-term impacts of tele-education, with the aim of improving health outcomes and reducing health inequalities among the older population.

The relationship between childhood psychological abuse and social media addiction among college students: the mediating role of fear of missing out and the moderating role of left-behind experience.

Introduction: Mobile social media is a new type of online media that is participatory, open, and communicative, among other characteristics. Due to the increasing popularity of social media, this technology has become an indispensable part of people's social lives. This study aims to examine the relationship between childhood psychological maltreatment and social media addiction among university students as well as the mediating role of fear of missing out and the moderating effect of left-behind experience in this context. Material and methods: A voluntary anonymous online survey of 1694 university students was conducted using the Childhood Psychological Maltreatment Scale, the Fear of Missing Out Scale, and the Social Media Addiction Scale. Results: First, significant positive correlations were observed between childhood psychological maltreatment and both fear of missing out and social media addiction among university students. Fear of missing out partially mediated the relationship between childhood psychological maltreatment and social media addiction. Second, left-behind experience was found to moderate the direct path from childhood psychological maltreatment to social media addiction as well as the first half of the mediating effect of missed anxiety. Conclusions: Childhood psychological maltreatment can predict social media addiction among university students not only directly but also indirectly through the mediating role of missed anxiety. The direct effect of childhood psychological maltreatment on social media addiction is moderated by left-behind experience. The first half of the mediating role of missed anxiety is also moderated by left-behind experience.

Spatiotemporal Transformation-Based Neural Network With Interpretable Structure for Modeling Distributed Parameter Systems.

Many industrial processes can be described by distributed parameter systems (DPSs) governed by partial differential equations (PDEs). In this research, a spatiotemporal network is proposed for DPS modeling without any process knowledge. Since traditional linear modeling methods may not work well for nonlinear DPSs, the proposed method considers the nonlinear space-time separation, which is transformed into a Lagrange dual optimization problem under the orthogonal constraint. The optimization problem can be solved by the proposed neural network with good structural interpretability. The spatial construction method is employed to derive the continuous spatial basis functions (SBFs) based on the discrete spatial features. The nonlinear temporal model is derived by the Gaussian process regression (GPR). Benefiting from spatial construction and GPR, the proposed method enables spatially continuous modeling and provides a reliable output range under the given confidence level. Experiments on a catalytic reaction process and a battery thermal process demonstrate the effectiveness and superiority of the proposed method.

Duplex Real-Time Fluorescent Quantitative PCR Assays for the Detection of Toxigenic Microcystis Genotypes Based on SNP/InDel Variation in mcy Gene Cluster.

In this study, the toxigenic characteristics of 14 strains of Microcystis were analyzed, and single nucleotide polymorphism (SNP) and insertion/deletion (InDel) loci in microcystin synthetase (mcy) gene clusters were screened. Based on SNP and InDel loci associated with the toxigenic characteristics, primers and TaqMan or Cycling fluorescent probes were designed to develop duplex real-time fluorescent quantitative PCR (FQ-PCR) assays. After evaluating specificity and sensitivity, these assays were applied to detect the toxigenic Microcystis genotypes in a shrimp pond where Microcystis blooms occurred. The results showed a total of 2155 SNP loci and 66 InDel loci were obtained, of which 12 SNP loci and 5 InDel loci were associated with the toxigenic characteristics. Three duplex real-time FQ-PCR assays were developed, each of which could quantify two genotypes of toxigenic Microcystis. These FQ-PCR assays were highly specific, and two Cycling assays were more sensitive than TaqMan assay. In the shrimp pond, six genotypes of toxigenic Microcystis were detected using the developed FQ-PCR assays, indicating that above genotyping assays have the potential for quantitative analysis of the toxigenic Microcystis genotypes in natural water.

Modulation of cardiac resident macrophages immunometabolism upon high-fat-diet feeding in mice.

Background: A high-fat diet (HFD) contributes to various metabolic disorders and obesity, which are major contributors to cardiovascular disease. As an essential regulator for heart homeostasis, cardiac resident macrophages may go awry and contribute to cardiac pathophysiology upon HFD. Thus, to better understand how HFD induced cardiac dysfunction, this study intends to explore the transcriptional and functional changes in cardiac resident macrophages of HFD mice. Methods: C57BL/6J female mice that were 6 weeks old were fed with HFD or normal chow diet (NCD) for 16 weeks. After an evaluation of cardiac functions by echocardiography, mouse hearts were harvested and cardiac resident CCR2- macrophages were sorted, followed by Smart sequencing. Bioinformatics analysis including GO, KEGG, and GSEA analyses were employed to elucidate transcriptional and functional changes. Results: Hyperlipidemia and obesity were observed easily upon HFD. The mouse hearts also displayed more severe fibrosis and diastolic dysfunction in HFD mice. Smart sequencing and functional analysis revealed metabolic dysfunctions, especially lipid-related genes and pathways. Besides this, antigen-presentation-related gene such as Ctsf and inflammation, particularly for NF-κB signaling and complement cascades, underwent drastic changes in cardiac resident macrophages. GO cellular compartment analysis was also performed and showed specific organelle enrichment trends of the involved genes. Conclusion: Dysregulated metabolism intertwines with inflammation in cardiac resident macrophages upon HFD feeding in mice, and further research on crosstalk among organelles could shed more light on potential mechanisms.

Stretchable Sweat Lactate Sensor with Dual-Signal Read-outs.

Innovations in wearable sweat sensors hold great promise to provide deeper insights into molecular level health information non-invasively. Lactate, a key metabolite present in sweat, holds immense significance in assessing physiological conditions and performance in sports physiology and health sensing. This paper presents the development and characterization of stretchable electrodes with ultrahigh active surface area of 648% for lactate sensing. The as-printed stretchable electrodes were functionalized with an electron transfer layer comprising of Toluidine Blue O and multi-walled carbon nanotubes (MWCNTs), and an enzymatic layer consisting of lactate dehydrogenase with ß-Nicotinamide adenine dinucleotide as the cofactor for lactate selectivity. This sensor achieves a dual-signal read-out in which both electrochemical and fluorescence signals were obtained during lactate detection, demonstrating promising sensor performance in terms of sensitivity and reliability. We demonstrate the robustness of the dual-signal sensor under simulated conditions of physical deformation and shifted excitation. Under these compromised conditions, the performance of the stretchable electrodes remained largely unaffected, showcasing their potential for robust and adaptable sensing platforms in wearable health monitoring applications.

A smart hypochlorous acid fluorescent probe enabling Ibuprofen-release for osteoarthritis theranostics.

Background: Osteoarthritis (OA) standing as the most prevalent form of arthritis, closely associates with heightened levels of reactive oxygen species, particularly hypochlorous acid (HOCl). Although there are numerous probes available for detecting HOCl in the OA region, probes with dual functions of diagnostic and therapeutic capabilities are still significantly lacking. While this type of probe can reduce the time gap between diagnosis and treatment, which is clinically needed. Methods: We developed a fluorescent probe (DHU-CBA1) toward HOCl with theranostics functions through the release of methylene blue (MB) and ibuprofen (IBP) in this work. DHU-CBA1 can detect HOCl with high specificity and sensitivity, releasing MB and IBP with an impressive efficiency of ≥ 95% in vitro. Results: DHU-CBA1 exhibits good biosafety, enabling in vivo imaging of endogenous HOCl, along with reducing arthritis scores, improving synovitis and cartilage damage, and maintaining catabolic balance while alleviating senescence in cartilage. Conclusions: This study proposes a novel approach to enhance osteoarthritis therapy by releasing IBP via a smart HOCl-enabled fluorescent probe.

Multiparametric MRI-based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is often treated with neoadjuvant systemic therapy (NAST). We investigated if radiomic models based on multiparametric Magnetic Resonance Imaging (MRI) obtained early during NAST predict pathologic complete response (pCR). We included 163 patients with stage I-III TNBC with multiparametric MRI at baseline and after 2 (C2) and 4 cycles of NAST. Seventy-eight patients (48%) had pCR, and 85 (52%) had non-pCR. Thirty-six multivariate models combining radiomic features from dynamic contrast-enhanced MRI and diffusion-weighted imaging had an area under the receiver operating characteristics curve (AUC) > 0.7. The top-performing model combined 35 radiomic features of relative difference between C2 and baseline; had an AUC = 0.905 in the training and AUC = 0.802 in the testing set. There was high inter-reader agreement and very similar AUC values of the pCR prediction models for the 2 readers. Our data supports multiparametric MRI-based radiomic models for early prediction of NAST response in TNBC.

Genetic variations associated with telomere length predict the risk of recurrence of non-oropharyngeal head and neck squamous cell carcinoma.

Genetic factors underlying lymphocyte telomere length (LTL) may provide insights into genomic stability and integrity, with direct links to susceptibility to cancer recurrence. Polymorphisms in telomere-associated genes are strongly associated with LTL and cancer risk, while few large studies have explored the associations between LTL-related polymorphisms and recurrence risk of non-oropharyngeal head and neck squamous cell carcinoma (non-OPHNSCC). Totally 1403 non-OPHNSCC patients were recruited and genotyped for 16 LTL-related polymorphisms identified by genome-wide association studies. Univariate and multivariate analyzes were performed to evaluate associations between the polymorphisms and non-OPHNSCC recurrence risk. Patients carrying rs755017 GA/GG, rs2487999 TC/TT, rs2736108 TC/TT, or rs6772228 AT/AA genotypes exhibited shorter DFS than those with the rs755017 AA, rs2487999 CC, rs2736108 CC, or s6772228 TT genotypes, respectively (all log-rank p < 0.05). Multivariable analysis confirmed an increased risk of recurrence for patients carrying rs755017 GA/GG, rs2487999 TC/TT, rs2736108 TC/TT, or rs6772228 AT/AA genotypes (adjusted hazard ratio [aHR]: 1.66, 95% confidence interval [CI]: 1.32-2.07; aHR: 1.77, 95% CI: 1.41-2.23; aHR: 1.56, 95% CI: 1.22-1.99; aHR: 1.52, 95% CI: 1.20-1.93, respectively). Further stratified analysis revealed stronger associations between these genotypes and recurrence risk in ever-smokers and patients undergoing chemoradiotherapy. The similar but particularly pronounced results were observed for the combined risk genotypes of the four significant polymorphisms. This is the first large study on non-OPHNSCC patients showing that LTL-related polymorphisms may modify risk of non-OPHNSCC recurrence individually and jointly, particularly when analyzed in the context of smoking status and personized treatment. Larger studies are needed to validate these results.

Dissecting PM sensor capabilities: A combined experimental and theoretical study on particle sizing and physicochemical properties.

Recent advancements in particulate matter (PM) optical measurement technology have enhanced the characterization of particle size distributions (PSDs) across various temporal and spatial scales, offering a more detailed analysis than traditional PM mass concentration monitoring. This study employs field experiments, laboratory tests, and model simulations to evaluate the influence of physicochemical characteristics of particulate matter (PM) on the performance of a compact, multi-channel PM sizing sensor. The sensor is integrated within a mini air station (MAS) designed to detect particles across 52 channels. The field experiments highlighted the sensor's ability to track hygroscopicity parameter κ-values across particle sizes, noting an increasing trend with particle size. The sensor's capability in identifying the size and mass concentration of different PM types, including ammonium nitrate, sodium chloride, smoke, incense, and silica dust particles, was assessed through laboratory tests. Laboratory comparisons with the Aerodynamic Particle Sizer (APS) showed high consistency (R2 > 0.96) for various PM sources, supported by Kolmogorov-Smirnov tests confirming the sensor's capability to match APSsize distributions. Model simulations further elucidated the influence of particle refractive index and size distributions on sensor performance, leading to optimized calibrant selection and application-specific recommendations. These comprehensive evaluations underscore the critical interplay between the chemical composition and physical properties of PM, significantly advancing the application and reliability of optical PM sensors in environmental monitoring.

Unveiling fenpropathrin resistance levels in field populations of Tetranychus cinnabarinus (Boisduval): Insights, risks, and RNAi strategy.

Indoor cases of Tetranychus cinnabarinus displaying resistance have been documented, but the resistance level in field populations remains unexplored in China. This study delves into the resistance dynamics of T. cinnabarinus to fenpropathrin in various field populations across China, a pressing concern in contemporary agricultural pest control. The conventional bioassay and amplicon sequencing reveal a notable absence of significant fenpropathrin resistance in field populations, contrasting with known resistance in indoor cases. Current study highlights the limitations of traditional bioassays in detecting early-stage resistance and underscores the nuanced capabilities and constraints of amplicon sequencing in resistance gene frequency analysis. By employing an integrated approach, we combined dose-response bioassays, amplicon sequencing, and statistical modeling to assess resistance levels and investigate underlying genetic factors. The model with empirical data indicates that a 5% mutation frequency represents the threshold before resistance emerges. However, the detection of the kdr mutation in certain populations ranging from 0 to 1.2%, signals an early looming threat of future resistance emergence. Additionally, we further assessed a specific dsRNA targeting VGSC genes at two concentrations (10 ng/µL and 100 ng/µL), both inducing substantial mortality by silencing target genes effectively. The exploration of RNA interference (RNAi) as a novel, more environmentally friendly pest control measure opens new avenues, despite the ongoing challenge of resistance evolution. Overall, this study underscores the necessity for evolving pest management strategies, integrating advanced biotechnological approaches with traditional methods, to effectively counter pesticide resistance and ensure sustainable agricultural productivity.