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PubMed2026

Evidence Gap in Managing Lateral Pelvic Lymph Nodes in Rectal Cancer: a Systematic Review of Radiation Boost Strategies.

PURPOSE: Lateral pelvic lymph node (LPLN) involvement is a significant predictor of local recurrence in patients with locally advanced rectal cancer (LARC). While lateral pelvic lymph node dissection (LPLND) is routinely used in some countries to manage suspicious nodes, it is associated with increased morbidity and is not widely adopted in Western practice. Radiation boost (dose escalation) to involved LPLNs during neoadjuvant chemoradiotherapy (nCRT) has emerged as a potential non-surgical alternative. Despite increasing adoption of radiation boost to clinically involved LPLNs, there remains limited evidence defining its safety, oncologic benefit, and role relative to LPLND. METHODS: A systematic search of MEDLINE, EMBASE, ClinicalTrials.gov, and Cochrane databases was conducted following PRISMA guidelines. Studies were included if they reported outcomes of radiation dose escalation specifically targeting radiologically suspicious LPLNs in the context of nCRT. RESULTS: Ten retrospective cohort studies encompassing 482 radiation boosted patients were included. Boost doses ranged from 35.0 to 60.2 Gy. Rates of Grade 2-3 toxicity ranged from 28.0% to 39.3% across individual studies, with only one study reporting a single Grade 4 adverse event. Across individual studies, reported nodal response rates ranged from 62.3% to 100%. Comparative studies suggest that radiation boost may improve local control and reduce LPLN recurrence. CONCLUSION: Current retrospective evidence suggests that radiation dose escalation to involved LPLNs is a promising treatment strategy; however, the available data are limited by retrospective study designs and substantial clinical heterogeneity. Given the absence of prospective evidence and lack of consensus in current guidelines, an important evidence gap remains. Well-designed prospective trials are warranted to define the role of LPLN boost relative to LPLND.

Humans↗

PubMed2026

Sea urchin co-culture boosts abalone growth by reducing environmental stress and remodeling gut microbiota.

Biofouling and microenvironmental deterioration are major bottlenecks restricting the intensive aquaculture of Pacific abalone (Haliotis discus hannai). While co-culturing offers an eco-friendly mitigation strategy, the underlying mechanisms promoting abalone growth remain poorly understood. This study evaluated the growth performance of H. d. hannai co-cultured with varying densities of the sea urchin (Strongylocentrotus intermedius). By employing transcriptome and 16S rRNA sequencing of the abalone gut, we investigated the synergistic responses of host gene expression and gut microbiota. Compared with the monoculture group, the co-culture groups showed significantly less biofouling and greater growth of abalone, with the co-culture (n = 15) exhibiting the best outcomes. Transcriptomic analysis revealed 1444, 760, and 508 DEGs in G5, G10, and G15, respectively, compared with G0. These DEGs were significantly enriched in metabolic pathways, including glycolysis and sterol metabolism, indicating a shift in intestinal energy metabolism from stress defense toward growth under co-culture conditions. Gut microbiota profiling identified Proteobacteria and Firmicutes as the dominant phyla, with specific functional taxa (e.g., Psychrilyobacter and Akkermansia) enriched in a density-dependent manner. Furthermore, correlation analysis demonstrated that growth traits positively correlated with growth-promoting taxa (e.g., the unclassified AB1 lineage), but negatively correlated with potentially opportunistic taxa (e.g., Tabrizicola). These findings provide insights into a potential synergistic mechanism of "environmental stress alleviation-metabolic reprogramming-microecological remodeling" driving abalone growth, providing a theoretical foundation for optimizing co-culture systems and developing growth-associated biomarkers.

Animals↗

PubMed2026

Morphology-engineered NiFe@C nanocages boosting electrochemical quantification of ractopamine in meat samples.

It is essential to acquire efficient electrocatalysts to develop ractopamine (RAC) electrochemical sensors. Herein, we report the synthesis of a series of carbon coated NiFe alloy nanostructures (e.g., NiFe@C nanoparticles, nanocubes and nanocages) using NiFe Prussian blue analogue (PBA) as the precursor. The NiFe@C nanocages exhibited the best electrocatalytic performance for RAC sensing. This is attributed to the embedded NiFe alloy nanoparticles that provide abundant active sites, and the unique nanocage structure facilitates electron transfer pathways while offering a high specific surface area. The resulting sensor achieves a low detection limit (LOD) of 54 nM (S/N = 3) within a linear range of 0.2-12 μM. Moreover, the sensor demonstrates good reproducibility, stability, and excellent long-term stability. Practical applicability was confirmed in meat samples, yielding satisfactory recovery rates ranging from 98% to 108%. A feasible strategy was introduced herein for rational design of metal@carbon electrocatalysts.

Phenethylamines↗

PubMed2026

Boosting kynurenic acid in kombucha via substrate selection: metagenomic and biochemical insights.

Kombucha is gaining global popularity for its health benefits. This study explored the use of chestnut honey, a rich source of kynurenic acid (KYNA), to produce kombucha enriched with this metabolite. Five variants were prepared using different green/black tea blends and carbon sources: white sugar or acacia honey (controls) versus chestnut honey. Samples were analyzed for tryptophan metabolites, physicochemical properties, and microbial diversity. Komagataeibacter and Enterobacter were predominant bacterial genera in SCOBY. Candida and Aspergillus were predominated in the single sample analyzed for fungi. During fermentation, tryptophan decreased, while kynurenine increased. KYNA levels remained largely stable during fermentation and were mainly influenced by the fermentation substrate. No melatonin pathway derivatives were detected. On day 7, chestnut honey yielded kombucha with 381.680-739.915 μmol/L KYNA and elevated myricetin. Overall, chestnut honey-based kombucha represents a system in which substrate composition appears to be the main factor influencing KYNA levels in the final beverage.

Kynurenic Acid↗

PubMed2026

Boosting domestic wastewater treatment with quorum signal-augmented heterotrophic nitrification-aerobic denitrification bacterial-algal aerobic granular sludge.

The aerobic bacterial-algal granular sludge (ABGS) enhanced with heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria, as a novel symbiotic technology, exhibits fluctuating treatment efficiency and unstable performance primarily due to the unstable symbiotic relationship. This study proposes an innovative approach to strengthening the bacteria-algae symbiosis by introducing exogenous signaling molecules. Concurrently, high-throughput, correlation analysis of environmental factors and metagenomic sequencing techniques are employed to elucidate the enhancement mechanisms of the signaling molecules. The results demonstrate that signaling molecule enhancement boosted total nitrogen (TN) removal efficiency by 24.51 % in the bacteria-algae symbiotic system (X1). Scanning electron microscopy (SEM) characterization revealed that the addition of signaling molecules resulted in more compact aerobic granular sludge (AGS) and markedly improved stability. High-throughput sequencing showed signaling molecules enriched denitrifying bacteria (Hydrogenophaga, Pseudoxanthomonas, Thauera, Zoogloea) and organic-degrading Desulfomicrobium, optimizing microbial diversity and enhancing nitrogen/organic removal. Correlation analysis of environmental factors indicate that the addition of C8-HSL facilitates the enrichment and functional activation of specific genera. Metagenomic analysis revealed that signaling molecules enhanced the system's denitrification performance by modulating gene expression and associated metabolic pathways. Quantitative polymerase chain reaction (qPCR) analysis further confirmed that the signaling molecules upregulated the expression of the napA, nirK, and nirS genes. An increased abundance of the napA gene facilitated aerobic denitrification (NO₃⁻-N→NO₂⁻-N), while upregulated abundance of the nirK and nirS genes accelerated nitrite reduction (NO₂⁻-N→N₂). This study aims to provide theoretical and practical foundations for implementing advanced bacteria-algae symbiotic technologies.

Denitrification↗

PubMed2026

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

PubMed2026

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

Humans↗

PubMed2026

Artificial intelligence in treatment prediction for skeletal Class III malocclusion: A systematic review.

In skeletal Class III patients, treatment options range from orthodontics to orthognathic surgery. Choosing the optimal approach requires a comprehensive clinical evaluation, which may be supported by AI tools. The aim of this study was to assess the performance of AI models in predicting the need for orthognathic surgery and in identifying predictors influencing treatment decisions. A PRISMA-guided electronic database search (PubMed, Web of Science; 2009-2024; English/French) was performed to identify studies using machine learning (ML) or deep learning (DL) on cephalometric and clinical data. After screening and assessment for eligibility, 15 studies were critically appraised. Model performance was summarized using accuracy, sensitivity, specificity, and the area under the curve (AUC). ML algorithms (particularly Random Forest and XGBoost) and DL models (ResNet-based convolutional neural networks (CNNs)) achieved high accuracy for predicting surgical need. Frequently selected predictors included Wits appraisal, ANB angle, the maxillomandibular ratio (Mx/Md), overjet, and the divergence of the lower gonial angle. AI methods show promise for assisting treatment decisions in Class III malocclusion, with Random Forest and XGBoost performing well on tabular cephalometric data and CNNs on imaging. Larger, multicentre datasets and external validation are needed to improve reliability, address bias, and support clinical implementation.

Humans↗

PubMed2026

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30‑day all‑cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged ≥ 60 years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K‑Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P < 0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR = 9.752), smoking (OR = 5.171), AIP (OR = 6.691), TyG index (OR = 4.393), HALP score (OR = 2.831), and ≥ 2 comorbidities (OR = 3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC = 0.884, accuracy = 0.829, sensitivity = 0.812, specificity = 0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30‑day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans↗

PubMed2026

Modulating sentence comprehension in people with aphasia through anodal tDCS: A double-blind randomized cross-over study.

This double-blind randomized cross-over study investigated the effects of perilesional anodal transcranial direct current stimulation (AtDCS) combined with speech-language therapy on sentence comprehension in eight individuals with chronic nonfluent agrammatic aphasia. The behavioral therapy consisted of an intensive comprehension treatment including drilling in sentence-to-picture matching and Mapping Therapy. Each participant underwent both the anodal tDCS and sham stimulation conditions (five received sham first followed by real stimulation, and the remaining three the reverse sequence), with each condition paired with the same behavioral treatment and separated by a four-month washout period. Stimulation was applied over the perilesional area (left BA6) for 20 min during daily 40-min therapy sessions over four consecutive weeks. Sentence comprehension was assessed with the RiComprendo battery and functional communication with the Communicative Effectiveness Index (CETI). Data were analyzed using paired t-tests, Bayesian analyses, and linear mixed-effects models to control for baseline performance and individual variability. Both stimulation conditions produced significant pre-to-post improvements in sentence comprehension, particularly for syntactically complex structures such as passives and center-embedded object relatives. However, gains were overall greater following AtDCS, as reflected in larger effect sizes, stronger Bayes factors, and a significant treatment effect in the mixed-effects models. Only the AtDCS condition yielded significant improvements in self-perceived comprehension abilities on the CETI. These findings suggest that AtDCS over perilesional cortical areas may boost the effects of traditional language therapy on sentence comprehension, supporting its feasibility and potential as an adjuvant intervention in post-stroke aphasia rehabilitation.

Humans↗

PubMed2026

Simultaneous Administration of Human Papillomavirus (HPV) Vaccine With Other Recommended Vaccines Among Adolescents Aged 13-17 years, National Immunization Survey-Teen (NIS-Teen), United States, 2023.

PURPOSE: To investigate the percent of adolescents who receive human papillomavirus (HPV) vaccine with one or more other vaccines recommended for adolescents in a single medical visit. METHODS: Data from the 2023 National Immunization Survey-Teen were analyzed. Timing of receipt of HPV vaccine, tetanus, diphtheria, and acellular pertussis vaccine (Tdap), quadrivalent meningococcal conjugate vaccine (MenACWY), and influenza vaccine was assessed using provider-reported vaccination histories. RESULTS: In 2023, among adolescents aged 13-17 years, 69.5% received HPV vaccine with one or more other vaccines recommended for adolescents in a single medical visit. In addition, 47.8% received specifically HPV vaccine, Tdap, and MenACWY together in a single medical visit. DISCUSSION: The HPV vaccine is commonly given with other vaccines recommended for adolescents in a single medical visit. These findings demonstrate variation in simultaneous vaccination patterns, suggesting that flexibility in the recommended adolescent vaccination schedule allows for different approaches to vaccination across clinical settings and family preferences while maintaining adherence to the recommended schedule.

Humans↗

PubMed2026

Simultaneous determination of imiquimod and terbinafine in skin permeation studies: Validation of a liquid chromatography method with fluorescence detection.

Chromoblastomycosis is a chronic, neglected subcutaneous mycosis posing significant therapeutic challenges. A topical strategy combining terbinafine (TBF), an antifungal, with imiquimod (IMQ), a TLR-7/8 agonist immunomodulator, has emerged a promising alternative. However, no validated analytical method is currently available to simultaneously quantify both drugs in skin, which is crucial for novel formulation development. This study reports the development and validation of a simple HPLC method with fluorescence detection (excitation 236 nm, emission 340 nm) for the simultaneous determination of TBF and IMQ extracted from porcine skin. Separation was achieved on a C8 reversed-phase column (125 × 4.0 mm, 5 μm) using a mobile phase of methanol and water (60,40, v/v), both containing 0.1% formic acid at a flow rate of 0.8 mL/min. The method showed excellent linearity (r > 0.999) over 0.01-1.0 μg/mL for IMQ and 0.1-2.0 μg/mL for TBF. Intra- and inter-day precision demonstrated coefficients of variation below 5%, and recovery rates from skin (79-105%) confirmed accuracy. Limits of detection were 0.001 μg/mL for IMQ and 0.004 μg/mL for TBF, with quantification limits of 0.02 μg/mL and 0.16 μg/mL, respectively. This selective, sensitive, and reproducible method represents a valuable analytical tool for supporting the development and quality control of topical formulations for chromoblastomycosis and other fungal skin diseases.

Animals↗

PubMed2026

Design of an innovative framework based hybrid catalyst for simultaneous and sensitive monitoring of food additive and preservative of vanillin and nitrite in direct samples.

As vanillin (VAN) and nitrite (NIT) contamination in the food chain poses substantial threats to environmental and public health, rapid and portable detection is essential. The present study presents the first electrochemical sensor report based on a hybrid composite of Ni-TPA-MOF and MoS2/Co3O4. The oxidation of VAN and NIT exhibited sharp peaks and less over-potential on Ni-TPA-MOF/MoS2/Co3O4/GCE than on control electrode surfaces. On modified composite electrode surfaces, pH and scan rate were investigated for VAN and NIT. Further, the oxidation current exhibited high linearity at VAN and NIT concentrations of 5 nM-1000 μM and 3 nM-1250 μM, with detection limits of 0.102 nM and 0.073 nM (S/N = 3). We also applied anti-interfering ability (five/ten-fold excess of co-interfering compounds) and practical tests to various food-based real samples, with high recoveries of 98.85-102.41%. This study highlights the catalytic properties of Ni-TPA-MOF/MoS2/Co3O4 and demonstrates the sensor as a promising tool for food safety.

Benzaldehydes↗

PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12 min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22 ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗

PubMed2026

Development and validation of a novel LC-MS/MS method for simultaneous quantification of fidaxomicin and metabolite (OP-1118) from feces for gut pharmacobiome studies.

Fidaxomicin is a first-line antibiotic for treating Clostridioides difficile infection. While it has low systemic absorption and reaches high colonic concentrations, it is hydrolyzed to a less active metabolite, OP-1118. Few studies have completely described critical experimental details of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for quantifying fecal fidaxomicin and OP-1118. This study developed and validated a simple, fast, and sensitive LC-MS/MS method to quantify fidaxomicin and OP-1118 in human and mouse feces. This method simplified fecal sample preparation without the use of solid phase extraction and optimized LC-MS/MS parameters. A broad working range (0.3-1000 ng/ml) in both diluted human and murine fecal matrices was achieved with good intra- and inter-day accuracy (93-107%), precision (1-7%), and recovery (70-105%) as well as little IS-normalized matrix effects. This method was utilized to quantify fidaxomicin and OP-1118 in human and murine fecal samples. This novel method was simple, fast, sensitive, and accurate in analyzing fecal fidaxomicin and OP-1118 and could be deployed to facilitate gut pharmacobiome research.

Feces↗

PubMed2026

Aflatoxins and their biosynthetic precursors in lotus seeds: simultaneous UPLC-MS/MS determination, contamination profiling, and matrix-specific accumulation during Aspergillus flavus infection.

Aflatoxin (AF) contamination poses a severe global threat to food and medicinal material safety, yet existing research focuses on terminal AF metabolites while neglecting residual biosynthetic precursors, leading to potential underestimation of contamination risks. In this study, a UPLC-MS/MS method was established for the simultaneous quantification of six AFs and their five precursors in lotus seeds, with optimization of mass spectrum parameters, chromatographic separation conditions, and sample pretreatment. Method validation confirmed linearity (R2 > 0.99), LODs (0.03-0.36 μg/kg), and recoveries (76.53%-120.0%, RSD < 15%). Analysis of 41 natural lotus seed samples revealed a 63.4% AF contamination rate, dominated by B-group AFs, while O-methylsterigmatocystin (OMST) and versicolorin hemiacetal (VOH) were identified as the primary co-residual precursors with co-occurrence rates ≥ 50%. Notably, AFM1 was predominantly detected in natural samples with AFB1 concentrations exceeding 100 μg/kg. Artificial inoculation experiments further demonstrated that sterilization and sealing conditions modulated AF biosynthesis in lotus seeds, with non-sterilized and non-sealed groups showing delayed fungal metabolism and lower toxin accumulation. A significant linear correlation was observed between AFM1 and AFB1 levels (r = 0.94) in infected samples, demonstrating their accumulation levels are coupled with fungal overall metabolic flux. Given the high co-occurrence rate of OMST/VOH with AFB1 in natural samples, their individual and combined toxicities require in-depth investigation. This work deciphers matrix-specific AF dynamics in lotus seeds, supporting regulatory standard refinement (e.g., precursor inclusion) and targeted control (e.g., time-sensitive drying after harvest). Further studies will focus on exploring the molecular mechanisms of substrate-dependent AF synthesis.

Aflatoxins↗

PubMed2026

Simultaneously PYCR-1 and ALH-6 inhibition exacerbates 6-PPD quinone toxicity via disrupting proline and glutamate metabolisms and activating insulin signals in Caenorhabditis elegans.

Glutamate synthesized from the proline can serve as a precursor for key intermediate metabolites of citric acid cycle. Recently, we observed reduced glutamate content and expression of alh-6 controlling glutamate synthesis by 6-PPD quinone (6-PPDQ) in Caenorhabditis elegans. However, possible effect of 6-PPDQ on proline synthesis and the association with 6-PPDQ toxicity induction remain unclear. After 0.1-10 μg/L 6-PPDQ exposure, proline content was further reduced, and expression of pycr-1 governing proline biosynthesis was decreased. In 6-PPDQ exposed nematodes, RNA interference (RNAi) of pycr-1 decreased α-ketoglutarate content, enhanced mitochondrial dysfunction, reduced nicotinamide adenine dinucleotide (NADH) and reduced flavine adenine dinucleotide (FADH₂) contents, inhibited mitochondrial complex I/II activities, and decreased expressions of gas-1 and mev-1. Moreover, compared to single RNAi, double RNAi of pycr-1 and alh-6 exacerbated the 6-PPDQ toxicity in reducing α-ketoglutarate, NADH, and FADH₂ contents, and suppressing mitochondrial complex I/II activities and gas-1 and mev-1 expressions. Additionally, double RNAi of pycr-1 and alh-6 intensified toxicity of 6-PPDQ on longevity and caused upregulation of insulin ligand and receptor genes and downregulation of daf-16 and its targeted genes in 6-PPDQ exposed nematodes. Furthermore, after 6-PPDQ exposure, daf-16 RNAi suppressed pycr-1 and alh-6 expressions, suggesting formation of a regulatory feedback loop between pycr-1/alh-6 and daf-16. Our findings highlight involvement of disrupted proline and glutamate metabolisms in 6-PPDQ-induced mitochondrial dysfunction and reduced longevity.

Animals↗

PubMed2026

A randomized trial of viral vector and adjuvanted protein HBV therapeutic vaccine in people with chronic hepatitis B on nucleos(t)ide analogs.

BACKGROUND: This study assessed the safety, efficacy, and immunogenicity of a therapeutic immunization strategy aimed at reaching a functional cure for chronic hepatitis B (CHB), relying on a heterologous prime-boost with viral vectors ChAd155-hIi-HBV and MVA-HBV, combined with sequential or concomitant administration of adjuvanted recombinant HBV proteins (HBc-HBs/AS01B). METHODS: This single-blind, randomized, controlled, first-in-human, phase 1/2 trial enrolled adults aged 18-65 years with HBeAg-negative CHB, virally suppressed on nucleos(t)ide analogs (NAs), with HBsAg >50 IU/mL. Participants received NAs and the following regimens of 4 doses (8-week intervals): sequential administration of ChAd155-hIi-HBV, MVA-HBV, and 2 HBc-HBs/AS01B doses; co-administration of ChAd155-hIi-HBV+HBc-HBs/AS01B, followed by 3 co-administered MVA-HBV+HBc-HBs/AS01B doses; 4 HBc-HBs/AS01B doses; 2 placebo doses followed by ChAd155-hIi-HBV and MVA-HBV administered alone or with HBc-HBs/AS01B; or 4 placebo doses. Safety, efficacy (≥1-log decrease in quantitative (q)HBsAg or HBsAg loss 24 weeks post-dose 4 [day (D)337]), antibody, and T-cell responses were evaluated. RESULTS: In all, 134 participants were vaccinated. Grade 3 solicited adverse events (AEs) (median duration: 2-3 days) were more frequent after co-administration (systemic: 59.3%; administration-site: 33.3%) than sequential administration (systemic: 10.3%; administration-site: 12.8%) of high-dose viral vectors and proteins. No vaccine-related or fatal serious AEs were reported. After 4 doses, no participant had HBsAg loss or ≥1-log decrease in qHBsAg (D337 vs. D1). Co-administration induced the strongest anti-HBs response (73.7% achieved anti-HBs ≥10 mIU/mL 2 weeks post-dose 4 vs. 40.0% after sequential administration). Both sequential and co-administration induced HBc-specific CD4+ and CD8+ T-cell responses, with a prime-boost effect of the viral vectors. CONCLUSIONS: Heterologous prime-boost with ChAd155-hIi-HBV and MVA-HBV, combined with sequential or co-administration of HBc-HBs/AS01B, had an acceptable safety profile, were moderately immunogenic, but no participants showed the expected efficacy outcome.

Humans↗