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PubMed2026

Toward personalized interventions for preventing depression in primary care: Qualitative and quantitative findings from the e-predictD pilot study.

BACKGROUND: The predictD intervention, delivered by family physicians (FPs), has demonstrated effectiveness and cost-efficiency in preventing depression and anxiety. The e-predictD study aims to design, develop, and evaluate a novel personalized intervention for depression prevention by integrating information and communication technologies (ICTs), risk prediction algorithms, and decision support systems (DSS) for both patients and FPs. OBJECTIVE: To evaluate the satisfaction, usability, and acceptability, of a beta version of the e-predictD intervention in primary care settings. METHODS: The e-predictD intervention follows a biopsychosocial approach, including an initial patient-FP interview, specific FP training, and an app. A β-version was tested in a pilot study without a control group over three months. The app integrates a validated depression risk prediction algorithm, decision algorithms, and a monitoring system supporting the DSS. The DSS generates a personalized prevention plan (PPP) from eight intervention modules: physical exercise, social relationships, problem-solving, communication skills, decision-making, assertiveness, sleep improvement, and cognitive restructuring. Patients and FPs discussed the PPP in a 15-minute baseline interview, selecting modules for implementation over three months. Semi-structured interviews gathered feedback. Assessments included depression (PHQ-9), anxiety (GAD-7), quality of life (SF-12), and major depression risk (predictD algorithm). RESULTS: Six FPs from six Spanish cities enrolled 56 non-depressed patients at moderate-to-high risk of depression; 47 (84%) completed follow-up. The app was used for a median of six days (interquartile range: 1-30). Both FPs and patients expressed satisfaction, leading to incorporated improvements. After three months, significant reductions in major depression risk and anxiety symptoms were observed, alongside improved mental quality of life. However, no significant changes were found in depressive symptoms or physical quality of life. CONCLUSION: This pilot study supports the feasibility and acceptability of the e-predictD β-version, despite lower-than-expected app usability. Health improvements were observed, warranting confirmation in a randomized controlled trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03990792.

Adult↗

PubMed2026

School-based sexual violence prevention: A systematic review.

PURPOSE: Sexual violence profoundly affects the health and development of children, adolescents, and young adults, representing a persistent challenge to public policy. This systematic review examined the effectiveness of school-based interventions aimed at prevention. METHODS: Eighteen randomized controlled trials published between 2012 and 2024 were retrieved from four major databases. The programs were implemented in primary, secondary, and higher education settings and targeted children, adolescents, and young adults. RESULTS: The results revealed improvements in knowledge and attitude, particularly regarding consent and awareness, whereas evidence supporting behavioral changes was less frequent and often limited. Methodological limitations, such as short follow-up periods and participant attrition, restricted the assessment of long-term outcomes. CONCLUSIONS: This review highlights the importance of multicomponent, participatory, and culturally sensitive approaches, along with the integration of digital tools and continuous evaluation systems, to strengthen the role of schools as safe and transformative spaces in the prevention of sexual violence. IMPLICATIONS AND CONTRIBUTIONS: This systematic review suggests that school-based interventions hold significant potential for the prevention of sexual violence. It identifies promising strategies and reinforces the importance of culturally sensitive, sustained, evidence-based approaches to ensure learning environments that are safe, protective, and promotive of gender equity.

Humans↗

PubMed2026

Effects of Photobiomodulation Therapy in Lateral Luxation of Anterior Permanent Teeth: A Randomized, Double-Blind Clinical Trial.

BACKGROUND: Among the traumatic dental injuries (TDIs), lateral luxation may present poor prognosis due to frequent root resorption and consequent tooth loss. Photobiomodulation therapy (PBMT) modulates cellular activities (proliferation, differentiation, growth factor secretion) and may improve outcomes. OBJECTIVE: This randomized, double-blind, placebo-controlled trial evaluated PBMT (660 vs. 808 nm) for post-operative pain and pulp sensitivity recovery in lateral luxation of permanent anterior teeth. METHODS: Initially, 41 patients were included, with a total of 63 teeth traumatized by lateral luxation and were allocated to G1 (n = 21): Splinting + sham PBM (placebo), G2 (n = 21): Splinting + 808 nm infrared PBM and G3 (n = 21): Splinting + 660 nm red PBM. Four weekly sessions (3 J/point, 3 points) were administered. Pain (by numeric rating scale) and pulp sensitivity (by cold test) were assessed weekly. Pain was analyzed using the Kruskal-Wallis test, followed by multiple comparisons using Dunn's method with Bonferroni correction, and pulp sensitivity by a logistic regression model (p < 0.05). RESULTS: Three participants (total of 5 teeth) were excluded due to loss to follow-up. Fifty-eight teeth were analyzed (G1 = 21, G2 = 17, G3 = 20). Pain: All groups showed a significant reduction in pain over time (p < 0.001). Both G2 and G3 demonstrated a significantly greater reduction in pain compared to G1 (p < 0.001 and p = 0.026, respectively). No significant difference in pain reduction was observed between G2 and G3. Pulp sensitivity: G2 showed a significant improvement over time (p < 0.001), despite starting from a more unfavorable baseline. In contrast, no significant change in pulp sensitivity was observed for G1 or G3 between the initial and final assessments. CONCLUSION: Within the limitations of this clinical study, all intervention groups were effective in reducing pain in lateral luxation of permanent anterior teeth, with superior results for laser groups compared to the placebo. However, only the 808 nm laser irradiation protocol demonstrated a significant improvement in pulp sensitivity, suggesting it may offer a more complete therapeutic response.

Humans↗

PubMed2026

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence↗

PubMed2026

Chalcone-indole hybrid scaffolds as promising anticancer drug candidates: a mini-review.

Cancer treatment is hampered by severe systemic side effects, poor tumor selectivity, and multidrug resistance (MDR). Molecular hybridization integrates chalcone and indole, two privileged antitumor pharmacophores, into one scaffold to generate chalcone-indole hybrids that synergistically enhance antitumor potency, improve tumor targeting, and reverse MDR. This mini-review analyzes literature from 2020 to 2026 on chalcone-indole anticancer hybrids. Based on structural modification patterns, the reported hybrids are categorized into four subgroups: simple substituted, α/β-position modified, N-1 fatty acid-substituted, and multi-pharmacophore fused hybrids. For each category, we summarize structure-activity relationships (SARs), antiproliferative activity, selective toxicity, molecular mechanisms, and in vivo xenograft performance. Most lead compounds exert tumor-suppressive effects via tubulin polymerization inhibition, G2/M cell cycle arrest, ROS overaccumulation, and mitochondrial-dependent apoptosis. Representative hybrids 10a, 12a, 21a, and 25a exhibit remarkable efficacy against drug-resistant colorectal, lung, and breast tumors with favorable in vivo safety. We highlight the application potential of different subtypes for specific malignancies, including α/β-modified analogues for resistant colorectal cancer, N-1 fatty acid-platinum conjugates for platinum-resistant lung cancer, NLRP3 inhibitor 7a for oral cancer, and multi-pharmacophore fused derivatives for broad-spectrum activity. Current bottlenecks limiting clinical transformation are discussed. This review provides structural design rules for developing novel chalcone-indole targeted anticancer agents.

Humans↗

PubMed2026

Dynamics and virulence of Enterobacteriaceae reservoirs harboring blaCTX-M group 1 in community wastewater.

UNLABELLED: Extended-spectrum beta-lactamase (ESBL)-producing bacteria are ubiquitous and can cause serious infections. Here, we examined untreated community wastewater influent as a reservoir for blaCTX-M group 1 organisms and their virulence potential. Raw influent samples (n = 268) were collected from four wastewater treatment plants (WWTPs) representing dense urban populations. We observed that blaCTX-M group 1 levels were high at all WWTPs and only ~1-2 log10 lower and not correlated to common human-specific microbiome fecal markers, Lachno3 and HF183, indicating a lack of connection to human fecal inputs. Concentrations of blaCTX-M group 1 genes and markers for presumptive host organisms Escherichia coli and Klebsiella pneumoniae were influenced by travel time and season. Amplicon sequencing revealed high diversity of blaCTX-M group 1-9 genes, with 63% belonging to group 1. Selective culture and 16S rRNA gene sequencing showed blaCTX-M group 1 isolates were 26% E. coli, 26% K. pneumoniae, 40% other Enterobacteriaceae, and 8% Aeromonas. Overall, E. coli averaged 3.6E7 cells/L, with 3% of all E. coli found to contain blaCTX-M group 1. Whole-genome sequencing of blaCTX-M group 1 E. coli from wastewater revealed resistance and virulence gene profiles similar to clinical isolates and distinct from other wastewater ESBL-resistant and non-resistant E. coli. Interpretation of wastewater data needs to consider both the existence of environmental reservoirs that contain potentially pathogenic organisms and the strong influence the dynamics of the conveyance system can have on final concentrations measured at the WWTP. IMPORTANCE: The CTX-M enzyme family is highly abundant in nosocomial, community, and environmental settings and is leading to treatment of infections with carbapenem antibiotics, a last-line therapeutic option. The progressive increase of the clinically relevant blaCTX-M group 1 resistance genes in the human population warrants investigation, particularly to understand the establishment and dynamics of environmental reservoirs. This study utilized molecular and culture methods to gain insight into the possible origin, abundance, and dynamics of blaCTX-M group 1 genes in untreated wastewater influent samples. We found extremely high levels of these genes, with Escherichia coli as a major host organism that closely resembled clinical strains, suggesting they are seeded and propagate in sewer pipe systems. The significance of our research is in developing approaches to monitor antimicrobial resistance reservoirs in community wastewater, which could shed light on global burdens and potential transmission cycles and indicate increasing inputs of clinically relevant strains originating from human populations.

E. coli↗

PubMed2026

Three-dimensional porous nano-hydroxyapatite@gelatin composite as efficient adsorbent for uranyl ion removal from low-level radioactive wastewater.

The contamination of water resources by uranyl (UO22+) ions poses significant environmental and health risks, requiring the development of efficient and sustainable remediation strategies. Adsorption-based techniques have emerged as promising approaches in the field of UO22+ removal, but the design of cost-effective, high-capacity, and environmentally friendly adsorbents remains challenging. In this study, a three-dimensional porous nano-hydroxyapatite@gelatin (nHAP@Ge) composite was synthesized through glutaraldehyde cross-linking, combining the structural stability of Ge with the high uranium affinity of nHAP. The optimized nHAP@Ge, with a nHAP:Ge mass ratio of 1:0.5, exhibited exceptional UO22+ removal efficiency (97 %), along with high adsorption capacity (364.03 mg/g). Systematic characterizations using scanning electron microscopy (SEM), thermogravimetric analysis (TGA), Fourier transform infrared (FT-IR) spectroscopy, and X-ray photoelectron spectroscopy (XPS) methods revealed that the porous structure and surface functional groups (-OH, Ca2+, and PO43-) of the material synergistically contributed to binding UO22+ species. Furthermore, the incorporation of nHAP into the Ge framework resulted in enhanced thermal stability while significantly improving the UO22+ adsorption performance. This work presents a scalable, eco-friendly, and recyclable strategy for the effective treatment of uranium-contaminated water, with potential applications in nuclear wastewater treatment and environmental remediation.

Adsorption↗

PubMed2026

Artificial Intelligence Technologies in Nursing Clinical Decision-Making: An Umbrella Review.

AIM: To describe contemporary peer-reviewed literature on artificial intelligence in nurses' clinical decision-making. METHODS: An umbrella review of literature reviews. DATA SOURCES: Four major databases were searched for reviews published between 2019 and 2024. RESULTS: Sixteen literature reviews reported on 965 nursing artificial intelligence primary studies. The studies focused on technology development and emerging performance evaluations, whilst real-world testing or implementation in nursing clinical settings was rare. Rigorous comparative analyses were lacking. While artificial intelligence demonstrates promise in decision-making, challenges such as a lack of controlled studies, algorithmic bias, limited reproducibility and insufficient clinical trials hinder its practical impact. Ethical concerns, transparency and patient data privacy issues pose barriers to AI integration in nursing practice. Ethical and legal guidelines for patient privacy are needed and should be taught along with AI literacy training for nurses. CONCLUSIONS: Artificial intelligence has the potential to enhance clinical nursing decision-making, although evidence is limited by too few examples of nurse participation during development. Underutilisation in administrative nursing functions hinders implementation. Nurses should assume a central role in the design and development of AI applications to ensure that these technologies address the realities of nursing practice. With such improvements, artificial intelligence can transform nursing practice, improve nurses' clinical decision-making and ultimately enhance consumer healthcare outcomes. PATIENT OR PUBLIC INVOLVEMENT: No Patient or Public Involvement. REPORTING METHOD: While there is no reporting checklist for umbrella reviews, the PRISMA guide for systematic reviews was followed.

Artificial Intelligence↗

PubMed2026

Morphological changes and transcriptomic insights into skeletal development of embryos and larvae of the sea urchin Strongylocentrotus intermedius.

To explore morphological features and molecular dynamics underlying skeletogenesis in the sea urchin Strongylocentrotus intermedius, we conducted combined morphological observation and comparative transcriptome analyses across representative embryonic and larval developmental stages. Morphological results showed that triradiate spicules first emerged at the gastrula stage. The 8-arm pluteus stage was identified as a key phase for skeletal remodeling, during which new three-radiate crystals transformed into complex stereoscopic ossicles including tube feet, spines and test plates. Transcriptomic data indicated that most differentially expressed genes (DEGs) were downregulated from the blastula to gastrula. The altered expression of basal metabolic genes and extracellular matrix genes including Colp2α and calm may be correlated with the linear mineralization of early spicules, which potentially reflects an energy adjustment pattern in developing larvae. During the transition from 6-arm to 8-arm pluteus, expression changes of calmodulin-like, Colp2α and SISin18G001660 suggest potential associations with regional calcium deposition and modifications of skeletal matrix properties. This work systematically characterizes morphological traits and transcriptional dynamics of skeletogenesis in S. intermedius. Its early spiculogenesis follows the conserved developmental pattern of echinoderms, while massive formation of stereoscopic ossicles occurs at the 8-arm pluteus stage. Stage-specific transcriptional changes across key larval skeletogenic stages are uncovered, offering transcriptomic resources for functional verification of skeletal regulatory genes.

Animals↗

PubMed2026

Venomous Lepidoptera: defensive toxin systems, venom composition, and clinical significance.

Venomous Lepidoptera constitute an underrecognized yet medically significant group of toxin-producing arthropods that employ contact-mediated defensive envenomation through specialized integumentary structures such as setae, spines, and scoli. Unlike actively stinging arthropods, these insects deliver venom passively upon contact, eliciting a diverse spectrum of clinical manifestations collectively termed lepidopterism. Clinical outcomes range from localized pain and dermatitis to severe systemic effects, including hemorrhagic syndromes, complement activation, and chronic inflammatory disorders. Recent advances in proteomic and transcriptomic technologies have transformed our understanding of lepidopteran venoms, revealing unexpectedly complex toxin repertoires comprising serine proteases, phospholipases, pore-forming proteins, disulfide-rich peptides, neuroactive RF-amide peptides, and immune-modulating components. These findings have provided new insights into the molecular basis of toxicity, host-pathogen interactions, and the evolutionary diversification of venom systems within Lepidoptera. This review synthesizes current knowledge on the morphology of venom-delivery structures, venom composition, mechanisms of action, and associated clinical manifestations, while highlighting medically important taxa, particularly species of the genus Lonomia. The successful development of antivenom against Lonomia envenomation underscores the translational relevance of lepidopteran toxin research and its potential for therapeutic innovation. By integrating molecular, clinical, and evolutionary perspectives, this review repositions venomous Lepidoptera as a legitimate and important component of arthropod toxinology. Furthermore, it identifies critical methodological limitations and key knowledge gaps, providing a framework for future investigations aimed at advancing our understanding of toxin biology, immunopathology, and the development of novel biomedical applications.

Animals↗

PubMed2026

CRISPR-Cas and Infectious Diseases: A Decade of Translational Advances in Molecular Biotechnology.

CRISPR-Cas systems have emerged as a versatile tool for diagnosing, treating, and preventing infectious diseases. This review highlights translational advancements in CRISPR-Cas-based applications, concentrating on the past decades in diagnostics, therapeutic genome editing, and vaccine development. The article highlights key platforms like DETECTR and SHERLOCK, which enable rapid, sensitive pathogen detection, and explores CRISPR-Cas9 systems in therapeutic strategies for directly targeting viral genomes and combating antimicrobial resistance. It also examines the role of CRISPR-Cas9 in engineering live-attenuated and personalized neoantigen vaccines. Principal findings demonstrate a clear progression from experimental proof-of-concept to preclinical applications primarily in CRISPR-based diagnostics and the engineering of live-attenuated vaccine candidates, whereas translation in CRISPR-based therapeutics and personalized neoantigen vaccines for infectious diseases remains at earlier, more exploratory stages. CRISPR-based diagnostics have progressed further toward clinical evaluation than therapeutics due to delivery and safety constraints, while personalized neoantigen vaccines are included mainly as an emerging, comparative concept for infectious diseases rather than a mature application. This review uniquely integrates CRISPR-based diagnostics, therapeutics, and vaccine development within a single infectious disease framework, critically assesses their current maturity, and systematically highlights technical, regulatory, and ethical barriers alongside realistic future priorities. The review concludes that while CRISPR-Cas holds transformative potential for infectious disease management, significant challenges in delivery efficiency, off-target effects, and ethical regulation must be addressed to ensure safe and equitable clinical translation.

Humans↗

PubMed2026

Power as equal ability, knowledge and resistance: Systematic review of experiences of adults with noncommunicable diseases.

PURPOSE: To analyse subjective experiences of power of adults with noncommunicable diseases in relationships with healthcare practitioners as well as underlying facilitators and barriers of these experiences. METHODS: Systematic review (4 databases) of experiences using reflexive thematic analysis underpinned by critical realist approach. The analysis was conducted with an abductive reasoning using previous theories on social power as well as retroduction. RESULTS: Based on 24 studies, we formed three themes, which depict experiences of power as 1) the position, equal ability and freedom to make one's own choices and (re)negotiate within shared dialogue, 2) the ability to use knowledge to claim one's rights, 3) resistance. Facilitators were connected to acknowledgement as an equally valuable individual, positive healthcare practitioner attitudes and actions towards patient activity and views, safety in the relationship as well as to sufficient, clear and varied information. Main barriers were experiences of dehumanisation, negative healthcare practitioner attitudes and actions, perceived or assumed practitioner domination in interactions, lack of or incomprehensible knowledge and testimonial smothering. CONCLUSION: Results suggest that adults with noncommunicable diseases may experience power primarily as a positive power: being acknowledged as having legitimate position to make decisions and being in possession of varied knowledge through which they can gain agency to protect and claim their rights, by resisting, if necessary. Healthcare practitioners are in key position to support these experiences through positive transforming actions, while knowledge asymmetries, persistent inequality and paternalistic structures continue to hinder it.

Humans↗

PubMed2026

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗

PubMed2026

Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis.

PURPOSE: To synthesizes evidence on artificial intelligence (AI) performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and genomic characterization. MATERIALS AND METHODS: A systematic review and meta-analysis was conducted following PRISMA 2020 guidelines (PROSPERO: CRD42024539475) across five databases. Meta-analyses used random-effects models with logit-transformed Area Under the Curve (AUCs) and cluster-robust standard errors. AI models were classified as Machine Learning Models (MLM) or Hybrid Nomograms (HN) based on their construction methodology. RESULTS: Of 3,742 articles identified, 53 were included. MLMs demonstrated higher point estimates than radiologists in differential diagnosis (AUC: 0.87 vs. 0.83), though this difference was not statistically significant and carried substantial uncertainty. HNs achieved stronger performance in risk stratification (AUC: 0.87). AI-derived nomograms (AUC: 0.9) and gene signatures (AUC: 0.8) outperformed conventional prognostic markers descriptively. Chemotherapy response prediction remained below clinical utility thresholds across all model types. Only 33.9% of models reported calibration and 24.5% underwent external validation. CONCLUSIONS: AI demonstrates proof-of-concept across multiple NB clinical domains. However, clinical adoption remains premature given persistent gaps in external validation, calibration, dataset size, and pediatric-specific model development. Future studies should test these models prospectively in multicenter pediatric cohorts, ideally through COG or SIOPEN, using shared definitions for diagnosis, risk group, treatment response, and survival outcomes.

Humans↗

PubMed2025

Effects of aerosol aging on composition and light-absorbance of nitrogen-containing organic compounds: Evidences from ultra-high-resolution mass spectrometry analysis.

Nitrogen-containing organic compounds (NOCs) are key components of particulate matter (PM), but their compositional evolution and light-absorbing properties during atmospheric aging remain poorly understood. In this study, ultra-high-performance liquid chromatography coupled with Orbitrap mass spectrometry was used to semi-quantitatively analyze 59 PM1 samples collected in Shanghai. NOCs accounted for 31 % and 64 % of the detected species in negative (ESI-) and positive (ESI+) ionization modes, respectively. Atmospheric aging significantly reduced the molecular diversity of polar organics, with both the number and mass concentration percentages of CHON- compounds showing significant negative correlations with aging degree. Van Krevelen analysis demonstrated a decrease in the number of carboxylic-rich alicyclic molecules and their CHON- contributions during the aging process (from 37.7 % in fresh samples to 21.2 % in aged samples). CHN+ compounds, a major NOCs group in ESI+ mode, also decreased with aging. Correlation analyses involving the Bep/(Bep+Bap) ratio, relative humidity, and mass absorption efficiency at 365 nm revealed a decline in light absorption capacity with aging, suggesting aqueous-phase oxidation as a dominant aging mechanism. CHON- and CHN+ compounds were identified as the principal light-absorbing constituents in PM1. This work provides new insights into the aging-induced transformations of NOCs in urban PM1, and their changing role in light absorption, highlighting the need for further investigation of the aging mechanisms of NOCs.

Aerosols↗

PubMed2026

Measurable Residual Disease and the Unresolved Biology of Leukemic Stem Cells.

Measurable residual disease (MRD) testing has transformed the management of hematologic cancers by enabling detection of residual malignant cells after therapy. Current approaches rely on qPCR and next-generation sequencing to monitor leukemia-associated somatic mutations, while multiparameter flow cytometry identifies aberrant leukemic immunophenotypes. Although these methods provide valuable prognostic and therapeutic information, MRD negativity remains an imperfect surrogate for cure. Most MRD platforms evaluate CD45+, rapidly dividing leukemic populations and fail to detect quiescent cells that may survive cytotoxic therapies which efficiently target proliferating hematopoietic cells. Relapse frequently occurs despite deep molecular remission, suggesting persistence of rare leukemic stem cells (LSCs) that are intrinsically resistant to chemotherapy and targeted therapies. The paradox of relapse despite molecular remission could be explained by the presence of very small embryonic-like stem cells (VSELs) which are pluripotent, quiescent stem cells sitting at the top of cellular hierarchy in multiple adult tissues including bone marrow. A pluripotent VSEL divides through asymmetrical cell division to give rise to two cells of different sizes and fates, smaller cell is to self-renew while the bigger is lineage-restricted and tissue-committed progenitor which undergoes extensive epigenetic changes, divides rapidly and undergoes clonal expansion before further differentiation. Dysfunctions of VSELs initiate both solid and hematologic cancers. Based on this view, somatic mutations monitored during MRD assessment possibly represent downstream consequences of clonal expansion rather than the initiating drivers of disease persistence. Thus, exclusive monitoring of somatic mutations and CD45 + leukemic populations possibly overlook rare, small-sized, CD45- VSELs that contribute to therapeutic resistance and relapse.

Humans↗

PubMed2026

Natural deep eutectic solvent in situ formation-based extraction method coupled to high-performance anion-exchange chromatography with pulsed amperometric detection for multiclass carbohydrates in hot pot bases.

A novel method was developed for the simultaneous extraction of fourteen multiclass carbohydrates from high-fat foods via the in situ formation of deep eutectic adducts from analytes and acetate ions. Different natural deep eutectic solvents (NADESs) composed of fructose and organic acids were tested as extraction solvents. A model NADES formulated with sodium acetate and fructose was characterized using Fourier transform infrared (FTIR) spectroscopy and hydrogen nuclear magnetic resonance (1H-NMR) spectroscopy. The critical extraction parameters were systematically optimized using multi-response surface methodology (MRSM) with a central composite design (CCD). The extract was analyzed using high-performance anion-exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD) using a sodium hydroxide-sodium acetate eluent, which did not require organic solvents. This approach exhibited good linearity over the concentration range of 0.02-10 mg L-1, with correlation coefficients (r) ranging from 0.9994 to 0.9999. The limits of detection and quantification were in the ranges of 0.06-0.42 mg kg-1 and 0.19-1.3 mg kg-1, respectively, which were significantly lower than those of liquid chromatography (LC). The protocol was successfully applied to the determination of fourteen carbohydrates in forty-five hotpot seasoning samples. The recoveries ranged from 86.3% to 104.1%, with relative standard deviations (RSDs) of 0.9-7.1%. By integrating multiple techniques, this strategy simplifies operations, shortens extraction time, and achieves baseline separation of three carbohydrate classes that exhibit poor resolution using a conventional LC method. This study describes an efficient procedure for the simultaneous determination of multiple trace-level carbohydrates in complex samples using HPAEC-PAD.

Journal Article↗

PubMed2026

To Treat or Not to Treat: Navigating Early-Stage CLL in the Era of Targeted Therapy.

Chronic lymphocytic leukemia (CLL) is most frequently diagnosed at early, asymptomatic stages (Rai 0/Binet A), in which a watch-and-wait strategy remains the standard of care, based on historical trials demonstrating no overall survival benefit from early treatment. Over the past two decades, however, substantial advances in genomic profiling-including immunoglobulin heavy-chain variable region (IGHV) mutational status, TP53 disruption, recurrent gene mutations, and complex karyotype-have uncovered marked biological heterogeneity among early-stage patients and substantially improved prediction of disease progression. In parallel, targeted therapies such as Bruton tyrosine kinase (BTK) inhibitors and venetoclax-based combinations have transformed the management of symptomatic CLL, raising renewed interest in whether early intervention might favorably alter the natural history of biologically high-risk disease. In this review, we critically examine the evolution of prognostication in early-stage CLL, integrate contemporary molecular and clinical risk models, and summarize evidence from both historical chemotherapy-era studies and modern early-intervention trials. We discuss key unresolved controversies, including reliance on surrogate endpoints, the risks of overtreatment, and the persistent absence of an overall survival benefit across all early-treatment strategies. Finally, we outline future research priorities, including refined genomic stratification, minimal residual disease-driven (MRD)-driven approaches, and combination targeted therapies currently under investigation. Despite renewed interest in preemptive treatment, available evidence supports continued observation for asymptomatic patients outside clinical trials.

Humans↗