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This article proposes an integrative map of mind designed to support whole-person, well-being coaching. It extends the author's 2013 hypothesis published in this journal, "Coaching the Multiplicity of Mind: A Strengths-Based Model," by aligning the author's nine science-informed capacities with Hartman's axiology, which describes three dimensions of value (Intrinsic, Extrinsic, and Systemic) and their 3×3=9 matrix of pairings. The nine pairings, referred to as nine value positions in this paper, are aligned with Self-Determination Theory, the Enneagram, Jung's cognitive functions, and the Big Five Ten Aspect personality traits. They are further organized into three functional bands (identity, stabilizing, and growth) with Confidence as the center, reflecting integration and wholeness. The nine value positions are recognizable as distinct ways people orient to experience through valuing, motivation, and attention, while remaining fluid, contextual, and interconnected in action. Organized into a map, they help coaches recognize which orientations are active, which are underrepresented, and where tensions between positions may call for self-awareness and integration. The integrative map is offered as a working hypothesis: a shared set of value positions that can align psychological frameworks commonly applied in coaching as a set of dimensions of each of the shared value positions. The map may allow coaches to (1) work from one map rather than holding many constructs and frameworks in parallel, (2) recognize which orientations a client is engaging and which are underrepresented, (3) approach tensions as integration opportunities.
Artificial intelligence (AI) possesses the transformative potential to reshape pediatric medicine, offering powerful tools for diagnosis, prognosis, and personalized therapy. This review focuses on three domains selected for their relative maturity in AI development and proximity to clinical translation-pediatric critical care, perinatal and neonatal medicine, and precision oncology-evaluating current evidence for clinical utility and outlining challenges to implementation. AI is demonstrating significant potential across these domains: in critical care, deep learning models outperform traditional scoring systems for dynamic prediction of adverse events; in perinatal and neonatal medicine, AI enhances prenatal ultrasonography and integrates multiomics data to guide complex therapies; and in oncology, radiomics, and genomic analysis enable non-invasive tumor characterization and personalized treatment strategies. However, significant hurdles remain. Foundational data challenges-including scarcity, heterogeneity, and limited sharing of pediatric data-are being addressed through transfer learning, federated learning, and synthetic data generation. Clinical translation is further impeded by algorithmic bias, the 'black box' problem, and the unique developmental physiology of children, which demands age-specific model validation. Future progress depends on multi-institutional collaboration, a research focus that extends beyond prediction to encompass causal inference and explainability, and the establishment of robust ethical, regulatory, and economic frameworks. Ultimately, responsible implementation of AI in pediatrics requires building systems that are not merely accurate but transparent, equitable, and trustworthy.
According to objectification theory, self-objectification adversely affects women's cognitive performance, leading to cognitive inhibition. However, results are inconsistent, and few studies have explored mechanisms and protective factors of cognitive inhibition. This study adopted a numerical Stroop paradigm with varying interference levels to investigate self-objectification's effect on women's cognitive inhibition, and highlights the role of interference level in understanding the effects of self-objectification on cognitive inhibition, revealing that self-objectification impaired cognitive performance primarily under the high-interference level. It also identifies appearance anxiety as a key mediator and self-compassion as a protective factor. By demonstrating that the effect of self-objectification on cognitive inhibition depends on interference level, this study resolves inconsistencies in previous research and extends objectification theory by identifying high cognitive load as a critical boundary condition and revealing self-compassion as a protective factor. These findings inform interventions to reduce self-objectification's cognitive impairment, particularly in high-demand tasks affecting women's performance.
To use Google Trends to assess whether interest in rotator cuff repair (RCR) has increased over the last 15 years and to identify the most frequently searched topics related to RCR. A retrospective longitudinal study was conducted on public interest in RCR using Google Trends. While using a focus group comprised of 2 sports-medicine fellowship-trained orthopaedic surgeons, 1 orthopaedic surgery resident, 3 medical students, and supplementing with ChatGPT, the 50 most commonly searched topics perioperatively regarding RCR were identified. The mean relative search volume (RSV) was obtained and compared for all 50 topics. Regarding RSV, which extends from 0 to 100, 0 represents no public interest, whereas 100 represents maximal public interest. Inclusion criteria for search topics included Google search terms concerning RCR which had a mean RSV available between January 2010 and December 2024. Analysis of variance tests were used to compare means. Statistical significance was set at a P value less than .05. Between January 2010 and December 2024, the mean RSV for "rotator cuff surgery" significantly increased (2010: 51; 2024: 90; P < .001), representing growing patient interest in rotator cuff surgery. Among the 50 perioperative topics, "recovery" and "pain" had significantly higher mean RSVs than other topics, whereas "sling," "therapy," "cost," "how long does rotator cuff surgery take," "arthroscopic surgery," "sleep," "rehab," and "healing" were also among the top ten topics with the highest mean RSV (79; 51; 20; 18; 14; 13; 9; 8; 7; 4; P < .001). Google searches for RCR have increased significantly during the past 15 years. Pain and recovery after RCR were the most frequently searched topics. This study investigates the public interest in RCR as indicated by Google search data. The level of interest has increased during the past 15 years, and the topics identified in this study should be included in patient education materials.
To use Google Trends to study whether public interest in meniscus surgery has increased during the last 15 years and after the COVID-19 pandemic, and to determine what specific topics regarding meniscus surgery the public is interested in. A longitudinal observational study was conducted between January 2010 and December 2024 on public interest in meniscus surgery utilizing Google Trends. Through establishing a focus group comprising two attending orthopaedic surgeons (sports-medicine fellowship trained), one orthopaedic surgery resident, and three medical students, and using ChatGPT, the 50 most commonly searched questions regarding meniscus surgery were identified. The mean relative search volume (RSV) was identified and compared for 50 search terms. RSV extends from 0 to 100, with 0 representing no public interest, and 100 representing maximal public interest. Analysis of variance tests compared means. Statistical significance was set at a P value less than .05. Between 2010 and 2024, the mean RSV for "meniscus surgery" increased significantly (2010: 40; 2024: 89; P < .001), after a transient decline during the COVID-19 pandemic. Among 50 topics regarding meniscus surgery, "recovery" and "pain" had the highest mean RSVs, while other topics including "arthroscopic meniscus surgery", "cost", "how long does meniscus surgery take", "therapy", "brace", "rehab", "swelling", and "arthritis" were also commonly searched (60 vs 25 vs 15 vs 9 vs 9 vs 6 vs 6 vs 5 vs 4 vs 2; P < .001). Patient interest in meniscus surgery has increased significantly during the past 15 years, and rebounded after the COVID-19 pandemic. Patients have interest in many topics regarding meniscus surgery, including recovery, pain, surgical length, cost, postoperative therapy, braces, and post-traumatic arthritis. This study showed that public interest in meniscus surgery has increased significantly in the last 15 years, and the various topics that are important to patients, as identified in this study, should be included in patient education materials.
This study uses density functional theory (DFT) calculations combined with molecular dynamics (MD) simulations to evaluate the water-splitting performance of the SrTiO3 perovskite improved through synergistic Si and As co-doping. While static DFT calculations capture only a single atomic configuration, MD simulations provide finite-temperature atomic ensembles, enabling realistic assessments of water adsorption, dissociation, and radical-formation processes. Pristine SrTiO3 shows pronounced thermal fluctuations, indicating weak thermal management, likely caused by limited generation of charge carriers and their rapid recombination. In contrast, the Si-doped, As-doped, and especially Si-As co-doped systems achieve faster thermal stabilization, suggesting enhanced charge-carrier dynamics and improved photocatalytic activity. Electronic analysis reveals significant band-gap narrowing in the doped structures due to the introduction of dopant-induced electronic states near the conduction band, increasing charge-carrier mobility. The band-gap trend-pure (2.12 eV) > As-doped (1.47 eV) > Si-As co-doped (1.50 eV) > Si-doped (1.28 eV)-extends absorption toward 570 nm, enabling visible-light-driven photocatalytic activity that is not exhibited by pristine SrTiO3. Overall, Si-As co-doping markedly enhances SrTiO3's water-splitting capability.
NLRP12, a member of the NOD-like receptor family, has traditionally been regarded as an inflammasome-associated regulator of inflammatory signaling. However, accumulating evidence indicates that its role in cancer extends far beyond classical inflammasome biology. Recent studies show that NLRP12 exerts highly context-dependent functions across malignancies, acting as either a tumor suppressor or a tumor promoter depending on tumor type, cellular source, and dominant signaling environment. In inflammation-associated and epithelial malignancies such as colorectal cancer, hepatocellular carcinoma, and triple-negative breast cancer, NLRP12 suppresses tumor progression by restraining noncanonical NF-κB, Wnt/β-catenin, JNK, or canonical NF-κB signaling. In contrast, in gastric cancer, ovarian cancer, glioma, and macrophage-rich tumor ecosystems, NLRP12 has been linked to glycolytic remodeling, lactate-associated epigenetic adaptation, aggressive clinicopathological features, and immune suppression. Mechanistically, NLRP12 has emerged as a multifunctional signaling regulator that connects inflammatory control with oncogenic pathway modulation, metabolic rewiring, tumor-associated macrophage polarization, and PANoptosis-related stress responses. These findings position NLRP12 at the crossroads of tumor progression, immunity, metabolism, and inflammatory cell death. In this review, we summarize the molecular and functional landscape of NLRP12 in cancer, with emphasis on its dual roles in tumor biology, its context-specific mechanisms, and its potential clinical relevance as a biomarker and therapeutic reference point. A deeper cell-resolved and mechanism-oriented understanding of NLRP12 may help redefine this molecule from a conventional innate immune regulator to a context-dependent organizer of tumor ecosystems.
Parkinson's disease (PD) is characterized by progressive motor impairment and large-scale network dysfunction that extends beyond dopaminergic degeneration. Although rehabilitative exercise improves clinical outcomes, its capacity to induce structural brain plasticity remains incompletely understood. Here, we tested the hypothesis that forced (high-intensity) upper-limb exercise induces white matter microstructural remodeling in PD. Twenty-three patients with idiopathic PD (mean age 69.1 ± 6.5 years) were allocated to a forced exercise group (FE; n = 13) or a voluntary exercise group (VE; n = 10) and underwent an 8-week supervised upper-limb training protocol. Groups were matched for age, sex, and clinical severity. Assessment included diffusion tensor imaging (DTI) of cerebellar and thalamocortical tracts, computerized dynamic posturography (CDP), the motor section of the Unified Parkinson's Disease Rating Scale (UPDRS-III) and the Hoehn and Yahr scale. Significant Group  ×  Time interactions were identified in the inferior cerebellar peduncle mean diffusivity (MD), Axial Diffusivity, Radial Diffusivity (RD); all p < 0.001 and middle cerebellar peduncle (MDP) p = 0.021), confirming that microstructural changes were significantly larger in the FE group. Results for the anterior corticothalamic radiation represent exploratory trends (p ≈ 0.06 for the interaction) and should be interpreted with caution. Findings were accompanied by significant improvements in postural stability in the FE group. These findings identify exercise-induced plasticity within distributed motor-vestibular networks, supporting a systems-level compensatory mechanism. Our results provide in vivo evidence that targeted rehabilitation can reshape structural connectivity in PD, with implications for developing disease-modifying interventions.
This analysis was conducted to assess the risk of anemia in schizophrenia patients during long-term treatment with the glycine transporter-1 (GlyT1) inhibitor iclepertin. A population pharmacokinetic-pharmacodynamic (popPKPD) analysis to characterize the impact of iclepertin exposure on hemoglobin levels was performed using a sequential nonlinear mixed effects modeling approach. The effects of patient characteristics were investigated in a covariate analysis to identify vulnerable patient subgroups, and population simulations were conducted to evaluate different treatment scenarios. Simulations predicted a new, decreased hemoglobin steady state under chronic iclepertin treatment, reached after approximately 120 days. For a typical patient, the intended therapeutic dose of 10 mg iclepertin daily led to a 2% decrease of hemoglobin levels. In a potential extreme scenario of iclepertin exposure fivefold higher than the average exposure following a 10 mg dose (e.g., due to co-administration of a strong CYP3A4 inhibitor), a 7.6% decrease of hemoglobin levels was found. In both scenarios more than 97.5% of the virtual patients stayed above the drug discontinuation safety threshold of 100 g/L hemoglobin (Phase III trial drug discontinuation threshold defined by the patient safety team). Sex, race, age, body mass index and alanine transaminase levels were found to correlate with changes in hemoglobin levels. No correlation with kidney function could be identified. None of the investigated covariate effects were strong enough to raise any safety concerns during chronic treatment with 10 mg iclepertin daily. This work provides a generalizable modeling and simulation framework to assess the anemia risk in patients and vulnerable patient subgroups during chronic iclepertin treatment. The results of this analysis suggest that iclepertin drug effects on patient hemoglobin levels are small, reversible, and of limited significance, even under long-term treatment. This is the first model of the relationship between iclepertin exposure and hemoglobin levels, and, to our best knowledge, the first model to characterize a drug effect on hemoglobin levels over time that has been validated with clinical data that extend beyond the erythrocyte life span of ∼126 days.
This study aimed to explore the network relationship between anxiety and cognition and its mechanism, providing a theoretical basis for formulating anxiety-related intervention strategies. Data were collected from 146 patients in the Rehabilitation Department of Dongfang Hospital, Beijing University of Chinese Medicine. The Hamilton Anxiety Scale (HAMA) and Montreal Cognitive Assessment (MoCA) were used to measure 14 anxiety dimensions and 7 cognitive dimensions, respectively. A regularized partial correlation network (Gaussian graphical model) was estimated using the graphical LASSO with the extended Bayesian information criterion (EBICglasso, γ = 0.5) on a cor_auto correlation matrix, and centrality, edge accuracy, and network stability were assessed using nonparametric bootstrapping. Network analysis showed that the anxiety dimensions of Behavior at Interview, Depressed Mood, Anxious Mood, Fears, and Tension, and the cognitive dimensions of Attention and Abstraction had higher centrality. The anxiety dimensions of Cognitive Impairment and Behavior at Interview had the highest betweenness in the "anxiety-cognition" network, while Genitourinary Symptoms had smaller strength and closeness compared to other network dimensions. The CS-coefficient (centrality stability coefficient) values were 0.596 for expected influence, 0.363 for strength, 0.281 for closeness, and 0.048 for betweenness. The network structure results were stable. In anxiety, Behavior at Interview, Depressed Mood, Anxious Mood, Fears, and Tension were key intervention candidate nodes. Because the cross-domain edges anchored on HAMA5 (Cognitive Impairment) partly reflect the construct overlap between subjective and objective cognition, the anxiety-cognition findings most directly relevant for intervention design are those connecting affective and behavioral HAMA items to specific MoCA dimensions.
Lithium-sulfur batteries (LSBs) fail catastrophically under ultralow temperature due to frozen polysulfide conversion kinetics, with no existing technology achieving high-energy-density operation below -40°C. Here, we report a self-regulating LSB system, the 'smart symbiosis' cell, that activates multifield synergy at interface reaction sites to overcome kinetic barriers under low temperature. This directly modulates the transport of ions/electrons and the spin electron states of reaction sites at the quantum level, enabling wave-shaped charge/discharge profiles and achieving a ratio of 3.11 between the first plateau and the second plateau (theoretical value 3.0). The ultratheoretical capacity mechanism is revealed-magnetic field-induced enhancement of kinetics and interfacial reactions. The pouch cell achieves an energy density of 454.5 Wh kg-1 (based on total system mass) and 219.1 Wh kg-1 (with device consumption) at -80°C. This technology could increase the capacity of batteries by 9.5 times at low temperatures with an energy consumption of ∼0.091% °C-1 of the battery energy, while the conversion retention rate remains as high as 87% after 200 cycles (∼2800 h), and breaks the lowest temperature record. This new battery system opens the door to extremely wide temperature applications for LSBs and could be extended to other batteries.
Background Colonic diverticula are mucosal pouch anomalies extending through vulnerable areas of the colonic wall. While common in Western nations, managing complicated perforated sigmoid and rectosigmoid diverticulitis remains contentious due to high rates of abscess and peritonitis. Hartmann's surgery is commonly employed for perforated sigmoid and rectosigmoid diverticulitis due to its efficiency and the mitigation of anastomotic leakage risks. However, reversal remains challenging due to inflammatory adhesions and shortened margins. This study aims to elucidate the morbidity and mortality associated with Hartmann's operation for perforated sigmoid colon and rectosigmoid diverticula. Methodology This retrospective cohort study evaluated 96 patients diagnosed with perforated sigmoid and rectosigmoid diverticulitis who underwent open Hartmann's procedures at the Department of Digestive Surgery, Cho Ray Hospital, between May 2020 and April 2025. Demographic profiles, surgical characteristics, and 30-day postoperative complications and mortality rates were documented. Results The cohort included 50 males and 46 females with a mean age of 67.7 ± 11.4 years; 42 (43.75%) patients were over 70 years of age. Preoperative stratification that showed 60 (62.5%) patients were American Society of Anesthesiologists (ASA) Class II and 36 (37.5%) were ASA Class III. The mean postoperative stay was 7.1 ± 4.8 days, and the overall 30-day postoperative mortality rate was 20.8% (n = 20). Surgical site infections (all superficial incisional) occurred in 24% (n = 23) of cases, and postoperative pneumonia (confirmed by postoperative chest X-ray) occurred in 21.9% (n = 20). Univariate analysis showed that advanced age (>70 years) and intraoperative fecal contamination significantly increased complication risks (p = 0.015 and p = 0.026, respectively). Predictors correlating with increased mortality in univariate analysis included an admission systolic blood pressure (SBP) <90 mmHg (p < 0.001) and fecal peritonitis (p = 0.028). Mortality rates increased with disease severity, reaching 38.1% for Hinchey Grade IV, in contrast to 19.3% for Grade III and 5.6% for Grade II (p = 0.05). Multivariable logistic regression indicated that age exceeding 70 years (odds ratio (OR) = 3.085, p = 0.013) and fecal contamination (OR = 3.328, p = 0.024) were independent predictors of postoperative complications, whereas an admission SBP below 90 mmHg (OR = 16.621, p = 0.001) was the sole independent predictor of mortality. Conclusions Hartmann's procedure is an appropriate intervention for severe perforated sigmoid and rectosigmoid diverticulitis with fecal contamination of the abdominal cavity, shock, or patients with multiple comorbidities. Baseline patient factors heavily dictate survival and morbidity outcomes, with advanced age, intraoperative fecal contamination, and admission hypotension serving as critical prognostic drivers.
Many transcription factors are considered "undruggable" and challenging targets due to the absence of ligandable pockets, large swaths of intrinsically disordered regions, and rapid turnover. Here, we describe a new induced-proximity therapeutic modality, Transcriptional Repression via Active Chemical Epigenetic Reprogramming (TRACER), that enforces locus-specific transcriptional silencing by recruiting endogenous corepressor complexes to transcription factor binding sites. We developed small-molecule TRACERs that tether methyl-CpG binding domain protein 2 (MBD2), a component of the Nucleosome Remodeling and Deacetylase (NuRD) complex, to transcription factor-directed ligands. Recruitment of the NuRD complex by an estrogen receptor (ER) TRACER potently suppressed ER transcriptional activity in breast cancer cells, downregulated ER target genes, and required MBD2 and histone deacetylase (HDAC1/2) for activity, confirming on-target epigenetic repression. Extending this approach to prostate cancer, an androgen receptor (AR) TRACER transcriptionally repressed both full-length AR and the drug-resistant truncation variant, AR-V7, thereby achieving >90% inhibition of AR-dependent transcription in androgen-independent prostate cancer cells with locus-specific gene repression. Collectively, these findings establish TRACERs as a generalizable modality to pharmacologically silence transcription factors through targeted epigenetic reprogramming, offering a powerful strategy for treating cancers refractory to existing therapies.
Predictive modeling of phototrophic cultures in photobioreactors remains challenging because growth emerges from the coupling between radiative transfer, intracellular bioenergetics, and physiological acclimation. Although existing approaches have progressively integrated light attenuation and reactor-scale heterogeneity, extending knowledge-based formulations to eukaryotic microalgae still raises difficulties, especially regarding the role of respiration under illumination and the dynamic adjustment of pigment content. In this work, we establish a biochemically structured predictive model of photoautotrophic growth for the eukaryotic microalga Chlamydomonas reinhardtii. The model is built from an explicit stoichiometric decomposition of the main metabolic functions involved in biomass synthesis, pigment synthesis, photosynthetic energy conversion, respiration, and ATP-consuming futile processes under redox regulation. Its structure is derived from intracellular conservation relationships and observability analysis, leading to a reduced formulation driven by two variables: the net conversion rate of photochemically productive photons within the biotic phase, q γ , and a dissipative ATP sink. The kinetic formulation explicitly couples growth to radiative transfer and accounts for dynamic pigment acclimation through variable partitioning of biomass formation between residual biomass and pigments. Model parameters were either fixed from previous physiological and bioenergetic analyses or identified from batch-culture experiments performed under different incident photon flux densities in a flat-panel photobioreactor illuminated from one side. The model satisfactorily predicts biomass and pigment dynamics in batch and continuous cultures over a broad range of light conditions and dilution rates, while comparisons with oxygen-exchange measurements under illumination provide additional support for its structural relevance. The proposed framework provides a predictive and mechanistically interpretable description of eukaryotic microalgal growth in photobioreactors.
As generative artificial intelligence (GenAI) becomes increasingly integrated into higher education, concerns have emerged regarding students' growing reliance on GenAI for academic tasks. Although prior studies have examined the educational benefits of GenAI, limited research has explored the psychological mechanisms underlying students' dependence on these technologies. This study investigated whether academic self-efficacy predicts GenAI dependence and examined the mediating roles of academic stress and perceived usefulness of GenAI. Using a time-lagged survey design, data were collected from 428 college students from five universities in eastern China. Participants completed validated measures of academic self-efficacy, academic stress, perceived usefulness of GenAI, and GenAI dependence. Structural equation modeling and bootstrap analyses were conducted to examine the hypothesized mediation pathways. Academic self-efficacy was significantly and negatively associated with GenAI dependence. Academic stress and perceived usefulness of GenAI each served as significant mediators between academic self-efficacy and GenAI dependence. Furthermore, academic stress was positively associated with perceived usefulness of GenAI, and the sequential pathway from academic self-efficacy to academic stress, perceived usefulness of GenAI, and GenAI dependence was significant. Specifically, students with lower academic self-efficacy experienced greater academic stress, which increased their perceptions of the usefulness of GenAI and subsequently strengthened their dependence on GenAI. Academic self-efficacy affects college students' GenAI dependence both directly and indirectly through academic stress and perceived usefulness of GenAI. The findings extend the application of the I-PACE framework to the context of generative artificial intelligence and provide practical insights for universities seeking to promote responsible GenAI use, enhance students' independent learning capabilities, and mitigate excessive reliance on AI-assisted learning tools.
Obesity is increasingly being recognized as a heterogeneous condition with strong genetic underpinnings. Monogenic obesity, caused by single-gene mutations, primarily affects the leptin-melanocortin pathway, which regulates hunger and satiety. Mutations in genes, such as LEP, LEPR, POMC, PCSK1, and MC4R, lead to hyperphagia, early onset severe obesity, and metabolic dysregulation. LEP and LEPR mutations impair leptin signaling, resulting in defective appetite suppression, whereas POMC and PCSK1 deficiencies disrupt prohormone processing. MC4R mutations, the most common cause of monogenic obesity, impair satiety signaling and are linked to rapid weight gain. Syndromic obesity, including the Bardet-Biedl and Alström syndromes, involves ciliary dysfunction, leading to developmental abnormalities alongside obesity. Other genes such as SH2B1, SIM1, and BDNF play crucial roles in hypothalamic development and energy regulation. Advances in genomic sequencing have improved the recognition of genetic etiologies; however, many patients remain undiagnosed due to limited testing availability and a lack of clinician awareness. Precision therapies, including set-melanotide for specific melanocortin pathway defects, demonstrate the promise of targeted treatments. However, management must extend beyond pharmacology; lifestyle interventions, psychosocial support, and family-centered care remain essential, especially when intellectual disability or behavioral challenges complicate adherence. Ethical considerations surrounding access and equity are critical, as high-cost therapies and the limited availability of genetic testing risk widening disparities between health systems. Polygenic risk scores and multi-omics approaches may expand precision medicine beyond rare genetic syndromes to common obesity, highlighting the importance of integrating genetics, psychosocial care, and policy advocacy in the management of pediatric obesity.
The optimal duration of voice rest after phonomicrosurgery remains a subject of debate, as clinical studies on its effect on vocal fold wound healing have yielded conflicting results, and a controlled animal model for investigating voice rest is currently unavailable. This study aimed to determine the optimal postoperative voice rest duration using a controlled rabbit model. Building on our established rabbit model for graded voice rest, we created two distinct phonomicrosurgery injury models: one involving the superficial lamina propria (SLP) and another extending to the mid-deep lamina propria (MDLP). The effects of different voice rest durations on wound healing were systematically evaluated through ex vivo laryngeal phonatory vibration experiments, histopathological examinations (hematoxylin-eosin, Alcian Blue, and Elastica van Gieson staining), and Gray Level Co-occurrence Matrix texture analysis. The optimal voice rest duration was dependent on surgical depth. In the SLP surgery model, a 1-day voice rest period resulted in the most favorable outcomes, characterized by superior voice quality and histological organization. In contrast, for the MDLP surgery model, a 3-day voice rest duration promoted optimal wound healing, yielding better vocal function, improved vibration, and reduced tissue fibrosis. Voice rest requirements differ based on surgical depth.
Oritavancin is a long-acting semisynthetic lipoglycopeptide with potent activity against a broad range of Gram-positive pathogens. Its multimodal mechanism of action and prolonged terminal half-life allow for extended dosing intervals, making it an off-label option for invasive infections requiring long-term antimicrobial exposure. However, evidence supporting its use in infective endocarditis and cardiac device-related infections remain limited. We performed a retrospective multicentre observational study including adult patients treated with multidose oritavancin for infective endocarditis and cardiac device-related infections between 2020 and 2025. Oritavancin was administered as consolidation or as long-term suppressive therapy. Demographic, clinical, microbiological, pharmacological, and outcome data were collected. Therapeutic drug monitoring was performed, and pre-dose plasma concentrations were analysed. Clinical outcomes included clinical cure, microbiological failure, adverse events, and 30- and 90-day all-cause mortality. Nine patients were included. Oritavancin was mainly administered at 1200 mg per dose, with a median dosing interval of 10 days. Clinical success was achieved in 6/9 patients (66.7%). One patient discontinued therapy due to infusion-related adverse events, and two experienced microbiological failure, both in left ventricular assist device-related infections. No 30- or 90-day mortality was observed. TDM, when performed, demonstrated persistent pre-dose plasma concentrations over several weeks, with marked interindividual variability across patients and intra-individual temporal changes over time, including drug accumulation in some cases. Multidose oritavancin appears to be a promising consolidation or suppressive strategy in selected patients with complex Gram-positive endovascular infections. Prospective studies are needed to define optimal dosing regimens and the role of TDM in this setting.
Cancer has become one of the leading causes to human death, which promotes scientists to develop various treatment modalities. Among them, hydrogen sulfide (H2S)-based gas therapy (GT) emerges as a facile but promising approach due to its unique merits including fast active tissue and cell penetration, robust bioactivity, negligible drug resistance. However, as a potent bioactive gas molecule, uncontrolled diffusion would significantly compromise the therapeutic efficacy and cause side effect. To address this issue, stimuli-responsive nanostructured H2S donors, a subtype of donors capable of forming nanostructures, have been explored. Compared with unassembled ones, they could not only prolong the release time and fine tune the release rate at the aid of nanostructures, but also achieve targeting delivery of H2S in a passive or active manner. Given that huge advancement has been made in the past few years, in this review, we survey and categorize the latest progress of these nanostructured H2S donors for cancer treatment in terms of different constituted materials from organic to hybrid. Both H2S-based single GT and combined therapies are examined in this review thoroughly. At the end, future outlooks and upcoming challenges of these emerging donors are discussed. We believe that it would inspire scientists to design new donors and extend their applications for human care.
NMR spectral simplification is a powerful strategy for facilitating the analysis and structural characterization of complex mixtures. In this work, we present a nanoparticle-assisted protocol that employs positively charged imidazolium ionic liquid-coated silica nanoparticles ( 1 ) to selectively interact with analytes. π-π interactions, electrostatic attractions, and hydrogen-bonding between the nanoparticles and target molecules extend the rotational correlation time, thereby accelerating relaxation processes. As a result, NMR signals from aromatic and negatively charged species undergo pronounced attenuation or even complete disappearance. In contrast, signals from positively charged analytes or compounds lacking π-bond systems remain largely unaffected. This selective suppression of resonances enables effective spectral simplification and highlights the potential of nanoparticle-based editing approaches for practical applications in the analysis and structural determination of complex mixtures.