Preclinical spine research is limited by heterogeneous experimental reporting, fragmented documentation, and barriers to reproducibility and translational alignment. Large language models (LLMs) and related artificial intelligence (AI) technologies may support semantic interpretation, structured data extraction, and reasoning over biomedical text, but their role in experimental spine science remains unclear. This focused scoping review and expert perspective mapped current AI/LLM applications in spine research, quantified the preclinical evidence gap, and identified responsible integration opportunities. A structured search of PubMed, Embase, and Web of Science was performed for studies published from January 2020 to January 2026 evaluating LLM, AI, chatbot, or advanced natural language processing applications in spine-related contexts. The search intentionally captured both LLM-specific and broader AI/chatbot applications to map the translational landscape. For this preclinical-focused analysis, the corpus was re-examined for experimental and translational use cases, supplemented by expert synthesis of methodologically relevant adjacent biomedical literature. Of 792 records identified, 166 unique studies met inclusion criteria. Publication activity increased markedly over time. The literature was dominated by conversational assessment/patient-reported outcome measure applications (82/166; 49.4%), patient education/information quality studies (53/166; 31.9%), and other LLM/AI applications (19/166; 11.4%). Preclinical/basic science applications were rare (3/166; 1.8%) and used classical machine learning, deep learning, or broader AI frameworks rather than generative LLMs. The most credible near-term opportunities include schema-constrained data extraction, protocol completeness checking, ontology-aligned data structuring, and evidence-grounded workflow support under human supervision. In preclinical spine research, LLMs are best positioned as human-supervised workflow instruments for structuring fragmented experimental knowledge. Spine-specific validation and robust governance are essential for responsible translational use.
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 ≥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.
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.
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.
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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; λ = 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.
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.
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.
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.
We investigated the risk of MI by RA status and seropositivity and performed exploratory analysis of biologic DMARD (bDMARD) and targeted synthetic DMARD (tsDMARD) use. This retrospective cohort study used the Korean National Health Insurance System database. Patients aged ≥ 40 years newly diagnosed with RA (n = 36,377) were matched 1:3 with non-RA controls (n = 109,131). Fine and Gray subdistribution hazard models estimated subdistribution hazard ratios (sHR) for MI risk by RA status, seropositivity, bDMARD, and tsDMARD use. During a mean follow-up of 5.6 ± 2.3 years, 1201 MI events in non-RA, 738 in RA, 186 in seronegative RA (SNRA), 552 in seropositive RA (SPRA), 64 with bDMARD use, and 4 with tsDMARD use were identified. Patients with RA had a 1.8-fold increased MI risk compared to non-RA (sHR: 1.84, 95% CI: 1.67-2.01). SNRA and SPRA showed similar risks (sHR: 1.74, 95% CI: 1.49-2.04, and sHR: 1.87, 95% CI: 1.69-2.07, respectively). MI risk remained elevated both with and without bDMARD use (sHR: 2.34, 95% CI: 2.05-2.67; sHR: 1.81, 95% CI: 1.72-1.91, respectively). Non-use of tsDMARDs was associated with increased MI risk (sHR: 1.86, 95% CI: 1.77-1.96), whereas tsDMARD use was not significantly associated with MI (sHR: 1.43, 95% CI: 0.90-2.28). RA was associated with increased MI risk irrespective of seropositivity status. Exploratory analyses suggested that tsDMARD users did not exhibit increased MI risk, although the small number of events warrants large-scale prospective studies. Patients with rheumatoid arthritis (RA) showed higher risk of MI than those without RA regardless of seropositivity status; further research is warranted to evaluate the impact of targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs) on cardiovascular risk in RA. Patients with RA showed a 80% higher risk of myocardial infarction (MI) compared to a non-RA control group, and the MI risk did not differ between patients with RA by seropositivity status.The risk of MI in those who used tsDMARDs was not significantly increased compared to the non-RA control group.
Colorectal cancer (CRC) is usually diagnosed when therapeutic options are limited, highlighting the need for novel molecular targeted therapies. MicroRNAs, as important regulators in cancer-related pathways, may provide therapeutic targets through their gene networks; however, the role of the miR-625-5p network in CRC remains unclear. Therefore, this study aimed to identify potential therapeutic targets in CRC through miR-625-5p-regulated network analysis. miR-625 expression in TCGA samples was analyzed to assess its potential role in CRC development/progression. miR-625-5p targets were integrated from multiple resources to construct a protein-protein interaction network (PPIN) and identify clusters and key hub genes using Cytoscape. Key hub genes underwent enrichment analysis using DAVID and CancerHallmarks, followed by validation in independent CRC datasets from GEO and TCGA. Validated Key hub genes were further analyzed using TNMplot and Kaplan-Meier survival analysis to assess their expression patterns and prognostic significance, respectively. Druggability of the prognostic final hub gene was assessed using the Open Targets Platform. miR-625 was significantly downregulated in CRC, particularly in advanced stages (p-value < 0.05). PPIN analysis of 755 target genes identified 24 key hub genes and four functional clusters. Enrichment analysis of key hub genes showed involvement in regulation of apoptotic processes, programmed cell death, and cancer-related pathways. Five candidate genes were validated in GEO and TCGA datasets; three were confirmed in TNMplot, and only HSP90AB1 was associated with poorer disease-free survival (p-value < 0.05) and exhibited druggable potential in CRC. HSP90AB1 is a candidate therapeutic target in CRC.
Pneumosepsis is a severe and potentially life-threatening infection of the lower respiratory tract. This study aimed to investigate the effect of combined vitamin D and A supplementation on clinical outcomes in patients with pneumosepsis. Eighty-four patients with pneumosepsis were randomly assigned to four groups in this double-blind clinical trial. Group 1 received standard treatment plus 300,000 IU intramuscular vitamin D and 50,000 IU intramuscular vitamin A. Group 2 received standard treatment plus 300,000 IU intramuscular vitamin D. Group 3 received standard treatment plus 50,000 IU intramuscular vitamin A. Group 4 received standard treatment only. Clinical parameters including ESR, CRP, creatinine, urea, and uric acid levels were recorded at baseline, 24, 48, and 72 hours after intervention. The combined vitamin D and A group (Group 1) demonstrated significantly lower blood pressure, respiratory rate, heart rate, temperature, ESR, CRP, and white blood cell count compared to the other groups at all three time points. The study suggests that combined vitamin D and A supplementation, in addition to standard treatment, may improve clinical outcomes and potentially reduce the duration of hospitalization in patients with pneumosepsis. However, further research is warranted to confirm these findings and elucidate the underlying mechanisms. This study is registered on Iranian Registry of Clinical Trials (IRCT) under the identifier IRCT20130424013110N10. (The registration date: July 6, 2020).
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 = 477 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.
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.
This study provides a nationwide assessment of stereotactic body radiotherapy (SBRT) technical standards in Italy in the National Recovery and Resilience Plan (NRRP) era, from the perspective of medical physicists, evaluating pre-investment status, innovation needs, NRRP-driven acquisitions, and perceived impact on SBRT practice. A nationwide survey by the Italian Association of Medical Physics (AIFM) SBRT Working Group was distributed to medical physicists in Italian radiotherapy centres. The questionnaire investigated technical implementation, available technologies, perceived needs (2020-2022), acquisitions and planned investments (2023-2025), funding sources, and perceived impact. Responses were stratified by geographic area, SBRT experience, annual SBRT accrual, and a composite SBRT Technology Index. Sixty-nine responses were collected, representing 37% of Italian RT centres (86% public institutions, of which 78% reported NRRP-funded acquisitions). Most centres reported a 10-25% increase in SBRT activity between 2022 and 2025. Compared to previous Italian and European data, availability of advanced delivery platforms, volumetric image guidance, six-degree-of-freedom couches, and type-C calculation algorithms increased markedly. Personnel education and dosimetry tools were identified as relevant needs by > 50% of respondents. NRRP funding mainly supported linac replacement and imaging technologies in public centres, while software-based innovations and workflow optimisation tools were mainly acquired through non-NRRP funding. Despite investments, the perceived impact was moderate, and ∼ 50% of respondents reported that additional investments and organisational changes are needed to fully exploit the technologies. NRRP funding accelerated SBRT technological modernisation in Italy. However, sustained and harmonised practice will require complementary investments in training, workflow integration, and organisational capacity.
Chronic low-grade inflammation ("inflammaging") is a key driver of age-related pathologies including cardiovascular disease, neurodegeneration, and metabolic syndrome. Diet plays a dual role in modulating this process, acting both as a source of pro-inflammatory molecular patterns and as a delivery system for geroprotective compounds. This review examines the pro-inflammatory dietary components (advanced glycation end products, lipid peroxidation products, oxysterols, trans fats, and microbiome-derived metabolites) that activate pattern recognition receptors and trigger inflammatory cascades, as well as the anti-inflammatory mechanisms of bioactive dietary compounds including polyphenols, omega-3 fatty acids, carotenoids, vitamins, and essential microelements. Evidence from cellular, animal, and clinical studies is synthesized to evaluate dietary interventions for healthy aging. PubMed and Google Scholar were systematically searched from inception through November 2025, with evidence quality and translational limitations critically appraised throughout. Pro-inflammatory dietary components activate nuclear factor-kappa B pathways, while geroprotective compounds demonstrate potent anti-inflammatory properties through multiple mechanisms: polyphenols (quercetin, EGCG, resveratrol, curcumin) inhibit pro-inflammatory signaling and activate sirtuin and Nrf2 pathways; omega-3 fatty acids reduce pro-inflammatory eicosanoids and increase specialized pro-resolving mediators; carotenoids, vitamins, and microelements (selenium, zinc, magnesium) suppress oxidative stress and modulate immune function. These dietary geroprotectors reduce inflammatory biomarkers in cellular and animal models, while clinical evidence in humans remains largely restricted to biomarker and healthspan-related endpoints rather than demonstrated lifespan extension. Optimized nutrition-emphasizing fruits, vegetables, legumes, nuts, whole grains, and omega-3-rich foods while limiting refined sugars and trans fats-represents a cornerstone intervention for mitigating inflammaging and promoting healthy longevity, with the Dietary Inflammatory Index providing a translational framework for implementation.
Saliva biomarker research requires understanding of how saliva collection and processing techniques affect results and reproducibility. Direct comparison of the effect of processing and storage conditions on downstream assay outcomes is important to understanding the ways that delay in freezing, methods of freezing, filtration protocols, and other factors can affect results and thus, interpretations about stress response and adaptation. This type of study compliments the work that is required to understand how saliva compares to tissue and blood responses and what the implications of changes in saliva biomarkers mean to our understanding of biomarkers of stress during exercise and environmental stress exposures. In this pilot study, we evaluated the effects of different processing methods on metabolomics results and discuss the implications of these findings for future experimental design. We assessed the effects of centrifugation, time-of-day collection, filtration, and mucinase treatments and determined that there are quantifiable differences in metabolomics results with different treatments. Adding processing steps did not increase the number of metabolites detected or the sensitivity and specificity of results. Comprehensive descriptions of methods in this area will support better interpretation and reproducibility in this field.
Primary pulmonary B-cell lymphomas are rare, accounting for <1% of non-Hodgkin lymphomas (NHLs) and 3-4% of extranodal NHL. Extranodal marginal zone lymphoma (MZL) of mucosa-associated lymphoid tissue (MALT; pulmonary MALT lymphoma), arising from bronchus-associated lymphoid tissue (BALT), represents over 80-90% of cases. These tumors typically develop as a result of chronic antigenic stimulation in the setting of persistent inflammation, due to infection, or autoimmune disease. Two main pathogenetic phases are recognized in their development: an antigen-dependent phase, in which clonal B-cell expansion and survival are driven by ongoing exposure to specific antigens, and an antigen-independent phase, in which B-cell proliferation becomes autonomous due to cytogenetic and molecular alterations. Clinically, pulmonary MALT lymphoma has an indolent course and is often detected incidentally; when symptoms occur, they are non-specific. Radiologic findings include consolidations, nodules, or masses. Diagnosis relies on histopathology, immunophenotyping (CD20+, light-chain restriction, CD5-/CD10-/cyclin D1-), and molecular studies. Most patients present at early Ann Arbor stages, with a 5-year overall survival exceeding 90%. Management should be tailored to the disease stage, symptoms, comorbidities, and patient preferences. A watch-and-wait approach is appropriate for asymptomatic patients without treatment indications. Radiotherapy is highly effective for localized disease, while rituximab alone or with chemotherapy, particularly bendamustine-rituximab, is preferred for advanced symptomatic disease. Bruton's tyrosine kinase inhibitors have shown efficacy in relapsed or refractory cases. This review summarizes the epidemiology, pathogenesis, clinicopathologic features, diagnosis, and evolving treatment strategies of pulmonary MALT lymphoma, highlighting its favorable prognosis and unique immunobiological origin.
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 = 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.