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Neoadjuvant radiotherapy (RT) in prostate cancer remains investigational. This prospective pilot study evaluated the feasibility, perioperative safety, and preliminary outcomes of neoadjuvant RT combined with androgen-deprivation therapy (ADT), followed by robot-assisted radical prostatectomy (RP), in high-risk locally advanced disease. Patients with high-risk locally advanced prostate cancer (clinical stage T3a-T3b, Gleason score ≥8, or prostate-specific antigen [PSA] ≥ 20 ng/mL) were prospectively enrolled. All patients received neoadjuvant RT (50 Gy in 25 fractions) with 3 months of ADT, then robot-assisted RP with pelvic lymph node dissection. A retrospective contemporaneous RP-alone cohort served as controls. Primary outcomes included perioperative safety, pathological response, and postoperative PSA levels. Secondary endpoints included oncological outcomes, functional outcomes, and MRI-derived imaging biomarkers. In total, 10 patients received neoadjuvant RT, and 11 patients served as controls. The median PSA at diagnosis was 19.46 ng/mL in the neoadjuvant group and 15.52 ng/mL in controls. No major complications occurred. Pathological downstaging was observed in 60% of the neoadjuvant group, whereas none occurred in controls (4/11 showed upstaging). At 12 months, urinary continence was achieved in four patients. After a median follow-up of 16.4 months, five patients developed biochemical recurrence, and one progressed to bone metastasis. Post-treatment changes in apparent diffusion coefficient values and T2-weighted MRI signals were associated with improved pathological outcomes, suggesting potential predictive value. Neoadjuvant RT with ADT followed by RP is feasible and well tolerated in high-risk locally advanced prostate cancer. Although pathological downstaging was observed, this pilot study does not support definitive conclusions regarding oncologic benefit, and larger prospective studies are warranted.

Hydrogels are versatile soft materials extensively applied in biomedical fields including tissue engineering, drug delivery, and biosensing. A critical challenge in these applications is maintaining hydrogel integrity at the target site, as the loss or displacement of the hydrogel can compromise tissue regeneration, therapeutic delivery, or sensor functionality. Adhesive hydrogels, therefore, are essential to ensure stable interfacial interactions with biological tissues. Silk fibroin, a natural polymer, offers biocompatibility, low toxicity, tunable mechanical properties, and controllable biodegradability, making it a promising candidate for hydrogel scaffolds and biosensor substrates. However, its limited functional sites restrict intrinsic adhesion, necessitating strategies to enhance interfacial bonding. This Review systematically examines approaches to improve the adhesion of silk-fibroin-based hydrogels, including chemical modification, incorporation of functional polymers, and catechol-mediated interactions, alongside the mechanistic principles underlying each strategy. Representative applications in tissue engineering, drug delivery, and biosensing are highlighted to demonstrate their translational potential. By integration of design strategies with mechanistic insights, this work provides a framework for developing silk-fibroin-based adhesive hydrogels tailored for specific tissue interfaces, enabling robust, multifunctional, and clinically relevant biomaterials for advanced biomedical and diagnostic applications.

The AAEV (American Association of Extracellular Vesicles) Annual Meeting at the John P. McGovern Commons in Houston, TX convened over 300 leading researchers, clinicians, and industry experts from around the world to advance the rapidly evolving field of extracellular vesicle (EV) science. EVs, nanoscale lipid-bound particles released by all prokaryotic and eukaryotic cells, have emerged as crucial mediators of intercellular communication, trans- porting proteins, nucleic acids, and lipids that influence a wide spectrum of physiological and pathological processes. Their involvement in immune modulation, tissue regeneration, cancer progression, metabolic regulation, and other complex biological functions positions EVs as promising diagnostic biomarkers and therapeutic delivery agents in precision medicine and personalized healthcare. However, significant challenges persist, including the heterogeneity of EV populations, complexities in isolation and purification, and the pressing need for standardized characterization protocols. The 2024 AAEV's annual gathering provided a pivotal forum for exchanging insights and cultivating collaborations. The meeting featured keynote addresses delved into the intricate heterogeneity, biogenesis pathways, and immu- nomodulatory capabilities of EVs, as well as their contributions to disease progression. Subsequent sessions covered a broad range of topics, showcasing cutting-edge technologies for EV isolation and characterization, revealing novel mechanisms by which EVs modulate immune responses and disease states, and presenting innovative EV engineering approaches for delivering therapeutics. Industry presentations complemented academic discussions by introducing scalable EV production systems, automated isolation methods, specialized analytical tools, and strategies to navigate regulatory pathways. Alongside these presentations, the association supports dissemination of the latest discoveries and methodologies through its flagship publication, Extracellular Vesicle (EV). Collectively, the insights shared at the AAEV Annual Meeting underscored the remarkable progress in understanding EV complexity, refining isolation and analysis techniques and translating fundamental discoveries into clinically actionable solutions. Speakers highlighted advanced isolation platforms, refined bioengineering methods, and efforts to integrate EV-based diagnostics and therapeutics into existing clinical frameworks. As the field matures, the forward momentum reflects a transition from theoretical potential to tangible applications. By fostering global collaboration, strengthening ties between academia and industry, and providing platforms like the EV journal, for ongoing dialogue, the EV community is well-positioned to surmount current challenges and accelerate the integration of EV-based approaches into mainstream healthcare.

Growing evidence suggests potential ethnic and geographical variations in chemotherapy efficacy. The CA125 ELIMination rate constant K score is a pragmatic and reproducible indicator of tumor chemosensitivity in newly diagnosed ovarian cancer. We compared ELIMination rate constant K distributions and prognostic performances between patients enrolled in Japanese and Western trials who had stage III/IV serous ovarian cancer from the Gynecologic Cancer InterGroup individual-patient-data Meta-Analysis in OVarian cancer. The ELIMination rate constant K values were previously estimated for 5884 women receiving first-line chemotherapy for ovarian cancer. Data from 246 women enrolled in the Japanese JGOG-3016 trial were compared to 2561 patients from Western trials. ELIMination rate constant K was analyzed as a binary variable (favorable &#x2265;1.0 vs unfavorable <1.0). Prognostic value for progression-free survival and overall survival was assessed using univariable and multi-variable models. A standardization cut-off specific to patients enrolled in the Japanese trial was explored using maximally selected rank statistics. KELIM was significantly higher in patients enrolled in the Japanese trial (median 0.071 day-1 vs 0.056 day-1; p <.0001). Using the standard cut-off, favorable ELIMination rate constant K was independently associated with improved progression-free survival (hazard ratio 0.59, 95% confidence interval 0.43 to 0.83) and overall survival (hazard ratio 0.53, 95% confidence interval 0.36 to 0.79) in patients from the Japanese trial. Applying the exploratory cut-off of 0.07 day-1 strengthened prognostic discrimination (progression-free survival: hazard ratio 0.35, 95% confidence interval 0.25 to 0.49, p <.0001; overall survival: hazard ratio 0.40, 95% confidence interval 0.26 to 0.61, p <.0001). Potential higher ELIMination rate constant K-assessed chemosensitivity is suggested in patients from Japan with advanced serous ovarian cancer, warranting further prospective validation and investigation into underlying biological and environmental determinants and implications for personalized therapeutic strategies.

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Research on van der Waals layered materials offers opportunities to explore diverse scientific phenomena at the nano- and atomic scales, along with their promising technological potential. Among the material family, graphitic carbon nitride (g-C3N4) has attracted substantial research attention due to its simple synthesis process, tunable electronic structure properties, and exceptional physicochemical properties arising from good interfacial compatibility with other materials. In this research, we investigated the potential of g-C3N4 as a gas sensing material. To overcome its intrinsically poor conductivity and limited surface activity, the electronic band structure of g-C3N4 was deliberately modulated through hybridization with Pt nanoparticles, which promotes surface conductivity and suppresses charge recombination. The formation of Pt/g-C3N4 heterojunctions sufficiently modulated the interfacial band structure upon gas absorption, resulting in pronounced sensitivity toward NO2, NH3, CO, H2S molecules, relative to a pristine g-C3N4 sensor. Furthermore, sensing properties were investigated under blue-light (BL; &#x3bb; = 457 nm) illumination with intensity of 1.55 W/m2. The photoinduced charge excitation led to distinctively different response for oxidizing and reducing nature of the target gases, and sensitivity and selectivity to NO2 gas molecules were significantly improved. This BL-assisted, gas-dependent response contrast provides insight into the underlying gas-sensing mechanism. Overall, this work elucidates how interfacial band engineering and photoexcited carrier dynamics govern gas sensing in g-C3N4-based systems, offering a mechanistic framework for advanced design of high-performance gas sensors.

Ovarian cancer (OC) is a highly fatal gynecologic malignancy with complex management challenges and limited long-term survival for advanced stages. Large language models (LLMs)-including systems such as GPT-4, Claude, Google Gemini, and others-are emerging artificial intelligence (AI) tools capable of performing health care-related tasks such as diagnostic support, treatment planning, report generation, and patient communication. However, their applications in OC care have not yet been comprehensively assessed. This protocol outlines a systematic review and meta-analysis aimed at evaluating the use, performance, and clinical impact of LLMs in OC management. We will examine how LLMs have been applied across various domains (eg, diagnosis, prognosis, treatment planning, and patient engagement), the metrics used to assess their performance (eg, accuracy, sensitivity, and area under the curve), and their strengths and limitations. This review will be conducted in accordance with PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) guidelines. A comprehensive search strategy will be implemented across biomedical, technical, and Chinese-language databases (eg, PubMed, Embase, Web of Science, IEEE Xplore, and China National Knowledge Infrastructure) from inception to December 31, 2025. Eligible studies include clinical evaluations, validation studies, and real-world implementation reports involving LLMs in OC care. Two independent reviewers will perform screening, data extraction, and quality appraisal using validated tools (eg, version 2 of the Cochrane risk-of-bias tool for randomized trials, Risk of Bias in Nonrandomized Studies of Interventions, Quality Assessment of Diagnostic Accuracy Studies 2, and Prediction Model Study Risk of Bias Assessment Tool+AI). Outcomes of interest include model performance metrics, clinical process impacts, safety concerns, and usability. Meta-analyses will be conducted where feasible using random-effects models in R (meta, metafor, and mada packages), including bivariate models for sensitivity and specificity. The review is currently in progress. The PROSPERO registration has been completed, and the literature search and selection process is underway. Study selection, data extraction, and quality assessment are expected to be completed by mid-2026. Final results will include pooled performance metrics (eg, accuracy, F1-score, and area under the curve), qualitative insights into clinical integration, and identification of limitations such as reporting bias or insufficient external validation. This systematic review will provide the first comprehensive synthesis of evidence on the application of LLMs in OC care. It will identify promising use cases, highlight safety and reporting challenges, and inform future research directions. The findings are expected to support evidence-based integration of LLMs into gynecologic oncology workflows while promoting transparency and methodological rigor in AI evaluation.

Occupational stress is a significant concern in the field of pre-hospital emergency care, affecting the well-being of healthcare professionals and the quality of patient care. This review aims to explore the influencing factors, consequences, and management strategies associated with occupational stress in this specific setting. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A literature search was conducted using relevant databases, including PubMed, Scopus, and Web of Science. Studies published within the last decade were included, with a focus on empirical research and systematic reviews. The eligibility of the studies was evaluated based on predetermined inclusion and exclusion criteria. The review identified several influencing factors contributing to occupational stress in pre-hospital emergency care, such as high workload, time pressure, exposure to traumatic events, organizational factors, and personal characteristics. The consequences of occupational stress encompassed burnout, decreased job satisfaction, compromised patient care, increased absenteeism, and higher turnover rates. Various management strategies were explored, including workload management, shift scheduling optimization, creating a supportive work environment, and stress management training. The findings highlight the need for effective management of occupational stress in pre-hospital emergency care. Addressing the influencing factors and implementing appropriate management strategies can mitigate the consequences of occupational stress and enhance the well-being of healthcare professionals. This review provides valuable insights for healthcare organizations, policymakers, and practitioners in developing interventions and policies to manage occupational stress and improve the overall quality of care in pre-hospital emergency settings. Further research is warranted to evaluate the effectiveness of specific interventions and develop tailored approaches to address occupational stress in this context.

The UMLS Metathesaurus, the largest thesaurus in the biomedical domain, provides a representation of biomedical knowledge consisting of concepts classified by semantic type and both hierarchical and non-hierarchical relationships among the concepts. This knowledge has proved useful for many applications including decision support systems, management of patient records, information retrieval (IR) and data mining. Gaining effective access to the knowledge is critical to the success of these applications. This paper describes MetaMap, a program developed at the National Library of Medicine (NLM) to map biomedical text to the Metathesaurus or, equivalently, to discover Metathesaurus concepts referred to in text. MetaMap uses a knowledge intensive approach based on symbolic, natural language processing (NLP) and computational linguistic techniques. Besides being applied for both IR and data mining applications, MetaMap is one of the foundations of NLM's Indexing Initiative System which is being applied to both semi-automatic and fully automatic indexing of the biomedical literature at the library.

Long-term implantable neural interfacing devices play a critical role in treating various neurological disorders, with their functionality largely dependent on the performance of electrodes and microelectrode arrays. Femtosecond laser Hierarchical Surface Restructuring (HSR&#x2122;) is an advanced surface treatment technology that significantly enhances a platinum-10% iridium (Pt-10Ir) electrode's electrochemical performance, improving energy efficiency, specificity, and signal-to-noise ratio. Additionally, HSR&#x2122; facilitates electrode miniaturization, allowing them to be manufactured smaller, for a less invasive profile. Electrode surfaces produced via HSR&#x2122; technology contain multiscale structures, including nanoscale features that, while contributing to superior performance, are sometimes weakly bonded and may detach due to mechanical agitation during testing or implantation. This detachment could lead to a high initial performance, that may gradually decline during prolonged use. Preemptively removing these nanostructures stabilizes the electrode surface, enhancing the stability of its morphology and potentially electrochemical performance. This study introduces a novel, in-operando, CO&#x2082;-snow-assisted HSR&#x2122; process and benchmarks it against other prevalent surface cleaning methods post-fabrication, such as ultrasonic cleaning, on improving electrode stability and performance. Both qualitative and quantitative analyses indicate that all cleaning methods enhance electrode stability. However, ultrasonic cleaning was found to be more destructive compared to CO&#x2082;-snow-assisted HSR&#x2122; processing, resulting in reduced electrochemical performance. In contrast, in-operando CO&#x2082;-snow-assisted processing provided similar or superior improvements in surface stability, while preserving higher electrochemical performance in vitro and enabling a faster processing time. This study is the gateway to further assess the stability in vivo, which is the intended next step of the research.

Fabricating high-fidelity, patient-specific aortic phantoms that possess both complex pathological features and physiological compliance remains a significant challenge for single-method manufacturing techniques. This study presents a complete virtual-to-physical prototyping workflow, enabled by a novel Hybrid Additive Manufacturing Platform (HAMP), for translating clinical imaging data into high-fidelity, patient-specific aortic phantoms. Building upon a validated brush-spin-coating technique capable of precise wall thickness control (&#xb1;0.1&#x2009;mm), the HAMP synergistically integrates 3D printing and casting. This integration overcomes the limitations of single-method techniques, uniquely enabling the creation of phantoms with (i) controllable interlayer delamination for mimicking dissection, (ii) enclosed multi-chamber structures for endoleak simulation, (iii) seamless integration of dissimilar materials, and (iv) the replication of complex intra-wall pathologies such as intramural hematoma. The platform's capability was rigorously demonstrated through the successful fabrication and application of four distinct classes of aortic phantoms. These high-fidelity models were directly employed in: fundamental biomechanical studies to visualize dissection propagation; advanced surgical training for complex procedures like ex vivo fenestration; emergency preoperative planning, where a patient-specific model was delivered in under 30&#x2009;h; and industrial medical device testing using parametric, ISO-compliant models. In each scenario, the phantoms provided functional, anatomically accurate representations suitable for the intended evaluation-whether physical testing, surgical rehearsal, or hydrodynamic assessment. In summary, the HAMP demonstrates a&#xa0;rapid virtual-to-physical prototyping workflow. By enabling the on-demand creation of complex, multi-material, patient-specific phantoms, it provides a versatile tool that bridges digital data and physical reality, addressing needs across research, clinical training, and device development.

To describe obstetric and perinatal outcomes of pregnant women with advanced maternal age (AMA) conceiving through in vitro fertilization (IVF) technology. A single-center prospective observational study was conducted between January and December 2024. All women aged 40 and older who conceived via IVF were included. Participants underwent regular prenatal follow-up in a maternal-fetal unit, including standardized maternal clinical assessment and fetal ultrasound evaluation. A subgroup analysis (40-44-year-old subgroup vs. &#x2265;45-year-old subgroup) was also conducted to identify potential differences in obstetric and perinatal outcomes within our study population. A total of 128 pregnant women were included. Nearly half were primigravid (n&#x2009;=&#x2009;60, 46.88%) and 71 pregnancies resulted from oocyte donation (55.47%). Obstetric complications observed in this cohort included gestational diabetes mellitus (n&#x2009;=&#x2009;3, 2.34%), hypertensive disorders (n&#x2009;=&#x2009;6, 4.76%) preterm premature rupture of membranes (n&#x2009;=&#x2009;11, 8.59%), preterm intrauterine growth restriction (n&#x2009;=&#x2009;7, 5.56%) and preterm delivery (n&#x2009;=&#x2009;15, 11.72%). It is noteworthy that these last three outcomes mentioned were observed significantly more frequently in the subgroup aged over 45 years. Cesarean delivery was performed in 62 cases (49.6%). Regarding neonatal outcomes, the median birth weight was 3,028&#x2005;g and the median umbilical cord pH was 7.29. Eight newborns (6.45%) required admission to intensive care unit. Postnatal comorbidities were identified in 14 infants, with respiratory complications being the most frequent (12/14). In this cohort of women of AMA following IVF, several obstetric and neonatal complications were observed. Additionally, the subgroup analysis revealed that PPROM, preterm IUGR and preterm delivery, lower neonatal weight and respiratory complications were significantly more frequent among women aged 45 or older. These findings provide descriptive clinical data regarding pregnancies in this specific population, which remains relatively underrepresented in the literature. Given the single-center design of the study, further research, including studies with appropriate comparison groups and larger sample size conducted across multiple centers, are needed to better clarify the individual and combined contributions of AMA and IVF to these outcomes.

Oncolytic viruses are currently the subject of cancer treatment research. Unlike other viruses, they can target tumor cells while avoiding healthy ones. The vesicular stomatitis virus (VSV) has the ability to kill tumor cells through one of two different apoptotic pathways, depending on which cell line is being studied. Even when no other viral components are present, the VSV matrix protein can induce cell death in HeLa cells through apoptosis. The purpose of this research was to examine the similarities and differences in the induction of cell death by native and mutant VSV matrix proteins. To create the mutant VSV matrix protein, the amino acid Ser was substituted with Lys at residue 89 (S89K). After the matrix gene was cloned into the expression vector, both the normal and mutant versions were transfected into HeLa cells. The expression was verified by fluorescence microscopy, and flow cytometry was used to evaluate the apoptosis rate. After 48 hours of transfection, the VSV matrix protein was found to promote cell death at the highest level. The results showed that once basic amino acids were substituted with alcoholic ones in the S89K mutant, the apoptotic activity of the VSV matrix protein was enhanced. This study discovered that increasing apoptosis induction by introducing a specific mutation at a specific location in the VSV matrix protein improved its apoptotic capabilities. The ability to engineer recombinant viruses with specific mutations is crucial for the development of cancer vaccines that target specific cell lines.

In recent years, cell-based medicinal products (CMPs) have emerged as novel therapeutics with specific potential to treat a wide range of diseases. These products should be produced in accordance with good manufacturing practices (GMPs) and follow specific guidelines to ensure their safety and meet standard quality control criteria. This manuscript reviews current standard methods for quality control and validation specific to CMPs intended for clinical applications. We summarize critical quality attributes, including safety assessments such as sterility, endotoxin, mycoplasma, viral testing, tumorigenicity, and genetic stability; quantitative parameters, including cell counts and dose determination; and quality characteristics encompassing cell viability, morphology, growth kinetics, and immunophenotyping. We also address purity evaluation, potency assays, and the importance of validating analytical methods to guarantee reproducible and reliable test results. Furthermore, this article discusses necessary considerations for donor screening, raw material sourcing, manufacturing environment monitoring, and stability testing to maintain product integrity throughout production and storage. Emphasis is placed on adherence to GMP and relevant regulatory guidelines as defined by international pharmacopeias and authorities, such as the Food and Drug Administration and the European Medicines Agency. Finally, we highlight challenges faced in standardizing quality control for CMPs and underscore the need for continued development of rapid and robust testing methods tailored to their unique characteristics. This comprehensive overview aims to support academic and industrial stakeholders in implementing effective quality control strategies for advanced cell-based therapies.

Intrinsically stretchable neuromorphic devices (ISNDs) have been widely investigated for intelligent wearable on-device computing. However, conventional material design strategies that soften the polymer conjugated moiety to impart stretchability have shown limited mechanical durability, typically 103 cycles at 50% strain, with severe electrical degradation. Here, we present a highly durable ISND that maintains stable electrical performance for up to 105 cycles at 50% strain, enabled by molecularly controlling chain stacking of the semiconducting polymer. This is achieved by incorporating a microstructure-controlling moiety into the polymer backbone, which modulates the chain packing from a bundle-like to a mesh-like structure. The resulting mesh-like morphology forms robust and long-range percolation networks that preserve charge transport pathways and structural integrity under mechanical deformation. Utilizing this material, we fabricate ISNDs that exhibit device-level stretchability of up to 150% and exceptional cyclic stability, with less than 15% variation in output current after 105 cycles at 50% strain. Furthermore, we demonstrate reliable on-device artificial intelligence using reservoir computing, with consistent classification accuracy maintained even after 105 mechanical cycling at 50% strain. This work offers a molecular design strategy for tuning semiconductor film morphology, achieving mechanical reliability in stretchable neuromorphic electronics for future wearable and biomedical systems.

Anxiety and depression are associated with advanced brain age (BA) and reduced cognitive functioning, but it remains unclear to what extent these effects reflect diagnostic status versus variability in cognition. We examined whether cognition explains regional brain age differences in individuals with anxiety and depression using local BA (LBA) and LBA gap (LBAG). UK Biobank participants (N&#x202f;=&#x202f;21,424) underwent LBA estimation from structural MRI. LBAG was analyzed using multivariate testing and hierarchical mixed-effects models to assess regional and global differences across diagnostic groups. Models were evaluated with and without adjustment for cognitive performance (principal component of cognitive tests) to isolate effects including and excluding cognition. Significant global brain age gap (GBAG) elevations were observed in anxiety and depression relative to diagnosis-free participants, with no differences between disorders, supporting a transdiagnostic pattern. Regionally, widespread LBAG elevations exist without adjusting for cognition, with mean differences of ~1.01 y (anxiety), 1.05 y (depression), and 1.14 y (comorbidity). Modeling for cognition attenuated these effects to ~0.80, 0.84, and 0.78 y, respectively (~20-25% reductions). Higher cognitive performance was associated with lower LBAG, with stronger associations in psychiatric groups than controls. Diagnostic effects are most prominent in anterior frontal and temporal cortices, whereas cognition-related associations are strongest in subcortical and ventral regions. Brain aging differences in people with anxiety and depression are partly associated with cognitive variability rather than diagnosis alone. Accounting for cognition alters interpretation of psychiatric BA effects and highlights the importance of integrating cognition into BA models when evaluating neuropsychiatric populations.

Hexafluoropropylene oxide dimer acid (HPFO-DA) is marketed under the trade name "GenX" and is used as a replacement for other per- and polyfluoroalkyl substance (PFAS) like perfluorooctanoic acid (PFOA). However, there are growing concerns about its regulation due to environmental and health impacts in organisms. Here, we review literature regarding the prevalence and toxicity of GenX in aquatic species and performed molecular docking and computational analysis to identify mechanisms of GenX-induced toxicity. Studies report measurable body burden levels of GenX in fish and other aquatic species, indicating that exposure and uptake do occur, which can lead to sub-lethal biological effects (e.g., developmental toxicity, oxidative stress, metabolic disruption, immune modulation, endocrine activity, neurobehavioral alterations). Effects on hormone receptor - mediated signaling (i.e., estrogenic and thyroid pathways) were noted based on computational analysis. In silico molecular docking of GenX to several fish receptors (e.g., estrogen, androgen, and thyroid hormone receptors) supported the potential for GenX to interact with key nuclear receptors, suggesting plausible mechanisms of endocrine disruption in fish. Molecular and omics-based analyses also revealed that GenX interferes with several pathways related to lipid and energy metabolism, as well as redox balance. Notably, several transcripts altered in abundance by GenX are related to the AGE-RAGE signaling pathway (Advanced Glycation End products (AGEs) bind to the Receptor for Advanced Glycation End products (RAGE)), which is related to oxidative stress and inflammation, and glucagon receptor (GCGR) signaling that activates transcription factors like CREB/CRTC2 and FOXO1 to promote gluconeogenesis. This review underscores useful toxicological endpoints for GenX in aquatic animals to guide future risk assessments.

Magnetic resonance (MR) is a powerful non-invasive technique for probing structural, functional, and metabolic processes with high spatial and temporal resolution. However, its inherently low sensitivity restricts broader applications. The use of hyperpolarized contrast agents has thus, emerged as an attractive approach to overcome this limitation and expand the capabilities. Among the available hyperpolarization techniques, parahydrogen-induced polarization (PHIP) provides a rapid and cost-efficient means to enhance magnetic resonance signals substantially. Yet, direct hyperpolarization of biomolecules, metabolites, or pharmaceuticals in vivo remains challenging, necessitating the development of versatile molecular tags and probes for hyperpolarized magnetic resonance (HP-MR). In particular, imparting specific sensing functions-such as pH responsiveness and enzyme activity detection-to these HP molecular tags is of growing importance. Herein, we introduce pyridine N-oxides as hyperpolarizable molecular tags and present [1 5N, D]-labeled 2-alkenylpyridine N-oxides as highly efficient candidates for HP-MR with up to 47% 15N spin polarization. This performance opens pathways for broad potential in biomedical and preclinical HP-MR applications. The systems feature long 1 5N spin-lattice relaxation times (up to T1&#xa0;=&#xa0;477&#xa0;s), broad functional-group compatibility, and excellent structural tunability. Their practical utility is exemplified by pH and H2O2 sensing and monitoring enzymatic reactions in water.

Streptococcus pneumoniae is a major cause of pneumonia in older adults, and long-term care facility (LTCF) residents are at high risk because of advanced age, multimorbidity, and the close contact environment. However, data on pneumococcal carriage and serotype distribution in LTCFs remain limited. This study evaluated pneumococcal carriage and serotype distribution among LTCF residents and healthcare workers. We conducted an observational study involving two LTCFs in Nagasaki, Japan, from October 2021 to March 2022, when COVID-19 infection control measures were implemented. Saliva samples were collected from residents and healthcare workers at up to five time-points, tested for the lytA gene, and serotyped using nanofluidic PCR. Healthcare worker characteristics were compared between those with and without pneumococcal carriage. We included 188 residents (median age: 90 years; 84.6% female; 82.4% with dementia; 55.9% requiring full assistance) and 88 healthcare workers (median age: 42 years; 68.2% female). Among residents, six of 806 samples were positive (0.7%; 95% confidence interval [CI]: 0.3-1.6), and 2.1% (95% CI: 0.8-5.3) were positive at least once across the five time-points. Among healthcare workers, 21 of 417 samples were positive (5.0%; 95% CI: 3.3-7.6), and 13.6% (95% CI: 8.0-22.3) were positive at least once. Carriage prevalence was higher among healthcare workers living with children aged <&#x202f;5 years (33.3% vs. 6.6%, p&#x202f;=&#x202f;0.018). Five serotypes were detected in residents and 15 in healthcare workers; serotype 35B was most frequent in healthcare workers (33.3%), followed by 10&#x202f;A and 9&#x202f;N/9&#x202f;L (25% each). Identical serotypes were detected in residents and healthcare workers, and several serotypes were identified on follow-up in the same individuals. Pneumococcal carriage was low among LTCF residents, despite the high risk of pneumococcal disease. Post-pandemic studies are needed to clarify transmission dynamics under routine conditions.